system

Abstract

We provide the system. [Solution] Perceptual means for acquiring external information, A processing means for analyzing the target's behavioral patterns based on acquired information, Monitoring means for continuously monitoring the target health data, Information processing means for protecting personal information, A notification system for issuing warnings when an anomaly is detected, A means of communication to provide emotional support through interaction using a terminal, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a problem of reducing the burden on people engaged in caregiving and childcare and preventing social isolation by effectively ensuring the safety of the elderly and children. Conventional methods have problems such as difficulties in physical monitoring, insufficient protection of data privacy, and a lack of an efficient mechanism for quickly detecting abnormalities.

Means for Solving the Problems

[0005] This invention provides a system that monitors the behavior and status of a subject 24 hours a day using sensor means to acquire external environmental information. This allows for the rapid detection of behaviors that deviate from normal behavior using analysis means to analyze behavioral patterns. Furthermore, monitoring means that continuously monitor vital data enable immediate detection of abnormal health conditions. The system also includes data processing means that consider privacy protection, and provides a system that can quickly notify external parties via notification means when an abnormality is detected. This effectively realizes the safety and health management of the elderly and children, and reduces the burden on caregivers and childcare providers.

[0006] "Sensing means" refers to devices and technologies used to acquire environmental and physical information of a subject.

[0007] "Analysis methods" refer to techniques that analyze acquired data to identify the behavioral patterns of the subjects.

[0008] "Monitoring measures" refer to devices and systems that continuously monitor a person's health and living conditions and quickly detect any abnormalities.

[0009] "Data processing means" refers to technologies that extract useful information while ensuring privacy protection for acquired data.

[0010] A "notification means" refers to a technology or device for quickly transmitting information to pre-configured recipients when an anomaly is detected. [Brief explanation of the drawing]

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

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

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

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

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

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

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

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

[0019] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0032] In implementing this invention, the system for protecting the safety and health of the elderly and children is designed so that each component functions in coordination. First, the terminal, acting as a sensor, acquires environmental information and vital data of the subject in real time through AI cameras and IoT sensors. This data is temporarily stored in the terminal and subjected to necessary data processing. In particular, camera images are masked to protect privacy.

[0033] Data acquired by the device is securely transmitted to the server. The server has analytical capabilities and analyzes the subject's behavioral patterns and health status based on the information stored in the database. If unusual behavior or abnormal values ​​are detected, the server's notification system quickly issues an alert and notifies designated family members or care staff. This notification can be made in multiple ways, such as email, application notifications, or, if necessary, by phone.

[0034] Users can receive daily monitoring of elderly individuals and children through the device, and also receive emotional support through interaction with AI. This interaction is made possible when the AI ​​on the device senses the user's voice and actions and sends relevant information to the server. The AI ​​constantly evaluates the user's condition and provides feedback to the family as needed to prevent social isolation.

[0035] As a concrete example, considering the monitoring of elderly people at night, the device monitors their breathing and heart rate while they sleep. If an abnormality is detected, the server immediately makes a judgment and sends a message via a notification system prompting emergency action. In this way, the health status of elderly people can be constantly monitored, and a rapid response is possible in emergencies. This enables comprehensive safety management and health maintenance.

[0036] The following describes the processing flow.

[0037] Step 1:

[0038] The device activates AI cameras and IoT sensors to acquire environmental information about the subject, collecting data in real time. This includes electricity usage, room temperature, motion detection, and vital signs.

[0039] Step 2:

[0040] The device temporarily stores the acquired raw data in its internal memory and applies a masking process to the video data to protect privacy. This process highlights necessary information without infringing on privacy.

[0041] Step 3:

[0042] The terminal sends the processed data to the server. During this process, the data is encrypted to ensure security during transmission.

[0043] Step 4:

[0044] The server stores the received data in a database and applies algorithms for behavioral analysis. This allows for the analysis of typical behavioral patterns and the establishment of benchmarks.

[0045] Step 5:

[0046] The server performs analysis based on the subject's behavior and vital data to detect anomalies. If it detects anomalies exceeding the criteria or unregistered behavior, it prepares an alert.

[0047] Step 6:

[0048] Based on detected anomalies, the server activates notification mechanisms to send alerts. Information is then quickly provided to family members and caregivers via email and app notifications.

[0049] Step 7:

[0050] The user interacts with the AI ​​assistant via the device. The device analyzes the user's voice input, assesses their emotions, and sends the information to the server as needed.

[0051] Step 8:

[0052] The server assesses the user's mental state and, if there are signs of social isolation, notifies the family and informs them of the need for follow-up.

[0053] Through these steps, the system comprehensively manages the safety and health of the individuals involved and enables immediate response as needed.

[0054] (Example 1)

[0055] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0056] There is a need to constantly monitor the safety and health of the elderly and children, and to quickly detect and address any abnormal behavior or changes in their health. Furthermore, it is necessary to provide appropriate communication methods while protecting privacy. There are currently insufficient systems that meet these requirements, and this is a challenge that needs to be addressed.

[0057] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0058] In this invention, the server includes sensor means for acquiring external information, analysis means for analyzing operating patterns based on the acquired information, and monitoring means for continuously monitoring health-related data. This makes it possible to monitor the safety and health of the elderly and children in real time and to quickly detect and notify of any abnormalities.

[0059] "Sensor means for acquiring external information" refers to devices that detect a subject's environmental information and health status in real time.

[0060] "Analysis methods for analyzing behavioral patterns" refers to technologies that perform processing to identify specific behavioral patterns or anomalies based on acquired data.

[0061] "Monitoring methods for continuously monitoring health-related data" refers to functions and tools for continuously monitoring biometric information in real time.

[0062] "Data processing measures to protect privacy" refers to methods and technologies for anonymizing or concealing personally identifiable information.

[0063] "Notification means for communication when an anomaly is detected" refers to a method for quickly informing relevant parties when an unusual situation occurs.

[0064] "A means of dialogue for interacting with a subject via voice input" refers to technology for communicating with a subject based on voice input.

[0065] This invention is a system aimed at monitoring the safety and health of the elderly and children, and it functions through the coordinated operation of terminals, servers, and users.

[0066] First, the device uses an AI camera and IoT sensors to acquire environmental information and vital data of the subject in real time. The AI ​​camera monitors surrounding movements and sounds, while the IoT sensors measure the subject's heart rate and respiratory rate. This allows the device to accumulate data on the subject's health status. The device incorporates data processing technologies to protect privacy; for example, camera footage is blurred.

[0067] The acquired data is temporarily stored on the device and then transmitted to the server using Wi-Fi or mobile data communication. The server analyzes this data and detects anomalies by comparing it with historical information stored in the database. Analysis using machine learning algorithms is performed, enabling the evaluation of behavioral patterns and health status.

[0068] If an anomaly is detected, the server will send email and application notifications to registered family members and care staff. It also has a function to make phone calls as needed. This ensures a system that allows for a quick response no matter where you are.

[0069] Users can receive daily monitoring from their device and even communicate with an interactive AI through voice. For example, if a user feels anxious, they can speak into the device, and the AI ​​will analyze their voice to provide appropriate advice and information. This voice interaction data is also sent to a server and used to assess the user's mental state.

[0070] As a concrete example, considering the monitoring of elderly people at night, the device monitors the elderly person's breathing and heart rate while they sleep. If an abnormality is detected, the server immediately makes a judgment and sends a message via a notification system prompting immediate action.

[0071] An example of a prompt sentence to input into the generating AI model is, "Please provide details about the nighttime health monitoring system for the elderly."

[0072] Thus, this invention is designed to comprehensively protect the safety and health of the elderly and children by making full use of technical means.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The device uses an AI camera and IoT sensors to collect environmental information and vital data from the subject. Inputs include physical movement and physiological data. The device acquires this data in real time and temporarily stores it in its internal memory. The AI ​​camera captures video data, while temperature and humidity sensors record environmental information.

[0076] Step 2:

[0077] The terminal performs preprocessing on the acquired data. Specifically, it removes noise from the input data and processes it into a format necessary for anomaly detection. For data calculation, it uses signal processing algorithms to filter out anomalies. In particular, it applies mosaic processing to video data to protect privacy. The output is a preprocessed dataset.

[0078] Step 3:

[0079] The terminal sends pre-processed data to the server. The input is the data processed in the previous step, and the output is the data securely transferred to the server. The data is encrypted and sent to the server via a secure communication protocol.

[0080] Step 4:

[0081] The server analyzes the received data. The input consists of multiple datasets from the terminal. The server uses machine learning algorithms to analyze the data and detect anomalies. For example, it can identify unnatural movements at night or sudden increases in heart rate. The output is a result confirming whether or not an anomaly was detected.

[0082] Step 5:

[0083] If an anomaly is detected, the server notifies registered family members or caregivers via a notification system. The input is the result of the anomaly detection. The server creates and sends an email or app notification. The output is that the recipient is notified of the anomaly.

[0084] Step 6:

[0085] Users receive daily monitoring and emotional support through the device. Input consists of the user's voice and actions, which the device detects and transmits to the server. Furthermore, a generative AI model is used to provide support through voice dialogue. Output includes feedback and advice for the user.

[0086] In this way, the system can continuously monitor the safety and health of the elderly and children through a series of processing steps.

[0087] (Application Example 1)

[0088] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0089] In today's aging society, effectively maintaining the safety and health of the elderly and children is a crucial challenge. Furthermore, it is essential to provide them with a supportive environment where they do not feel isolated and receive emotional support. However, there are insufficient means to simultaneously achieve both daily monitoring and emotional support. The development of a system that can provide integrated physical and emotional safety and security is necessary.

[0090] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0091] In this invention, the server includes perceptual means for acquiring external information, processing means for analyzing the target's behavioral patterns based on the acquired information, monitoring means for continuously monitoring the target's health data and psychological state, information processing means for protecting personal information, notification means for issuing warnings when an anomaly is detected, and communication means for providing mental support through communication using a terminal. This makes it possible to comprehensively manage both the physical safety and mental support provided to the target.

[0092] "Means of perception" refers to sensors and devices used to acquire external information, and the function of sensing the environment and state of a subject through these means.

[0093] A "processing means" is a system that includes algorithms and programs for analyzing the target's behavioral patterns based on acquired information and extracting meaningful data.

[0094] "Monitoring methods" refer to technologies used to continuously observe a subject's health data and psychological state and to detect any abnormal conditions.

[0095] "Information processing means" refers to technologies and protocols that appropriately mask or encrypt data while protecting personal information.

[0096] A "notification system" is a function that immediately issues a warning when an anomaly is detected and transmits the information to the necessary parties.

[0097] "Means of interaction" refers to functions that use terminals to engage in dialogue with the target individual and provide emotional support and communication.

[0098] To realize this invention, IoT sensors and AI cameras are first used as perceptual means for acquiring external information. This makes it possible to sense environmental information and vital data of the target elderly person or child in real time. The terminal continuously monitors this data and applies masking processing to the video data as an information processing means to protect personal information.

[0099] The acquired data is transmitted to the server via a secure protocol. The server analyzes the data using a generative AI model and, in the event of an anomaly, promptly notifies family members and care staff through notification mechanisms. Notifications are made via email or application notifications. Furthermore, the device provides emotional support by engaging in natural conversations with the individual as a means of interaction.

[0100] As a concrete example, consider monitoring elderly people at night. The device uses an AI camera to monitor the elderly person's breathing and heart rate while they sleep. If an abnormality is detected, the server makes a judgment and sends a notification, prompting emergency action. The generated information is analyzed by a generative AI model and fed back to the family. Through this process, it becomes possible to consistently manage the safety and health of the elderly person.

[0101] An example of how the generative AI model can be used is a prompt such as, "Please describe in detail a scenario in which an abnormality is detected while an elderly person is napping in their living room, and what kind of support should be provided and how it should be notified." In this way, technologically advanced monitoring and emotional support are realized.

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The device acquires external environmental information and vital data of the subject. Using an AI camera and IoT sensors, it detects data in real time and temporarily stores the results within the device. Inputs are environmental data and vital signs, while output is organized data.

