system

Abstract

Provide a system. A remote monitoring system for monitoring the health status of elderly people, comprising: a terminal means for acquiring health data; means for transmitting the acquired health data to a server; a server means for receiving and storing the transmitted health data; An AI module means for analyzing the received health data and detecting abnormal values; a means for sending an emergency notification when an abnormality is detected based on the analysis results; A means for notifying the normal state based on the analysis result; A system including:

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 modern society, the number of elderly people living alone is increasing, creating a need for continuous remote monitoring of their health. However, conventional remote monitoring systems are limited to simple data collection and routine notifications, and lack the functionality to immediately detect abnormalities or provide specific support for specific actions. Furthermore, they do not provide assistance with purchasing items necessary for daily life, resulting in insufficient comprehensive lifestyle support. Therefore, the present invention aims to efficiently monitor the health status of elderly people, provide immediate notification of abnormalities, and provide appropriate support for actions, thereby improving the convenience of daily life. [Means for solving the problem]

[0005] The present invention solves the aforementioned problems by the following means. A remote monitoring system for monitoring the health status of elderly people includes a terminal means for acquiring health data, a means for transmitting the acquired health data to a server, a server means for receiving and storing the transmitted health data, an AI module means for analyzing the received health data and detecting abnormal values, a means for sending an emergency notification if an abnormality is detected based on the analysis results, and a means for notifying the user of a normal condition based on the analysis results. The system also includes a means for sending a notification from the server means and displaying an emergency alert to the user if an abnormality based on the health data is detected. The system further includes a means for receiving purchase requests from users and generating and transmitting appropriate product provision links. These means enable comprehensive monitoring and lifestyle support for elderly people.

[0006] "Terminal means" refers to the device used to acquire health data and the associated application, including, for example, a smartphone or wearable device.

[0007] "Server means" refers to a computer system for receiving, storing, and analyzing data sent from terminal means.

[0008] "Health data" refers to biometric information that indicates the health status of an elderly person, such as body temperature, blood pressure, and heart rate.

[0009] "AI module means" refers to artificial intelligence software for analyzing health data and performing outlier detection and pattern recognition.

[0010] "Emergency notification" refers to a communication means that sends a prompt warning to the user when the AI ​​module means detects an abnormal value.

[0011] The "means for notifying normal status" refers to a communication means for notifying the user of the status when the analysis result is normal.

[0012] A "purchase request" refers to the act of a user informing the system that they need a particular item.

[0013] "Product Offering Link" refers to a web link for purchasing an item that is suggested based on a user's purchase request. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention provides a remote monitoring system that monitors the health status of elderly people, detects abnormalities, and provides support for purchasing items necessary for daily life. Specific embodiments of the system will be described below.

[0036] Health Data Collection and Transmission

[0037] Health data collection

[0038] 1. The device (smartphone or wearable device) periodically collects health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors.

[0039] 2. Health data includes body temperature, blood pressure, heart rate, etc.

[0040] Sending data

[0041] 1. The device sends the collected health data to the server at regular intervals (e.g., every hour).

[0042] 2. Data transmission is carried out using secure and fast communication protocols.

[0043] Data analysis and notification

[0044] Receiving and storing data

[0045] 1. The server receives the health data sent from the device and stores it in a database.

[0046] Data analysis

[0047] 1. The server passes the received health data to the AI ​​module.

[0048] 2. The AI ​​module analyzes the data to see if there are any abnormal values ​​or patterns, comparing them with past data.

[0049] Sending notifications

[0050] 1. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately."

[0051] 2. If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning is 36.5 degrees, which is normal."

[0052] Purchase assistance

[0053] Receiving product requests

[0054] 1. The user or elderly person sends a request for an item necessary for daily life using the LINE app. Example: "I need toilet paper."

[0055] Handling the request

[0056] 1. The server receives the request message from the user, analyzes it, and identifies the required product.

[0057] 2. The server searches for information about the relevant product using the Yahoo Shopping API.

[0058] Generate and send the link

[0059] 1. The server generates appropriate product offer links from the search results.

[0060] 2. The server sends the generated link to the user via LINE message. Example: "You can buy toilet paper here [LINK]".

[0061] Specific examples

[0062] Health Data Monitoring

[0063] At 7:00 a.m., the device acquires blood pressure data and sends it to the server. The server passes the data to the AI ​​module for analysis. If the analysis results are normal, a LINE notification is sent stating, "Mom's blood pressure this morning is 120 / 80, which is normal." If an abnormality is detected, a notification is sent stating, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0064] Assisted Buy execution

[0065] A user sends a message on LINE saying, "I need toilet paper." The server receives and analyzes the message, searches for the relevant product using the Yahoo Shopping API, generates a link, and replies, "You can buy toilet paper here [link]."

[0066] This system will enable efficient monitoring of the health status of the elderly, enable immediate response to emergencies, and improve the convenience of their daily lives.

[0067] The processing flow will be explained below.

[0068] Health data collection and analysis

[0069] Health data collection

[0070] Step 1:

[0071] The device acquires health data from linked healthcare devices (e.g., thermometers and blood pressure monitors).

[0072] Step 2:

[0073] The device transmits the acquired health data to the server at regular intervals (for example, every hour).

[0074] Data analysis

[0075] Step 3:

[0076] The server receives the health data sent from the device and stores it in a database.

[0077] Step 4:

[0078] The server passes the stored health data to an AI module for analysis.

[0079] Step 5:

[0080] The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[0081] Sending notifications

[0082] Step 6:

[0083] The server generates an emergency notification if an anomaly is detected based on the analysis results of the AI ​​module.

[0084] Step 7:

[0085] The server sends the generated emergency notification to the user (family member) via the LINE app.

[0086] For example: "Urgent! Dad's heart rate is over 160. Please check immediately."

[0087] Step 8:

[0088] If no abnormality is detected, the server notifies the user of the normal status.

[0089] For example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[0090] Purchase assistance

[0091] Receiving product requests

[0092] Step 9:

[0093] Users or elderly people use the LINE app to send requests for items necessary for daily life.

[0094] For example: "I need toilet paper."

[0095] Handling the request

[0096] Step 10:

[0097] The server analyzes the request message received from the user and identifies the required product.

[0098] Step 11:

[0099] The server uses the Yahoo Shopping API to search for information about the relevant product.

[0100] Generate and send the link

[0101] Step 12:

[0102] The server generates appropriate product offering links from the search results.

[0103] Step 13:

[0104] The server sends the generated link to the user via a LINE message.

[0105] For example: "You can buy toilet paper here [link]"

[0106] Specific examples

[0107] Health Data Monitoring

[0108] Step 1:

[0109] The device collects blood pressure data at 7:00 a.m.

[0110] Step 2:

[0111] The terminal transmits the acquired data to the server.

[0112] Step 3:

[0113] The server receives the data and stores it in a database.

[0114] Step 4:

[0115] The server passes the data to the AI ​​module for analysis.

[0116] Step 5:

[0117] The AI ​​module analyzes the data and returns the results to the server.

[0118] Step 6:

[0119] Based on the analysis results, the server will either notify you of a normal condition or generate an emergency notification.

[0120] Step 7:

[0121] If the result is normal, the server sends a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[0122] Step 8:

[0123] If an abnormality is detected, the server will send a LINE notification saying, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0124] Assisted Buy execution

[0125] Step 1:

[0126] A user sends a message on LINE saying, "I need toilet paper."

[0127] Step 2:

[0128] The server receives and parses the message.

[0129] Step 3:

[0130] The server calls the Yahoo Shopping API and searches for the relevant product.

[0131] Step 4:

[0132] The server generates a product offer link from the search results.

[0133] Step 5:

[0134] The server replies with a link via LINE saying, "You can buy toilet paper here [link]."

[0135] Example 1

[0136] 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."

[0137] While there is a need to monitor the health status of the elderly and respond to emergencies, there is a lack of efficient ways to do this remotely. Support for purchasing necessary items is also essential for the elderly's daily lives, but this process must be simple. Conventional systems do not integrate real-time health monitoring, prompt notification in the event of an abnormality, and support for purchasing items, causing inconvenience to the elderly and their families.

[0138] 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.

[0139] In this invention, the server includes means for transmitting health data acquired from the terminal means to the server, means for receiving the transmitted health data and storing it in a database, means for passing the received health data to an AI module and comparing it with past data to detect abnormal values, means for generating an emergency notification and notifying the user via a communication application if an abnormality is detected, means for notifying the user of a normal condition if no abnormality is detected, means for receiving an item purchase request from the user, identifying an appropriate item, and generating a provision link, and means for transmitting the generated link to the user via the communication application. This enables comprehensive monitoring of the health status of elderly people, enabling prompt response in the event of an abnormality, and efficient support for purchasing items necessary for daily life.

[0140] "Terminal means" refers to hardware devices such as smartphones and wearable devices for collecting health data.

[0141] The "server means" is a central processing device that receives data sent from the terminal means and stores and analyzes it.

[0142] "AI module means" is a software or hardware configuration having artificial intelligence algorithms for analyzing received health data and detecting abnormal values.

[0143] "Means for generating an emergency notification and notifying the user through a communication application" refers to a mechanism that creates a notification message when an abnormality is detected and sends the message to the user using a communication application such as LINE.

[0144] The "means for notifying the user of a normal state" is a mechanism for generating and sending a message to the user informing them of a normal state when no abnormalities are found in the health data.

[0145] The "means for receiving a product purchase request, identifying an appropriate product, and generating a provision link" is a mechanism for analyzing a purchase request from a user, identifying the appropriate product, and generating a purchase link for that product.

[0146] "Means of sending via a communication application" refers to a mechanism for sending the generated product offer link or notification message to the user using a communication application such as LINE.

[0147] The present invention provides a remote monitoring system that remotely monitors the health status of elderly people, detects abnormalities, and provides support for purchasing items necessary for daily life. Specific embodiments of the system are described below.

[0148] Health Data Collection and Transmission

[0149] First, we will discuss the "collection and transmission of health data" in this invention. The terminal means is a smartphone or wearable device for collecting health data. Specifically, it works in conjunction with healthcare devices such as a blood pressure monitor, thermometer, and heart rate sensor to periodically acquire data. For example, a wearable device such as the Apple Watch uses Bluetooth to acquire blood pressure data from a blood pressure monitor and transmit it to a smartphone.

[0150] The terminal means transmits the collected data to the server means at regular intervals (for example, every hour). This data transmission uses the HTTPS protocol, which enables secure and fast data communication.

[0151] Data analysis and notification

[0152] Next, we will discuss "Data Analysis and Notification." The server means receives the health data sent from the terminal means and stores it in a database. The database records the health data for each user, and uses a database system such as MySQL (registered trademark).

[0153] The received data is analyzed by the AI ​​module means. The AI ​​module uses machine learning algorithms such as TENSORFLOW (registered trademark) to compare the data with past data and detect abnormal values ​​or patterns. If an abnormality is detected, the server means generates an emergency notification and promptly notifies the user through a communication application such as the LINE app. For example, a message such as "Urgent! Dad's heart rate has exceeded 160. Please check immediately" may be sent.

[0154] On the other hand, if no abnormality is detected, the server means notifies the user of the normal state, for example, a message such as "Mom's temperature this morning is 36.5 degrees, which is normal" is sent to the user.

[0155] Purchase assistance

[0156] Finally, we will explain "purchase assistance." Users or elderly people can use the LINE app to send requests for items necessary for daily life. For example, they can send a message saying, "I need toilet paper."

[0157] The server receives this request message and uses natural language processing (NLP) to identify the required product. The server then calls the Yahoo Shopping API and searches for information on the relevant product. It then generates an appropriate product link from the search results and sends it to the user via LINE message. For example, a message such as "You can purchase toilet paper here [link]" is sent.

[0158] Specific operation example

[0159] Health Data Monitoring

[0160] At 7:00 AM, the terminal means (e.g., smartwatch) automatically measures blood pressure and sends the data to the server means. The server means then passes the data to the AI ​​module, which analyzes whether there is an abnormality. If normal, it notifies the user, "Mom's blood pressure this morning is 120 / 80, which is normal," and if an abnormality is detected, it notifies the user, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0161] Assisted Buy execution

[0162] The user sends a message on LINE saying, "I need toilet paper." The server receives the message and identifies "toilet paper" through NLP. It then retrieves information about the product using the Yahoo Shopping API and replies, "You can buy toilet paper here [link]."

[0163] This system will enable efficient monitoring of the health status of elderly people, enabling rapid response in emergencies and improving convenience in daily life.

[0164] Prompt Sentence Examples

[0165] Below is an example of a prompt sentence that will be input to the generative AI model.

[0166] Please describe in natural language a remote monitoring system that collects health data on elderly people and sends notifications when abnormalities are detected based on that data. Please also provide specific examples of the notification messages, including the specific names of the hardware and software used.

[0167] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0168] Step 1:

[0169] Health data collection

[0170] The device acquires health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. Specifically, the device (e.g., a smartwatch) acquires blood pressure data from the blood pressure monitor and receives body temperature data from the thermometer via Bluetooth. The heart rate sensor directly transmits heart rate data to the device. Health data includes body temperature, blood pressure, and heart rate.

[0171] Input: Health data from healthcare devices

[0172] Output: Health data temporarily stored in the device

[0173] Step 2:

[0174] Sending data

[0175] The device sends the collected health data to the server at regular intervals (e.g., every hour). The HTTPS protocol is used for data transmission, ensuring secure data transfer. The device temporarily stores the collected data and sends it in batches at specified intervals.

[0176] Input: Health data temporarily stored in the device

[0177] Output: Health data sent to the server

[0178] Step 3:

[0179] Receiving and storing data

[0180] The server receives the health data sent from the device. The received data is parsed in JSON format and stored in a database. A database management system such as MySQL is used for the database, and the health data is managed in chronological order.

[0181] Input: Health data sent from the device

[0182] Output: Health data stored in a database

[0183] Step 4:

[0184] Data analysis

[0185] The server then passes the received health data to the AI ​​module, which compares it with past data and analyzes it for outliers and abnormal patterns. The AI ​​module uses machine learning frameworks such as TensorFlow to run models to detect outliers.

[0186] Input: Health data retrieved from a database

[0187] Output: Anomaly information analyzed by the AI ​​module

[0188] Step 5:

[0189] Generate and send anomaly notifications

[0190] If an abnormality is detected, the server generates an emergency notification and promptly notifies the user through a communication application such as the LINE app. For example, a message such as "Urgent! Dad's heart rate has exceeded 160. Please check immediately" is generated. The notification is sent using the LINE Messaging API.

[0191] Input: Anomaly information analyzed by the AI ​​module

[0192] Output: Urgent notification message sent to the user

[0193] Step 6:

[0194] Normal status notification

[0195] If no abnormalities are detected, the server generates a message informing the user of the normal condition, for example, "Mom's temperature this morning is 36.5 degrees, which is normal."

[0196] Input: Normal information analyzed by the AI ​​module

[0197] Output: Normal status notification message sent to the user

[0198] Step 7:

[0199] Receiving a purchase request

[0200] Users send requests for items necessary for daily life to the server through the LINE app. For example, they can send a message such as "I need toilet paper" via LINE. The server receives the message from the user using the LINE API.

[0201] Input: The request message sent by the user

[0202] Output: The request message received by the server

[0203] Step 8:

[0204] Parsing purchase requests

[0205] The server analyzes the received request message and identifies the required product. It uses natural language processing (NLP) techniques to analyze and identify the requested item.

[0206] Input: The request message received by the server

[0207] Output: Requested item information

[0208] Step 9:

[0209] Generate and send product offer links

[0210] The server calls the Yahoo Shopping API based on the identified product information and searches for information on the corresponding product. It then generates an appropriate product link from the search results and sends it to the user via a communication application. For example, it generates a message such as "You can buy toilet paper here [link]."

[0211] Input: Requested item information

[0212] Output: Offer link sent to user

[0213] (Application example 1)

[0214] 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."

[0215] Remote health monitoring systems for the elderly have the problem of being unable to immediately respond to health risks, especially when the elderly visit a store. Furthermore, they provide insufficient support for elderly people's everyday purchases, which can lead to a decline in their quality of life. Furthermore, if health monitoring of the elderly in a store is not performed in real time, there is also the problem of being unable to respond quickly to abnormalities.

[0216] 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.

[0217] In this invention, the server includes a terminal means for acquiring health data, a means for transmitting the acquired health data to the server, a means for receiving and storing the transmitted health data, an AI module means for analyzing the received health data and detecting abnormal values, a means for sending an emergency notification if an abnormality is detected based on the analysis results, a means for notifying a normal condition based on the analysis results, a means for collecting health data of visitors in real time using an in-store health monitoring terminal, and a means for analyzing the collected health data and notifying a store clerk if an abnormality is detected. This not only enables real-time monitoring of the health status of elderly people and emergency response when they visit, but also enables efficient support for purchasing items necessary for daily life.

[0218] "Terminal means for acquiring health data" refers to devices or equipment used to collect health information such as body temperature, blood pressure, and heart rate of elderly people.

[0219] "Means for transmitting acquired health data to a server" refers to a communication device or communication protocol for transmitting collected health data to a server via a network.

[0220] The "server means for receiving and storing transmitted health data" is a server system for receiving health data transmitted from a terminal and storing it in a database.

[0221] The "AI module means for analyzing received health data and detecting abnormal values" is an artificial intelligence module for analyzing health data stored on the server and detecting abnormal values.

[0222] "Means for sending an emergency notification when an abnormality is detected based on the analysis results" refers to a communication means for sending an emergency notification to the user when the AI ​​module detects an abnormality.

[0223] "Means for notifying the user of a normal state based on the analysis results" refers to a communication means for notifying the user of a normal health state if the AI ​​module does not detect any abnormalities.

[0224] "Means for collecting visitor health data in real time using health monitoring terminals in the store" refers to equipment for collecting visitor health data in real time using terminals installed in the store.

[0225] "Means for analyzing collected health data and notifying store staff if an abnormality is detected" refers to a communication means for analyzing health data collected in the store and sending an emergency notification to store staff if an abnormality is detected.

[0226] The present invention is a remote monitoring system that monitors the health status of elderly people, detects abnormalities, monitors the health of visitors in real time, and provides purchasing support. Specific embodiments will be described below.

[0227] Health Data Collection and Transmission

[0228] Health data collection

[0229] Terminals (smartphones, tablets, wearable devices) connect to healthcare devices such as blood pressure monitors, heart rate sensors, and thermometers to periodically collect health data, including body temperature, blood pressure, and heart rate.

[0230] Sending data

[0231] The device sends the collected health data to a server at regular intervals (e.g., every hour) using a secure and fast communication protocol.

[0232] Data analysis and notification

[0233] Receiving and storing data

[0234] The server receives the health data sent from the device and stores it in a database. Specific server systems that can be used include AWS (registered trademark) and Google (registered trademark) Cloud Platform.

[0235] Data analysis

[0236] The server passes the received health data to an AI module (e.g., a model using TensorFlow or PyTorch), which then compares the data with past data and analyzes it for abnormal values ​​or patterns.

[0237] Sending notifications

[0238] If an abnormality is detected, the server generates an emergency notification and promptly notifies the user (e.g., family or caregiver) using a communication method (e.g., LINE API, SMS API). If no abnormality is detected, the server notifies the user of their normal health status.

[0239] In-store health monitoring and purchasing assistance

[0240] In-store health monitoring

[0241] Health monitoring devices (e.g., kiosks, tablets) installed in stores collect visitors' health data in real time. The collected health data is sent to a server and analyzed by an AI module. If an abnormality is detected, the server sends an emergency notification to the store staff's device (e.g., smartphone, in-store display).

[0242] Purchase assistance

[0243] Users or seniors use in-store terminals or wearable devices to send requests for items necessary for daily life. The server receives and analyzes the request message, then generates and notifies the user of the appropriate product link. Product information is searched using APIs such as Yahoo Shopping.

[0244] Specific examples

[0245] Health Data Monitoring

[0246] At 7:00 AM, the device acquires blood pressure data and sends it to the server. The server passes the data to an AI module (e.g., TensorFlow model) for analysis. If the analysis results are normal, a LINE notification is sent stating, "This morning's blood pressure is 120 / 80, which is normal." If an abnormality is detected, a notification is sent stating, "Urgent! Your blood pressure is 180 / 110. Please check immediately."

[0247] Assisted Buy execution

[0248] The user sends a request to a terminal in the store saying, "I need toilet paper." The server receives the request, analyzes it, searches for the relevant product from the Yahoo Shopping API, generates a link, and notifies the user, "You can buy toilet paper here [link]."

[0249] Example prompts for generative AI models

[0250] Generate the following Python program:

[0251] I want to develop an application that collects health data (heart rate, blood pressure, body temperature) of elderly people and sends it to a server.

[0252] The data sent to the server detects any abnormalities and notifies store staff or managers as necessary.

[0253] For data collection, we use the requests library, and for notifications, we use SMS or the LINE API.

[0254] Abnormal thresholds are a heart rate above 100, blood pressure above 160 / 100, and body temperature above 38°C.

[0255] Set these thresholds within your program and include a process to notify you when an anomaly is detected.

[0256] The above is a specific embodiment of the present invention. This system can efficiently monitor the health status of elderly people and provide emergency response in stores. It can also provide support for purchasing items necessary for daily life.

[0257] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0258] Step 1:

[0259] The device acquires health data. Specifically, the device (smartphone, tablet, wearable device) measures body temperature, blood pressure, and heart rate from healthcare devices such as blood pressure monitors, heart rate sensors, and thermometers, and collects health data. At this stage, the input is the raw data acquired from the healthcare devices, and the output is the collected health data (e.g., body temperature 36.5°C, blood pressure 120 / 80, heart rate 75).

[0260] Step 2:

[0261] The collected health data is sent to the server. The device uses a secure and fast communication protocol (e.g., HTTPS) to send the acquired health data to the server at regular intervals (e.g., every hour). The input is the health data acquired in step 1, and the output is the health data sent to the server. Specifically, the data is encrypted and sent using the communication protocol.

[0262] Step 3:

[0263] The server stores the received health data. The server receives the health data sent from the device and stores it in a database. Specific server systems include AWS RDS and Google Cloud SQL. The input is the sent health data, and the output is the health data stored in the database. Specific operations include receiving data and storing it in the database.

[0264] Step 4:

[0265] The server analyzes the received data and detects abnormal values. The server passes the stored health data to an AI module (e.g., TensorFlow or PyTorch), which compares it with past data and analyzes whether there are any abnormal values ​​or patterns. The input is the stored past health data and newly received health data, and the output is the analysis results. Specifically, data analysis is performed using a machine learning model.

[0266] Step 5:

[0267] An emergency notification is sent if an abnormality is detected. If the server detects an abnormality based on the analysis results, it generates an emergency notification and notifies the user using a communication method (e.g., LINE API, short message API). The input is the analysis result (whether or not there is an abnormality), and the output is the emergency notification that was sent. Specifically, when an abnormality is detected, a notification message is generated and sent.

[0268] Step 6:

[0269] Notifies normal status. If the server detects no abnormalities based on the analysis results, it notifies normal health status. The input is the analysis result (normal value), and the output is the sent notification. Specifically, when a normal condition is detected, a notification message is generated and sent.

[0270] Step 7:

[0271] In-store health monitoring terminals collect visitors' health data in real time. Terminals installed in the store (e.g., kiosks, tablets) measure visitors' blood pressure, body temperature, and heart rate and collect health data. The input is raw data from the in-store healthcare devices, and the output is the collected health data.

