System

Abstract

A system is provided.SOLUTION: A system comprising: device means for collecting data for monitoring a behavior of a living elderly person; terminal means for temporarily storing the collected data and transmitting the data to a server at regular intervals; server means for analyzing the received data and detecting an abnormality; notification means for issuing a notification when an abnormality is detected; and report generation means for periodically generating a report and providing the report to a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In an aging society, ensuring the safety and health management of elderly people living alone is becoming increasingly important. However, when elderly people living alone suddenly become ill or have an accident at home, it is currently difficult to respond quickly. Furthermore, regular health monitoring and real-time notifications in the event of an abnormality are insufficient, making it difficult to prevent serious situations. There is a need for a system that can solve these issues and provide an environment where elderly people living alone can live with peace of mind. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by the following means. A system is provided that includes a device means for collecting data to monitor the behavior of elderly people living alone; a terminal means for temporarily storing the collected data and transmitting it to a server at regular intervals; a server means for analyzing the received data and detecting abnormalities; a notification means for issuing a notification when an abnormality is detected; and a report generation means for periodically generating reports and providing them to a user. This system constantly monitors the health status and behavioral patterns of elderly people living alone and promptly notifies users when an abnormality occurs, enabling prompt responses and regular monitoring. This also provides an environment in which elderly people living alone can live with peace of mind.

[0006] "Device means" refers to physical devices such as sensors, cameras, and wearable devices used to monitor and collect data on the behavior and health status of elderly people living alone.

[0007] "Terminal means" refers to an electronic device that has the function of temporarily storing data collected from device means and transmitting it to a server at regular intervals.

[0008] The "server means" is a central processing unit or cloud system for receiving and analyzing data sent from the terminal means.

[0009] "Notification means" refers to a mechanism for sending a notification to the user or a designated emergency contact when the server means detects an abnormality, and includes formats such as email, app notification, and SMS.

[0010] The "report generation means" is a part having a function of generating a report based on data periodically collected and analyzed by the server means and providing the report to the user. [Brief explanation of the drawings]

[0011] [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

[0012] 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.

[0013] First, the terms used in the following description will be explained.

[0014] 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).

[0015] 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.

[0016] 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.

[0017] 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.

[0018] 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."

[0019] [First embodiment]

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

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0026] 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.

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

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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."

[0032] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[0033] server

[0034] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to the user (family member or caregiver) via the notification means. The server also periodically analyzes the data and creates reports using the report generation means.

[0035] Terminal

[0036] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensor, movement sensor, heart rate monitor). The collected data is temporarily stored in the terminal, and is then transmitted to the server, for example, every hour.

[0037] User

[0038] The user (elderly person living alone) does not need to operate the device themselves; they simply go about their daily life as normal. The user (family or caregiver) can receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[0039] Program processing overview

[0040] Initial Setup

[0041] The server sets up individual profiles for elderly people living alone and initializes the database. The terminal pairs with various devices and verifies that the devices are working properly.

[0042] Data collection and transmission

[0043] Devices collect data from the daily lives of elderly people living alone. For example, temperature sensors, movement sensors, and heart rate monitors send their respective data to a terminal. The terminal temporarily stores this data and periodically sends it to a server.

[0044] Data analysis and anomaly detection

[0045] The server analyzes the received data in real time and detects any abnormalities. If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via a notification means. The type of abnormality is identified, and the user is notified of countermeasures based on that information.

[0046] Generate scheduled reports

[0047] The server periodically generates a report summarizing the health status and behavioral patterns of the elderly person living alone. The report is provided to the user, who can share it with caregivers and medical professionals to manage the health of the elderly person living alone.

[0048] Specific examples

[0049] For example, consider the case of an 80-year-old elderly person living alone who is using this system. Temperature sensors, movement sensors, and heart rate monitors are installed in the elderly person's home. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. Upon receiving the data, the server immediately analyzes it and sends a notification to the elderly person's family or caregiver if an abnormality is detected. In addition, periodically generated reports can provide a comprehensive understanding of the elderly person's health condition and can be used to take preventive medical measures.

[0050] In this way, the present invention provides a system that supports elderly people living alone to lead safe and healthy lives.

[0051] The processing flow will be explained below.

[0052] Step 1:

[0053] Users install various sensors, cameras, and wearable devices in the homes of elderly people living alone, including temperature sensors, movement sensors, and heart rate monitors.

[0054] Step 2:

[0055] The terminal pairs with the installed devices and checks the operation of each device, confirming that they are connected properly and making them ready to collect data.

[0056] Step 3:

[0057] The terminal receives real-time data collected from devices, such as indoor temperature data from a temperature sensor, movement patterns of elderly people living alone from a movement sensor, and heart rate data from a heart rate monitor.

[0058] Step 4:

[0059] The device temporarily stores the collected data, which is then set to be sent to the server periodically (e.g., every hour).

[0060] Step 5:

[0061] The server receives the data sent from the device, which is then stored in a database for later analysis.

[0062] Step 6:

[0063] The server analyzes the received data in real time using anomaly detection algorithms, for example, to check whether the heart rate of an elderly person living alone is outside the normal range or if there are any abnormalities in their movement patterns.

[0064] Step 7:

[0065] The server generates an alert if an abnormality is detected. A notification is generated containing the details of the abnormality (e.g., heart rate is too high, the user has not moved for a long time, etc.).

[0066] Step 8:

[0067] The server sends an alert to the user (family member or caregiver) via a notification method, which can be in the form of email, app notification, SMS, etc.

[0068] Step 9:

[0069] The user (family member or caregiver) receives the notification from the server and responds promptly. They check the content of the notification and take necessary measures, such as contacting the elderly person living alone or heading to the scene.

[0070] Step 10:

[0071] The server periodically (e.g., weekly or monthly) collects and analyzes data and generates reports based on the collected data. The reports summarize the health status and behavioral patterns of elderly people living alone, and also include a history of abnormal occurrences.

[0072] Step 11:

[0073] The server provides the generated report to the user (family or caregiver), who can share the report with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[0074] Example 1

[0075] 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."

[0076] Ensuring the safety and health management of elderly people living alone is an important issue in modern society. Because many elderly people live alone, a rapid response is required in the event of a sudden change in their physical condition or an accident. However, it is difficult to continuously monitor their health status and behavioral patterns on a daily basis, and there is a lack of systems that provide appropriate notifications in the event of an abnormality. To address these issues, the present invention aims to provide a system that monitors the behavior and health status of elderly people living alone in real time and immediately issues an alert in the event of an abnormality.

[0077] 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.

[0078] In this invention, the server includes a sensor means, a terminal means, a data analysis means, a warning means, a report generation means, a setting means, and a pairing means. This makes it possible to monitor the behavior and health status of elderly people living alone in real time and analyze the collected data at regular intervals. Furthermore, if an abnormality is detected, a notification is sent to the user immediately, and periodic reports can be generated and provided, thereby enabling efficient safety and health management of elderly people living alone.

[0079] The "sensor means" is a device that collects data to monitor the behavior and health condition of elderly people living alone, and specifically includes a temperature sensor, a movement sensor, a heart rate monitor, and the like.

[0080] The "terminal means" is a device that temporarily stores collected data and transmits it to a data processing device at regular intervals.

[0081] "Data analysis means" is a combination of software and hardware for analyzing data received by the server and detecting abnormalities.

[0082] "Warning means" refers to the means for sending a notification when an abnormality is detected, and specifically includes email, app notification, SMS, etc.

[0083] The "report generating means" is a means for periodically generating a report based on the health condition and behavior patterns of an elderly person living alone and providing the report to a user.

[0084] The "setting means" is a means for setting the initial settings of the server and individual profiles of elderly people living alone, and for initializing the database.

[0085] The "pairing means" is a means for connecting various sensor means and terminal means so that they can communicate with each other, and for confirming that the devices are operating normally.

[0086] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[0087] server

[0088] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with anomaly detection algorithms using libraries such as Python, Pandas, and NumPy, and if an abnormality is detected, it promptly sends an alert to family members or caregivers via notification means. The server also periodically analyzes the data and generates reports using Microsoft Power BI or Tableau.

[0089] Terminal

[0090] The terminal temporarily stores data from various sensor means. The terminal is installed in the home of an elderly person living alone and collects data in real time from temperature sensors, movement sensors, heart rate monitors, etc. For example, it uses a Bluetooth stack to pair with the device and checks that it is working properly. The collected data is temporarily stored in the terminal and sent to the server at regular intervals (for example, every hour). HTTP or MQTT is used as the communication protocol.

[0091] User

[0092] The user (elderly person living alone) simply lives their daily life as normal and does not need to operate the device themselves. Family members or caregivers can also receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[0093] Specific examples

[0094] For example, consider the case of an 80-year-old elderly person living alone who is using this system. Temperature sensors, movement sensors, and heart rate monitors are installed in the elderly person's home. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. When the server receives the data, it immediately analyzes it and sends a notification to the family or caregiver if an abnormality is detected. In addition, the periodically generated reports can provide a comprehensive understanding of the elderly person's health condition and can be used to take preventive medical measures.

[0095] An example prompt is:

[0096] "Describe a data analysis system that helps an 80-year-old person living alone live a safe and healthy life. Please explain in detail the entire process from data collection, storage, analysis, and notification, as well as the relevant hardware and software."

[0097] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0098] Step 1: Initial Setup

[0099] The server inputs basic information about the elderly person living alone and sets up an individual profile. Specifically, it registers data such as name, age, health status, and emergency contact information in the database and initializes the system. Next, it sets information about various sensor means (temperature sensors, movement sensors, heart rate monitors, etc.) and defines the role and characteristics of each.

[0100] Input: Basic information of elderly people living alone, information on sensor means

[0101] Output: Individual profiles registered in the database, initialized system settings

[0102] Step 2: Pairing devices

[0103] The device pairs with various sensor means and verifies that they are working properly. Using the Bluetooth stack, the device is configured to receive data from each sensor. This prepares the device to collect data in real time.

[0104] Input: Sensor connection information

[0105] Output: Pairing successful, communication established between device and sensor

[0106] Step 3: Data collection

[0107] The device collects data from the daily life of elderly people living alone through various sensor means (temperature sensor, movement sensor, heart rate monitor). Specifically, the temperature sensor measures the room temperature, the movement sensor detects the elderly person's movements, and the heart rate monitor measures the heart rate.

[0108] Input: Real-time data from various sensor means

[0109] Output: Sensor data temporarily stored on the device

[0110] Step 4: Temporarily save data

[0111] The device temporarily stores the collected data in its internal storage, where it is saved as a CSV or JSON file for further processing.

[0112] Input: Collected sensor data

[0113] Output: Data file saved in internal storage

[0114] Step 5: Send data periodically

[0115] The device sends the stored data to the server at regular intervals (for example, every hour). The communication protocol is HTTP or MQTT, and the data is sent in JSON or Protobuf format.

[0116] Input: Data files stored in internal storage

[0117] Output: Data sent to the server

[0118] Step 6: Data analysis

[0119] The server analyzes the received data in real time, preprocessing the data and extracting features using libraries such as Python, Pandas, and NumPy, and applying anomaly detection algorithms to detect anomalies using generative AI models.

[0120] Input: Sensor data sent from the device

[0121] Output: Analysis results, whether anomalies were detected

[0122] Step 7: Anomaly detection and notification

[0123] If the server detects an abnormality through analysis, it will promptly send an alert to family members or caregivers via notification methods (email, app notification, SMS, etc.) that include the type of abnormality and recommended actions to take.

[0124] Input: Analysis results, whether anomalies were detected

[0125] Output: Alert notification sent to family members or caregivers

[0126] Step 8: Generate scheduled reports

[0127] The server periodically analyzes the health status and behavioral patterns of elderly people living alone and generates reports using Microsoft Power BI and Tableau, which are presented in a visually easy-to-understand format.

[0128] Input: Analyzed health and behavioral data

[0129] Output: Generated scheduled reports

[0130] Step 9: Provide to users

[0131] The server provides the generated reports to family members and caregivers, and the reports are delivered in PDF format or as a web application for easy viewing by users.

[0132] Input: Generated Scheduled Report

[0133] Output: Report provided to family and caregivers

[0134] (Application example 1)

[0135] 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."

[0136] In modern society, the safety and health management of elderly people living alone are important issues. In particular, it is necessary to ensure the safety of elderly people living alone when they go out, and to constantly and accurately monitor their health status and respond quickly and effectively if an abnormality is detected. Furthermore, conventional systems do not adequately guarantee the safety of elderly people living alone while they are traveling, and there is also the issue of a lack of reliable means of managing their safety when they are out.

[0137] 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.

[0138] In this invention, the server includes a system that adds a device means for monitoring the behavior and health status of elderly people living alone, a terminal means for temporarily storing collected data and sending it to the server at regular intervals, a server means for analyzing the received data and detecting abnormalities, a notification means for issuing a notification when an abnormality is detected, a report generation means for periodically generating reports and providing them to the user, and a means for adjusting the operation of the autonomous vehicle and notifying medical institutions and designated contacts when an abnormality is detected. This makes it possible to improve the safety of elderly people living alone and manage their safety when they are out and about.

[0139] "Elderly people living alone" refers to elderly people who live alone.

[0140] "Devices and means for monitoring behavior and health status" refers to sensors and devices used to monitor the daily behavior and health status of elderly people living alone.

[0141] "Terminal means" refers to a device that temporarily stores data collected from device means and transmits it to a server at regular intervals.

[0142] "Server means" refers to a central management device or system that analyzes received data and detects abnormalities.

[0143] "Notification means" refers to a mechanism for issuing a notification when an abnormality is detected.

[0144] "Report generation means" refers to a mechanism that periodically analyzes data, generates reports, and provides them to users.

[0145] "Means for adjusting the operation of self-driving vehicles" refers to a system for controlling the operation status of self-driving vehicles and ensuring the safety of elderly people living alone.

[0146] "Means of notifying medical institutions and designated contacts" refers to a system for sending emergency notifications to medical institutions and pre-designated contacts when an abnormality occurs.

[0147] A "temperature sensor" refers to a device that measures the ambient temperature and transmits that data to a terminal.

[0148] A "movement sensor" refers to a device that detects the movement of an object and transmits that data to a terminal.

[0149] A "heart rate monitor" refers to a device that measures heart rate and transmits that data to a terminal.

[0150] "Smart glasses" refers to eyeglass-type devices that enhance the wearer's visual information or provide additional data.

[0151] "Head-mounted display" refers to a display device used to present digital information to the wearer's field of vision.

[0152] "Email" refers to a means of sending and receiving messages electronically over the Internet.

[0153] "App notifications" refers to the means by which applications notify users of messages or information on smartphones and other devices.

[0154] "SMS" refers to the service of sending and receiving short text messages over a mobile phone network.

[0155] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[0156] server

[0157] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to family members or caregivers via a notification means. The server also periodically analyzes the data and creates reports using a report generation means. The main software used includes anomaly detection algorithms such as TensorFlow and PyTorch, and database management using SQL / RDS.

[0158] Terminal

[0159] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensors, movement sensors, heart rate monitors) as well as smart glasses and head-mounted displays. The collected data is temporarily stored in the terminal and then transmitted to the server, for example, every hour.

[0160] User

[0161] The user (elderly person living alone) does not need to operate the device in their daily life. The user (family member or caregiver) also receives notifications sent from the system and can respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, and these can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone. If an abnormality is detected, the system also includes means to adjust the operation of the autonomous vehicle and notify medical institutions and designated contacts.

[0162] Specific examples

[0163] For example, consider the case of an 80-year-old man living alone who uses this system. His home is equipped with temperature sensors, movement sensors, a heart rate monitor, smart glasses, and a head-mounted display. These devices monitor the man's daily activities and health in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to his family or caregiver if an abnormality is detected. The system also has the function of coordinating the operation of the autonomous vehicle and making emergency calls to medical institutions if necessary. Periodically generated reports help family members, caregivers, and medical professionals understand the man's overall health and take preventive medical measures.

[0164] Example prompts to be input to the generative AI model

[0165] Please explain how the "health monitoring system" ensures the safety and health of elderly people living alone. In particular, please include a detailed process flow for the anomaly detection algorithm and periodic report generation, as well as the names of the specific hardware and software used. For example, please also provide details of what kind of notification is sent when an anomaly is detected.

[0166] Such prompts can be used to elicit detailed and specific responses from the AI ​​model.

[0167] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0168] Step 1: Initial setup of device means

[0169] A temperature sensor, movement sensor, heart rate monitor, smart glasses, and head-mounted display are installed in the home of the user (elderly person living alone). This prepares the device means to monitor the behavior and health of the elderly person living alone. The input is the device installation and setting data, and the output is confirmation of normal operation. Specifically, each device is tested to see if it is operating normally.

[0170] Step 2: Data collection

[0171] The device means collects data on the daily activities and health status of elderly people living alone from temperature sensors, movement sensors, heart rate monitors, smart glasses, and head-mounted displays. The input is real-time data from each sensor, and the output is data temporarily stored in the terminal means. Specifically, each sensor periodically transmits data to the terminal.

[0172] Step 3: Send data

[0173] The terminal means transmits the collected data to the server at regular intervals (for example, every hour). The input is the temporarily stored data, and the output is the data transmitted to the server. Specifically, the terminal transmits the stored data in packets at regular intervals to the server.

[0174] Step 4: Data analysis and anomaly detection

[0175] The server receives data sent from the device and analyzes it in real time. Anomalies are detected using an anomaly detection algorithm (e.g., TensorFlow or PyTorch). The input is the data sent to the server, and the output is the anomaly detection results. Specifically, the server inputs the received data into the anomaly detection algorithm and obtains the analysis results.

[0176] Step 5: Notification

[0177] If an abnormality is detected, the server sends a notification to family members or caregivers via a notification method, which can include email, app notification, SMS, or emergency calls to medical institutions. The input is the abnormality detection result, and the output is a notification message. Specifically, the server selects the appropriate notification method, generates a notification message, and sends it.

[0178] Step 6: Coordinating autonomous vehicle operations

[0179] If an abnormality is detected, the operation of the autonomous vehicle is adjusted. For example, if an abnormality is detected while an elderly person living alone is out, the vehicle's speed can be adjusted or the vehicle can be set to automatically head to the nearest medical facility. The input is the abnormality detection result, and the output is an operation command for the autonomous vehicle. Specifically, the server sends a command to the vehicle's operation system.

[0180] Step 7: Generate and deliver scheduled reports

[0181] The server periodically generates a report summarizing the health status and behavioral patterns of elderly people living alone and provides it to the user (family or caregiver). This is done using a report generation means. The input is analyzed past data, and the output is the generated report. Specifically, the server retrieves past data from the database, performs statistical processing, and generates a report.

[0182] Prompt Sentence Examples

[0183] Please explain how the "health monitoring system" ensures the safety and health of elderly people living alone. In particular, please include a detailed process flow for the anomaly detection algorithm and periodic report generation, as well as the names of the specific hardware and software used. For example, please also provide details of what kind of notification is sent when an anomaly is detected.

[0184] 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.