[0105] Step 2:

[0106] The device applies data processing to the acquired data to protect privacy. Specifically, video data is masked. This process blurs information so that individuals cannot be identified. The input is the original video data, and the output is the video data after masking.

[0107] Step 3:

[0108] The masked data is sent to the server via a secure protocol. The server receives this data and prepares to analyze the information. The input is the masked data, and the output is the organized data for analysis.

[0109] Step 4:

[0110] The server uses a generative AI model to analyze data. It evaluates the target's behavioral patterns and health status to determine if there are any abnormalities. The input is organized data, and the output is the analysis result regarding the presence or absence of abnormalities.

[0111] Step 5:

[0112] If an anomaly is detected, the server will notify relevant family members or care staff using notification methods. Application notifications and email are used as notification methods. The input is the analysis results, and the output is a notification alert message.

[0113] Step 6:

[0114] The device engages in dialogue to provide emotional support through means of interaction with the user. It utilizes a generative AI model to support the user's mental well-being through relaxed conversation. Input is the user's statements and actions, and output is the AI-generated dialogue.

[0115] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0116] In implementing the present invention, the system for effectively monitoring the safety and health of the elderly and children includes, in addition to sensor means, analysis means, monitoring means, data processing means, and notification means, an emotion engine that recognizes the user's emotions. The terminal uses an AI camera or IoT sensor as a sensor means to acquire environmental data and vital signs of the subject. This data is masked to protect privacy before being transmitted to the server.

[0117] The server analyzes the received data using analytical tools to evaluate the subject's behavioral patterns and health status. Furthermore, the emotion engine is responsible for analyzing the user's emotional state through voice input. The emotion engine has the function of recognizing the user's emotional changes in real time and evaluating their mental state based on this.

[0118] The user participates in a process of evaluating their own emotional state by interacting with AI through the device. The device interprets voice information and nonverbal elements using an emotion engine and sends the results to the server. The server continuously evaluates the user's mental state based on this information. If an abnormality is detected, it quickly notifies family members and care staff via a notification system.

[0119] For example, if a user makes a statement indicating emotional distress during a normal conversation, the device's emotion engine detects this change. The server immediately analyzes the results and, if necessary, sends a notification to family members to encourage early intervention. This process enables rapid support and follow-up tailored to the user's emotions and mental state.

[0120] The following describes the processing flow.

[0121] Step 1:

[0122] The device activates sensor devices to acquire environmental information and vital data of the subject. This includes collecting video data using an AI camera and measuring temperature, humidity, and heart rate using IoT sensors.

[0123] Step 2:

[0124] The device applies a masking process to the acquired data to protect privacy. This ensures privacy before the data is transmitted.

[0125] Step 3:

[0126] The terminal sends the processed data to the server. The data transmission is encrypted to ensure data security.

[0127] Step 4:

[0128] The server stores the received data in a database and uses analysis tools to analyze behavioral patterns and health status. It detects unusual behavior and changes in vital signs.

[0129] Step 5:

[0130] The device activates an emotion engine, collects voice data through interaction with the user, and recognizes changes in emotion. The emotion engine analyzes voice tone and speech content to evaluate the user's emotional state.

[0131] Step 6:

[0132] The server analyzes the emotional state evaluation results obtained from the emotion engine and activates a notification system if it detects abnormal emotions or mental burden.

[0133] Step 7:

[0134] The server notifies family members and caregivers of any detected anomalies or emotional disturbances. Notifications are sent via email or app to encourage prompt action.

[0135] Step 8:

[0136] Users can receive feedback and advice from the server through their device interface as needed. This enhances user confidence and improves the support system.

[0137] (Example 2)

[0138] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0139] To effectively monitor the safety and health of the elderly and children, it is necessary to continuously monitor situational and biometric data and to quickly detect anomalies while protecting privacy. However, existing systems have difficulty evaluating non-physical elements such as emotional changes in real time, which can lead to delays in early response.

[0140] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0141] In this invention, the server includes detection means for acquiring external situational data, evaluation means for evaluating the behavioral patterns of a subject based on the acquired situational data, and emotion analysis means for recognizing the user's emotional state from voice input. This makes it possible to comprehensively evaluate the user's physical and emotional state and take prompt action as needed.

[0142] "Detection means" refers to a device or method used to acquire external situational data.

[0143] "Evaluation means" refers to a process or technique used to evaluate the behavioral patterns of a subject based on acquired situational data.

[0144] "Monitoring means" refers to a device or system for continuously monitoring a subject's biometric data.

[0145] "Information processing means" refers to a system or algorithm used to process and modify data in order to protect privacy.

[0146] "Notification means" refers to a method or device for informing relevant parties when an anomaly is detected.

[0147] "Emotional analysis means" refers to a technology or system for recognizing a user's emotional state from voice input.

[0148] A "dialogue method" is a communication system for evaluating the mental state of the subject and, if necessary, notifying external parties.

[0149] "Treatment measures" refer to actions or methods for providing prompt support based on the emotional state of the person concerned.

[0150] This invention is specifically implemented as a system for monitoring the safety and health of the elderly and children. The system is primarily composed of the interaction between terminals, servers, and users.

[0151] The device uses hardware such as AI cameras and IoT sensors to acquire data on the subject's surrounding environment and biometric data. This data includes temperature, humidity, heart rate, and activity level. This information is masked to protect data privacy before being sent to the server.

[0152] The server uses machine learning algorithms as an analysis tool to evaluate the subject's behavioral patterns and health status based on the received data. Furthermore, the server employs emotion analysis tools to recognize changes in the user's emotional state by analyzing their voice in real time. These analysis results serve as important input for evaluating the mental state.

[0153] The user participates in an interaction with the AI ​​through the device and is involved in the emotion analysis process. The user provides voice input, which the device processes through an emotion analysis system and sends the analysis results to a server. Based on this information, if the server detects an anomaly, it will promptly notify family members or care staff through a notification system.

[0154] As a concrete example, if a user makes a statement indicating emotional distress during a normal conversation, the device detects this change using emotion analysis. The server analyzes the change in emotion and, if necessary, sends a notification to the family. This process enables rapid support for the user's mental state.

[0155] As an example of a prompt to a generative AI model, you could use a sentence like, "Please describe the procedure for identifying the user's emotional state from their voice data, evaluating its changes in real time, and providing notifications."

[0156] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0157] Step 1:

[0158] The device uses an AI camera and IoT sensors to acquire external environmental data and biometric data of the subject. The input here is raw data from the sensors, and the output is a dataset including temperature, humidity, heart rate, activity level, etc. Specifically, the AI ​​camera captures the subject's movements, and the IoT sensors measure vital signs.

[0159] Step 2:

[0160] The device performs privacy-protecting masking on the acquired data. The dataset acquired in the previous step is used as input, and the output is data with privacy information protected. Specifically, personally identifiable information is extracted and encrypted or deleted.

[0161] Step 3:

[0162] The terminal sends masked data to the server. The input here is the masked data, and the output is the transfer of that data to the server. Specifically, the terminal generates a data package and transfers it using a secure protocol.

[0163] Step 4:

[0164] The server analyzes the received data and evaluates behavioral patterns and health status. The input here is the data sent to the server, and the output is an indicator of behavioral patterns and health status as an evaluation result. Specifically, it uses machine learning algorithms to analyze the data, and the evaluation model is executed within the software.

[0165] Step 5:

[0166] The server analyzes the user's voice input using emotion analysis tools. The input is voice data, and the output is an evaluation result indicating the emotional state. Specifically, the tone and tempo of the voice are passed through an analysis algorithm, and an emotion model is executed.

[0167] Step 6:

[0168] Users interact with the AI ​​through their device and participate in the assessment of their emotional state. The input is the user's voice, and the output is feedback resulting from the emotion analysis. Specifically, the user speaks into the device, and their voice is interpreted in real time.

[0169] Step 7:

[0170] The server, upon detecting an anomaly, promptly notifies family members and caregivers through notification channels. Inputs are assessed health and emotional states, and outputs are notification messages. Specifically, the server automatically sends emails or alerts when notification conditions are met.

[0171] (Application Example 2)

[0172] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0173] To ensure the safety and health of the elderly and children, real-time monitoring of their health and emotional states is necessary. However, systems that effectively achieve this lack mechanisms to accurately assess emotional states, quickly detect abnormalities, and prompt appropriate responses. Solving this challenge is essential to providing faster and more appropriate care and support.

[0174] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0175] In this invention, the server includes sensing means for acquiring external environmental information, analysis means for analyzing the behavioral patterns of a subject based on the acquired environmental information, and monitoring means for continuously monitoring the subject's health data. This enables real-time evaluation of the subject's emotional state, immediate detection of abnormalities, appropriate notification, and rapid response.

[0176] "Sensing means" refers to devices or methods for acquiring external environmental information, and is a technology that uses cameras, sensors, etc., to detect the situation of a subject.

[0177] "Analysis means" refers to devices or methods that analyze the behavioral patterns of subjects based on acquired environmental information, and is a technology for understanding the trends of subjects by analyzing data.

[0178] "Health data" refers to data that indicates the physical condition of a subject, and includes information used to evaluate their health status, such as vital signs and sleep patterns.

[0179] "Monitoring means" refers to devices or methods that continuously monitor a subject's health data, and is a technology for constantly checking the latest health status and detecting abnormalities.

[0180] "Information processing means" refers to devices and methods that process acquired data while protecting privacy, and is a technology for safely handling personal information.

[0181] A "notification system" is a device or method that quickly notifies relevant parties when an anomaly is detected, and is a technology that prompts necessary action.

[0182] An "emotion recognition engine" is a device or method for evaluating a person's emotional state in real time, and it is a technology that determines emotions by analyzing voice, facial expressions, etc.

[0183] The system for implementing this invention includes several key components to monitor the safety and health of the subject. The system operates via devices such as smart glasses or smartphones, which are equipped with AI cameras and sensors. This makes it possible to acquire environmental information and health data in real time.

[0184] The device uses an emotion recognition engine based on Python and TensorFlow® to analyze the subject's emotional state in real time. Video data is preprocessed using OpenCV to extract specific features. Then, emotions are analyzed using a TensorFlow generative AI model.

[0185] The server receives data transmitted from the terminal and evaluates behavioral patterns using analysis tools. It also continuously monitors health data using monitoring tools, and if an abnormality is detected, it notifies relevant parties using notification tools.

[0186] For example, if a particular resident exhibits unusual behavior or facial expressions, the emotion recognition engine analyzes the change, and the server immediately determines that something is wrong. It can then notify family members or care staff as needed, prompting a quick response.

[0187] Examples of prompts for a generative AI model are as follows:

[0188] "Analyze the camera footage and assess the residents' emotional and physical condition. If any abnormalities are found, provide advice on what actions should be taken."

[0189] This system enables prompt and appropriate monitoring and support based on the emotions and health status of the individuals involved.

[0190] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0191] Step 1:

[0192] The device uses an AI camera to capture video of the subject. The input is real-time video data, and by acquiring this video data, it captures the basic information necessary for subsequent processing steps.

[0193] Step 2:

[0194] The device preprocesses video data using OpenCV to extract the subject's features. The input is captured video data, and the output is numerical data related to facial features and expressions. This preprocessing allows for more accurate emotion analysis.

[0195] Step 3:

[0196] The device uses TensorFlow and analyzes emotional states from feature points extracted using a generative AI model. The input is feature point data, and the output is data indicating the type and degree of emotion. This visualizes the user's current emotional state.

[0197] Step 4:

[0198] The terminal sends the analyzed emotional data to the server. The input is the result of the emotional analysis, and the output is data used for further analysis on the server side. This transmission allows the emotional state of the subject to be managed centrally.

[0199] Step 5:

[0200] The server analyzes the received emotional data and evaluates the subject's behavioral patterns and health status. The input consists of the emotional analysis results and past health data, while the output is data showing the evaluation results. The analysis clarifies the subject's mental state.

[0201] Step 6:

[0202] If the server detects an anomaly based on the analysis results, it will promptly notify the relevant parties using a notification system. The input is the analysis result data, and the output is alert information sent to the relevant parties. This notification will prompt appropriate action.

