system

Abstract

Provide a system. [Solution] A means for receiving data such as movement, temperature, and heart rate from sensors installed in the home; A means for analyzing the received data and detecting inactivity or abnormal vital signs; means for calling emergency services if there is no response from the user; A means of providing support for daily life in the form of voice dialogue; A system including:

Description

[Technical Field]

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

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

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

[0004] As the aging society with a declining birthrate progresses, the number of elderly people living alone is increasing. Under these circumstances, there is a growing risk that elderly people will become isolated at home and that a sudden deterioration in their health or an accident will go unnoticed. As a result, elderly people may not receive appropriate medical services or emergency response, which could lead to serious problems. To solve these problems, the present invention aims to provide a system that monitors the living conditions and health conditions of residents at home in real time and takes immediate appropriate action if an abnormality is detected. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by the following means. Specifically, it provides a means for receiving data in real time from multiple sensors (motion sensors, temperature sensors, heart rate sensors, etc.) installed in the home. It also includes a means for analyzing this sensor data and detecting inactivity or abnormal vital signs. It also provides a voice dialogue means for confirming a response from the user if an abnormality is detected based on the analysis results, and includes a means for automatically calling emergency services if there is no response from the user. In addition, it includes a system that provides support for daily life in a voice dialogue format, comprehensively supporting the user's life. This makes it possible to create an environment where elderly people can live safely and securely at home.

[0006] A "sensor" is a device that is installed inside a home and collects various data such as movement, temperature, and heart rate.

[0007] "Means for receiving data" refers to a device or system for receiving data obtained from a sensor in real time.

[0008] "Means for analyzing data" refers to algorithms and software for detecting inactivity or abnormal vital signs based on received sensor data.

[0009] "Immotence" is an indicator of a state in which a resident remains motionless for a certain period of time.

[0010] "Abnormal vital signs" refers to conditions in which heart rate, body temperature, etc. are outside of normal ranges.

[0011] "Users" refer to residents and elderly people who use this system.

[0012] "Voice interaction means" refers to a function or device that interacts with a user by voice recognition and voice generation using a microphone and speaker.

[0013] "Means for calling emergency services" refers to devices or functions that automatically contact emergency support services such as an ambulance or security company if the user does not respond.

[0014] "Daily life support" refers to functions and systems that provide users with schedule management, notifications on when to take medication, and other support necessary for daily life in the form of voice dialogue.

[0015] "Real-time" refers to the process of processing data immediately and reflecting it without any time delay.

[0016] An "algorithm" is a set of rules or methods that define the computational procedures and processes for data analysis and anomaly detection.

[0017] A "system" is a collection of devices and software that operate by comprehensively combining the above means and functions. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] This system receives data from multiple sensors installed in the home and monitors the user's living conditions and health status, and automatically takes appropriate action if an abnormality is detected. This system consists of three main components: a server, a terminal, and the user.

[0040] System Configuration and Operation

[0041] Sensor placement and data collection

[0042] Server: Receives real-time data from various sensors installed in the home (motion sensors, temperature sensors, heart rate sensors, etc.). Each sensor is installed in a different location and collects information on the user's behavior and environment.

[0043] Data analysis

[0044] Server: Analyzes the received sensor data and evaluates whether there is inactivity or abnormal vital signs. For example, if there is inactivity for a certain period of time or if the heart rate is outside the normal range, it is determined to be abnormal.

[0045] The analysis means uses an algorithm that compares the current time with the timestamp sent by the sensor and detects whether there has been a period of inactivity.

[0046] Anomaly detection and user notification

[0047] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The user will respond by voice to confirm that there is no abnormality.

[0048] The device uses voice recognition technology to analyze the user's response and provide appropriate feedback.

[0049] Emergency response

[0050] Server: If the user does not respond within a certain time frame, the server automatically calls emergency services, allowing for a quick response to ensure the user's safety.

[0051] Emergency contact methods send emergency messages to pre-defined contacts (emergency services, family, security companies, etc.).

[0052] Daily support

[0053] Terminal: Providing everyday support through voice interaction. For example, providing appropriate information in response to a user's question such as "What is my schedule for today?"

[0054] The device manages the user's schedule and sets reminders when necessary.

[0055] Specific Examples

[0056] Example 1: Daily support

[0057] 1. User: Says to the device, "What's on my schedule for today?"

[0058] 2. Terminal: Recognizes the user's question and announces in voice, "Your regular checkup will be at 3:00 p.m. today."

[0059] Example 2: Emergency response

[0060] 1. Server: Receives data from sensors and detects inactivity for more than two hours.

[0061] 2. Terminal: The user is prompted with a voice message saying "Please answer. Are you OK?"

[0062] 3. User: No response.

[0063] 4. Server: No response within a certain time, so call emergency services.

[0064] Example 3: Detecting abnormalities in vital signs

[0065] 1. Server: Receives abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[0066] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[0067] 3. Terminal: Notify the user, "Please answer. Are you OK?"

[0068] 4. User: No response.

[0069] 5. Server: Calls emergency services after no response within a certain time.

[0070] As described above, the present invention uses sensors to monitor the living conditions and health status of residents in real time, and responds quickly if an abnormality is detected, thereby providing an environment in which residents can live in peace of mind.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] Server: Receives data in real time from various sensors (motion sensor, temperature sensor, heart rate sensor, etc.). The server centrally manages this data and stores it with a timestamp. For example, the server receives data such as "no_movement" from the motion sensor, "60 BPM" from the heart rate sensor, and "22°C" from the temperature sensor.

[0074] Step 2:

[0075] Server: Analyzes the received sensor data and runs algorithms to detect inactivity and abnormal vital signs. Iactivity detection compares the current time with the time of the last detected movement to determine whether the person has been inactive for a certain period of time. It also determines an abnormality if the heart rate is outside the set normal range.

[0076] Step 3:

[0077] Server: If an abnormality is detected based on the analysis results, proceed to the next step. If normal, switch to daily support functions. For example, if a user wants to know "today's schedule," provide appropriate information.

[0078] Step 4:

[0079] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The terminal will use voice recognition technology to analyze the user's response. If the user responds, it will determine that there is no abnormality.

[0080] Step 5:

[0081] Server: If no response is received from the user within a certain time, the server will automatically initiate action to call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[0082] Step 6:

[0083] Server: When calling emergency services, the server attempts to contact the emergency service as quickly as possible using multiple methods (telephone, email, SMS, etc.) and accurately communicates details of the emergency (e.g., "inactivity for more than two hours" or "heart rate below 50 BPM").

[0084] Step 7:

[0085] Terminal: Responds to user requests as a daily support function. When a user says, "Please tell me what's on my schedule for today," the terminal retrieves schedule information from the server and notifies them by voice, "I have a regular checkup at 3:00 p.m. today." It also has a reminder function that notifies users when it's time to take their medication.

[0086] Step 8:

[0087] User: Uses the daily support functions to check their schedule and medication times. Obtains necessary information through dialogue with the device as needed. In an emergency, ensures safety by responding promptly to response confirmation notifications from the device.

[0088] The above are the specific processing steps of the system of the present invention. At each step, the server, terminal, and user work in cooperation to safely and effectively support the lives of residents.

[0089] Example 1

[0090] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0091] Daily health monitoring and rapid response in the event of an abnormality are important for elderly people and residents with health concerns to live with peace of mind. However, conventional systems lack the means to detect abnormalities in real time, notify users through voice dialogue, and automatically take emergency action based on the subsequent response. Furthermore, the functionality to provide continuous support for daily life was also insufficient. This resulted in a delay in appropriate response in the event of an abnormality, posing a risk of not ensuring the safety of users.

[0092] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0093] In this invention, the server includes means for receiving data from multiple sensors installed in the house, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for notifying the user by voice of the detected abnormality, means for calling emergency services if the user does not respond, and means for providing support for daily life in the form of voice dialogue. This allows the user's living situation and health condition to be monitored in real time, and if an abnormality is detected, a prompt response can be made, creating an environment in which the user can live with peace of mind.

[0094] "House" refers to a building for human habitation.

[0095] A "sensor" refers to a device that detects physical or environmental phenomena and collects that information as data.

[0096] "Data" refers to detected information, which is recorded in the form of numbers, character strings, or the like.

[0097] "Means" refers to a method or device used to achieve a particular purpose.

[0098] "Analysis" refers to the process of breaking down and interpreting data in order to evaluate and make judgments.

[0099] "Idle" refers to a period of no movement.

[0100] "Vital signs" refers to vital signs such as heart rate, body temperature, and respiratory rate.

[0101] "User" refers to a person who uses the system.

[0102] "Responding" refers to the user's response to a notification from the system.

[0103] "Emergency services" refers to emergency response agencies and services such as emergency medical services, police, and fire departments.

[0104] "Voice dialogue" refers to two-way communication using voice.

[0105] "Life support" refers to assistance with daily activities and the provision of information.

[0106] This invention is a system that receives data from multiple sensors installed in a home and monitors a user's living conditions and health status. The system consists of three main components: a server, a terminal, and a user. The detailed configuration and operation of the system are described below.

[0107] Sensor placement and data collection

[0108] Server: Receives real-time data from various sensors (e.g., motion sensor, temperature sensor, heart rate sensor) placed in the home. Each sensor is installed in a different location and collects information on the user's behavior and environment.

[0109] Hardware used: Raspberry Pi, Arduino sensors, etc.

[0110] Data analysis

[0111] Server: Analyzes the received sensor data and evaluates whether there is any motion or abnormal vital signs. This analysis is performed using Python, processing the data using Pandas and NumPy.

[0112] For example, if there is no movement for a certain period of time (e.g., 30 minutes) or if the heart rate falls outside a certain range (e.g., 40 BPM or less), it is determined to be abnormal.

[0113] Anomaly detection and notification

[0114] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" This notification uses the Google (registered trademark) Speech-to-Text API.

[0115] The device uses voice recognition technology to analyze the user's response and confirm that there are no abnormalities.

[0116] Emergency response

[0117] Server: If no response is received from the user within a certain time (e.g., 1 minute), the server automatically calls emergency services. It uses the Twilio API to communicate with the emergency services, sending messages and calls to pre-defined contacts.

[0118] Software used: Twilio API, SMTP server, etc.

[0119] Support for daily life

[0120] Device: Provides daily support through voice interaction. For example, in response to a user question such as "What are your plans for today?", the device retrieves schedule information using the Google Calendar API and sets reminders at the appropriate time.

[0121] Software used: Google Calendar API, Amazon Alexa, etc.

[0122] Specific Examples

[0123] Example 1: Daily support

[0124] 1. User: Say to the device, "What's on my schedule for today?"

[0125] 2. Device: Uses the Google Calendar API to retrieve the schedule for the day and notifies the user via voice message, saying, "Your regular checkup will be at 3:00 p.m. today."

[0126] Example 2: Emergency response

[0127] 1. Server: Receives data from the motion sensor and detects inactivity for more than two hours.

[0128] 2. Device: A voice message will say "Please answer. Are you OK?"

[0129] 3. User: No response.

[0130] 4. Server: No response within 1 minute, so calls emergency services using the Twilio API.

[0131] Example 3: Detecting abnormalities in vital signs

[0132] 1. Server: Receives abnormal heart rate (e.g., below 40 BPM) from the heart rate sensor.

[0133] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[0134] 3. Terminal: Notify "Please answer. Are you OK?"

[0135] 4. User: No response.

[0136] 5. Server: No response within 1 minute, so calls emergency services using the Twilio API.

[0137] In this way, the present invention uses sensors to monitor the living conditions and health status of residents in real time, and by responding quickly if an abnormality is detected, it provides an environment in which residents can live in peace of mind.

[0138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0139] Step 1: Collect data from sensors

[0140] Server: Receives real-time data from sensors (motion sensors, temperature sensors, heart rate sensors, etc.). The sensors transmit data from each device via Bluetooth or Wi-Fi.

[0141] Input: Measurement data sent from sensors (movement, temperature, heart rate)

[0142] Specific operation: The server receives data from each sensor every second and records it in a database (e.g., MySQL (registered trademark)) in chronological order.

[0143] Output: Sensor data stored in a database

[0144] Step 2: Analyze the data

[0145] Server: Analyzes the received sensor data and detects inactivity or abnormal vital signs. This is done using a Python script that processes the data using Pandas and NumPy.

[0146] Input: Sensor data retrieved from a database

[0147] Data processing: A Python script analyzes the data from each sensor and calculates the average, maximum, and minimum values ​​of inactivity time and vital signs.

[0148] Specific operation: If there is no movement for more than 30 minutes or if the heart rate is below 40 BPM, an abnormality flag is raised.

[0149] Output: Analysis results flagged as abnormal

[0150] Step 3: Anomaly detection and notification

[0151] Device: If an abnormality is detected, the device will notify the user by voice, saying, "Please respond. Are you OK?" The user's voice response will be analyzed using the Google Speech-to-Text API.

[0152] Input: Analysis results flagged as abnormal

[0153] Specific operation: The device plays a voice prompt every 10 seconds, collects the user's voice response using the microphone, converts the collected voice into text, and analyzes the response content.

[0154] Output: User response text

[0155] Step 4: Response analysis and feedback

[0156] Server: Analyzes the user's response and verifies that there are no abnormalities. If an abnormality is detected, prepares further countermeasures.

[0157] Input: User response text

[0158] Data calculation: If the response is positive, such as "It's okay," it is determined that there is no abnormality, and if the response is negative or there is no response, an emergency response is prepared.

[0159] Specific operation: The server evaluates the presence and content of the response and decides whether to proceed to the next step or cancel the abnormality alarm.

[0160] Output: Emergency response flag or alarm clear

[0161] Step 5: Emergency response

[0162] Server: If there is no response from the user within a certain time (e.g. 1 minute), automatically call emergency services. Use the Twilio API to call and email emergency contacts.

[0163] Input: Emergency Response Flag

[0164] What it does: The server calls Twilio's API to send an emergency message to pre-defined contacts, including information about the user's inactivity time and abnormal vital signs.

[0165] Output: Notification of emergency message transmission completion

[0166] Step 6: Support for daily living

[0167] Device: Providing daily support through voice interaction. For example, in response to a user's question, "What's on my schedule for today?", the device retrieves schedule information using the Google Calendar API.

[0168] Input: User's voice input (question)

[0169] Data processing: Amazon Alexa analyzes the voice input and calls the Google Calendar API to obtain schedule information.

[0170] Specific operation: The device recognizes the user's question, obtains schedule information, and notifies the user by voice.

[0171] Output: Schedule information announced by voice

[0172] (Application example 1)

[0173] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0174] Conventional home monitoring systems are required to respond quickly and effectively when an abnormality is detected, but they have problems such as being unable to respond appropriately to an emergency situation due to the user's absence or delayed response.In addition, they lack daily support functions, making them less practical as systems that support the user's daily life in general.

[0175] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0176] In this invention, the server includes means for receiving data such as movement, temperature, and heart rate from sensors installed in the house, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for calling emergency services if the user does not respond, means for providing support for daily life in the form of voice dialogue, means for monitoring data from the sensors in real time and sending an alarm notification to the smartphone if an abnormality is detected, means for analyzing the response using voice recognition technology if the user does not respond to the voice notification, and means for automatically making an emergency call if the user does not respond. This ensures the user's safety and enables rapid emergency response, while also providing daily life support functions and improving the user's quality of life.

[0177] A "sensor" is a device that is installed inside a home and collects various data such as movement, temperature, and heart rate.

[0178] The "means for receiving data" refers to a device or program that has the function of acquiring information sent from a sensor and transferring it to a server.

[0179] A "means for analyzing data" is a method or device that statistically or algorithmically processes received data to detect inactivity or abnormal vital signs.

[0180] A "means for calling emergency services" is a device or program that automatically contacts pre-defined emergency contacts if there is no response from the user.

[0181] The "means for providing support for daily life in a voice interactive format" is a device or program for providing information in a voice interactive format in response to a user's questions or requests.

[0182] "Means for real-time monitoring" refers to devices or programs that have the function of instantly acquiring and analyzing data obtained from sensors.

[0183] The "means for sending an alarm notification" is a device or program for issuing a warning to a user's device such as a smartphone when an abnormality is detected.

[0184] The "means for analyzing a response using voice recognition technology" refers to a technology or device for recognizing a user's voice response and analyzing its content.

[0185] The "means for automatically making an emergency contact" is a device or program for automatically contacting a set emergency contact if the user does not respond.

[0186] This invention is a system for monitoring a user's lifestyle and health status and responding quickly when an abnormality is detected. This system consists of three main components: a server, a terminal, and a user. Each of these components is explained in detail below.

[0187] System Configuration and Operation

[0188] 1. Sensor placement and data collection

[0189] The server receives real-time data from various sensors installed in the home (motion sensors, temperature sensors, heart rate sensors, etc.). Each sensor is installed in a different location and collects information on the user's behavior and environment.

[0190] 2. Data Analysis

[0191] The server analyzes the received sensor data and determines if there is an abnormality if there is no movement for a certain period of time or if the heart rate is outside the normal range. The analysis method includes an algorithm that compares the current time with the timestamp sent from the sensor to detect whether there has been a prolonged period of no movement.

[0192] 3. Anomaly detection and user notification

[0193] If an abnormality is detected, the device will notify the user by voice, saying, "Please respond. Are you OK?" This uses voice recognition technology to analyze the user's response and provide appropriate feedback. The main interfaces include smartphones and headsets.

[0194] 4. Emergency Response

[0195] If the server does not receive a response from the user within a certain time, it will call emergency services and send an emergency message to pre-defined contacts (emergency services, family, security companies, etc.).

[0196] 5. Daily support

[0197] The device provides daily support through voice interaction. For example, in response to a user's question such as "What is your schedule for today?", the device will respond by voice with "Your regular checkup will be at 3:00 p.m. today."

[0198] Specific examples of the technology

[0199] Example 1: Daily support

[0200] 1. The user speaks to the device, "What are your plans for today?"