[0272] Step 8:

[0273] Health data from within the store is sent to the server for analysis. The collected health data is sent to the server, where it is analyzed by the AI ​​module. The input is the collected health data and past data, and the output is the analysis results. The specific operation is the same as steps 2 to 4.

[0274] Step 9:

[0275] If an abnormality is detected, the store clerk is notified. If an abnormality is detected based on the analysis results, the server sends an emergency notification to the store clerk's device (e.g., smartphone, in-store display). The input is the analysis result, and the output is the emergency notification sent to the store clerk.

[0276] Step 10:

[0277] A user requests an item needed for daily life. The user or elderly person sends a request for the needed item using an in-store terminal or a wearable device. The input is the request message created by the user, and the output is the request sent to the server.

[0278] Step 11:

[0279] The server analyzes the request and generates a product offer link. The server receives the request message, analyzes it, and generates an appropriate product offer link (e.g., Yahoo Shopping API). The input is the request message, and the output is the generated product offer link.

[0280] Step 12:

[0281] The product provision link is notified to the user. The server notifies the user of the generated product provision link. The input is the product provision link, and the output is the sent notification message. The specific operations are link generation and notification message transmission.

[0282] 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.

[0283] The present invention provides a remote monitoring system that monitors the health status of an elderly person, detects abnormalities, analyzes the user's emotions, and provides appropriate responses and support. Specific embodiments of the system are described below.

[0284] Health Data Collection and Transmission

[0285] Health data collection

[0286] 1. The device (smartphone or wearable device) periodically collects health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors.

[0287] 2. Health data includes body temperature, blood pressure, heart rate, etc.

[0288] Sending data

[0289] 1. The device sends the acquired health data to the server at regular intervals (e.g., every hour).

[0290] 2. Data transmission is carried out using secure and fast communication protocols.

[0291] Data analysis and notification

[0292] Receiving and storing data

[0293] 1. The server receives the health data sent from the device and stores it in a database.

[0294] Data analysis

[0295] 1. The server passes the stored health data to the AI ​​module for analysis.

[0296] 2. The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[0297] Sending notifications

[0298] 1. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately."

[0299] 2. If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning is 36.5 degrees, which is normal."

[0300] Emotion data collection and analysis

[0301] Collecting Emotional Data

[0302] 1. The device collects the user's facial expressions and voice using sensors such as a camera and microphone.

[0303] 2. The emotion engine estimates the user's emotional state based on the collected data.

[0304] Emotional Data Analysis

[0305] 1. The server receives and analyzes the emotion data sent from the emotion engine.

[0306] 2. The server comprehensively analyzes the user's health data and emotional data to detect abnormal emotional and health states.

[0307] Response and Support

[0308] Generating a response

[0309] 1. Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response to the user.

[0310] 2. Example) If the user is feeling stressed: "You seem to be feeling more stressed lately. Try some relaxation techniques."

[0311] Sending notifications

[0312] 1. Comprehensively analyzes emotional and health data, and if an abnormality is detected, the server generates an emergency notification and sends it to the user (family member) via the LINE app. Example: "Emergency! Mom's heart rate is over 160 and her emotional state is unstable. Please check on her immediately."

[0313] Purchase assistance

[0314] Receiving product requests

[0315] 1. The user or elderly person sends a request for an item necessary for daily life using the LINE app. Example: "I need toilet paper."

[0316] Handling the request

[0317] 1. The server receives the request message from the user, analyzes it, and identifies the required product.

[0318] 2. The server searches for information about the relevant product using the Yahoo Shopping API.

[0319] Generate and send the link

[0320] 1. The server generates appropriate product offer links from the search results.

[0321] 2. The server sends the generated link to the user via LINE message. Example: "You can buy toilet paper here [LINK]".

[0322] Specific examples

[0323] Health data monitoring and emotion data analysis

[0324] 1. At 7:00 a.m., the device acquires blood pressure data and sends it to the server.

[0325] 2. The server receives the data and stores it in a database.

[0326] 3. The server passes the data to the AI ​​module for analysis.

[0327] 4. If the AI ​​module does not detect any abnormalities, the server will send a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[0328] 5. If an abnormality is detected, the server will notify, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0329] 6. At the same time, the device captures the user's facial expressions with a camera, which the emotion engine analyzes. If the emotional state is determined to be unstable, the server will notify the user, saying, "You've been feeling stressed lately. Please try some relaxation techniques."

[0330] Assisted Buy execution

[0331] 1. A user sends a message on LINE saying, "I need toilet paper."

[0332] 2. The server receives the message, analyzes it, searches for the relevant product using the Yahoo Shopping API, generates a link, and replies with "You can buy toilet paper here [link]."

[0333] This system will enable efficient monitoring of the health status of elderly people and enable immediate response to any abnormalities, as well as analyze the user's emotional state and provide appropriate responses and support, improving the convenience of everyday life.

[0334] The processing flow will be explained below.

[0335] Health data collection and analysis

[0336] Health data collection

[0337] Step 1:

[0338] The device acquires health data from linked healthcare devices (e.g., thermometers and blood pressure monitors).

[0339] Step 2:

[0340] The device transmits the acquired health data to the server at regular intervals (for example, every hour).

[0341] Data analysis

[0342] Step 3:

[0343] The server receives the health data sent from the device and stores it in a database.

[0344] Step 4:

[0345] The server passes the stored health data to an AI module for analysis.

[0346] Step 5:

[0347] The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[0348] Sending notifications

[0349] Step 6:

[0350] The server generates an emergency notification if an anomaly is detected based on the analysis results of the AI ​​module.

[0351] Step 7:

[0352] The server sends the generated emergency notification to the user (family member) via the LINE app.

[0353] For example: "Urgent! Dad's heart rate is over 160. Please check immediately."

[0354] Step 8:

[0355] If no abnormality is detected, the server notifies the user of the normal status.

[0356] For example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[0357] Emotion data collection and analysis

[0358] Collecting Emotional Data

[0359] Step 9:

[0360] The device collects the user's facial expressions and voice using sensors such as a camera and microphone.

[0361] Step 10:

[0362] The terminal sends the collected data to an emotion engine to estimate the user's emotional state.

[0363] Emotional Data Analysis

[0364] Step 11:

[0365] The server receives the emotion data sent from the emotion engine and stores it in a database.

[0366] Step 12:

[0367] The server passes the desired emotional data to the AI ​​module for analysis.

[0368] Step 13:

[0369] The server comprehensively analyzes the user's health data and emotional data to detect abnormal emotional and health states.

[0370] Response and Support

[0371] Generating a response

[0372] Step 14:

[0373] Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response to the user.

[0374] For example, if the user is feeling stressed: "You seem to be feeling more stressed lately. Try some relaxation techniques."

[0375] Sending notifications

[0376] Step 15:

[0377] Emotional data and health data are analyzed comprehensively, and if an abnormality is detected, the server generates an emergency notification and sends it to the user (family) via the LINE app.

[0378] For example: "Urgent! Mom's heart rate is over 160 and she's in an unstable emotional state. Please check in immediately."

[0379] Purchase assistance

[0380] Receiving product requests

[0381] Step 16:

[0382] Users or elderly people use the LINE app to send requests for items necessary for daily life.

[0383] For example: "I need toilet paper."

[0384] Handling the request

[0385] Step 17:

[0386] The server analyzes the request message received from the user and identifies the required product.

[0387] Step 18:

[0388] The server uses the Yahoo Shopping API to search for information about the relevant product.

[0389] Generate and send the link

[0390] Step 19:

[0391] The server generates appropriate product offering links from the search results.

[0392] Step 20:

[0393] The server sends the generated link to the user via a LINE message.

[0394] For example: "You can buy toilet paper here [link]"

[0395] Specific examples

[0396] Health data monitoring and emotion data analysis

[0397] Step 1:

[0398] The device collects blood pressure data at 7:00 a.m.

[0399] Step 2:

[0400] The terminal transmits the acquired data to the server.

[0401] Step 3:

[0402] The server receives the data and stores it in a database.

[0403] Step 4:

[0404] The server passes the data to the AI ​​module for analysis.

[0405] Step 5:

[0406] The AI ​​module analyzes the data and returns the results to the server.

[0407] Step 6:

[0408] Based on the analysis results, the server will either notify you of a normal condition or generate an emergency notification.

[0409] Step 7:

[0410] If the result is normal, the server sends a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[0411] Step 8:

[0412] If an abnormality is detected, the server will send a LINE notification saying, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0413] Step 9:

[0414] At the same time, the device captures the user's facial expressions with a camera, which are then analyzed by the emotion engine.

[0415] Step 10:

[0416] If the emotional state is determined to be unstable, the server will notify the user, "You've been feeling stressed lately. Try some relaxation techniques."

[0417] Assisted Buy execution

[0418] Step 1:

[0419] A user sends a message on LINE saying, "I need toilet paper."

[0420] Step 2:

[0421] The server receives and parses the message.

[0422] Step 3:

[0423] The server calls the Yahoo Shopping API and searches for the relevant product.

[0424] Step 4:

[0425] The server generates a product offer link from the search results.

[0426] Step 5:

[0427] The server replies with a link via LINE saying, "You can buy toilet paper here [link]."

[0428] Example 2

[0429] 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."

[0430] Continuously monitoring the health status of elderly people and immediately detecting and responding to abnormalities or emergencies are important challenges in today's aging society. It is also necessary to understand the emotional state of elderly people and provide appropriate support. However, current systems lack the ability to collect and analyze health and emotional data, preventing effective monitoring and support. Furthermore, there is a growing demand for systems that can quickly respond to users' requests for everyday items.

[0431] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a mobile information terminal means for acquiring health data, a means for transmitting the acquired health data to the central processing unit, a central processing unit means for receiving and storing the transmitted health data, an artificial intelligence module means for analyzing the received health data and detecting abnormal values, a means for sending an emergency notification if an abnormality is detected based on the analysis results, a means for notifying the user of a normal state based on the analysis results, a mobile information terminal means and an emotion engine means for collecting and analyzing emotion data, a means for generating and notifying an appropriate response based on the emotion data, and a means for receiving purchase requests from users and generating and transmitting an appropriate product provision link. This enables real-time monitoring of the health and emotional states of elderly people and immediate response when an abnormality occurs. Furthermore, the server can quickly respond to user requests, improving convenience in daily life.

[0432] "Terminal means" refers to a portable information terminal for collecting health data and emotional data and transmitting them to a server.

[0433] "Central processing unit means" refers to a processing unit that receives, stores, and analyzes data sent from the terminal.

[0434] "Artificial intelligence module means" refers to an artificial intelligence system that has the function of analyzing received data and detecting abnormal values.

[0435] "Means for sending emergency notifications" refers to a function that promptly sends a warning or notification to the user when an abnormality is detected.

[0436] "Means for notifying normal status" refers to a function that notifies the user when there is no abnormality in the health data.

[0437] "Emotion engine means" refers to a system that has the function of analyzing the user's emotional data and understanding their state.

[0438] The "means for generating and notifying an appropriate response" refers to a function for generating an appropriate response message for the user based on the analysis results of the emotion data and transmitting that message.

[0439] "Means for receiving a purchase request, generating a product provision link, and transmitting the same" refers to a function for receiving a purchase request from a user, generating an appropriate product provision link based on the request, and transmitting the link to the user.

[0440] The present invention provides a remote monitoring system that monitors the health status of elderly people, detects abnormalities, analyzes the user's emotions, and provides appropriate responses and support. This system includes the following components:

[0441] Terminal means

[0442] The terminal means consists of a smartphone or wearable device, and has the function of periodically acquiring health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. For example, the terminal automatically collects blood pressure data at 7:00 a.m. The terminal communicates with the healthcare devices using Bluetooth or Wi-Fi to acquire the data.

[0443] central processing unit means

[0444] The health data sent from the terminal is received by the central processing unit. The central processing unit is composed of a server, and the server stores the received data in a database. The database stores health data such as body temperature, blood pressure, and heart rate.

[0445] Artificial Intelligence Module Means

[0446] The health data stored in the central processing unit means is analyzed by the artificial intelligence module means. The AI ​​module compares it with past data and detects the presence of abnormal values ​​or patterns. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app.

[0447] Emergency and regular notifications

[0448] If an abnormality is detected, the server will send an emergency notification, such as a message saying, "Urgent! Dad's heart rate has exceeded 160. Please check immediately." If no abnormality is detected, the server will notify the normal condition, such as a message saying, "Mom's temperature this morning is 36.5 degrees, which is normal."

[0449] Emotion Data and Emotion Engine Methods

[0450] The terminal means uses a camera and microphone to collect the user's facial expressions and voice and transmits them to the emotion engine means. The emotion engine means estimates the user's emotional state based on the collected data. The analysis results are transmitted to a server, which comprehensively analyzes the user's health data and emotional data to detect abnormal emotional or health states.

[0451] A means of generating and notifying responses

[0452] Based on the analysis results of the emotion engine, the server generates an appropriate response for the user. For example, if the user is feeling stressed, the server generates a message such as "You seem to be feeling more stressed recently. Try to find ways to relax," and sends it through the LINE app.

[0453] Purchase Request Processing

[0454] Users use the LINE app to send requests for items necessary for daily life on their devices. The server receives the request message, analyzes it, and identifies the required products. The server then searches for information about the relevant product using a common online shopping API and generates an appropriate product link. This link is then sent to the user via a LINE message. For example, a message such as "You can purchase toilet paper here [link]" may be sent.

[0455] Example prompt

[0456] "Your father's blood pressure is abnormal. Please check it immediately."

[0457] "Mom's temperature is normal."

[0458] "Your stress levels are rising. Relax."

[0459] "I need toilet paper."

[0460] This system will monitor the health status of the elderly in real time, respond immediately if an abnormality occurs, and analyze the user's emotional state to provide appropriate responses and support. It will also be able to quickly respond to requests from users for items necessary for daily life, greatly improving the convenience of daily life.

[0461] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0462] Step 1: Collecting health data

[0463] The device uses a smartphone or wearable device to collect health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. Specifically, the device's app communicates with the healthcare devices via Bluetooth or Wi-Fi to collect data. For example, the device automatically collects blood pressure data at 7:00 a.m.

[0464] Input: Health data from blood pressure monitor, thermometer, and heart rate sensor

[0465] Output: Save acquired health data (body temperature, blood pressure, heart rate) on the device

[0466] Step 2: Send your health data

[0467] The device sends the acquired health data to the server at regular intervals (e.g., every hour) using a secure and fast communication protocol (e.g., HTTPS).

[0468] Input: Health data stored on the device

[0469] Output: Health data sent to the server using HTTPS protocol

[0470] Step 3: Receiving and storing health data

[0471] The server receives the health data sent from the device and automatically stores it in a database.

[0472] Input: Health data sent from the device

[0473] Output: Health data stored in a database

[0474] Step 4: Analyze health data

[0475] The server passes the stored health data to an AI module for analysis, which compares it with past data to detect any abnormal values ​​or patterns.

[0476] Input: Health data stored in a database

[0477] Output: Analysis results by the AI ​​module (outliers and patterns)

[0478] Step 5: Generate and send notifications

[0479] If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately." If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[0480] Input: Analysis results of the AI ​​module

[0481] Output: Sends an emergency or normal notification to the LINE app.

[0482] Step 6: Collect emotion data

[0483] The device uses a camera and microphone to collect the user's facial expressions and voice. Specifically, the camera is activated at regular intervals to capture the user's facial expressions, and the microphone is used to record the user's tone and intonation of voice.

[0484] Input: User facial and voice data

[0485] Output: Emotion data stored on the device

[0486] Step 7: Sending Emotion Data

[0487] The device sends the collected emotion data to a server using a secure and fast communication protocol (e.g., HTTPS).

[0488] Input: Emotion data stored on the device

[0489] Output: Emotion data sent to the server using HTTPS protocol

[0490] Step 8: Analyze the sentiment data

[0491] The emotion engine estimates the user's emotional state based on the collected data and sends the analysis results to the server.

[0492] Input: Emotion data sent to the server

[0493] Output: Analysis results by the emotion engine

[0494] Step 9: Comprehensive analysis and response generation

[0495] The server comprehensively analyzes the user's health and emotional data to detect abnormal emotional or health conditions. Based on the results, the server generates an appropriate response. For example, if the user is feeling stressed, the server generates a message such as, "You seem to be feeling more stressed recently. Please try to find ways to relax."

[0496] Input: Comprehensive analysis results of health data and emotional data

[0497] Output: The appropriate response message

[0498] Step 10: Send a response message

[0499] The server sends the generated response message to the user via the LINE app.

[0500] Input: Server-generated response message

[0501] Output: Response message sent to the LINE app

[0502] Step 11: Receiving a Purchase Request

[0503] Users use the LINE app to send requests for items necessary for daily life via their terminal means.

[0504] Input: Purchase request message sent by the user

[0505] Output: Purchase request message received on the device

[0506] Step 12: Parse the purchase request

[0507] The server receives the request message, analyzes it, and identifies the required product. The server then searches for information about the corresponding product using a standard online shopping API.

[0508] Input: Purchase request message sent from the device

[0509] Output: Product information search results

[0510] Step 13: Generate and send your product offer link

[0511] The server generates the appropriate product link from the search results and sends it to the user via LINE message. Example: "You can buy toilet paper here [link]".

[0512] Input: Product information search results

[0513] Output: LINE message containing the product offer link

[0514] This system will enable real-time monitoring of the health and emotional state of the elderly, and will respond immediately if an abnormality occurs. It will also be able to quickly respond to requests from users for items necessary for daily life, improving the convenience of daily life.

[0515] (Application example 2)

[0516] 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."

[0517] Until now, there has been no system that can monitor not only the health status of elderly people but also the emotional state of passengers in real time to comprehensively improve safety and comfort. Furthermore, autonomous vehicles with many elderly passengers are required to instantly detect abnormalities in their health and emotional states and take appropriate action. Furthermore, a system is needed that can comprehensively analyze passenger health and emotional data and promptly notify passengers and relevant parties when an abnormality is detected.

[0518] The specific processing by the specific 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 terminal means for acquiring health data, means for transmitting the acquired health data to the server, server means for receiving and storing the transmitted health data, AI module means for analyzing the received health data and detecting abnormal values, means for sending an emergency notification if an abnormality is detected based on the analysis results, means for notifying the normal state based on the analysis results, sensor means for acquiring the facial expressions and voice of the occupant and estimating their emotional state, server means for transmitting and analyzing the emotional data, and means for generating and notifying an appropriate response based on the emotional data. This enables real-time monitoring of the health and emotional states of elderly people and promptly sending an emergency notification if an abnormality is detected. Furthermore, providing appropriate responses and support according to the occupant's emotional state can improve safety and comfort.

[0519] "Elderly" refers to people aged 65 and over, and health risks generally increase with age.

[0520] "Health status" refers to the physical condition of an individual, assessed comprehensively from physical data such as body temperature, blood pressure, and heart rate.

[0521] "Monitoring" is the act of acquiring and analyzing data in real time to detect abnormalities and changes.

[0522] A "remote monitoring system" is a system that monitors the health and safety of people in remote locations via the Internet or wireless communications, without the need for physical contact.

[0523] "Terminal means" refers to hardware such as smartphones and wearable devices that are used to collect health data.

[0524] "Server means" refers to a server for receiving, storing, and analyzing data.

[0525] "Data transmission means" refers to the communication protocol or technology used to transmit health data from the terminal to the server.

[0526] "AI module means" is a software module that uses artificial intelligence to analyze data and detect anomalies.

[0527] "Notification means" refers to a method for notifying users of abnormal or normal conditions, and includes messaging services such as the LINE app.

[0528] "Sensor means" refers to devices such as cameras and microphones used to capture emotional data such as facial expressions and voice.

[0529] "Emotion data" is data that indicates the emotional state of the user estimated from facial expressions, voice, etc.

[0530] An "urgent notification" is a warning message that is sent to the user immediately when an abnormality is detected.

[0531] An "appropriate response" is a response that includes support or suggestions appropriate to the user's situation and is generated based on the acquired data.

[0532] A "response generation means" is an AI engine or algorithm that creates an appropriate response based on emotional data.

[0533] The present invention is a remote monitoring system that monitors the health and emotional state of elderly people and provides appropriate responses and support based on the results. This system is designed to ensure the safety and comfort of passengers, especially elderly people, in autonomous vehicles.

[0534] Health Data Collection and Transmission

[0535] Health data collection

[0536] The terminal (smartphone or wearable device) periodically collects health data from devices installed in the car, such as "smart seats," blood pressure sensors, and heart rate sensors. Health data includes body temperature, blood pressure, heart rate, etc.

[0537] Sending data

[0538] The device sends the acquired health data to the server at regular intervals (e.g., every 30 minutes). Communication uses a secure and fast protocol (e.g., HTTPS).

[0539] Data analysis and notification

[0540] Receiving and storing data

[0541] The server receives the health data sent from the terminal and stores it in a database.

[0542] Data analysis

[0543] The server passes the stored health data to an AI module for analysis. The AI ​​module compares it with past data to detect abnormal values ​​and patterns. The analysis uses a generative AI model.

[0544] Sending notifications

[0545] If an abnormality is detected, the server generates an emergency notification and promptly notifies the passengers and maintenance staff via the in-car smart display, voice system, or passenger's smartphone, for example, by sending a prompt message such as "Emergency! Your heart rate is very high. Contact a medical institution immediately."

[0546] Emotion data collection and analysis

[0547] Collecting Emotional Data

[0548] The device collects the passenger's facial expressions and voice using cameras and microphones inside the vehicle, and the emotion engine estimates the passenger's emotional state based on the collected data.

[0549] Emotional Data Analysis

[0550] The server receives and analyzes the emotion data sent from the emotion engine. The server comprehensively analyzes the passenger's health data and emotion data to detect abnormal emotional or health conditions.

[0551] Response and Support

[0552] Generating a response

[0553] Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response for the passenger. For example, if the passenger is feeling stressed, it generates a prompt such as, "Your stress is increasing. Please take a moment to take a deep breath."

[0554] Sending notifications

[0555] Emotional data and health data are comprehensively analyzed, and if an abnormality is detected, the server generates an emergency notification and sends it to the occupants and relevant parties.

[0556] Specific examples

[0557] Health data monitoring and emotion data analysis

[0558] 1. At 7:00 AM, the device acquires blood pressure data and sends it to the server.

[0559] 2. The server receives the data and stores it in a database.

[0560] 3. The server passes the data to the AI ​​module for analysis.

[0561] 4. If the AI ​​module does not detect any abnormalities, the server will notify the smart display that "No abnormalities were detected."

[0562] 5. If an abnormality is detected, the server will notify you: "Urgent! Your blood pressure is very high. Please check."

[0563] 6. At the same time, the device captures the passenger's facial expressions with a camera and the emotion engine analyzes them. If the emotional state is determined to be unstable, the device will notify the passenger, saying, "You've been feeling stressed recently. Try to find ways to relax."

[0564] Hardware and software used

[0565] Camera: Used to capture facial expressions (e.g., a general-purpose camera).

[0566] Sensors: Used to acquire health data (e.g., general-purpose sensors).

[0567] software:

[0568] Server communication: Uses the requests module.

[0569] Image processing: Uses cv2 (OpenCV).