[0185] The present invention is a system that aims to ensure the safety and health management of elderly people living alone by combining an emotion engine with the system, which can also grasp their emotional state and take appropriate measures. It includes the following components.

[0186] server

[0187] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to the user (family member or caregiver) via a notification means. The server also periodically analyzes the data and creates reports using a report generation means. In addition, it is equipped with an emotion engine that also analyzes the user's emotional data.

[0188] Terminal

[0189] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensor, movement sensor, heart rate monitor). The collected data is temporarily stored in the terminal, and is then transmitted to the server, for example, every hour.

[0190] Emotion Engine

[0191] The emotion engine has the ability to recognize the emotional state of elderly people living alone by analyzing their facial expressions, tone of voice, and behavioral patterns. For example, it uses a camera and microphone to collect and analyze facial and voice data. It also uses data from temperature and movement sensors to achieve more accurate emotion recognition.

[0192] User

[0193] The user (elderly person living alone) does not need to operate the device themselves; they simply go about their daily life as normal. The user (family or caregiver) can receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[0194] Program processing overview

[0195] Initial Setup

[0196] The server sets up individual profiles for elderly people living alone and initializes the database. The terminal pairs with various devices and verifies that they are working properly. The emotion engine is also configured in the same way, and collects basic data to record the facial expressions and voices of elderly people living alone.

[0197] Data collection and transmission

[0198] Devices collect data from the daily lives of elderly people living alone. For example, temperature sensors, movement sensors, and heart rate monitors send their respective data to the terminal. The emotion engine uses a camera and microphone to collect the elderly person's facial expressions and tone of voice and analyzes their emotions. The terminal temporarily stores this data and periodically sends it to a server.

[0199] Data analysis and anomaly detection

[0200] The server analyzes the received data in real time and detects any abnormalities. It also analyzes data from the emotion engine, and if any changes in emotions or stress levels are confirmed, these are also included in the notification content. If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via the notification means. The type of abnormality is identified, and the user is notified of countermeasures based on this.

[0201] Generate scheduled reports

[0202] The server periodically generates a report summarizing the health status and behavioral patterns of elderly people living alone. It also includes the results of emotion analysis, allowing for a comprehensive understanding of the elderly person's mental health. The report is provided to the user, who can share it with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[0203] Specific examples

[0204] For example, consider the case of an 80-year-old elderly person living alone who is using this system. The elderly person's home is equipped with temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to family members or caregivers if an abnormality is detected. In addition, the emotion engine analyzes the elderly person's emotional state from facial expressions and voice, and if the elderly person is feeling stressed, it sends an alert including that information. Periodically generated reports provide a comprehensive understanding of the elderly person's health condition and are used to take preventive medical measures.

[0205] In this way, the present invention provides a system that supports elderly people living alone to lead safe and healthy lives.

[0206] The processing flow will be explained below.

[0207] Step 1:

[0208] The user installs various sensors, cameras, microphones, and wearable devices in the homes of elderly people living alone, including temperature sensors, movement sensors, heart rate monitors, cameras, and microphones.

[0209] Step 2:

[0210] The terminal pairs with each installed device and checks the operation of each device, confirming that they are connected properly and making them ready to collect data.

[0211] Step 3:

[0212] The terminal receives data from each device in real time. Specific examples of data collected from a specific device include indoor temperature from a temperature sensor, movement patterns of elderly people living alone from a movement sensor, heart rate from a heart rate monitor, facial expressions from a camera, and tone of voice from a microphone.

[0213] Step 4:

[0214] The terminal temporarily stores the collected data and transmits it to the server at regular intervals (for example, every hour).

[0215] Step 5:

[0216] The server receives the data sent from the device, which is then stored in a database for later analysis.

[0217] Step 6:

[0218] The server analyzes the received data in real time using anomaly detection algorithms to check, for example, whether an elderly person living alone has an abnormal heart rate or an abnormal movement pattern.

[0219] Step 7:

[0220] The server uses an emotion engine to analyze the emotional state of the elderly person living alone. Based on data collected from the camera and microphone, it evaluates facial expressions and tone of voice to determine whether the elderly person is under stress.

[0221] Step 8:

[0222] If an abnormality is detected, the server generates an alert containing the details of the abnormality (e.g., heart rate is too high, no movement for a long time, high stress, etc.).

[0223] Step 9:

[0224] The server sends an alert to the user (family member or caregiver) via a notification method, which can be in the form of email, app notification, SMS, etc.

[0225] Step 10:

[0226] The user (family member or caregiver) receives the notification from the server and responds promptly. They check the content of the notification and take necessary measures, such as contacting the elderly person living alone or heading to the scene.

[0227] Step 11:

[0228] The server periodically (e.g., weekly or monthly) collects and analyzes data and generates reports based on the collected data. The reports summarize the health status, behavioral patterns, and emotional states of elderly people living alone, and also include a history of abnormal occurrences.

[0229] Step 12:

[0230] The server provides the generated report to the user (family or caregiver), who can share the report with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[0231] Example 2

[0232] 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."

[0233] In modern society, the number of elderly people living alone is increasing, making their safety and health management a major issue. Elderly people living alone are particularly at high risk of getting into dangerous situations, and delaying appropriate responses can lead to serious consequences. Furthermore, while mental health is important in addition to physical health, there are very limited means of remotely monitoring it. A system that can resolve these issues and manage the safety and health of elderly people living alone more comprehensively and quickly is needed.

[0234] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a sensor means for collecting data on the behavior and health condition of the elderly person living alone, a terminal means for temporarily storing the collected data and transmitting it to the server at regular intervals, an analysis means for analyzing the received data and detecting abnormalities, a notification means for issuing a notification when an abnormality is detected, a report generation means for periodically generating reports and providing them to the user, and an emotion analysis means for analyzing the emotional state of the elderly person living alone. This makes it possible to ensure the safety of the elderly person living alone and manage their health condition comprehensively.

[0235] "Elderly people living alone" refers to elderly people who live alone and do not live with others on a daily basis.

[0236] "Sensor means" refers to devices for collecting data such as temperature, movement, heart rate, etc.

[0237] The term "terminal means" refers to a device that temporarily stores data collected from the sensor means and transmits the data to the server at regular intervals.

[0238] "Analysis means" refers to an algorithm or program that analyzes data received by the server and detects abnormalities.

[0239] "Notification means" refers to a method or system for sending an alert to the user (family member or caregiver) when an abnormality is detected.

[0240] "Report generation means" refers to the function of periodically compiling data and creating a report summarizing the health status and behavioral patterns of elderly people living alone.

[0241] "Emotion analysis means" refers to algorithms or devices that analyze the facial expressions and tone of voice of elderly people living alone and recognize their emotional state.

[0242] "Database" refers to an information accumulation system that stores collected data and allows for quick search and retrieval of required data.

[0243] "Anomaly detection algorithm" refers to a mathematical or statistical method or program that analyzes received data and detects abnormal conditions.

[0244] MODE FOR CARRYING OUT THE INVENTION

[0245] The present invention provides a system for ensuring the safety and health management of elderly people living alone. This system can monitor the behavior, health status, and emotional state of elderly people living alone. The system includes the following main hardware and software components:

[0246] Hardware

[0247] server

[0248] The server collects and analyzes data on the behavior and health status of elderly people living alone. Specifically, it stores the received data in a database and analyzes it using an anomaly detection algorithm. It also has an emotion engine that analyzes the emotional data of elderly people living alone. If an abnormality is detected, it sends an alert to the user (family member or caregiver) via a notification means.

[0249] Terminal

[0250] The terminal is installed in the home of an elderly person living alone. It collects and temporarily stores data from devices such as temperature sensors, movement sensors, and heart rate monitors. The terminal has the function of transmitting this data to a server at regular intervals (for example, every hour).

[0251] Sensors

[0252] Temperature sensor: Measures the temperature inside the room.

[0253] Movement sensor: Detects the movements of elderly people living alone and collects that data.

[0254] Heart rate monitor: Real-time monitoring of the heart rate of elderly people living alone.

[0255] Camera: Captures the facial expression of an elderly man living alone.

[0256] Microphone: Collects the tone of voice of elderly people living alone.

[0257] software

[0258] Server Software

[0259] Database: A system for storing collected data, such as an SQL database.

[0260] Anomaly detection algorithms: Mathematical and statistical methods for analyzing received data and detecting anomalies.

[0261] Emotion engine: An algorithm that analyzes facial expressions and tone of voice to recognize the emotional state of elderly people living alone.

[0262] Terminal Software

[0263] The terminal software includes a program to collect and temporarily store data from various sensors in real time and send it to a server at regular intervals. The format of the data is also checked when it is sent.

[0264] Specific examples

[0265] For example, consider the case of an 80-year-old elderly person living alone who uses this system. The elderly person's home is equipped with temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to family members or caregivers if an abnormality is detected. In addition, the emotion engine analyzes the elderly person's emotional state from facial expressions and voice, and if stress is confirmed, it sends an alert including that information. Periodically generated reports are used to comprehensively understand the elderly person's health condition and take preventive medical measures.

[0266] Prompt Sentence Examples

[0267] "An 80-year-old elderly person living alone uses a system to monitor his daily activities and health. The system includes temperature sensors, movement sensors, a heart rate monitor, a camera, and a microphone. Data collected from the device is stored on the terminal and periodically sent to a server. The server analyzes the data and notifies family members or caregivers if an abnormality is detected. An emotion engine analyzes the emotional state from facial expressions and voice, and if stress is confirmed, that information is also notified. Periodically generated reports help to understand the patient's overall health."

[0268] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0269] Step 1: Initial Setup

[0270] server:

[0271] The server performs the initial setup of the system. First, it sets up an individual profile based on basic information about the elderly person living alone and initializes the database. The profile includes information such as the normal range of heart rate and reference values ​​for behavioral patterns. Next, it loads anomaly detection algorithms and emotion analysis algorithms and checks their operation. Based on this setup, the server prepares for data analysis.

[0272] Device:

[0273] The device pairs with each device installed in the home (temperature sensor, movement sensor, heart rate monitor, camera, microphone). Once pairing is complete, the device checks whether it is ready to collect data. The device prepares to send data to the server at the set interval (usually every hour).

[0274] Step 2: Data collection and temporary storage

[0275] Device:

[0276] Each device connected to the terminal begins collecting data. The temperature sensor captures the room temperature, the movement sensor detects the elderly person's movements and records the data. The heart rate monitor monitors the heart rate in real time and collects data every second. The camera uses facial recognition technology to collect facial expression data, and the microphone records the tone of voice. This data is stored in the terminal's temporary memory.

[0277] Input and Output:

[0278] Input: Sensor data generated by the device (temperature, movement, heart rate, facial expression, voice)

[0279] Data processing: Each data is stored in temporary memory according to the terminal format.

[0280] Output: Sensor data stored in the device's temporary memory

[0281] Step 3: Send data

[0282] Device:

[0283] The terminal sends collected data to the server at set intervals (e.g., every hour). Before sending, the data is checked to see if it is missing or if the format is correct. If the data transmission is successful, the next collection interval begins.

[0284] Input and Output:

[0285] Input: Sensor data stored in temporary memory

[0286] Data processing: format check and data formatting

[0287] Output: Sensor data sent to the server

[0288] Step 4: Data analysis

[0289] server:

[0290] The server analyzes the received sensor data. It combines temperature, movement, and heart rate data to detect abnormal patterns. Facial expression and voice data are used for emotion analysis. The analysis results are stored in a database, including information on any abnormalities detected.

[0291] Input and Output:

[0292] Input: Received sensor data

[0293] Data computation: running anomaly detection and sentiment analysis algorithms

[0294] Output: Analysis results (abnormal data, emotional state)

[0295] Step 5: Anomaly detection and notification

[0296] server:

[0297] If the server detects any abnormalities as a result of the analysis, it will send a notification. Based on the type of abnormality (abnormal heart rate, length of inactivity, abnormal room temperature, etc.), it will send a notification to the user (family member or caregiver) urging them to take action. Notification methods include email, app notification, and SMS.

[0298] Input and Output:

[0299] Input: Analysis results (abnormal data)

[0300] Data processing: Notification content generation

[0301] Output: Alert notification sent to user

[0302] Step 6: Sentiment Analysis

[0303] server:

[0304] Using an emotion engine, the system analyzes facial expression and voice data to recognize the emotional state of elderly people living alone. It constantly monitors and records the analysis results in a database, instantly detecting abnormalities such as stress or anxiety. If an abnormality is detected, the system notifies the user.

[0305] Input and Output:

[0306] Input: Received facial expression data and voice data

[0307] Data computation: running sentiment analysis algorithms

[0308] Output: Emotion analysis results (stress, etc.), notification to user

[0309] Step 7: Generate scheduled reports

[0310] server:

[0311] The server aggregates and analyzes the data at regular intervals (e.g., daily, weekly, monthly) and generates a report that comprehensively summarizes the health status, behavioral patterns, and emotional state of the elderly person living alone. The report is provided to the user (family or caregiver) and used for caregiving or medical treatment.

[0312] Input and Output:

[0313] Input: Sensor data and analysis results stored in a database

[0314] Data processing: data aggregation, trend analysis, conversion to report format

[0315] Output: Regular reports provided to users

[0316] The above is the specific processing flow of this system. By explaining in detail the input, data processing, data calculation, and output at each step, the overall picture of the system can be made clearer.

[0317] (Application example 2)

[0318] 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."

[0319] In modern society, the number of elderly people living alone is increasing significantly, and ensuring their safety and health management is a major social issue. Conventional systems focus on monitoring basic behavior and health status, but do not consider emotional state or mental health. As a result, psychological stress and loneliness increase, which increases health risks.

[0320] 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 sensor means for collecting data to monitor the behavior of elderly people living alone, information processing means for temporarily storing the collected data and transmitting it to the server at regular intervals, server means for analyzing the received data and detecting abnormalities, warning means for issuing a notification when an abnormality is detected, information generation means for periodically generating reports and providing them to the user, and emotion analysis means for analyzing facial expressions and voice to recognize emotional states. This makes it possible to comprehensively manage the safety and health of elderly people living alone and reduce psychological stress and loneliness.

[0321] The "sensor means" is a device for collecting data on the behavior and health status of elderly people living alone.

[0322] "Information processing means" refers to a device or software that temporarily stores collected data and transmits it to a server at regular intervals.

[0323] The "server means" is a central management system that analyzes received data and detects abnormalities.

[0324] The "alert issuing means" is a device or software that sends an alert to the user when an abnormality is detected.

[0325] An "information generating means" is a device or software that periodically generates reports and provides them to a user.

[0326] "Emotion analysis means" refers to a device or software that analyzes facial expressions and voice and recognizes emotional states.

[0327] This invention is a security and healthcare system aimed at ensuring the safety and health management of elderly people living alone. This system makes it possible to monitor behavior and manage health conditions, as well as grasp emotional states. Specific embodiments are described below.

[0328] server

[0329] The server plays a central role in collecting and analyzing data sent from the sensor means and information processing means installed in the homes of elderly people living alone. The server has the following functions:

[0330] 1. Data reception and storage: The server receives the temperature, movement, heart rate, camera images, and audio data sent from the device and stores them in a database.

[0331] 2. Data Analysis: The server analyzes the stored data and runs algorithms to detect anomalies, including emotion analysis, which analyzes facial expressions and voice data to understand the user's emotional state.

[0332] 3. Abnormality notification: If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via an alert notification method, such as email, app notification, or SMS.

[0333] 4. Report generation: The server periodically analyzes the data and generates a report including the health status, behavioral patterns, and emotional state of the elderly living alone, and provides it to the user.

[0334] Terminal

[0335] The terminal temporarily stores the data collected from the sensor means and transmits it to the server at regular intervals. The terminal has the following functions.

[0336] 1. Data Collection: Collect data in real time from temperature sensors, movement sensors, heart rate monitors, and cameras.

[0337] 2. Data transmission: Collected data is temporarily stored and periodically transmitted to the server.

[0338] User

[0339] Users (family members or caregivers) can receive notifications from the server and monitor the condition of the elderly living alone in real time. They can also get a comprehensive understanding of the elderly's health and emotional state through periodically generated reports.

[0340] Hardware and Software

[0341] Hardware: Camera, microphone, temperature sensor, movement sensor, heart rate monitor

[0342] Software: Data analysis software (including anomaly detection algorithms), emotion analysis software (e.g., OpenCV and voice analysis software)

[0343] Specific examples of processing

[0344] For example, the home of an 80-year-old elderly person living alone is equipped with temperature sensors, movement sensors, a heart rate monitor, a camera, and a microphone. Data collected from these devices is sent to the terminal and then sent to a server every hour. The server analyzes the data and sends a notification to the user if an abnormality is detected. It also identifies the user's emotional state through analysis of facial expressions and voice, and sends a notification if stress or anxiety is detected. Periodically generated reports detail changes in health status and emotions, allowing the user to take prompt action at home or in a nursing home.

[0345] Prompt Sentence Examples

[0346] "Please generate a notification message for the family when an 80-year-old person living alone experiences a sudden increase in heart rate, but their behavioral patterns are normal. Please also include a response message if facial expression analysis indicates anxiety."

[0347] In this way, the present invention provides a comprehensive system for supporting elderly people living alone to lead safe and healthy lives.

[0348] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0349] Step 1:

[0350] The device collects data from sensors. Specifically, it acquires data in real time from temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. The input is data from each sensor, which is temporarily stored. The output is data stored in the device.

[0351] Step 2:

[0352] The terminal sends the collected data to the server at a predetermined time interval (for example, every hour). The input is the data saved in step 1, and a data format is created to send it to the server. The output is the data sent to the server.

[0353] Step 3:

[0354] The server stores the data received from the terminal in the database. The input is the data sent from the terminal and stores it in the database in the specified format. The output is the data successfully stored in the database.

[0355] Step 4:

[0356] The server analyzes the stored data and detects anomalies. Specifically, it analyzes temperature, movement, and heart rate data, as well as emotion analysis from camera and audio data. The input is the data stored in the database, and it runs anomaly detection algorithms and emotion analysis algorithms. The output is the analysis results.

[0357] Step 5:

[0358] If an anomaly is detected, the server notifies the user via an alerting mechanism. The input is the analysis result from step 4, and a notification is generated only if an anomaly is identified. The output is a notification to the user (email, app notification, SMS).

[0359] Step 6:

[0360] The server periodically generates reports that include the health status, behavioral patterns, and emotional states of elderly people living alone. The input is the data stored in the database and the analysis results, which are then automatically generated as a formatted report. The output is a report that is provided to the user.

[0361] Step 7:

[0362] The user receives reports provided by the server and understands the condition of the elderly person living alone. If an abnormality is notified, the user responds promptly. The input is the notification and report sent from the server, and the user considers countermeasures based on this. The output is the implementation of the countermeasures.

[0363] This processing flow enables the system to comprehensively manage the health and safety of elderly people living alone and respond quickly when necessary.

[0364] 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.

[0365] 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.

[0366] 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.

[0367] [Second embodiment]

[0368] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0369] 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.

[0370] 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).