[0201] 2. The device recognizes the user's question and provides appropriate information by voice.

[0202] Example 2: Emergency response

[0203] 1. The server receives data from the sensor and detects anomalies, such as inactivity for more than two hours.

[0204] 2. The terminal notifies the user, "Please answer. Are you OK?"

[0205] 3. If the user does not respond, the server will recognize that there has been no response within a certain time and will call emergency services.

[0206] Example 3: Detecting abnormalities in vital signs

[0207] 1. The server receives an abnormal heart rate from the heart rate sensor, for example, a value below 50 BPM.

[0208] 2. The server analyzes the abnormality and determines that a prompt response is required.

[0209] 3. The terminal notifies the user, "Please answer. Are you OK?"

[0210] 4. If the user does not respond, the server will automatically contact an emergency number.

[0211] Technology and software used

[0212] Hardware: sensors (motion sensors, temperature sensors, heart rate sensors, etc.), smartphones, headsets

[0213] Software: Sensor app SDK, speech recognition API (Google Speech-to-Text, Apple SiriKit), data analysis algorithm

[0214] Prompt Sentence Examples

[0215] When you receive the notification "Please respond. Are you OK?", generate a program that analyzes the user's response using a speech recognition API and provides appropriate feedback.

[0216] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0217] Step 1:

[0218] Sensor data collection

[0219] The server receives real-time data from motion sensors, temperature sensors, heart rate sensors, etc. installed inside the home.

[0220] Input: Data sent from sensors, such as movement, temperature, and heart rate.

[0221] Output: Sensor data stored on the server.

[0222] Specific operation: The server receives the data sent from each sensor along with the time stamp and stores the data in a database.

[0223] Step 2:

[0224] Data analysis

[0225] The server analyzes the received data and evaluates whether there has been a period of inactivity or abnormal vital signs.

[0226] Input: Sensor data stored on the server.

[0227] Output: Result of normal / abnormal condition.

[0228] What it does: The server compares the current time with the timestamp sent by the sensor and runs algorithms to detect if there has been a period of inactivity or if the heart rate is outside of the normal range.

[0229] Step 3:

[0230] Anomaly detection and user notification

[0231] If an abnormality is detected, the terminal will notify the user by voice, saying, "Please respond. Are you OK?"

[0232] Input: Abnormal notification from the server.

[0233] Output: Audio notification to the user.

[0234] Specific operation: When an abnormality is detected, the device uses a voice recognition API to issue a message prompting the user to respond.

[0235] Step 4:

[0236] User response analysis

[0237] The device uses voice recognition technology to analyze the user's response and check for any abnormalities.

[0238] Input: The user's spoken response.

[0239] Output: Parsed response.

[0240] Specific operation: Uses a speech recognition API (e.g., Google Speech-to-Text or Apple SiriKit) to convert the user's voice response into text and analyze its content.

[0241] Step 5:

[0242] Emergency response

[0243] The server calls emergency services if no response is received from the user within a certain time.

[0244] Input: Parsed response result.

[0245] Output: Emergency contact is made.

[0246] Specific behavior: If there is no response from the user within a certain period of time, the server will automatically contact pre-defined emergency contacts (e.g., emergency services or family members) and report the emergency situation.

[0247] Step 6:

[0248] Daily support

[0249] The terminal provides daily support to the user in the form of voice dialogue.

[0250] Input: The user's voice command.

[0251] Output: Audio feedback.

[0252] Specific operation: When a user speaks to the device, for example, "Please tell me what my schedule is for today," the device processes the question using a voice recognition API and responds with appropriate information (such as the schedule) via voice.

[0253] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0254] This system receives data from multiple sensors installed in the home, monitors the user's living situation and health status, and automatically takes appropriate action if an abnormality is detected. The system is combined with an emotion engine that recognizes the user's emotions and adjusts daily support, enabling more personalized responses. The system consists of three main components: a server, a terminal, and the user.

[0255] System Configuration and Operation

[0256] Sensor placement and data collection

[0257] Server: Receives data in real time from various sensors installed in the house (motion sensor, temperature sensor, heart rate sensor, etc.). The server centrally manages this data and stores it with a timestamp. For example, the server receives data such as "no_movement" from the motion sensor, "60 BPM" from the heart rate sensor, and "22°C" from the temperature sensor.

[0258] Data analysis

[0259] Server: Analyzes the received sensor data and runs algorithms to detect inactivity and abnormal vital signs. Iactivity detection compares the current time with the time of the last detected movement to determine whether the person has been inactive for a certain period of time. It also determines an abnormality if the heart rate is outside the set normal range.

[0260] Anomaly detection and user notification

[0261] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The terminal will use voice recognition technology and an emotion engine to analyze the user's response and evaluate their emotional state. If the user responds, it will determine that there is no abnormality and provide feedback according to their emotional state.

[0262] Emergency response

[0263] Server: If no response is received from the user within a certain time, the server will automatically initiate action to call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[0264] Daily support

[0265] Terminal: Provides daily support through voice dialogue. For example, responds to user questions such as "What are your plans for today?" with appropriate information. Analyzes the user's emotions using an emotion engine and adjusts the support content according to their emotional state.

[0266] Specific Examples

[0267] Example 1: Daily support

[0268] 1. User: Says to the device, "What's on my schedule for today?"

[0269] 2. Device: Recognizes the user's question and uses an emotion engine to analyze the tone and pace of the user's voice. If it determines that the user is stressed, it notifies the user, "You have a regular checkup at 3 PM today, but we recommend that you take some time to relax." If the user is in a normal state, it notifies the user, "You have a regular checkup at 3 PM today."

[0270] Example 2: Emergency response

[0271] 1. Server: Receives data from sensors and detects inactivity for more than two hours.

[0272] 2. Terminal: Notifies the user by voice, "Please respond. Are you OK?". Analyzes the user's response using the emotion engine to determine their emotional state.

[0273] 3. User: No response.

[0274] 4. Server: No response within a certain time, so call emergency services.

[0275] Example 3: Detecting abnormalities in vital signs

[0276] 1. Server: Receives abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[0277] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[0278] 3. Terminal: Notifies the user, "Please respond. Are you OK?". Analyzes the user's response using the emotion engine to determine their emotional state.

[0279] 4. User: No response.

[0280] 5. Server: Calls emergency services after no response within a certain time.

[0281] Example 4: Daily support based on emotional state

[0282] 1. User: Says to the device, "I'm feeling a little tired today."

[0283] 2. Terminal: Recognizes the user's speech and analyzes the user's level of fatigue using an emotion engine.

[0284] 3. Device: Notify: "Would you like to schedule more time for relaxation today?"

[0285] As described above, the system of the present invention uses sensors to monitor the living conditions and health status of residents in real time, and by combining it with an emotion engine, it individualizes responses when abnormalities are detected and daily support, providing an environment in which users can live with peace of mind.

[0286] The processing flow will be explained below.

[0287] Step 1:

[0288] Server: Receives data from various sensors (motion sensor, temperature sensor, heart rate sensor, etc.) in real time and stores it with a timestamp. For example, it receives data such as "Motion sensor: no_movement", "Heart rate sensor: 60 BPM", and "Temperature sensor: 22°C".

[0289] Step 2:

[0290] Server: Analyzes the received sensor data. To detect inactivity, it compares the current time with the time of the last detected movement to determine whether there has been inactivity for a certain period of time. It also determines that there is an abnormality if the heart rate is outside the set normal range.

[0291] Step 3:

[0292] Server: If an abnormality is detected based on the analysis results, proceed to the next step. If the condition is normal, switch to the daily support function. For example, if the user wants to know "today's schedule," provide schedule information.

[0293] Step 4:

[0294] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?". The emotion engine will be used to analyze the user's response and evaluate their emotional state. If the user responds, it will be determined that there is no abnormality.

[0295] Step 5:

[0296] Server: If the user does not respond within a certain time frame, the server automatically calls emergency services, which can include pre-defined contacts (ambulance services, family, security companies, etc.).

[0297] Step 6:

[0298] Server: When calling emergency services, the server attempts to contact the emergency service as quickly as possible using multiple methods (telephone, email, SMS, etc.) and accurately communicates details of the emergency (e.g., "inactivity for more than two hours" or "heart rate below 50 BPM").

[0299] Step 7:

[0300] Terminal: Responds to user requests as a daily support function. When a user says, "Tell me what's on my schedule for today," the terminal retrieves schedule information from the server and notifies them by voice.

[0301] Step 8:

[0302] Emotion engine: Analyzes the tone, pace, and intonation of the user's voice to assess their emotional state. For example, if it determines that the user is stressed, it will offer advice on how to relax.

[0303] Step 9:

[0304] Device: Adjust daily support based on the results of the emotion engine. For example, if a user says, "I'm a little tired today," the device will notify them, "When adjusting your schedule for today, would you like us to suggest more time for relaxation?"

[0305] Step 10:

[0306] User: Use the daily support features to check their schedule and medication times. For example, they can say, "What's my schedule for today?" and receive notifications from the device. They can also respond to notifications from the device in the event of an emergency.

[0307] Specific Examples

[0308] Example 1: Daily support

[0309] Step 1: The user speaks to the device, "What's on my schedule for today?"

[0310] Step 2: The device recognizes the user's question and uses an emotion engine to analyze the tone and pace of the user's voice.

[0311] Step 8: If the device determines that the user is stressed, it notifies the user, "You have a regular checkup at 3 PM today, but we recommend that you take some time to relax." If the user is in a normal state, it notifies the user, "You have a regular checkup at 3 PM today."

[0312] Example 2: Emergency response

[0313] Step 1: The server receives data from the sensors and detects inactivity for more than two hours.

[0314] Step 4: The device notifies the user by voice, "Please respond. Are you OK?" The emotion engine analyzes the user's response and determines their emotional state.

[0315] Step 5: The user does not respond.

[0316] Step 6: The server does not respond within a certain time, so emergency services are called.

[0317] Example 3: Detecting abnormalities in vital signs

[0318] Step 1: The server receives an abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[0319] Step 2: The server analyzes the anomaly and determines that emergency action is required.

[0320] Step 4: The device notifies the user, "Please respond. Are you OK?" The emotion engine analyzes the user's response and determines their emotional state.

[0321] Step 5: The user does not respond.

[0322] Step 6: The server does not respond within a certain time, so emergency services are called.

[0323] Example 4: Daily support based on emotional state

[0324] Step 1: The user says to the device, "I'm feeling a little tired today."

[0325] Step 8: The device recognizes the user's speech and uses an emotion engine to analyze the user's level of fatigue.

[0326] Step 9: Your device will notify you, "Would you like us to suggest more time for relaxation for your schedule today?"

[0327] The above are the specific processing steps of the system of the present invention. At each step, the server, terminal, and user work in cooperation to safely and effectively support the lives of residents.

[0328] Example 2

[0329] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0330] In modern residential environments, there is a need to understand the living conditions and health status of residents in real time and respond quickly when abnormalities occur, but conventional systems have difficulty meeting these requirements. Furthermore, when it comes to supporting users' daily lives, they lack the ability to respond in detail to individual situations and emotions. Therefore, providing an environment where residents can live with peace of mind has become a challenge.

[0331] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving data such as movement, temperature, and heart rate from sensors installed in the house; means for centrally managing the received data and saving it with a timestamp; means for analyzing the received data and detecting inactivity or abnormal vital signs; means for issuing a voice notification when an abnormality is detected and analyzing the user's response using an emotion engine; means for calling emergency services when there is no response from the user; and means for providing support for daily life in the form of voice dialogue and using the emotion engine to provide support according to the user's emotional state. This makes it possible to provide an environment in which the user can live with peace of mind by monitoring the user's living situation and health condition in real time and taking necessary measures promptly.

[0332] A "sensor" is a device that is installed inside a home and collects data such as movement, temperature, and heart rate.

[0333] A "centralized management system" is a system that manages received data in one place and stores it with a timestamp.

[0334] The "analysis means" is a function that uses the received data to execute an algorithm for detecting immobility or abnormal vital signs.

[0335] An "emotion engine" is a technology that analyzes a user's emotional state and determines the appropriate response based on that.

[0336] "Emergency services" are contacts that are automatically contacted if there is no response from the user, and include ambulance services, family, security companies, etc.

[0337] "Voice notification" is a function that notifies the user by voice when an abnormality is detected.

[0338] "Voice interaction" refers to a format in which information is exchanged between a user and a system using voice.

[0339] MODE FOR CARRYING OUT THE INVENTION

[0340] This invention is a system that monitors the user's living situation and health status based on data from sensors installed in the home, and automatically responds if an abnormality is detected. This system consists of three main components: a server, a terminal, and the user.

[0341] Hardware or software used

[0342] The main hardware and software required to implement this system are as follows:

[0343] 1. Sensors: Multiple types of sensors, such as motion sensors, temperature sensors, heart rate sensors, etc.

[0344] 2. Server: A central device that receives, analyzes, stores, detects anomalies, and handles emergency responses.

[0345] 3. Terminal: A device that provides voice notifications, voice interaction, emotion engine analysis, and support for daily life.

[0346] Data processing and calculation

[0347] 1. Data Collection:

[0348] The server receives real-time data such as temperature and heart rate from various sensors installed inside the home and stores it in a centralized management system with a timestamp.

[0349] 2. Data Analysis:

[0350] The server runs an analysis algorithm based on the received data to detect inactivity or abnormal vital signs. To detect inactivity, it compares the current time with the time of the last detected movement and determines whether the person has been inactive for a certain period of time (e.g., two hours). It also determines an abnormality if the heart rate exceeds a set range (e.g., 50 BPM to 100 BPM).

[0351] 3. User response analysis:

[0352] The device has a means for issuing a voice notification when an abnormality is detected, and uses an emotion engine to analyze the user's response and evaluate their emotional state. For example, if the user responds "Yes, I'm fine," the emotion engine evaluates whether the user is calm.

[0353] 4. Emergency Response:

[0354] The server has a mechanism to automatically call emergency services if no response is received from the user within a certain time (e.g., 5 minutes), and has the ability to contact pre-defined contacts (e.g., emergency services, family, security companies, etc.).

[0355] 5. Daily support:

[0356] The device provides support for the user's daily life through voice dialogue, and uses an emotion engine to provide appropriate information according to the user's emotional state. For example, if a user says, "What are your plans for today?", the emotion engine analyzes the tone and pace of the user's voice. If it determines that the user is stressed, it will notify the user, "You have a regular checkup at 3:00 p.m. today, but we recommend that you take some time to relax."

[0357] Prompt Sentence Examples

[0358] Examples of prompts to input to a generative AI model include:

[0359] "Analyze the data from the sensors and explain how you will respond if there are any abnormalities."

[0360] "Recognize the user's emotions and tell me how to provide support based on those emotions."

[0361] The system of the present invention, which includes the above functions, makes it possible to monitor a user's living situation and health condition in real time and take necessary measures quickly, thereby providing an environment in which the user can live with peace of mind.

[0362] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0363] Step 1: Collect sensor data

[0364] The server receives real-time data from sensors installed in the home, such as movement, temperature, and heart rate. The input is the data sent from each sensor (e.g., "no_movement," "22°C," "60 BPM"), and the output is to store this data with a timestamp in a centralized management system. Specifically, the sensors send their measurements to the server, which receives the data and stores it in a database.

[0365] Step 2: Analyze the data

[0366] The server analyzes the collected data. The input is the stored sensor data with a timestamp, and the output is the detection of inactivity or abnormal vital signs. Specifically, the server compares the timestamps of the motion sensor data and checks whether inactivity has continued for a certain period of time (for example, two hours). It also analyzes whether the heart rate data is within a set range (50 BPM to 100 BPM).

[0367] Step 3: Anomaly detection

[0368] The server detects abnormalities based on the analysis results. The input is the analyzed data, and the output is information that an abnormality has been detected. Specifically, if inactivity or an abnormal heart rate is detected, the server records that information and determines that this is an abnormal condition that requires proceeding to the next processing step.

[0369] Step 4: User Notification

[0370] If an abnormality is detected, the device will notify the user by voice. The input is notification data from the server indicating the abnormality, and the output is the voice notification and a response from the user. Specifically, the device will notify by voice, "Please respond. Are you OK?", receive the user's response via the microphone, convert it into text data, and pass it to the emotion engine.

[0371] Step 5: User response analysis

[0372] The device uses an emotion engine to analyze the user's response. The input is text data converted from the user's voice response, and the output is the user's emotional state. Specifically, the device inputs the text data analyzed from the voice into the emotion engine, which evaluates whether the user is calm or stressed.

[0373] Step 6: Emergency response

[0374] If the server does not receive a response from the user within a certain time (e.g., 5 minutes), it automatically calls emergency services. The input is the user's no-response information, and the output is a call to emergency services. Specifically, the server automatically calls and sends messages to pre-defined contacts (e.g., 119, family, security company).

[0375] Step 7: Daily support

[0376] The device provides support for daily life through voice dialogue. The input is questions or requests from the user, and the output is appropriate information or advice. In concrete terms, when a user says, "What are your plans for today?", the device uses an emotion engine to analyze the tone and pace of the user's voice and assess whether they are feeling stressed. If they are feeling stressed, the device will notify them, "You have a regular checkup at 3:00 PM today, but we recommend that you take some time to relax," and if they are feeling normal, it will notify them, "You have a regular checkup at 3:00 PM today."

[0377] As described above, by performing specific data processing or calculations based on the input data at each step and passing the output to the next step, it is possible to monitor the user's living situation and health condition in real time and take any necessary measures quickly.

[0378] (Application example 2)

[0379] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0380] In modern living environments and brick-and-mortar stores, real-time monitoring systems for the health and safety of residents, store staff, and customers are important, but current technology often cannot adequately address these issues. There is a particular need for emergency response and daily life support that is tailored to each individual. In addition to monitoring, there is also a need for personalized responses using emotion engines.