[0203] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0204] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0205] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0206] [Second Embodiment]

[0207] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0208] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0209] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0210] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0211] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0212] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0213] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0214] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0215] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0216] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0217] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0218] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0219] In implementing this invention, the system for protecting the safety and health of the elderly and children is designed so that each component functions in coordination. First, the terminal, acting as a sensor, acquires environmental information and vital data of the subject in real time through AI cameras and IoT sensors. This data is temporarily stored in the terminal and subjected to necessary data processing. In particular, camera images are masked to protect privacy.

[0220] Data acquired by the device is securely transmitted to the server. The server has analytical capabilities and analyzes the subject's behavioral patterns and health status based on the information stored in the database. If unusual behavior or abnormal values ​​are detected, the server's notification system quickly issues an alert and notifies designated family members or care staff. This notification can be made in multiple ways, such as email, application notifications, or, if necessary, by phone.

[0221] Users can receive daily monitoring of elderly individuals and children through the device, and also receive emotional support through interaction with AI. This interaction is made possible when the AI ​​on the device senses the user's voice and actions and sends relevant information to the server. The AI ​​constantly evaluates the user's condition and provides feedback to the family as needed to prevent social isolation.

[0222] As a concrete example, considering the monitoring of elderly people at night, the device monitors their breathing and heart rate while they sleep. If an abnormality is detected, the server immediately makes a judgment and sends a message via a notification system prompting emergency action. In this way, the health status of elderly people can be constantly monitored, and a rapid response is possible in emergencies. This enables comprehensive safety management and health maintenance.

[0223] The following describes the processing flow.

[0224] Step 1:

[0225] The device activates AI cameras and IoT sensors to acquire environmental information about the subject, collecting data in real time. This includes electricity usage, room temperature, motion detection, and vital signs.

[0226] Step 2:

[0227] The device temporarily stores the acquired raw data in its internal memory and applies a masking process to the video data to protect privacy. This process highlights necessary information without infringing on privacy.

[0228] Step 3:

[0229] The terminal sends the processed data to the server. During this process, the data is encrypted to ensure security during transmission.

[0230] Step 4:

[0231] The server stores the received data in a database and applies algorithms for behavioral analysis. This allows for the analysis of typical behavioral patterns and the establishment of benchmarks.

[0232] Step 5:

[0233] The server performs analysis based on the subject's behavior and vital data to detect anomalies. If it detects anomalies exceeding the criteria or unregistered behavior, it prepares an alert.

[0234] Step 6:

[0235] Based on detected anomalies, the server activates notification mechanisms to send alerts. Information is then quickly provided to family members and caregivers via email and app notifications.

[0236] Step 7:

[0237] The user interacts with the AI ​​assistant via the device. The device analyzes the user's voice input, assesses their emotions, and sends the information to the server as needed.

[0238] Step 8:

[0239] The server assesses the user's mental state and, if there are signs of social isolation, notifies the family and informs them of the need for follow-up.

[0240] Through these steps, the system comprehensively manages the safety and health of the individuals involved and enables immediate response as needed.

[0241] (Example 1)

[0242] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0243] There is a need to constantly monitor the safety and health of the elderly and children, and to quickly detect and address any abnormal behavior or changes in their health. Furthermore, it is necessary to provide appropriate communication methods while protecting privacy. There are currently insufficient systems that meet these requirements, and this is a challenge that needs to be addressed.

[0244] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0245] In this invention, the server includes sensor means for acquiring external information, analysis means for analyzing operating patterns based on the acquired information, and monitoring means for continuously monitoring health-related data. This makes it possible to monitor the safety and health of the elderly and children in real time and to quickly detect and notify of any abnormalities.

[0246] "Sensor means for acquiring external information" refers to devices that detect a subject's environmental information and health status in real time.

[0247] "Analysis methods for analyzing behavioral patterns" refers to technologies that perform processing to identify specific behavioral patterns or anomalies based on acquired data.

[0248] "Monitoring methods for continuously monitoring health-related data" refers to functions and tools for continuously monitoring biometric information in real time.

[0249] "Data processing measures to protect privacy" refers to methods and technologies for anonymizing or concealing personally identifiable information.

[0250] "Notification means for communication when an anomaly is detected" refers to a method for quickly informing relevant parties when an unusual situation occurs.

[0251] "A means of dialogue for interacting with a subject via voice input" refers to technology for communicating with a subject based on voice input.

[0252] This invention is a system aimed at monitoring the safety and health of the elderly and children, and it functions through the coordinated operation of terminals, servers, and users.

[0253] First, the device uses an AI camera and IoT sensors to acquire environmental information and vital data of the subject in real time. The AI ​​camera monitors surrounding movements and sounds, while the IoT sensors measure the subject's heart rate and respiratory rate. This allows the device to accumulate data on the subject's health status. The device incorporates data processing technologies to protect privacy; for example, camera footage is blurred.

[0254] The acquired data is temporarily stored on the device and then transmitted to the server using Wi-Fi or mobile data communication. The server analyzes this data and detects anomalies by comparing it with historical information stored in the database. Analysis using machine learning algorithms is performed, enabling the evaluation of behavioral patterns and health status.

[0255] If an anomaly is detected, the server will send email and application notifications to registered family members and care staff. It also has a function to make phone calls as needed. This ensures a system that allows for a quick response no matter where you are.

[0256] Users can receive daily monitoring from their device and even communicate with an interactive AI through voice. For example, if a user feels anxious, they can speak into the device, and the AI ​​will analyze their voice to provide appropriate advice and information. This voice interaction data is also sent to a server and used to assess the user's mental state.

[0257] As a concrete example, considering the monitoring of elderly people at night, the device monitors the elderly person's breathing and heart rate while they sleep. If an abnormality is detected, the server immediately makes a judgment and sends a message via a notification system prompting immediate action.

[0258] An example of a prompt sentence to input into the generating AI model is, "Please provide details about the nighttime health monitoring system for the elderly."

[0259] Thus, this invention is designed to comprehensively protect the safety and health of the elderly and children by making full use of technical means.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The device uses an AI camera and IoT sensors to collect environmental information and vital data from the subject. Inputs include physical movement and physiological data. The device acquires this data in real time and temporarily stores it in its internal memory. The AI ​​camera captures video data, while temperature and humidity sensors record environmental information.

[0263] Step 2:

[0264] The terminal performs preprocessing on the acquired data. Specifically, it removes noise from the input data and processes it into a format necessary for anomaly detection. For data calculation, it uses signal processing algorithms to filter out anomalies. In particular, it applies mosaic processing to video data to protect privacy. The output is a preprocessed dataset.

[0265] Step 3:

[0266] The terminal sends pre-processed data to the server. The input is the data processed in the previous step, and the output is the data securely transferred to the server. The data is encrypted and sent to the server via a secure communication protocol.

[0267] Step 4:

[0268] The server analyzes the received data. The input consists of multiple datasets from the terminal. The server uses machine learning algorithms to analyze the data and detect anomalies. For example, it can identify unnatural movements at night or sudden increases in heart rate. The output is a result confirming whether or not an anomaly was detected.

[0269] Step 5:

[0270] If an anomaly is detected, the server notifies registered family members or caregivers via a notification system. The input is the result of the anomaly detection. The server creates and sends an email or app notification. The output is that the recipient is notified of the anomaly.

[0271] Step 6:

[0272] Users receive daily monitoring and emotional support through the device. Input consists of the user's voice and actions, which the device detects and transmits to the server. Furthermore, a generative AI model is used to provide support through voice dialogue. Output includes feedback and advice for the user.

[0273] In this way, the system can continuously monitor the safety and health of the elderly and children through a series of processing steps.

[0274] (Application Example 1)

[0275] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0276] In today's aging society, effectively maintaining the safety and health of the elderly and children is a crucial challenge. Furthermore, it is essential to provide them with a supportive environment where they do not feel isolated and receive emotional support. However, there are insufficient means to simultaneously achieve both daily monitoring and emotional support. The development of a system that can provide integrated physical and emotional safety and security is necessary.

[0277] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0278] In this invention, the server includes perceptual means for acquiring external information, processing means for analyzing the target's behavioral patterns based on the acquired information, monitoring means for continuously monitoring the target's health data and psychological state, information processing means for protecting personal information, notification means for issuing warnings when an anomaly is detected, and communication means for providing mental support through communication using a terminal. This makes it possible to comprehensively manage both the physical safety and mental support provided to the target.

[0279] "Means of perception" refers to sensors and devices used to acquire external information, and the function of sensing the environment and state of a subject through these means.

[0280] A "processing means" is a system that includes algorithms and programs for analyzing the target's behavioral patterns based on acquired information and extracting meaningful data.

[0281] The "monitoring means" is a technology used to continuously observe the target's health data and mental state and detect abnormal states different from normal ones.

[0282] The "information processing means" refers to technologies and protocols for appropriately masking and encrypting data while protecting personal information.

[0283] The "notification means" is a function that immediately gives a warning when an abnormality is detected and transmits information to necessary related parties.

[0284] The "communication means" is a function for interacting with the target using a terminal and providing mental support and communication.

[0285] To implement this invention, first, IoT sensors and AI cameras are used as perception means for acquiring external information. Thereby, it becomes possible to sense in real time the environmental information and vital data of the target elderly people or children. The terminal continuously monitors these data and performs mask processing on the video data as information processing means for protecting personal information.

[0286] The acquired data is transmitted to the server through a secure protocol. The server performs data analysis using a generative AI model and, when an abnormality occurs, promptly notifies the family and care staff via the notification means. The notification is made using email or application notifications. Furthermore, the terminal conducts natural conversations with the target as the communication means and provides mental support.

[0287] As a specific example, consider the monitoring of the elderly at night. The terminal monitors the breathing and heart rate of the elderly during sleep with an AI camera. When an abnormality is detected, the server judges this and issues a notification to prompt an emergency response. The generated information is analyzed by the generative AI model and fed back to the family. Through this process, it becomes possible to consistently manage the safety and health of the elderly.

[0288] An example of how the generative AI model can be used is a prompt such as, "Please describe in detail a scenario in which an abnormality is detected while an elderly person is napping in their living room, and what kind of support should be provided and how it should be notified." In this way, technologically advanced monitoring and emotional support are realized.

[0289] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0290] Step 1:

[0291] The device acquires external environmental information and vital data of the subject. Using an AI camera and IoT sensors, it detects data in real time and temporarily stores the results within the device. Inputs are environmental data and vital signs, while output is organized data.

[0292] Step 2:

[0293] The device applies data processing to the acquired data to protect privacy. Specifically, video data is masked. This process blurs information so that individuals cannot be identified. The input is the original video data, and the output is the video data after masking.

[0294] Step 3:

[0295] The masked data is sent to the server via a secure protocol. The server receives this data and prepares to analyze the information. The input is the masked data, and the output is the organized data for analysis.

[0296] Step 4:

[0297] The server uses a generative AI model to analyze data. It evaluates the target's behavioral patterns and health status to determine if there are any abnormalities. The input is organized data, and the output is the analysis result regarding the presence or absence of abnormalities.

[0298] Step 5:

[0299] If an anomaly is detected, the server will notify relevant family members or care staff using notification methods. Application notifications and email are used as notification methods. The input is the analysis results, and the output is a notification alert message.

[0300] Step 6:

[0301] The device engages in dialogue to provide emotional support through means of interaction with the user. It utilizes a generative AI model to support the user's mental well-being through relaxed conversation. Input is the user's statements and actions, and output is the AI-generated dialogue.

[0302] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0303] In implementing the present invention, the system for effectively monitoring the safety and health of the elderly and children includes, in addition to sensor means, analysis means, monitoring means, data processing means, and notification means, an emotion engine that recognizes the user's emotions. The terminal uses an AI camera or IoT sensor as a sensor means to acquire environmental data and vital signs of the subject. This data is masked to protect privacy before being transmitted to the server.

[0304] The server analyzes the received data using analytical tools to evaluate the subject's behavioral patterns and health status. Furthermore, the emotion engine is responsible for analyzing the user's emotional state through voice input. The emotion engine has the function of recognizing the user's emotional changes in real time and evaluating their mental state based on this.