[0570] Time management: time and datetime modules.

[0571] Prompt Sentence Examples

[0572] "Urgent! Heart rate is very high. Call medical help immediately."

[0573] "You've been under a lot of stress lately. Try some relaxation techniques."

[0574] The system can efficiently monitor the health and emotional state of passengers, enabling immediate response to abnormal situations and providing appropriate responses and obedient actions, thereby improving the safety and comfort of autonomous vehicles.

[0575] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0576] Step 1:

[0577] The device collects health data of passengers using the "smart seat" installed in the vehicle and various sensors (blood pressure sensor, heart rate sensor). This data includes body temperature, blood pressure, and heart rate. The input is an analog signal from the sensor, which is converted to a digital signal and stored in the device. The output is the collected health data.

[0578] Step 2:

[0579] The device sends the acquired health data to the server at regular intervals (e.g., every 30 minutes). The device specifically sends data securely using the HTTPS protocol. The input is the health data acquired in step 1, and the output is the data sent to the server.

[0580] Step 3:

[0581] The server receives the health data sent from the device and stores it in a database. Here, the health data sent from the device is the input, and the data stored in the database is the output. The stored data accumulates over time.

[0582] Step 4:

[0583] The server passes the accumulated health data to an AI module for analysis. The AI ​​module compares it with past data to detect abnormal patterns. The input is health data stored in a database, and the output is the result of AI anomaly detection. A generative AI model is used for the analysis.

[0584] Step 5:

[0585] If the server detects an abnormality based on the analysis results, it generates an emergency notification and sends it to the in-car smart display, voice system, and passengers' smartphones. Specific emergency notifications include prompts such as "Emergency! Your heart rate is very high. Contact a medical institution immediately." The input is the anomaly detection result from the AI ​​module, and the output is the generated emergency notification, which is then sent.

[0586] Step 6:

[0587] At the same time, the device uses cameras and microphones inside the vehicle to collect facial expressions and voices of the occupants. The input is analog signals from the cameras and microphones, which are converted into digital data and output as data sent to the emotion engine.

[0588] Step 7:

[0589] The emotion engine estimates the emotional state of the passenger based on the collected data. It uses AI technology to analyze voice and facial expression data to estimate the emotional state (e.g., stress, anxiety, etc.). The input is the digital data obtained in step 6, and the output is the analyzed emotional state.

[0590] Step 8:

[0591] The emotion engine sends the analyzed emotion data to the server, and the server generates an appropriate response based on that data. For example, if the emotion data indicates stress, it generates a prompt such as "Your stress is increasing. Take a moment to take a deep breath." The input is the analyzed data from the emotion engine, and the output is the generated prompt.

[0592] Step 9:

[0593] The server comprehensively analyzes the health data and emotional data, and if an abnormality is detected, generates an emergency notification and sends it to the crew and relevant parties. For example, it generates a comprehensive notification such as "Emergency! Your heart rate is very high and your stress level is also high. Please check." Both health data and emotional data are input, and a comprehensive emergency notification is generated as output.

[0594] This process flow realizes a system that can monitor the health and emotional state of passengers in real time and respond immediately.

[0595] 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.

[0596] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0597] 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.

[0598] [Second embodiment]

[0599] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0600] 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.

[0601] 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).

[0602] 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.

[0603] 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.

[0604] 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).

[0605] 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.

[0606] 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.

[0607] 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.

[0608] 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.

[0609] 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.

[0610] 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."

[0611] The present invention provides a remote monitoring system that monitors the health status of elderly people, detects abnormalities, and provides support for purchasing items necessary for daily life. Specific embodiments of the system will be described below.

[0612] Health Data Collection and Transmission

[0613] Health data collection

[0614] 1. The device (smartphone or wearable device) periodically collects health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors.

[0615] 2. Health data includes body temperature, blood pressure, heart rate, etc.

[0616] Sending data

[0617] 1. The device sends the collected health data to the server at regular intervals (e.g., every hour).

[0618] 2. Data transmission is carried out using secure and fast communication protocols.

[0619] Data analysis and notification

[0620] Receiving and storing data

[0621] 1. The server receives the health data sent from the device and stores it in a database.

[0622] Data analysis

[0623] 1. The server passes the received health data to the AI ​​module.

[0624] 2. The AI ​​module analyzes the data to see if there are any abnormal values ​​or patterns, comparing them with past data.

[0625] Sending notifications

[0626] 1. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately."

[0627] 2. If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning is 36.5 degrees, which is normal."

[0628] Purchase assistance

[0629] Receiving product requests

[0630] 1. The user or elderly person sends a request for an item necessary for daily life using the LINE app. Example: "I need toilet paper."

[0631] Handling the request

[0632] 1. The server receives the request message from the user, analyzes it, and identifies the required product.

[0633] 2. The server searches for information about the relevant product using the Yahoo Shopping API.

[0634] Generate and send the link

[0635] 1. The server generates appropriate product offer links from the search results.

[0636] 2. The server sends the generated link to the user via LINE message. Example: "You can buy toilet paper here [LINK]".

[0637] Specific examples

[0638] Health Data Monitoring

[0639] At 7:00 a.m., the device acquires blood pressure data and sends it to the server. The server passes the data to the AI ​​module for analysis. If the analysis results are normal, a LINE notification is sent stating, "Mom's blood pressure this morning is 120 / 80, which is normal." If an abnormality is detected, a notification is sent stating, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0640] Assisted Buy execution

[0641] A user sends a message on LINE saying, "I need toilet paper." The server receives and analyzes the message, searches for the relevant product using the Yahoo Shopping API, generates a link, and replies, "You can buy toilet paper here [link]."

[0642] This system will enable efficient monitoring of the health status of the elderly, enable immediate response to emergencies, and improve the convenience of their daily lives.

[0643] The processing flow will be explained below.

[0644] Health data collection and analysis

[0645] Health data collection

[0646] Step 1:

[0647] The device acquires health data from linked healthcare devices (e.g., thermometers and blood pressure monitors).

[0648] Step 2:

[0649] The device transmits the acquired health data to the server at regular intervals (for example, every hour).

[0650] Data analysis

[0651] Step 3:

[0652] The server receives the health data sent from the device and stores it in a database.

[0653] Step 4:

[0654] The server passes the stored health data to an AI module for analysis.

[0655] Step 5:

[0656] The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[0657] Sending notifications

[0658] Step 6:

[0659] The server generates an emergency notification if an anomaly is detected based on the analysis results of the AI ​​module.

[0660] Step 7:

[0661] The server sends the generated emergency notification to the user (family member) via the LINE app.

[0662] For example: "Urgent! Dad's heart rate is over 160. Please check immediately."

[0663] Step 8:

[0664] If no abnormality is detected, the server notifies the user of the normal status.

[0665] For example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[0666] Purchase assistance

[0667] Receiving product requests

[0668] Step 9:

[0669] Users or elderly people use the LINE app to send requests for items necessary for daily life.

[0670] For example: "I need toilet paper."

[0671] Handling the request

[0672] Step 10:

[0673] The server analyzes the request message received from the user and identifies the required product.

[0674] Step 11:

[0675] The server uses the Yahoo Shopping API to search for information about the relevant product.

[0676] Generate and send the link

[0677] Step 12:

[0678] The server generates appropriate product offering links from the search results.

[0679] Step 13:

[0680] The server sends the generated link to the user via a LINE message.

[0681] For example: "You can buy toilet paper here [link]"

[0682] Specific examples

[0683] Health Data Monitoring

[0684] Step 1:

[0685] The device collects blood pressure data at 7:00 a.m.

[0686] Step 2:

[0687] The terminal transmits the acquired data to the server.

[0688] Step 3:

[0689] The server receives the data and stores it in a database.

[0690] Step 4:

[0691] The server passes the data to the AI ​​module for analysis.

[0692] Step 5:

[0693] The AI ​​module analyzes the data and returns the results to the server.

[0694] Step 6:

[0695] Based on the analysis results, the server will either notify you of a normal condition or generate an emergency notification.

[0696] Step 7:

[0697] If the result is normal, the server sends a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[0698] Step 8:

[0699] If an abnormality is detected, the server will send a LINE notification saying, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0700] Assisted Buy execution

[0701] Step 1:

[0702] A user sends a message on LINE saying, "I need toilet paper."

[0703] Step 2:

[0704] The server receives and parses the message.

[0705] Step 3:

[0706] The server calls the Yahoo Shopping API and searches for the relevant product.

[0707] Step 4:

[0708] The server generates a product offer link from the search results.

[0709] Step 5:

[0710] The server replies with a link via LINE saying, "You can buy toilet paper here [link]."

[0711] Example 1

[0712] 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."

[0713] While there is a need to monitor the health status of the elderly and respond to emergencies, there is a lack of efficient ways to do this remotely. Support for purchasing necessary items is also essential for the elderly's daily lives, but this process must be simple. Conventional systems do not integrate real-time health monitoring, prompt notification in the event of an abnormality, and support for purchasing items, causing inconvenience to the elderly and their families.

[0714] 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.

[0715] In this invention, the server includes means for transmitting health data acquired from the terminal means to the server, means for receiving the transmitted health data and storing it in a database, means for passing the received health data to an AI module and comparing it with past data to detect abnormal values, means for generating an emergency notification and notifying the user via a communication application if an abnormality is detected, means for notifying the user of a normal condition if no abnormality is detected, means for receiving an item purchase request from the user, identifying an appropriate item, and generating a provision link, and means for transmitting the generated link to the user via the communication application. This enables comprehensive monitoring of the health status of elderly people, enabling prompt response in the event of an abnormality, and efficient support for purchasing items necessary for daily life.

[0716] "Terminal means" refers to hardware devices such as smartphones and wearable devices for collecting health data.

[0717] The "server means" is a central processing device that receives data sent from the terminal means and stores and analyzes it.

[0718] "AI module means" is a software or hardware configuration having artificial intelligence algorithms for analyzing received health data and detecting abnormal values.

[0719] "Means for generating an emergency notification and notifying the user through a communication application" refers to a mechanism that creates a notification message when an abnormality is detected and sends the message to the user using a communication application such as LINE.

[0720] The "means for notifying the user of a normal state" is a mechanism for generating and sending a message to the user informing them of a normal state when no abnormalities are found in the health data.

[0721] The "means for receiving a product purchase request, identifying an appropriate product, and generating a provision link" is a mechanism for analyzing a purchase request from a user, identifying the appropriate product, and generating a purchase link for that product.

[0722] "Means of sending via a communication application" refers to a mechanism for sending the generated product offer link or notification message to the user using a communication application such as LINE.

[0723] The present invention provides a remote monitoring system that remotely monitors the health status of elderly people, detects abnormalities, and provides support for purchasing items necessary for daily life. Specific embodiments of the system are described below.

[0724] Health Data Collection and Transmission

[0725] First, we will discuss the "collection and transmission of health data" in this invention. The terminal means is a smartphone or wearable device for collecting health data. Specifically, it works in conjunction with healthcare devices such as a blood pressure monitor, thermometer, and heart rate sensor to periodically acquire data. For example, a wearable device such as the Apple Watch uses Bluetooth to acquire blood pressure data from a blood pressure monitor and transmit it to a smartphone.

[0726] The terminal means transmits the collected data to the server means at regular intervals (for example, every hour). This data transmission uses the HTTPS protocol, which enables secure and fast data communication.

[0727] Data analysis and notification

[0728] Next, we will discuss "Data Analysis and Notification." The server means receives the health data sent from the terminal means and stores it in a database. The database records the health data for each user, and uses a database system such as MySQL.

[0729] The received data is analyzed by the AI ​​module means. The AI ​​module uses machine learning algorithms such as TensorFlow to compare it with past data and detect abnormal values ​​or patterns. If an abnormality is detected, the server means generates an emergency notification and promptly notifies the user through a communication application such as the LINE app. For example, a message such as "Urgent! Dad's heart rate has exceeded 160. Please check immediately" may be sent.

[0730] On the other hand, if no abnormality is detected, the server means notifies the user of the normal state, for example, a message such as "Mom's temperature this morning is 36.5 degrees, which is normal" is sent to the user.

[0731] Purchase assistance

[0732] Finally, we will explain "purchase assistance." Users or elderly people can use the LINE app to send requests for items necessary for daily life. For example, they can send a message saying, "I need toilet paper."

[0733] The server receives this request message and uses natural language processing (NLP) to identify the required product. The server then calls the Yahoo Shopping API and searches for information on the relevant product. It then generates an appropriate product link from the search results and sends it to the user via LINE message. For example, a message such as "You can purchase toilet paper here [link]" is sent.

[0734] Specific operation example

[0735] Health Data Monitoring

[0736] At 7:00 AM, the terminal means (e.g., smartwatch) automatically measures blood pressure and sends the data to the server means. The server means then passes the data to the AI ​​module, which analyzes whether there is an abnormality. If normal, it notifies the user, "Mom's blood pressure this morning is 120 / 80, which is normal," and if an abnormality is detected, it notifies the user, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0737] Assisted Buy execution

[0738] The user sends a message on LINE saying, "I need toilet paper." The server receives the message and identifies "toilet paper" through NLP. It then retrieves information about the product using the Yahoo Shopping API and replies, "You can buy toilet paper here [link]."

[0739] This system will enable efficient monitoring of the health status of elderly people, enabling rapid response in emergencies and improving convenience in daily life.

[0740] Prompt Sentence Examples

[0741] Below is an example of a prompt sentence that will be input to the generative AI model.

[0742] Please describe in natural language a remote monitoring system that collects health data on elderly people and sends notifications when abnormalities are detected based on that data. Please also provide specific examples of the notification messages, including the specific names of the hardware and software used.

[0743] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0744] Step 1:

[0745] Health data collection

[0746] The device acquires health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. Specifically, the device (e.g., a smartwatch) acquires blood pressure data from the blood pressure monitor and receives body temperature data from the thermometer via Bluetooth. The heart rate sensor directly transmits heart rate data to the device. Health data includes body temperature, blood pressure, and heart rate.

[0747] Input: Health data from healthcare devices

[0748] Output: Health data temporarily stored in the device

[0749] Step 2:

[0750] Sending data

[0751] The device sends the collected health data to the server at regular intervals (e.g., every hour). The HTTPS protocol is used for data transmission, ensuring secure data transfer. The device temporarily stores the collected data and sends it in batches at specified intervals.

[0752] Input: Health data temporarily stored in the device

[0753] Output: Health data sent to the server

[0754] Step 3:

[0755] Receiving and storing data

[0756] The server receives the health data sent from the device. The received data is parsed in JSON format and stored in a database. A database management system such as MySQL is used for the database, and the health data is managed in chronological order.

[0757] Input: Health data sent from the device

[0758] Output: Health data stored in a database

[0759] Step 4:

[0760] Data analysis

[0761] The server then passes the received health data to the AI ​​module, which compares it with past data and analyzes it for outliers and abnormal patterns. The AI ​​module uses machine learning frameworks such as TensorFlow to run models to detect outliers.

[0762] Input: Health data retrieved from a database

[0763] Output: Anomaly information analyzed by the AI ​​module

[0764] Step 5:

[0765] Generate and send anomaly notifications

[0766] If an abnormality is detected, the server generates an emergency notification and promptly notifies the user through a communication application such as the LINE app. For example, a message such as "Urgent! Dad's heart rate has exceeded 160. Please check immediately" is generated. The notification is sent using the LINE Messaging API.

[0767] Input: Anomaly information analyzed by the AI ​​module

[0768] Output: Urgent notification message sent to the user

[0769] Step 6:

[0770] Normal status notification

[0771] If no abnormalities are detected, the server generates a message informing the user of the normal condition, for example, "Mom's temperature this morning is 36.5 degrees, which is normal."

[0772] Input: Normal information analyzed by the AI ​​module

[0773] Output: Normal status notification message sent to the user

[0774] Step 7:

[0775] Receiving a purchase request

[0776] Users send requests for items necessary for daily life to the server through the LINE app. For example, they can send a message such as "I need toilet paper" via LINE. The server receives the message from the user using the LINE API.

[0777] Input: The request message sent by the user

[0778] Output: The request message received by the server

[0779] Step 8:

[0780] Parsing purchase requests

[0781] The server analyzes the received request message and identifies the required product. It uses natural language processing (NLP) techniques to analyze and identify the requested item.

[0782] Input: The request message received by the server

[0783] Output: Requested item information

[0784] Step 9:

[0785] Generate and send product offer links

[0786] The server calls the Yahoo Shopping API based on the identified product information and searches for information on the corresponding product. It then generates an appropriate product link from the search results and sends it to the user via a communication application. For example, it generates a message such as "You can buy toilet paper here [link]."

[0787] Input: Requested item information

[0788] Output: Offer link sent to user

[0789] (Application example 1)

[0790] 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."

[0791] Remote health monitoring systems for the elderly have the problem of being unable to immediately respond to health risks, especially when the elderly visit a store. Furthermore, they provide insufficient support for elderly people's everyday purchases, which can lead to a decline in their quality of life. Furthermore, if health monitoring of the elderly in a store is not performed in real time, there is also the problem of being unable to respond quickly to abnormalities.

[0792] 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.

[0793] In this invention, the server includes a terminal means for acquiring health data, a means for transmitting the acquired health data to the server, a means for receiving and storing the transmitted health data, an AI module means for analyzing the received health data and detecting abnormal values, a means for sending an emergency notification if an abnormality is detected based on the analysis results, a means for notifying a normal condition based on the analysis results, a means for collecting health data of visitors in real time using an in-store health monitoring terminal, and a means for analyzing the collected health data and notifying a store clerk if an abnormality is detected. This not only enables real-time monitoring of the health status of elderly people and emergency response when they visit, but also enables efficient support for purchasing items necessary for daily life.

[0794] "Terminal means for acquiring health data" refers to devices or equipment used to collect health information such as body temperature, blood pressure, and heart rate of elderly people.

[0795] "Means for transmitting acquired health data to a server" refers to a communication device or communication protocol for transmitting collected health data to a server via a network.

[0796] The "server means for receiving and storing transmitted health data" is a server system for receiving health data transmitted from a terminal and storing it in a database.

[0797] The "AI module means for analyzing received health data and detecting abnormal values" is an artificial intelligence module for analyzing health data stored on the server and detecting abnormal values.

[0798] "Means for sending an emergency notification when an abnormality is detected based on the analysis results" refers to a communication means for sending an emergency notification to the user when the AI ​​module detects an abnormality.

[0799] "Means for notifying the user of a normal state based on the analysis results" refers to a communication means for notifying the user of a normal health state if the AI ​​module does not detect any abnormalities.

[0800] "Means for collecting visitor health data in real time using health monitoring terminals in the store" refers to equipment for collecting visitor health data in real time using terminals installed in the store.

[0801] "Means for analyzing collected health data and notifying store staff if an abnormality is detected" refers to a communication means for analyzing health data collected in the store and sending an emergency notification to store staff if an abnormality is detected.

[0802] The present invention is a remote monitoring system that monitors the health status of elderly people, detects abnormalities, monitors the health of visitors in real time, and provides purchasing support. Specific embodiments will be described below.

[0803] Health Data Collection and Transmission

[0804] Health data collection

[0805] Terminals (smartphones, tablets, wearable devices) connect to healthcare devices such as blood pressure monitors, heart rate sensors, and thermometers to periodically collect health data, including body temperature, blood pressure, and heart rate.

[0806] Sending data

[0807] The device sends the collected health data to a server at regular intervals (e.g., every hour) using a secure and fast communication protocol.

[0808] Data analysis and notification

[0809] Receiving and storing data

[0810] The server receives the health data sent from the device and stores it in a database. Specific server systems used include AWS and Google Cloud Platform.

[0811] Data analysis

[0812] The server passes the received health data to an AI module (e.g., a model using TensorFlow or PyTorch), which then compares the data with past data and analyzes it for abnormal values ​​or patterns.

[0813] Sending notifications

[0814] If an abnormality is detected, the server generates an emergency notification and promptly notifies the user (e.g., family or caregiver) using a communication method (e.g., LINE API, SMS API). If no abnormality is detected, the server notifies the user of their normal health status.

[0815] In-store health monitoring and purchasing assistance

[0816] In-store health monitoring

[0817] Health monitoring devices (e.g., kiosks, tablets) installed in stores collect visitors' health data in real time. The collected health data is sent to a server and analyzed by an AI module. If an abnormality is detected, the server sends an emergency notification to the store staff's device (e.g., smartphone, in-store display).

[0818] Purchase assistance

[0819] Users or seniors use in-store terminals or wearable devices to send requests for items necessary for daily life. The server receives and analyzes the request message, then generates and notifies the user of the appropriate product link. Product information is searched using APIs such as Yahoo Shopping.

[0820] Specific examples

[0821] Health Data Monitoring

[0822] At 7:00 AM, the device acquires blood pressure data and sends it to the server. The server passes the data to an AI module (e.g., TensorFlow model) for analysis. If the analysis results are normal, a LINE notification is sent stating, "This morning's blood pressure is 120 / 80, which is normal." If an abnormality is detected, a notification is sent stating, "Urgent! Your blood pressure is 180 / 110. Please check immediately."

[0823] Assisted Buy execution

[0824] The user sends a request to a terminal in the store saying, "I need toilet paper." The server receives the request, analyzes it, searches for the relevant product from the Yahoo Shopping API, generates a link, and notifies the user, "You can buy toilet paper here [link]."

[0825] Example prompts for generative AI models

[0826] Generate the following Python program:

[0827] I want to develop an application that collects health data (heart rate, blood pressure, body temperature) of elderly people and sends it to a server.

[0828] The data sent to the server detects any abnormalities and notifies store staff or managers as necessary.

[0829] For data collection, we use the requests library, and for notifications, we use SMS or the LINE API.

[0830] Abnormal thresholds are a heart rate above 100, blood pressure above 160 / 100, and body temperature above 38°C.

[0831] Set these thresholds within your program and include a process to notify you when an anomaly is detected.

[0832] The above is a specific embodiment of the present invention. This system can efficiently monitor the health status of elderly people and provide emergency response in stores. It can also provide support for purchasing items necessary for daily life.

[0833] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0834] Step 1:

[0835] The device acquires health data. Specifically, the device (smartphone, tablet, wearable device) measures body temperature, blood pressure, and heart rate from healthcare devices such as blood pressure monitors, heart rate sensors, and thermometers, and collects health data. At this stage, the input is the raw data acquired from the healthcare devices, and the output is the collected health data (e.g., body temperature 36.5°C, blood pressure 120 / 80, heart rate 75).

[0836] Step 2:

[0837] The collected health data is sent to the server. The device uses a secure and fast communication protocol (e.g., HTTPS) to send the acquired health data to the server at regular intervals (e.g., every hour). The input is the health data acquired in step 1, and the output is the health data sent to the server. Specifically, the data is encrypted and sent using the communication protocol.

[0838] Step 3:

[0839] The server stores the received health data. The server receives the health data sent from the device and stores it in a database. Specific server systems include AWS RDS and Google Cloud SQL. The input is the sent health data, and the output is the health data stored in the database. Specific operations include receiving data and storing it in the database.

[0840] Step 4:

[0841] The server analyzes the received data and detects abnormal values. The server passes the stored health data to an AI module (e.g., TensorFlow or PyTorch), which compares it with past data and analyzes whether there are any abnormal values ​​or patterns. The input is the stored past health data and newly received health data, and the output is the analysis results. Specifically, data analysis is performed using a machine learning model.