[0381] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0382] In this invention, the server includes means for receiving data such as movement, temperature, and heart rate from sensors installed in the home or store, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for calling emergency services if there is no response from the user, means for providing support for daily life in the form of voice dialogue, means for receiving data from sensors installed in the store and monitoring the behavior of store staff and customers, means for analyzing the received data to detect abnormalities and notifying store staff, and means for analyzing and evaluating the emotions of store staff using an emotion engine along with responses.This improves the safety and health of users, store staff, and customers, and enables individually tailored support and emergency responses.

[0383] "Sensors installed inside the home" refers to various sensors installed inside the home, which are devices for collecting data such as movement, temperature, and heart rate.

[0384] A "motion sensor" is a sensor used to detect motion and to monitor inactivity.

[0385] A "temperature sensor" is a sensor for detecting the ambient temperature and for monitoring changes in the temperature of the environment.

[0386] A "heart rate sensor" is a sensor that measures an individual's heart rate and is used to monitor vital signs.

[0387] A "means for receiving data" is a method or device for acquiring data sent from a sensor.

[0388] A "means for analyzing data" is a method or device for processing received data and detecting abnormal conditions or patterns.

[0389] "Means for invoking emergency services" means a method or device for notifying emergency services or relevant authorities when an abnormality is detected and there is no response from the user.

[0390] The "means for providing in the form of voice interaction" refers to a method or device for interacting with a user using voice to provide support for daily life.

[0391] "Sensors installed in stores" refer to various sensors installed in commercial facilities, and are devices for monitoring the movements and status of store staff and customers.

[0392] An "emotion engine" is an algorithm or device that analyzes the emotional state of users and store clerks and makes appropriate evaluations.

[0393] The "means for notifying a store clerk" is a method or device for notifying a store clerk when an abnormality is detected.

[0394] "Means for analyzing and evaluating emotions" refers to a method or device for analyzing and evaluating the emotional state of a user or store clerk.

[0395] This invention is a system that receives data from multiple sensors installed in homes and stores, monitors the user's living situation and health status, and automatically takes appropriate action if an abnormality is detected. Furthermore, by combining it with an emotion engine, it can recognize the emotions of users, store clerks, and customers and provide individually tailored daily support and emergency responses.

[0396] Hardware and Software Configuration

[0397] 1. Sensor System

[0398] Various sensors (such as motion sensors, temperature sensors, and heart rate sensors) are placed in homes and stores to monitor the environment and personal vital signs in real time.

[0399] 2. Server

[0400] The server receives and centralizes data from various sensors, stores it with a timestamp, analyzes the data, and runs algorithms to detect inactivity or abnormal vital signs. If an abnormality is detected, the server can call emergency services as an appropriate response.

[0401] 3. Terminal

[0402] The terminal provides daily support to users and store staff through voice interaction, utilizing voice recognition technology (e.g., Google Speech-to-Text API) and emotion engines (e.g., Emotion API) to analyze the user's responses and emotional state and provide appropriate feedback.

[0403] System Operation

[0404] Receiving and storing data

[0405] The server receives real-time data from each sensor in a home or store and manages it centrally. For example, it receives data such as "no_movement" from a motion sensor, "22°C" from a temperature sensor, and "60 BPM" from a heart rate sensor. This data is saved with a timestamp.

[0406] Data analysis and anomaly detection

[0407] The server analyzes the received data and detects an abnormality, for example, if the device is inactive for a certain period of time or if the heart rate is outside the normal range.

[0408] Notification and Response

[0409] If an abnormality is detected, the device will notify the user or store clerk by voice, saying, "Please respond. Are you OK?" The device will use an emotion engine to analyze the user's or store clerk's response and evaluate their emotional state. If the user or store clerk responds, it will provide appropriate feedback based on their response.

[0410] Emergency response

[0411] If no response is received from the user or store staff within a certain time frame, the server will automatically call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[0412] Specific examples

[0413] When a user says to the device, "I feel a little tired today," the device will recognize the voice, analyze the user's level of fatigue using an emotion engine, and notify the user, "Would you like us to suggest that you increase your relaxation time when adjusting your schedule for today?"

[0414] If the store's motion sensors detect inactivity for more than two hours, the device will issue a voice message saying, "Please respond. Are you OK?" and will call emergency services if there is no response.

[0415] Prompt Sentence Examples

[0416] "How can we build a system that uses data from sensors in the home to monitor the user's health and take appropriate action if an abnormality is detected?"

[0417] As a result, this system improves the safety and health of users, store staff, and customers, and enables individually tailored support and rapid emergency response.

[0418] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0419] Step 1:

[0420] Receiving data

[0421] The server receives data in real time from various sensors (motion sensors, temperature sensors, heart rate sensors, etc.) installed in homes and stores.

[0422] (Input) Data from each sensor (e.g., movement sensor -> "no_movement", temperature sensor -> "22°C", heart rate sensor -> "60BPM")

[0423] (Output) Sensor data with timestamp

[0424] (Specific operation) The server receives data sent from each sensor through the interface and stores the data in a centralized database with a timestamp.

[0425] Step 2:

[0426] Data analysis

[0427] The server analyzes the received sensor data and executes algorithms to detect abnormal conditions, such as inactivity or abnormal vital signs.

[0428] (Input) Time-stamped sensor data

[0429] (Output) Anomaly detection result (e.g., "Normal", "Abnormal", "No operation", etc.)

[0430] (Specific operation) The server analyzes the sensor data using a preset anomaly detection algorithm (for example, determining periods of inactivity) and determines whether an anomaly has occurred.

[0431] Step 3:

[0432] Abnormal notification

[0433] If an abnormality is detected, the server sends a notification to the terminal, which then issues a voice message to the user or store clerk saying, "Please respond. Are you OK?"

[0434] (Input) Anomaly detection results

[0435] (Output) The execution status of the voice notification (e.g., "Notification sent").

[0436] (Specific Operation) When an abnormality is notified from the server, the terminal uses its voice synthesis function to generate a voice message and notifies the user or store clerk through the speaker.

[0437] Step 4:

[0438] User Response and Sentiment Analysis

[0439] When a user or a store clerk responds to the terminal, the terminal uses voice recognition technology to convert the response into text data and uses an emotion engine to analyze the emotion.

[0440] (Input) User or store clerk's voice response

[0441] (Output) Analyzed emotional state (e.g., "stressed," "normal," etc.)

[0442] (Specific operation) The device uses voice recognition technology such as the Google Speech-to-Text API to convert speech into text, and then inputs the text data into the Emotion API to analyze the emotional state.

[0443] Step 5:

[0444] Providing feedback

[0445] Based on the analysis results, the terminal provides appropriate feedback to the user or store clerk via voice.

[0446] (Input) Analyzed emotional state

[0447] (Output) Feedback message (e.g. "Relax" or "Everything is fine")

[0448] (Specific operation) The terminal selects a feedback message based on the analysis results, generates a voice message using the voice synthesis function, and transmits it to the user or store clerk through the speaker.

[0449] Step 6:

[0450] Emergency response

[0451] If the user or store attendant does not respond within a certain time, the server automatically calls emergency services.

[0452] (Input) Response waiting time and re-detection result

[0453] (Output) The execution status of the emergency call (e.g., "Emergency services called").

[0454] (Specific operation) The server confirms that the pre-set response waiting time has elapsed and automatically sends a notification to emergency contacts (emergency services, family, security company, etc.).

[0455] Through the above processing steps, this system improves the safety and health of users, store staff, and customers, and enables individually tailored support and rapid emergency response.

[0456] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0457] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0458] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0459] [Second embodiment]

[0460] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0461] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0462] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0463] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0464] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0465] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0466] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0467] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0468] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0469] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0470] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0471] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0472] This system receives data from multiple sensors installed in the home and monitors the user's living conditions and health status, and automatically takes appropriate action if an abnormality is detected. This system consists of three main components: a server, a terminal, and the user.

[0473] System Configuration and Operation

[0474] Sensor placement and data collection

[0475] Server: Receives real-time data from various sensors installed in the home (motion sensors, temperature sensors, heart rate sensors, etc.). Each sensor is installed in a different location and collects information on the user's behavior and environment.

[0476] Data analysis

[0477] Server: Analyzes the received sensor data and evaluates whether there is inactivity or abnormal vital signs. For example, if there is inactivity for a certain period of time or if the heart rate is outside the normal range, it is determined to be abnormal.

[0478] The analysis means uses an algorithm that compares the current time with the timestamp sent by the sensor and detects whether there has been a period of inactivity.

[0479] Anomaly detection and user notification

[0480] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The user will respond by voice to confirm that there is no abnormality.

[0481] The device uses voice recognition technology to analyze the user's response and provide appropriate feedback.

[0482] Emergency response

[0483] Server: If the user does not respond within a certain time frame, the server automatically calls emergency services, allowing for a quick response to ensure the user's safety.

[0484] Emergency contact methods send emergency messages to pre-defined contacts (emergency services, family, security companies, etc.).

[0485] Daily support

[0486] Terminal: Providing everyday support through voice interaction. For example, providing appropriate information in response to a user's question such as "What is my schedule for today?"

[0487] The device manages the user's schedule and sets reminders when necessary.

[0488] Specific Examples

[0489] Example 1: Daily support

[0490] 1. User: Says to the device, "What's on my schedule for today?"

[0491] 2. Terminal: Recognizes the user's question and announces in voice, "Your regular checkup will be at 3:00 p.m. today."

[0492] Example 2: Emergency response

[0493] 1. Server: Receives data from sensors and detects inactivity for more than two hours.

[0494] 2. Terminal: The user is prompted with a voice message saying "Please answer. Are you OK?"

[0495] 3. User: No response.

[0496] 4. Server: No response within a certain time, so call emergency services.

[0497] Example 3: Detecting abnormalities in vital signs

[0498] 1. Server: Receives abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[0499] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[0500] 3. Terminal: Notify the user, "Please answer. Are you OK?"

[0501] 4. User: No response.

[0502] 5. Server: Calls emergency services after no response within a certain time.

[0503] As described above, the present invention uses sensors to monitor the living conditions and health status of residents in real time, and responds quickly if an abnormality is detected, thereby providing an environment in which residents can live in peace of mind.

[0504] The processing flow will be explained below.

[0505] Step 1:

[0506] Server: Receives data in real time from various sensors (motion sensor, temperature sensor, heart rate sensor, etc.). The server centrally manages this data and stores it with a timestamp. For example, the server receives data such as "no_movement" from the motion sensor, "60 BPM" from the heart rate sensor, and "22°C" from the temperature sensor.

[0507] Step 2:

[0508] Server: Analyzes the received sensor data and runs algorithms to detect inactivity and abnormal vital signs. Iactivity detection compares the current time with the time of the last detected movement to determine whether the person has been inactive for a certain period of time. It also determines an abnormality if the heart rate is outside the set normal range.

[0509] Step 3:

[0510] Server: If an abnormality is detected based on the analysis results, proceed to the next step. If normal, switch to daily support functions. For example, if a user wants to know "today's schedule," provide appropriate information.

[0511] Step 4:

[0512] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The terminal will use voice recognition technology to analyze the user's response. If the user responds, it will determine that there is no abnormality.

[0513] Step 5:

[0514] Server: If no response is received from the user within a certain time, the server will automatically initiate action to call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[0515] Step 6:

[0516] Server: When calling emergency services, the server attempts to contact the emergency service as quickly as possible using multiple methods (telephone, email, SMS, etc.) and accurately communicates details of the emergency (e.g., "inactivity for more than two hours" or "heart rate below 50 BPM").

[0517] Step 7:

[0518] Terminal: Responds to user requests as a daily support function. When a user says, "Please tell me what's on my schedule for today," the terminal retrieves schedule information from the server and notifies them by voice, "I have a regular checkup at 3:00 p.m. today." It also has a reminder function that notifies users when it's time to take their medication.

[0519] Step 8:

[0520] User: Uses the daily support functions to check their schedule and medication times. Obtains necessary information through appropriate interactions with the device. In an emergency, ensures safety by responding promptly to response confirmation notifications from the device.

[0521] The above are the specific processing steps of the system of the present invention. At each step, the server, terminal, and user work in cooperation to safely and effectively support the lives of residents.

[0522] Example 1

[0523] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0524] Daily health monitoring and rapid response in the event of an abnormality are important for elderly people and residents with health concerns to live with peace of mind. However, conventional systems lack the means to detect abnormalities in real time, notify users through voice dialogue, and automatically take emergency action based on the subsequent response. Furthermore, the functionality to provide continuous support for daily life was also insufficient. This resulted in a delay in appropriate response in the event of an abnormality, posing a risk of not ensuring the safety of users.

[0525] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0526] In this invention, the server includes means for receiving data from multiple sensors installed in the house, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for notifying the user by voice of the detected abnormality, means for calling emergency services if the user does not respond, and means for providing support for daily life in the form of voice dialogue. This allows the user's living situation and health condition to be monitored in real time, and if an abnormality is detected, a prompt response can be made, creating an environment in which the user can live with peace of mind.

[0527] "House" refers to a building for human habitation.

[0528] A "sensor" refers to a device that detects physical or environmental phenomena and collects that information as data.

[0529] "Data" refers to detected information, which is recorded in the form of numbers, character strings, or the like.

[0530] "Means" refers to a method or device used to achieve a particular purpose.

[0531] "Analysis" refers to the process of breaking down and interpreting data in order to evaluate and make judgments.

[0532] "Idle" refers to a period of no movement.

[0533] "Vital signs" refers to vital signs such as heart rate, body temperature, and respiratory rate.

[0534] "User" refers to a person who uses the system.

[0535] "Responding" refers to the user's response to a notification from the system.

[0536] "Emergency services" refers to emergency response agencies and services such as emergency medical services, police, and fire departments.

[0537] "Voice dialogue" refers to two-way communication using voice.

[0538] "Life support" refers to assistance with daily activities and the provision of information.

[0539] This invention is a system that receives data from multiple sensors installed in a home and monitors a user's living conditions and health status. The system consists of three main components: a server, a terminal, and a user. The detailed configuration and operation of the system are described below.

[0540] Sensor placement and data collection

[0541] Server: Receives real-time data from various sensors (e.g., motion sensor, temperature sensor, heart rate sensor) placed in the home. Each sensor is installed in a different location and collects information on the user's behavior and environment.

[0542] Hardware used: Raspberry Pi, Arduino sensors, etc.

[0543] Data analysis

[0544] Server: Analyzes the received sensor data and evaluates whether there is any motion or abnormal vital signs. This analysis is performed using Python, processing the data using Pandas and NumPy.

[0545] For example, if there is no movement for a certain period of time (e.g., 30 minutes) or if the heart rate falls outside a certain range (e.g., 40 BPM or less), it is determined to be abnormal.

[0546] Anomaly detection and notification

[0547] Device: If an abnormality is detected, the device will notify the user by voice, "Please respond. Are you OK?" This notification uses the Google Speech-to-Text API.

[0548] The device uses voice recognition technology to analyze the user's response and confirm that there are no abnormalities.

[0549] Emergency response

[0550] Server: If no response is received from the user within a certain time (e.g., 1 minute), the server automatically calls emergency services. It uses the Twilio API to communicate with the emergency services, sending messages and calls to pre-defined contacts.

[0551] Software used: Twilio API, SMTP server, etc.

[0552] Support for daily life

[0553] Device: Provides daily support through voice interaction. For example, in response to a user question such as "What are your plans for today?", the device retrieves schedule information using the Google Calendar API and sets reminders at the appropriate time.

[0554] Software used: Google Calendar API, Amazon Alexa, etc.

[0555] Specific Examples

[0556] Example 1: Daily support

[0557] 1. User: Say to the device, "What's on my schedule for today?"

[0558] 2. Device: Uses the Google Calendar API to retrieve the schedule for the day and notifies the user via voice message, saying, "Your regular checkup will be at 3:00 p.m. today."

[0559] Example 2: Emergency response

[0560] 1. Server: Receives data from the motion sensor and detects inactivity for more than two hours.

[0561] 2. Device: A voice message will say "Please answer. Are you OK?"

[0562] 3. User: No response.

[0563] 4. Server: No response within 1 minute, so calls emergency services using the Twilio API.

[0564] Example 3: Detecting abnormalities in vital signs

[0565] 1. Server: Receives abnormal heart rate (e.g., below 40 BPM) from the heart rate sensor.

[0566] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[0567] 3. Terminal: Notify "Please answer. Are you OK?"

[0568] 4. User: No response.

[0569] 5. Server: No response within 1 minute, so calls emergency services using the Twilio API.

[0570] In this way, the present invention uses sensors to monitor the living conditions and health status of residents in real time, and by responding quickly if an abnormality is detected, it provides an environment in which residents can live in peace of mind.

[0571] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0572] Step 1: Collect data from sensors

[0573] Server: Receives real-time data from sensors (motion sensors, temperature sensors, heart rate sensors, etc.). The sensors transmit data from each device via Bluetooth or Wi-Fi.

[0574] Input: Measurement data sent from sensors (movement, temperature, heart rate)

[0575] Specific operation: The server receives data from each sensor every second and records it in a database (e.g., MySQL) in chronological order.

[0576] Output: Sensor data stored in a database

[0577] Step 2: Analyze the data

[0578] Server: Analyzes the received sensor data and detects inactivity or abnormal vital signs. This is done using a Python script that processes the data using Pandas and NumPy.

[0579] Input: Sensor data retrieved from a database

[0580] Data processing: A Python script analyzes the data from each sensor and calculates the average, maximum, and minimum values ​​of inactivity time and vital signs.

[0581] Specific operation: If there is no movement for more than 30 minutes or if the heart rate is below 40 BPM, an abnormality flag is raised.

[0582] Output: Analysis results flagged as abnormal

[0583] Step 3: Anomaly detection and notification

[0584] Device: If an abnormality is detected, the device will notify the user by voice, saying, "Please respond. Are you OK?" The user's voice response will be analyzed using the Google Speech-to-Text API.