[0371] 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.

[0372] 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.

[0373] 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).

[0374] 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.

[0375] 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.

[0376] 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.

[0377] 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.

[0378] 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.

[0379] 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."

[0380] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[0381] server

[0382] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to the user (family member or caregiver) via the notification means. The server also periodically analyzes the data and creates reports using the report generation means.

[0383] Terminal

[0384] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensor, movement sensor, heart rate monitor). The collected data is temporarily stored in the terminal, and is then transmitted to the server, for example, every hour.

[0385] User

[0386] The user (elderly person living alone) does not need to operate the device themselves; they simply go about their daily life as normal. The user (family or caregiver) can receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[0387] Program processing overview

[0388] Initial Setup

[0389] The server sets up individual profiles for elderly people living alone and initializes the database. The terminal pairs with various devices and verifies that the devices are working properly.

[0390] Data collection and transmission

[0391] Devices collect data from the daily lives of elderly people living alone. For example, temperature sensors, movement sensors, and heart rate monitors send their respective data to a terminal. The terminal temporarily stores this data and periodically sends it to a server.

[0392] Data analysis and anomaly detection

[0393] The server analyzes the received data in real time and detects any abnormalities. If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via a notification means. The type of abnormality is identified, and the user is notified of countermeasures based on that information.

[0394] Generate scheduled reports

[0395] The server periodically generates a report summarizing the health status and behavioral patterns of the elderly person living alone. The report is provided to the user, who can share it with caregivers and medical professionals to manage the health of the elderly person living alone.

[0396] Specific examples

[0397] For example, consider the case of an 80-year-old elderly person living alone who is using this system. Temperature sensors, movement sensors, and heart rate monitors are installed in the elderly person's home. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. Upon receiving the data, the server immediately analyzes it and sends a notification to the elderly person's family or caregiver if an abnormality is detected. In addition, periodically generated reports can provide a comprehensive understanding of the elderly person's health condition and can be used to take preventive medical measures.

[0398] In this way, the present invention provides a system that supports elderly people living alone to lead safe and healthy lives.

[0399] The processing flow will be explained below.

[0400] Step 1:

[0401] Users install various sensors, cameras, and wearable devices in the homes of elderly people living alone, including temperature sensors, movement sensors, and heart rate monitors.

[0402] Step 2:

[0403] The terminal pairs with the installed devices and checks the operation of each device, confirming that they are connected properly and making them ready to collect data.

[0404] Step 3:

[0405] The terminal receives real-time data collected from devices, such as indoor temperature data from a temperature sensor, movement patterns of elderly people living alone from a movement sensor, and heart rate data from a heart rate monitor.

[0406] Step 4:

[0407] The device temporarily stores the collected data, which is then set to be sent to the server periodically (e.g., every hour).

[0408] Step 5:

[0409] The server receives the data sent from the device, which is then stored in a database for later analysis.

[0410] Step 6:

[0411] The server analyzes the received data in real time using anomaly detection algorithms, for example, to check whether the heart rate of an elderly person living alone is outside the normal range or if there are any abnormalities in their movement patterns.

[0412] Step 7:

[0413] The server generates an alert if an abnormality is detected. A notification is generated containing the details of the abnormality (e.g., heart rate is too high, the user has not moved for a long time, etc.).

[0414] Step 8:

[0415] The server sends an alert to the user (family member or caregiver) via a notification method, which can be in the form of email, app notification, SMS, etc.

[0416] Step 9:

[0417] The user (family member or caregiver) receives the notification from the server and responds promptly. They check the content of the notification and take necessary measures, such as contacting the elderly person living alone or heading to the scene.

[0418] Step 10:

[0419] The server periodically (e.g., weekly or monthly) collects and analyzes data and generates reports based on the collected data. The reports summarize the health status and behavioral patterns of elderly people living alone, and also include a history of abnormal occurrences.

[0420] Step 11:

[0421] The server provides the generated report to the user (family or caregiver), who can share the report with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[0422] Example 1

[0423] 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."

[0424] Ensuring the safety and health management of elderly people living alone is an important issue in modern society. Because many elderly people live alone, a rapid response is required in the event of a sudden change in their physical condition or an accident. However, it is difficult to continuously monitor their health status and behavioral patterns on a daily basis, and there is a lack of systems that provide appropriate notifications in the event of an abnormality. To address these issues, the present invention aims to provide a system that monitors the behavior and health status of elderly people living alone in real time and immediately issues an alert in the event of an abnormality.

[0425] 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.

[0426] In this invention, the server includes a sensor means, a terminal means, a data analysis means, a warning means, a report generation means, a setting means, and a pairing means. This makes it possible to monitor the behavior and health status of elderly people living alone in real time and analyze the collected data at regular intervals. Furthermore, if an abnormality is detected, a notification is sent to the user immediately, and periodic reports can be generated and provided, thereby enabling efficient safety and health management of elderly people living alone.

[0427] The "sensor means" is a device that collects data to monitor the behavior and health condition of elderly people living alone, and specifically includes a temperature sensor, a movement sensor, a heart rate monitor, and the like.

[0428] The "terminal means" is a device that temporarily stores collected data and transmits it to a data processing device at regular intervals.

[0429] "Data analysis means" is a combination of software and hardware for analyzing data received by the server and detecting abnormalities.

[0430] "Warning means" refers to the means for sending a notification when an abnormality is detected, and specifically includes email, app notification, SMS, etc.

[0431] The "report generating means" is a means for periodically generating a report based on the health condition and behavior patterns of an elderly person living alone and providing the report to a user.

[0432] The "setting means" is a means for setting the initial settings of the server and individual profiles of elderly people living alone, and for initializing the database.

[0433] The "pairing means" is a means for connecting various sensor means and terminal means so that they can communicate with each other, and for confirming that the devices are operating normally.

[0434] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[0435] server

[0436] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with anomaly detection algorithms using libraries such as Python, Pandas, and NumPy, and if an abnormality is detected, it promptly sends an alert to family members or caregivers via notification means. The server also periodically analyzes the data and generates reports using Microsoft Power BI or Tableau.

[0437] Terminal

[0438] The terminal temporarily stores data from various sensor means. The terminal is installed in the home of an elderly person living alone and collects data in real time from temperature sensors, movement sensors, heart rate monitors, etc. For example, it uses a Bluetooth stack to pair with the device and checks that it is working properly. The collected data is temporarily stored in the terminal and sent to the server at regular intervals (for example, every hour). HTTP or MQTT is used as the communication protocol.

[0439] User

[0440] The user (elderly person living alone) simply lives their daily life as normal and does not need to operate the device themselves. Family members or caregivers can also receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[0441] Specific examples

[0442] For example, consider the case of an 80-year-old elderly person living alone who is using this system. Temperature sensors, movement sensors, and heart rate monitors are installed in the elderly person's home. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. When the server receives the data, it immediately analyzes it and sends a notification to the family or caregiver if an abnormality is detected. In addition, the periodically generated reports can provide a comprehensive understanding of the elderly person's health condition and can be used to take preventive medical measures.

[0443] An example prompt is:

[0444] "Describe a data analysis system that helps an 80-year-old person living alone live a safe and healthy life. Please explain in detail the entire process from data collection, storage, analysis, and notification, as well as the relevant hardware and software."

[0445] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0446] Step 1: Initial Setup

[0447] The server inputs basic information about the elderly person living alone and sets up an individual profile. Specifically, it registers data such as name, age, health status, and emergency contact information in the database and initializes the system. Next, it sets information about various sensor means (temperature sensors, movement sensors, heart rate monitors, etc.) and defines the role and characteristics of each.

[0448] Input: Basic information of elderly people living alone, information on sensor means

[0449] Output: Individual profiles registered in the database, initialized system settings

[0450] Step 2: Pairing devices

[0451] The device pairs with various sensor means and verifies that they are working properly. Using the Bluetooth stack, the device is configured to receive data from each sensor. This prepares the device to collect data in real time.

[0452] Input: Sensor connection information

[0453] Output: Pairing successful, communication established between device and sensor

[0454] Step 3: Data collection

[0455] The device collects data from the daily life of elderly people living alone through various sensor means (temperature sensor, movement sensor, heart rate monitor). Specifically, the temperature sensor measures the room temperature, the movement sensor detects the elderly person's movements, and the heart rate monitor measures the heart rate.

[0456] Input: Real-time data from various sensor means

[0457] Output: Sensor data temporarily stored on the device

[0458] Step 4: Temporarily save data

[0459] The device temporarily stores the collected data in its internal storage, where it is saved as a CSV or JSON file for further processing.

[0460] Input: Collected sensor data

[0461] Output: Data file saved in internal storage

[0462] Step 5: Send data periodically

[0463] The device sends the stored data to the server at regular intervals (for example, every hour). The communication protocol is HTTP or MQTT, and the data is sent in JSON or Protobuf format.

[0464] Input: Data files stored in internal storage

[0465] Output: Data sent to the server

[0466] Step 6: Data analysis

[0467] The server analyzes the received data in real time, preprocessing the data and extracting features using libraries such as Python, Pandas, and NumPy, and applying anomaly detection algorithms to detect anomalies using generative AI models.

[0468] Input: Sensor data sent from the device

[0469] Output: Analysis results, whether anomalies were detected

[0470] Step 7: Anomaly detection and notification

[0471] If the server detects an abnormality through analysis, it will promptly send an alert to family members or caregivers via notification methods (email, app notification, SMS, etc.) that include the type of abnormality and recommended actions to take.

[0472] Input: Analysis results, whether anomalies were detected

[0473] Output: Alert notification sent to family members or caregivers

[0474] Step 8: Generate scheduled reports

[0475] The server periodically analyzes the health status and behavioral patterns of elderly people living alone and generates reports using Microsoft Power BI and Tableau, which are presented in a visually easy-to-understand format.

[0476] Input: Analyzed health and behavioral data

[0477] Output: Generated scheduled reports

[0478] Step 9: Provide to users

[0479] The server provides the generated reports to family members and caregivers, and the reports are delivered in PDF format or as a web application for easy viewing by users.

[0480] Input: Generated Scheduled Report

[0481] Output: Report provided to family and caregivers

[0482] (Application example 1)

[0483] 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."

[0484] In modern society, the safety and health management of elderly people living alone are important issues. In particular, it is necessary to ensure the safety of elderly people living alone when they go out, and to constantly and accurately monitor their health status and respond quickly and effectively if an abnormality is detected. Furthermore, conventional systems do not adequately guarantee the safety of elderly people living alone while they are traveling, and there is also the issue of a lack of reliable means of managing their safety when they are out.

[0485] 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.

[0486] In this invention, the server includes a system that adds a device means for monitoring the behavior and health status of elderly people living alone, a terminal means for temporarily storing collected data and sending it to the server at regular intervals, a server means for analyzing the received data and detecting abnormalities, a notification means for issuing a notification when an abnormality is detected, a report generation means for periodically generating reports and providing them to the user, and a means for adjusting the operation of the autonomous vehicle and notifying medical institutions and designated contacts when an abnormality is detected. This makes it possible to improve the safety of elderly people living alone and manage their safety when they are out and about.

[0487] "Elderly people living alone" refers to elderly people who live alone.

[0488] "Devices and means for monitoring behavior and health status" refers to sensors and devices used to monitor the daily behavior and health status of elderly people living alone.

[0489] "Terminal means" refers to a device that temporarily stores data collected from device means and transmits it to a server at regular intervals.

[0490] "Server means" refers to a central management device or system that analyzes received data and detects abnormalities.

[0491] "Notification means" refers to a mechanism for issuing a notification when an abnormality is detected.

[0492] "Report generation means" refers to a mechanism that periodically analyzes data, generates reports, and provides them to users.

[0493] "Means for adjusting the operation of self-driving vehicles" refers to a system for controlling the operation status of self-driving vehicles and ensuring the safety of elderly people living alone.

[0494] "Means of notifying medical institutions and designated contacts" refers to a system for sending emergency notifications to medical institutions and pre-designated contacts when an abnormality occurs.

[0495] A "temperature sensor" refers to a device that measures the ambient temperature and transmits that data to a terminal.

[0496] A "movement sensor" refers to a device that detects the movement of an object and transmits that data to a terminal.

[0497] A "heart rate monitor" refers to a device that measures heart rate and transmits that data to a terminal.

[0498] "Smart glasses" refers to eyeglass-type devices that enhance the wearer's visual information or provide additional data.

[0499] "Head-mounted display" refers to a display device used to present digital information to the wearer's field of vision.

[0500] "Email" refers to a means of sending and receiving messages electronically over the Internet.

[0501] "App notifications" refers to the means by which applications notify users of messages or information on smartphones and other devices.

[0502] "SMS" refers to the service of sending and receiving short text messages over a mobile phone network.

[0503] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[0504] server

[0505] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to family members or caregivers via a notification means. The server also periodically analyzes the data and creates reports using a report generation means. The main software used includes anomaly detection algorithms such as TensorFlow and PyTorch, and database management using SQL / RDS.

[0506] Terminal

[0507] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensors, movement sensors, heart rate monitors) as well as smart glasses and head-mounted displays. The collected data is temporarily stored in the terminal and then transmitted to the server, for example, every hour.

[0508] User

[0509] The user (elderly person living alone) does not need to operate the device in their daily life. The user (family member or caregiver) also receives notifications sent from the system and can respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, and these can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone. If an abnormality is detected, the system also includes means to adjust the operation of the autonomous vehicle and notify medical institutions and designated contacts.

[0510] Specific examples

[0511] For example, consider the case of an 80-year-old man living alone who uses this system. His home is equipped with temperature sensors, movement sensors, a heart rate monitor, smart glasses, and a head-mounted display. These devices monitor the man's daily activities and health in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to his family or caregiver if an abnormality is detected. The system also has the function of coordinating the operation of the autonomous vehicle and making emergency calls to medical institutions if necessary. Periodically generated reports help family members, caregivers, and medical professionals understand the man's overall health and take preventive medical measures.

[0512] Example prompts to be input to the generative AI model

[0513] Please explain how the "health monitoring system" ensures the safety and health of elderly people living alone. In particular, please include a detailed process flow for the anomaly detection algorithm and periodic report generation, as well as the names of the specific hardware and software used. For example, please also provide details of what kind of notification is sent when an anomaly is detected.

[0514] Such prompts can be used to elicit detailed and specific responses from the AI ​​model.

[0515] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0516] Step 1: Initial setup of device means

[0517] A temperature sensor, movement sensor, heart rate monitor, smart glasses, and head-mounted display are installed in the home of the user (elderly person living alone). This prepares the device means to monitor the behavior and health of the elderly person living alone. The input is the device installation and setting data, and the output is confirmation of normal operation. Specifically, each device is tested to see if it is operating normally.

[0518] Step 2: Data collection

[0519] The device means collects data on the daily activities and health status of elderly people living alone from temperature sensors, movement sensors, heart rate monitors, smart glasses, and head-mounted displays. The input is real-time data from each sensor, and the output is data temporarily stored in the terminal means. Specifically, each sensor periodically transmits data to the terminal.

[0520] Step 3: Send data

[0521] The terminal means transmits the collected data to the server at regular intervals (for example, every hour). The input is the temporarily stored data, and the output is the data transmitted to the server. Specifically, the terminal transmits the stored data in packets at regular intervals to the server.

[0522] Step 4: Data analysis and anomaly detection

[0523] The server receives data sent from the device and analyzes it in real time. Anomalies are detected using an anomaly detection algorithm (e.g., TensorFlow or PyTorch). The input is the data sent to the server, and the output is the anomaly detection results. Specifically, the server inputs the received data into the anomaly detection algorithm and obtains the analysis results.

[0524] Step 5: Notification

[0525] If an abnormality is detected, the server sends a notification to family members or caregivers via a notification method, which can include email, app notification, SMS, or emergency calls to medical institutions. The input is the abnormality detection result, and the output is a notification message. Specifically, the server selects the appropriate notification method, generates a notification message, and sends it.

[0526] Step 6: Coordinating autonomous vehicle operations

[0527] If an abnormality is detected, the operation of the autonomous vehicle is adjusted. For example, if an abnormality is detected while an elderly person living alone is out, the vehicle's speed can be adjusted or the vehicle can be set to automatically head to the nearest medical facility. The input is the abnormality detection result, and the output is an operation command for the autonomous vehicle. Specifically, the server sends a command to the vehicle's operation system.

[0528] Step 7: Generate and deliver scheduled reports

[0529] The server periodically generates a report summarizing the health status and behavioral patterns of elderly people living alone and provides it to the user (family or caregiver). This is done using a report generation means. The input is analyzed past data, and the output is the generated report. Specifically, the server retrieves past data from the database, performs statistical processing, and generates a report.

[0530] Prompt Sentence Examples

[0531] Please explain how the "health monitoring system" ensures the safety and health of elderly people living alone. In particular, please include a detailed process flow for the anomaly detection algorithm and periodic report generation, as well as the names of the specific hardware and software used. For example, please also provide details of what kind of notification is sent when an anomaly is detected.

[0532] 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.

[0533] The present invention is a system that aims to ensure the safety and health management of elderly people living alone by combining an emotion engine with the system, which can also grasp their emotional state and take appropriate measures. It includes the following components.

[0534] server

[0535] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to the user (family member or caregiver) via a notification means. The server also periodically analyzes the data and creates reports using a report generation means. In addition, it is equipped with an emotion engine that also analyzes the user's emotional data.

[0536] Terminal

[0537] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensor, movement sensor, heart rate monitor). The collected data is temporarily stored in the terminal, and is then transmitted to the server, for example, every hour.

[0538] Emotion Engine

[0539] The emotion engine has the ability to recognize the emotional state of elderly people living alone by analyzing their facial expressions, tone of voice, and behavioral patterns. For example, it uses a camera and microphone to collect and analyze facial and voice data. It also uses data from temperature and movement sensors to achieve more accurate emotion recognition.

[0540] User

[0541] The user (elderly person living alone) does not need to operate the device themselves; they simply go about their daily life as normal. The user (family or caregiver) can receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[0542] Program processing overview

[0543] Initial Setup

[0544] The server sets up individual profiles for elderly people living alone and initializes the database. The terminal pairs with various devices and verifies that they are working properly. The emotion engine is also configured in the same way, and collects basic data to record the facial expressions and voices of elderly people living alone.

[0545] Data collection and transmission

[0546] Devices collect data from the daily lives of elderly people living alone. For example, temperature sensors, movement sensors, and heart rate monitors send their respective data to the terminal. The emotion engine uses a camera and microphone to collect the elderly person's facial expressions and tone of voice and analyzes their emotions. The terminal temporarily stores this data and periodically sends it to a server.

[0547] Data analysis and anomaly detection

[0548] The server analyzes the received data in real time and detects any abnormalities. It also analyzes data from the emotion engine, and if any changes in emotions or stress levels are confirmed, these are also included in the notification content. If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via the notification means. The type of abnormality is identified, and the user is notified of countermeasures based on this.