[0842] Step 5:

[0843] An emergency notification is sent if an abnormality is detected. If the server detects an abnormality based on the analysis results, it generates an emergency notification and notifies the user using a communication method (e.g., LINE API, short message API). The input is the analysis result (whether or not there is an abnormality), and the output is the emergency notification that was sent. Specifically, when an abnormality is detected, a notification message is generated and sent.

[0844] Step 6:

[0845] Notifies normal status. If the server detects no abnormalities based on the analysis results, it notifies normal health status. The input is the analysis result (normal value), and the output is the sent notification. Specifically, when a normal condition is detected, a notification message is generated and sent.

[0846] Step 7:

[0847] In-store health monitoring terminals collect visitors' health data in real time. Terminals installed in the store (e.g., kiosks, tablets) measure visitors' blood pressure, body temperature, and heart rate and collect health data. The input is raw data from the in-store healthcare devices, and the output is the collected health data.

[0848] Step 8:

[0849] Health data from within the store is sent to the server for analysis. The collected health data is sent to the server, where it is analyzed by the AI ​​module. The input is the collected health data and past data, and the output is the analysis results. The specific operation is the same as steps 2 to 4.

[0850] Step 9:

[0851] If an abnormality is detected, the store clerk is notified. If an abnormality is detected based on the analysis results, the server sends an emergency notification to the store clerk's device (e.g., smartphone, in-store display). The input is the analysis result, and the output is the emergency notification sent to the store clerk.

[0852] Step 10:

[0853] A user requests an item needed for daily life. The user or elderly person sends a request for the needed item using an in-store terminal or a wearable device. The input is the request message created by the user, and the output is the request sent to the server.

[0854] Step 11:

[0855] The server analyzes the request and generates a product offer link. The server receives the request message, analyzes it, and generates an appropriate product offer link (e.g., Yahoo Shopping API). The input is the request message, and the output is the generated product offer link.

[0856] Step 12:

[0857] The product provision link is notified to the user. The server notifies the user of the generated product provision link. The input is the product provision link, and the output is the sent notification message. The specific operations are link generation and notification message transmission.

[0858] 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.

[0859] The present invention provides a remote monitoring system that monitors the health status of an elderly person, detects abnormalities, analyzes the user's emotions, and provides appropriate responses and support. Specific embodiments of the system are described below.

[0860] Health Data Collection and Transmission

[0861] Health data collection

[0862] 1. The device (smartphone or wearable device) periodically collects health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors.

[0863] 2. Health data includes body temperature, blood pressure, heart rate, etc.

[0864] Sending data

[0865] 1. The device sends the acquired health data to the server at regular intervals (e.g., every hour).

[0866] 2. Data transmission is carried out using secure and fast communication protocols.

[0867] Data analysis and notification

[0868] Receiving and storing data

[0869] 1. The server receives the health data sent from the device and stores it in a database.

[0870] Data analysis

[0871] 1. The server passes the stored health data to the AI ​​module for analysis.

[0872] 2. The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[0873] Sending notifications

[0874] 1. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately."

[0875] 2. If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning is 36.5 degrees, which is normal."

[0876] Emotion data collection and analysis

[0877] Collecting Emotional Data

[0878] 1. The device collects the user's facial expressions and voice using sensors such as a camera and microphone.

[0879] 2. The emotion engine estimates the user's emotional state based on the collected data.

[0880] Emotional Data Analysis

[0881] 1. The server receives and analyzes the emotion data sent from the emotion engine.

[0882] 2. The server comprehensively analyzes the user's health data and emotional data to detect abnormal emotional and health states.

[0883] Response and Support

[0884] Generating a response

[0885] 1. Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response to the user.

[0886] 2. Example) If the user is feeling stressed: "You seem to be feeling more stressed lately. Try some relaxation techniques."

[0887] Sending notifications

[0888] 1. Comprehensively analyzes emotional and health data, and if an abnormality is detected, the server generates an emergency notification and sends it to the user (family member) via the LINE app. Example: "Emergency! Mom's heart rate is over 160 and her emotional state is unstable. Please check on her immediately."

[0889] Purchase assistance

[0890] Receiving product requests

[0891] 1. The user or elderly person sends a request for an item necessary for daily life using the LINE app. Example: "I need toilet paper."

[0892] Handling the request

[0893] 1. The server receives the request message from the user, analyzes it, and identifies the required product.

[0894] 2. The server searches for information about the relevant product using the Yahoo Shopping API.

[0895] Generate and send the link

[0896] 1. The server generates appropriate product offer links from the search results.

[0897] 2. The server sends the generated link to the user via LINE message. Example: "You can buy toilet paper here [LINK]".

[0898] Specific examples

[0899] Health data monitoring and emotion data analysis

[0900] 1. At 7:00 a.m., the device acquires blood pressure data and sends it to the server.

[0901] 2. The server receives the data and stores it in a database.

[0902] 3. The server passes the data to the AI ​​module for analysis.

[0903] 4. If the AI ​​module does not detect any abnormalities, the server will send a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[0904] 5. If an abnormality is detected, the server will notify, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0905] 6. At the same time, the device captures the user's facial expressions with a camera, which the emotion engine analyzes. If the emotional state is determined to be unstable, the server will notify the user, saying, "You've been feeling stressed lately. Please try some relaxation techniques."

[0906] Assisted Buy execution

[0907] 1. A user sends a message on LINE saying, "I need toilet paper."

[0908] 2. The server receives the message, analyzes it, searches for the relevant product using the Yahoo Shopping API, generates a link, and replies with "You can buy toilet paper here [link]."

[0909] This system will enable efficient monitoring of the health status of elderly people and enable immediate response to any abnormalities, as well as analyze the user's emotional state and provide appropriate responses and support, improving the convenience of everyday life.

[0910] The processing flow will be explained below.

[0911] Health data collection and analysis

[0912] Health data collection

[0913] Step 1:

[0914] The device acquires health data from linked healthcare devices (e.g., thermometers and blood pressure monitors).

[0915] Step 2:

[0916] The device transmits the acquired health data to the server at regular intervals (for example, every hour).

[0917] Data analysis

[0918] Step 3:

[0919] The server receives the health data sent from the device and stores it in a database.

[0920] Step 4:

[0921] The server passes the stored health data to an AI module for analysis.

[0922] Step 5:

[0923] The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[0924] Sending notifications

[0925] Step 6:

[0926] The server generates an emergency notification if an anomaly is detected based on the analysis results of the AI ​​module.

[0927] Step 7:

[0928] The server sends the generated emergency notification to the user (family member) via the LINE app.

[0929] For example: "Urgent! Dad's heart rate is over 160. Please check immediately."

[0930] Step 8:

[0931] If no abnormality is detected, the server notifies the user of the normal status.

[0932] For example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[0933] Emotion data collection and analysis

[0934] Collecting Emotional Data

[0935] Step 9:

[0936] The device collects the user's facial expressions and voice using sensors such as a camera and microphone.

[0937] Step 10:

[0938] The terminal sends the collected data to an emotion engine to estimate the user's emotional state.

[0939] Emotional Data Analysis

[0940] Step 11:

[0941] The server receives the emotion data sent from the emotion engine and stores it in a database.

[0942] Step 12:

[0943] The server passes the desired emotional data to the AI ​​module for analysis.

[0944] Step 13:

[0945] The server comprehensively analyzes the user's health data and emotional data to detect abnormal emotional and health states.

[0946] Response and Support

[0947] Generating a response

[0948] Step 14:

[0949] Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response to the user.

[0950] For example, if the user is feeling stressed: "You seem to be feeling more stressed lately. Try some relaxation techniques."

[0951] Sending notifications

[0952] Step 15:

[0953] Emotional data and health data are analyzed comprehensively, and if an abnormality is detected, the server generates an emergency notification and sends it to the user (family) via the LINE app.

[0954] For example: "Urgent! Mom's heart rate is over 160 and she's in an unstable emotional state. Please check in immediately."

[0955] Purchase assistance

[0956] Receiving product requests

[0957] Step 16:

[0958] Users or elderly people use the LINE app to send requests for items necessary for daily life.

[0959] For example: "I need toilet paper."

[0960] Handling the request

[0961] Step 17:

[0962] The server analyzes the request message received from the user and identifies the required product.

[0963] Step 18:

[0964] The server uses the Yahoo Shopping API to search for information about the relevant product.

[0965] Generate and send the link

[0966] Step 19:

[0967] The server generates appropriate product offering links from the search results.

[0968] Step 20:

[0969] The server sends the generated link to the user via a LINE message.

[0970] For example: "You can buy toilet paper here [link]"

[0971] Specific examples

[0972] Health data monitoring and emotion data analysis

[0973] Step 1:

[0974] The device collects blood pressure data at 7:00 a.m.

[0975] Step 2:

[0976] The terminal transmits the acquired data to the server.

[0977] Step 3:

[0978] The server receives the data and stores it in a database.

[0979] Step 4:

[0980] The server passes the data to the AI ​​module for analysis.

[0981] Step 5:

[0982] The AI ​​module analyzes the data and returns the results to the server.

[0983] Step 6:

[0984] Based on the analysis results, the server will either notify you of a normal condition or generate an emergency notification.

[0985] Step 7:

[0986] If the result is normal, the server sends a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[0987] Step 8:

[0988] If an abnormality is detected, the server will send a LINE notification saying, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[0989] Step 9:

[0990] At the same time, the device captures the user's facial expressions with a camera, which are then analyzed by the emotion engine.

[0991] Step 10:

[0992] If the emotional state is determined to be unstable, the server will notify the user, "You've been feeling stressed lately. Try some relaxation techniques."

[0993] Assisted Buy execution

[0994] Step 1:

[0995] A user sends a message on LINE saying, "I need toilet paper."

[0996] Step 2:

[0997] The server receives and parses the message.

[0998] Step 3:

[0999] The server calls the Yahoo Shopping API and searches for the relevant product.

[1000] Step 4:

[1001] The server generates a product offer link from the search results.

[1002] Step 5:

[1003] The server replies with a link via LINE saying, "You can buy toilet paper here [link]."

[1004] Example 2

[1005] 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."

[1006] Continuously monitoring the health status of elderly people and immediately detecting and responding to abnormalities or emergencies are important challenges in today's aging society. It is also necessary to understand the emotional state of elderly people and provide appropriate support. However, current systems lack the ability to collect and analyze health and emotional data, preventing effective monitoring and support. Furthermore, there is a growing demand for systems that can quickly respond to users' requests for everyday items.

[1007] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a mobile information terminal means for acquiring health data, a means for transmitting the acquired health data to the central processing unit, a central processing unit means for receiving and storing the transmitted health data, an artificial intelligence module means for analyzing the received health data and detecting abnormal values, a means for sending an emergency notification if an abnormality is detected based on the analysis results, a means for notifying the user of a normal state based on the analysis results, a mobile information terminal means and an emotion engine means for collecting and analyzing emotion data, a means for generating and notifying an appropriate response based on the emotion data, and a means for receiving purchase requests from users and generating and transmitting an appropriate product provision link. This enables real-time monitoring of the health and emotional states of elderly people and immediate response when an abnormality occurs. Furthermore, the server can quickly respond to user requests, improving convenience in daily life.

[1008] "Terminal means" refers to a portable information terminal for collecting health data and emotional data and transmitting them to a server.

[1009] "Central processing unit means" refers to a processing unit that receives, stores, and analyzes data sent from the terminal.

[1010] "Artificial intelligence module means" refers to an artificial intelligence system that has the function of analyzing received data and detecting abnormal values.

[1011] "Means for sending emergency notifications" refers to a function that promptly sends a warning or notification to the user when an abnormality is detected.

[1012] "Means for notifying normal status" refers to a function that notifies the user when there is no abnormality in the health data.

[1013] "Emotion engine means" refers to a system that has the function of analyzing the user's emotional data and understanding their state.

[1014] The "means for generating and notifying an appropriate response" refers to a function for generating an appropriate response message for the user based on the analysis results of the emotion data and transmitting that message.

[1015] "Means for receiving a purchase request, generating a product provision link, and transmitting the same" refers to a function for receiving a purchase request from a user, generating an appropriate product provision link based on the request, and transmitting the link to the user.

[1016] The present invention provides a remote monitoring system that monitors the health status of elderly people, detects abnormalities, analyzes the user's emotions, and provides appropriate responses and support. This system includes the following components:

[1017] Terminal means

[1018] The terminal means consists of a smartphone or wearable device, and has the function of periodically acquiring health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. For example, the terminal automatically collects blood pressure data at 7:00 a.m. The terminal communicates with the healthcare devices using Bluetooth or Wi-Fi to acquire the data.

[1019] central processing unit means

[1020] The health data sent from the terminal is received by the central processing unit. The central processing unit is composed of a server, and the server stores the received data in a database. The database stores health data such as body temperature, blood pressure, and heart rate.

[1021] Artificial Intelligence Module Means

[1022] The health data stored in the central processing unit means is analyzed by the artificial intelligence module means. The AI ​​module compares it with past data and detects the presence of abnormal values ​​or patterns. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app.

[1023] Emergency and regular notifications

[1024] If an abnormality is detected, the server will send an emergency notification, such as a message saying, "Urgent! Dad's heart rate has exceeded 160. Please check immediately." If no abnormality is detected, the server will notify the normal condition, such as a message saying, "Mom's temperature this morning is 36.5 degrees, which is normal."

[1025] Emotion Data and Emotion Engine Methods

[1026] The terminal means uses a camera and microphone to collect the user's facial expressions and voice and transmits them to the emotion engine means. The emotion engine means estimates the user's emotional state based on the collected data. The analysis results are transmitted to a server, which comprehensively analyzes the user's health data and emotional data to detect abnormal emotional or health states.

[1027] A means of generating and notifying responses

[1028] Based on the analysis results of the emotion engine, the server generates an appropriate response for the user. For example, if the user is feeling stressed, the server generates a message such as "You seem to be feeling more stressed recently. Try to find ways to relax," and sends it through the LINE app.

[1029] Purchase Request Processing

[1030] Users use the LINE app to send requests for items necessary for daily life on their devices. The server receives the request message, analyzes it, and identifies the required products. The server then searches for information about the relevant product using a common online shopping API and generates an appropriate product link. This link is then sent to the user via a LINE message. For example, a message such as "You can purchase toilet paper here [link]" may be sent.

[1031] Example prompt

[1032] "Your father's blood pressure is abnormal. Please check it immediately."

[1033] "Mom's temperature is normal."

[1034] "Your stress levels are rising. Relax."

[1035] "I need toilet paper."

[1036] This system will monitor the health status of the elderly in real time, respond immediately if an abnormality occurs, and analyze the user's emotional state to provide appropriate responses and support. It will also be able to quickly respond to requests from users for items necessary for daily life, greatly improving the convenience of daily life.

[1037] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1038] Step 1: Collecting health data

[1039] The device uses a smartphone or wearable device to collect health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. Specifically, the device's app communicates with the healthcare devices via Bluetooth or Wi-Fi to collect data. For example, the device automatically collects blood pressure data at 7:00 a.m.

[1040] Input: Health data from blood pressure monitor, thermometer, and heart rate sensor

[1041] Output: Save acquired health data (body temperature, blood pressure, heart rate) on the device

[1042] Step 2: Send your health data

[1043] The device sends the acquired health data to the server at regular intervals (e.g., every hour) using a secure and fast communication protocol (e.g., HTTPS).

[1044] Input: Health data stored on the device

[1045] Output: Health data sent to the server using HTTPS protocol

[1046] Step 3: Receiving and storing health data

[1047] The server receives the health data sent from the device and automatically stores it in a database.

[1048] Input: Health data sent from the device

[1049] Output: Health data stored in a database

[1050] Step 4: Analyze health data

[1051] The server passes the stored health data to an AI module for analysis, which compares it with past data to detect any abnormal values ​​or patterns.

[1052] Input: Health data stored in a database

[1053] Output: Analysis results by the AI ​​module (outliers and patterns)

[1054] Step 5: Generate and send notifications

[1055] If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately." If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[1056] Input: Analysis results of the AI ​​module

[1057] Output: Sends an emergency or normal notification to the LINE app.

[1058] Step 6: Collect emotion data

[1059] The device uses a camera and microphone to collect the user's facial expressions and voice. Specifically, the camera is activated at regular intervals to capture the user's facial expressions, and the microphone is used to record the user's tone and intonation of voice.

[1060] Input: User facial and voice data

[1061] Output: Emotion data stored on the device

[1062] Step 7: Sending Emotion Data

[1063] The device sends the collected emotion data to a server using a secure and fast communication protocol (e.g., HTTPS).

[1064] Input: Emotion data stored on the device

[1065] Output: Emotion data sent to the server using HTTPS protocol

[1066] Step 8: Analyze the sentiment data

[1067] The emotion engine estimates the user's emotional state based on the collected data and sends the analysis results to the server.

[1068] Input: Emotion data sent to the server

[1069] Output: Analysis results by the emotion engine

[1070] Step 9: Comprehensive analysis and response generation

[1071] The server comprehensively analyzes the user's health and emotional data to detect abnormal emotional or health conditions. Based on the results, the server generates an appropriate response. For example, if the user is feeling stressed, the server generates a message such as, "You seem to be feeling more stressed recently. Please try to find ways to relax."

[1072] Input: Comprehensive analysis results of health data and emotional data

[1073] Output: The appropriate response message

[1074] Step 10: Send a response message

[1075] The server sends the generated response message to the user via the LINE app.

[1076] Input: Server-generated response message

[1077] Output: Response message sent to the LINE app

[1078] Step 11: Receiving a Purchase Request

[1079] Users use the LINE app to send requests for items necessary for daily life via their terminal means.

[1080] Input: Purchase request message sent by the user

[1081] Output: Purchase request message received on the device

[1082] Step 12: Parse the purchase request

[1083] The server receives the request message, analyzes it, and identifies the required product. The server then searches for information about the corresponding product using a standard online shopping API.

[1084] Input: Purchase request message sent from the device

[1085] Output: Product information search results

[1086] Step 13: Generate and send your product offer link

[1087] The server generates the appropriate product link from the search results and sends it to the user via LINE message. Example: "You can buy toilet paper here [link]".

[1088] Input: Product information search results

[1089] Output: LINE message containing the product offer link

[1090] This system will enable real-time monitoring of the health and emotional state of the elderly, and will respond immediately if an abnormality occurs. It will also be able to quickly respond to requests from users for items necessary for daily life, improving the convenience of daily life.

[1091] (Application example 2)

[1092] 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."

[1093] Until now, there has been no system that can monitor not only the health status of elderly people but also the emotional state of passengers in real time to comprehensively improve safety and comfort. Furthermore, autonomous vehicles with many elderly passengers are required to instantly detect abnormalities in their health and emotional states and take appropriate action. Furthermore, a system is needed that can comprehensively analyze passenger health and emotional data and promptly notify passengers and relevant parties when an abnormality is detected.

[1094] The specific processing by the specific 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 terminal means for acquiring health data, means for transmitting the acquired health data to the server, server means for receiving and storing the transmitted health data, AI module means for analyzing the received health data and detecting abnormal values, means for sending an emergency notification if an abnormality is detected based on the analysis results, means for notifying the normal state based on the analysis results, sensor means for acquiring the facial expressions and voice of the occupant and estimating their emotional state, server means for transmitting and analyzing the emotional data, and means for generating and notifying an appropriate response based on the emotional data. This enables real-time monitoring of the health and emotional states of elderly people and promptly sending an emergency notification if an abnormality is detected. Furthermore, providing appropriate responses and support according to the occupant's emotional state can improve safety and comfort.

[1095] "Elderly" refers to people aged 65 and over, and health risks generally increase with age.

[1096] "Health status" refers to the physical condition of an individual, assessed comprehensively from physical data such as body temperature, blood pressure, and heart rate.

[1097] "Monitoring" is the act of acquiring and analyzing data in real time to detect abnormalities and changes.

[1098] A "remote monitoring system" is a system that monitors the health and safety of people in remote locations via the Internet or wireless communications, without the need for physical contact.

[1099] "Terminal means" refers to hardware such as smartphones and wearable devices that are used to collect health data.

[1100] "Server means" refers to a server for receiving, storing, and analyzing data.

[1101] "Data transmission means" refers to the communication protocol or technology used to transmit health data from the terminal to the server.

[1102] "AI module means" is a software module that uses artificial intelligence to analyze data and detect anomalies.

[1103] "Notification means" refers to a method for notifying users of abnormal or normal conditions, and includes messaging services such as the LINE app.

[1104] "Sensor means" refers to devices such as cameras and microphones used to capture emotional data such as facial expressions and voice.

[1105] "Emotion data" is data that indicates the emotional state of the user estimated from facial expressions, voice, etc.

[1106] An "urgent notification" is a warning message that is sent to the user immediately when an abnormality is detected.

[1107] An "appropriate response" is a response that includes support or suggestions appropriate to the user's situation and is generated based on the acquired data.

[1108] A "response generation means" is an AI engine or algorithm that creates an appropriate response based on emotional data.

[1109] The present invention is a remote monitoring system that monitors the health and emotional state of elderly people and provides appropriate responses and support based on the results. This system is designed to ensure the safety and comfort of passengers, especially elderly people, in autonomous vehicles.

[1110] Health Data Collection and Transmission

[1111] Health data collection

[1112] The terminal (smartphone or wearable device) periodically collects health data from devices installed in the car, such as "smart seats," blood pressure sensors, and heart rate sensors. Health data includes body temperature, blood pressure, heart rate, etc.

[1113] Sending data

[1114] The device sends the acquired health data to the server at regular intervals (e.g., every 30 minutes). Communication uses a secure and fast protocol (e.g., HTTPS).

[1115] Data analysis and notification

[1116] Receiving and storing data

[1117] The server receives the health data sent from the terminal and stores it in a database.

[1118] Data analysis

[1119] The server passes the stored health data to an AI module for analysis. The AI ​​module compares it with past data to detect abnormal values ​​and patterns. The analysis uses a generative AI model.

[1120] Sending notifications

[1121] If an abnormality is detected, the server generates an emergency notification and promptly notifies the passengers and maintenance staff via the in-car smart display, voice system, or passenger's smartphone, for example, by sending a prompt message such as "Emergency! Your heart rate is very high. Contact a medical institution immediately."

[1122] Emotion data collection and analysis

[1123] Collecting Emotional Data

[1124] The device collects the passenger's facial expressions and voice using cameras and microphones inside the vehicle, and the emotion engine estimates the passenger's emotional state based on the collected data.

[1125] Emotional Data Analysis

[1126] The server receives and analyzes the emotion data sent from the emotion engine. The server comprehensively analyzes the passenger's health data and emotion data to detect abnormal emotional or health conditions.

[1127] Response and Support

[1128] Generating a response

[1129] Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response for the passenger. For example, if the passenger is feeling stressed, it generates a prompt such as, "Your stress is increasing. Please take a moment to take a deep breath."

[1130] Sending notifications

[1131] Emotional data and health data are comprehensively analyzed, and if an abnormality is detected, the server generates an emergency notification and sends it to the occupants and relevant parties.

[1132] Specific examples

[1133] Health data monitoring and emotion data analysis

[1134] 1. At 7:00 AM, the device acquires blood pressure data and sends it to the server.

[1135] 2. The server receives the data and stores it in a database.

[1136] 3. The server passes the data to the AI ​​module for analysis.