[0585] Input: Analysis results flagged as abnormal

[0586] Specific operation: The device plays a voice prompt every 10 seconds, collects the user's voice response using the microphone, converts the collected voice into text, and analyzes the response content.

[0587] Output: User response text

[0588] Step 4: Response analysis and feedback

[0589] Server: Analyzes the user's response and verifies that there are no abnormalities. If an abnormality is detected, prepares further countermeasures.

[0590] Input: User response text

[0591] Data calculation: If the response is positive, such as "It's okay," it is determined that there is no abnormality, and if the response is negative or there is no response, an emergency response is prepared.

[0592] Specific operation: The server evaluates the presence and content of the response and decides whether to proceed to the next step or cancel the abnormality alarm.

[0593] Output: Emergency response flag or alarm clear

[0594] Step 5: Emergency response

[0595] Server: If there is no response from the user within a certain time (e.g. 1 minute), automatically call emergency services. Use the Twilio API to call and email emergency contacts.

[0596] Input: Emergency Response Flag

[0597] What it does: The server calls Twilio's API to send an emergency message to pre-defined contacts, including information about the user's inactivity time and abnormal vital signs.

[0598] Output: Notification of emergency message transmission completion

[0599] Step 6: Support for daily living

[0600] Device: Providing daily support through voice interaction. For example, in response to a user's question, "What's on my schedule for today?", the device retrieves schedule information using the Google Calendar API.

[0601] Input: User's voice input (question)

[0602] Data processing: Amazon Alexa analyzes the voice input and calls the Google Calendar API to obtain schedule information.

[0603] Specific operation: The device recognizes the user's question, obtains schedule information, and notifies the user by voice.

[0604] Output: Schedule information announced by voice

[0605] (Application example 1)

[0606] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0607] Conventional home monitoring systems are required to respond quickly and effectively when an abnormality is detected, but they have problems such as being unable to respond appropriately to an emergency situation due to the user's absence or delayed response.In addition, they lack daily support functions, making them less practical as systems that support the user's daily life in general.

[0608] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0609] In this invention, the server includes means for receiving data such as movement, temperature, and heart rate from sensors installed in the house, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for calling emergency services if the user does not respond, means for providing support for daily life in the form of voice dialogue, means for monitoring data from the sensors in real time and sending an alarm notification to the smartphone if an abnormality is detected, means for analyzing the response using voice recognition technology if the user does not respond to the voice notification, and means for automatically making an emergency call if the user does not respond. This ensures the user's safety and enables rapid emergency response, while also providing daily life support functions and improving the user's quality of life.

[0610] A "sensor" is a device that is installed inside a home and collects various data such as movement, temperature, and heart rate.

[0611] The "means for receiving data" refers to a device or program that has the function of acquiring information sent from a sensor and transferring it to a server.

[0612] A "means for analyzing data" is a method or device that statistically or algorithmically processes received data to detect inactivity or abnormal vital signs.

[0613] A "means for calling emergency services" is a device or program that automatically contacts pre-defined emergency contacts if there is no response from the user.

[0614] The "means for providing support for daily life in a voice interactive format" is a device or program for providing information in a voice interactive format in response to a user's questions or requests.

[0615] "Means for real-time monitoring" refers to devices or programs that have the function of instantly acquiring and analyzing data obtained from sensors.

[0616] The "means for sending an alarm notification" is a device or program for issuing a warning to a user's device such as a smartphone when an abnormality is detected.

[0617] The "means for analyzing a response using voice recognition technology" refers to a technology or device for recognizing a user's voice response and analyzing its content.

[0618] The "means for automatically making an emergency contact" is a device or program for automatically contacting a set emergency contact if the user does not respond.

[0619] This invention is a system for monitoring a user's lifestyle and health status and responding quickly when an abnormality is detected. This system consists of three main components: a server, a terminal, and a user. Each of these components is explained in detail below.

[0620] System Configuration and Operation

[0621] 1. Sensor placement and data collection

[0622] The server receives real-time data from various sensors installed in the home (motion sensors, temperature sensors, heart rate sensors, etc.). Each sensor is installed in a different location and collects information on the user's behavior and environment.

[0623] 2. Data Analysis

[0624] The server analyzes the received sensor data and determines if there is an abnormality if there is no movement for a certain period of time or if the heart rate is outside the normal range. The analysis method includes an algorithm that compares the current time with the timestamp sent from the sensor to detect whether there has been a prolonged period of no movement.

[0625] 3. Anomaly detection and user notification

[0626] If an abnormality is detected, the device will notify the user by voice, saying, "Please respond. Are you OK?" This uses voice recognition technology to analyze the user's response and provide appropriate feedback. The main interfaces include smartphones and headsets.

[0627] 4. Emergency Response

[0628] If the server does not receive a response from the user within a certain time, it will call emergency services and send an emergency message to pre-defined contacts (emergency services, family, security companies, etc.).

[0629] 5. Daily support

[0630] The device provides daily support through voice interaction. For example, in response to a user's question such as "What is your schedule for today?", the device will respond by voice with "Your regular checkup will be at 3:00 p.m. today."

[0631] Specific examples of the technology

[0632] Example 1: Daily support

[0633] 1. The user speaks to the device, "What are your plans for today?"

[0634] 2. The device recognizes the user's question and provides appropriate information by voice.

[0635] Example 2: Emergency response

[0636] 1. The server receives data from the sensor and detects anomalies, such as inactivity for more than two hours.

[0637] 2. The terminal notifies the user, "Please answer. Are you OK?"

[0638] 3. If the user does not respond, the server will recognize that there has been no response within a certain time and will call emergency services.

[0639] Example 3: Detecting abnormalities in vital signs

[0640] 1. The server receives an abnormal heart rate from the heart rate sensor, for example, a value below 50 BPM.

[0641] 2. The server analyzes the abnormality and determines that a prompt response is required.

[0642] 3. The terminal notifies the user, "Please answer. Are you OK?"

[0643] 4. If the user does not respond, the server will automatically contact an emergency number.

[0644] Technology and software used

[0645] Hardware: sensors (motion sensors, temperature sensors, heart rate sensors, etc.), smartphones, headsets

[0646] Software: Sensor app SDK, speech recognition API (Google Speech-to-Text, Apple SiriKit), data analysis algorithm

[0647] Prompt Sentence Examples

[0648] When you receive the notification "Please respond. Are you OK?", generate a program that analyzes the user's response using a speech recognition API and provides appropriate feedback.

[0649] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0650] Step 1:

[0651] Sensor data collection

[0652] The server receives real-time data from motion sensors, temperature sensors, heart rate sensors, etc. installed inside the home.

[0653] Input: Data sent from sensors, such as movement, temperature, and heart rate.

[0654] Output: Sensor data stored on the server.

[0655] Specific operation: The server receives the data sent from each sensor along with the time stamp and stores the data in a database.

[0656] Step 2:

[0657] Data analysis

[0658] The server analyzes the received data and evaluates whether there has been a period of inactivity or abnormal vital signs.

[0659] Input: Sensor data stored on the server.

[0660] Output: Result of normal / abnormal condition.

[0661] What it does: The server compares the current time with the timestamp sent by the sensor and runs algorithms to detect if there has been a period of inactivity or if the heart rate is outside of the normal range.

[0662] Step 3:

[0663] Anomaly detection and user notification

[0664] If an abnormality is detected, the terminal will notify the user by voice, saying, "Please respond. Are you OK?"

[0665] Input: Abnormal notification from the server.

[0666] Output: Audio notification to the user.

[0667] Specific operation: When an abnormality is detected, the device uses a voice recognition API to issue a message prompting the user to respond.

[0668] Step 4:

[0669] User response analysis

[0670] The device uses voice recognition technology to analyze the user's response and check for any abnormalities.

[0671] Input: The user's spoken response.

[0672] Output: Parsed response.

[0673] Specific operation: Uses a speech recognition API (e.g., Google Speech-to-Text or Apple SiriKit) to convert the user's voice response into text and analyze its content.

[0674] Step 5:

[0675] Emergency response

[0676] The server calls emergency services if no response is received from the user within a certain time.

[0677] Input: Parsed response result.

[0678] Output: Emergency contact is made.

[0679] Specific behavior: If there is no response from the user within a certain period of time, the server will automatically contact pre-defined emergency contacts (e.g., emergency services or family members) and report the emergency situation.

[0680] Step 6:

[0681] Daily support

[0682] The terminal provides daily support to the user in the form of voice dialogue.

[0683] Input: The user's voice command.

[0684] Output: Audio feedback.

[0685] Specific operation: When a user speaks to the device, for example, "Please tell me what my schedule is for today," the device processes the question using a voice recognition API and responds with appropriate information (such as the schedule) via voice.

[0686] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0687] This system receives data from multiple sensors installed in the home, monitors the user's living situation and health status, and automatically takes appropriate action if an abnormality is detected. The system is combined with an emotion engine that recognizes the user's emotions and adjusts daily support, enabling more personalized responses. The system consists of three main components: a server, a terminal, and the user.

[0688] System Configuration and Operation

[0689] Sensor placement and data collection

[0690] Server: Receives data in real time from various sensors installed in the house (motion sensor, temperature sensor, heart rate sensor, etc.). The server centrally manages this data and stores it with a timestamp. For example, the server receives data such as "no_movement" from the motion sensor, "60 BPM" from the heart rate sensor, and "22°C" from the temperature sensor.

[0691] Data analysis

[0692] Server: Analyzes the received sensor data and runs algorithms to detect inactivity and abnormal vital signs. Iactivity detection compares the current time with the time of the last detected movement to determine whether the person has been inactive for a certain period of time. It also determines an abnormality if the heart rate is outside the set normal range.

[0693] Anomaly detection and user notification

[0694] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The terminal will use voice recognition technology and an emotion engine to analyze the user's response and evaluate their emotional state. If the user responds, it will determine that there is no abnormality and provide feedback according to their emotional state.

[0695] Emergency response

[0696] Server: If no response is received from the user within a certain time, the server will automatically initiate action to call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[0697] Daily support

[0698] Terminal: Provides daily support through voice dialogue. For example, responds to user questions such as "What are your plans for today?" with appropriate information. Analyzes the user's emotions using an emotion engine and adjusts the support content according to their emotional state.

[0699] Specific Examples

[0700] Example 1: Daily support

[0701] 1. User: Says to the device, "What's on my schedule for today?"

[0702] 2. Device: Recognizes the user's question and uses an emotion engine to analyze the tone and pace of the user's voice. If it determines that the user is stressed, it notifies the user, "You have a regular checkup at 3 PM today, but we recommend that you take some time to relax." If the user is in a normal state, it notifies the user, "You have a regular checkup at 3 PM today."

[0703] Example 2: Emergency response

[0704] 1. Server: Receives data from sensors and detects inactivity for more than two hours.

[0705] 2. Terminal: Notifies the user by voice, "Please respond. Are you OK?". Analyzes the user's response using the emotion engine to determine their emotional state.

[0706] 3. User: No response.

[0707] 4. Server: No response within a certain time, so call emergency services.

[0708] Example 3: Detecting abnormalities in vital signs

[0709] 1. Server: Receives abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[0710] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[0711] 3. Terminal: Notifies the user, "Please respond. Are you OK?". Analyzes the user's response using the emotion engine to determine their emotional state.

[0712] 4. User: No response.

[0713] 5. Server: Calls emergency services after no response within a certain time.

[0714] Example 4: Daily support based on emotional state

[0715] 1. User: Says to the device, "I'm feeling a little tired today."

[0716] 2. Terminal: Recognizes the user's speech and analyzes the user's level of fatigue using an emotion engine.

[0717] 3. Device: Notify: "Would you like to schedule more time for relaxation today?"

[0718] As described above, the system of the present invention uses sensors to monitor the living conditions and health status of residents in real time, and by combining it with an emotion engine, it individualizes responses when abnormalities are detected and daily support, providing an environment in which users can live with peace of mind.

[0719] The processing flow will be explained below.

[0720] Step 1:

[0721] Server: Receives data from various sensors (motion sensor, temperature sensor, heart rate sensor, etc.) in real time and stores it with a timestamp. For example, it receives data such as "Motion sensor: no_movement", "Heart rate sensor: 60 BPM", and "Temperature sensor: 22°C".

[0722] Step 2:

[0723] Server: Analyzes the received sensor data. To detect inactivity, it compares the current time with the time of the last detected movement to determine whether there has been inactivity for a certain period of time. It also determines that there is an abnormality if the heart rate is outside the set normal range.

[0724] Step 3:

[0725] Server: If an abnormality is detected based on the analysis results, proceed to the next step. If the condition is normal, switch to the daily support function. For example, if the user wants to know "today's schedule," provide schedule information.

[0726] Step 4:

[0727] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?". The emotion engine will analyze the user's response and evaluate their emotional state. If the user responds, it will be determined that there is no abnormality.

[0728] Step 5:

[0729] Server: If the user does not respond within a certain time frame, the server automatically calls emergency services, which can include pre-defined contacts (ambulance services, family, security companies, etc.).

[0730] Step 6:

[0731] Server: When calling emergency services, the server attempts to contact the emergency service as quickly as possible using multiple methods (telephone, email, SMS, etc.) and accurately communicates details of the emergency (e.g., "inactivity for more than two hours" or "heart rate below 50 BPM").

[0732] Step 7:

[0733] Terminal: Responds to user requests as a daily support function. When a user says, "Tell me what's on my schedule for today," the terminal retrieves schedule information from the server and notifies them by voice.

[0734] Step 8:

[0735] Emotion engine: Analyzes the tone, pace, and intonation of the user's voice to assess their emotional state. For example, if it determines that the user is stressed, it will offer advice on how to relax.

[0736] Step 9:

[0737] Device: Adjust daily support based on the results of the emotion engine. For example, if a user says, "I'm a little tired today," the device will notify them, "When adjusting your schedule for today, would you like us to suggest more time for relaxation?"

[0738] Step 10:

[0739] User: Use the daily support features to check their schedule and medication times. For example, they can say, "What's my schedule for today?" and receive notifications from the device. They can also respond to notifications from the device in the event of an emergency.

[0740] Specific Examples

[0741] Example 1: Daily support

[0742] Step 1: The user speaks to the device, "What's on my schedule for today?"

[0743] Step 2: The device recognizes the user's question and uses an emotion engine to analyze the tone and pace of the user's voice.

[0744] Step 8: If the device determines that the user is stressed, it notifies the user, "You have a regular checkup at 3 PM today, but we recommend that you take some time to relax." If the user is in a normal state, it notifies the user, "You have a regular checkup at 3 PM today."

[0745] Example 2: Emergency response

[0746] Step 1: The server receives data from the sensors and detects inactivity for more than two hours.

[0747] Step 4: The device notifies the user by voice, "Please respond. Are you OK?" The emotion engine analyzes the user's response and determines their emotional state.

[0748] Step 5: The user does not respond.

[0749] Step 6: The server does not respond within a certain time, so emergency services are called.

[0750] Example 3: Detecting abnormalities in vital signs

[0751] Step 1: The server receives an abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[0752] Step 2: The server analyzes the anomaly and determines that emergency action is required.

[0753] Step 4: The device notifies the user, "Please respond. Are you OK?" The emotion engine analyzes the user's response and determines their emotional state.

[0754] Step 5: The user does not respond.

[0755] Step 6: The server does not respond within a certain time, so emergency services are called.

[0756] Example 4: Daily support based on emotional state

[0757] Step 1: The user says to the device, "I'm feeling a little tired today."

[0758] Step 8: The device recognizes the user's speech and uses an emotion engine to analyze the user's level of fatigue.

[0759] Step 9: Your device will notify you, "Would you like us to suggest more time for relaxation for your schedule today?"

[0760] The above are the specific processing steps of the system of the present invention. At each step, the server, terminal, and user work in cooperation to safely and effectively support the lives of residents.

[0761] Example 2

[0762] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0763] In modern residential environments, there is a need to understand the living conditions and health status of residents in real time and respond quickly when abnormalities occur, but conventional systems have difficulty meeting these requirements. Furthermore, when it comes to supporting users' daily lives, they lack the ability to respond in detail to individual situations and emotions. Therefore, providing an environment where residents can live with peace of mind has become a challenge.

[0764] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving data such as movement, temperature, and heart rate from sensors installed in the house; means for centrally managing the received data and saving it with a timestamp; means for analyzing the received data and detecting inactivity or abnormal vital signs; means for issuing a voice notification when an abnormality is detected and analyzing the user's response using an emotion engine; means for calling emergency services when there is no response from the user; and means for providing support for daily life in the form of voice dialogue and using the emotion engine to provide support according to the user's emotional state. This makes it possible to provide an environment in which the user can live with peace of mind by monitoring the user's living situation and health condition in real time and taking necessary measures promptly.

[0765] A "sensor" is a device that is installed inside a home and collects data such as movement, temperature, and heart rate.

[0766] A "centralized management system" is a system that manages received data in one place and stores it with a timestamp.

[0767] The "analysis means" is a function that uses the received data to execute an algorithm for detecting immobility or abnormal vital signs.

[0768] An "emotion engine" is a technology that analyzes a user's emotional state and determines the appropriate response based on that.

[0769] "Emergency services" are contacts that are automatically contacted if there is no response from the user, and include ambulance services, family, security companies, etc.

[0770] "Voice notification" is a function that notifies the user by voice when an abnormality is detected.

[0771] "Voice interaction" refers to a format in which information is exchanged between a user and a system using voice.

[0772] MODE FOR CARRYING OUT THE INVENTION

[0773] This invention is a system that monitors the user's living situation and health status based on data from sensors installed in the home, and automatically responds if an abnormality is detected. This system consists of three main components: a server, a terminal, and the user.

[0774] Hardware or software used

[0775] The main hardware and software required to implement this system are as follows:

[0776] 1. Sensors: Multiple types of sensors, such as motion sensors, temperature sensors, heart rate sensors, etc.

[0777] 2. Server: A central device that receives, analyzes, stores, detects anomalies, and handles emergency responses.