[0549] Generate scheduled reports

[0550] The server periodically generates a report summarizing the health status and behavioral patterns of elderly people living alone. It also includes the results of emotion analysis, allowing for a comprehensive understanding of the elderly person's mental health. The report is provided to the user, who can share it with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[0551] Specific examples

[0552] For example, consider the case of an 80-year-old elderly person living alone who is using this system. The elderly person's home is equipped with temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to family members or caregivers if an abnormality is detected. In addition, the emotion engine analyzes the elderly person's emotional state from facial expressions and voice, and if the elderly person is feeling stressed, it sends an alert including that information. Periodically generated reports provide a comprehensive understanding of the elderly person's health condition and are used to take preventive medical measures.

[0553] In this way, the present invention provides a system that supports elderly people living alone to lead safe and healthy lives.

[0554] The processing flow will be explained below.

[0555] Step 1:

[0556] The user installs various sensors, cameras, microphones, and wearable devices in the homes of elderly people living alone, including temperature sensors, movement sensors, heart rate monitors, cameras, and microphones.

[0557] Step 2:

[0558] The terminal pairs with each installed device and checks the operation of each device, confirming that they are connected properly and making them ready to collect data.

[0559] Step 3:

[0560] The terminal receives data from each device in real time. Specific examples of data collected from a specific device include indoor temperature from a temperature sensor, movement patterns of elderly people living alone from a movement sensor, heart rate from a heart rate monitor, facial expressions from a camera, and tone of voice from a microphone.

[0561] Step 4:

[0562] The terminal temporarily stores the collected data and transmits it to the server at regular intervals (for example, every hour).

[0563] Step 5:

[0564] The server receives the data sent from the device, which is then stored in a database for later analysis.

[0565] Step 6:

[0566] The server analyzes the received data in real time using anomaly detection algorithms to check, for example, whether an elderly person living alone has an abnormal heart rate or an abnormal movement pattern.

[0567] Step 7:

[0568] The server uses an emotion engine to analyze the emotional state of the elderly person living alone. Based on data collected from the camera and microphone, it evaluates facial expressions and tone of voice to determine whether the elderly person is under stress.

[0569] Step 8:

[0570] If an abnormality is detected, the server generates an alert containing the details of the abnormality (e.g., heart rate is too high, no movement for a long time, high stress, etc.).

[0571] Step 9:

[0572] The server sends an alert to the user (family member or caregiver) via a notification method, which can be in the form of email, app notification, SMS, etc.

[0573] Step 10:

[0574] The user (family member or caregiver) receives the notification from the server and responds promptly. They check the content of the notification and take necessary measures, such as contacting the elderly person living alone or heading to the scene.

[0575] Step 11:

[0576] The server periodically (e.g., weekly or monthly) collects and analyzes data and generates reports based on the collected data. The reports summarize the health status, behavioral patterns, and emotional states of elderly people living alone, and also include a history of abnormal occurrences.

[0577] Step 12:

[0578] The server provides the generated report to the user (family or caregiver), who can share the report with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[0579] Example 2

[0580] 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."

[0581] In modern society, the number of elderly people living alone is increasing, making their safety and health management a major issue. Elderly people living alone are particularly at high risk of getting into dangerous situations, and delaying appropriate responses can lead to serious consequences. Furthermore, while mental health is important in addition to physical health, there are very limited means of remotely monitoring it. A system that can resolve these issues and manage the safety and health of elderly people living alone more comprehensively and quickly is needed.

[0582] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a sensor means for collecting data on the behavior and health condition of the elderly person living alone, a terminal means for temporarily storing the collected data and transmitting it to the server at regular intervals, an analysis means for analyzing the received data and detecting abnormalities, a notification means for issuing a notification when an abnormality is detected, a report generation means for periodically generating reports and providing them to the user, and an emotion analysis means for analyzing the emotional state of the elderly person living alone. This makes it possible to ensure the safety of the elderly person living alone and manage their health condition comprehensively.

[0583] "Elderly people living alone" refers to elderly people who live alone and do not live with others on a daily basis.

[0584] "Sensor means" refers to devices for collecting data such as temperature, movement, heart rate, etc.

[0585] The term "terminal means" refers to a device that temporarily stores data collected from the sensor means and transmits the data to the server at regular intervals.

[0586] "Analysis means" refers to an algorithm or program that analyzes data received by the server and detects abnormalities.

[0587] "Notification means" refers to a method or system for sending an alert to the user (family member or caregiver) when an abnormality is detected.

[0588] "Report generation means" refers to the function of periodically compiling data and creating a report summarizing the health status and behavioral patterns of elderly people living alone.

[0589] "Emotion analysis means" refers to algorithms or devices that analyze the facial expressions and tone of voice of elderly people living alone and recognize their emotional state.

[0590] "Database" refers to an information accumulation system that stores collected data and allows for quick search and retrieval of required data.

[0591] "Anomaly detection algorithm" refers to a mathematical or statistical method or program that analyzes received data and detects abnormal conditions.

[0592] MODE FOR CARRYING OUT THE INVENTION

[0593] The present invention provides a system for ensuring the safety and health management of elderly people living alone. This system can monitor the behavior, health status, and emotional state of elderly people living alone. The system includes the following main hardware and software components:

[0594] Hardware

[0595] server

[0596] The server collects and analyzes data on the behavior and health status of elderly people living alone. Specifically, it stores the received data in a database and analyzes it using an anomaly detection algorithm. It also has an emotion engine that analyzes the emotional data of elderly people living alone. If an abnormality is detected, it sends an alert to the user (family member or caregiver) via a notification means.

[0597] Terminal

[0598] The terminal is installed in the home of an elderly person living alone. It collects and temporarily stores data from devices such as temperature sensors, movement sensors, and heart rate monitors. The terminal has the function of transmitting this data to a server at regular intervals (for example, every hour).

[0599] Sensors

[0600] Temperature sensor: Measures the temperature inside the room.

[0601] Movement sensor: Detects the movements of elderly people living alone and collects that data.

[0602] Heart rate monitor: Real-time monitoring of the heart rate of elderly people living alone.

[0603] Camera: Captures the facial expression of an elderly man living alone.

[0604] Microphone: Collects the tone of voice of elderly people living alone.

[0605] software

[0606] Server Software

[0607] Database: A system for storing collected data, such as an SQL database.

[0608] Anomaly detection algorithms: Mathematical and statistical methods for analyzing received data and detecting anomalies.

[0609] Emotion engine: An algorithm that analyzes facial expressions and tone of voice to recognize the emotional state of elderly people living alone.

[0610] Terminal Software

[0611] The terminal software includes a program to collect and temporarily store data from various sensors in real time and send it to a server at regular intervals. The format of the data is also checked when it is sent.

[0612] Specific examples

[0613] For example, consider the case of an 80-year-old elderly person living alone who uses this system. The elderly person's home is equipped with temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to family members or caregivers if an abnormality is detected. In addition, the emotion engine analyzes the elderly person's emotional state from facial expressions and voice, and if stress is confirmed, it sends an alert including that information. Periodically generated reports are used to comprehensively understand the elderly person's health condition and take preventive medical measures.

[0614] Prompt Sentence Examples

[0615] "An 80-year-old elderly person living alone uses a system to monitor his daily activities and health. The system includes temperature sensors, movement sensors, a heart rate monitor, a camera, and a microphone. Data collected from the device is stored on the terminal and periodically sent to a server. The server analyzes the data and notifies family members or caregivers if an abnormality is detected. An emotion engine analyzes the emotional state from facial expressions and voice, and if stress is confirmed, that information is also notified. Periodically generated reports help to understand the patient's overall health."

[0616] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0617] Step 1: Initial Setup

[0618] server:

[0619] The server performs the initial setup of the system. First, it sets up an individual profile based on basic information about the elderly person living alone and initializes the database. The profile includes information such as the normal range of heart rate and reference values ​​for behavioral patterns. Next, it loads anomaly detection algorithms and emotion analysis algorithms and checks their operation. Based on this setup, the server prepares for data analysis.

[0620] Device:

[0621] The device pairs with each device installed in the home (temperature sensor, movement sensor, heart rate monitor, camera, microphone). Once pairing is complete, the device checks whether it is ready to collect data. The device prepares to send data to the server at the set interval (usually every hour).

[0622] Step 2: Data collection and temporary storage

[0623] Device:

[0624] Each device connected to the terminal begins collecting data. The temperature sensor captures the room temperature, the movement sensor detects the elderly person's movements and records the data. The heart rate monitor monitors the heart rate in real time and collects data every second. The camera uses facial recognition technology to collect facial expression data, and the microphone records the tone of voice. This data is stored in the terminal's temporary memory.

[0625] Input and Output:

[0626] Input: Sensor data generated by the device (temperature, movement, heart rate, facial expression, voice)

[0627] Data processing: Each data is stored in temporary memory according to the terminal format.

[0628] Output: Sensor data stored in the device's temporary memory

[0629] Step 3: Send data

[0630] Device:

[0631] The terminal sends collected data to the server at set intervals (e.g., every hour). Before sending, the data is checked to see if it is missing or if the format is correct. If the data transmission is successful, the next collection interval begins.

[0632] Input and Output:

[0633] Input: Sensor data stored in temporary memory

[0634] Data processing: format check and data formatting

[0635] Output: Sensor data sent to the server

[0636] Step 4: Data analysis

[0637] server:

[0638] The server analyzes the received sensor data. It combines temperature, movement, and heart rate data to detect abnormal patterns. Facial expression and voice data are used for emotion analysis. The analysis results are stored in a database, including information on any abnormalities detected.

[0639] Input and Output:

[0640] Input: Received sensor data

[0641] Data computation: running anomaly detection and sentiment analysis algorithms

[0642] Output: Analysis results (abnormal data, emotional state)

[0643] Step 5: Anomaly detection and notification

[0644] server:

[0645] If the server detects any abnormalities as a result of the analysis, it will send a notification. Based on the type of abnormality (abnormal heart rate, length of inactivity, abnormal room temperature, etc.), it will send a notification to the user (family member or caregiver) urging them to take action. Notification methods include email, app notification, and SMS.

[0646] Input and Output:

[0647] Input: Analysis results (abnormal data)

[0648] Data processing: Notification content generation

[0649] Output: Alert notification sent to user

[0650] Step 6: Sentiment Analysis

[0651] server:

[0652] Using an emotion engine, the system analyzes facial expression and voice data to recognize the emotional state of elderly people living alone. It constantly monitors and records the analysis results in a database, instantly detecting abnormalities such as stress or anxiety. If an abnormality is detected, the system notifies the user.

[0653] Input and Output:

[0654] Input: Received facial expression data and voice data

[0655] Data computation: running sentiment analysis algorithms

[0656] Output: Emotion analysis results (stress, etc.), notification to user

[0657] Step 7: Generate scheduled reports

[0658] server:

[0659] The server aggregates and analyzes the data at regular intervals (e.g., daily, weekly, monthly) and generates a report that comprehensively summarizes the health status, behavioral patterns, and emotional state of the elderly person living alone. The report is provided to the user (family or caregiver) and used for caregiving or medical treatment.

[0660] Input and Output:

[0661] Input: Sensor data and analysis results stored in a database

[0662] Data processing: data aggregation, trend analysis, conversion to report format

[0663] Output: Regular reports provided to users

[0664] The above is the specific processing flow of this system. By explaining in detail the input, data processing, data calculation, and output at each step, the overall picture of the system can be made clearer.

[0665] (Application example 2)

[0666] 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."

[0667] In modern society, the number of elderly people living alone is increasing significantly, and ensuring their safety and health management is a major social issue. Conventional systems focus on monitoring basic behavior and health status, but do not consider emotional state or mental health. As a result, psychological stress and loneliness increase, which increases health risks.

[0668] 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 sensor means for collecting data to monitor the behavior of elderly people living alone, information processing means for temporarily storing the collected data and transmitting it to the server at regular intervals, server means for analyzing the received data and detecting abnormalities, warning means for issuing a notification when an abnormality is detected, information generation means for periodically generating reports and providing them to the user, and emotion analysis means for analyzing facial expressions and voice to recognize emotional states. This makes it possible to comprehensively manage the safety and health of elderly people living alone and reduce psychological stress and loneliness.

[0669] The "sensor means" is a device for collecting data on the behavior and health status of elderly people living alone.

[0670] "Information processing means" refers to a device or software that temporarily stores collected data and transmits it to a server at regular intervals.

[0671] The "server means" is a central management system that analyzes received data and detects abnormalities.

[0672] The "alert issuing means" is a device or software that sends an alert to the user when an abnormality is detected.

[0673] An "information generating means" is a device or software that periodically generates reports and provides them to a user.

[0674] "Emotion analysis means" refers to a device or software that analyzes facial expressions and voice and recognizes emotional states.

[0675] This invention is a security and healthcare system aimed at ensuring the safety and health management of elderly people living alone. This system makes it possible to monitor behavior and manage health conditions, as well as grasp emotional states. Specific embodiments are described below.

[0676] server

[0677] The server plays a central role in collecting and analyzing data sent from the sensor means and information processing means installed in the homes of elderly people living alone. The server has the following functions:

[0678] 1. Data reception and storage: The server receives the temperature, movement, heart rate, camera images, and audio data sent from the device and stores them in a database.

[0679] 2. Data Analysis: The server analyzes the stored data and runs algorithms to detect anomalies, including emotion analysis, which analyzes facial expressions and voice data to understand the user's emotional state.

[0680] 3. Abnormality notification: If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via an alert notification method, such as email, app notification, or SMS.

[0681] 4. Report generation: The server periodically analyzes the data and generates a report including the health status, behavioral patterns, and emotional state of the elderly living alone, and provides it to the user.

[0682] Terminal

[0683] The terminal temporarily stores the data collected from the sensor means and transmits it to the server at regular intervals. The terminal has the following functions.

[0684] 1. Data Collection: Collect data in real time from temperature sensors, movement sensors, heart rate monitors, and cameras.

[0685] 2. Data transmission: Collected data is temporarily stored and periodically transmitted to the server.

[0686] User

[0687] Users (family members or caregivers) can receive notifications from the server and monitor the condition of the elderly living alone in real time. They can also get a comprehensive understanding of the elderly's health and emotional state through periodically generated reports.

[0688] Hardware and Software

[0689] Hardware: Camera, microphone, temperature sensor, movement sensor, heart rate monitor

[0690] Software: Data analysis software (including anomaly detection algorithms), emotion analysis software (e.g., OpenCV and voice analysis software)

[0691] Specific examples of processing

[0692] For example, the home of an 80-year-old elderly person living alone is equipped with temperature sensors, movement sensors, a heart rate monitor, a camera, and a microphone. Data collected from these devices is sent to the terminal and then sent to a server every hour. The server analyzes the data and sends a notification to the user if an abnormality is detected. It also identifies the user's emotional state through analysis of facial expressions and voice, and sends a notification if stress or anxiety is detected. Periodically generated reports detail changes in health status and emotions, allowing the user to take prompt action at home or in a nursing home.

[0693] Prompt Sentence Examples

[0694] "Please generate a notification message for the family when an 80-year-old person living alone experiences a sudden increase in heart rate, but their behavioral patterns are normal. Please also include a response message if facial expression analysis indicates anxiety."

[0695] In this way, the present invention provides a comprehensive system for supporting elderly people living alone to lead safe and healthy lives.

[0696] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0697] Step 1:

[0698] The device collects data from sensors. Specifically, it acquires data in real time from temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. The input is data from each sensor, which is temporarily stored. The output is data stored in the device.

[0699] Step 2:

[0700] The terminal sends the collected data to the server at a predetermined time interval (for example, every hour). The input is the data saved in step 1, and a data format is created to send it to the server. The output is the data sent to the server.

[0701] Step 3:

[0702] The server stores the data received from the terminal in the database. The input is the data sent from the terminal and stores it in the database in the specified format. The output is the data successfully stored in the database.

[0703] Step 4:

[0704] The server analyzes the stored data and detects anomalies. Specifically, it analyzes temperature, movement, and heart rate data, as well as emotion analysis from camera and audio data. The input is the data stored in the database, and it runs anomaly detection algorithms and emotion analysis algorithms. The output is the analysis results.

[0705] Step 5:

[0706] If an anomaly is detected, the server notifies the user via an alerting mechanism. The input is the analysis result from step 4, and a notification is generated only if an anomaly is identified. The output is a notification to the user (email, app notification, SMS).

[0707] Step 6:

[0708] The server periodically generates reports that include the health status, behavioral patterns, and emotional states of elderly people living alone. The input is the data stored in the database and the analysis results, which are then automatically generated as a formatted report. The output is a report that is provided to the user.

[0709] Step 7:

[0710] The user receives reports provided by the server and understands the condition of the elderly person living alone. If an abnormality is notified, the user responds promptly. The input is the notification and report sent from the server, and the user considers countermeasures based on this. The output is the implementation of the countermeasures.

[0711] This processing flow enables the system to comprehensively manage the health and safety of elderly people living alone and respond quickly when necessary.

[0712] 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.

[0713] 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.

[0714] 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.

[0715] [Third embodiment]

[0716] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0717] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0718] 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).

[0719] 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.

[0720] 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.

[0721] 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).

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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."

[0728] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[0729] server

[0730] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to the user (family member or caregiver) via the notification means. The server also periodically analyzes the data and creates reports using the report generation means.

[0731] Terminal

[0732] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensor, movement sensor, heart rate monitor). The collected data is temporarily stored in the terminal, and is then transmitted to the server, for example, every hour.

[0733] User

[0734] The user (elderly person living alone) does not need to operate the device themselves; they simply go about their daily life as normal. The user (family or caregiver) can receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[0735] Program processing overview

[0736] Initial Setup

[0737] The server sets up individual profiles for elderly people living alone and initializes the database. The terminal pairs with various devices and verifies that the devices are working properly.

[0738] Data collection and transmission

[0739] Devices collect data from the daily lives of elderly people living alone. For example, temperature sensors, movement sensors, and heart rate monitors send their respective data to a terminal. The terminal temporarily stores this data and periodically sends it to a server.

[0740] Data analysis and anomaly detection

[0741] The server analyzes the received data in real time and detects any abnormalities. If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via a notification means. The type of abnormality is identified, and the user is notified of countermeasures based on that information.

[0742] Generate scheduled reports

[0743] The server periodically generates a report summarizing the health status and behavioral patterns of the elderly person living alone. The report is provided to the user, who can share it with caregivers and medical professionals to manage the health of the elderly person living alone.

[0744] Specific examples

[0745] For example, consider the case of an 80-year-old elderly person living alone who is using this system. Temperature sensors, movement sensors, and heart rate monitors are installed in the elderly person's home. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. Upon receiving the data, the server immediately analyzes it and sends a notification to the elderly person's family or caregiver if an abnormality is detected. In addition, periodically generated reports can provide a comprehensive understanding of the elderly person's health condition and can be used to take preventive medical measures.

[0746] In this way, the present invention provides a system that supports elderly people living alone to lead safe and healthy lives.

[0747] The processing flow will be explained below.

[0748] Step 1:

[0749] Users install various sensors, cameras, and wearable devices in the homes of elderly people living alone, including temperature sensors, movement sensors, and heart rate monitors.