[1137] 4. If the AI ​​module does not detect any abnormalities, the server will notify the smart display that "No abnormalities were detected."

[1138] 5. If an abnormality is detected, the server will notify you: "Urgent! Your blood pressure is very high. Please check."

[1139] 6. At the same time, the device captures the passenger's facial expressions with a camera and the emotion engine analyzes them. If the emotional state is determined to be unstable, the device will notify the passenger, saying, "You've been feeling stressed recently. Try to find ways to relax."

[1140] Hardware and software used

[1141] Camera: Used to capture facial expressions (e.g., a general-purpose camera).

[1142] Sensors: Used to acquire health data (e.g., general-purpose sensors).

[1143] software:

[1144] Server communication: Uses the requests module.

[1145] Image processing: Uses cv2 (OpenCV).

[1146] Time management: time and datetime modules.

[1147] Prompt Sentence Examples

[1148] "Urgent! Heart rate is very high. Call medical help immediately."

[1149] "You've been under a lot of stress lately. Try some relaxation techniques."

[1150] The system can efficiently monitor the health and emotional state of passengers, enabling immediate response to abnormal situations and providing appropriate responses and obedient actions, thereby improving the safety and comfort of autonomous vehicles.

[1151] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1152] Step 1:

[1153] The device collects health data of passengers using the "smart seat" installed in the vehicle and various sensors (blood pressure sensor, heart rate sensor). This data includes body temperature, blood pressure, and heart rate. The input is an analog signal from the sensor, which is converted to a digital signal and stored in the device. The output is the collected health data.

[1154] Step 2:

[1155] The device sends the acquired health data to the server at regular intervals (e.g., every 30 minutes). The device specifically sends data securely using the HTTPS protocol. The input is the health data acquired in step 1, and the output is the data sent to the server.

[1156] Step 3:

[1157] The server receives the health data sent from the device and stores it in a database. Here, the health data sent from the device is the input, and the data stored in the database is the output. The stored data accumulates over time.

[1158] Step 4:

[1159] The server passes the accumulated health data to an AI module for analysis. The AI ​​module compares it with past data to detect abnormal patterns. The input is health data stored in a database, and the output is the result of AI anomaly detection. A generative AI model is used for the analysis.

[1160] Step 5:

[1161] If the server detects an abnormality based on the analysis results, it generates an emergency notification and sends it to the in-car smart display, voice system, and passengers' smartphones. Specific emergency notifications include prompts such as "Emergency! Your heart rate is very high. Contact a medical institution immediately." The input is the anomaly detection result from the AI ​​module, and the output is the generated emergency notification, which is then sent.

[1162] Step 6:

[1163] At the same time, the device uses cameras and microphones inside the vehicle to collect facial expressions and voices of the occupants. The input is analog signals from the cameras and microphones, which are converted into digital data and output as data sent to the emotion engine.

[1164] Step 7:

[1165] The emotion engine estimates the emotional state of the passenger based on the collected data. It uses AI technology to analyze voice and facial expression data to estimate the emotional state (e.g., stress, anxiety, etc.). The input is the digital data obtained in step 6, and the output is the analyzed emotional state.

[1166] Step 8:

[1167] The emotion engine sends the analyzed emotion data to the server, and the server generates an appropriate response based on that data. For example, if the emotion data indicates stress, it generates a prompt such as "Your stress is increasing. Take a moment to take a deep breath." The input is the analyzed data from the emotion engine, and the output is the generated prompt.

[1168] Step 9:

[1169] The server comprehensively analyzes the health data and emotional data, and if an abnormality is detected, generates an emergency notification and sends it to the crew and relevant parties. For example, it generates a comprehensive notification such as "Emergency! Your heart rate is very high and your stress level is also high. Please check." Both health data and emotional data are input, and a comprehensive emergency notification is generated as output.

[1170] This process flow realizes a system that can monitor the health and emotional state of passengers in real time and respond immediately.

[1171] 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.

[1172] 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.

[1173] 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.

[1174] [Third embodiment]

[1175] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1176] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1177] 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).

[1178] 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.

[1179] 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.

[1180] 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).

[1181] 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.

[1182] 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.

[1183] 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.

[1184] 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.

[1185] 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.

[1186] 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."

[1187] The present invention provides a remote monitoring system that monitors the health status of elderly people, detects abnormalities, and provides support for purchasing items necessary for daily life. Specific embodiments of the system will be described below.

[1188] Health Data Collection and Transmission

[1189] Health data collection

[1190] 1. The device (smartphone or wearable device) periodically collects health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors.

[1191] 2. Health data includes body temperature, blood pressure, heart rate, etc.

[1192] Sending data

[1193] 1. The device sends the collected health data to the server at regular intervals (e.g., every hour).

[1194] 2. Data transmission is carried out using secure and fast communication protocols.

[1195] Data analysis and notification

[1196] Receiving and storing data

[1197] 1. The server receives the health data sent from the device and stores it in a database.

[1198] Data analysis

[1199] 1. The server passes the received health data to the AI ​​module.

[1200] 2. The AI ​​module analyzes the data to see if there are any abnormal values ​​or patterns, comparing them with past data.

[1201] Sending notifications

[1202] 1. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately."

[1203] 2. If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning is 36.5 degrees, which is normal."

[1204] Purchase assistance

[1205] Receiving product requests

[1206] 1. The user or elderly person sends a request for an item necessary for daily life using the LINE app. Example: "I need toilet paper."

[1207] Handling the request

[1208] 1. The server receives the request message from the user, analyzes it, and identifies the required product.

[1209] 2. The server searches for information about the relevant product using the Yahoo Shopping API.

[1210] Generate and send the link

[1211] 1. The server generates appropriate product offer links from the search results.

[1212] 2. The server sends the generated link to the user via LINE message. Example: "You can buy toilet paper here [LINK]".

[1213] Specific examples

[1214] Health Data Monitoring

[1215] At 7:00 a.m., the device acquires blood pressure data and sends it to the server. The server passes the data to the AI ​​module for analysis. If the analysis results are normal, a LINE notification is sent stating, "Mom's blood pressure this morning is 120 / 80, which is normal." If an abnormality is detected, a notification is sent stating, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[1216] Assisted Buy execution

[1217] A user sends a message on LINE saying, "I need toilet paper." The server receives and analyzes the message, searches for the relevant product using the Yahoo Shopping API, generates a link, and replies, "You can buy toilet paper here [link]."

[1218] This system will enable efficient monitoring of the health status of the elderly, enable immediate response to emergencies, and improve the convenience of their daily lives.

[1219] The processing flow will be explained below.

[1220] Health data collection and analysis

[1221] Health data collection

[1222] Step 1:

[1223] The device acquires health data from linked healthcare devices (e.g., thermometers and blood pressure monitors).

[1224] Step 2:

[1225] The device transmits the acquired health data to the server at regular intervals (for example, every hour).

[1226] Data analysis

[1227] Step 3:

[1228] The server receives the health data sent from the device and stores it in a database.

[1229] Step 4:

[1230] The server passes the stored health data to an AI module for analysis.

[1231] Step 5:

[1232] The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[1233] Sending notifications

[1234] Step 6:

[1235] The server generates an emergency notification if an anomaly is detected based on the analysis results of the AI ​​module.

[1236] Step 7:

[1237] The server sends the generated emergency notification to the user (family member) via the LINE app.

[1238] For example: "Urgent! Dad's heart rate is over 160. Please check immediately."

[1239] Step 8:

[1240] If no abnormality is detected, the server notifies the user of the normal status.

[1241] For example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[1242] Purchase assistance

[1243] Receiving product requests

[1244] Step 9:

[1245] Users or elderly people use the LINE app to send requests for items necessary for daily life.

[1246] For example: "I need toilet paper."

[1247] Handling the request

[1248] Step 10:

[1249] The server analyzes the request message received from the user and identifies the required product.

[1250] Step 11:

[1251] The server uses the Yahoo Shopping API to search for information about the relevant product.

[1252] Generate and send the link

[1253] Step 12:

[1254] The server generates appropriate product offering links from the search results.

[1255] Step 13:

[1256] The server sends the generated link to the user via a LINE message.

[1257] For example: "You can buy toilet paper here [link]"

[1258] Specific examples

[1259] Health Data Monitoring

[1260] Step 1:

[1261] The device collects blood pressure data at 7:00 a.m.

[1262] Step 2:

[1263] The terminal transmits the acquired data to the server.

[1264] Step 3:

[1265] The server receives the data and stores it in a database.

[1266] Step 4:

[1267] The server passes the data to the AI ​​module for analysis.

[1268] Step 5:

[1269] The AI ​​module analyzes the data and returns the results to the server.

[1270] Step 6:

[1271] Based on the analysis results, the server will either notify you of a normal condition or generate an emergency notification.

[1272] Step 7:

[1273] If the result is normal, the server sends a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[1274] Step 8:

[1275] If an abnormality is detected, the server will send a LINE notification saying, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[1276] Assisted Buy execution

[1277] Step 1:

[1278] A user sends a message on LINE saying, "I need toilet paper."

[1279] Step 2:

[1280] The server receives and parses the message.

[1281] Step 3:

[1282] The server calls the Yahoo Shopping API and searches for the relevant product.

[1283] Step 4:

[1284] The server generates a product offer link from the search results.

[1285] Step 5:

[1286] The server replies with a link via LINE saying, "You can buy toilet paper here [link]."

[1287] Example 1

[1288] 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."

[1289] While there is a need to monitor the health status of the elderly and respond to emergencies, there is a lack of efficient ways to do this remotely. Support for purchasing necessary items is also essential for the elderly's daily lives, but this process must be simple. Conventional systems do not integrate real-time health monitoring, prompt notification in the event of an abnormality, and support for purchasing items, causing inconvenience to the elderly and their families.

[1290] 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.

[1291] In this invention, the server includes means for transmitting health data acquired from the terminal means to the server, means for receiving the transmitted health data and storing it in a database, means for passing the received health data to an AI module and comparing it with past data to detect abnormal values, means for generating an emergency notification and notifying the user via a communication application if an abnormality is detected, means for notifying the user of a normal condition if no abnormality is detected, means for receiving an item purchase request from the user, identifying an appropriate item, and generating a provision link, and means for transmitting the generated link to the user via the communication application. This enables comprehensive monitoring of the health status of elderly people, enabling prompt response in the event of an abnormality, and efficient support for purchasing items necessary for daily life.

[1292] "Terminal means" refers to hardware devices such as smartphones and wearable devices for collecting health data.

[1293] The "server means" is a central processing device that receives data sent from the terminal means and stores and analyzes it.

[1294] "AI module means" is a software or hardware configuration having artificial intelligence algorithms for analyzing received health data and detecting abnormal values.

[1295] "Means for generating an emergency notification and notifying the user through a communication application" refers to a mechanism that creates a notification message when an abnormality is detected and sends the message to the user using a communication application such as LINE.

[1296] The "means for notifying the user of a normal state" is a mechanism for generating and sending a message to the user informing them of a normal state when no abnormalities are found in the health data.

[1297] The "means for receiving a product purchase request, identifying an appropriate product, and generating a provision link" is a mechanism for analyzing a purchase request from a user, identifying the appropriate product, and generating a purchase link for that product.

[1298] "Means of sending via a communication application" refers to a mechanism for sending the generated product offer link or notification message to the user using a communication application such as LINE.

[1299] The present invention provides a remote monitoring system that remotely monitors the health status of elderly people, detects abnormalities, and provides support for purchasing items necessary for daily life. Specific embodiments of the system are described below.

[1300] Health Data Collection and Transmission

[1301] First, we will discuss the "collection and transmission of health data" in this invention. The terminal means is a smartphone or wearable device for collecting health data. Specifically, it works in conjunction with healthcare devices such as a blood pressure monitor, thermometer, and heart rate sensor to periodically acquire data. For example, a wearable device such as the Apple Watch uses Bluetooth to acquire blood pressure data from a blood pressure monitor and transmit it to a smartphone.

[1302] The terminal means transmits the collected data to the server means at regular intervals (for example, every hour). This data transmission uses the HTTPS protocol, which enables secure and fast data communication.

[1303] Data analysis and notification

[1304] Next, we will discuss "Data Analysis and Notification." The server means receives the health data sent from the terminal means and stores it in a database. The database records the health data for each user, and uses a database system such as MySQL.

[1305] The received data is analyzed by the AI ​​module means. The AI ​​module uses machine learning algorithms such as TensorFlow to compare it with past data and detect abnormal values ​​or patterns. If an abnormality is detected, the server means generates an emergency notification and promptly notifies the user through a communication application such as the LINE app. For example, a message such as "Urgent! Dad's heart rate has exceeded 160. Please check immediately" may be sent.

[1306] On the other hand, if no abnormality is detected, the server means notifies the user of the normal state, for example, a message such as "Mom's temperature this morning is 36.5 degrees, which is normal" is sent to the user.

[1307] Purchase assistance

[1308] Finally, we will explain "purchase assistance." Users or elderly people can use the LINE app to send requests for items necessary for daily life. For example, they can send a message saying, "I need toilet paper."

[1309] The server receives this request message and uses natural language processing (NLP) to identify the required product. The server then calls the Yahoo Shopping API and searches for information on the relevant product. It then generates an appropriate product link from the search results and sends it to the user via LINE message. For example, a message such as "You can purchase toilet paper here [link]" is sent.

[1310] Specific operation example

[1311] Health Data Monitoring

[1312] At 7:00 AM, the terminal means (e.g., smartwatch) automatically measures blood pressure and sends the data to the server means. The server means then passes the data to the AI ​​module, which analyzes whether there is an abnormality. If normal, it notifies the user, "Mom's blood pressure this morning is 120 / 80, which is normal," and if an abnormality is detected, it notifies the user, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[1313] Assisted Buy execution

[1314] The user sends a message on LINE saying, "I need toilet paper." The server receives the message and identifies "toilet paper" through NLP. It then retrieves information about the product using the Yahoo Shopping API and replies, "You can buy toilet paper here [link]."

[1315] This system will enable efficient monitoring of the health status of elderly people, enabling rapid response in emergencies and improving convenience in daily life.

[1316] Prompt Sentence Examples

[1317] Below is an example of a prompt sentence that will be input to the generative AI model.

[1318] Please describe in natural language a remote monitoring system that collects health data on elderly people and sends notifications when abnormalities are detected based on that data. Please also provide specific examples of the notification messages, including the specific names of the hardware and software used.

[1319] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1320] Step 1:

[1321] Health data collection

[1322] The device acquires health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. Specifically, the device (e.g., a smartwatch) acquires blood pressure data from the blood pressure monitor and receives body temperature data from the thermometer via Bluetooth. The heart rate sensor directly transmits heart rate data to the device. Health data includes body temperature, blood pressure, and heart rate.

[1323] Input: Health data from healthcare devices

[1324] Output: Health data temporarily stored in the device

[1325] Step 2:

[1326] Sending data

[1327] The device sends the collected health data to the server at regular intervals (e.g., every hour). The HTTPS protocol is used for data transmission, ensuring secure data transfer. The device temporarily stores the collected data and sends it in batches at specified intervals.

[1328] Input: Health data temporarily stored in the device

[1329] Output: Health data sent to the server

[1330] Step 3:

[1331] Receiving and storing data

[1332] The server receives the health data sent from the device. The received data is parsed in JSON format and stored in a database. A database management system such as MySQL is used for the database, and the health data is managed in chronological order.

[1333] Input: Health data sent from the device

[1334] Output: Health data stored in a database

[1335] Step 4:

[1336] Data analysis

[1337] The server then passes the received health data to the AI ​​module, which compares it with past data and analyzes it for outliers and abnormal patterns. The AI ​​module uses machine learning frameworks such as TensorFlow to run models to detect outliers.

[1338] Input: Health data retrieved from a database

[1339] Output: Anomaly information analyzed by the AI ​​module

[1340] Step 5:

[1341] Generate and send anomaly notifications

[1342] If an abnormality is detected, the server generates an emergency notification and promptly notifies the user through a communication application such as the LINE app. For example, a message such as "Urgent! Dad's heart rate has exceeded 160. Please check immediately" is generated. The notification is sent using the LINE Messaging API.

[1343] Input: Anomaly information analyzed by the AI ​​module

[1344] Output: Urgent notification message sent to the user

[1345] Step 6:

[1346] Normal status notification

[1347] If no abnormalities are detected, the server generates a message informing the user of the normal condition, for example, "Mom's temperature this morning is 36.5 degrees, which is normal."

[1348] Input: Normal information analyzed by the AI ​​module

[1349] Output: Normal status notification message sent to the user

[1350] Step 7:

[1351] Receiving a purchase request

[1352] Users send requests for items necessary for daily life to the server through the LINE app. For example, they can send a message such as "I need toilet paper" via LINE. The server receives the message from the user using the LINE API.

[1353] Input: The request message sent by the user

[1354] Output: The request message received by the server

[1355] Step 8:

[1356] Parsing purchase requests

[1357] The server analyzes the received request message and identifies the required product. It uses natural language processing (NLP) techniques to analyze and identify the requested item.

[1358] Input: The request message received by the server

[1359] Output: Requested item information

[1360] Step 9:

[1361] Generate and send product offer links

[1362] The server calls the Yahoo Shopping API based on the identified product information and searches for information on the corresponding product. It then generates an appropriate product link from the search results and sends it to the user via a communication application. For example, it generates a message such as "You can buy toilet paper here [link]."

[1363] Input: Requested item information

[1364] Output: Offer link sent to user

[1365] (Application example 1)

[1366] 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."

[1367] Remote health monitoring systems for the elderly have the problem of being unable to immediately respond to health risks, especially when the elderly visit a store. Furthermore, they provide insufficient support for elderly people's everyday purchases, which can lead to a decline in their quality of life. Furthermore, if health monitoring of the elderly in a store is not performed in real time, there is also the problem of being unable to respond quickly to abnormalities.

[1368] 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.

[1369] In this invention, the server includes a terminal means for acquiring health data, a means for transmitting the acquired health data to the server, a means for receiving and storing the transmitted health data, an AI module means for analyzing the received health data and detecting abnormal values, a means for sending an emergency notification if an abnormality is detected based on the analysis results, a means for notifying a normal condition based on the analysis results, a means for collecting health data of visitors in real time using an in-store health monitoring terminal, and a means for analyzing the collected health data and notifying a store clerk if an abnormality is detected. This not only enables real-time monitoring of the health status of elderly people and emergency response when they visit, but also enables efficient support for purchasing items necessary for daily life.

[1370] "Terminal means for acquiring health data" refers to devices or equipment used to collect health information such as body temperature, blood pressure, and heart rate of elderly people.

[1371] "Means for transmitting acquired health data to a server" refers to a communication device or communication protocol for transmitting collected health data to a server via a network.

[1372] The "server means for receiving and storing transmitted health data" is a server system for receiving health data transmitted from a terminal and storing it in a database.

[1373] The "AI module means for analyzing received health data and detecting abnormal values" is an artificial intelligence module for analyzing health data stored on the server and detecting abnormal values.

[1374] "Means for sending an emergency notification when an abnormality is detected based on the analysis results" refers to a communication means for sending an emergency notification to the user when the AI ​​module detects an abnormality.

[1375] "Means for notifying the user of a normal state based on the analysis results" refers to a communication means for notifying the user of a normal health state if the AI ​​module does not detect any abnormalities.

[1376] "Means for collecting visitor health data in real time using health monitoring terminals in the store" refers to equipment for collecting visitor health data in real time using terminals installed in the store.

[1377] "Means for analyzing collected health data and notifying store staff if an abnormality is detected" refers to a communication means for analyzing health data collected in the store and sending an emergency notification to store staff if an abnormality is detected.

[1378] The present invention is a remote monitoring system that monitors the health status of elderly people, detects abnormalities, monitors the health of visitors in real time, and provides purchasing support. Specific embodiments will be described below.

[1379] Health Data Collection and Transmission

[1380] Health data collection

[1381] Terminals (smartphones, tablets, wearable devices) connect to healthcare devices such as blood pressure monitors, heart rate sensors, and thermometers to periodically collect health data, including body temperature, blood pressure, and heart rate.

[1382] Sending data

[1383] The device sends the collected health data to a server at regular intervals (e.g., every hour) using a secure and fast communication protocol.

[1384] Data analysis and notification

[1385] Receiving and storing data

[1386] The server receives the health data sent from the device and stores it in a database. Specific server systems used include AWS and Google Cloud Platform.

[1387] Data analysis

[1388] The server passes the received health data to an AI module (e.g., a model using TensorFlow or PyTorch), which then compares the data with past data and analyzes it for abnormal values ​​or patterns.

[1389] Sending notifications

[1390] If an abnormality is detected, the server generates an emergency notification and promptly notifies the user (e.g., family or caregiver) using a communication method (e.g., LINE API, SMS API). If no abnormality is detected, the server notifies the user of their normal health status.

[1391] In-store health monitoring and purchasing assistance

[1392] In-store health monitoring

[1393] Health monitoring devices (e.g., kiosks, tablets) installed in stores collect visitors' health data in real time. The collected health data is sent to a server and analyzed by an AI module. If an abnormality is detected, the server sends an emergency notification to the store staff's device (e.g., smartphone, in-store display).

[1394] Purchase assistance

[1395] Users or seniors use in-store terminals or wearable devices to send requests for items necessary for daily life. The server receives and analyzes the request message, then generates and notifies the user of the appropriate product link. Product information is searched using APIs such as Yahoo Shopping.

[1396] Specific examples

[1397] Health Data Monitoring

[1398] At 7:00 AM, the device acquires blood pressure data and sends it to the server. The server passes the data to an AI module (e.g., TensorFlow model) for analysis. If the analysis results are normal, a LINE notification is sent stating, "This morning's blood pressure is 120 / 80, which is normal." If an abnormality is detected, a notification is sent stating, "Urgent! Your blood pressure is 180 / 110. Please check immediately."

[1399] Assisted Buy execution

[1400] The user sends a request to a terminal in the store saying, "I need toilet paper." The server receives the request, analyzes it, searches for the relevant product from the Yahoo Shopping API, generates a link, and notifies the user, "You can buy toilet paper here [link]."

[1401] Example prompts for generative AI models

[1402] Generate the following Python program:

[1403] I want to develop an application that collects health data (heart rate, blood pressure, body temperature) of elderly people and sends it to a server.

[1404] The data sent to the server detects any abnormalities and notifies store staff or managers as necessary.

[1405] For data collection, we use the requests library, and for notifications, we use SMS or the LINE API.

[1406] Abnormal thresholds are a heart rate above 100, blood pressure above 160 / 100, and body temperature above 38°C.

[1407] Set these thresholds within your program and include a process to notify you when an anomaly is detected.

[1408] The above is a specific embodiment of the present invention. This system can efficiently monitor the health status of elderly people and provide emergency response in stores. It can also provide support for purchasing items necessary for daily life.

[1409] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1410] Step 1:

[1411] The device acquires health data. Specifically, the device (smartphone, tablet, wearable device) measures body temperature, blood pressure, and heart rate from healthcare devices such as blood pressure monitors, heart rate sensors, and thermometers, and collects health data. At this stage, the input is the raw data acquired from the healthcare devices, and the output is the collected health data (e.g., body temperature 36.5°C, blood pressure 120 / 80, heart rate 75).