[0778] 3. Terminal: A device that provides voice notifications, voice interaction, emotion engine analysis, and support for daily life.

[0779] Data processing and calculation

[0780] 1. Data Collection:

[0781] The server receives real-time data such as temperature and heart rate from various sensors installed inside the home and stores it in a centralized management system with a timestamp.

[0782] 2. Data Analysis:

[0783] The server runs an analysis algorithm based on the received data to detect inactivity or abnormal vital signs. To detect inactivity, it compares the current time with the time of the last detected movement and determines whether the person has been inactive for a certain period of time (e.g., two hours). It also determines an abnormality if the heart rate exceeds a set range (e.g., 50 BPM to 100 BPM).

[0784] 3. User response analysis:

[0785] The device has a means for issuing a voice notification when an abnormality is detected, and uses an emotion engine to analyze the user's response and evaluate their emotional state. For example, if the user responds "Yes, I'm fine," the emotion engine evaluates whether the user is calm.

[0786] 4. Emergency Response:

[0787] The server has a mechanism to automatically call emergency services if no response is received from the user within a certain time (e.g., 5 minutes), and has the ability to contact pre-defined contacts (e.g., emergency services, family, security companies, etc.).

[0788] 5. Daily support:

[0789] The device provides support for the user's daily life through voice dialogue, and uses an emotion engine to provide appropriate information according to the user's emotional state. For example, if a user says, "What are your plans for today?", the emotion engine analyzes the tone and pace of the user's voice. If it determines that the user is stressed, it will notify the user, "You have a regular checkup at 3:00 p.m. today, but we recommend that you take some time to relax."

[0790] Prompt Sentence Examples

[0791] Examples of prompts to input to a generative AI model include:

[0792] "Analyze the data from the sensors and explain how you will respond if there are any abnormalities."

[0793] "Recognize the user's emotions and tell me how to provide support based on those emotions."

[0794] The system of the present invention, which includes the above functions, makes it possible to monitor a user's living situation and health condition in real time and take necessary measures quickly, thereby providing an environment in which the user can live with peace of mind.

[0795] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0796] Step 1: Collect sensor data

[0797] The server receives real-time data from sensors installed in the home, such as movement, temperature, and heart rate. The input is the data sent from each sensor (e.g., "no_movement," "22°C," "60 BPM"), and the output is to store this data with a timestamp in a centralized management system. Specifically, the sensors send their measurements to the server, which receives the data and stores it in a database.

[0798] Step 2: Analyze the data

[0799] The server analyzes the collected data. The input is the stored sensor data with a timestamp, and the output is the detection of inactivity or abnormal vital signs. Specifically, the server compares the timestamps of the motion sensor data and checks whether inactivity has continued for a certain period of time (for example, two hours). It also analyzes whether the heart rate data is within a set range (50 BPM to 100 BPM).

[0800] Step 3: Anomaly detection

[0801] The server detects abnormalities based on the analysis results. The input is the analyzed data, and the output is information that an abnormality has been detected. Specifically, if inactivity or an abnormal heart rate is detected, the server records that information and determines that this is an abnormal condition that requires proceeding to the next processing step.

[0802] Step 4: User Notification

[0803] If an abnormality is detected, the device will notify the user by voice. The input is notification data from the server indicating the abnormality, and the output is the voice notification and a response from the user. Specifically, the device will notify by voice, "Please respond. Are you OK?", receive the user's response via the microphone, convert it into text data, and pass it to the emotion engine.

[0804] Step 5: User response analysis

[0805] The device uses an emotion engine to analyze the user's response. The input is text data converted from the user's voice response, and the output is the user's emotional state. Specifically, the device inputs the text data analyzed from the voice into the emotion engine, which evaluates whether the user is calm or stressed.

[0806] Step 6: Emergency response

[0807] If the server does not receive a response from the user within a certain time (e.g., 5 minutes), it automatically calls emergency services. The input is the user's no-response information, and the output is a call to emergency services. Specifically, the server automatically calls and sends messages to pre-defined contacts (e.g., 119, family, security company).

[0808] Step 7: Daily support

[0809] The device provides support for daily life through voice dialogue. The input is questions or requests from the user, and the output is appropriate information or advice. In concrete terms, when a user says, "What are your plans for today?", the device uses an emotion engine to analyze the tone and pace of the user's voice and assess whether they are feeling stressed. If they are feeling stressed, the device will notify them, "You have a regular checkup at 3:00 PM today, but we recommend that you take some time to relax," and if they are feeling normal, it will notify them, "You have a regular checkup at 3:00 PM today."

[0810] As described above, by performing specific data processing or calculations based on the input data at each step and passing the output to the next step, it is possible to monitor the user's living situation and health condition in real time and take any necessary measures quickly.

[0811] (Application example 2)

[0812] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0813] In modern living environments and brick-and-mortar stores, real-time monitoring systems for the health and safety of residents, store staff, and customers are important, but current technology often cannot adequately address these issues. There is a particular need for emergency response and daily life support that is tailored to each individual. In addition to monitoring, there is also a need for personalized responses using emotion engines.

[0814] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0815] In this invention, the server includes means for receiving data such as movement, temperature, and heart rate from sensors installed in the home or store, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for calling emergency services if there is no response from the user, means for providing support for daily life in the form of voice dialogue, means for receiving data from sensors installed in the store and monitoring the behavior of store staff and customers, means for analyzing the received data to detect abnormalities and notifying store staff, and means for analyzing and evaluating the emotions of store staff using an emotion engine along with responses.This improves the safety and health of users, store staff, and customers, and enables individually tailored support and emergency responses.

[0816] "Sensors installed inside the home" refers to various sensors installed inside the home, which are devices for collecting data such as movement, temperature, and heart rate.

[0817] A "motion sensor" is a sensor used to detect motion and to monitor inactivity.

[0818] A "temperature sensor" is a sensor for detecting the ambient temperature and for monitoring changes in the temperature of the environment.

[0819] A "heart rate sensor" is a sensor that measures an individual's heart rate and is used to monitor vital signs.

[0820] A "means for receiving data" is a method or device for acquiring data sent from a sensor.

[0821] A "means for analyzing data" is a method or device for processing received data and detecting abnormal conditions or patterns.

[0822] "Means for invoking emergency services" means a method or device for notifying emergency services or relevant authorities when an abnormality is detected and there is no response from the user.

[0823] The "means for providing in the form of voice interaction" refers to a method or device for interacting with a user using voice to provide support for daily life.

[0824] "Sensors installed in stores" refer to various sensors installed in commercial facilities, and are devices for monitoring the movements and status of store staff and customers.

[0825] An "emotion engine" is an algorithm or device that analyzes the emotional state of users and store clerks and makes appropriate evaluations.

[0826] The "means for notifying a store clerk" is a method or device for notifying a store clerk when an abnormality is detected.

[0827] "Means for analyzing and evaluating emotions" refers to a method or device for analyzing and evaluating the emotional state of a user or store clerk.

[0828] This invention is a system that receives data from multiple sensors installed in homes and stores, monitors the user's living situation and health status, and automatically takes appropriate action if an abnormality is detected. Furthermore, by combining it with an emotion engine, it can recognize the emotions of users, store clerks, and customers and provide individually tailored daily support and emergency responses.

[0829] Hardware and Software Configuration

[0830] 1. Sensor System

[0831] Various sensors (such as motion sensors, temperature sensors, and heart rate sensors) are placed in homes and stores to monitor the environment and personal vital signs in real time.

[0832] 2. Server

[0833] The server receives and centralizes data from various sensors, stores it with a timestamp, analyzes the data, and runs algorithms to detect inactivity or abnormal vital signs. If an abnormality is detected, the server can call emergency services as an appropriate response.

[0834] 3. Terminal

[0835] The terminal provides daily support to users and store staff through voice interaction, utilizing voice recognition technology (e.g., Google Speech-to-Text API) and emotion engines (e.g., Emotion API) to analyze the user's responses and emotional state and provide appropriate feedback.

[0836] System Operation

[0837] Receiving and storing data

[0838] The server receives real-time data from each sensor in a home or store and manages it centrally. For example, it receives data such as "no_movement" from a motion sensor, "22°C" from a temperature sensor, and "60 BPM" from a heart rate sensor. This data is saved with a timestamp.

[0839] Data analysis and anomaly detection

[0840] The server analyzes the received data and detects an abnormality, for example, if the device is inactive for a certain period of time or if the heart rate is outside the normal range.

[0841] Notification and Response

[0842] If an abnormality is detected, the device will notify the user or store clerk by voice, saying, "Please respond. Are you OK?" The device will use an emotion engine to analyze the user's or store clerk's response and evaluate their emotional state. If the user or store clerk responds, it will provide appropriate feedback based on their response.

[0843] Emergency response

[0844] If no response is received from the user or store staff within a certain time frame, the server will automatically call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[0845] Specific examples

[0846] When a user says to the device, "I feel a little tired today," the device will recognize the voice, analyze the user's level of fatigue using an emotion engine, and notify them, "Would you like us to suggest that you increase your relaxation time when adjusting your schedule for today?"

[0847] If the store's motion sensors detect inactivity for more than two hours, the device will issue a voice message saying, "Please respond. Are you OK?" and will call emergency services if there is no response.

[0848] Prompt Sentence Examples

[0849] "How can we build a system that uses data from sensors in the home to monitor the user's health and take appropriate action if an abnormality is detected?"

[0850] As a result, this system improves the safety and health of users, store staff, and customers, and enables individually tailored support and rapid emergency response.

[0851] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0852] Step 1:

[0853] Receiving data

[0854] The server receives data in real time from various sensors (motion sensors, temperature sensors, heart rate sensors, etc.) installed in homes and stores.

[0855] (Input) Data from each sensor (e.g., movement sensor -> "no_movement", temperature sensor -> "22°C", heart rate sensor -> "60BPM")

[0856] (Output) Sensor data with timestamp

[0857] (Specific operation) The server receives data sent from each sensor through the interface and stores the data in a centralized database with a timestamp.

[0858] Step 2:

[0859] Data analysis

[0860] The server analyzes the received sensor data and executes algorithms to detect abnormal conditions, such as inactivity or abnormal vital signs.

[0861] (Input) Time-stamped sensor data

[0862] (Output) Anomaly detection result (e.g., "Normal", "Abnormal", "No operation", etc.)

[0863] (Specific operation) The server analyzes the sensor data using a preset anomaly detection algorithm (for example, determining periods of inactivity) and determines whether an anomaly has occurred.

[0864] Step 3:

[0865] Abnormal notification

[0866] If an abnormality is detected, the server sends a notification to the terminal, which then issues a voice message to the user or store clerk saying, "Please respond. Are you OK?"

[0867] (Input) Anomaly detection results

[0868] (Output) The execution status of the voice notification (e.g., "Notification sent").

[0869] (Specific Operation) When an abnormality is notified from the server, the terminal uses its voice synthesis function to generate a voice message and notifies the user or store clerk through the speaker.

[0870] Step 4:

[0871] User Response and Sentiment Analysis

[0872] When a user or a store clerk responds to the terminal, the terminal uses voice recognition technology to convert the response into text data and uses an emotion engine to analyze the emotion.

[0873] (Input) User or store clerk's voice response

[0874] (Output) Analyzed emotional state (e.g., "stressed," "normal," etc.)

[0875] (Specific operation) The device uses voice recognition technology such as the Google Speech-to-Text API to convert speech into text, and then inputs the text data into the Emotion API to analyze the emotional state.

[0876] Step 5:

[0877] Providing feedback

[0878] Based on the analysis results, the terminal provides appropriate feedback to the user or store clerk via voice.

[0879] (Input) Analyzed emotional state

[0880] (Output) Feedback message (e.g. "Relax" or "Everything is fine")

[0881] (Specific operation) The terminal selects a feedback message based on the analysis results, generates a voice message using the voice synthesis function, and transmits it to the user or store clerk through the speaker.

[0882] Step 6:

[0883] Emergency response

[0884] If the user or store attendant does not respond within a certain time, the server automatically calls emergency services.

[0885] (Input) Response waiting time and re-detection result

[0886] (Output) The execution status of the emergency call (e.g., "Emergency services called").

[0887] (Specific operation) The server confirms that the pre-set response waiting time has elapsed and automatically sends a notification to emergency contacts (emergency services, family, security company, etc.).

[0888] Through the above processing steps, this system improves the safety and health of users, store staff, and customers, and enables individually tailored support and rapid emergency response.

[0889] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0890] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0891] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0892] [Third embodiment]

[0893] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0894] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0895] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0896] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0897] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0898] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0899] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0900] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0901] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0902] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0903] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0904] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0905] This system receives data from multiple sensors installed in the home and monitors the user's living conditions and health status, and automatically takes appropriate action if an abnormality is detected. This system consists of three main components: a server, a terminal, and the user.

[0906] System Configuration and Operation

[0907] Sensor placement and data collection

[0908] Server: Receives real-time data from various sensors installed in the home (motion sensors, temperature sensors, heart rate sensors, etc.). Each sensor is installed in a different location and collects information on the user's behavior and environment.

[0909] Data analysis

[0910] Server: Analyzes the received sensor data and evaluates whether there is inactivity or abnormal vital signs. For example, if there is inactivity for a certain period of time or if the heart rate is outside the normal range, it is determined to be abnormal.

[0911] The analysis means uses an algorithm that compares the current time with the timestamp sent by the sensor and detects whether there has been a period of inactivity.

[0912] Anomaly detection and user notification

[0913] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The user will respond by voice to confirm that there is no abnormality.

[0914] The device uses voice recognition technology to analyze the user's response and provide appropriate feedback.

[0915] Emergency response

[0916] Server: If the user does not respond within a certain time frame, the server automatically calls emergency services, allowing for a quick response to ensure the user's safety.

[0917] Emergency contact methods send emergency messages to pre-defined contacts (emergency services, family, security companies, etc.).

[0918] Daily support

[0919] Terminal: Providing everyday support through voice interaction. For example, providing appropriate information in response to a user's question such as "What is my schedule for today?"

[0920] The device manages the user's schedule and sets reminders when necessary.

[0921] Specific Examples

[0922] Example 1: Daily support

[0923] 1. User: Says to the device, "What's on my schedule for today?"

[0924] 2. Terminal: Recognizes the user's question and announces in voice, "Your regular checkup will be at 3:00 p.m. today."

[0925] Example 2: Emergency response

[0926] 1. Server: Receives data from sensors and detects inactivity for more than two hours.

[0927] 2. Terminal: The user is prompted with a voice message saying "Please answer. Are you OK?"

[0928] 3. User: No response.

[0929] 4. Server: No response within a certain time, so call emergency services.

[0930] Example 3: Detecting abnormalities in vital signs

[0931] 1. Server: Receives abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[0932] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[0933] 3. Terminal: Notify the user, "Please answer. Are you OK?"

[0934] 4. User: No response.

[0935] 5. Server: Calls emergency services after no response within a certain time.

[0936] As described above, the present invention uses sensors to monitor the living conditions and health status of residents in real time, and responds quickly if an abnormality is detected, thereby providing an environment in which residents can live in peace of mind.

[0937] The processing flow will be explained below.

[0938] Step 1:

[0939] Server: Receives data in real time from various sensors (motion sensor, temperature sensor, heart rate sensor, etc.). The server centrally manages this data and stores it with a timestamp. For example, the server receives data such as "no_movement" from the motion sensor, "60 BPM" from the heart rate sensor, and "22°C" from the temperature sensor.

[0940] Step 2:

[0941] Server: Analyzes the received sensor data and runs algorithms to detect inactivity and abnormal vital signs. Iactivity detection compares the current time with the time of the last detected movement to determine whether the person has been inactive for a certain period of time. It also determines an abnormality if the heart rate is outside the set normal range.

[0942] Step 3:

[0943] Server: If an abnormality is detected based on the analysis results, proceed to the next step. If normal, switch to daily support functions. For example, if a user wants to know "today's schedule," provide appropriate information.

[0944] Step 4:

[0945] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The terminal will use voice recognition technology to analyze the user's response. If the user responds, it will determine that there is no abnormality.

[0946] Step 5:

[0947] Server: If no response is received from the user within a certain time, the server will automatically initiate action to call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[0948] Step 6:

[0949] Server: When calling emergency services, the server attempts to contact the emergency service as quickly as possible using multiple methods (telephone, email, SMS, etc.) and accurately communicates details of the emergency (e.g., "inactivity for more than two hours" or "heart rate below 50 BPM").

[0950] Step 7:

[0951] Terminal: Responds to user requests as a daily support function. When a user says, "Please tell me what's on my schedule for today," the terminal retrieves schedule information from the server and notifies them by voice, "I have a regular checkup at 3:00 p.m. today." It also has a reminder function that notifies users when it's time to take their medication.

[0952] Step 8:

[0953] User: Uses the daily support functions to check their schedule and medication times. Obtains necessary information through appropriate interactions with the device. In an emergency, ensures safety by responding promptly to response confirmation notifications from the device.

[0954] The above are the specific processing steps of the system of the present invention. At each step, the server, terminal, and user work in cooperation to safely and effectively support the lives of residents.

[0955] Example 1

[0956] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0957] Daily health monitoring and rapid response in the event of an abnormality are important for elderly people and residents with health concerns to live with peace of mind. However, conventional systems lack the means to detect abnormalities in real time, notify users through voice dialogue, and automatically take emergency action based on the subsequent response. Furthermore, the functionality to provide continuous support for daily life was also insufficient. This resulted in a delay in appropriate response in the event of an abnormality, posing a risk of not ensuring the safety of users.

[0958] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0959] In this invention, the server includes means for receiving data from multiple sensors installed in the house, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for notifying the user by voice of the detected abnormality, means for calling emergency services if the user does not respond, and means for providing support for daily life in the form of voice dialogue. This allows the user's living situation and health condition to be monitored in real time, and if an abnormality is detected, a prompt response can be made, creating an environment in which the user can live with peace of mind.

[0960] "House" refers to a building for human habitation.