[0750] Step 2:

[0751] The terminal pairs with the installed devices and checks the operation of each device, confirming that they are connected properly and making them ready to collect data.

[0752] Step 3:

[0753] The terminal receives real-time data collected from devices, such as indoor temperature data from a temperature sensor, movement patterns of elderly people living alone from a movement sensor, and heart rate data from a heart rate monitor.

[0754] Step 4:

[0755] The device temporarily stores the collected data, which is then set to be sent to the server periodically (e.g., every hour).

[0756] Step 5:

[0757] The server receives the data sent from the device, which is then stored in a database for later analysis.

[0758] Step 6:

[0759] The server analyzes the received data in real time using anomaly detection algorithms, for example, to check whether the heart rate of an elderly person living alone is outside the normal range or if there are any abnormalities in their movement patterns.

[0760] Step 7:

[0761] The server generates an alert if an abnormality is detected. A notification is generated containing the details of the abnormality (e.g., heart rate is too high, the user has not moved for a long time, etc.).

[0762] Step 8:

[0763] The server sends an alert to the user (family member or caregiver) via a notification method, which can be in the form of email, app notification, SMS, etc.

[0764] Step 9:

[0765] The user (family member or caregiver) receives the notification from the server and responds promptly. They check the content of the notification and take necessary measures, such as contacting the elderly person living alone or heading to the scene.

[0766] Step 10:

[0767] The server periodically (e.g., weekly or monthly) collects and analyzes data and generates reports based on the collected data. The reports summarize the health status and behavioral patterns of elderly people living alone, and also include a history of abnormal occurrences.

[0768] Step 11:

[0769] The server provides the generated report to the user (family or caregiver), who can share the report with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[0770] Example 1

[0771] 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."

[0772] Ensuring the safety and health management of elderly people living alone is an important issue in modern society. Because many elderly people live alone, a rapid response is required in the event of a sudden change in their physical condition or an accident. However, it is difficult to continuously monitor their health status and behavioral patterns on a daily basis, and there is a lack of systems that provide appropriate notifications in the event of an abnormality. To address these issues, the present invention aims to provide a system that monitors the behavior and health status of elderly people living alone in real time and immediately issues an alert in the event of an abnormality.

[0773] 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.

[0774] In this invention, the server includes a sensor means, a terminal means, a data analysis means, a warning means, a report generation means, a setting means, and a pairing means. This makes it possible to monitor the behavior and health status of elderly people living alone in real time and analyze the collected data at regular intervals. Furthermore, if an abnormality is detected, a notification is sent to the user immediately, and periodic reports can be generated and provided, thereby enabling efficient safety and health management of elderly people living alone.

[0775] The "sensor means" is a device that collects data to monitor the behavior and health condition of elderly people living alone, and specifically includes a temperature sensor, a movement sensor, a heart rate monitor, and the like.

[0776] The "terminal means" is a device that temporarily stores collected data and transmits it to a data processing device at regular intervals.

[0777] "Data analysis means" is a combination of software and hardware for analyzing data received by the server and detecting abnormalities.

[0778] "Warning means" refers to the means for sending a notification when an abnormality is detected, and specifically includes email, app notification, SMS, etc.

[0779] The "report generating means" is a means for periodically generating a report based on the health condition and behavior patterns of an elderly person living alone and providing the report to a user.

[0780] The "setting means" is a means for setting the initial settings of the server and individual profiles of elderly people living alone, and for initializing the database.

[0781] The "pairing means" is a means for connecting various sensor means and terminal means so that they can communicate with each other, and for confirming that the devices are operating normally.

[0782] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[0783] server

[0784] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with anomaly detection algorithms using libraries such as Python, Pandas, and NumPy, and if an abnormality is detected, it promptly sends an alert to family members or caregivers via notification means. The server also periodically analyzes the data and generates reports using Microsoft Power BI or Tableau.

[0785] Terminal

[0786] The terminal temporarily stores data from various sensor means. The terminal is installed in the home of an elderly person living alone and collects data in real time from temperature sensors, movement sensors, heart rate monitors, etc. For example, it uses a Bluetooth stack to pair with the device and checks that it is working properly. The collected data is temporarily stored in the terminal and sent to the server at regular intervals (for example, every hour). HTTP or MQTT is used as the communication protocol.

[0787] User

[0788] The user (elderly person living alone) simply lives their daily life as normal and does not need to operate the device themselves. Family members or caregivers can also receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[0789] Specific examples

[0790] For example, consider the case of an 80-year-old elderly person living alone who is using this system. Temperature sensors, movement sensors, and heart rate monitors are installed in the elderly person's home. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. When the server receives the data, it immediately analyzes it and sends a notification to the family or caregiver if an abnormality is detected. In addition, the periodically generated reports can provide a comprehensive understanding of the elderly person's health condition and can be used to take preventive medical measures.

[0791] An example prompt is:

[0792] "Describe a data analysis system that helps an 80-year-old person living alone live a safe and healthy life. Please explain in detail the entire process from data collection, storage, analysis, and notification, as well as the relevant hardware and software."

[0793] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0794] Step 1: Initial Setup

[0795] The server inputs basic information about the elderly person living alone and sets up an individual profile. Specifically, it registers data such as name, age, health status, and emergency contact information in the database and initializes the system. Next, it sets information about various sensor means (temperature sensors, movement sensors, heart rate monitors, etc.) and defines the role and characteristics of each.

[0796] Input: Basic information of elderly people living alone, information on sensor means

[0797] Output: Individual profiles registered in the database, initialized system settings

[0798] Step 2: Pairing devices

[0799] The device pairs with various sensor means and verifies that they are working properly. Using the Bluetooth stack, the device is configured to receive data from each sensor. This prepares the device to collect data in real time.

[0800] Input: Sensor connection information

[0801] Output: Pairing successful, communication established between device and sensor

[0802] Step 3: Data collection

[0803] The device collects data from the daily life of elderly people living alone through various sensor means (temperature sensor, movement sensor, heart rate monitor). Specifically, the temperature sensor measures the room temperature, the movement sensor detects the elderly person's movements, and the heart rate monitor measures the heart rate.

[0804] Input: Real-time data from various sensor means

[0805] Output: Sensor data temporarily stored on the device

[0806] Step 4: Temporarily save data

[0807] The device temporarily stores the collected data in its internal storage, where it is saved as a CSV or JSON file for further processing.

[0808] Input: Collected sensor data

[0809] Output: Data file saved in internal storage

[0810] Step 5: Send data periodically

[0811] The device sends the stored data to the server at regular intervals (for example, every hour). The communication protocol is HTTP or MQTT, and the data is sent in JSON or Protobuf format.

[0812] Input: Data files stored in internal storage

[0813] Output: Data sent to the server

[0814] Step 6: Data analysis

[0815] The server analyzes the received data in real time, preprocessing the data and extracting features using libraries such as Python, Pandas, and NumPy, and applying anomaly detection algorithms to detect anomalies using generative AI models.

[0816] Input: Sensor data sent from the device

[0817] Output: Analysis results, whether anomalies were detected

[0818] Step 7: Anomaly detection and notification

[0819] If the server detects an abnormality through analysis, it will promptly send an alert to family members or caregivers via notification methods (email, app notification, SMS, etc.) that include the type of abnormality and recommended actions to take.

[0820] Input: Analysis results, whether anomalies were detected

[0821] Output: Alert notification sent to family members or caregivers

[0822] Step 8: Generate scheduled reports

[0823] The server periodically analyzes the health status and behavioral patterns of elderly people living alone and generates reports using Microsoft Power BI and Tableau, which are presented in a visually easy-to-understand format.

[0824] Input: Analyzed health and behavioral data

[0825] Output: Generated scheduled reports

[0826] Step 9: Provide to users

[0827] The server provides the generated reports to family members and caregivers, and the reports are delivered in PDF format or as a web application for easy viewing by users.

[0828] Input: Generated Scheduled Report

[0829] Output: Report provided to family and caregivers

[0830] (Application example 1)

[0831] 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."

[0832] In modern society, the safety and health management of elderly people living alone are important issues. In particular, it is necessary to ensure the safety of elderly people living alone when they go out, and to constantly and accurately monitor their health status and respond quickly and effectively if an abnormality is detected. Furthermore, conventional systems do not adequately guarantee the safety of elderly people living alone while they are traveling, and there is also the issue of a lack of reliable means of managing their safety when they are out.

[0833] 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.

[0834] In this invention, the server includes a system that adds a device means for monitoring the behavior and health status of elderly people living alone, a terminal means for temporarily storing collected data and sending it to the server at regular intervals, a server means for analyzing the received data and detecting abnormalities, a notification means for issuing a notification when an abnormality is detected, a report generation means for periodically generating reports and providing them to the user, and a means for adjusting the operation of the autonomous vehicle and notifying medical institutions and designated contacts when an abnormality is detected. This makes it possible to improve the safety of elderly people living alone and manage their safety when they are out and about.

[0835] "Elderly people living alone" refers to elderly people who live alone.

[0836] "Devices and means for monitoring behavior and health status" refers to sensors and devices used to monitor the daily behavior and health status of elderly people living alone.

[0837] "Terminal means" refers to a device that temporarily stores data collected from device means and transmits it to a server at regular intervals.

[0838] "Server means" refers to a central management device or system that analyzes received data and detects abnormalities.

[0839] "Notification means" refers to a mechanism for issuing a notification when an abnormality is detected.

[0840] "Report generation means" refers to a mechanism that periodically analyzes data, generates reports, and provides them to users.

[0841] "Means for adjusting the operation of self-driving vehicles" refers to a system for controlling the operation status of self-driving vehicles and ensuring the safety of elderly people living alone.

[0842] "Means of notifying medical institutions and designated contacts" refers to a system for sending emergency notifications to medical institutions and pre-designated contacts when an abnormality occurs.

[0843] A "temperature sensor" refers to a device that measures the ambient temperature and transmits that data to a terminal.

[0844] A "movement sensor" refers to a device that detects the movement of an object and transmits that data to a terminal.

[0845] A "heart rate monitor" refers to a device that measures heart rate and transmits that data to a terminal.

[0846] "Smart glasses" refers to eyeglass-type devices that enhance the wearer's visual information or provide additional data.

[0847] "Head-mounted display" refers to a display device used to present digital information to the wearer's field of vision.

[0848] "Email" refers to a means of sending and receiving messages electronically over the Internet.

[0849] "App notifications" refers to the means by which applications notify users of messages or information on smartphones and other devices.

[0850] "SMS" refers to the service of sending and receiving short text messages over a mobile phone network.

[0851] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[0852] server

[0853] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to family members or caregivers via a notification means. The server also periodically analyzes the data and creates reports using a report generation means. The main software used includes anomaly detection algorithms such as TensorFlow and PyTorch, and database management using SQL / RDS.

[0854] Terminal

[0855] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensors, movement sensors, heart rate monitors) as well as smart glasses and head-mounted displays. The collected data is temporarily stored in the terminal and then transmitted to the server, for example, every hour.

[0856] User

[0857] The user (elderly person living alone) does not need to operate the device in their daily life. The user (family member or caregiver) also receives notifications sent from the system and can respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, and these can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone. If an abnormality is detected, the system also includes means to adjust the operation of the autonomous vehicle and notify medical institutions and designated contacts.

[0858] Specific examples

[0859] For example, consider the case of an 80-year-old man living alone who uses this system. His home is equipped with temperature sensors, movement sensors, a heart rate monitor, smart glasses, and a head-mounted display. These devices monitor the man's daily activities and health in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to his family or caregiver if an abnormality is detected. The system also has the function of coordinating the operation of the autonomous vehicle and making emergency calls to medical institutions if necessary. Periodically generated reports help family members, caregivers, and medical professionals understand the man's overall health and take preventive medical measures.

[0860] Example prompts to be input to the generative AI model

[0861] Please explain how the "health monitoring system" ensures the safety and health of elderly people living alone. In particular, please include a detailed process flow for the anomaly detection algorithm and periodic report generation, as well as the names of the specific hardware and software used. For example, please also provide details of what kind of notification is sent when an anomaly is detected.

[0862] Such prompts can be used to elicit detailed and specific responses from the AI ​​model.

[0863] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0864] Step 1: Initial setup of device means

[0865] A temperature sensor, movement sensor, heart rate monitor, smart glasses, and head-mounted display are installed in the home of the user (elderly person living alone). This prepares the device means to monitor the behavior and health of the elderly person living alone. The input is the device installation and setting data, and the output is confirmation of normal operation. Specifically, each device is tested to see if it is operating normally.

[0866] Step 2: Data collection

[0867] The device means collects data on the daily activities and health status of elderly people living alone from temperature sensors, movement sensors, heart rate monitors, smart glasses, and head-mounted displays. The input is real-time data from each sensor, and the output is data temporarily stored in the terminal means. Specifically, each sensor periodically transmits data to the terminal.

[0868] Step 3: Send data

[0869] The terminal means transmits the collected data to the server at regular intervals (for example, every hour). The input is the temporarily stored data, and the output is the data transmitted to the server. Specifically, the terminal transmits the stored data in packets at regular intervals to the server.

[0870] Step 4: Data analysis and anomaly detection

[0871] The server receives data sent from the device and analyzes it in real time. Anomalies are detected using an anomaly detection algorithm (e.g., TensorFlow or PyTorch). The input is the data sent to the server, and the output is the anomaly detection results. Specifically, the server inputs the received data into the anomaly detection algorithm and obtains the analysis results.

[0872] Step 5: Notification

[0873] If an abnormality is detected, the server sends a notification to family members or caregivers via a notification method, which can include email, app notification, SMS, or emergency calls to medical institutions. The input is the abnormality detection result, and the output is a notification message. Specifically, the server selects the appropriate notification method, generates a notification message, and sends it.

[0874] Step 6: Coordinating autonomous vehicle operations

[0875] If an abnormality is detected, the operation of the autonomous vehicle is adjusted. For example, if an abnormality is detected while an elderly person living alone is out, the vehicle's speed can be adjusted or the vehicle can be set to automatically head to the nearest medical facility. The input is the abnormality detection result, and the output is an operation command for the autonomous vehicle. Specifically, the server sends a command to the vehicle's operation system.

[0876] Step 7: Generate and deliver scheduled reports

[0877] The server periodically generates a report summarizing the health status and behavioral patterns of elderly people living alone and provides it to the user (family or caregiver). This is done using a report generation means. The input is analyzed past data, and the output is the generated report. Specifically, the server retrieves past data from the database, performs statistical processing, and generates a report.

[0878] Prompt Sentence Examples

[0879] Please explain how the "health monitoring system" ensures the safety and health of elderly people living alone. In particular, please include a detailed process flow for the anomaly detection algorithm and periodic report generation, as well as the names of the specific hardware and software used. For example, please also provide details of what kind of notification is sent when an anomaly is detected.

[0880] 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.

[0881] The present invention is a system that aims to ensure the safety and health management of elderly people living alone by combining an emotion engine with the system, which can also grasp their emotional state and take appropriate measures. It includes the following components.

[0882] server

[0883] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to the user (family member or caregiver) via a notification means. The server also periodically analyzes the data and creates reports using a report generation means. In addition, it is equipped with an emotion engine that also analyzes the user's emotional data.

[0884] Terminal

[0885] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensor, movement sensor, heart rate monitor). The collected data is temporarily stored in the terminal, and is then transmitted to the server, for example, every hour.

[0886] Emotion Engine

[0887] The emotion engine has the ability to recognize the emotional state of elderly people living alone by analyzing their facial expressions, tone of voice, and behavioral patterns. For example, it uses a camera and microphone to collect and analyze facial and voice data. It also uses data from temperature and movement sensors to achieve more accurate emotion recognition.

[0888] User

[0889] The user (elderly person living alone) does not need to operate the device themselves; they simply go about their daily life as normal. The user (family or caregiver) can receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[0890] Program processing overview

[0891] Initial Setup

[0892] The server sets up individual profiles for elderly people living alone and initializes the database. The terminal pairs with various devices and verifies that they are working properly. The emotion engine is also configured in the same way, and collects basic data to record the facial expressions and voices of elderly people living alone.

[0893] Data collection and transmission

[0894] Devices collect data from the daily lives of elderly people living alone. For example, temperature sensors, movement sensors, and heart rate monitors send their respective data to the terminal. The emotion engine uses a camera and microphone to collect the elderly person's facial expressions and tone of voice and analyzes their emotions. The terminal temporarily stores this data and periodically sends it to a server.

[0895] Data analysis and anomaly detection

[0896] The server analyzes the received data in real time and detects any abnormalities. It also analyzes data from the emotion engine, and if any changes in emotions or stress levels are confirmed, these are also included in the notification content. If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via the notification means. The type of abnormality is identified, and the user is notified of countermeasures based on this.

[0897] Generate scheduled reports

[0898] The server periodically generates a report summarizing the health status and behavioral patterns of elderly people living alone. It also includes the results of emotion analysis, allowing for a comprehensive understanding of the elderly person's mental health. The report is provided to the user, who can share it with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[0899] Specific examples

[0900] For example, consider the case of an 80-year-old elderly person living alone who is using this system. The elderly person's home is equipped with temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to family members or caregivers if an abnormality is detected. In addition, the emotion engine analyzes the elderly person's emotional state from facial expressions and voice, and if the elderly person is feeling stressed, it sends an alert including that information. Periodically generated reports provide a comprehensive understanding of the elderly person's health condition and are used to take preventive medical measures.

[0901] In this way, the present invention provides a system that supports elderly people living alone to lead safe and healthy lives.

[0902] The processing flow will be explained below.

[0903] Step 1:

[0904] The user installs various sensors, cameras, microphones, and wearable devices in the homes of elderly people living alone, including temperature sensors, movement sensors, heart rate monitors, cameras, and microphones.

[0905] Step 2:

[0906] The terminal pairs with each installed device and checks the operation of each device, confirming that they are connected properly and making them ready to collect data.

[0907] Step 3:

[0908] The terminal receives data from each device in real time. Specific examples of data collected from a specific device include indoor temperature from a temperature sensor, movement patterns of elderly people living alone from a movement sensor, heart rate from a heart rate monitor, facial expressions from a camera, and tone of voice from a microphone.

[0909] Step 4:

[0910] The terminal temporarily stores the collected data and transmits it to the server at regular intervals (for example, every hour).

[0911] Step 5:

[0912] The server receives the data sent from the device, which is then stored in a database for later analysis.

[0913] Step 6:

[0914] The server analyzes the received data in real time using anomaly detection algorithms to check, for example, whether an elderly person living alone has an abnormal heart rate or an abnormal movement pattern.

[0915] Step 7:

[0916] The server uses an emotion engine to analyze the emotional state of the elderly person living alone. Based on data collected from the camera and microphone, it evaluates facial expressions and tone of voice to determine whether the elderly person is under stress.

[0917] Step 8:

[0918] If an abnormality is detected, the server generates an alert containing the details of the abnormality (e.g., heart rate is too high, no movement for a long time, high stress, etc.).