[1412] Step 2:

[1413] The collected health data is sent to the server. The device uses a secure and fast communication protocol (e.g., HTTPS) to send the acquired health data to the server at regular intervals (e.g., every hour). The input is the health data acquired in step 1, and the output is the health data sent to the server. Specifically, the data is encrypted and sent using the communication protocol.

[1414] Step 3:

[1415] The server stores the received health data. The server receives the health data sent from the device and stores it in a database. Specific server systems include AWS RDS and Google Cloud SQL. The input is the sent health data, and the output is the health data stored in the database. Specific operations include receiving data and storing it in the database.

[1416] Step 4:

[1417] The server analyzes the received data and detects abnormal values. The server passes the stored health data to an AI module (e.g., TensorFlow or PyTorch), which compares it with past data and analyzes whether there are any abnormal values ​​or patterns. The input is the stored past health data and newly received health data, and the output is the analysis results. Specifically, data analysis is performed using a machine learning model.

[1418] Step 5:

[1419] An emergency notification is sent if an abnormality is detected. If the server detects an abnormality based on the analysis results, it generates an emergency notification and notifies the user using a communication method (e.g., LINE API, short message API). The input is the analysis result (whether or not there is an abnormality), and the output is the emergency notification that was sent. Specifically, when an abnormality is detected, a notification message is generated and sent.

[1420] Step 6:

[1421] Notifies normal status. If the server detects no abnormalities based on the analysis results, it notifies normal health status. The input is the analysis result (normal value), and the output is the sent notification. Specifically, when a normal condition is detected, a notification message is generated and sent.

[1422] Step 7:

[1423] In-store health monitoring terminals collect visitors' health data in real time. Terminals installed in the store (e.g., kiosks, tablets) measure visitors' blood pressure, body temperature, and heart rate and collect health data. The input is raw data from the in-store healthcare devices, and the output is the collected health data.

[1424] Step 8:

[1425] Health data from within the store is sent to the server for analysis. The collected health data is sent to the server, where it is analyzed by the AI ​​module. The input is the collected health data and past data, and the output is the analysis results. The specific operation is the same as steps 2 to 4.

[1426] Step 9:

[1427] If an abnormality is detected, the store clerk is notified. If an abnormality is detected based on the analysis results, the server sends an emergency notification to the store clerk's device (e.g., smartphone, in-store display). The input is the analysis result, and the output is the emergency notification sent to the store clerk.

[1428] Step 10:

[1429] A user requests an item needed for daily life. The user or elderly person sends a request for the needed item using an in-store terminal or a wearable device. The input is the request message created by the user, and the output is the request sent to the server.

[1430] Step 11:

[1431] The server analyzes the request and generates a product offer link. The server receives the request message, analyzes it, and generates an appropriate product offer link (e.g., Yahoo Shopping API). The input is the request message, and the output is the generated product offer link.

[1432] Step 12:

[1433] The product provision link is notified to the user. The server notifies the user of the generated product provision link. The input is the product provision link, and the output is the sent notification message. The specific operations are link generation and notification message transmission.

[1434] 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.

[1435] The present invention provides a remote monitoring system that monitors the health status of an elderly person, detects abnormalities, analyzes the user's emotions, and provides appropriate responses and support. Specific embodiments of the system are described below.

[1436] Health Data Collection and Transmission

[1437] Health data collection

[1438] 1. The device (smartphone or wearable device) periodically collects health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors.

[1439] 2. Health data includes body temperature, blood pressure, heart rate, etc.

[1440] Sending data

[1441] 1. The device sends the acquired health data to the server at regular intervals (e.g., every hour).

[1442] 2. Data transmission is carried out using secure and fast communication protocols.

[1443] Data analysis and notification

[1444] Receiving and storing data

[1445] 1. The server receives the health data sent from the device and stores it in a database.

[1446] Data analysis

[1447] 1. The server passes the stored health data to the AI ​​module for analysis.

[1448] 2. The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[1449] Sending notifications

[1450] 1. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately."

[1451] 2. If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning is 36.5 degrees, which is normal."

[1452] Emotion data collection and analysis

[1453] Collecting Emotional Data

[1454] 1. The device collects the user's facial expressions and voice using sensors such as a camera and microphone.

[1455] 2. The emotion engine estimates the user's emotional state based on the collected data.

[1456] Emotional Data Analysis

[1457] 1. The server receives and analyzes the emotion data sent from the emotion engine.

[1458] 2. The server comprehensively analyzes the user's health data and emotional data to detect abnormal emotional and health states.

[1459] Response and Support

[1460] Generating a response

[1461] 1. Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response to the user.

[1462] 2. Example) If the user is feeling stressed: "You seem to be feeling more stressed lately. Try some relaxation techniques."

[1463] Sending notifications

[1464] 1. Comprehensively analyzes emotional and health data, and if an abnormality is detected, the server generates an emergency notification and sends it to the user (family member) via the LINE app. Example: "Emergency! Mom's heart rate is over 160 and her emotional state is unstable. Please check on her immediately."

[1465] Purchase assistance

[1466] Receiving product requests

[1467] 1. The user or elderly person sends a request for an item necessary for daily life using the LINE app. Example: "I need toilet paper."

[1468] Handling the request

[1469] 1. The server receives the request message from the user, analyzes it, and identifies the required product.

[1470] 2. The server searches for information about the relevant product using the Yahoo Shopping API.

[1471] Generate and send the link

[1472] 1. The server generates appropriate product offer links from the search results.

[1473] 2. The server sends the generated link to the user via LINE message. Example: "You can buy toilet paper here [LINK]".

[1474] Specific examples

[1475] Health data monitoring and emotion data analysis

[1476] 1. At 7:00 a.m., the device acquires blood pressure data and sends it to the server.

[1477] 2. The server receives the data and stores it in a database.

[1478] 3. The server passes the data to the AI ​​module for analysis.

[1479] 4. If the AI ​​module does not detect any abnormalities, the server will send a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[1480] 5. If an abnormality is detected, the server will notify, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[1481] 6. At the same time, the device captures the user's facial expressions with a camera, which the emotion engine analyzes. If the emotional state is determined to be unstable, the server will notify the user, saying, "You've been feeling stressed lately. Please try some relaxation techniques."

[1482] Assisted Buy execution

[1483] 1. A user sends a message on LINE saying, "I need toilet paper."

[1484] 2. The server receives the message, analyzes it, searches for the relevant product using the Yahoo Shopping API, generates a link, and replies with "You can buy toilet paper here [link]."

[1485] This system will enable efficient monitoring of the health status of elderly people and enable immediate response to any abnormalities, as well as analyze the user's emotional state and provide appropriate responses and support, improving the convenience of everyday life.

[1486] The processing flow will be explained below.

[1487] Health data collection and analysis

[1488] Health data collection

[1489] Step 1:

[1490] The device acquires health data from linked healthcare devices (e.g., thermometers and blood pressure monitors).

[1491] Step 2:

[1492] The device transmits the acquired health data to the server at regular intervals (for example, every hour).

[1493] Data analysis

[1494] Step 3:

[1495] The server receives the health data sent from the device and stores it in a database.

[1496] Step 4:

[1497] The server passes the stored health data to an AI module for analysis.

[1498] Step 5:

[1499] The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[1500] Sending notifications

[1501] Step 6:

[1502] The server generates an emergency notification if an anomaly is detected based on the analysis results of the AI ​​module.

[1503] Step 7:

[1504] The server sends the generated emergency notification to the user (family member) via the LINE app.

[1505] For example: "Urgent! Dad's heart rate is over 160. Please check immediately."

[1506] Step 8:

[1507] If no abnormality is detected, the server notifies the user of the normal status.

[1508] For example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[1509] Emotion data collection and analysis

[1510] Collecting Emotional Data

[1511] Step 9:

[1512] The device collects the user's facial expressions and voice using sensors such as a camera and microphone.

[1513] Step 10:

[1514] The terminal sends the collected data to an emotion engine to estimate the user's emotional state.

[1515] Emotional Data Analysis

[1516] Step 11:

[1517] The server receives the emotion data sent from the emotion engine and stores it in a database.

[1518] Step 12:

[1519] The server passes the desired emotional data to the AI ​​module for analysis.

[1520] Step 13:

[1521] The server comprehensively analyzes the user's health data and emotional data to detect abnormal emotional and health states.

[1522] Response and Support

[1523] Generating a response

[1524] Step 14:

[1525] Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response to the user.

[1526] For example, if the user is feeling stressed: "You seem to be feeling more stressed lately. Try some relaxation techniques."

[1527] Sending notifications

[1528] Step 15:

[1529] Emotional data and health data are analyzed comprehensively, and if an abnormality is detected, the server generates an emergency notification and sends it to the user (family) via the LINE app.

[1530] For example: "Urgent! Mom's heart rate is over 160 and she's in an unstable emotional state. Please check in immediately."

[1531] Purchase assistance

[1532] Receiving product requests

[1533] Step 16:

[1534] Users or elderly people use the LINE app to send requests for items necessary for daily life.

[1535] For example: "I need toilet paper."

[1536] Handling the request

[1537] Step 17:

[1538] The server analyzes the request message received from the user and identifies the required product.

[1539] Step 18:

[1540] The server uses the Yahoo Shopping API to search for information about the relevant product.

[1541] Generate and send the link

[1542] Step 19:

[1543] The server generates appropriate product offering links from the search results.

[1544] Step 20:

[1545] The server sends the generated link to the user via a LINE message.

[1546] For example: "You can buy toilet paper here [link]"

[1547] Specific examples

[1548] Health data monitoring and emotion data analysis

[1549] Step 1:

[1550] The device collects blood pressure data at 7:00 a.m.

[1551] Step 2:

[1552] The terminal transmits the acquired data to the server.

[1553] Step 3:

[1554] The server receives the data and stores it in a database.

[1555] Step 4:

[1556] The server passes the data to the AI ​​module for analysis.

[1557] Step 5:

[1558] The AI ​​module analyzes the data and returns the results to the server.

[1559] Step 6:

[1560] Based on the analysis results, the server will either notify you of a normal condition or generate an emergency notification.

[1561] Step 7:

[1562] If the result is normal, the server sends a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[1563] Step 8:

[1564] If an abnormality is detected, the server will send a LINE notification saying, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[1565] Step 9:

[1566] At the same time, the device captures the user's facial expressions with a camera, which are then analyzed by the emotion engine.

[1567] Step 10:

[1568] If the emotional state is determined to be unstable, the server will notify the user, "You've been feeling stressed lately. Try some relaxation techniques."

[1569] Assisted Buy execution

[1570] Step 1:

[1571] A user sends a message on LINE saying, "I need toilet paper."

[1572] Step 2:

[1573] The server receives and parses the message.

[1574] Step 3:

[1575] The server calls the Yahoo Shopping API and searches for the relevant product.

[1576] Step 4:

[1577] The server generates a product offer link from the search results.

[1578] Step 5:

[1579] The server replies with a link via LINE saying, "You can buy toilet paper here [link]."

[1580] Example 2

[1581] 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."

[1582] Continuously monitoring the health status of elderly people and immediately detecting and responding to abnormalities or emergencies are important challenges in today's aging society. It is also necessary to understand the emotional state of elderly people and provide appropriate support. However, current systems lack the ability to collect and analyze health and emotional data, preventing effective monitoring and support. Furthermore, there is a growing demand for systems that can quickly respond to users' requests for everyday items.

[1583] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a mobile information terminal means for acquiring health data, a means for transmitting the acquired health data to the central processing unit, a central processing unit means for receiving and storing the transmitted health data, an artificial intelligence module means for analyzing the received health data and detecting abnormal values, a means for sending an emergency notification if an abnormality is detected based on the analysis results, a means for notifying the user of a normal state based on the analysis results, a mobile information terminal means and an emotion engine means for collecting and analyzing emotion data, a means for generating and notifying an appropriate response based on the emotion data, and a means for receiving purchase requests from users and generating and transmitting an appropriate product provision link. This enables real-time monitoring of the health and emotional states of elderly people and immediate response when an abnormality occurs. Furthermore, the server can quickly respond to user requests, improving convenience in daily life.

[1584] "Terminal means" refers to a portable information terminal for collecting health data and emotional data and transmitting them to a server.

[1585] "Central processing unit means" refers to a processing unit that receives, stores, and analyzes data sent from the terminal.

[1586] "Artificial intelligence module means" refers to an artificial intelligence system that has the function of analyzing received data and detecting abnormal values.

[1587] "Means for sending emergency notifications" refers to a function that promptly sends a warning or notification to the user when an abnormality is detected.

[1588] "Means for notifying normal status" refers to a function that notifies the user when there is no abnormality in the health data.

[1589] "Emotion engine means" refers to a system that has the function of analyzing the user's emotional data and understanding their state.

[1590] The "means for generating and notifying an appropriate response" refers to a function for generating an appropriate response message for the user based on the analysis results of the emotion data and transmitting that message.

[1591] "Means for receiving a purchase request, generating a product provision link, and transmitting the same" refers to a function for receiving a purchase request from a user, generating an appropriate product provision link based on the request, and transmitting the link to the user.

[1592] The present invention provides a remote monitoring system that monitors the health status of elderly people, detects abnormalities, analyzes the user's emotions, and provides appropriate responses and support. This system includes the following components:

[1593] Terminal means

[1594] The terminal means consists of a smartphone or wearable device, and has the function of periodically acquiring health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. For example, the terminal automatically collects blood pressure data at 7:00 a.m. The terminal communicates with the healthcare devices using Bluetooth or Wi-Fi to acquire the data.

[1595] central processing unit means

[1596] The health data sent from the terminal is received by the central processing unit. The central processing unit is composed of a server, and the server stores the received data in a database. The database stores health data such as body temperature, blood pressure, and heart rate.

[1597] Artificial Intelligence Module Means

[1598] The health data stored in the central processing unit means is analyzed by the artificial intelligence module means. The AI ​​module compares it with past data and detects the presence of abnormal values ​​or patterns. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app.

[1599] Emergency and regular notifications

[1600] If an abnormality is detected, the server will send an emergency notification, such as a message saying, "Urgent! Dad's heart rate has exceeded 160. Please check immediately." If no abnormality is detected, the server will notify the normal condition, such as a message saying, "Mom's temperature this morning is 36.5 degrees, which is normal."

[1601] Emotion Data and Emotion Engine Methods

[1602] The terminal means uses a camera and microphone to collect the user's facial expressions and voice and transmits them to the emotion engine means. The emotion engine means estimates the user's emotional state based on the collected data. The analysis results are transmitted to a server, which comprehensively analyzes the user's health data and emotional data to detect abnormal emotional or health states.

[1603] A means of generating and notifying responses

[1604] Based on the analysis results of the emotion engine, the server generates an appropriate response for the user. For example, if the user is feeling stressed, the server generates a message such as "You seem to be feeling more stressed recently. Try to find ways to relax," and sends it through the LINE app.

[1605] Purchase Request Processing

[1606] Users use the LINE app to send requests for items necessary for daily life on their devices. The server receives the request message, analyzes it, and identifies the required products. The server then searches for information about the relevant product using a common online shopping API and generates an appropriate product link. This link is then sent to the user via a LINE message. For example, a message such as "You can purchase toilet paper here [link]" may be sent.

[1607] Example prompt

[1608] "Your father's blood pressure is abnormal. Please check it immediately."

[1609] "Mom's temperature is normal."

[1610] "Your stress levels are rising. Relax."

[1611] "I need toilet paper."

[1612] This system will monitor the health status of the elderly in real time, respond immediately if an abnormality occurs, and analyze the user's emotional state to provide appropriate responses and support. It will also be able to quickly respond to requests from users for items necessary for daily life, greatly improving the convenience of daily life.

[1613] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1614] Step 1: Collecting health data

[1615] The device uses a smartphone or wearable device to collect health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. Specifically, the device's app communicates with the healthcare devices via Bluetooth or Wi-Fi to collect data. For example, the device automatically collects blood pressure data at 7:00 a.m.

[1616] Input: Health data from blood pressure monitor, thermometer, and heart rate sensor

[1617] Output: Save acquired health data (body temperature, blood pressure, heart rate) on the device

[1618] Step 2: Send your health data

[1619] The device sends the acquired health data to the server at regular intervals (e.g., every hour) using a secure and fast communication protocol (e.g., HTTPS).

[1620] Input: Health data stored on the device

[1621] Output: Health data sent to the server using HTTPS protocol

[1622] Step 3: Receiving and storing health data

[1623] The server receives the health data sent from the device and automatically stores it in a database.

[1624] Input: Health data sent from the device

[1625] Output: Health data stored in a database

[1626] Step 4: Analyze health data

[1627] The server passes the stored health data to an AI module for analysis, which compares it with past data to detect any abnormal values ​​or patterns.

[1628] Input: Health data stored in a database

[1629] Output: Analysis results by the AI ​​module (outliers and patterns)

[1630] Step 5: Generate and send notifications

[1631] If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately." If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[1632] Input: Analysis results of the AI ​​module

[1633] Output: Sends an emergency or normal notification to the LINE app.

[1634] Step 6: Collect emotion data

[1635] The device uses a camera and microphone to collect the user's facial expressions and voice. Specifically, the camera is activated at regular intervals to capture the user's facial expressions, and the microphone is used to record the user's tone and intonation of voice.

[1636] Input: User facial and voice data

[1637] Output: Emotion data stored on the device

[1638] Step 7: Sending Emotion Data

[1639] The device sends the collected emotion data to a server using a secure and fast communication protocol (e.g., HTTPS).

[1640] Input: Emotion data stored on the device

[1641] Output: Emotion data sent to the server using HTTPS protocol

[1642] Step 8: Analyze the sentiment data

[1643] The emotion engine estimates the user's emotional state based on the collected data and sends the analysis results to the server.

[1644] Input: Emotion data sent to the server

[1645] Output: Analysis results by the emotion engine

[1646] Step 9: Comprehensive analysis and response generation

[1647] The server comprehensively analyzes the user's health and emotional data to detect abnormal emotional or health conditions. Based on the results, the server generates an appropriate response. For example, if the user is feeling stressed, the server generates a message such as, "You seem to be feeling more stressed recently. Please try to find ways to relax."

[1648] Input: Comprehensive analysis results of health data and emotional data

[1649] Output: The appropriate response message

[1650] Step 10: Send a response message

[1651] The server sends the generated response message to the user via the LINE app.

[1652] Input: Server-generated response message

[1653] Output: Response message sent to the LINE app

[1654] Step 11: Receiving a Purchase Request

[1655] Users use the LINE app to send requests for items necessary for daily life via their terminal means.

[1656] Input: Purchase request message sent by the user

[1657] Output: Purchase request message received on the device

[1658] Step 12: Parse the purchase request

[1659] The server receives the request message, analyzes it, and identifies the required product. The server then searches for information about the corresponding product using a standard online shopping API.

[1660] Input: Purchase request message sent from the device

[1661] Output: Product information search results

[1662] Step 13: Generate and send your product offer link

[1663] The server generates the appropriate product link from the search results and sends it to the user via LINE message. Example: "You can buy toilet paper here [link]".

[1664] Input: Product information search results

[1665] Output: LINE message containing the product offer link

[1666] This system will enable real-time monitoring of the health and emotional state of the elderly, and will respond immediately if an abnormality occurs. It will also be able to quickly respond to requests from users for items necessary for daily life, improving the convenience of daily life.

[1667] (Application example 2)

[1668] 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."

[1669] Until now, there has been no system that can monitor not only the health status of elderly people but also the emotional state of passengers in real time to comprehensively improve safety and comfort. Furthermore, autonomous vehicles with many elderly passengers are required to instantly detect abnormalities in their health and emotional states and take appropriate action. Furthermore, a system is needed that can comprehensively analyze passenger health and emotional data and promptly notify passengers and relevant parties when an abnormality is detected.

[1670] The specific processing by the specific 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 terminal means for acquiring health data, means for transmitting the acquired health data to the server, server means for receiving and storing the transmitted health data, AI module means for analyzing the received health data and detecting abnormal values, means for sending an emergency notification if an abnormality is detected based on the analysis results, means for notifying the normal state based on the analysis results, sensor means for acquiring the facial expressions and voice of the occupant and estimating their emotional state, server means for transmitting and analyzing the emotional data, and means for generating and notifying an appropriate response based on the emotional data. This enables real-time monitoring of the health and emotional states of elderly people and promptly sending an emergency notification if an abnormality is detected. Furthermore, providing appropriate responses and support according to the occupant's emotional state can improve safety and comfort.

[1671] "Elderly" refers to people aged 65 and over, and health risks generally increase with age.

[1672] "Health status" refers to the physical condition of an individual, assessed comprehensively from physical data such as body temperature, blood pressure, and heart rate.

[1673] "Monitoring" is the act of acquiring and analyzing data in real time to detect abnormalities and changes.

[1674] A "remote monitoring system" is a system that monitors the health and safety of people in remote locations via the Internet or wireless communications, without the need for physical contact.

[1675] "Terminal means" refers to hardware such as smartphones and wearable devices that are used to collect health data.

[1676] "Server means" refers to a server for receiving, storing, and analyzing data.

[1677] "Data transmission means" refers to the communication protocol or technology used to transmit health data from the terminal to the server.

[1678] "AI module means" is a software module that uses artificial intelligence to analyze data and detect anomalies.

[1679] "Notification means" refers to a method for notifying users of abnormal or normal conditions, and includes messaging services such as the LINE app.

[1680] "Sensor means" refers to devices such as cameras and microphones used to capture emotional data such as facial expressions and voice.

[1681] "Emotion data" is data that indicates the emotional state of the user estimated from facial expressions, voice, etc.

[1682] An "urgent notification" is a warning message that is sent to the user immediately when an abnormality is detected.

[1683] An "appropriate response" is a response that includes support or suggestions appropriate to the user's situation and is generated based on the acquired data.

[1684] A "response generation means" is an AI engine or algorithm that creates an appropriate response based on emotional data.

[1685] The present invention is a remote monitoring system that monitors the health and emotional state of elderly people and provides appropriate responses and support based on the results. This system is designed to ensure the safety and comfort of passengers, especially elderly people, in autonomous vehicles.

[1686] Health Data Collection and Transmission

[1687] Health data collection

[1688] The terminal (smartphone or wearable device) periodically collects health data from devices installed in the car, such as "smart seats," blood pressure sensors, and heart rate sensors. Health data includes body temperature, blood pressure, heart rate, etc.

[1689] Sending data

[1690] The device sends the acquired health data to the server at regular intervals (e.g., every 30 minutes). Communication uses a secure and fast protocol (e.g., HTTPS).

[1691] Data analysis and notification

[1692] Receiving and storing data

[1693] The server receives the health data sent from the terminal and stores it in a database.

[1694] Data analysis

[1695] The server passes the stored health data to an AI module for analysis. The AI ​​module compares it with past data to detect abnormal values ​​and patterns. The analysis uses a generative AI model.

[1696] Sending notifications

[1697] If an abnormality is detected, the server generates an emergency notification and promptly notifies the passengers and maintenance staff via the in-car smart display, voice system, or passenger's smartphone, for example, by sending a prompt message such as "Emergency! Your heart rate is very high. Contact a medical institution immediately."

[1698] Emotion data collection and analysis

[1699] Collecting Emotional Data

[1700] The device collects the passenger's facial expressions and voice using cameras and microphones inside the vehicle, and the emotion engine estimates the passenger's emotional state based on the collected data.