[0305] The user participates in the process of evaluating their own emotional state by interacting with the AI through the terminal. The terminal interprets voice information and non-verbal elements by means of an emotion engine and transmits the results to the server. The server continuously evaluates the mental state of the target person based on this information. When an abnormality is detected, a prompt notification is sent to the family members or care staff via the notification means.

[0306] As a specific example, when the user makes a statement indicating emotional disturbance in daily conversation, the emotion engine of the terminal grasps the change. The server immediately analyzes the result and sends a notification to the family if necessary, prompting early response. This process enables prompt support and follow-up according to the user's emotions and mental state.

[0307] The following describes the processing flow.

[0308] Step 1:

[0309] The terminal activates the sensor means to acquire the environmental information and vital data of the target person. This includes the collection of video data by an AI camera and the measurement of temperature, humidity, and heart rate by IoT sensors.

[0310] Step 2:

[0311] The terminal performs a masking process to protect the privacy of the acquired data. This ensures privacy before the data is transmitted.

[0312] Step 3:

[0313] The terminal transmits the processed data to the server. The data transmission is encrypted to ensure data security.

[0314] Step 4:

[0315] The server stores the received data in a database and uses analysis tools to analyze behavioral patterns and health status. It detects unusual behavior and changes in vital signs.

[0316] Step 5:

[0317] The device activates an emotion engine, collects voice data through interaction with the user, and recognizes changes in emotion. The emotion engine analyzes voice tone and speech content to evaluate the user's emotional state.

[0318] Step 6:

[0319] The server analyzes the emotional state evaluation results obtained from the emotion engine and activates a notification system if it detects abnormal emotions or mental burden.

[0320] Step 7:

[0321] The server notifies family members and caregivers of any detected anomalies or emotional disturbances. Notifications are sent via email or app to encourage prompt action.

[0322] Step 8:

[0323] Users can receive feedback and advice from the server through their device interface as needed. This enhances user confidence and improves the support system.

[0324] (Example 2)

[0325] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0326] To effectively monitor the safety and health of the elderly and children, it is necessary to continuously monitor situational and biometric data and to quickly detect anomalies while protecting privacy. However, existing systems have difficulty evaluating non-physical elements such as emotional changes in real time, which can lead to delays in early response.

[0327] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0328] In this invention, the server includes detection means for acquiring external situational data, evaluation means for evaluating the behavioral patterns of a subject based on the acquired situational data, and emotion analysis means for recognizing the user's emotional state from voice input. This makes it possible to comprehensively evaluate the user's physical and emotional state and take prompt action as needed.

[0329] "Detection means" refers to a device or method used to acquire external situational data.

[0330] "Evaluation means" refers to a process or technique used to evaluate the behavioral patterns of a subject based on acquired situational data.

[0331] "Monitoring means" refers to a device or system for continuously monitoring a subject's biometric data.

[0332] "Information processing means" refers to a system or algorithm used to process and modify data in order to protect privacy.

[0333] "Notification means" refers to a method or device for informing relevant parties when an anomaly is detected.

[0334] "Emotional analysis means" refers to a technology or system for recognizing a user's emotional state from voice input.

[0335] A "dialogue method" is a communication system for evaluating the mental state of the subject and, if necessary, notifying external parties.

[0336] "Treatment measures" refer to actions or methods for providing prompt support based on the emotional state of the person concerned.

[0337] This invention is specifically implemented as a system for monitoring the safety and health of the elderly and children. The system is primarily composed of the interaction between terminals, servers, and users.

[0338] The device uses hardware such as AI cameras and IoT sensors to acquire data on the subject's surrounding environment and biometric data. This data includes temperature, humidity, heart rate, and activity level. This information is masked to protect data privacy before being sent to the server.

[0339] The server uses machine learning algorithms as an analysis tool to evaluate the subject's behavioral patterns and health status based on the received data. Furthermore, the server employs emotion analysis tools to recognize changes in the user's emotional state by analyzing their voice in real time. These analysis results serve as important input for evaluating the mental state.

[0340] The user participates in an interaction with the AI ​​through the device and is involved in the emotion analysis process. The user provides voice input, which the device processes through an emotion analysis system and sends the analysis results to a server. Based on this information, if the server detects an anomaly, it will promptly notify family members or care staff through a notification system.

[0341] As a concrete example, if a user makes a statement indicating emotional distress during a normal conversation, the device detects this change using emotion analysis. The server analyzes the change in emotion and, if necessary, sends a notification to the family. This process enables rapid support for the user's mental state.

[0342] As an example of a prompt to a generative AI model, you could use a sentence like, "Please describe the procedure for identifying the user's emotional state from their voice data, evaluating its changes in real time, and providing notifications."

[0343] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0344] Step 1:

[0345] The device uses an AI camera and IoT sensors to acquire external environmental data and biometric data of the subject. The input here is raw data from the sensors, and the output is a dataset including temperature, humidity, heart rate, activity level, etc. Specifically, the AI ​​camera captures the subject's movements, and the IoT sensors measure vital signs.

[0346] Step 2:

[0347] The device performs privacy-protecting masking on the acquired data. The dataset acquired in the previous step is used as input, and the output is data with privacy information protected. Specifically, personally identifiable information is extracted and encrypted or deleted.

[0348] Step 3:

[0349] The terminal sends masked data to the server. The input here is the masked data, and the output is the transfer of that data to the server. Specifically, the terminal generates a data package and transfers it using a secure protocol.

[0350] Step 4:

[0351] The server analyzes the received data and evaluates behavioral patterns and health status. The input here is the data sent to the server, and the output is an indicator of behavioral patterns and health status as an evaluation result. Specifically, it uses machine learning algorithms to analyze the data, and the evaluation model is executed within the software.

[0352] Step 5:

[0353] The server analyzes the user's voice input using emotion analysis tools. The input is voice data, and the output is an evaluation result indicating the emotional state. Specifically, the tone and tempo of the voice are passed through an analysis algorithm, and an emotion model is executed.

[0354] Step 6:

[0355] Users interact with the AI ​​through their device and participate in the assessment of their emotional state. The input is the user's voice, and the output is feedback resulting from the emotion analysis. Specifically, the user speaks into the device, and their voice is interpreted in real time.

[0356] Step 7:

[0357] The server, upon detecting an anomaly, promptly notifies family members and caregivers through notification channels. Inputs are assessed health and emotional states, and outputs are notification messages. Specifically, the server automatically sends emails or alerts when notification conditions are met.

[0358] (Application Example 2)

[0359] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0360] To ensure the safety and health of the elderly and children, real-time monitoring of their health and emotional states is necessary. However, systems that effectively achieve this lack mechanisms to accurately assess emotional states, quickly detect abnormalities, and prompt appropriate responses. Solving this challenge is essential to providing faster and more appropriate care and support.

[0361] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0362] In this invention, the server includes sensing means for acquiring external environmental information, analysis means for analyzing the behavioral patterns of a subject based on the acquired environmental information, and monitoring means for continuously monitoring the subject's health data. This enables real-time evaluation of the subject's emotional state, immediate detection of abnormalities, appropriate notification, and rapid response.

[0363] "Sensing means" refers to devices or methods for acquiring external environmental information, and is a technology that uses cameras, sensors, etc., to detect the situation of a subject.

[0364] "Analysis means" refers to devices or methods that analyze the behavioral patterns of subjects based on acquired environmental information, and is a technology for understanding the trends of subjects by analyzing data.

[0365] "Health data" refers to data that indicates the physical condition of a subject, and includes information used to evaluate their health status, such as vital signs and sleep patterns.

[0366] "Monitoring means" refers to devices or methods that continuously monitor a subject's health data, and is a technology for constantly checking the latest health status and detecting abnormalities.

[0367] "Information processing means" refers to devices and methods that process acquired data while protecting privacy, and is a technology for safely handling personal information.

[0368] A "notification system" is a device or method that quickly notifies relevant parties when an anomaly is detected, and is a technology that prompts necessary action.

[0369] An "emotion recognition engine" is a device or method for evaluating a person's emotional state in real time, and it is a technology that determines emotions by analyzing voice, facial expressions, etc.

[0370] The system for implementing this invention includes several key components to monitor the safety and health of the subject. The system operates via devices such as smart glasses or smartphones, which are equipped with AI cameras and sensors. This makes it possible to acquire environmental information and health data in real time.

[0371] The device uses an emotion recognition engine based on Python and TensorFlow to analyze the subject's emotional state in real time. Video data is preprocessed using OpenCV to extract specific features. Then, emotions are analyzed using a TensorFlow generative AI model.

[0372] The server receives data transmitted from the terminal and evaluates behavioral patterns using analysis tools. It also continuously monitors health data using monitoring tools, and if an abnormality is detected, it notifies relevant parties using notification tools.

[0373] For example, if a particular resident exhibits unusual behavior or facial expressions, the emotion recognition engine analyzes the change, and the server immediately determines that something is wrong. It can then notify family members or care staff as needed, prompting a quick response.

[0374] Examples of prompts for a generative AI model are as follows:

[0375] "Analyze the camera footage and assess the residents' emotional and physical condition. If any abnormalities are found, provide advice on what actions should be taken."

[0376] This system enables prompt and appropriate monitoring and support based on the emotions and health status of the individuals involved.

[0377] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0378] Step 1:

[0379] The device uses an AI camera to capture video of the subject. The input is real-time video data, and by acquiring this video data, it captures the basic information necessary for subsequent processing steps.

[0380] Step 2:

[0381] The device preprocesses video data using OpenCV to extract the subject's features. The input is captured video data, and the output is numerical data related to facial features and expressions. This preprocessing allows for more accurate emotion analysis.

[0382] Step 3:

[0383] The device uses TensorFlow and analyzes emotional states from feature points extracted using a generative AI model. The input is feature point data, and the output is data indicating the type and degree of emotion. This visualizes the user's current emotional state.

[0384] Step 4:

[0385] The terminal sends the analyzed emotional data to the server. The input is the result of the emotional analysis, and the output is data used for further analysis on the server side. This transmission allows the emotional state of the subject to be managed centrally.

[0386] Step 5:

[0387] The server analyzes the received emotional data and evaluates the subject's behavioral patterns and health status. The input consists of the emotional analysis results and past health data, while the output is data showing the evaluation results. The analysis clarifies the subject's mental state.

[0388] Step 6:

[0389] If the server detects an anomaly based on the analysis results, it will promptly notify the relevant parties using a notification system. The input is the analysis result data, and the output is alert information sent to the relevant parties. This notification will prompt appropriate action.

[0390] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0391] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0392] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0393] [Third Embodiment]

[0394] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0395] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0396] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0397] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0398] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0399] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0400] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0401] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0402] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0403] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0404] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0405] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0406] In implementing this invention, the system for protecting the safety and health of the elderly and children is designed so that each component functions in coordination. First, the terminal, acting as a sensor, acquires environmental information and vital data of the subject in real time through AI cameras and IoT sensors. This data is temporarily stored in the terminal and subjected to necessary data processing. In particular, camera images are masked to protect privacy.

[0407] Data acquired by the device is securely transmitted to the server. The server has analytical capabilities and analyzes the subject's behavioral patterns and health status based on the information stored in the database. If unusual behavior or abnormal values ​​are detected, the server's notification system quickly issues an alert and notifies designated family members or care staff. This notification can be made in multiple ways, such as email, application notifications, or, if necessary, by phone.

[0408] Users can receive daily monitoring of elderly individuals and children through the device, and also receive emotional support through interaction with AI. This interaction is made possible when the AI ​​on the device senses the user's voice and actions and sends relevant information to the server. The AI ​​constantly evaluates the user's condition and provides feedback to the family as needed to prevent social isolation.

[0409] As a concrete example, considering the monitoring of elderly people at night, the device monitors their breathing and heart rate while they sleep. If an abnormality is detected, the server immediately makes a judgment and sends a message via a notification system prompting emergency action. In this way, the health status of elderly people can be constantly monitored, and a rapid response is possible in emergencies. This enables comprehensive safety management and health maintenance.