[0919] Step 9:

[0920] The server sends an alert to the user (family member or caregiver) via a notification method, which can be in the form of email, app notification, SMS, etc.

[0921] Step 10:

[0922] The user (family member or caregiver) receives the notification from the server and responds promptly. They check the content of the notification and take necessary measures, such as contacting the elderly person living alone or heading to the scene.

[0923] Step 11:

[0924] The server periodically (e.g., weekly or monthly) collects and analyzes data and generates reports based on the collected data. The reports summarize the health status, behavioral patterns, and emotional states of elderly people living alone, and also include a history of abnormal occurrences.

[0925] Step 12:

[0926] The server provides the generated report to the user (family or caregiver), who can share the report with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[0927] Example 2

[0928] 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."

[0929] In modern society, the number of elderly people living alone is increasing, making their safety and health management a major issue. Elderly people living alone are particularly at high risk of getting into dangerous situations, and delaying appropriate responses can lead to serious consequences. Furthermore, while mental health is important in addition to physical health, there are very limited means of remotely monitoring it. A system that can resolve these issues and manage the safety and health of elderly people living alone more comprehensively and quickly is needed.

[0930] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a sensor means for collecting data on the behavior and health condition of the elderly person living alone, a terminal means for temporarily storing the collected data and transmitting it to the server at regular intervals, an analysis means for analyzing the received data and detecting abnormalities, a notification means for issuing a notification when an abnormality is detected, a report generation means for periodically generating reports and providing them to the user, and an emotion analysis means for analyzing the emotional state of the elderly person living alone. This makes it possible to ensure the safety of the elderly person living alone and manage their health condition comprehensively.

[0931] "Elderly people living alone" refers to elderly people who live alone and do not live with others on a daily basis.

[0932] "Sensor means" refers to devices for collecting data such as temperature, movement, heart rate, etc.

[0933] The term "terminal means" refers to a device that temporarily stores data collected from the sensor means and transmits the data to the server at regular intervals.

[0934] "Analysis means" refers to an algorithm or program that analyzes data received by the server and detects abnormalities.

[0935] "Notification means" refers to a method or system for sending an alert to the user (family member or caregiver) when an abnormality is detected.

[0936] "Report generation means" refers to the function of periodically compiling data and creating a report summarizing the health status and behavioral patterns of elderly people living alone.

[0937] "Emotion analysis means" refers to algorithms or devices that analyze the facial expressions and tone of voice of elderly people living alone and recognize their emotional state.

[0938] "Database" refers to an information accumulation system that stores collected data and allows for quick search and retrieval of required data.

[0939] "Anomaly detection algorithm" refers to a mathematical or statistical method or program that analyzes received data and detects abnormal conditions.

[0940] MODE FOR CARRYING OUT THE INVENTION

[0941] The present invention provides a system for ensuring the safety and health management of elderly people living alone. This system can monitor the behavior, health status, and emotional state of elderly people living alone. The system includes the following main hardware and software components:

[0942] Hardware

[0943] server

[0944] The server collects and analyzes data on the behavior and health status of elderly people living alone. Specifically, it stores the received data in a database and analyzes it using an anomaly detection algorithm. It also has an emotion engine that analyzes the emotional data of elderly people living alone. If an abnormality is detected, it sends an alert to the user (family member or caregiver) via a notification means.

[0945] Terminal

[0946] The terminal is installed in the home of an elderly person living alone. It collects and temporarily stores data from devices such as temperature sensors, movement sensors, and heart rate monitors. The terminal has the function of transmitting this data to a server at regular intervals (for example, every hour).

[0947] Sensors

[0948] Temperature sensor: Measures the temperature inside the room.

[0949] Movement sensor: Detects the movements of elderly people living alone and collects that data.

[0950] Heart rate monitor: Real-time monitoring of the heart rate of elderly people living alone.

[0951] Camera: Captures the facial expression of an elderly man living alone.

[0952] Microphone: Collects the tone of voice of elderly people living alone.

[0953] software

[0954] Server Software

[0955] Database: A system for storing collected data, such as an SQL database.

[0956] Anomaly detection algorithms: Mathematical and statistical methods for analyzing received data and detecting anomalies.

[0957] Emotion engine: An algorithm that analyzes facial expressions and tone of voice to recognize the emotional state of elderly people living alone.

[0958] Terminal Software

[0959] The terminal software includes a program to collect and temporarily store data from various sensors in real time and send it to a server at regular intervals. The format of the data is also checked when it is sent.

[0960] Specific examples

[0961] For example, consider the case of an 80-year-old elderly person living alone who uses this system. The elderly person's home is equipped with temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to family members or caregivers if an abnormality is detected. In addition, the emotion engine analyzes the elderly person's emotional state from facial expressions and voice, and if stress is confirmed, it sends an alert including that information. Periodically generated reports are used to comprehensively understand the elderly person's health condition and take preventive medical measures.

[0962] Prompt Sentence Examples

[0963] "An 80-year-old elderly person living alone uses a system to monitor his daily activities and health. The system includes temperature sensors, movement sensors, a heart rate monitor, a camera, and a microphone. Data collected from the device is stored on the terminal and periodically sent to a server. The server analyzes the data and notifies family members or caregivers if an abnormality is detected. An emotion engine analyzes the emotional state from facial expressions and voice, and if stress is confirmed, that information is also notified. Periodically generated reports help to understand the patient's overall health."

[0964] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0965] Step 1: Initial Setup

[0966] server:

[0967] The server performs the initial setup of the system. First, it sets up an individual profile based on basic information about the elderly person living alone and initializes the database. The profile includes information such as the normal range of heart rate and reference values ​​for behavioral patterns. Next, it loads anomaly detection algorithms and emotion analysis algorithms and checks their operation. Based on this setup, the server prepares for data analysis.

[0968] Device:

[0969] The device pairs with each device installed in the home (temperature sensor, movement sensor, heart rate monitor, camera, microphone). Once pairing is complete, the device checks whether it is ready to collect data. The device prepares to send data to the server at the set interval (usually every hour).

[0970] Step 2: Data collection and temporary storage

[0971] Device:

[0972] Each device connected to the terminal begins collecting data. The temperature sensor captures the room temperature, the movement sensor detects the elderly person's movements and records the data. The heart rate monitor monitors the heart rate in real time and collects data every second. The camera uses facial recognition technology to collect facial expression data, and the microphone records the tone of voice. This data is stored in the terminal's temporary memory.

[0973] Input and Output:

[0974] Input: Sensor data generated by the device (temperature, movement, heart rate, facial expression, voice)

[0975] Data processing: Each data is stored in temporary memory according to the terminal format.

[0976] Output: Sensor data stored in the device's temporary memory

[0977] Step 3: Send data

[0978] Device:

[0979] The terminal sends collected data to the server at set intervals (e.g., every hour). Before sending, the data is checked to see if it is missing or if the format is correct. If the data transmission is successful, the next collection interval begins.

[0980] Input and Output:

[0981] Input: Sensor data stored in temporary memory

[0982] Data processing: format check and data formatting

[0983] Output: Sensor data sent to the server

[0984] Step 4: Data analysis

[0985] server:

[0986] The server analyzes the received sensor data. It combines temperature, movement, and heart rate data to detect abnormal patterns. Facial expression and voice data are used for emotion analysis. The analysis results are stored in a database, including information on any abnormalities detected.

[0987] Input and Output:

[0988] Input: Received sensor data

[0989] Data computation: running anomaly detection and sentiment analysis algorithms

[0990] Output: Analysis results (abnormal data, emotional state)

[0991] Step 5: Anomaly detection and notification

[0992] server:

[0993] If the server detects any abnormalities as a result of the analysis, it will send a notification. Based on the type of abnormality (abnormal heart rate, length of inactivity, abnormal room temperature, etc.), it will send a notification to the user (family member or caregiver) urging them to take action. Notification methods include email, app notification, and SMS.

[0994] Input and Output:

[0995] Input: Analysis results (abnormal data)

[0996] Data processing: Notification content generation

[0997] Output: Alert notification sent to user

[0998] Step 6: Sentiment Analysis

[0999] server:

[1000] Using an emotion engine, the system analyzes facial expression and voice data to recognize the emotional state of elderly people living alone. It constantly monitors and records the analysis results in a database, instantly detecting abnormalities such as stress or anxiety. If an abnormality is detected, the system notifies the user.

[1001] Input and Output:

[1002] Input: Received facial expression data and voice data

[1003] Data computation: running sentiment analysis algorithms

[1004] Output: Emotion analysis results (stress, etc.), notification to user

[1005] Step 7: Generate scheduled reports

[1006] server:

[1007] The server aggregates and analyzes the data at regular intervals (e.g., daily, weekly, monthly) and generates a report that comprehensively summarizes the health status, behavioral patterns, and emotional state of the elderly person living alone. The report is provided to the user (family or caregiver) and used for caregiving or medical treatment.

[1008] Input and Output:

[1009] Input: Sensor data and analysis results stored in a database

[1010] Data processing: data aggregation, trend analysis, conversion to report format

[1011] Output: Regular reports provided to users

[1012] The above is the specific processing flow of this system. By explaining in detail the input, data processing, data calculation, and output at each step, the overall picture of the system can be made clearer.

[1013] (Application example 2)

[1014] 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."

[1015] In modern society, the number of elderly people living alone is increasing significantly, and ensuring their safety and health management is a major social issue. Conventional systems focus on monitoring basic behavior and health status, but do not consider emotional state or mental health. As a result, psychological stress and loneliness increase, which increases health risks.

[1016] 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 sensor means for collecting data to monitor the behavior of elderly people living alone, information processing means for temporarily storing the collected data and transmitting it to the server at regular intervals, server means for analyzing the received data and detecting abnormalities, warning means for issuing a notification when an abnormality is detected, information generation means for periodically generating reports and providing them to the user, and emotion analysis means for analyzing facial expressions and voice to recognize emotional states. This makes it possible to comprehensively manage the safety and health of elderly people living alone and reduce psychological stress and loneliness.

[1017] The "sensor means" is a device for collecting data on the behavior and health status of elderly people living alone.

[1018] "Information processing means" refers to a device or software that temporarily stores collected data and transmits it to a server at regular intervals.

[1019] The "server means" is a central management system that analyzes received data and detects abnormalities.

[1020] The "alert issuing means" is a device or software that sends an alert to the user when an abnormality is detected.

[1021] An "information generating means" is a device or software that periodically generates reports and provides them to a user.

[1022] "Emotion analysis means" refers to a device or software that analyzes facial expressions and voice and recognizes emotional states.

[1023] This invention is a security and healthcare system aimed at ensuring the safety and health management of elderly people living alone. This system makes it possible to monitor behavior and manage health conditions, as well as grasp emotional states. Specific embodiments are described below.

[1024] server

[1025] The server plays a central role in collecting and analyzing data sent from the sensor means and information processing means installed in the homes of elderly people living alone. The server has the following functions:

[1026] 1. Data reception and storage: The server receives the temperature, movement, heart rate, camera images, and audio data sent from the device and stores them in a database.

[1027] 2. Data Analysis: The server analyzes the stored data and runs algorithms to detect anomalies, including emotion analysis, which analyzes facial expressions and voice data to understand the user's emotional state.

[1028] 3. Abnormality notification: If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via an alert notification method, such as email, app notification, or SMS.

[1029] 4. Report generation: The server periodically analyzes the data and generates a report including the health status, behavioral patterns, and emotional state of the elderly living alone, and provides it to the user.

[1030] Terminal

[1031] The terminal temporarily stores the data collected from the sensor means and transmits it to the server at regular intervals. The terminal has the following functions.

[1032] 1. Data Collection: Collect data in real time from temperature sensors, movement sensors, heart rate monitors, and cameras.

[1033] 2. Data transmission: Collected data is temporarily stored and periodically transmitted to the server.

[1034] User

[1035] Users (family members or caregivers) can receive notifications from the server and monitor the condition of the elderly living alone in real time. They can also get a comprehensive understanding of the elderly's health and emotional state through periodically generated reports.

[1036] Hardware and Software

[1037] Hardware: Camera, microphone, temperature sensor, movement sensor, heart rate monitor

[1038] Software: Data analysis software (including anomaly detection algorithms), emotion analysis software (e.g., OpenCV and voice analysis software)

[1039] Specific examples of processing

[1040] For example, the home of an 80-year-old elderly person living alone is equipped with temperature sensors, movement sensors, a heart rate monitor, a camera, and a microphone. Data collected from these devices is sent to the terminal and then sent to a server every hour. The server analyzes the data and sends a notification to the user if an abnormality is detected. It also identifies the user's emotional state through analysis of facial expressions and voice, and sends a notification if stress or anxiety is detected. Periodically generated reports detail changes in health status and emotions, allowing the user to take prompt action at home or in a nursing home.

[1041] Prompt Sentence Examples

[1042] "Please generate a notification message for the family when an 80-year-old person living alone experiences a sudden increase in heart rate, but their behavioral patterns are normal. Please also include a response message if facial expression analysis indicates anxiety."

[1043] In this way, the present invention provides a comprehensive system for supporting elderly people living alone to lead safe and healthy lives.

[1044] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1045] Step 1:

[1046] The device collects data from sensors. Specifically, it acquires data in real time from temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. The input is data from each sensor, which is temporarily stored. The output is data stored in the device.

[1047] Step 2:

[1048] The terminal sends the collected data to the server at a predetermined time interval (for example, every hour). The input is the data saved in step 1, and a data format is created to send it to the server. The output is the data sent to the server.

[1049] Step 3:

[1050] The server stores the data received from the terminal in the database. The input is the data sent from the terminal and stores it in the database in the specified format. The output is the data successfully stored in the database.

[1051] Step 4:

[1052] The server analyzes the stored data and detects anomalies. Specifically, it analyzes temperature, movement, and heart rate data, as well as emotion analysis from camera and audio data. The input is the data stored in the database, and it runs anomaly detection algorithms and emotion analysis algorithms. The output is the analysis results.

[1053] Step 5:

[1054] If an anomaly is detected, the server notifies the user via an alerting mechanism. The input is the analysis result from step 4, and a notification is generated only if an anomaly is identified. The output is a notification to the user (email, app notification, SMS).

[1055] Step 6:

[1056] The server periodically generates reports that include the health status, behavioral patterns, and emotional states of elderly people living alone. The input is the data stored in the database and the analysis results, which are then automatically generated as a formatted report. The output is a report that is provided to the user.

[1057] Step 7:

[1058] The user receives reports provided by the server and understands the condition of the elderly person living alone. If an abnormality is notified, the user responds promptly. The input is the notification and report sent from the server, and the user considers countermeasures based on this. The output is the implementation of the countermeasures.

[1059] This processing flow enables the system to comprehensively manage the health and safety of elderly people living alone and respond quickly when necessary.

[1060] 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.

[1061] 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.

[1062] 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.

[1063] [Fourth embodiment]

[1064] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1065] 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.

[1066] 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).

[1067] 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.

[1068] 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.

[1069] 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).

[1070] 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.

[1071] 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.

[1072] 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.

[1073] 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.

[1074] 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.

[1075] 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.

[1076] 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."

[1077] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[1078] server

[1079] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to the user (family member or caregiver) via the notification means. The server also periodically analyzes the data and creates reports using the report generation means.

[1080] Terminal

[1081] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensor, movement sensor, heart rate monitor). The collected data is temporarily stored in the terminal, and is then transmitted to the server, for example, every hour.

[1082] User

[1083] The user (elderly person living alone) does not need to operate the device themselves; they simply go about their daily life as normal. The user (family or caregiver) can receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[1084] Program processing overview

[1085] Initial Setup

[1086] The server sets up individual profiles for elderly people living alone and initializes the database. The terminal pairs with various devices and verifies that the devices are working properly.

[1087] Data collection and transmission

[1088] Devices collect data from the daily lives of elderly people living alone. For example, temperature sensors, movement sensors, and heart rate monitors send their respective data to a terminal. The terminal temporarily stores this data and periodically sends it to a server.

[1089] Data analysis and anomaly detection

[1090] The server analyzes the received data in real time and detects any abnormalities. If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via a notification means. The type of abnormality is identified, and the user is notified of countermeasures based on that information.

[1091] Generate scheduled reports

[1092] The server periodically generates a report summarizing the health status and behavioral patterns of the elderly person living alone. The report is provided to the user, who can share it with caregivers and medical professionals to manage the health of the elderly person living alone.

[1093] Specific examples

[1094] For example, consider the case of an 80-year-old elderly person living alone who is using this system. Temperature sensors, movement sensors, and heart rate monitors are installed in the elderly person's home. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. Upon receiving the data, the server immediately analyzes it and sends a notification to the elderly person's family or caregiver if an abnormality is detected. In addition, periodically generated reports can provide a comprehensive understanding of the elderly person's health condition and can be used to take preventive medical measures.

[1095] In this way, the present invention provides a system that supports elderly people living alone to lead safe and healthy lives.

[1096] The processing flow will be explained below.

[1097] Step 1:

[1098] Users install various sensors, cameras, and wearable devices in the homes of elderly people living alone, including temperature sensors, movement sensors, and heart rate monitors.

[1099] Step 2:

[1100] The terminal pairs with the installed devices and checks the operation of each device, confirming that they are connected properly and making them ready to collect data.

[1101] Step 3:

[1102] The terminal receives real-time data collected from devices, such as indoor temperature data from a temperature sensor, movement patterns of elderly people living alone from a movement sensor, and heart rate data from a heart rate monitor.

[1103] Step 4:

[1104] The device temporarily stores the collected data, which is then set to be sent to the server periodically (e.g., every hour).

[1105] Step 5:

[1106] The server receives the data sent from the device, which is then stored in a database for later analysis.

[1107] Step 6:

[1108] The server analyzes the received data in real time using anomaly detection algorithms, for example, to check whether the heart rate of an elderly person living alone is outside the normal range or if there are any abnormalities in their movement patterns.

[1109] Step 7:

[1110] The server generates an alert if an abnormality is detected. A notification is generated containing the details of the abnormality (e.g., heart rate is too high, the user has not moved for a long time, etc.).

[1111] Step 8:

[1112] The server sends an alert to the user (family member or caregiver) via a notification method, which can be in the form of email, app notification, SMS, etc.

[1113] Step 9:

[1114] The user (family member or caregiver) receives the notification from the server and responds promptly. They check the content of the notification and take necessary measures, such as contacting the elderly person living alone or heading to the scene.

[1115] Step 10:

[1116] The server periodically (e.g., weekly or monthly) collects and analyzes data and generates reports based on the collected data. The reports summarize the health status and behavioral patterns of elderly people living alone, and also include a history of abnormal occurrences.

[1117] Step 11:

[1118] The server provides the generated report to the user (family or caregiver), who can share the report with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[1119] Example 1

[1120] 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."

[1121] Ensuring the safety and health management of elderly people living alone is an important issue in modern society. Because many elderly people live alone, a rapid response is required in the event of a sudden change in their physical condition or an accident. However, it is difficult to continuously monitor their health status and behavioral patterns on a daily basis, and there is a lack of systems that provide appropriate notifications in the event of an abnormality. To address these issues, the present invention aims to provide a system that monitors the behavior and health status of elderly people living alone in real time and immediately issues an alert in the event of an abnormality.