[1701] Emotional Data Analysis

[1702] The server receives and analyzes the emotion data sent from the emotion engine. The server comprehensively analyzes the passenger's health data and emotion data to detect abnormal emotional or health conditions.

[1703] Response and Support

[1704] Generating a response

[1705] Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response for the passenger. For example, if the passenger is feeling stressed, it generates a prompt such as, "Your stress is increasing. Please take a moment to take a deep breath."

[1706] Sending notifications

[1707] Emotional data and health data are comprehensively analyzed, and if an abnormality is detected, the server generates an emergency notification and sends it to the occupants and relevant parties.

[1708] Specific examples

[1709] Health data monitoring and emotion data analysis

[1710] 1. At 7:00 AM, the device acquires blood pressure data and sends it to the server.

[1711] 2. The server receives the data and stores it in a database.

[1712] 3. The server passes the data to the AI ​​module for analysis.

[1713] 4. If the AI ​​module does not detect any abnormalities, the server will notify the smart display that "No abnormalities were detected."

[1714] 5. If an abnormality is detected, the server will notify you: "Urgent! Your blood pressure is very high. Please check."

[1715] 6. At the same time, the device captures the passenger's facial expressions with a camera and the emotion engine analyzes them. If the emotional state is determined to be unstable, the device will notify the passenger, saying, "You've been feeling stressed recently. Try to find ways to relax."

[1716] Hardware and software used

[1717] Camera: Used to capture facial expressions (e.g., a general-purpose camera).

[1718] Sensors: Used to acquire health data (e.g., general-purpose sensors).

[1719] software:

[1720] Server communication: Uses the requests module.

[1721] Image processing: Uses cv2 (OpenCV).

[1722] Time management: time and datetime modules.

[1723] Prompt Sentence Examples

[1724] "Urgent! Heart rate is very high. Call medical help immediately."

[1725] "You've been under a lot of stress lately. Try some relaxation techniques."

[1726] The system can efficiently monitor the health and emotional state of passengers, enabling immediate response to abnormal situations and providing appropriate responses and obedient actions, thereby improving the safety and comfort of autonomous vehicles.

[1727] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1728] Step 1:

[1729] The device collects health data of passengers using the "smart seat" installed in the vehicle and various sensors (blood pressure sensor, heart rate sensor). This data includes body temperature, blood pressure, and heart rate. The input is an analog signal from the sensor, which is converted to a digital signal and stored in the device. The output is the collected health data.

[1730] Step 2:

[1731] The device sends the acquired health data to the server at regular intervals (e.g., every 30 minutes). The device specifically sends data securely using the HTTPS protocol. The input is the health data acquired in step 1, and the output is the data sent to the server.

[1732] Step 3:

[1733] The server receives the health data sent from the device and stores it in a database. Here, the health data sent from the device is the input, and the data stored in the database is the output. The stored data accumulates over time.

[1734] Step 4:

[1735] The server passes the accumulated health data to an AI module for analysis. The AI ​​module compares it with past data to detect abnormal patterns. The input is health data stored in a database, and the output is the result of AI anomaly detection. A generative AI model is used for the analysis.

[1736] Step 5:

[1737] If the server detects an abnormality based on the analysis results, it generates an emergency notification and sends it to the in-car smart display, voice system, and passengers' smartphones. Specific emergency notifications include prompts such as "Emergency! Your heart rate is very high. Contact a medical institution immediately." The input is the anomaly detection result from the AI ​​module, and the output is the generated emergency notification, which is then sent.

[1738] Step 6:

[1739] At the same time, the device uses cameras and microphones inside the vehicle to collect facial expressions and voices of the occupants. The input is analog signals from the cameras and microphones, which are converted into digital data and output as data sent to the emotion engine.

[1740] Step 7:

[1741] The emotion engine estimates the emotional state of the passenger based on the collected data. It uses AI technology to analyze voice and facial expression data to estimate the emotional state (e.g., stress, anxiety, etc.). The input is the digital data obtained in step 6, and the output is the analyzed emotional state.

[1742] Step 8:

[1743] The emotion engine sends the analyzed emotion data to the server, and the server generates an appropriate response based on that data. For example, if the emotion data indicates stress, it generates a prompt such as "Your stress is increasing. Take a moment to take a deep breath." The input is the analyzed data from the emotion engine, and the output is the generated prompt.

[1744] Step 9:

[1745] The server comprehensively analyzes the health data and emotional data, and if an abnormality is detected, generates an emergency notification and sends it to the crew and relevant parties. For example, it generates a comprehensive notification such as "Emergency! Your heart rate is very high and your stress level is also high. Please check." Both health data and emotional data are input, and a comprehensive emergency notification is generated as output.

[1746] This process flow realizes a system that can monitor the health and emotional state of passengers in real time and respond immediately.

[1747] 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.

[1748] 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.

[1749] 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.

[1750] [Fourth embodiment]

[1751] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1752] 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.

[1753] 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).

[1754] 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.

[1755] 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.

[1756] 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).

[1757] 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.

[1758] 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.

[1759] 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.

[1760] 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.

[1761] 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.

[1762] 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.

[1763] 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."

[1764] The present invention provides a remote monitoring system that monitors the health status of elderly people, detects abnormalities, and provides support for purchasing items necessary for daily life. Specific embodiments of the system will be described below.

[1765] Health Data Collection and Transmission

[1766] Health data collection

[1767] 1. The device (smartphone or wearable device) periodically collects health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors.

[1768] 2. Health data includes body temperature, blood pressure, heart rate, etc.

[1769] Sending data

[1770] 1. The device sends the collected health data to the server at regular intervals (e.g., every hour).

[1771] 2. Data transmission is carried out using secure and fast communication protocols.

[1772] Data analysis and notification

[1773] Receiving and storing data

[1774] 1. The server receives the health data sent from the device and stores it in a database.

[1775] Data analysis

[1776] 1. The server passes the received health data to the AI ​​module.

[1777] 2. The AI ​​module analyzes the data to see if there are any abnormal values ​​or patterns, comparing them with past data.

[1778] Sending notifications

[1779] 1. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately."

[1780] 2. If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning is 36.5 degrees, which is normal."

[1781] Purchase assistance

[1782] Receiving product requests

[1783] 1. The user or elderly person sends a request for an item necessary for daily life using the LINE app. Example: "I need toilet paper."

[1784] Handling the request

[1785] 1. The server receives the request message from the user, analyzes it, and identifies the required product.

[1786] 2. The server searches for information about the relevant product using the Yahoo Shopping API.

[1787] Generate and send the link

[1788] 1. The server generates appropriate product offer links from the search results.

[1789] 2. The server sends the generated link to the user via LINE message. Example: "You can buy toilet paper here [LINK]".

[1790] Specific examples

[1791] Health Data Monitoring

[1792] At 7:00 a.m., the device acquires blood pressure data and sends it to the server. The server passes the data to the AI ​​module for analysis. If the analysis results are normal, a LINE notification is sent stating, "Mom's blood pressure this morning is 120 / 80, which is normal." If an abnormality is detected, a notification is sent stating, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[1793] Assisted Buy execution

[1794] A user sends a message on LINE saying, "I need toilet paper." The server receives and analyzes the message, searches for the relevant product using the Yahoo Shopping API, generates a link, and replies, "You can buy toilet paper here [link]."

[1795] This system will enable efficient monitoring of the health status of the elderly, enable immediate response to emergencies, and improve the convenience of their daily lives.

[1796] The processing flow will be explained below.

[1797] Health data collection and analysis

[1798] Health data collection

[1799] Step 1:

[1800] The device acquires health data from linked healthcare devices (e.g., thermometers and blood pressure monitors).

[1801] Step 2:

[1802] The device transmits the acquired health data to the server at regular intervals (for example, every hour).

[1803] Data analysis

[1804] Step 3:

[1805] The server receives the health data sent from the device and stores it in a database.

[1806] Step 4:

[1807] The server passes the stored health data to an AI module for analysis.

[1808] Step 5:

[1809] The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[1810] Sending notifications

[1811] Step 6:

[1812] The server generates an emergency notification if an anomaly is detected based on the analysis results of the AI ​​module.

[1813] Step 7:

[1814] The server sends the generated emergency notification to the user (family member) via the LINE app.

[1815] For example: "Urgent! Dad's heart rate is over 160. Please check immediately."

[1816] Step 8:

[1817] If no abnormality is detected, the server notifies the user of the normal status.

[1818] For example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[1819] Purchase assistance

[1820] Receiving product requests

[1821] Step 9:

[1822] Users or elderly people use the LINE app to send requests for items necessary for daily life.

[1823] For example: "I need toilet paper."

[1824] Handling the request

[1825] Step 10:

[1826] The server analyzes the request message received from the user and identifies the required product.

[1827] Step 11:

[1828] The server uses the Yahoo Shopping API to search for information about the relevant product.

[1829] Generate and send the link

[1830] Step 12:

[1831] The server generates appropriate product offering links from the search results.

[1832] Step 13:

[1833] The server sends the generated link to the user via a LINE message.

[1834] For example: "You can buy toilet paper here [link]"

[1835] Specific examples

[1836] Health Data Monitoring

[1837] Step 1:

[1838] The device collects blood pressure data at 7:00 a.m.

[1839] Step 2:

[1840] The terminal transmits the acquired data to the server.

[1841] Step 3:

[1842] The server receives the data and stores it in a database.

[1843] Step 4:

[1844] The server passes the data to the AI ​​module for analysis.

[1845] Step 5:

[1846] The AI ​​module analyzes the data and returns the results to the server.

[1847] Step 6:

[1848] Based on the analysis results, the server will either notify you of a normal condition or generate an emergency notification.

[1849] Step 7:

[1850] If the result is normal, the server sends a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[1851] Step 8:

[1852] If an abnormality is detected, the server will send a LINE notification saying, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[1853] Assisted Buy execution

[1854] Step 1:

[1855] A user sends a message on LINE saying, "I need toilet paper."

[1856] Step 2:

[1857] The server receives and parses the message.

[1858] Step 3:

[1859] The server calls the Yahoo Shopping API and searches for the relevant product.

[1860] Step 4:

[1861] The server generates a product offer link from the search results.

[1862] Step 5:

[1863] The server replies with a link via LINE saying, "You can buy toilet paper here [link]."

[1864] Example 1

[1865] 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."

[1866] While there is a need to monitor the health status of the elderly and respond to emergencies, there is a lack of efficient ways to do this remotely. Support for purchasing necessary items is also essential for the elderly's daily lives, but this process must be simple. Conventional systems do not integrate real-time health monitoring, prompt notification in the event of an abnormality, and support for purchasing items, causing inconvenience to the elderly and their families.

[1867] 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.

[1868] In this invention, the server includes means for transmitting health data acquired from the terminal means to the server, means for receiving the transmitted health data and storing it in a database, means for passing the received health data to an AI module and comparing it with past data to detect abnormal values, means for generating an emergency notification and notifying the user via a communication application if an abnormality is detected, means for notifying the user of a normal condition if no abnormality is detected, means for receiving an item purchase request from the user, identifying an appropriate item, and generating a provision link, and means for transmitting the generated link to the user via the communication application. This enables comprehensive monitoring of the health status of elderly people, enabling prompt response in the event of an abnormality, and efficient support for purchasing items necessary for daily life.

[1869] "Terminal means" refers to hardware devices such as smartphones and wearable devices for collecting health data.

[1870] The "server means" is a central processing device that receives data sent from the terminal means and stores and analyzes it.

[1871] "AI module means" is a software or hardware configuration having artificial intelligence algorithms for analyzing received health data and detecting abnormal values.

[1872] "Means for generating an emergency notification and notifying the user through a communication application" refers to a mechanism that creates a notification message when an abnormality is detected and sends the message to the user using a communication application such as LINE.

[1873] The "means for notifying the user of a normal state" is a mechanism for generating and sending a message to the user informing them of a normal state when no abnormalities are found in the health data.

[1874] The "means for receiving a product purchase request, identifying an appropriate product, and generating a provision link" is a mechanism for analyzing a purchase request from a user, identifying the appropriate product, and generating a purchase link for that product.

[1875] "Means of sending via a communication application" refers to a mechanism for sending the generated product offer link or notification message to the user using a communication application such as LINE.

[1876] The present invention provides a remote monitoring system that remotely monitors the health status of elderly people, detects abnormalities, and provides support for purchasing items necessary for daily life. Specific embodiments of the system are described below.

[1877] Health Data Collection and Transmission

[1878] First, we will discuss the "collection and transmission of health data" in this invention. The terminal means is a smartphone or wearable device for collecting health data. Specifically, it works in conjunction with healthcare devices such as a blood pressure monitor, thermometer, and heart rate sensor to periodically acquire data. For example, a wearable device such as the Apple Watch uses Bluetooth to acquire blood pressure data from a blood pressure monitor and transmit it to a smartphone.

[1879] The terminal means transmits the collected data to the server means at regular intervals (for example, every hour). This data transmission uses the HTTPS protocol, which enables secure and fast data communication.

[1880] Data analysis and notification

[1881] Next, we will discuss "Data Analysis and Notification." The server means receives the health data sent from the terminal means and stores it in a database. The database records the health data for each user, and uses a database system such as MySQL.

[1882] The received data is analyzed by the AI ​​module means. The AI ​​module uses machine learning algorithms such as TensorFlow to compare it with past data and detect abnormal values ​​or patterns. If an abnormality is detected, the server means generates an emergency notification and promptly notifies the user through a communication application such as the LINE app. For example, a message such as "Urgent! Dad's heart rate has exceeded 160. Please check immediately" may be sent.

[1883] On the other hand, if no abnormality is detected, the server means notifies the user of the normal state, for example, a message such as "Mom's temperature this morning is 36.5 degrees, which is normal" is sent to the user.

[1884] Purchase assistance

[1885] Finally, we will explain "purchase assistance." Users or elderly people can use the LINE app to send requests for items necessary for daily life. For example, they can send a message saying, "I need toilet paper."

[1886] The server receives this request message and uses natural language processing (NLP) to identify the required product. The server then calls the Yahoo Shopping API and searches for information on the relevant product. It then generates an appropriate product link from the search results and sends it to the user via LINE message. For example, a message such as "You can purchase toilet paper here [link]" is sent.

[1887] Specific operation example

[1888] Health Data Monitoring

[1889] At 7:00 AM, the terminal means (e.g., smartwatch) automatically measures blood pressure and sends the data to the server means. The server means then passes the data to the AI ​​module, which analyzes whether there is an abnormality. If normal, it notifies the user, "Mom's blood pressure this morning is 120 / 80, which is normal," and if an abnormality is detected, it notifies the user, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[1890] Assisted Buy execution

[1891] The user sends a message on LINE saying, "I need toilet paper." The server receives the message and identifies "toilet paper" through NLP. It then retrieves information about the product using the Yahoo Shopping API and replies, "You can buy toilet paper here [link]."

[1892] This system will enable efficient monitoring of the health status of elderly people, enabling rapid response in emergencies and improving convenience in daily life.

[1893] Prompt Sentence Examples

[1894] Below is an example of a prompt sentence that will be input to the generative AI model.

[1895] Please describe in natural language a remote monitoring system that collects health data on elderly people and sends notifications when abnormalities are detected based on that data. Please also provide specific examples of the notification messages, including the specific names of the hardware and software used.

[1896] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1897] Step 1:

[1898] Health data collection

[1899] The device acquires health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. Specifically, the device (e.g., a smartwatch) acquires blood pressure data from the blood pressure monitor and receives body temperature data from the thermometer via Bluetooth. The heart rate sensor directly transmits heart rate data to the device. Health data includes body temperature, blood pressure, and heart rate.

[1900] Input: Health data from healthcare devices

[1901] Output: Health data temporarily stored in the device

[1902] Step 2:

[1903] Sending data

[1904] The device sends the collected health data to the server at regular intervals (e.g., every hour). The HTTPS protocol is used for data transmission, ensuring secure data transfer. The device temporarily stores the collected data and sends it in batches at specified intervals.

[1905] Input: Health data temporarily stored in the device

[1906] Output: Health data sent to the server

[1907] Step 3:

[1908] Receiving and storing data

[1909] The server receives the health data sent from the device. The received data is parsed in JSON format and stored in a database. A database management system such as MySQL is used for the database, and the health data is managed in chronological order.

[1910] Input: Health data sent from the device

[1911] Output: Health data stored in a database

[1912] Step 4:

[1913] Data analysis

[1914] The server then passes the received health data to the AI ​​module, which compares it with past data and analyzes it for outliers and abnormal patterns. The AI ​​module uses machine learning frameworks such as TensorFlow to run models to detect outliers.

[1915] Input: Health data retrieved from a database

[1916] Output: Anomaly information analyzed by the AI ​​module

[1917] Step 5:

[1918] Generate and send anomaly notifications

[1919] If an abnormality is detected, the server generates an emergency notification and promptly notifies the user through a communication application such as the LINE app. For example, a message such as "Urgent! Dad's heart rate has exceeded 160. Please check immediately" is generated. The notification is sent using the LINE Messaging API.

[1920] Input: Anomaly information analyzed by the AI ​​module

[1921] Output: Urgent notification message sent to the user

[1922] Step 6:

[1923] Normal status notification

[1924] If no abnormalities are detected, the server generates a message informing the user of the normal condition, for example, "Mom's temperature this morning is 36.5 degrees, which is normal."

[1925] Input: Normal information analyzed by the AI ​​module

[1926] Output: Normal status notification message sent to the user

[1927] Step 7:

[1928] Receiving a purchase request

[1929] Users send requests for items necessary for daily life to the server through the LINE app. For example, they can send a message such as "I need toilet paper" via LINE. The server receives the message from the user using the LINE API.

[1930] Input: The request message sent by the user

[1931] Output: The request message received by the server

[1932] Step 8:

[1933] Parsing purchase requests

[1934] The server analyzes the received request message and identifies the required product. It uses natural language processing (NLP) techniques to analyze and identify the requested item.

[1935] Input: The request message received by the server

[1936] Output: Requested item information

[1937] Step 9:

[1938] Generate and send product offer links

[1939] The server calls the Yahoo Shopping API based on the identified product information and searches for information on the corresponding product. It then generates an appropriate product link from the search results and sends it to the user via a communication application. For example, it generates a message such as "You can buy toilet paper here [link]."

[1940] Input: Requested item information

[1941] Output: Offer link sent to user

[1942] (Application example 1)

[1943] 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."

[1944] Remote health monitoring systems for the elderly have the problem of being unable to immediately respond to health risks, especially when the elderly visit a store. Furthermore, they provide insufficient support for elderly people's everyday purchases, which can lead to a decline in their quality of life. Furthermore, if health monitoring of the elderly in a store is not performed in real time, there is also the problem of being unable to respond quickly to abnormalities.

[1945] 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.

[1946] In this invention, the server includes a terminal means for acquiring health data, a means for transmitting the acquired health data to the server, a means for receiving and storing the transmitted health data, an AI module means for analyzing the received health data and detecting abnormal values, a means for sending an emergency notification if an abnormality is detected based on the analysis results, a means for notifying a normal condition based on the analysis results, a means for collecting health data of visitors in real time using an in-store health monitoring terminal, and a means for analyzing the collected health data and notifying a store clerk if an abnormality is detected. This not only enables real-time monitoring of the health status of elderly people and emergency response when they visit, but also enables efficient support for purchasing items necessary for daily life.

[1947] "Terminal means for acquiring health data" refers to devices or equipment used to collect health information such as body temperature, blood pressure, and heart rate of elderly people.

[1948] "Means for transmitting acquired health data to a server" refers to a communication device or communication protocol for transmitting collected health data to a server via a network.

[1949] The "server means for receiving and storing transmitted health data" is a server system for receiving health data transmitted from a terminal and storing it in a database.

[1950] The "AI module means for analyzing received health data and detecting abnormal values" is an artificial intelligence module for analyzing health data stored on the server and detecting abnormal values.

[1951] "Means for sending an emergency notification when an abnormality is detected based on the analysis results" refers to a communication means for sending an emergency notification to the user when the AI ​​module detects an abnormality.

[1952] "Means for notifying the user of a normal state based on the analysis results" refers to a communication means for notifying the user of a normal health state if the AI ​​module does not detect any abnormalities.

[1953] "Means for collecting visitor health data in real time using health monitoring terminals in the store" refers to equipment for collecting visitor health data in real time using terminals installed in the store.

[1954] "Means for analyzing collected health data and notifying store staff if an abnormality is detected" refers to a communication means for analyzing health data collected in the store and sending an emergency notification to store staff if an abnormality is detected.

[1955] The present invention is a remote monitoring system that monitors the health status of elderly people, detects abnormalities, monitors the health of visitors in real time, and provides purchasing support. Specific embodiments will be described below.

[1956] Health Data Collection and Transmission

[1957] Health data collection

[1958] Terminals (smartphones, tablets, wearable devices) connect to healthcare devices such as blood pressure monitors, heart rate sensors, and thermometers to periodically collect health data, including body temperature, blood pressure, and heart rate.

[1959] Sending data

[1960] The device sends the collected health data to a server at regular intervals (e.g., every hour) using a secure and fast communication protocol.

[1961] Data analysis and notification

[1962] Receiving and storing data

[1963] The server receives the health data sent from the device and stores it in a database. Specific server systems used include AWS and Google Cloud Platform.

[1964] Data analysis

[1965] The server passes the received health data to an AI module (e.g., a model using TensorFlow or PyTorch), which then compares the data with past data and analyzes it for abnormal values ​​or patterns.

[1966] Sending notifications

[1967] If an abnormality is detected, the server generates an emergency notification and promptly notifies the user (e.g., family or caregiver) using a communication method (e.g., LINE API, SMS API). If no abnormality is detected, the server notifies the user of their normal health status.

[1968] In-store health monitoring and purchasing assistance

[1969] In-store health monitoring

[1970] Health monitoring devices (e.g., kiosks, tablets) installed in stores collect visitors' health data in real time. The collected health data is sent to a server and analyzed by an AI module. If an abnormality is detected, the server sends an emergency notification to the store staff's device (e.g., smartphone, in-store display).

[1971] Purchase assistance

[1972] Users or seniors use in-store terminals or wearable devices to send requests for items necessary for daily life. The server receives and analyzes the request message, then generates and notifies the user of the appropriate product link. Product information is searched using APIs such as Yahoo Shopping.

[1973] Specific examples

[1974] Health Data Monitoring

[1975] At 7:00 AM, the device acquires blood pressure data and sends it to the server. The server passes the data to an AI module (e.g., TensorFlow model) for analysis. If the analysis results are normal, a LINE notification is sent stating, "This morning's blood pressure is 120 / 80, which is normal." If an abnormality is detected, a notification is sent stating, "Urgent! Your blood pressure is 180 / 110. Please check immediately."

[1976] Assisted Buy execution

[1977] The user sends a request to a terminal in the store saying, "I need toilet paper." The server receives the request, analyzes it, searches for the relevant product from the Yahoo Shopping API, generates a link, and notifies the user, "You can buy toilet paper here [link]."

[1978] Example prompts for generative AI models

[1979] Generate the following Python program:

[1980] I want to develop an application that collects health data (heart rate, blood pressure, body temperature) of elderly people and sends it to a server.

[1981] The data sent to the server detects any abnormalities and notifies store staff or managers as necessary.

[1982] For data collection, we use the requests library, and for notifications, we use SMS or the LINE API.