[0410] The following describes the processing flow.

[0411] Step 1:

[0412] The device activates AI cameras and IoT sensors to acquire environmental information about the subject, collecting data in real time. This includes electricity usage, room temperature, motion detection, and vital signs.

[0413] Step 2:

[0414] The device temporarily stores the acquired raw data in its internal memory and applies a masking process to the video data to protect privacy. This process highlights necessary information without infringing on privacy.

[0415] Step 3:

[0416] The terminal sends the processed data to the server. During this process, the data is encrypted to ensure security during transmission.

[0417] Step 4:

[0418] The server stores the received data in a database and applies algorithms for behavioral analysis. This allows for the analysis of typical behavioral patterns and the establishment of benchmarks.

[0419] Step 5:

[0420] The server performs analysis based on the subject's behavior and vital data to detect anomalies. If it detects anomalies exceeding the criteria or unregistered behavior, it prepares an alert.

[0421] Step 6:

[0422] Based on detected anomalies, the server activates notification mechanisms to send alerts. Information is then quickly provided to family members and caregivers via email and app notifications.

[0423] Step 7:

[0424] The user interacts with the AI ​​assistant via the device. The device analyzes the user's voice input, assesses their emotions, and sends the information to the server as needed.

[0425] Step 8:

[0426] The server assesses the user's mental state and, if there are signs of social isolation, notifies the family and informs them of the need for follow-up.

[0427] Through these steps, the system comprehensively manages the safety and health of the individuals involved and enables immediate response as needed.

[0428] (Example 1)

[0429] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0430] There is a need to constantly monitor the safety and health of the elderly and children, and to quickly detect and address any abnormal behavior or changes in their health. Furthermore, it is necessary to provide appropriate communication methods while protecting privacy. There are currently insufficient systems that meet these requirements, and this is a challenge that needs to be addressed.

[0431] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0432] In this invention, the server includes sensor means for acquiring external information, analysis means for analyzing operating patterns based on the acquired information, and monitoring means for continuously monitoring health-related data. This makes it possible to monitor the safety and health of the elderly and children in real time and to quickly detect and notify of any abnormalities.

[0433] "Sensor means for acquiring external information" refers to devices that detect a subject's environmental information and health status in real time.

[0434] "Analysis methods for analyzing behavioral patterns" refers to technologies that perform processing to identify specific behavioral patterns or anomalies based on acquired data.

[0435] "Monitoring methods for continuously monitoring health-related data" refers to functions and tools for continuously monitoring biometric information in real time.

[0436] "Data processing measures to protect privacy" refers to methods and technologies for anonymizing or concealing personally identifiable information.

[0437] "Notification means for communication when an anomaly is detected" refers to a method for quickly informing relevant parties when an unusual situation occurs.

[0438] "A means of dialogue for interacting with a subject via voice input" refers to technology for communicating with a subject based on voice input.

[0439] This invention is a system aimed at monitoring the safety and health of the elderly and children, and it functions through the coordinated operation of terminals, servers, and users.

[0440] First, the device uses an AI camera and IoT sensors to acquire environmental information and vital data of the subject in real time. The AI ​​camera monitors surrounding movements and sounds, while the IoT sensors measure the subject's heart rate and respiratory rate. This allows the device to accumulate data on the subject's health status. The device incorporates data processing technologies to protect privacy; for example, camera footage is blurred.

[0441] The acquired data is temporarily stored on the device and then transmitted to the server using Wi-Fi or mobile data communication. The server analyzes this data and detects anomalies by comparing it with historical information stored in the database. Analysis using machine learning algorithms is performed, enabling the evaluation of behavioral patterns and health status.

[0442] If an anomaly is detected, the server will send email and application notifications to registered family members and care staff. It also has a function to make phone calls as needed. This ensures a system that allows for a quick response no matter where you are.

[0443] Users can receive daily monitoring from their device and even communicate with an interactive AI through voice. For example, if a user feels anxious, they can speak into the device, and the AI ​​will analyze their voice to provide appropriate advice and information. This voice interaction data is also sent to a server and used to assess the user's mental state.

[0444] As a concrete example, considering the monitoring of elderly people at night, the device monitors the elderly person's breathing and heart rate while they sleep. If an abnormality is detected, the server immediately makes a judgment and sends a message via a notification system prompting immediate action.

[0445] An example of a prompt sentence to input into the generating AI model is, "Please provide details about the nighttime health monitoring system for the elderly."

[0446] Thus, this invention is designed to comprehensively protect the safety and health of the elderly and children by making full use of technical means.

[0447] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0448] Step 1:

[0449] The device uses an AI camera and IoT sensors to collect environmental information and vital data from the subject. Inputs include physical movement and physiological data. The device acquires this data in real time and temporarily stores it in its internal memory. The AI ​​camera captures video data, while temperature and humidity sensors record environmental information.

[0450] Step 2:

[0451] The terminal performs preprocessing on the acquired data. Specifically, it removes noise from the input data and processes it into a format necessary for anomaly detection. For data calculation, it uses signal processing algorithms to filter out anomalies. In particular, it applies mosaic processing to video data to protect privacy. The output is a preprocessed dataset.

[0452] Step 3:

[0453] The terminal sends pre-processed data to the server. The input is the data processed in the previous step, and the output is the data securely transferred to the server. The data is encrypted and sent to the server via a secure communication protocol.

[0454] Step 4:

[0455] The server analyzes the received data. The input consists of multiple datasets from the terminal. The server uses machine learning algorithms to analyze the data and detect anomalies. For example, it can identify unnatural movements at night or sudden increases in heart rate. The output is a result confirming whether or not an anomaly was detected.

[0456] Step 5:

[0457] If an anomaly is detected, the server notifies registered family members or caregivers via a notification system. The input is the result of the anomaly detection. The server creates and sends an email or app notification. The output is that the recipient is notified of the anomaly.

[0458] Step 6:

[0459] Users receive daily monitoring and emotional support through the device. Input consists of the user's voice and actions, which the device detects and transmits to the server. Furthermore, a generative AI model is used to provide support through voice dialogue. Output includes feedback and advice for the user.

[0460] In this way, the system can continuously monitor the safety and health of the elderly and children through a series of processing steps.

[0461] (Application Example 1)

[0462] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0463] In today's aging society, effectively maintaining the safety and health of the elderly and children is a crucial challenge. Furthermore, it is essential to provide them with a supportive environment where they do not feel isolated and receive emotional support. However, there are insufficient means to simultaneously achieve both daily monitoring and emotional support. The development of a system that can provide integrated physical and emotional safety and security is necessary.

[0464] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0465] In this invention, the server includes perceptual means for acquiring external information, processing means for analyzing the target's behavioral patterns based on the acquired information, monitoring means for continuously monitoring the target's health data and psychological state, information processing means for protecting personal information, notification means for issuing warnings when an anomaly is detected, and communication means for providing mental support through communication using a terminal. This makes it possible to comprehensively manage both the physical safety and mental support provided to the target.

[0466] "Means of perception" refers to sensors and devices used to acquire external information, and the function of sensing the environment and state of a subject through these means.

[0467] A "processing means" is a system that includes algorithms and programs for analyzing the target's behavioral patterns based on acquired information and extracting meaningful data.

[0468] "Monitoring methods" refer to technologies used to continuously observe a subject's health data and psychological state and to detect any abnormal conditions.

[0469] "Information processing means" refers to technologies and protocols that appropriately mask or encrypt data while protecting personal information.

[0470] A "notification system" is a function that immediately issues a warning when an anomaly is detected and transmits the information to the necessary parties.

[0471] "Means of interaction" refers to functions that use terminals to engage in dialogue with the target individual and provide emotional support and communication.

[0472] To realize this invention, IoT sensors and AI cameras are first used as perceptual means for acquiring external information. This makes it possible to sense environmental information and vital data of the target elderly person or child in real time. The terminal continuously monitors this data and applies masking processing to the video data as an information processing means to protect personal information.

[0473] The acquired data is transmitted to the server via a secure protocol. The server analyzes the data using a generative AI model and, in the event of an anomaly, promptly notifies family members and care staff through notification mechanisms. Notifications are made via email or application notifications. Furthermore, the device provides emotional support by engaging in natural conversations with the individual as a means of interaction.

[0474] As a concrete example, consider monitoring elderly people at night. The device uses an AI camera to monitor the elderly person's breathing and heart rate while they sleep. If an abnormality is detected, the server makes a judgment and sends a notification, prompting emergency action. The generated information is analyzed by a generative AI model and fed back to the family. Through this process, it becomes possible to consistently manage the safety and health of the elderly person.

[0475] An example of how the generative AI model can be used is a prompt such as, "Please describe in detail a scenario in which an abnormality is detected while an elderly person is napping in their living room, and what kind of support should be provided and how it should be notified." In this way, technologically advanced monitoring and emotional support are realized.

[0476] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0477] Step 1:

[0478] The device acquires external environmental information and vital data of the subject. Using an AI camera and IoT sensors, it detects data in real time and temporarily stores the results within the device. Inputs are environmental data and vital signs, while output is organized data.

[0479] Step 2:

[0480] The device applies data processing to the acquired data to protect privacy. Specifically, video data is masked. This process blurs information so that individuals cannot be identified. The input is the original video data, and the output is the video data after masking.

[0481] Step 3:

[0482] The masked data is sent to the server via a secure protocol. The server receives this data and prepares to analyze the information. The input is the masked data, and the output is the organized data for analysis.

[0483] Step 4:

[0484] The server uses a generative AI model to analyze data. It evaluates the target's behavioral patterns and health status to determine if there are any abnormalities. The input is organized data, and the output is the analysis result regarding the presence or absence of abnormalities.

[0485] Step 5:

[0486] If an anomaly is detected, the server will notify relevant family members or care staff using notification methods. Application notifications and email are used as notification methods. The input is the analysis results, and the output is a notification alert message.

[0487] Step 6:

[0488] The device engages in dialogue to provide emotional support through means of interaction with the user. It utilizes a generative AI model to support the user's mental well-being through relaxed conversation. Input is the user's statements and actions, and output is the AI-generated dialogue.

[0489] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0490] In implementing the present invention, the system for effectively monitoring the safety and health of the elderly and children includes, in addition to sensor means, analysis means, monitoring means, data processing means, and notification means, an emotion engine that recognizes the user's emotions. The terminal uses an AI camera or IoT sensor as a sensor means to acquire environmental data and vital signs of the subject. This data is masked to protect privacy before being transmitted to the server.

[0491] The server analyzes the received data using analytical tools to evaluate the subject's behavioral patterns and health status. Furthermore, the emotion engine is responsible for analyzing the user's emotional state through voice input. The emotion engine has the function of recognizing the user's emotional changes in real time and evaluating their mental state based on this.

[0492] The user participates in a process of evaluating their own emotional state by interacting with AI through the device. The device interprets voice information and nonverbal elements using an emotion engine and sends the results to the server. The server continuously evaluates the user's mental state based on this information. If an abnormality is detected, it quickly notifies family members and care staff via a notification system.

[0493] For example, if a user makes a statement indicating emotional distress during a normal conversation, the device's emotion engine detects this change. The server immediately analyzes the results and, if necessary, sends a notification to family members to encourage early intervention. This process enables rapid support and follow-up tailored to the user's emotions and mental state.

[0494] The following describes the processing flow.

[0495] Step 1:

[0496] The device activates sensor devices to acquire environmental information and vital data of the subject. This includes collecting video data using an AI camera and measuring temperature, humidity, and heart rate using IoT sensors.

[0497] Step 2:

[0498] The device applies a masking process to the acquired data to protect privacy. This ensures privacy before the data is transmitted.

[0499] Step 3:

[0500] The terminal sends the processed data to the server. The data transmission is encrypted to ensure data security.

[0501] Step 4:

[0502] The server stores the received data in a database and uses analysis tools to analyze behavioral patterns and health status. It detects unusual behavior and changes in vital signs.

[0503] Step 5:

[0504] The device activates an emotion engine, collects voice data through interaction with the user, and recognizes changes in emotion. The emotion engine analyzes voice tone and speech content to evaluate the user's emotional state.