[0961] A "sensor" refers to a device that detects physical or environmental phenomena and collects that information as data.

[0962] "Data" refers to detected information, which is recorded in the form of numbers, character strings, or the like.

[0963] "Means" refers to a method or device used to achieve a particular purpose.

[0964] "Analysis" refers to the process of breaking down and interpreting data in order to evaluate and make judgments.

[0965] "Idle" refers to a period of no movement.

[0966] "Vital signs" refers to vital signs such as heart rate, body temperature, and respiratory rate.

[0967] "User" refers to a person who uses the system.

[0968] "Responding" refers to the user's response to a notification from the system.

[0969] "Emergency services" refers to emergency response agencies and services such as emergency medical services, police, and fire departments.

[0970] "Voice dialogue" refers to two-way communication using voice.

[0971] "Life support" refers to assistance with daily activities and the provision of information.

[0972] This invention is a system that receives data from multiple sensors installed in a home and monitors a user's living conditions and health status. The system consists of three main components: a server, a terminal, and a user. The detailed configuration and operation of the system are described below.

[0973] Sensor placement and data collection

[0974] Server: Receives real-time data from various sensors (e.g., motion sensor, temperature sensor, heart rate sensor) placed in the home. Each sensor is installed in a different location and collects information on the user's behavior and environment.

[0975] Hardware used: Raspberry Pi, Arduino sensors, etc.

[0976] Data analysis

[0977] Server: Analyzes the received sensor data and evaluates whether there is any motion or abnormal vital signs. This analysis is performed using Python, processing the data using Pandas and NumPy.

[0978] For example, if there is no movement for a certain period of time (e.g., 30 minutes) or if the heart rate falls outside a certain range (e.g., 40 BPM or less), it is determined to be abnormal.

[0979] Anomaly detection and notification

[0980] Device: If an abnormality is detected, the device will notify the user by voice, "Please respond. Are you OK?" This notification uses the Google Speech-to-Text API.

[0981] The device uses voice recognition technology to analyze the user's response and confirm that there are no abnormalities.

[0982] Emergency response

[0983] Server: If no response is received from the user within a certain time (e.g., 1 minute), the server automatically calls emergency services. It uses the Twilio API to communicate with the emergency services, sending messages and calls to pre-defined contacts.

[0984] Software used: Twilio API, SMTP server, etc.

[0985] Support for daily life

[0986] Device: Provides daily support through voice interaction. For example, in response to a user question such as "What are your plans for today?", the device retrieves schedule information using the Google Calendar API and sets reminders at the appropriate time.

[0987] Software used: Google Calendar API, Amazon Alexa, etc.

[0988] Specific Examples

[0989] Example 1: Daily support

[0990] 1. User: Say to the device, "What's on my schedule for today?"

[0991] 2. Device: Uses the Google Calendar API to retrieve the schedule for the day and notifies the user via voice message, saying, "Your regular checkup will be at 3:00 p.m. today."

[0992] Example 2: Emergency response

[0993] 1. Server: Receives data from the motion sensor and detects inactivity for more than two hours.

[0994] 2. Device: A voice message will say "Please answer. Are you OK?"

[0995] 3. User: No response.

[0996] 4. Server: No response within 1 minute, so calls emergency services using the Twilio API.

[0997] Example 3: Detecting abnormalities in vital signs

[0998] 1. Server: Receives abnormal heart rate (e.g., below 40 BPM) from the heart rate sensor.

[0999] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[1000] 3. Terminal: Notify "Please answer. Are you OK?"

[1001] 4. User: No response.

[1002] 5. Server: No response within 1 minute, so calls emergency services using the Twilio API.

[1003] In this way, the present invention uses sensors to monitor the living conditions and health status of residents in real time, and by responding quickly if an abnormality is detected, it provides an environment in which residents can live in peace of mind.

[1004] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1005] Step 1: Collect data from sensors

[1006] Server: Receives real-time data from sensors (motion sensors, temperature sensors, heart rate sensors, etc.). The sensors transmit data from each device via Bluetooth or Wi-Fi.

[1007] Input: Measurement data sent from sensors (movement, temperature, heart rate)

[1008] Specific operation: The server receives data from each sensor every second and records it in a database (e.g., MySQL) in chronological order.

[1009] Output: Sensor data stored in a database

[1010] Step 2: Analyze the data

[1011] Server: Analyzes the received sensor data and detects inactivity or abnormal vital signs. This is done using a Python script that processes the data using Pandas and NumPy.

[1012] Input: Sensor data retrieved from a database

[1013] Data processing: A Python script analyzes the data from each sensor and calculates the average, maximum, and minimum values ​​of inactivity time and vital signs.

[1014] Specific operation: If there is no movement for more than 30 minutes or if the heart rate is below 40 BPM, an abnormality flag is raised.

[1015] Output: Analysis results flagged as abnormal

[1016] Step 3: Anomaly detection and notification

[1017] Device: If an abnormality is detected, the device will notify the user by voice, saying, "Please respond. Are you OK?" The user's voice response will be analyzed using the Google Speech-to-Text API.

[1018] Input: Analysis results flagged as abnormal

[1019] Specific operation: The device plays a voice prompt every 10 seconds, collects the user's voice response using the microphone, converts the collected voice into text, and analyzes the response content.

[1020] Output: User response text

[1021] Step 4: Response analysis and feedback

[1022] Server: Analyzes the user's response and verifies that there are no abnormalities. If an abnormality is detected, prepares further countermeasures.

[1023] Input: User response text

[1024] Data calculation: If the response is positive, such as "It's okay," it is determined that there is no abnormality, and if the response is negative or there is no response, an emergency response is prepared.

[1025] Specific operation: The server evaluates the presence and content of the response and decides whether to proceed to the next step or cancel the abnormality alarm.

[1026] Output: Emergency response flag or alarm clear

[1027] Step 5: Emergency response

[1028] Server: If there is no response from the user within a certain time (e.g. 1 minute), automatically call emergency services. Use the Twilio API to call and email emergency contacts.

[1029] Input: Emergency Response Flag

[1030] What it does: The server calls Twilio's API to send an emergency message to pre-defined contacts, including information about the user's inactivity time and abnormal vital signs.

[1031] Output: Notification of emergency message transmission completion

[1032] Step 6: Support for daily living

[1033] Device: Providing daily support through voice interaction. For example, in response to a user's question, "What's on my schedule for today?", the device retrieves schedule information using the Google Calendar API.

[1034] Input: User's voice input (question)

[1035] Data processing: Amazon Alexa analyzes the voice input and calls the Google Calendar API to obtain schedule information.

[1036] Specific operation: The device recognizes the user's question, obtains schedule information, and notifies the user by voice.

[1037] Output: Schedule information announced by voice

[1038] (Application example 1)

[1039] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1040] Conventional home monitoring systems are required to respond quickly and effectively when an abnormality is detected, but they have problems such as being unable to respond appropriately to an emergency situation due to the user's absence or delayed response.In addition, they lack daily support functions, making them less practical as systems that support the user's daily life in general.

[1041] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1042] In this invention, the server includes means for receiving data such as movement, temperature, and heart rate from sensors installed in the house, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for calling emergency services if the user does not respond, means for providing support for daily life in the form of voice dialogue, means for monitoring data from the sensors in real time and sending an alarm notification to the smartphone if an abnormality is detected, means for analyzing the response using voice recognition technology if the user does not respond to the voice notification, and means for automatically making an emergency call if the user does not respond. This ensures the user's safety and enables rapid emergency response, while also providing daily life support functions and improving the user's quality of life.

[1043] A "sensor" is a device that is installed inside a home and collects various data such as movement, temperature, and heart rate.

[1044] The "means for receiving data" refers to a device or program that has the function of acquiring information sent from a sensor and transferring it to a server.

[1045] A "means for analyzing data" is a method or device that statistically or algorithmically processes received data to detect inactivity or abnormal vital signs.

[1046] A "means for calling emergency services" is a device or program that automatically contacts a pre-defined emergency contact if there is no response from the user.

[1047] The "means for providing support for daily life in a voice interactive format" is a device or program for providing information in a voice interactive format in response to a user's questions or requests.

[1048] "Means for real-time monitoring" refers to devices or programs that have the function of instantly acquiring and analyzing data obtained from sensors.

[1049] The "means for sending an alarm notification" is a device or program for issuing a warning to a user's device such as a smartphone when an abnormality is detected.

[1050] The "means for analyzing a response using voice recognition technology" refers to a technology or device for recognizing a user's voice response and analyzing its content.

[1051] The "means for automatically making an emergency contact" is a device or program for automatically contacting a set emergency contact if the user does not respond.

[1052] This invention is a system for monitoring a user's lifestyle and health status and responding quickly when an abnormality is detected. This system consists of three main components: a server, a terminal, and a user. Each of these components is explained in detail below.

[1053] System Configuration and Operation

[1054] 1. Sensor placement and data collection

[1055] The server receives real-time data from various sensors installed in the home (motion sensors, temperature sensors, heart rate sensors, etc.). Each sensor is installed in a different location and collects information on the user's behavior and environment.

[1056] 2. Data Analysis

[1057] The server analyzes the received sensor data and determines if there is an abnormality if there is no movement for a certain period of time or if the heart rate is outside the normal range. The analysis method includes an algorithm that compares the current time with the timestamp sent from the sensor to detect whether there has been a prolonged period of no movement.

[1058] 3. Anomaly detection and user notification

[1059] If an abnormality is detected, the device will notify the user by voice, saying, "Please respond. Are you OK?" This uses voice recognition technology to analyze the user's response and provide appropriate feedback. The main interfaces include smartphones and headsets.

[1060] 4. Emergency Response

[1061] If the server does not receive a response from the user within a certain time, it will call emergency services and send an emergency message to pre-defined contacts (emergency services, family, security companies, etc.).

[1062] 5. Daily support

[1063] The device provides daily support through voice interaction. For example, in response to a user's question such as "What is your schedule for today?", the device will respond by voice with "Your regular checkup will be at 3:00 p.m. today."

[1064] Specific examples of the technology

[1065] Example 1: Daily support

[1066] 1. The user speaks to the device, "What are your plans for today?"

[1067] 2. The device recognizes the user's question and provides appropriate information by voice.

[1068] Example 2: Emergency response

[1069] 1. The server receives data from the sensor and detects anomalies, such as inactivity for more than two hours.

[1070] 2. The terminal notifies the user, "Please answer. Are you OK?"

[1071] 3. If the user does not respond, the server will recognize that there has been no response within a certain time and will call emergency services.

[1072] Example 3: Detecting abnormalities in vital signs

[1073] 1. The server receives an abnormal heart rate from the heart rate sensor, for example, a value below 50 BPM.

[1074] 2. The server analyzes the abnormality and determines that a prompt response is required.

[1075] 3. The terminal notifies the user, "Please answer. Are you OK?"

[1076] 4. If the user does not respond, the server will automatically contact an emergency number.

[1077] Technology and software used

[1078] Hardware: sensors (motion sensors, temperature sensors, heart rate sensors, etc.), smartphones, headsets

[1079] Software: Sensor app SDK, speech recognition API (Google Speech-to-Text, Apple SiriKit), data analysis algorithm

[1080] Prompt Sentence Examples

[1081] When you receive the notification "Please respond. Are you OK?", generate a program that analyzes the user's response using a speech recognition API and provides appropriate feedback.

[1082] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1083] Step 1:

[1084] Sensor data collection

[1085] The server receives real-time data from motion sensors, temperature sensors, heart rate sensors, etc. installed inside the home.

[1086] Input: Data sent from sensors, such as movement, temperature, and heart rate.

[1087] Output: Sensor data stored on the server.

[1088] Specific operation: The server receives the data sent from each sensor along with the time stamp and stores the data in a database.

[1089] Step 2:

[1090] Data analysis

[1091] The server analyzes the received data and evaluates whether there has been a period of inactivity or abnormal vital signs.

[1092] Input: Sensor data stored on the server.

[1093] Output: Result of normal / abnormal condition.

[1094] What it does: The server compares the current time with the timestamp sent by the sensor and runs algorithms to detect if there has been a period of inactivity or if the heart rate is outside of the normal range.

[1095] Step 3:

[1096] Anomaly detection and user notification

[1097] If an abnormality is detected, the terminal will notify the user by voice, saying, "Please respond. Are you OK?"

[1098] Input: Abnormal notification from the server.

[1099] Output: Audio notification to the user.

[1100] Specific operation: When an abnormality is detected, the device uses a voice recognition API to issue a message prompting the user to respond.

[1101] Step 4:

[1102] User response analysis

[1103] The device uses voice recognition technology to analyze the user's response and check for any abnormalities.

[1104] Input: The user's spoken response.

[1105] Output: Parsed response.

[1106] Specific operation: Uses a speech recognition API (e.g., Google Speech-to-Text or Apple SiriKit) to convert the user's voice response into text and analyze its content.

[1107] Step 5:

[1108] Emergency response

[1109] The server calls emergency services if no response is received from the user within a certain time.

[1110] Input: Parsed response result.

[1111] Output: Emergency contact is made.

[1112] Specific behavior: If there is no response from the user within a certain period of time, the server will automatically contact pre-defined emergency contacts (e.g., emergency services or family members) and report the emergency situation.

[1113] Step 6:

[1114] Daily support

[1115] The terminal provides daily support to the user in the form of voice dialogue.

[1116] Input: The user's voice command.

[1117] Output: Audio feedback.

[1118] Specific operation: When a user speaks to the device, for example, "Please tell me what my schedule is for today," the device processes the question using a voice recognition API and responds with appropriate information (such as the schedule) via voice.

[1119] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1120] This system receives data from multiple sensors installed in the home, monitors the user's living situation and health status, and automatically takes appropriate action if an abnormality is detected. The system is combined with an emotion engine that recognizes the user's emotions and adjusts daily support, enabling more personalized responses. The system consists of three main components: a server, a terminal, and the user.

[1121] System Configuration and Operation

[1122] Sensor placement and data collection

[1123] Server: Receives data in real time from various sensors installed in the house (motion sensor, temperature sensor, heart rate sensor, etc.). The server centrally manages this data and stores it with a timestamp. For example, the server receives data such as "no_movement" from the motion sensor, "60 BPM" from the heart rate sensor, and "22°C" from the temperature sensor.

[1124] Data analysis

[1125] Server: Analyzes the received sensor data and runs algorithms to detect inactivity and abnormal vital signs. Iactivity detection compares the current time with the time of the last detected movement to determine whether the person has been inactive for a certain period of time. It also determines an abnormality if the heart rate is outside the set normal range.

[1126] Anomaly detection and user notification

[1127] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The terminal will use voice recognition technology and an emotion engine to analyze the user's response and evaluate their emotional state. If the user responds, it will determine that there is no abnormality and provide feedback according to their emotional state.

[1128] Emergency response

[1129] Server: If the user does not respond within a certain time, the server automatically initiates action to call emergency services, which can include pre-defined contacts (ambulance services, family, security companies, etc.).

[1130] Daily support

[1131] Terminal: Provides daily support through voice dialogue. For example, responds to user questions such as "What are your plans for today?" with appropriate information. Analyzes the user's emotions using an emotion engine and adjusts the support content according to their emotional state.

[1132] Specific Examples

[1133] Example 1: Daily support

[1134] 1. User: Says to the device, "What's on my schedule for today?"

[1135] 2. Device: Recognizes the user's question and uses an emotion engine to analyze the tone and pace of the user's voice. If it determines that the user is stressed, it notifies the user, "You have a regular checkup at 3 PM today, but we recommend that you take some time to relax." If the user is in a normal state, it notifies the user, "You have a regular checkup at 3 PM today."

[1136] Example 2: Emergency response

[1137] 1. Server: Receives data from sensors and detects inactivity for more than two hours.

[1138] 2. Terminal: Notifies the user by voice, "Please respond. Are you OK?". Analyzes the user's response using the emotion engine to determine their emotional state.

[1139] 3. User: No response.

[1140] 4. Server: No response within a certain time, so call emergency services.

[1141] Example 3: Detecting abnormalities in vital signs

[1142] 1. Server: Receives abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[1143] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[1144] 3. Terminal: Notifies the user, "Please respond. Are you OK?". Analyzes the user's response using the emotion engine to determine their emotional state.

[1145] 4. User: No response.

[1146] 5. Server: Calls emergency services after no response within a certain time.

[1147] Example 4: Daily support based on emotional state

[1148] 1. User: Says to the device, "I'm feeling a little tired today."

[1149] 2. Terminal: Recognizes the user's speech and analyzes the user's level of fatigue using an emotion engine.

[1150] 3. Device: Notify: "Would you like to schedule more time for relaxation today?"

[1151] As described above, the system of the present invention uses sensors to monitor the living conditions and health status of residents in real time, and by combining it with an emotion engine, it individualizes responses when abnormalities are detected and daily support, providing an environment in which users can live with peace of mind.

[1152] The processing flow will be explained below.

[1153] Step 1:

[1154] Server: Receives data from various sensors (motion sensor, temperature sensor, heart rate sensor, etc.) in real time and stores it with a timestamp. For example, it receives data such as "Motion sensor: no_movement", "Heart rate sensor: 60 BPM", and "Temperature sensor: 22°C".

[1155] Step 2:

[1156] Server: Analyzes the received sensor data. To detect inactivity, it compares the current time with the time of the last detected movement to determine whether there has been inactivity for a certain period of time. It also determines that there is an abnormality if the heart rate is outside the set normal range.

[1157] Step 3:

[1158] Server: If an abnormality is detected based on the analysis results, proceed to the next step. If the condition is normal, switch to the daily support function. For example, if the user wants to know "today's schedule," provide schedule information.

[1159] Step 4:

[1160] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?". The emotion engine will analyze the user's response and evaluate their emotional state. If the user responds, it will be determined that there is no abnormality.

[1161] Step 5:

[1162] Server: If the user does not respond within a certain time frame, the server automatically calls emergency services, which can include pre-defined contacts (ambulance services, family, security companies, etc.).