[1122] 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.

[1123] In this invention, the server includes a sensor means, a terminal means, a data analysis means, a warning means, a report generation means, a setting means, and a pairing means. This makes it possible to monitor the behavior and health status of elderly people living alone in real time and analyze the collected data at regular intervals. Furthermore, if an abnormality is detected, a notification is sent to the user immediately, and periodic reports can be generated and provided, thereby enabling efficient safety and health management of elderly people living alone.

[1124] The "sensor means" is a device that collects data to monitor the behavior and health condition of elderly people living alone, and specifically includes a temperature sensor, a movement sensor, a heart rate monitor, and the like.

[1125] The "terminal means" is a device that temporarily stores collected data and transmits it to a data processing device at regular intervals.

[1126] "Data analysis means" is a combination of software and hardware for analyzing data received by the server and detecting abnormalities.

[1127] "Warning means" refers to the means for sending a notification when an abnormality is detected, and specifically includes email, app notification, SMS, etc.

[1128] The "report generating means" is a means for periodically generating a report based on the health condition and behavior patterns of an elderly person living alone and providing the report to a user.

[1129] The "setting means" is a means for setting the initial settings of the server and individual profiles of elderly people living alone, and for initializing the database.

[1130] The "pairing means" is a means for connecting various sensor means and terminal means so that they can communicate with each other, and for confirming that the devices are operating normally.

[1131] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[1132] server

[1133] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with anomaly detection algorithms using libraries such as Python, Pandas, and NumPy, and if an abnormality is detected, it promptly sends an alert to family members or caregivers via notification means. The server also periodically analyzes the data and generates reports using Microsoft Power BI or Tableau.

[1134] Terminal

[1135] The terminal temporarily stores data from various sensor means. The terminal is installed in the home of an elderly person living alone and collects data in real time from temperature sensors, movement sensors, heart rate monitors, etc. For example, it uses a Bluetooth stack to pair with the device and checks that it is working properly. The collected data is temporarily stored in the terminal and sent to the server at regular intervals (for example, every hour). HTTP or MQTT is used as the communication protocol.

[1136] User

[1137] The user (elderly person living alone) simply lives their daily life as normal and does not need to operate the device themselves. Family members or caregivers can also receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[1138] Specific examples

[1139] For example, consider the case of an 80-year-old elderly person living alone who is using this system. Temperature sensors, movement sensors, and heart rate monitors are installed in the elderly person's home. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. When the server receives the data, it immediately analyzes it and sends a notification to the family or caregiver if an abnormality is detected. In addition, the periodically generated reports can provide a comprehensive understanding of the elderly person's health condition and can be used to take preventive medical measures.

[1140] An example prompt is:

[1141] "Describe a data analysis system that helps an 80-year-old person living alone live a safe and healthy life. Please explain in detail the entire process from data collection, storage, analysis, and notification, as well as the relevant hardware and software."

[1142] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1143] Step 1: Initial Setup

[1144] The server inputs basic information about the elderly person living alone and sets up an individual profile. Specifically, it registers data such as name, age, health status, and emergency contact information in the database and initializes the system. Next, it sets information about various sensor means (temperature sensors, movement sensors, heart rate monitors, etc.) and defines the role and characteristics of each.

[1145] Input: Basic information of elderly people living alone, information on sensor means

[1146] Output: Individual profiles registered in the database, initialized system settings

[1147] Step 2: Pairing devices

[1148] The device pairs with various sensor means and verifies that they are working properly. Using the Bluetooth stack, the device is configured to receive data from each sensor. This prepares the device to collect data in real time.

[1149] Input: Sensor connection information

[1150] Output: Pairing successful, communication established between device and sensor

[1151] Step 3: Data collection

[1152] The device collects data from the daily life of elderly people living alone through various sensor means (temperature sensor, movement sensor, heart rate monitor). Specifically, the temperature sensor measures the room temperature, the movement sensor detects the elderly person's movements, and the heart rate monitor measures the heart rate.

[1153] Input: Real-time data from various sensor means

[1154] Output: Sensor data temporarily stored on the device

[1155] Step 4: Temporarily save data

[1156] The device temporarily stores the collected data in its internal storage, where it is saved as a CSV or JSON file for further processing.

[1157] Input: Collected sensor data

[1158] Output: Data file saved in internal storage

[1159] Step 5: Send data periodically

[1160] The device sends the stored data to the server at regular intervals (for example, every hour). The communication protocol is HTTP or MQTT, and the data is sent in JSON or Protobuf format.

[1161] Input: Data files stored in internal storage

[1162] Output: Data sent to the server

[1163] Step 6: Data analysis

[1164] The server analyzes the received data in real time, preprocessing the data and extracting features using libraries such as Python, Pandas, and NumPy, and applying anomaly detection algorithms to detect anomalies using generative AI models.

[1165] Input: Sensor data sent from the device

[1166] Output: Analysis results, whether anomalies were detected

[1167] Step 7: Anomaly detection and notification

[1168] If the server detects an abnormality through analysis, it will promptly send an alert to family members or caregivers via notification methods (email, app notification, SMS, etc.) that include the type of abnormality and recommended actions to take.

[1169] Input: Analysis results, whether anomalies were detected

[1170] Output: Alert notification sent to family members or caregivers

[1171] Step 8: Generate scheduled reports

[1172] The server periodically analyzes the health status and behavioral patterns of elderly people living alone and generates reports using Microsoft Power BI and Tableau, which are presented in a visually easy-to-understand format.

[1173] Input: Analyzed health and behavioral data

[1174] Output: Generated scheduled reports

[1175] Step 9: Provide to users

[1176] The server provides the generated reports to family members and caregivers, and the reports are delivered in PDF format or as a web application for easy viewing by users.

[1177] Input: Generated Scheduled Report

[1178] Output: Report provided to family and caregivers

[1179] (Application example 1)

[1180] 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."

[1181] In modern society, the safety and health management of elderly people living alone are important issues. In particular, it is necessary to ensure the safety of elderly people living alone when they go out, and to constantly and accurately monitor their health status and respond quickly and effectively if an abnormality is detected. Furthermore, conventional systems do not adequately guarantee the safety of elderly people living alone while they are traveling, and there is also the issue of a lack of reliable means of managing their safety when they are out.

[1182] 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.

[1183] In this invention, the server includes a system that adds a device means for monitoring the behavior and health status of elderly people living alone, a terminal means for temporarily storing collected data and sending it to the server at regular intervals, a server means for analyzing the received data and detecting abnormalities, a notification means for issuing a notification when an abnormality is detected, a report generation means for periodically generating reports and providing them to the user, and a means for adjusting the operation of the autonomous vehicle and notifying medical institutions and designated contacts when an abnormality is detected. This makes it possible to improve the safety of elderly people living alone and manage their safety when they are out and about.

[1184] "Elderly people living alone" refers to elderly people who live alone.

[1185] "Devices and means for monitoring behavior and health status" refers to sensors and devices used to monitor the daily behavior and health status of elderly people living alone.

[1186] "Terminal means" refers to a device that temporarily stores data collected from device means and transmits it to a server at regular intervals.

[1187] "Server means" refers to a central management device or system that analyzes received data and detects abnormalities.

[1188] "Notification means" refers to a mechanism for issuing a notification when an abnormality is detected.

[1189] "Report generation means" refers to a mechanism that periodically analyzes data, generates reports, and provides them to users.

[1190] "Means for adjusting the operation of self-driving vehicles" refers to a system for controlling the operation status of self-driving vehicles and ensuring the safety of elderly people living alone.

[1191] "Means of notifying medical institutions and designated contacts" refers to a system for sending emergency notifications to medical institutions and pre-designated contacts when an abnormality occurs.

[1192] A "temperature sensor" refers to a device that measures the ambient temperature and transmits that data to a terminal.

[1193] A "movement sensor" refers to a device that detects the movement of an object and transmits that data to a terminal.

[1194] A "heart rate monitor" refers to a device that measures heart rate and transmits that data to a terminal.

[1195] "Smart glasses" refers to eyeglass-type devices that enhance the wearer's visual information or provide additional data.

[1196] "Head-mounted display" refers to a display device used to present digital information to the wearer's field of vision.

[1197] "Email" refers to a means of sending and receiving messages electronically over the Internet.

[1198] "App notifications" refers to the means by which applications notify users of messages or information on smartphones and other devices.

[1199] "SMS" refers to the service of sending and receiving short text messages over a mobile phone network.

[1200] The present invention is a system for ensuring the safety and health management of elderly people living alone, and includes the following components.

[1201] server

[1202] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to family members or caregivers via a notification means. The server also periodically analyzes the data and creates reports using a report generation means. The main software used includes anomaly detection algorithms such as TensorFlow and PyTorch, and database management using SQL / RDS.

[1203] Terminal

[1204] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensors, movement sensors, heart rate monitors) as well as smart glasses and head-mounted displays. The collected data is temporarily stored in the terminal and then transmitted to the server, for example, every hour.

[1205] User

[1206] The user (elderly person living alone) does not need to operate the device in their daily life. The user (family member or caregiver) also receives notifications sent from the system and can respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, and these can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone. If an abnormality is detected, the system also includes means to adjust the operation of the autonomous vehicle and notify medical institutions and designated contacts.

[1207] Specific examples

[1208] For example, consider the case of an 80-year-old man living alone who uses this system. His home is equipped with temperature sensors, movement sensors, a heart rate monitor, smart glasses, and a head-mounted display. These devices monitor the man's daily activities and health in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to his family or caregiver if an abnormality is detected. The system also has the function of coordinating the operation of the autonomous vehicle and making emergency calls to medical institutions if necessary. Periodically generated reports help family members, caregivers, and medical professionals understand the man's overall health and take preventive medical measures.

[1209] Example prompts to be input to the generative AI model

[1210] Please explain how the "health monitoring system" ensures the safety and health of elderly people living alone. In particular, please include a detailed process flow for the anomaly detection algorithm and periodic report generation, as well as the names of the specific hardware and software used. For example, please also provide details of what kind of notification is sent when an anomaly is detected.

[1211] Such prompts can be used to elicit detailed and specific responses from the AI ​​model.

[1212] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1213] Step 1: Initial setup of device means

[1214] A temperature sensor, movement sensor, heart rate monitor, smart glasses, and head-mounted display are installed in the home of the user (elderly person living alone). This prepares the device means to monitor the behavior and health of the elderly person living alone. The input is the device installation and setting data, and the output is confirmation of normal operation. Specifically, each device is tested to see if it is operating normally.

[1215] Step 2: Data collection

[1216] The device means collects data on the daily activities and health status of elderly people living alone from temperature sensors, movement sensors, heart rate monitors, smart glasses, and head-mounted displays. The input is real-time data from each sensor, and the output is data temporarily stored in the terminal means. Specifically, each sensor periodically transmits data to the terminal.

[1217] Step 3: Send data

[1218] The terminal means transmits the collected data to the server at regular intervals (for example, every hour). The input is the temporarily stored data, and the output is the data transmitted to the server. Specifically, the terminal transmits the stored data in packets at regular intervals to the server.

[1219] Step 4: Data analysis and anomaly detection

[1220] The server receives data sent from the device and analyzes it in real time. Anomalies are detected using an anomaly detection algorithm (e.g., TensorFlow or PyTorch). The input is the data sent to the server, and the output is the anomaly detection results. Specifically, the server inputs the received data into the anomaly detection algorithm and obtains the analysis results.

[1221] Step 5: Notification

[1222] If an abnormality is detected, the server sends a notification to family members or caregivers via a notification method, which can include email, app notification, SMS, or emergency calls to medical institutions. The input is the abnormality detection result, and the output is a notification message. Specifically, the server selects the appropriate notification method, generates a notification message, and sends it.

[1223] Step 6: Coordinating autonomous vehicle operations

[1224] If an abnormality is detected, the operation of the autonomous vehicle is adjusted. For example, if an abnormality is detected while an elderly person living alone is out, the vehicle's speed can be adjusted or the vehicle can be set to automatically head to the nearest medical facility. The input is the abnormality detection result, and the output is an operation command for the autonomous vehicle. Specifically, the server sends a command to the vehicle's operation system.

[1225] Step 7: Generate and deliver scheduled reports

[1226] The server periodically generates a report summarizing the health status and behavioral patterns of elderly people living alone and provides it to the user (family or caregiver). This is done using a report generation means. The input is analyzed past data, and the output is the generated report. Specifically, the server retrieves past data from the database, performs statistical processing, and generates a report.

[1227] Prompt Sentence Examples

[1228] Please explain how the "health monitoring system" ensures the safety and health of elderly people living alone. In particular, please include a detailed process flow for the anomaly detection algorithm and periodic report generation, as well as the names of the specific hardware and software used. For example, please also provide details of what kind of notification is sent when an anomaly is detected.

[1229] 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.

[1230] The present invention is a system that aims to ensure the safety and health management of elderly people living alone by combining an emotion engine with the system, which can also grasp their emotional state and take appropriate measures. It includes the following components.

[1231] server

[1232] The server plays a central role in collecting and analyzing data on the behavior and health status of elderly people living alone. Specifically, it receives data sent from the devices and stores it in a database. The server is equipped with an anomaly detection algorithm, and if an abnormality is detected, it promptly sends an alert to the user (family member or caregiver) via a notification means. The server also periodically analyzes the data and creates reports using a report generation means. In addition, it is equipped with an emotion engine that also analyzes the user's emotional data.

[1233] Terminal

[1234] The terminal temporarily stores data collected from the device means. The terminal has the function of transmitting this data to a server at regular intervals. For example, a terminal may be installed in the home of an elderly person living alone, and collect data in real time from various sensors (temperature sensor, movement sensor, heart rate monitor). The collected data is temporarily stored in the terminal, and is then transmitted to the server, for example, every hour.

[1235] Emotion Engine

[1236] The emotion engine has the ability to recognize the emotional state of elderly people living alone by analyzing their facial expressions, tone of voice, and behavioral patterns. For example, it uses a camera and microphone to collect and analyze facial and voice data. It also uses data from temperature and movement sensors to achieve more accurate emotion recognition.

[1237] User

[1238] The user (elderly person living alone) does not need to operate the device themselves; they simply go about their daily life as normal. The user (family or caregiver) can receive notifications from the system and respond quickly in the event of an abnormality. In this case, the user receives abnormality alerts via email, app notification, SMS, etc. Regular reports are also provided to the user, which can be shared with caregivers and medical professionals to manage the condition of the elderly person living alone.

[1239] Program processing overview

[1240] Initial Setup

[1241] The server sets up individual profiles for elderly people living alone and initializes the database. The terminal pairs with various devices and verifies that they are working properly. The emotion engine is also configured in the same way, and collects basic data to record the facial expressions and voices of elderly people living alone.

[1242] Data collection and transmission

[1243] Devices collect data from the daily lives of elderly people living alone. For example, temperature sensors, movement sensors, and heart rate monitors send their respective data to the terminal. The emotion engine uses a camera and microphone to collect the elderly person's facial expressions and tone of voice and analyzes their emotions. The terminal temporarily stores this data and periodically sends it to a server.

[1244] Data analysis and anomaly detection

[1245] The server analyzes the received data in real time and detects any abnormalities. It also analyzes data from the emotion engine, and if any changes in emotions or stress levels are confirmed, these are also included in the notification content. If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via the notification means. The type of abnormality is identified, and the user is notified of countermeasures based on this.

[1246] Generate scheduled reports

[1247] The server periodically generates a report summarizing the health status and behavioral patterns of elderly people living alone. It also includes the results of emotion analysis, allowing for a comprehensive understanding of the elderly person's mental health. The report is provided to the user, who can share it with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[1248] Specific examples

[1249] For example, consider the case of an 80-year-old elderly person living alone who is using this system. The elderly person's home is equipped with temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to family members or caregivers if an abnormality is detected. In addition, the emotion engine analyzes the elderly person's emotional state from facial expressions and voice, and if the elderly person is feeling stressed, it sends an alert including that information. Periodically generated reports provide a comprehensive understanding of the elderly person's health condition and are used to take preventive medical measures.

[1250] In this way, the present invention provides a system that supports elderly people living alone to lead safe and healthy lives.

[1251] The processing flow will be explained below.

[1252] Step 1:

[1253] The user installs various sensors, cameras, microphones, and wearable devices in the homes of elderly people living alone, including temperature sensors, movement sensors, heart rate monitors, cameras, and microphones.

[1254] Step 2:

[1255] The terminal pairs with each installed device and checks the operation of each device, confirming that they are connected properly and making them ready to collect data.

[1256] Step 3:

[1257] The terminal receives data from each device in real time. Specific examples of data collected from a specific device include indoor temperature from a temperature sensor, movement patterns of elderly people living alone from a movement sensor, heart rate from a heart rate monitor, facial expressions from a camera, and tone of voice from a microphone.

[1258] Step 4:

[1259] The terminal temporarily stores the collected data and transmits it to the server at regular intervals (for example, every hour).

[1260] Step 5:

[1261] The server receives the data sent from the device, which is then stored in a database for later analysis.

[1262] Step 6:

[1263] The server analyzes the received data in real time using anomaly detection algorithms to check, for example, whether an elderly person living alone has an abnormal heart rate or an abnormal movement pattern.

[1264] Step 7:

[1265] The server uses an emotion engine to analyze the emotional state of the elderly person living alone. Based on data collected from the camera and microphone, it evaluates facial expressions and tone of voice to determine whether the elderly person is under stress.

[1266] Step 8:

[1267] If an abnormality is detected, the server generates an alert containing the details of the abnormality (e.g., heart rate is too high, no movement for a long time, high stress, etc.).

[1268] Step 9:

[1269] The server sends an alert to the user (family member or caregiver) via a notification method, which can be in the form of email, app notification, SMS, etc.

[1270] Step 10:

[1271] The user (family member or caregiver) receives the notification from the server and responds promptly. They check the content of the notification and take necessary measures, such as contacting the elderly person living alone or heading to the scene.

[1272] Step 11:

[1273] The server periodically (e.g., weekly or monthly) collects and analyzes data and generates reports based on the collected data. The reports summarize the health status, behavioral patterns, and emotional states of elderly people living alone, and also include a history of abnormal occurrences.

[1274] Step 12:

[1275] The server provides the generated report to the user (family or caregiver), who can share the report with caregivers and medical professionals to comprehensively manage the condition of the elderly person living alone.

[1276] Example 2

[1277] 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."

[1278] In modern society, the number of elderly people living alone is increasing, making their safety and health management a major issue. Elderly people living alone are particularly at high risk of getting into dangerous situations, and delaying appropriate responses can lead to serious consequences. Furthermore, while mental health is important in addition to physical health, there are very limited means of remotely monitoring it. A system that can resolve these issues and manage the safety and health of elderly people living alone more comprehensively and quickly is needed.