[0505] Step 6:

[0506] The server analyzes the emotional state evaluation results obtained from the emotion engine and activates a notification system if it detects abnormal emotions or mental burden.

[0507] Step 7:

[0508] The server notifies family members and caregivers of any detected anomalies or emotional disturbances. Notifications are sent via email or app to encourage prompt action.

[0509] Step 8:

[0510] Users can receive feedback and advice from the server through their device interface as needed. This enhances user confidence and improves the support system.

[0511] (Example 2)

[0512] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0513] To effectively monitor the safety and health of the elderly and children, it is necessary to continuously monitor situational and biometric data and to quickly detect anomalies while protecting privacy. However, existing systems have difficulty evaluating non-physical elements such as emotional changes in real time, which can lead to delays in early response.

[0514] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0515] In this invention, the server includes detection means for acquiring external situational data, evaluation means for evaluating the behavioral patterns of a subject based on the acquired situational data, and emotion analysis means for recognizing the user's emotional state from voice input. This makes it possible to comprehensively evaluate the user's physical and emotional state and take prompt action as needed.

[0516] "Detection means" refers to a device or method used to acquire external situational data.

[0517] "Evaluation means" refers to a process or technique used to evaluate the behavioral patterns of a subject based on acquired situational data.

[0518] "Monitoring means" refers to a device or system for continuously monitoring a subject's biometric data.

[0519] "Information processing means" refers to a system or algorithm used to process and modify data in order to protect privacy.

[0520] "Notification means" refers to a method or device for informing relevant parties when an anomaly is detected.

[0521] "Emotional analysis means" refers to a technology or system for recognizing a user's emotional state from voice input.

[0522] A "dialogue method" is a communication system for evaluating the mental state of the subject and, if necessary, notifying external parties.

[0523] "Treatment measures" refer to actions or methods for providing prompt support based on the emotional state of the person concerned.

[0524] This invention is specifically implemented as a system for monitoring the safety and health of the elderly and children. The system is primarily composed of the interaction between terminals, servers, and users.

[0525] The device uses hardware such as AI cameras and IoT sensors to acquire data on the subject's surrounding environment and biometric data. This data includes temperature, humidity, heart rate, and activity level. This information is masked to protect data privacy before being sent to the server.

[0526] The server uses machine learning algorithms as an analysis tool to evaluate the subject's behavioral patterns and health status based on the received data. Furthermore, the server employs emotion analysis tools to recognize changes in the user's emotional state by analyzing their voice in real time. These analysis results serve as important input for evaluating the mental state.

[0527] The user participates in an interaction with the AI ​​through the device and is involved in the emotion analysis process. The user provides voice input, which the device processes through an emotion analysis system and sends the analysis results to a server. Based on this information, if the server detects an anomaly, it will promptly notify family members or care staff through a notification system.

[0528] As a concrete example, if a user makes a statement indicating emotional distress during a normal conversation, the device detects this change using emotion analysis. The server analyzes the change in emotion and, if necessary, sends a notification to the family. This process enables rapid support for the user's mental state.

[0529] As an example of a prompt to a generative AI model, you could use a sentence like, "Please describe the procedure for identifying the user's emotional state from their voice data, evaluating its changes in real time, and providing notifications."

[0530] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0531] Step 1:

[0532] The device uses an AI camera and IoT sensors to acquire external environmental data and biometric data of the subject. The input here is raw data from the sensors, and the output is a dataset including temperature, humidity, heart rate, activity level, etc. Specifically, the AI ​​camera captures the subject's movements, and the IoT sensors measure vital signs.

[0533] Step 2:

[0534] The device performs privacy-protecting masking on the acquired data. The dataset acquired in the previous step is used as input, and the output is data with privacy information protected. Specifically, personally identifiable information is extracted and encrypted or deleted.

[0535] Step 3:

[0536] The terminal sends masked data to the server. The input here is the masked data, and the output is the transfer of that data to the server. Specifically, the terminal generates a data package and transfers it using a secure protocol.

[0537] Step 4:

[0538] The server analyzes the received data and evaluates behavioral patterns and health status. The input here is the data sent to the server, and the output is an indicator of behavioral patterns and health status as an evaluation result. Specifically, it uses machine learning algorithms to analyze the data, and the evaluation model is executed within the software.

[0539] Step 5:

[0540] The server analyzes the user's voice input using emotion analysis tools. The input is voice data, and the output is an evaluation result indicating the emotional state. Specifically, the tone and tempo of the voice are passed through an analysis algorithm, and an emotion model is executed.

[0541] Step 6:

[0542] Users interact with the AI ​​through their device and participate in the assessment of their emotional state. The input is the user's voice, and the output is feedback resulting from the emotion analysis. Specifically, the user speaks into the device, and their voice is interpreted in real time.

[0543] Step 7:

[0544] The server, upon detecting an anomaly, promptly notifies family members and caregivers through notification channels. Inputs are assessed health and emotional states, and outputs are notification messages. Specifically, the server automatically sends emails or alerts when notification conditions are met.

[0545] (Application Example 2)

[0546] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0547] To ensure the safety and health of the elderly and children, real-time monitoring of their health and emotional states is necessary. However, systems that effectively achieve this lack mechanisms to accurately assess emotional states, quickly detect abnormalities, and prompt appropriate responses. Solving this challenge is essential to providing faster and more appropriate care and support.

[0548] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0549] In this invention, the server includes sensing means for acquiring external environmental information, analysis means for analyzing the behavioral patterns of a subject based on the acquired environmental information, and monitoring means for continuously monitoring the subject's health data. This enables real-time evaluation of the subject's emotional state, immediate detection of abnormalities, appropriate notification, and rapid response.

[0550] "Sensing means" refers to devices or methods for acquiring external environmental information, and is a technology that uses cameras, sensors, etc., to detect the situation of a subject.

[0551] "Analysis means" refers to devices or methods that analyze the behavioral patterns of subjects based on acquired environmental information, and is a technology for understanding the trends of subjects by analyzing data.

[0552] "Health data" refers to data that indicates the physical condition of a subject, and includes information used to evaluate their health status, such as vital signs and sleep patterns.

[0553] "Monitoring means" refers to devices or methods that continuously monitor a subject's health data, and is a technology for constantly checking the latest health status and detecting abnormalities.

[0554] "Information processing means" refers to devices and methods that process acquired data while protecting privacy, and is a technology for safely handling personal information.

[0555] A "notification system" is a device or method that quickly notifies relevant parties when an anomaly is detected, and is a technology that prompts necessary action.

[0556] An "emotion recognition engine" is a device or method for evaluating a person's emotional state in real time, and it is a technology that determines emotions by analyzing voice, facial expressions, etc.

[0557] The system for implementing this invention includes several key components to monitor the safety and health of the subject. The system operates via devices such as smart glasses or smartphones, which are equipped with AI cameras and sensors. This makes it possible to acquire environmental information and health data in real time.

[0558] The device uses an emotion recognition engine based on Python and TensorFlow to analyze the subject's emotional state in real time. Video data is preprocessed using OpenCV to extract specific features. Then, emotions are analyzed using a TensorFlow generative AI model.

[0559] The server receives data transmitted from the terminal and evaluates behavioral patterns using analysis tools. It also continuously monitors health data using monitoring tools, and if an abnormality is detected, it notifies relevant parties using notification tools.

[0560] For example, if a particular resident exhibits unusual behavior or facial expressions, the emotion recognition engine analyzes the change, and the server immediately determines that something is wrong. It can then notify family members or care staff as needed, prompting a quick response.

[0561] Examples of prompts for a generative AI model are as follows:

[0562] "Analyze the camera footage and assess the residents' emotional and physical condition. If any abnormalities are found, provide advice on what actions should be taken."

[0563] This system enables prompt and appropriate monitoring and support based on the emotions and health status of the individuals involved.

[0564] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0565] Step 1:

[0566] The device uses an AI camera to capture video of the subject. The input is real-time video data, and by acquiring this video data, it captures the basic information necessary for subsequent processing steps.

[0567] Step 2:

[0568] The device preprocesses video data using OpenCV to extract the subject's features. The input is captured video data, and the output is numerical data related to facial features and expressions. This preprocessing allows for more accurate emotion analysis.

[0569] Step 3:

[0570] The device uses TensorFlow and analyzes emotional states from feature points extracted using a generative AI model. The input is feature point data, and the output is data indicating the type and degree of emotion. This visualizes the user's current emotional state.

[0571] Step 4:

[0572] The terminal sends the analyzed emotional data to the server. The input is the result of the emotional analysis, and the output is data used for further analysis on the server side. This transmission allows the emotional state of the subject to be managed centrally.

[0573] Step 5:

[0574] The server analyzes the received emotional data and evaluates the subject's behavioral patterns and health status. The input consists of the emotional analysis results and past health data, while the output is data showing the evaluation results. The analysis clarifies the subject's mental state.

[0575] Step 6:

[0576] If the server detects an anomaly based on the analysis results, it will promptly notify the relevant parties using a notification system. The input is the analysis result data, and the output is alert information sent to the relevant parties. This notification will prompt appropriate action.

[0577] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0578] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0579] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0580] [Fourth Embodiment]

[0581] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0582] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0583] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0584] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0585] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0586] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0587] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0588] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0589] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0590] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0591] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0592] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0593] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0594] In implementing this invention, the system for protecting the safety and health of the elderly and children is designed so that each component functions in coordination. First, the terminal, acting as a sensor, acquires environmental information and vital data of the subject in real time through AI cameras and IoT sensors. This data is temporarily stored in the terminal and subjected to necessary data processing. In particular, camera images are masked to protect privacy.

[0595] Data acquired by the device is securely transmitted to the server. The server has analytical capabilities and analyzes the subject's behavioral patterns and health status based on the information stored in the database. If unusual behavior or abnormal values ​​are detected, the server's notification system quickly issues an alert and notifies designated family members or care staff. This notification can be made in multiple ways, such as email, application notifications, or, if necessary, by phone.

[0596] Users can receive daily monitoring of elderly individuals and children through the device, and also receive emotional support through interaction with AI. This interaction is made possible when the AI ​​on the device senses the user's voice and actions and sends relevant information to the server. The AI ​​constantly evaluates the user's condition and provides feedback to the family as needed to prevent social isolation.

[0597] As a concrete example, considering the monitoring of elderly people at night, the device monitors their breathing and heart rate while they sleep. If an abnormality is detected, the server immediately makes a judgment and sends a message via a notification system prompting emergency action. In this way, the health status of elderly people can be constantly monitored, and a rapid response is possible in emergencies. This enables comprehensive safety management and health maintenance.

[0598] The following describes the processing flow.

[0599] Step 1:

[0600] The device activates AI cameras and IoT sensors to acquire environmental information about the subject, collecting data in real time. This includes electricity usage, room temperature, motion detection, and vital signs.

[0601] Step 2:

[0602] The device temporarily stores the acquired raw data in its internal memory and applies a masking process to the video data to protect privacy. This process highlights necessary information without infringing on privacy.

[0603] Step 3:

[0604] The terminal sends the processed data to the server. During this process, the data is encrypted to ensure security during transmission.

[0605] Step 4:

[0606] The server stores the received data in a database and applies algorithms for behavioral analysis. This allows for the analysis of typical behavioral patterns and the establishment of benchmarks.

[0607] Step 5:

[0608] The server performs analysis based on the subject's behavior and vital data to detect anomalies. If it detects anomalies exceeding the criteria or unregistered behavior, it prepares an alert.

[0609] Step 6:

[0610] Based on detected anomalies, the server activates notification mechanisms to send alerts. Information is then quickly provided to family members and caregivers via email and app notifications.

[0611] Step 7:

[0612] The user interacts with the AI ​​assistant via the device. The device analyzes the user's voice input, assesses their emotions, and sends the information to the server as needed.

[0613] Step 8:

[0614] The server assesses the user's mental state and, if there are signs of social isolation, notifies the family and informs them of the need for follow-up.

[0615] Through these steps, the system comprehensively manages the safety and health of the individuals involved and enables immediate response as needed.