[1163] Step 6:

[1164] Server: When calling emergency services, the server attempts to contact the emergency service as quickly as possible using multiple methods (telephone, email, SMS, etc.) and accurately communicates details of the emergency (e.g., "inactivity for more than two hours" or "heart rate below 50 BPM").

[1165] Step 7:

[1166] Terminal: Responds to user requests as a daily support function. When a user says, "Tell me what's on my schedule for today," the terminal retrieves schedule information from the server and notifies them by voice.

[1167] Step 8:

[1168] Emotion engine: Analyzes the tone, pace, and intonation of the user's voice to assess their emotional state. For example, if it determines that the user is stressed, it will offer advice on how to relax.

[1169] Step 9:

[1170] Device: Adjust daily support based on the results of the emotion engine. For example, if a user says, "I'm a little tired today," the device will notify them, "When adjusting your schedule for today, would you like us to suggest more time for relaxation?"

[1171] Step 10:

[1172] User: Use the daily support features to check their schedule and medication times. For example, they can say, "What's my schedule for today?" and receive notifications from the device. They can also respond to notifications from the device in the event of an emergency.

[1173] Specific Examples

[1174] Example 1: Daily support

[1175] Step 1: The user speaks to the device, "What's on my schedule for today?"

[1176] Step 2: The device recognizes the user's question and uses an emotion engine to analyze the tone and pace of the user's voice.

[1177] Step 8: If the device determines that the user is stressed, it notifies the user, "You have a regular checkup at 3 PM today, but we recommend that you take some time to relax." If the user is in a normal state, it notifies the user, "You have a regular checkup at 3 PM today."

[1178] Example 2: Emergency response

[1179] Step 1: The server receives data from the sensors and detects inactivity for more than two hours.

[1180] Step 4: The device notifies the user by voice, "Please respond. Are you OK?" The emotion engine analyzes the user's response and determines their emotional state.

[1181] Step 5: The user does not respond.

[1182] Step 6: The server does not respond within a certain time, so emergency services are called.

[1183] Example 3: Detecting abnormalities in vital signs

[1184] Step 1: The server receives an abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[1185] Step 2: The server analyzes the anomaly and determines that emergency action is required.

[1186] Step 4: The device notifies the user, "Please respond. Are you OK?" The emotion engine analyzes the user's response and determines their emotional state.

[1187] Step 5: The user does not respond.

[1188] Step 6: The server does not respond within a certain time, so emergency services are called.

[1189] Example 4: Daily support based on emotional state

[1190] Step 1: The user says to the device, "I'm feeling a little tired today."

[1191] Step 8: The device recognizes the user's speech and uses an emotion engine to analyze the user's level of fatigue.

[1192] Step 9: Your device will notify you, "Would you like us to suggest more time for relaxation for your schedule today?"

[1193] The above are the specific processing steps of the system of the present invention. At each step, the server, terminal, and user work in cooperation to safely and effectively support the lives of residents.

[1194] Example 2

[1195] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1196] In modern residential environments, there is a need to understand the living conditions and health status of residents in real time and respond quickly when abnormalities occur, but conventional systems have difficulty meeting these requirements. Furthermore, when it comes to supporting users' daily lives, they lack the ability to respond in detail to individual situations and emotions. Therefore, providing an environment where residents can live with peace of mind has become a challenge.

[1197] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving data such as movement, temperature, and heart rate from sensors installed in the house; means for centrally managing the received data and saving it with a timestamp; means for analyzing the received data and detecting inactivity or abnormal vital signs; means for issuing a voice notification when an abnormality is detected and analyzing the user's response using an emotion engine; means for calling emergency services when there is no response from the user; and means for providing support for daily life in the form of voice dialogue and using the emotion engine to provide support according to the user's emotional state. This makes it possible to provide an environment in which the user can live with peace of mind by monitoring the user's living situation and health condition in real time and taking necessary measures promptly.

[1198] A "sensor" is a device that is installed inside a home and collects data such as movement, temperature, and heart rate.

[1199] A "centralized management system" is a system that manages received data in one place and stores it with a timestamp.

[1200] The "analysis means" is a function that uses the received data to execute an algorithm for detecting immobility or abnormal vital signs.

[1201] An "emotion engine" is a technology that analyzes a user's emotional state and determines the appropriate response based on that.

[1202] "Emergency services" are contacts that are automatically contacted if there is no response from the user, and include ambulance services, family, security companies, etc.

[1203] "Voice notification" is a function that notifies the user by voice when an abnormality is detected.

[1204] "Voice interaction" refers to a format in which information is exchanged between a user and a system using voice.

[1205] MODE FOR CARRYING OUT THE INVENTION

[1206] This invention is a system that monitors the user's living situation and health status based on data from sensors installed in the home, and automatically responds if an abnormality is detected. This system consists of three main components: a server, a terminal, and the user.

[1207] Hardware or software used

[1208] The main hardware and software required to implement this system are as follows:

[1209] 1. Sensors: Multiple types of sensors, such as motion sensors, temperature sensors, heart rate sensors, etc.

[1210] 2. Server: A central device that receives, analyzes, stores, detects anomalies, and handles emergency responses.

[1211] 3. Terminal: A device that provides voice notifications, voice interaction, emotion engine analysis, and support for daily life.

[1212] Data processing and calculation

[1213] 1. Data Collection:

[1214] The server receives real-time data such as temperature and heart rate from various sensors installed inside the home and stores it in a centralized management system with a timestamp.

[1215] 2. Data Analysis:

[1216] The server runs an analysis algorithm based on the received data to detect inactivity or abnormal vital signs. To detect inactivity, it compares the current time with the time of the last detected movement and determines whether the person has been inactive for a certain period of time (e.g., two hours). It also determines an abnormality if the heart rate exceeds a set range (e.g., 50 BPM to 100 BPM).

[1217] 3. User response analysis:

[1218] The device has a means for issuing a voice notification when an abnormality is detected, and uses an emotion engine to analyze the user's response and evaluate their emotional state. For example, if the user responds "Yes, I'm fine," the emotion engine evaluates whether the user is calm.

[1219] 4. Emergency Response:

[1220] The server has a mechanism to automatically call emergency services if no response is received from the user within a certain time (e.g., 5 minutes), and has the ability to contact pre-defined contacts (e.g., emergency services, family, security companies, etc.).

[1221] 5. Daily support:

[1222] The device provides support for the user's daily life through voice dialogue, and uses an emotion engine to provide appropriate information according to the user's emotional state. For example, if a user says, "What are your plans for today?", the emotion engine analyzes the tone and pace of the user's voice. If it determines that the user is stressed, it will notify the user, "You have a regular checkup at 3:00 p.m. today, but we recommend that you take some time to relax."

[1223] Prompt Sentence Examples

[1224] Examples of prompts to input to a generative AI model include:

[1225] "Analyze the data from the sensors and explain how you will respond if there are any abnormalities."

[1226] "Recognize the user's emotions and tell me how to provide support based on those emotions."

[1227] The system of the present invention, which includes the above functions, makes it possible to monitor a user's living situation and health condition in real time and take necessary measures quickly, thereby providing an environment in which the user can live with peace of mind.

[1228] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1229] Step 1: Collect sensor data

[1230] The server receives real-time data from sensors installed in the home, such as movement, temperature, and heart rate. The input is the data sent from each sensor (e.g., "no_movement," "22°C," "60 BPM"), and the output is to store this data with a timestamp in a centralized management system. Specifically, the sensors send their measurements to the server, which receives the data and stores it in a database.

[1231] Step 2: Analyze the data

[1232] The server analyzes the collected data. The input is the stored sensor data with a timestamp, and the output is the detection of inactivity or abnormal vital signs. Specifically, the server compares the timestamps of the motion sensor data and checks whether inactivity has continued for a certain period of time (for example, two hours). It also analyzes whether the heart rate data is within a set range (50 BPM to 100 BPM).

[1233] Step 3: Anomaly detection

[1234] The server detects abnormalities based on the analysis results. The input is the analyzed data, and the output is information that an abnormality has been detected. Specifically, if inactivity or an abnormal heart rate is detected, the server records that information and determines that this is an abnormal condition that requires proceeding to the next processing step.

[1235] Step 4: User Notification

[1236] If an abnormality is detected, the device will notify the user by voice. The input is notification data from the server indicating the abnormality, and the output is the voice notification and a response from the user. Specifically, the device will notify by voice, "Please respond. Are you OK?", receive the user's response via the microphone, convert it into text data, and pass it to the emotion engine.

[1237] Step 5: User response analysis

[1238] The device uses an emotion engine to analyze the user's response. The input is text data converted from the user's voice response, and the output is the user's emotional state. Specifically, the device inputs the text data analyzed from the voice into the emotion engine, which evaluates whether the user is calm or stressed.

[1239] Step 6: Emergency response

[1240] If the server does not receive a response from the user within a certain time (e.g., 5 minutes), it automatically calls emergency services. The input is the user's no-response information, and the output is a call to emergency services. Specifically, the server automatically calls and sends messages to pre-defined contacts (e.g., 119, family, security company).

[1241] Step 7: Daily support

[1242] The device provides support for daily life through voice dialogue. The input is questions or requests from the user, and the output is appropriate information or advice. In concrete terms, when a user says, "What are your plans for today?", the device uses an emotion engine to analyze the tone and pace of the user's voice and assess whether they are feeling stressed. If they are feeling stressed, the device will notify them, "You have a regular checkup at 3:00 PM today, but we recommend that you take some time to relax," and if they are feeling normal, it will notify them, "You have a regular checkup at 3:00 PM today."

[1243] As described above, by performing specific data processing or calculations based on the input data at each step and passing the output to the next step, it is possible to monitor the user's living situation and health condition in real time and take any necessary measures quickly.

[1244] (Application example 2)

[1245] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1246] In modern living environments and brick-and-mortar stores, real-time monitoring systems for the health and safety of residents, store staff, and customers are important, but current technology often cannot adequately address these issues. There is a particular need for emergency response and daily life support that is tailored to each individual. In addition to monitoring, there is also a need for personalized responses using emotion engines.

[1247] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1248] In this invention, the server includes means for receiving data such as movement, temperature, and heart rate from sensors installed in the home or store, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for calling emergency services if there is no response from the user, means for providing support for daily life in the form of voice dialogue, means for receiving data from sensors installed in the store and monitoring the behavior of store staff and customers, means for analyzing the received data to detect abnormalities and notifying store staff, and means for analyzing and evaluating the emotions of store staff using an emotion engine along with responses.This improves the safety and health of users, store staff, and customers, and enables individually tailored support and emergency responses.

[1249] "Sensors installed inside the home" refers to various sensors installed inside the home, which are devices for collecting data such as movement, temperature, and heart rate.

[1250] A "motion sensor" is a sensor used to detect motion and to monitor inactivity.

[1251] A "temperature sensor" is a sensor for detecting the ambient temperature and for monitoring changes in the temperature of the environment.

[1252] A "heart rate sensor" is a sensor that measures an individual's heart rate and is used to monitor vital signs.

[1253] A "means for receiving data" is a method or device for acquiring data sent from a sensor.

[1254] A "means for analyzing data" is a method or device for processing received data and detecting abnormal conditions or patterns.

[1255] "Means for invoking emergency services" means a method or device for notifying emergency services or relevant authorities when an abnormality is detected and there is no response from the user.

[1256] The "means for providing in the form of voice interaction" refers to a method or device for interacting with a user using voice to provide support for daily life.

[1257] "Sensors installed in stores" refer to various sensors installed in commercial facilities, and are devices for monitoring the movements and status of store staff and customers.

[1258] An "emotion engine" is an algorithm or device that analyzes the emotional state of users and store clerks and makes appropriate evaluations.

[1259] The "means for notifying a store clerk" is a method or device for notifying a store clerk when an abnormality is detected.

[1260] "Means for analyzing and evaluating emotions" refers to a method or device for analyzing and evaluating the emotional state of a user or store clerk.

[1261] This invention is a system that receives data from multiple sensors installed in homes and stores, monitors the user's living situation and health status, and automatically takes appropriate action if an abnormality is detected. Furthermore, by combining it with an emotion engine, it can recognize the emotions of users, store clerks, and customers and provide individually tailored daily support and emergency responses.

[1262] Hardware and Software Configuration

[1263] 1. Sensor System

[1264] Various sensors (such as motion sensors, temperature sensors, and heart rate sensors) are placed in homes and stores to monitor the environment and personal vital signs in real time.

[1265] 2. Server

[1266] The server receives and centralizes data from various sensors, stores it with a timestamp, analyzes the data, and runs algorithms to detect inactivity or abnormal vital signs. If an abnormality is detected, the server can call emergency services as an appropriate response.

[1267] 3. Terminal

[1268] The terminal provides daily support to users and store staff through voice interaction, utilizing voice recognition technology (e.g., Google Speech-to-Text API) and emotion engines (e.g., Emotion API) to analyze the user's responses and emotional state and provide appropriate feedback.

[1269] System Operation

[1270] Receiving and storing data

[1271] The server receives real-time data from each sensor in a home or store and manages it centrally. For example, it receives data such as "no_movement" from a motion sensor, "22°C" from a temperature sensor, and "60 BPM" from a heart rate sensor. This data is saved with a timestamp.

[1272] Data analysis and anomaly detection

[1273] The server analyzes the received data and detects an abnormality, for example, if the device is inactive for a certain period of time or if the heart rate is outside the normal range.

[1274] Notification and Response

[1275] If an abnormality is detected, the device will notify the user or store clerk by voice, saying, "Please respond. Are you OK?" The device will use an emotion engine to analyze the user's or store clerk's response and evaluate their emotional state. If the user or store clerk responds, it will provide appropriate feedback based on their response.

[1276] Emergency response

[1277] If no response is received from the user or store staff within a certain time frame, the server will automatically call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[1278] Specific examples

[1279] When a user says to the device, "I feel a little tired today," the device will recognize the voice, analyze the user's level of fatigue using an emotion engine, and notify them, "Would you like us to suggest that you increase your relaxation time when adjusting your schedule for today?"

[1280] If the store's motion sensors detect inactivity for more than two hours, the device will issue a voice message saying, "Please respond. Are you OK?" and will call emergency services if there is no response.

[1281] Prompt Sentence Examples

[1282] "How can we build a system that uses data from sensors in the home to monitor the user's health and take appropriate action if an abnormality is detected?"

[1283] As a result, this system improves the safety and health of users, store staff, and customers, and enables individually tailored support and rapid emergency response.

[1284] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1285] Step 1:

[1286] Receiving data

[1287] The server receives data in real time from various sensors (motion sensors, temperature sensors, heart rate sensors, etc.) installed in homes and stores.

[1288] (Input) Data from each sensor (e.g., movement sensor -> "no_movement", temperature sensor -> "22°C", heart rate sensor -> "60BPM")

[1289] (Output) Sensor data with timestamp

[1290] (Specific operation) The server receives data sent from each sensor through the interface and stores the data in a centralized database with a timestamp.

[1291] Step 2:

[1292] Data analysis

[1293] The server analyzes the received sensor data and executes algorithms to detect abnormal conditions, such as inactivity or abnormal vital signs.

[1294] (Input) Time-stamped sensor data

[1295] (Output) Anomaly detection result (e.g., "Normal", "Abnormal", "No operation", etc.)

[1296] (Specific operation) The server analyzes the sensor data using a preset anomaly detection algorithm (for example, determining periods of inactivity) and determines whether an anomaly has occurred.

[1297] Step 3:

[1298] Abnormal notification

[1299] If an abnormality is detected, the server sends a notification to the terminal, which then issues a voice message to the user or store clerk saying, "Please respond. Are you OK?"

[1300] (Input) Anomaly detection results

[1301] (Output) The execution status of the voice notification (e.g., "Notification sent").

[1302] (Specific Operation) When an abnormality is notified from the server, the terminal uses its voice synthesis function to generate a voice message and notifies the user or store clerk through the speaker.

[1303] Step 4:

[1304] User Response and Sentiment Analysis

[1305] When a user or a store clerk responds to the terminal, the terminal uses voice recognition technology to convert the response into text data and uses an emotion engine to analyze the emotion.

[1306] (Input) User or store clerk's voice response

[1307] (Output) Analyzed emotional state (e.g., "stressed," "normal," etc.)

[1308] (Specific operation) The device uses voice recognition technology such as the Google Speech-to-Text API to convert speech into text, and then inputs the text data into the Emotion API to analyze the emotional state.

[1309] Step 5:

[1310] Providing feedback

[1311] Based on the analysis results, the terminal provides appropriate feedback to the user or store clerk via voice.

[1312] (Input) Analyzed emotional state

[1313] (Output) Feedback message (e.g. "Relax" or "Everything is fine")

[1314] (Specific operation) The terminal selects a feedback message based on the analysis results, generates a voice message using the voice synthesis function, and transmits it to the user or store clerk through the speaker.

[1315] Step 6:

[1316] Emergency response

[1317] If the user or store attendant does not respond within a certain time, the server automatically calls emergency services.

[1318] (Input) Response waiting time and re-detection result

[1319] (Output) The execution status of the emergency call (e.g., "Emergency services called").

[1320] (Specific operation) The server confirms that the pre-set response waiting time has elapsed and automatically sends a notification to emergency contacts (emergency services, family, security company, etc.).

[1321] Through the above processing steps, this system improves the safety and health of users, store staff, and customers, and enables individually tailored support and rapid emergency response.

[1322] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1323] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1324] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1325] [Fourth embodiment]

[1326] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1327] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1328] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1329] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1330] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1331] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1332] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1333] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1334] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1335] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1336] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1337] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1338] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1339] This system receives data from multiple sensors installed in the home and monitors the user's living conditions and health status, and automatically takes appropriate action if an abnormality is detected. This system consists of three main components: a server, a terminal, and the user.