[1983] Abnormal thresholds are a heart rate above 100, blood pressure above 160 / 100, and body temperature above 38°C.

[1984] Set these thresholds within your program and include a process to notify you when an anomaly is detected.

[1985] The above is a specific embodiment of the present invention. This system can efficiently monitor the health status of elderly people and provide emergency response in stores. It can also provide support for purchasing items necessary for daily life.

[1986] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1987] Step 1:

[1988] The device acquires health data. Specifically, the device (smartphone, tablet, wearable device) measures body temperature, blood pressure, and heart rate from healthcare devices such as blood pressure monitors, heart rate sensors, and thermometers, and collects health data. At this stage, the input is the raw data acquired from the healthcare devices, and the output is the collected health data (e.g., body temperature 36.5°C, blood pressure 120 / 80, heart rate 75).

[1989] Step 2:

[1990] The collected health data is sent to the server. The device uses a secure and fast communication protocol (e.g., HTTPS) to send the acquired health data to the server at regular intervals (e.g., every hour). The input is the health data acquired in step 1, and the output is the health data sent to the server. Specifically, the data is encrypted and sent using the communication protocol.

[1991] Step 3:

[1992] The server stores the received health data. The server receives the health data sent from the device and stores it in a database. Specific server systems include AWS RDS and Google Cloud SQL. The input is the sent health data, and the output is the health data stored in the database. Specific operations include receiving data and storing it in the database.

[1993] Step 4:

[1994] The server analyzes the received data and detects abnormal values. The server passes the stored health data to an AI module (e.g., TensorFlow or PyTorch), which compares it with past data and analyzes whether there are any abnormal values ​​or patterns. The input is the stored past health data and newly received health data, and the output is the analysis results. Specifically, data analysis is performed using a machine learning model.

[1995] Step 5:

[1996] An emergency notification is sent if an abnormality is detected. If the server detects an abnormality based on the analysis results, it generates an emergency notification and notifies the user using a communication method (e.g., LINE API, short message API). The input is the analysis result (whether or not there is an abnormality), and the output is the emergency notification that was sent. Specifically, when an abnormality is detected, a notification message is generated and sent.

[1997] Step 6:

[1998] Notifies normal status. If the server detects no abnormalities based on the analysis results, it notifies normal health status. The input is the analysis result (normal value), and the output is the sent notification. Specifically, when a normal condition is detected, a notification message is generated and sent.

[1999] Step 7:

[2000] In-store health monitoring terminals collect visitors' health data in real time. Terminals installed in the store (e.g., kiosks, tablets) measure visitors' blood pressure, body temperature, and heart rate and collect health data. The input is raw data from the in-store healthcare devices, and the output is the collected health data.

[2001] Step 8:

[2002] Health data from within the store is sent to the server for analysis. The collected health data is sent to the server, where it is analyzed by the AI ​​module. The input is the collected health data and past data, and the output is the analysis results. The specific operation is the same as steps 2 to 4.

[2003] Step 9:

[2004] If an abnormality is detected, the store clerk is notified. If an abnormality is detected based on the analysis results, the server sends an emergency notification to the store clerk's device (e.g., smartphone, in-store display). The input is the analysis result, and the output is the emergency notification sent to the store clerk.

[2005] Step 10:

[2006] A user requests an item needed for daily life. The user or elderly person sends a request for the needed item using an in-store terminal or a wearable device. The input is the request message created by the user, and the output is the request sent to the server.

[2007] Step 11:

[2008] The server analyzes the request and generates a product offer link. The server receives the request message, analyzes it, and generates an appropriate product offer link (e.g., Yahoo Shopping API). The input is the request message, and the output is the generated product offer link.

[2009] Step 12:

[2010] The product provision link is notified to the user. The server notifies the user of the generated product provision link. The input is the product provision link, and the output is the sent notification message. The specific operations are link generation and notification message transmission.

[2011] 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.

[2012] The present invention provides a remote monitoring system that monitors the health status of an elderly person, detects abnormalities, analyzes the user's emotions, and provides appropriate responses and support. Specific embodiments of the system are described below.

[2013] Health Data Collection and Transmission

[2014] Health data collection

[2015] 1. The device (smartphone or wearable device) periodically collects health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors.

[2016] 2. Health data includes body temperature, blood pressure, heart rate, etc.

[2017] Sending data

[2018] 1. The device sends the acquired health data to the server at regular intervals (e.g., every hour).

[2019] 2. Data transmission is carried out using secure and fast communication protocols.

[2020] Data analysis and notification

[2021] Receiving and storing data

[2022] 1. The server receives the health data sent from the device and stores it in a database.

[2023] Data analysis

[2024] 1. The server passes the stored health data to the AI ​​module for analysis.

[2025] 2. The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[2026] Sending notifications

[2027] 1. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately."

[2028] 2. If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning is 36.5 degrees, which is normal."

[2029] Emotion data collection and analysis

[2030] Collecting Emotional Data

[2031] 1. The device collects the user's facial expressions and voice using sensors such as a camera and microphone.

[2032] 2. The emotion engine estimates the user's emotional state based on the collected data.

[2033] Emotional Data Analysis

[2034] 1. The server receives and analyzes the emotion data sent from the emotion engine.

[2035] 2. The server comprehensively analyzes the user's health data and emotional data to detect abnormal emotional and health states.

[2036] Response and Support

[2037] Generating a response

[2038] 1. Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response to the user.

[2039] 2. Example) If the user is feeling stressed: "You seem to be feeling more stressed lately. Try some relaxation techniques."

[2040] Sending notifications

[2041] 1. Comprehensively analyzes emotional and health data, and if an abnormality is detected, the server generates an emergency notification and sends it to the user (family member) via the LINE app. Example: "Emergency! Mom's heart rate is over 160 and her emotional state is unstable. Please check on her immediately."

[2042] Purchase assistance

[2043] Receiving product requests

[2044] 1. The user or elderly person sends a request for an item necessary for daily life using the LINE app. Example: "I need toilet paper."

[2045] Handling the request

[2046] 1. The server receives the request message from the user, analyzes it, and identifies the required product.

[2047] 2. The server searches for information about the relevant product using the Yahoo Shopping API.

[2048] Generate and send the link

[2049] 1. The server generates appropriate product offer links from the search results.

[2050] 2. The server sends the generated link to the user via LINE message. Example: "You can buy toilet paper here [LINK]".

[2051] Specific examples

[2052] Health data monitoring and emotion data analysis

[2053] 1. At 7:00 a.m., the device acquires blood pressure data and sends it to the server.

[2054] 2. The server receives the data and stores it in a database.

[2055] 3. The server passes the data to the AI ​​module for analysis.

[2056] 4. If the AI ​​module does not detect any abnormalities, the server will send a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[2057] 5. If an abnormality is detected, the server will notify, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[2058] 6. At the same time, the device captures the user's facial expressions with a camera, which the emotion engine analyzes. If the emotional state is determined to be unstable, the server will notify the user, saying, "You've been feeling stressed lately. Please try some relaxation techniques."

[2059] Assisted Buy execution

[2060] 1. A user sends a message on LINE saying, "I need toilet paper."

[2061] 2. The server receives the message, analyzes it, searches for the relevant product using the Yahoo Shopping API, generates a link, and replies with "You can buy toilet paper here [link]."

[2062] This system will enable efficient monitoring of the health status of elderly people and enable immediate response to any abnormalities, as well as analyze the user's emotional state and provide appropriate responses and support, improving the convenience of everyday life.

[2063] The processing flow will be explained below.

[2064] Health data collection and analysis

[2065] Health data collection

[2066] Step 1:

[2067] The device acquires health data from linked healthcare devices (e.g., thermometers and blood pressure monitors).

[2068] Step 2:

[2069] The device transmits the acquired health data to the server at regular intervals (for example, every hour).

[2070] Data analysis

[2071] Step 3:

[2072] The server receives the health data sent from the device and stores it in a database.

[2073] Step 4:

[2074] The server passes the stored health data to an AI module for analysis.

[2075] Step 5:

[2076] The AI ​​module compares data with past data to detect any abnormal values ​​or patterns.

[2077] Sending notifications

[2078] Step 6:

[2079] The server generates an emergency notification if an anomaly is detected based on the analysis results of the AI ​​module.

[2080] Step 7:

[2081] The server sends the generated emergency notification to the user (family member) via the LINE app.

[2082] For example: "Urgent! Dad's heart rate is over 160. Please check immediately."

[2083] Step 8:

[2084] If no abnormality is detected, the server notifies the user of the normal status.

[2085] For example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[2086] Emotion data collection and analysis

[2087] Collecting Emotional Data

[2088] Step 9:

[2089] The device collects the user's facial expressions and voice using sensors such as a camera and microphone.

[2090] Step 10:

[2091] The terminal sends the collected data to an emotion engine to estimate the user's emotional state.

[2092] Emotional Data Analysis

[2093] Step 11:

[2094] The server receives the emotion data sent from the emotion engine and stores it in a database.

[2095] Step 12:

[2096] The server passes the desired emotional data to the AI ​​module for analysis.

[2097] Step 13:

[2098] The server comprehensively analyzes the user's health data and emotional data to detect abnormal emotional and health states.

[2099] Response and Support

[2100] Generating a response

[2101] Step 14:

[2102] Based on the emotional data analyzed by the emotion engine, the server generates an appropriate response to the user.

[2103] For example, if the user is feeling stressed: "You seem to be feeling more stressed lately. Try some relaxation techniques."

[2104] Sending notifications

[2105] Step 15:

[2106] Emotional data and health data are analyzed comprehensively, and if an abnormality is detected, the server generates an emergency notification and sends it to the user (family) via the LINE app.

[2107] For example: "Urgent! Mom's heart rate is over 160 and she's in an unstable emotional state. Please check in immediately."

[2108] Purchase assistance

[2109] Receiving product requests

[2110] Step 16:

[2111] Users or elderly people use the LINE app to send requests for items necessary for daily life.

[2112] For example: "I need toilet paper."

[2113] Handling the request

[2114] Step 17:

[2115] The server analyzes the request message received from the user and identifies the required product.

[2116] Step 18:

[2117] The server uses the Yahoo Shopping API to search for information about the relevant product.

[2118] Generate and send the link

[2119] Step 19:

[2120] The server generates appropriate product offering links from the search results.

[2121] Step 20:

[2122] The server sends the generated link to the user via a LINE message.

[2123] For example: "You can buy toilet paper here [link]"

[2124] Specific examples

[2125] Health data monitoring and emotion data analysis

[2126] Step 1:

[2127] The device collects blood pressure data at 7:00 a.m.

[2128] Step 2:

[2129] The terminal transmits the acquired data to the server.

[2130] Step 3:

[2131] The server receives the data and stores it in a database.

[2132] Step 4:

[2133] The server passes the data to the AI ​​module for analysis.

[2134] Step 5:

[2135] The AI ​​module analyzes the data and returns the results to the server.

[2136] Step 6:

[2137] Based on the analysis results, the server will either notify you of a normal condition or generate an emergency notification.

[2138] Step 7:

[2139] If the result is normal, the server sends a LINE notification saying, "Mom's blood pressure this morning is 120 / 80, which is normal."

[2140] Step 8:

[2141] If an abnormality is detected, the server will send a LINE notification saying, "Urgent! Mom's blood pressure is 180 / 110. Please check immediately."

[2142] Step 9:

[2143] At the same time, the device captures the user's facial expressions with a camera, which are then analyzed by the emotion engine.

[2144] Step 10:

[2145] If the emotional state is determined to be unstable, the server will notify the user, "You've been feeling stressed lately. Try some relaxation techniques."

[2146] Assisted Buy execution

[2147] Step 1:

[2148] A user sends a message on LINE saying, "I need toilet paper."

[2149] Step 2:

[2150] The server receives and parses the message.

[2151] Step 3:

[2152] The server calls the Yahoo Shopping API and searches for the relevant product.

[2153] Step 4:

[2154] The server generates a product offer link from the search results.

[2155] Step 5:

[2156] The server replies with a link via LINE saying, "You can buy toilet paper here [link]."

[2157] Example 2

[2158] 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."

[2159] Continuously monitoring the health status of elderly people and immediately detecting and responding to abnormalities or emergencies are important challenges in today's aging society. It is also necessary to understand the emotional state of elderly people and provide appropriate support. However, current systems lack the ability to collect and analyze health and emotional data, preventing effective monitoring and support. Furthermore, there is a growing demand for systems that can quickly respond to users' requests for everyday items.

[2160] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a mobile information terminal means for acquiring health data, a means for transmitting the acquired health data to the central processing unit, a central processing unit means for receiving and storing the transmitted health data, an artificial intelligence module means for analyzing the received health data and detecting abnormal values, a means for sending an emergency notification if an abnormality is detected based on the analysis results, a means for notifying the user of a normal state based on the analysis results, a mobile information terminal means and an emotion engine means for collecting and analyzing emotion data, a means for generating and notifying an appropriate response based on the emotion data, and a means for receiving purchase requests from users and generating and transmitting an appropriate product provision link. This enables real-time monitoring of the health and emotional states of elderly people and immediate response when an abnormality occurs. Furthermore, the server can quickly respond to user requests, improving convenience in daily life.

[2161] "Terminal means" refers to a portable information terminal for collecting health data and emotional data and transmitting them to a server.

[2162] "Central processing unit means" refers to a processing unit that receives, stores, and analyzes data sent from the terminal.

[2163] "Artificial intelligence module means" refers to an artificial intelligence system that has the function of analyzing received data and detecting abnormal values.

[2164] "Means for sending emergency notifications" refers to a function that promptly sends a warning or notification to the user when an abnormality is detected.

[2165] "Means for notifying normal status" refers to a function that notifies the user when there is no abnormality in the health data.

[2166] "Emotion engine means" refers to a system that has the function of analyzing the user's emotional data and understanding their state.

[2167] The "means for generating and notifying an appropriate response" refers to a function for generating an appropriate response message for the user based on the analysis results of the emotion data and transmitting that message.

[2168] "Means for receiving a purchase request, generating a product provision link, and transmitting the same" refers to a function for receiving a purchase request from a user, generating an appropriate product provision link based on the request, and transmitting the link to the user.

[2169] The present invention provides a remote monitoring system that monitors the health status of elderly people, detects abnormalities, analyzes the user's emotions, and provides appropriate responses and support. This system includes the following components:

[2170] Terminal means

[2171] The terminal means consists of a smartphone or wearable device, and has the function of periodically acquiring health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. For example, the terminal automatically collects blood pressure data at 7:00 a.m. The terminal communicates with the healthcare devices using Bluetooth or Wi-Fi to acquire the data.

[2172] central processing unit means

[2173] The health data sent from the terminal is received by the central processing unit. The central processing unit is composed of a server, and the server stores the received data in a database. The database stores health data such as body temperature, blood pressure, and heart rate.

[2174] Artificial Intelligence Module Means

[2175] The health data stored in the central processing unit means is analyzed by the artificial intelligence module means. The AI ​​module compares it with past data and detects the presence of abnormal values ​​or patterns. If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app.

[2176] Emergency and regular notifications

[2177] If an abnormality is detected, the server will send an emergency notification, such as a message saying, "Urgent! Dad's heart rate has exceeded 160. Please check immediately." If no abnormality is detected, the server will notify the normal condition, such as a message saying, "Mom's temperature this morning is 36.5 degrees, which is normal."

[2178] Emotion Data and Emotion Engine Methods

[2179] The terminal means uses a camera and microphone to collect the user's facial expressions and voice and transmits them to the emotion engine means. The emotion engine means estimates the user's emotional state based on the collected data. The analysis results are transmitted to a server, which comprehensively analyzes the user's health data and emotional data to detect abnormal emotional or health states.

[2180] A means of generating and notifying responses

[2181] Based on the analysis results of the emotion engine, the server generates an appropriate response for the user. For example, if the user is feeling stressed, the server generates a message such as "You seem to be feeling more stressed recently. Try to find ways to relax," and sends it through the LINE app.

[2182] Purchase Request Processing

[2183] Users use the LINE app to send requests for items necessary for daily life on their devices. The server receives the request message, analyzes it, and identifies the required products. The server then searches for information about the relevant product using a common online shopping API and generates an appropriate product link. This link is then sent to the user via a LINE message. For example, a message such as "You can purchase toilet paper here [link]" may be sent.

[2184] Example prompt

[2185] "Your father's blood pressure is abnormal. Please check it immediately."

[2186] "Mom's temperature is normal."

[2187] "Your stress levels are rising. Relax."

[2188] "I need toilet paper."

[2189] This system will monitor the health status of the elderly in real time, respond immediately if an abnormality occurs, and analyze the user's emotional state to provide appropriate responses and support. It will also be able to quickly respond to requests from users for items necessary for daily life, greatly improving the convenience of daily life.

[2190] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2191] Step 1: Collecting health data

[2192] The device uses a smartphone or wearable device to collect health data from healthcare devices such as blood pressure monitors, thermometers, and heart rate sensors. Specifically, the device's app communicates with the healthcare devices via Bluetooth or Wi-Fi to collect data. For example, the device automatically collects blood pressure data at 7:00 a.m.

[2193] Input: Health data from blood pressure monitor, thermometer, and heart rate sensor

[2194] Output: Save acquired health data (body temperature, blood pressure, heart rate) on the device

[2195] Step 2: Send your health data

[2196] The device sends the acquired health data to the server at regular intervals (e.g., every hour) using a secure and fast communication protocol (e.g., HTTPS).

[2197] Input: Health data stored on the device

[2198] Output: Health data sent to the server using HTTPS protocol

[2199] Step 3: Receiving and storing health data

[2200] The server receives the health data sent from the device and automatically stores it in a database.

[2201] Input: Health data sent from the device

[2202] Output: Health data stored in a database

[2203] Step 4: Analyze health data

[2204] The server passes the stored health data to an AI module for analysis, which compares it with past data to detect any abnormal values ​​or patterns.

[2205] Input: Health data stored in a database

[2206] Output: Analysis results by the AI ​​module (outliers and patterns)

[2207] Step 5: Generate and send notifications

[2208] If an abnormality is detected, the server generates an emergency notification and promptly sends it to the user (family member) via the LINE app. Example: "Urgent! Dad's heart rate has exceeded 160. Please check immediately." If no abnormality is detected, the server notifies the user of the normal condition. Example: "Mom's temperature this morning was 36.5 degrees, which is normal."

[2209] Input: Analysis results of the AI ​​module

[2210] Output: Sends an emergency or normal notification to the LINE app.

[2211] Step 6: Collect emotion data

[2212] The device uses a camera and microphone to collect the user's facial expressions and voice. Specifically, the camera is activated at regular intervals to capture the user's facial expressions, and the microphone is used to record the user's tone and intonation of voice.

[2213] Input: User facial and voice data

[2214] Output: Emotion data stored on the device

[2215] Step 7: Sending Emotion Data

[2216] The device sends the collected emotion data to a server using a secure and fast communication protocol (e.g., HTTPS).

[2217] Input: Emotion data stored on the device

[2218] Output: Emotion data sent to the server using HTTPS protocol

[2219] Step 8: Analyze the sentiment data

[2220] The emotion engine estimates the user's emotional state based on the collected data and sends the analysis results to the server.

[2221] Input: Emotion data sent to the server

[2222] Output: Analysis results by the emotion engine

[2223] Step 9: Comprehensive analysis and response generation

[2224] The server comprehensively analyzes the user's health and emotional data to detect abnormal emotional or health conditions. Based on the results, the server generates an appropriate response. For example, if the user is feeling stressed, the server generates a message such as, "You seem to be feeling more stressed recently. Please try to find ways to relax."

[2225] Input: Comprehensive analysis results of health data and emotional data

[2226] Output: The appropriate response message

[2227] Step 10: Send a response message

[2228] The server sends the generated response message to the user via the LINE app.

[2229] Input: Server-generated response message

[2230] Output: Response message sent to the LINE app

[2231] Step 11: Receiving a Purchase Request

[2232] Users use the LINE app to send requests for items necessary for daily life via their terminal means.

[2233] Input: Purchase request message sent by the user

[2234] Output: Purchase request message received on the device

[2235] Step 12: Parse the purchase request

[2236] The server receives the request message, analyzes it, and identifies the required product. The server then searches for information about the corresponding product using a standard online shopping API.

[2237] Input: Purchase request message sent from the device

[2238] Output: Product information search results

[2239] Step 13: Generate and send your product offer link

[2240] The server generates the appropriate product link from the search results and sends it to the user via LINE message. Example: "You can buy toilet paper here [link]".

[2241] Input: Product information search results

[2242] Output: LINE message containing the product offer link

[2243] This system will enable real-time monitoring of the health and emotional state of the elderly, and will respond immediately if an abnormality occurs. It will also be able to quickly respond to requests from users for items necessary for daily life, improving the convenience of daily life.

[2244] (Application example 2)

[2245] 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."

[2246] Until now, there has been no system that can monitor not only the health status of elderly people but also the emotional state of passengers in real time to comprehensively improve safety and comfort. Furthermore, autonomous vehicles with many elderly passengers are required to instantly detect abnormalities in their health and emotional states and take appropriate action. Furthermore, a system is needed that can comprehensively analyze passenger health and emotional data and promptly notify passengers and relevant parties when an abnormality is detected.

[2247] The specific processing by the specific 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 terminal means for acquiring health data, means for transmitting the acquired health data to the server, server means for receiving and storing the transmitted health data, AI module means for analyzing the received health data and detecting abnormal values, means for sending an emergency notification if an abnormality is detected based on the analysis results, means for notifying the normal state based on the analysis results, sensor means for acquiring the facial expressions and voice of the occupant and estimating their emotional state, server means for transmitting and analyzing the emotional data, and means for generating and notifying an appropriate response based on the emotional data. This enables real-time monitoring of the health and emotional states of elderly people and promptly sending an emergency notification if an abnormality is detected. Furthermore, providing appropriate responses and support according to the occupant's emotional state can improve safety and comfort.

[2248] "Elderly" refers to people aged 65 and over, and health risks generally increase with age.

[2249] "Health status" refers to the physical condition of an individual, assessed comprehensively from physical data such as body temperature, blood pressure, and heart rate.

[2250] "Monitoring" is the act of acquiring and analyzing data in real time to detect abnormalities and changes.

[2251] A "remote monitoring system" is a system that monitors the health and safety of people in remote locations via the Internet or wireless communications, without the need for physical contact.

[2252] "Terminal means" refers to hardware such as smartphones and wearable devices that are used to collect health data.

[2253] "Server means" refers to a server for receiving, storing, and analyzing data.

[2254] "Data transmission means" refers to the communication protocol or technology used to transmit health data from the terminal to the server.

[2255] "AI module means" is a software module that uses artificial intelligence to analyze data and detect anomalies.

[2256] "Notifi...

Claims

1. A remote monitoring system for monitoring the health status of an elderly person, a terminal means for acquiring health data; means for transmitting the acquired health data to a server; a server means for receiving and storing the transmitted health data; An AI module means for analyzing the received health data and detecting abnormal values; a means for sending an emergency notification when an abnormality is detected based on the analysis results; A means for notifying the normal state based on the analysis result; A system including:

2. 10. The system of claim 1, further comprising means for transmitting a notification from the server means and displaying an emergency alert to the user when an abnormality based on the health data is detected.

3. 10. The system of claim 1, further comprising means for receiving a purchase request from a user and generating and transmitting an appropriate product offering link.

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