[0616] (Example 1)

[0617] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0618] There is a need to constantly monitor the safety and health of the elderly and children, and to quickly detect and address any abnormal behavior or changes in their health. Furthermore, it is necessary to provide appropriate communication methods while protecting privacy. There are currently insufficient systems that meet these requirements, and this is a challenge that needs to be addressed.

[0619] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0620] In this invention, the server includes sensor means for acquiring external information, analysis means for analyzing operating patterns based on the acquired information, and monitoring means for continuously monitoring health-related data. This makes it possible to monitor the safety and health of the elderly and children in real time and to quickly detect and notify of any abnormalities.

[0621] "Sensor means for acquiring external information" refers to devices that detect a subject's environmental information and health status in real time.

[0622] "Analysis methods for analyzing behavioral patterns" refers to technologies that perform processing to identify specific behavioral patterns or anomalies based on acquired data.

[0623] "Monitoring methods for continuously monitoring health-related data" refers to functions and tools for continuously monitoring biometric information in real time.

[0624] "Data processing measures to protect privacy" refers to methods and technologies for anonymizing or concealing personally identifiable information.

[0625] "Notification means for communication when an anomaly is detected" refers to a method for quickly informing relevant parties when an unusual situation occurs.

[0626] "A means of dialogue for interacting with a subject via voice input" refers to technology for communicating with a subject based on voice input.

[0627] This invention is a system aimed at monitoring the safety and health of the elderly and children, and it functions through the coordinated operation of terminals, servers, and users.

[0628] First, the device uses an AI camera and IoT sensors to acquire environmental information and vital data of the subject in real time. The AI ​​camera monitors surrounding movements and sounds, while the IoT sensors measure the subject's heart rate and respiratory rate. This allows the device to accumulate data on the subject's health status. The device incorporates data processing technologies to protect privacy; for example, camera footage is blurred.

[0629] The acquired data is temporarily stored on the device and then transmitted to the server using Wi-Fi or mobile data communication. The server analyzes this data and detects anomalies by comparing it with historical information stored in the database. Analysis using machine learning algorithms is performed, enabling the evaluation of behavioral patterns and health status.

[0630] If an anomaly is detected, the server will send email and application notifications to registered family members and care staff. It also has a function to make phone calls as needed. This ensures a system that allows for a quick response no matter where you are.

[0631] Users can receive daily monitoring from their device and even communicate with an interactive AI through voice. For example, if a user feels anxious, they can speak into the device, and the AI ​​will analyze their voice to provide appropriate advice and information. This voice interaction data is also sent to a server and used to assess the user's mental state.

[0632] As a concrete example, considering the monitoring of elderly people at night, the device monitors the elderly person's breathing and heart rate while they sleep. If an abnormality is detected, the server immediately makes a judgment and sends a message via a notification system prompting immediate action.

[0633] An example of a prompt sentence to input into the generating AI model is, "Please provide details about the nighttime health monitoring system for the elderly."

[0634] Thus, this invention is designed to comprehensively protect the safety and health of the elderly and children by making full use of technical means.

[0635] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0636] Step 1:

[0637] The device uses an AI camera and IoT sensors to collect environmental information and vital data from the subject. Inputs include physical movement and physiological data. The device acquires this data in real time and temporarily stores it in its internal memory. The AI ​​camera captures video data, while temperature and humidity sensors record environmental information.

[0638] Step 2:

[0639] The terminal performs preprocessing on the acquired data. Specifically, it removes noise from the input data and processes it into a format necessary for anomaly detection. For data calculation, it uses signal processing algorithms to filter out anomalies. In particular, it applies mosaic processing to video data to protect privacy. The output is a preprocessed dataset.

[0640] Step 3:

[0641] The terminal sends pre-processed data to the server. The input is the data processed in the previous step, and the output is the data securely transferred to the server. The data is encrypted and sent to the server via a secure communication protocol.

[0642] Step 4:

[0643] The server analyzes the received data. The input consists of multiple datasets from the terminal. The server uses machine learning algorithms to analyze the data and detect anomalies. For example, it can identify unnatural movements at night or sudden increases in heart rate. The output is a result confirming whether or not an anomaly was detected.

[0644] Step 5:

[0645] If an anomaly is detected, the server notifies registered family members or caregivers via a notification system. The input is the result of the anomaly detection. The server creates and sends an email or app notification. The output is that the recipient is notified of the anomaly.

[0646] Step 6:

[0647] Users receive daily monitoring and emotional support through the device. Input consists of the user's voice and actions, which the device detects and transmits to the server. Furthermore, a generative AI model is used to provide support through voice dialogue. Output includes feedback and advice for the user.

[0648] In this way, the system can continuously monitor the safety and health of the elderly and children through a series of processing steps.

[0649] (Application Example 1)

[0650] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0651] In today's aging society, effectively maintaining the safety and health of the elderly and children is a crucial challenge. Furthermore, it is essential to provide them with a supportive environment where they do not feel isolated and receive emotional support. However, there are insufficient means to simultaneously achieve both daily monitoring and emotional support. The development of a system that can provide integrated physical and emotional safety and security is necessary.

[0652] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0653] In this invention, the server includes perceptual means for acquiring external information, processing means for analyzing the target's behavioral patterns based on the acquired information, monitoring means for continuously monitoring the target's health data and psychological state, information processing means for protecting personal information, notification means for issuing warnings when an anomaly is detected, and communication means for providing mental support through communication using a terminal. This makes it possible to comprehensively manage both the physical safety and mental support provided to the target.

[0654] "Means of perception" refers to sensors and devices used to acquire external information, and the function of sensing the environment and state of a subject through these means.

[0655] A "processing means" is a system that includes algorithms and programs for analyzing the target's behavioral patterns based on acquired information and extracting meaningful data.

[0656] "Monitoring methods" refer to technologies used to continuously observe a subject's health data and psychological state and to detect any abnormal conditions.

[0657] "Information processing means" refers to technologies and protocols that appropriately mask or encrypt data while protecting personal information.

[0658] A "notification system" is a function that immediately issues a warning when an anomaly is detected and transmits the information to the necessary parties.

[0659] "Means of interaction" refers to functions that use terminals to engage in dialogue with the target individual and provide emotional support and communication.

[0660] To realize this invention, IoT sensors and AI cameras are first used as perceptual means for acquiring external information. This makes it possible to sense environmental information and vital data of the target elderly person or child in real time. The terminal continuously monitors this data and applies masking processing to the video data as an information processing means to protect personal information.

[0661] The acquired data is transmitted to the server via a secure protocol. The server analyzes the data using a generative AI model and, in the event of an anomaly, promptly notifies family members and care staff through notification mechanisms. Notifications are made via email or application notifications. Furthermore, the device provides emotional support by engaging in natural conversations with the individual as a means of interaction.

[0662] As a concrete example, consider monitoring elderly people at night. The device uses an AI camera to monitor the elderly person's breathing and heart rate while they sleep. If an abnormality is detected, the server makes a judgment and sends a notification, prompting emergency action. The generated information is analyzed by a generative AI model and fed back to the family. Through this process, it becomes possible to consistently manage the safety and health of the elderly person.

[0663] An example of how the generative AI model can be used is a prompt such as, "Please describe in detail a scenario in which an abnormality is detected while an elderly person is napping in their living room, and what kind of support should be provided and how it should be notified." In this way, technologically advanced monitoring and emotional support are realized.

[0664] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0665] Step 1:

[0666] The device acquires external environmental information and vital data of the subject. Using an AI camera and IoT sensors, it detects data in real time and temporarily stores the results within the device. Inputs are environmental data and vital signs, while output is organized data.

[0667] Step 2:

[0668] The device applies data processing to the acquired data to protect privacy. Specifically, video data is masked. This process blurs information so that individuals cannot be identified. The input is the original video data, and the output is the video data after masking.

[0669] Step 3:

[0670] The masked data is sent to the server via a secure protocol. The server receives this data and prepares to analyze the information. The input is the masked data, and the output is the organized data for analysis.

[0671] Step 4:

[0672] The server uses a generative AI model to analyze data. It evaluates the target's behavioral patterns and health status to determine if there are any abnormalities. The input is organized data, and the output is the analysis result regarding the presence or absence of abnormalities.

[0673] Step 5:

[0674] If an anomaly is detected, the server will notify relevant family members or care staff using notification methods. Application notifications and email are used as notification methods. The input is the analysis results, and the output is a notification alert message.

[0675] Step 6:

[0676] The device engages in dialogue to provide emotional support through means of interaction with the user. It utilizes a generative AI model to support the user's mental well-being through relaxed conversation. Input is the user's statements and actions, and output is the AI-generated dialogue.

[0677] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0678] In implementing the present invention, the system for effectively monitoring the safety and health of the elderly and children includes, in addition to sensor means, analysis means, monitoring means, data processing means, and notification means, an emotion engine that recognizes the user's emotions. The terminal uses an AI camera or IoT sensor as a sensor means to acquire environmental data and vital signs of the subject. This data is masked to protect privacy before being transmitted to the server.

[0679] The server analyzes the received data using analytical tools to evaluate the subject's behavioral patterns and health status. Furthermore, the emotion engine is responsible for analyzing the user's emotional state through voice input. The emotion engine has the function of recognizing the user's emotional changes in real time and evaluating their mental state based on this.

[0680] The user participates in a process of evaluating their own emotional state by interacting with AI through the device. The device interprets voice information and nonverbal elements using an emotion engine and sends the results to the server. The server continuously evaluates the user's mental state based on this information. If an abnormality is detected, it quickly notifies family members and care staff via a notification system.

[0681] For example, if a user makes a statement indicating emotional distress during a normal conversation, the device's emotion engine detects this change. The server immediately analyzes the results and, if necessary, sends a notification to family members to encourage early intervention. This process enables rapid support and follow-up tailored to the user's emotions and mental state.

[0682] The following describes the processing flow.

[0683] Step 1:

[0684] The device activates sensor devices to acquire environmental information and vital data of the subject. This includes collecting video data using an AI camera and measuring temperature, humidity, and heart rate using IoT sensors.

[0685] Step 2:

[0686] The device applies a masking process to the acquired data to protect privacy. This ensures privacy before the data is transmitted.

[0687] Step 3:

[0688] The terminal sends the processed data to the server. The data transmission is encrypted to ensure data security.

[0689] Step 4:

[0690] The server stores the received data in a database and uses analysis tools to analyze behavioral patterns and health status. It detects unusual behavior and changes in vital signs.

[0691] Step 5:

[0692] The device activates an emotion engine, collects voice data through interaction with the user, and recognizes changes in emotion. The emotion engine analyzes voice tone and speech content to evaluate the user's emotional state.

[0693] Step 6:

[0694] The server analyzes the emotional state evaluation results obtained from the emotion engine and activates a notification system if it detects abnormal emotions or mental burden.

[0695] Step 7:

[0696] The server notifies family members and caregivers of any detected anomalies or emotional disturbances. Notifications are sent via email or app to encourage prompt action.

[0697] Step 8:

[0698] Users can receive feedback and advice from the server through their device interface as needed. This enhances user confidence and improves the support system.

[0699] (Example 2)

[0700] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0701] To effectively monitor the safety and health of the elderly and children, it is necessary to continuously monitor situational and biometric data and to quickly detect anomalies while protecting privacy. However, existing systems have difficulty evaluating non-physical elements such as emotional changes in real time, which can lead to delays in early response.

[0702] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0703] In this invention, the server includes detection means for acquiring external situational data, evaluation means for evaluating the behavioral patterns of a subject based on the acquired situational data, and emotion analysis means for recognizing the user's emotional state from voice input. This makes it possible to comprehensively evaluate the user's physical and emotional state and take prompt action as needed.

[0704] "Detection means" refers to a device or method used to acquire external situational data.

[0705] "Evaluation means" refers to a process or technique used to evaluate the behavioral patterns of a subject based on acquired situational data.

[0706] "Monitoring means" refers to a device or system for continuously monitoring a subject's biometric data.

[0707] "Information processing means" refers to a system or algorithm used to process and modify data in order to protect privacy.