[1279] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a sensor means for collecting data on the behavior and health condition of the elderly person living alone, a terminal means for temporarily storing the collected data and transmitting it to the server at regular intervals, an analysis means for analyzing the received data and detecting abnormalities, a notification means for issuing a notification when an abnormality is detected, a report generation means for periodically generating reports and providing them to the user, and an emotion analysis means for analyzing the emotional state of the elderly person living alone. This makes it possible to ensure the safety of the elderly person living alone and manage their health condition comprehensively.

[1280] "Elderly people living alone" refers to elderly people who live alone and do not live with others on a daily basis.

[1281] "Sensor means" refers to devices for collecting data such as temperature, movement, heart rate, etc.

[1282] The term "terminal means" refers to a device that temporarily stores data collected from the sensor means and transmits the data to the server at regular intervals.

[1283] "Analysis means" refers to an algorithm or program that analyzes data received by the server and detects abnormalities.

[1284] "Notification means" refers to a method or system for sending an alert to the user (family member or caregiver) when an abnormality is detected.

[1285] "Report generation means" refers to the function of periodically compiling data and creating a report summarizing the health status and behavioral patterns of elderly people living alone.

[1286] "Emotion analysis means" refers to algorithms or devices that analyze the facial expressions and tone of voice of elderly people living alone and recognize their emotional state.

[1287] "Database" refers to an information accumulation system that stores collected data and allows for quick search and retrieval of required data.

[1288] "Anomaly detection algorithm" refers to a mathematical or statistical method or program that analyzes received data and detects abnormal conditions.

[1289] MODE FOR CARRYING OUT THE INVENTION

[1290] The present invention provides a system for ensuring the safety and health management of elderly people living alone. This system can monitor the behavior, health status, and emotional state of elderly people living alone. The system includes the following main hardware and software components:

[1291] Hardware

[1292] server

[1293] The server collects and analyzes data on the behavior and health status of elderly people living alone. Specifically, it stores the received data in a database and analyzes it using an anomaly detection algorithm. It also has an emotion engine that analyzes the emotional data of elderly people living alone. If an abnormality is detected, it sends an alert to the user (family member or caregiver) via a notification means.

[1294] Terminal

[1295] The terminal is installed in the home of an elderly person living alone. It collects and temporarily stores data from devices such as temperature sensors, movement sensors, and heart rate monitors. The terminal has the function of transmitting this data to a server at regular intervals (for example, every hour).

[1296] Sensors

[1297] Temperature sensor: Measures the temperature inside the room.

[1298] Movement sensor: Detects the movements of elderly people living alone and collects that data.

[1299] Heart rate monitor: Real-time monitoring of the heart rate of elderly people living alone.

[1300] Camera: Captures the facial expression of an elderly man living alone.

[1301] Microphone: Collects the tone of voice of elderly people living alone.

[1302] software

[1303] Server Software

[1304] Database: A system for storing collected data, such as an SQL database.

[1305] Anomaly detection algorithms: Mathematical and statistical methods for analyzing received data and detecting anomalies.

[1306] Emotion engine: An algorithm that analyzes facial expressions and tone of voice to recognize the emotional state of elderly people living alone.

[1307] Terminal Software

[1308] The terminal software includes a program to collect and temporarily store data from various sensors in real time and send it to a server at regular intervals. The format of the data is also checked when it is sent.

[1309] Specific examples

[1310] For example, consider the case of an 80-year-old elderly person living alone who uses this system. The elderly person's home is equipped with temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. These devices monitor the elderly person's daily behavior and health condition in real time and send the data to a terminal. The terminal temporarily stores the data and sends it to the server every hour. The server immediately analyzes the data upon receiving it and sends a notification to family members or caregivers if an abnormality is detected. In addition, the emotion engine analyzes the elderly person's emotional state from facial expressions and voice, and if stress is confirmed, it sends an alert including that information. Periodically generated reports are used to comprehensively understand the elderly person's health condition and take preventive medical measures.

[1311] Prompt Sentence Examples

[1312] "An 80-year-old elderly person living alone uses a system to monitor his daily activities and health. The system includes temperature sensors, movement sensors, a heart rate monitor, a camera, and a microphone. Data collected from the device is stored on the terminal and periodically sent to a server. The server analyzes the data and notifies family members or caregivers if an abnormality is detected. An emotion engine analyzes the emotional state from facial expressions and voice, and if stress is confirmed, that information is also notified. Periodically generated reports help to understand the patient's overall health."

[1313] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1314] Step 1: Initial Setup

[1315] server:

[1316] The server performs the initial setup of the system. First, it sets up an individual profile based on basic information about the elderly person living alone and initializes the database. The profile includes information such as the normal range of heart rate and reference values ​​for behavioral patterns. Next, it loads anomaly detection algorithms and emotion analysis algorithms and checks their operation. Based on this setup, the server prepares for data analysis.

[1317] Device:

[1318] The device pairs with each device installed in the home (temperature sensor, movement sensor, heart rate monitor, camera, microphone). Once pairing is complete, the device checks whether it is ready to collect data. The device prepares to send data to the server at the set interval (usually every hour).

[1319] Step 2: Data collection and temporary storage

[1320] Device:

[1321] Each device connected to the terminal begins collecting data. The temperature sensor captures the room temperature, the movement sensor detects the elderly person's movements and records the data. The heart rate monitor monitors the heart rate in real time and collects data every second. The camera uses facial recognition technology to collect facial expression data, and the microphone records the tone of voice. This data is stored in the terminal's temporary memory.

[1322] Input and Output:

[1323] Input: Sensor data generated by the device (temperature, movement, heart rate, facial expression, voice)

[1324] Data processing: Each data is stored in temporary memory according to the terminal format.

[1325] Output: Sensor data stored in the device's temporary memory

[1326] Step 3: Send data

[1327] Device:

[1328] The terminal sends collected data to the server at set intervals (e.g., every hour). Before sending, the data is checked to see if it is missing or if the format is correct. If the data transmission is successful, the next collection interval begins.

[1329] Input and Output:

[1330] Input: Sensor data stored in temporary memory

[1331] Data processing: format check and data formatting

[1332] Output: Sensor data sent to the server

[1333] Step 4: Data analysis

[1334] server:

[1335] The server analyzes the received sensor data. It combines temperature, movement, and heart rate data to detect abnormal patterns. Facial expression and voice data are used for emotion analysis. The analysis results are stored in a database, including information on any abnormalities detected.

[1336] Input and Output:

[1337] Input: Received sensor data

[1338] Data computation: running anomaly detection and sentiment analysis algorithms

[1339] Output: Analysis results (abnormal data, emotional state)

[1340] Step 5: Anomaly detection and notification

[1341] server:

[1342] If the server detects any abnormalities as a result of the analysis, it will send a notification. Based on the type of abnormality (abnormal heart rate, length of inactivity, abnormal room temperature, etc.), it will send a notification to the user (family member or caregiver) urging them to take action. Notification methods include email, app notification, and SMS.

[1343] Input and Output:

[1344] Input: Analysis results (abnormal data)

[1345] Data processing: Notification content generation

[1346] Output: Alert notification sent to user

[1347] Step 6: Sentiment Analysis

[1348] server:

[1349] Using an emotion engine, the system analyzes facial expression and voice data to recognize the emotional state of elderly people living alone. It constantly monitors and records the analysis results in a database, instantly detecting abnormalities such as stress or anxiety. If an abnormality is detected, the system notifies the user.

[1350] Input and Output:

[1351] Input: Received facial expression data and voice data

[1352] Data computation: running sentiment analysis algorithms

[1353] Output: Emotion analysis results (stress, etc.), notification to user

[1354] Step 7: Generate scheduled reports

[1355] server:

[1356] The server aggregates and analyzes the data at regular intervals (e.g., daily, weekly, monthly) and generates a report that comprehensively summarizes the health status, behavioral patterns, and emotional state of the elderly person living alone. The report is provided to the user (family or caregiver) and used for caregiving or medical treatment.

[1357] Input and Output:

[1358] Input: Sensor data and analysis results stored in a database

[1359] Data processing: data aggregation, trend analysis, conversion to report format

[1360] Output: Regular reports provided to users

[1361] The above is the specific processing flow of this system. By explaining in detail the input, data processing, data calculation, and output at each step, the overall picture of the system can be made clearer.

[1362] (Application example 2)

[1363] 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."

[1364] In modern society, the number of elderly people living alone is increasing significantly, and ensuring their safety and health management is a major social issue. Conventional systems focus on monitoring basic behavior and health status, but do not consider emotional state or mental health. As a result, psychological stress and loneliness increase, which increases health risks.

[1365] 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 sensor means for collecting data to monitor the behavior of elderly people living alone, information processing means for temporarily storing the collected data and transmitting it to the server at regular intervals, server means for analyzing the received data and detecting abnormalities, warning means for issuing a notification when an abnormality is detected, information generation means for periodically generating reports and providing them to the user, and emotion analysis means for analyzing facial expressions and voice to recognize emotional states. This makes it possible to comprehensively manage the safety and health of elderly people living alone and reduce psychological stress and loneliness.

[1366] The "sensor means" is a device for collecting data on the behavior and health status of elderly people living alone.

[1367] "Information processing means" refers to a device or software that temporarily stores collected data and transmits it to a server at regular intervals.

[1368] The "server means" is a central management system that analyzes received data and detects abnormalities.

[1369] The "alert issuing means" is a device or software that sends an alert to the user when an abnormality is detected.

[1370] An "information generating means" is a device or software that periodically generates reports and provides them to a user.

[1371] "Emotion analysis means" refers to a device or software that analyzes facial expressions and voice and recognizes emotional states.

[1372] This invention is a security and healthcare system aimed at ensuring the safety and health management of elderly people living alone. This system makes it possible to monitor behavior and manage health conditions, as well as grasp emotional states. Specific embodiments are described below.

[1373] server

[1374] The server plays a central role in collecting and analyzing data sent from the sensor means and information processing means installed in the homes of elderly people living alone. The server has the following functions:

[1375] 1. Data reception and storage: The server receives the temperature, movement, heart rate, camera images, and audio data sent from the device and stores them in a database.

[1376] 2. Data Analysis: The server analyzes the stored data and runs algorithms to detect anomalies, including emotion analysis, which analyzes facial expressions and voice data to understand the user's emotional state.

[1377] 3. Abnormality notification: If an abnormality is detected, the server sends an alert to the user (family member or caregiver) via an alert notification method, such as email, app notification, or SMS.

[1378] 4. Report generation: The server periodically analyzes the data and generates a report including the health status, behavioral patterns, and emotional state of the elderly living alone, and provides it to the user.

[1379] Terminal

[1380] The terminal temporarily stores the data collected from the sensor means and transmits it to the server at regular intervals. The terminal has the following functions.

[1381] 1. Data Collection: Collect data in real time from temperature sensors, movement sensors, heart rate monitors, and cameras.

[1382] 2. Data transmission: Collected data is temporarily stored and periodically transmitted to the server.

[1383] User

[1384] Users (family members or caregivers) can receive notifications from the server and monitor the condition of the elderly living alone in real time. They can also get a comprehensive understanding of the elderly's health and emotional state through periodically generated reports.

[1385] Hardware and Software

[1386] Hardware: Camera, microphone, temperature sensor, movement sensor, heart rate monitor

[1387] Software: Data analysis software (including anomaly detection algorithms), emotion analysis software (e.g., OpenCV and voice analysis software)

[1388] Specific examples of processing

[1389] For example, the home of an 80-year-old elderly person living alone is equipped with temperature sensors, movement sensors, a heart rate monitor, a camera, and a microphone. Data collected from these devices is sent to the terminal and then sent to a server every hour. The server analyzes the data and sends a notification to the user if an abnormality is detected. It also identifies the user's emotional state through analysis of facial expressions and voice, and sends a notification if stress or anxiety is detected. Periodically generated reports detail changes in health status and emotions, allowing the user to take prompt action at home or in a nursing home.

[1390] Prompt Sentence Examples

[1391] "Please generate a notification message for the family when an 80-year-old person living alone experiences a sudden increase in heart rate, but their behavioral patterns are normal. Please also include a response message if facial expression analysis indicates anxiety."

[1392] In this way, the present invention provides a comprehensive system for supporting elderly people living alone to lead safe and healthy lives.

[1393] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1394] Step 1:

[1395] The device collects data from sensors. Specifically, it acquires data in real time from temperature sensors, movement sensors, heart rate monitors, cameras, and microphones. The input is data from each sensor, which is temporarily stored. The output is data stored in the device.

[1396] Step 2:

[1397] The terminal sends the collected data to the server at a predetermined time interval (for example, every hour). The input is the data saved in step 1, and a data format is created to send it to the server. The output is the data sent to the server.

[1398] Step 3:

[1399] The server stores the data received from the terminal in the database. The input is the data sent from the terminal and stores it in the database in the specified format. The output is the data successfully stored in the database.

[1400] Step 4:

[1401] The server analyzes the stored data and detects anomalies. Specifically, it analyzes temperature, movement, and heart rate data, as well as emotion analysis from camera and audio data. The input is the data stored in the database, and it runs anomaly detection algorithms and emotion analysis algorithms. The output is the analysis results.

[1402] Step 5:

[1403] If an anomaly is detected, the server notifies the user via an alerting mechanism. The input is the analysis result from step 4, and a notification is generated only if an anomaly is identified. The output is a notification to the user (email, app notification, SMS).

[1404] Step 6:

[1405] The server periodically generates reports that include the health status, behavioral patterns, and emotional states of elderly people living alone. The input is the data stored in the database and the analysis results, which are then automatically generated as a formatted report. The output is a report that is provided to the user.

[1406] Step 7:

[1407] The user receives reports provided by the server and understands the condition of the elderly person living alone. If an abnormality is notified, the user responds promptly. The input is the notification and report sent from the server, and the user considers countermeasures based on this. The output is the implementation of the countermeasures.

[1408] This processing flow enables the system to comprehensively manage the health and safety of elderly people living alone and respond quickly when necessary.

[1409] 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.

[1410] 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.

[1411] 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.

[1412] 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.

[1413] 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.

[1414] 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.

[1415] 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).

[1416] 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.

[1417] 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."

[1418] 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.

[1419] 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).

[1420] 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.

[1421] 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.

[1422] 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.

[1423] 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.

[1424] 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.

[1425] 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.

[1426] 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.

[1427] 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.

[1428] 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.

[1429] 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.

[1430] The following is further disclosed regarding the above embodiment.

[1431] (Claim 1)

[1432] A device means for collecting data for monitoring the behavior of an elderly person living alone;

[1433] a terminal means for temporarily storing the collected data and transmitting it to a server at regular intervals;

[1434] a server means for analyzing the received data and detecting anomalies;

[1435] a notification means for issuing a notification when an abnormality is detected;

[1436] a report generating means for periodically generating reports and providing them to a user;

[1437] A system including:

[1438] (Claim 2)

[1439] 10. The system of claim 1, wherein the device means includes one or more of a temperature sensor, a movement sensor, and a heart rate monitor.

[1440] (Claim 3)

[1441] The system of claim 1 , wherein the notification means uses one or more of email, app notification, and SMS.

[1442] "Example 1"

[1443] (Claim 1)

[1444] a sensor means for collecting data for monitoring the behavior of the elderly person living alone;

[1445] a terminal means for temporarily storing the collected data and transmitting it to a data processing device at regular intervals;

[1446] data analysis means for analyzing the received data and detecting anomalies;

[1447] an alerting means for issuing a notification when an anomaly is detected;

[1448] a report generating means for periodically generating reports and providing them to a user;

[1449] a configuration means for configuring individual profiles and initializing the database;

[1450] Pairing means for pairing with the sensor means and confirming that the device is operating normally;

[1451] A system including:

[1452] (Claim 2)

[1453] 10. The system of claim 1, wherein the sensor means includes one or more of a temperature sensor, a movement sensor, and a heart rate monitor.

[1454] (Claim 3)

[1455] 10. The system of claim 1, wherein the alerting means uses one or more of an email, an app notification, and an SMS.

[1456] "Application Example 1"

[1457] New Claims

[1458] (Claim 1)

[1459] A device means for collecting data to monitor the behavior and health status of elderly people living alone;

[1460] a terminal means for temporarily storing the collected data and transmitting it to a server at regular intervals;

[1461] a server means for analyzing the received data and detecting anomalies;

[1462] a notification means for issuing a notification when an abnormality is detected;

[1463] a report generating means for periodically generating reports and providing them to a user;

[1464] The system adds a means to adjust the operation of the self-driving vehicle and notify medical institutions and designated contacts if an abnormality is detected.

[1465] (Claim 2)

[1466] 10. The system of claim 1, wherein the device means comprises one or more of a temperature sensor, a movement sensor, a heart rate monitor, smart glasses, and a head-mounted display.

[1467] (Claim 3)

[1468] The system of claim 1 , wherein the notification means uses one or more of email, app notification, SMS, and emergency call to a medical institution.

[1469] "Example 2: Combining Emotion Engines"

[1470] (Claim 1)

[1471] a sensor means for collecting data on the behavior and health status of elderly people living alone;

[1472] a terminal means for temporarily storing the collected data and transmitting it to a server at regular intervals;

[1473] an analysis means for analyzing the received data and detecting anomalies;

[1474] a notification means for issuing a notification when an abnormality is detected;

[1475] a report generating means for periodically generating reports and providing them to a user;

[1476] an emotion analysis means for analyzing the emotional state of an elderly person living alone;

[1477] A system including:

[1478] (Claim 2)

[1479] 10. The system of claim 1, wherein the sensor means includes one or more of a temperature sensor, a movement sensor, and a heart rate monitor.

[1480] (Claim 3)

[1481] The system of claim 1 , wherein the notification means uses one or more of email, app notification, and SMS.

[1482] "Application example 2 when combining emotion engines"

[1483] (Claim 1)

[1484] a sensor means for collecting data for monitoring the behavior of the elderly person living alone;

[1485] an information processing means for temporarily storing the collected data and transmitting it to a server at regular intervals;

[1486] a server means for analyzing the received data and detecting anomalies;

[1487] an alarm issuing means for issuing a notification when an abnormality is detected;

[1488] an information generating means for periodically generating reports and providing them to a user;

[1489] An emotion analysis means for recognizing an emotional state by analyzing facial expressions and voice;

[1490] A system including:

[1491] (Claim 2)

[1492] 10. The system of claim 1, wherein the sensor means includes one or more of a temperature sensor, a movement sensor, a heart rate monitor, and a camera.

[1493] (Claim 3)

[1494] 2. The system of claim 1, wherein the alerting means uses one or more of an email, an app notification, and an SMS. [Explanation of symbols]

[1495] 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 device means for collecting data for monitoring the behavior of an elderly person living alone; a terminal means for temporarily storing the collected data and transmitting it to a server at regular intervals; a server means for analyzing the received data and detecting anomalies; a notification means for issuing a notification when an abnormality is detected; a report generating means for periodically generating reports and providing them to a user; A system including:

2. The system of claim 1 , wherein the device means includes one or more of a temperature sensor, a movement sensor, and a heart rate monitor.

3. The system of claim 1 , wherein the notification means uses one or more of email, app notification, and SMS.

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