[0708] "Notification means" refers to a method or device for informing relevant parties when an anomaly is detected.

[0709] "Emotional analysis means" refers to a technology or system for recognizing a user's emotional state from voice input.

[0710] A "dialogue method" is a communication system for evaluating the mental state of the subject and, if necessary, notifying external parties.

[0711] "Treatment measures" refer to actions or methods for providing prompt support based on the emotional state of the person concerned.

[0712] This invention is specifically implemented as a system for monitoring the safety and health of the elderly and children. The system is primarily composed of the interaction between terminals, servers, and users.

[0713] The device uses hardware such as AI cameras and IoT sensors to acquire data on the subject's surrounding environment and biometric data. This data includes temperature, humidity, heart rate, and activity level. This information is masked to protect data privacy before being sent to the server.

[0714] The server uses machine learning algorithms as an analysis tool to evaluate the subject's behavioral patterns and health status based on the received data. Furthermore, the server employs emotion analysis tools to recognize changes in the user's emotional state by analyzing their voice in real time. These analysis results serve as important input for evaluating the mental state.

[0715] The user participates in an interaction with the AI ​​through the device and is involved in the emotion analysis process. The user provides voice input, which the device processes through an emotion analysis system and sends the analysis results to a server. Based on this information, if the server detects an anomaly, it will promptly notify family members or care staff through a notification system.

[0716] As a concrete example, if a user makes a statement indicating emotional distress during a normal conversation, the device detects this change using emotion analysis. The server analyzes the change in emotion and, if necessary, sends a notification to the family. This process enables rapid support for the user's mental state.

[0717] As an example of a prompt to a generative AI model, you could use a sentence like, "Please describe the procedure for identifying the user's emotional state from their voice data, evaluating its changes in real time, and providing notifications."

[0718] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0719] Step 1:

[0720] The device uses an AI camera and IoT sensors to acquire external environmental data and biometric data of the subject. The input here is raw data from the sensors, and the output is a dataset including temperature, humidity, heart rate, activity level, etc. Specifically, the AI ​​camera captures the subject's movements, and the IoT sensors measure vital signs.

[0721] Step 2:

[0722] The device performs privacy-protecting masking on the acquired data. The dataset acquired in the previous step is used as input, and the output is data with privacy information protected. Specifically, personally identifiable information is extracted and encrypted or deleted.

[0723] Step 3:

[0724] The terminal sends masked data to the server. The input here is the masked data, and the output is the transfer of that data to the server. Specifically, the terminal generates a data package and transfers it using a secure protocol.

[0725] Step 4:

[0726] The server analyzes the received data and evaluates behavioral patterns and health status. The input here is the data sent to the server, and the output is an indicator of behavioral patterns and health status as an evaluation result. Specifically, it uses machine learning algorithms to analyze the data, and the evaluation model is executed within the software.

[0727] Step 5:

[0728] The server analyzes the user's voice input using emotion analysis tools. The input is voice data, and the output is an evaluation result indicating the emotional state. Specifically, the tone and tempo of the voice are passed through an analysis algorithm, and an emotion model is executed.

[0729] Step 6:

[0730] Users interact with the AI ​​through their device and participate in the assessment of their emotional state. The input is the user's voice, and the output is feedback resulting from the emotion analysis. Specifically, the user speaks into the device, and their voice is interpreted in real time.

[0731] Step 7:

[0732] The server, upon detecting an anomaly, promptly notifies family members and caregivers through notification channels. Inputs are assessed health and emotional states, and outputs are notification messages. Specifically, the server automatically sends emails or alerts when notification conditions are met.

[0733] (Application Example 2)

[0734] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0735] To ensure the safety and health of the elderly and children, real-time monitoring of their health and emotional states is necessary. However, systems that effectively achieve this lack mechanisms to accurately assess emotional states, quickly detect abnormalities, and prompt appropriate responses. Solving this challenge is essential to providing faster and more appropriate care and support.

[0736] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0737] In this invention, the server includes sensing means for acquiring external environmental information, analysis means for analyzing the behavioral patterns of a subject based on the acquired environmental information, and monitoring means for continuously monitoring the subject's health data. This enables real-time evaluation of the subject's emotional state, immediate detection of abnormalities, appropriate notification, and rapid response.

[0738] "Sensing means" refers to devices or methods for acquiring external environmental information, and is a technology that uses cameras, sensors, etc., to detect the situation of a subject.

[0739] "Analysis means" refers to devices or methods that analyze the behavioral patterns of subjects based on acquired environmental information, and is a technology for understanding the trends of subjects by analyzing data.

[0740] "Health data" refers to data that indicates the physical condition of a subject, and includes information used to evaluate their health status, such as vital signs and sleep patterns.

[0741] "Monitoring means" refers to devices or methods that continuously monitor a subject's health data, and is a technology for constantly checking the latest health status and detecting abnormalities.

[0742] "Information processing means" refers to devices and methods that process acquired data while protecting privacy, and is a technology for safely handling personal information.

[0743] A "notification system" is a device or method that quickly notifies relevant parties when an anomaly is detected, and is a technology that prompts necessary action.

[0744] An "emotion recognition engine" is a device or method for evaluating a person's emotional state in real time, and it is a technology that determines emotions by analyzing voice, facial expressions, etc.

[0745] The system for implementing this invention includes several key components to monitor the safety and health of the subject. The system operates via devices such as smart glasses or smartphones, which are equipped with AI cameras and sensors. This makes it possible to acquire environmental information and health data in real time.

[0746] The device uses an emotion recognition engine based on Python and TensorFlow to analyze the subject's emotional state in real time. Video data is preprocessed using OpenCV to extract specific features. Then, emotions are analyzed using a TensorFlow generative AI model.

[0747] The server receives data transmitted from the terminal and evaluates behavioral patterns using analysis tools. It also continuously monitors health data using monitoring tools, and if an abnormality is detected, it notifies relevant parties using notification tools.

[0748] For example, if a particular resident exhibits unusual behavior or facial expressions, the emotion recognition engine analyzes the change, and the server immediately determines that something is wrong. It can then notify family members or care staff as needed, prompting a quick response.

[0749] Examples of prompts for a generative AI model are as follows:

[0750] "Analyze the camera footage and assess the residents' emotional and physical condition. If any abnormalities are found, provide advice on what actions should be taken."

[0751] This system enables prompt and appropriate monitoring and support based on the emotions and health status of the individuals involved.

[0752] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0753] Step 1:

[0754] The device uses an AI camera to capture video of the subject. The input is real-time video data, and by acquiring this video data, it captures the basic information necessary for subsequent processing steps.

[0755] Step 2:

[0756] The device preprocesses video data using OpenCV to extract the subject's features. The input is captured video data, and the output is numerical data related to facial features and expressions. This preprocessing allows for more accurate emotion analysis.

[0757] Step 3:

[0758] The device uses TensorFlow and analyzes emotional states from feature points extracted using a generative AI model. The input is feature point data, and the output is data indicating the type and degree of emotion. This visualizes the user's current emotional state.

[0759] Step 4:

[0760] The terminal sends the analyzed emotional data to the server. The input is the result of the emotional analysis, and the output is data used for further analysis on the server side. This transmission allows the emotional state of the subject to be managed centrally.

[0761] Step 5:

[0762] The server analyzes the received emotional data and evaluates the subject's behavioral patterns and health status. The input consists of the emotional analysis results and past health data, while the output is data showing the evaluation results. The analysis clarifies the subject's mental state.

[0763] Step 6:

[0764] If the server detects an anomaly based on the analysis results, it will promptly notify the relevant parties using a notification system. The input is the analysis result data, and the output is alert information sent to the relevant parties. This notification will prompt appropriate action.

[0765] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0766] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0767] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0768] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0769] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0770] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0771] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0772] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0773] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0774] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0775] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0776] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0777] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0778] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0779] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0780] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0781] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0782] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0783] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0784] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0785] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0786] The following is further disclosed regarding the embodiments described above.

[0787] (Claim 1)

[0788] Sensor means for acquiring external environmental information,

[0789] An analytical means for analyzing the behavioral patterns of subjects based on acquired environmental information,

[0790] A monitoring system for continuously monitoring the vital data of the subject,

[0791] Data processing means for protecting privacy,

[0792] A notification mechanism for notifying when an anomaly is detected,

[0793] A system that includes this.

[0794] (Claim 2)

[0795] The system according to claim 1, which uses sensor means to monitor the sleep state of a subject and detect abnormalities.

[0796] (Claim 3)

[0797] The system according to claim 1, which evaluates the mental state of a subject through dialogue and notifies external parties as necessary.

[0798] "Example 1"

[0799] (Claim 1)

[0800] Sensor means for acquiring external information,

[0801] An analysis means for analyzing the operation pattern based on the acquired information,

[0802] Monitoring means for continuously monitoring health-related data,

[0803] Data processing means for protecting privacy,

[0804] A notification means for communicating when an anomaly is detected,

[0805] A means of dialogue for interacting with a subject via voice input,

[0806] A system that includes this.

[0807] (Claim 2)

[0808] The system according to claim 1, which uses sensor means to monitor the state during rest and detect abnormalities.

[0809] (Claim 3)

[0810] The system according to claim 1, which evaluates the mental state of a subject and communicates with an external party as necessary.

[0811] "Application Example 1"

[0812] (Claim 1)

[0813] Perceptual means for acquiring external information,

[0814] A processing means for analyzing the target's behavioral patterns based on acquired information,

[0815] Monitoring means for continuously monitoring the target health data,

[0816] Information processing means for protecting personal information,

[0817] A notification system for issuing warnings when an anomaly is detected,

[0818] A means of communication to provide emotional support through interaction using a terminal,

[0819] A system that includes this.

[0820] (Claim 2)

[0821] The system according to claim 1, which uses perceptual means to monitor the resting state of an object and issues a warning in the event of an abnormality.

[0822] (Claim 3)

[0823] The system according to claim 1, which evaluates the mental state of a subject through interaction and, if necessary, notifies a remote location.

[0824] "Example 2 of combining an emotion engine"

[0825] (Claim 1)

[0826] A detection means for acquiring external situational data,

[0827] An evaluation method for evaluating the behavioral patterns of subjects based on acquired situational data,

[0828] A monitoring system for continuously monitoring the biometric data of the subject,

[0829] Information processing means for protecting privacy,

[0830] A notification mechanism for notifying when an anomaly is detected,

[0831] A means of emotion analysis for recognizing the user's emotional state from voice input,

[0832] A means of dialogue for evaluating the mental state of the subject and notifying external parties as necessary,

[0833] A system that includes this.

[0834] (Claim 2)

[0835] The system according to claim 1, which uses emotion analysis means to recognize changes in a user's emotions in real time.

[0836] (Claim 3)

[0837] The system according to claim 1, comprising means for providing prompt support based on the emotional state of the subject.

[0838] "Application example 2 when combining with an emotional engine"

[0839] (Claim 1)

[0840] A sensing means for acquiring external environmental information,

[0841] An analytical means for analyzing the behavioral patterns of subjects based on acquired environmental information,

[0842] Monitoring means for continuously monitoring the health data of the target individuals,

[0843] Information processing means for protecting privacy,

[0844] A notification method for sending notifications when an anomaly is detected,

[0845] Equipped with an emotion recognition engine to evaluate the emotional state of subjects in real time,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, which uses sensing means to monitor the sleep state of a subject and detect abnormalities.

[0849] (Claim 3)

[0850] The system according to claim 1, which evaluates the mental state of a subject through dialogue and, if necessary, notifies an external party. [Explanation of symbols]

[0851] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Perceptual means for acquiring external information, A processing means for analyzing the target's behavioral patterns based on acquired information, Monitoring means for continuously monitoring the target health data, Information processing means for protecting personal information, A notification system for issuing warnings when an anomaly is detected, A means of communication to provide emotional support through interaction using a terminal, A system that includes this.

2. The system according to claim 1, which uses perceptual means to monitor the resting state of an object and issues a warning in the event of an abnormality.

3. The system according to claim 1, which evaluates the mental state of a subject through interaction and, if necessary, notifies a remote location.

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