[1340] System Configuration and Operation

[1341] Sensor placement and data collection

[1342] Server: Receives real-time data from various sensors installed in the home (motion sensors, temperature sensors, heart rate sensors, etc.). Each sensor is installed in a different location and collects information on the user's behavior and environment.

[1343] Data analysis

[1344] Server: Analyzes the received sensor data and evaluates whether there is inactivity or abnormal vital signs. For example, if there is inactivity for a certain period of time or if the heart rate is outside the normal range, it is determined to be abnormal.

[1345] The analysis means uses an algorithm that compares the current time with the timestamp sent by the sensor and detects whether there has been a period of inactivity.

[1346] Anomaly detection and user notification

[1347] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The user will respond by voice to confirm that there is no abnormality.

[1348] The device uses voice recognition technology to analyze the user's response and provide appropriate feedback.

[1349] Emergency response

[1350] Server: If the user does not respond within a certain time frame, the server automatically calls emergency services, allowing for a quick response to ensure the user's safety.

[1351] Emergency contact methods send emergency messages to pre-defined contacts (emergency services, family, security companies, etc.).

[1352] Daily support

[1353] Terminal: Providing everyday support through voice interaction. For example, providing appropriate information in response to a user's question such as "What is my schedule for today?"

[1354] The device manages the user's schedule and sets reminders when necessary.

[1355] Specific Examples

[1356] Example 1: Daily support

[1357] 1. User: Says to the device, "What's on my schedule for today?"

[1358] 2. Terminal: Recognizes the user's question and announces in voice, "Your regular checkup will be at 3:00 p.m. today."

[1359] Example 2: Emergency response

[1360] 1. Server: Receives data from sensors and detects inactivity for more than two hours.

[1361] 2. Terminal: The user is prompted with a voice message saying "Please answer. Are you OK?"

[1362] 3. User: No response.

[1363] 4. Server: No response within a certain time, so call emergency services.

[1364] Example 3: Detecting abnormalities in vital signs

[1365] 1. Server: Receives abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[1366] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[1367] 3. Terminal: Notify the user, "Please answer. Are you OK?"

[1368] 4. User: No response.

[1369] 5. Server: Calls emergency services after no response within a certain time.

[1370] As described above, the present invention uses sensors to monitor the living conditions and health status of residents in real time, and responds quickly if an abnormality is detected, thereby providing an environment in which residents can live in peace of mind.

[1371] The processing flow will be explained below.

[1372] Step 1:

[1373] Server: Receives data in real time from various sensors (motion sensor, temperature sensor, heart rate sensor, etc.). The server centrally manages this data and stores it with a timestamp. For example, the server receives data such as "no_movement" from the motion sensor, "60 BPM" from the heart rate sensor, and "22°C" from the temperature sensor.

[1374] Step 2:

[1375] Server: Analyzes the received sensor data and runs algorithms to detect inactivity and abnormal vital signs. Iactivity detection compares the current time with the time of the last detected movement to determine whether the person has been inactive for a certain period of time. It also determines an abnormality if the heart rate is outside the set normal range.

[1376] Step 3:

[1377] Server: If an abnormality is detected based on the analysis results, proceed to the next step. If normal, switch to daily support functions. For example, if a user wants to know "today's schedule," provide appropriate information.

[1378] Step 4:

[1379] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The terminal will use voice recognition technology to analyze the user's response. If the user responds, it will determine that there is no abnormality.

[1380] Step 5:

[1381] Server: If no response is received from the user within a certain time, the server will automatically initiate action to call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[1382] Step 6:

[1383] Server: When calling emergency services, the server attempts to contact the emergency service as quickly as possible using multiple methods (telephone, email, SMS, etc.) and accurately communicates details of the emergency (e.g., "inactivity for more than two hours" or "heart rate below 50 BPM").

[1384] Step 7:

[1385] Terminal: Responds to user requests as a daily support function. When a user says, "Please tell me what's on my schedule for today," the terminal retrieves schedule information from the server and notifies them by voice, "I have a regular checkup at 3:00 p.m. today." It also has a reminder function that notifies users when it's time to take their medication.

[1386] Step 8:

[1387] User: Uses the daily support functions to check their schedule and medication times. Obtains necessary information through appropriate interactions with the device. In an emergency, ensures safety by responding promptly to response confirmation notifications from the device.

[1388] The above are the specific processing steps of the system of the present invention. At each step, the server, terminal, and user work in cooperation to safely and effectively support the lives of residents.

[1389] Example 1

[1390] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1391] Daily health monitoring and rapid response in the event of an abnormality are important for elderly people and residents with health concerns to live with peace of mind. However, conventional systems lack the means to detect abnormalities in real time, notify users through voice dialogue, and automatically take emergency action based on the subsequent response. Furthermore, the functionality to provide continuous support for daily life was also insufficient. This resulted in a delay in appropriate response in the event of an abnormality, posing a risk of not ensuring the safety of users.

[1392] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1393] In this invention, the server includes means for receiving data from multiple sensors installed in the house, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for notifying the user by voice of the detected abnormality, means for calling emergency services if the user does not respond, and means for providing support for daily life in the form of voice dialogue. This allows the user's living situation and health condition to be monitored in real time, and if an abnormality is detected, a prompt response can be made, creating an environment in which the user can live with peace of mind.

[1394] "House" refers to a building for human habitation.

[1395] A "sensor" refers to a device that detects physical or environmental phenomena and collects that information as data.

[1396] "Data" refers to detected information, which is recorded in the form of numbers, character strings, or the like.

[1397] "Means" refers to a method or device used to achieve a particular purpose.

[1398] "Analysis" refers to the process of breaking down and interpreting data in order to evaluate and make judgments.

[1399] "Idle" refers to a period of no movement.

[1400] "Vital signs" refers to vital signs such as heart rate, body temperature, and respiratory rate.

[1401] "User" refers to a person who uses the system.

[1402] "Responding" refers to the user's response to a notification from the system.

[1403] "Emergency services" refers to emergency response agencies and services such as emergency medical services, police, and fire departments.

[1404] "Voice dialogue" refers to two-way communication using voice.

[1405] "Life support" refers to assistance with daily activities and the provision of information.

[1406] This invention is a system that receives data from multiple sensors installed in a home and monitors a user's living conditions and health status. The system consists of three main components: a server, a terminal, and a user. The detailed configuration and operation of the system are described below.

[1407] Sensor placement and data collection

[1408] Server: Receives real-time data from various sensors (e.g., motion sensor, temperature sensor, heart rate sensor) placed in the home. Each sensor is installed in a different location and collects information on the user's behavior and environment.

[1409] Hardware used: Raspberry Pi, Arduino sensors, etc.

[1410] Data analysis

[1411] Server: Analyzes the received sensor data and evaluates whether there is any motion or abnormal vital signs. This analysis is performed using Python, processing the data using Pandas and NumPy.

[1412] For example, if there is no movement for a certain period of time (e.g., 30 minutes) or if the heart rate falls outside a certain range (e.g., 40 BPM or less), it is determined to be abnormal.

[1413] Anomaly detection and notification

[1414] Device: If an abnormality is detected, the device will notify the user by voice, "Please respond. Are you OK?" This notification uses the Google Speech-to-Text API.

[1415] The device uses voice recognition technology to analyze the user's response and confirm that there are no abnormalities.

[1416] Emergency response

[1417] Server: If no response is received from the user within a certain time (e.g., 1 minute), the server automatically calls emergency services. It uses the Twilio API to communicate with the emergency services, sending messages and calls to pre-defined contacts.

[1418] Software used: Twilio API, SMTP server, etc.

[1419] Support for daily life

[1420] Device: Provides daily support through voice interaction. For example, in response to a user question such as "What are your plans for today?", the device retrieves schedule information using the Google Calendar API and sets reminders at the appropriate time.

[1421] Software used: Google Calendar API, Amazon Alexa, etc.

[1422] Specific Examples

[1423] Example 1: Daily support

[1424] 1. User: Say to the device, "What's on my schedule for today?"

[1425] 2. Device: Uses the Google Calendar API to retrieve the schedule for the day and notifies the user via voice message, saying, "Your regular checkup will be at 3:00 p.m. today."

[1426] Example 2: Emergency response

[1427] 1. Server: Receives data from the motion sensor and detects inactivity for more than two hours.

[1428] 2. Device: A voice message will say "Please answer. Are you OK?"

[1429] 3. User: No response.

[1430] 4. Server: No response within 1 minute, so calls emergency services using the Twilio API.

[1431] Example 3: Detecting abnormalities in vital signs

[1432] 1. Server: Receives abnormal heart rate (e.g., below 40 BPM) from the heart rate sensor.

[1433] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[1434] 3. Terminal: Notify "Please answer. Are you OK?"

[1435] 4. User: No response.

[1436] 5. Server: No response within 1 minute, so calls emergency services using the Twilio API.

[1437] In this way, the present invention uses sensors to monitor the living conditions and health status of residents in real time, and by responding quickly if an abnormality is detected, it provides an environment in which residents can live in peace of mind.

[1438] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1439] Step 1: Collect data from sensors

[1440] Server: Receives real-time data from sensors (motion sensors, temperature sensors, heart rate sensors, etc.). The sensors transmit data from each device via Bluetooth or Wi-Fi.

[1441] Input: Measurement data sent from sensors (movement, temperature, heart rate)

[1442] Specific operation: The server receives data from each sensor every second and records it in a database (e.g., MySQL) in chronological order.

[1443] Output: Sensor data stored in a database

[1444] Step 2: Analyze the data

[1445] Server: Analyzes the received sensor data and detects inactivity or abnormal vital signs. This is done using a Python script that processes the data using Pandas and NumPy.

[1446] Input: Sensor data retrieved from a database

[1447] Data processing: A Python script analyzes the data from each sensor and calculates the average, maximum, and minimum values ​​of inactivity time and vital signs.

[1448] Specific operation: If there is no movement for more than 30 minutes or if the heart rate is below 40 BPM, an abnormality flag is raised.

[1449] Output: Analysis results flagged as abnormal

[1450] Step 3: Anomaly detection and notification

[1451] Device: If an abnormality is detected, the device will notify the user by voice, saying, "Please respond. Are you OK?" The user's voice response will be analyzed using the Google Speech-to-Text API.

[1452] Input: Analysis results flagged as abnormal

[1453] Specific operation: The device plays a voice prompt every 10 seconds, collects the user's voice response using the microphone, converts the collected voice into text, and analyzes the response content.

[1454] Output: User response text

[1455] Step 4: Response analysis and feedback

[1456] Server: Analyzes the user's response and verifies that there are no abnormalities. If an abnormality is detected, prepares further countermeasures.

[1457] Input: User response text

[1458] Data calculation: If the response is positive, such as "It's okay," it is determined that there is no abnormality, and if the response is negative or there is no response, an emergency response is prepared.

[1459] Specific operation: The server evaluates the presence and content of the response and decides whether to proceed to the next step or cancel the abnormality alarm.

[1460] Output: Emergency response flag or alarm clear

[1461] Step 5: Emergency response

[1462] Server: If there is no response from the user within a certain time (e.g. 1 minute), automatically call emergency services. Use the Twilio API to call and email emergency contacts.

[1463] Input: Emergency Response Flag

[1464] What it does: The server calls Twilio's API to send an emergency message to pre-defined contacts, including information about the user's inactivity time and abnormal vital signs.

[1465] Output: Notification of emergency message transmission completion

[1466] Step 6: Support for daily living

[1467] Device: Providing daily support through voice interaction. For example, in response to a user's question, "What's on my schedule for today?", the device retrieves schedule information using the Google Calendar API.

[1468] Input: User's voice input (question)

[1469] Data processing: Amazon Alexa analyzes the voice input and calls the Google Calendar API to obtain schedule information.

[1470] Specific operation: The device recognizes the user's question, obtains schedule information, and notifies the user by voice.

[1471] Output: Schedule information announced by voice

[1472] (Application example 1)

[1473] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1474] Conventional home monitoring systems are required to respond quickly and effectively when an abnormality is detected, but they have problems such as being unable to respond appropriately to an emergency situation due to the user's absence or delayed response.In addition, they lack daily support functions, making them less practical as systems that support the user's daily life in general.

[1475] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1476] In this invention, the server includes means for receiving data such as movement, temperature, and heart rate from sensors installed in the house, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for calling emergency services if the user does not respond, means for providing support for daily life in the form of voice dialogue, means for monitoring data from the sensors in real time and sending an alarm notification to the smartphone if an abnormality is detected, means for analyzing the response using voice recognition technology if the user does not respond to the voice notification, and means for automatically making an emergency call if the user does not respond. This ensures the user's safety and enables rapid emergency response, while also providing daily life support functions and improving the user's quality of life.

[1477] A "sensor" is a device that is installed inside a home and collects various data such as movement, temperature, and heart rate.

[1478] The "means for receiving data" refers to a device or program that has the function of acquiring information sent from a sensor and transferring it to a server.

[1479] A "means for analyzing data" is a method or device that statistically or algorithmically processes received data to detect inactivity or abnormal vital signs.

[1480] A "means for calling emergency services" is a device or program that automatically contacts pre-defined emergency contacts if there is no response from the user.

[1481] The "means for providing support for daily life in a voice interactive format" is a device or program for providing information in a voice interactive format in response to a user's questions or requests.

[1482] "Means for real-time monitoring" refers to devices or programs that have the function of instantly acquiring and analyzing data obtained from sensors.

[1483] The "means for sending an alarm notification" is a device or program for issuing a warning to a user's device such as a smartphone when an abnormality is detected.

[1484] The "means for analyzing a response using voice recognition technology" refers to a technology or device for recognizing a user's voice response and analyzing its content.

[1485] The "means for automatically making an emergency contact" is a device or program for automatically contacting a set emergency contact if the user does not respond.

[1486] This invention is a system for monitoring a user's lifestyle and health status and responding quickly when an abnormality is detected. This system consists of three main components: a server, a terminal, and a user. Each of these components is explained in detail below.

[1487] System Configuration and Operation

[1488] 1. Sensor placement and data collection

[1489] The server receives real-time data from various sensors installed in the home (motion sensors, temperature sensors, heart rate sensors, etc.). Each sensor is installed in a different location and collects information on the user's behavior and environment.

[1490] 2. Data Analysis

[1491] The server analyzes the received sensor data and determines if there is an abnormality if there is no movement for a certain period of time or if the heart rate is outside the normal range. The analysis method includes an algorithm that compares the current time with the timestamp sent from the sensor to detect whether there has been a prolonged period of no movement.

[1492] 3. Anomaly detection and user notification

[1493] If an abnormality is detected, the device will notify the user by voice, saying, "Please respond. Are you OK?" This uses voice recognition technology to analyze the user's response and provide appropriate feedback. The main interfaces include smartphones and headsets.

[1494] 4. Emergency Response

[1495] If the server does not receive a response from the user within a certain time, it will call emergency services and send an emergency message to pre-defined contacts (emergency services, family, security companies, etc.).

[1496] 5. Daily support

[1497] The device provides daily support through voice interaction. For example, in response to a user's question such as "What is your schedule for today?", the device will respond by voice with "Your regular checkup will be at 3:00 p.m. today."

[1498] Specific examples of the technology

[1499] Example 1: Daily support

[1500] 1. The user speaks to the device, "What are your plans for today?"

[1501] 2. The device recognizes the user's question and provides appropriate information by voice.

[1502] Example 2: Emergency response

[1503] 1. The server receives data from the sensor and detects anomalies, such as inactivity for more than two hours.

[1504] 2. The terminal notifies the user, "Please answer. Are you OK?"

[1505] 3. If the user does not respond, the server will recognize that there has been no response within a certain time and will call emergency services.

[1506] Example 3: Detecting abnormalities in vital signs

[1507] 1. The server receives an abnormal heart rate from the heart rate sensor, for example, a value below 50 BPM.

[1508] 2. The server analyzes the abnormality and determines that a prompt response is required.

[1509] 3. The terminal notifies the user, "Please answer. Are you OK?"

[1510] 4. If the user does not respond, the server will automatically contact an emergency number.

[1511] Technology and software used

[1512] Hardware: sensors (motion sensors, temperature sensors, heart rate sensors, etc.), smartphones, headsets

[1513] Software: Sensor app SDK, speech recognition API (Google Speech-to-Text, Apple SiriKit), data analysis algorithm

[1514] Prompt Sentence Examples

[1515] When you receive the notification "Please respond. Are you OK?", generate a program that analyzes the user's response using a speech recognition API and provides appropriate feedback.

[1516] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1517] Step 1:

[1518] Sensor data collection

[1519] The server receives real-time data from motion sensors, temperature sensors, heart rate sensors, etc. installed inside the home.

[1520] Input: Data sent from sensors, such as movement, temperature, and heart rate.

[1521] Output: Sensor data stored on the server.

[1522] Specific operation: The server receives the data sent from each sensor along with the time stamp and stores the data in a database.

[1523] Step 2:

[1524] Data analysis

[1525] The server analyzes the received data and evaluates whether there has been a period of inactivity or abnormal vital signs.

[1526] Input: Sensor data stored on the server.

[1527] Output: Result of normal / abnormal condition.

[1528] What it does: The server compares the current time with the timestamp sent by the sensor and runs algorithms to detect if there has been a period of inactivity or if the heart rate is outside of the normal range.

[1529] Step 3:

[1530] Anomaly detection and user notification

[1531] If an abnormality is detected, the terminal will notify the user by voice, saying, "Please respond. Are you OK?"

[1532] Input: Abnormal notification from the server.

[1533] Output: Audio notification to the user.

[1534] Specific operation: When an abnormality is detected, the device uses a voice recognition API to issue a message prompting the user to respond.

[1535] Step 4:

[1536] User response analysis

[1537] The device uses voice recognition technology to analyze the user's response and check for any abnormalities.

[1538] Input: The user's spoken response.

[1539] Output: Parsed response.

[1540] Specific operation: Uses a speech recognition API (e.g., Google Speech-to-Text or Apple SiriKit) to convert the user's voice response into text and analyze its content.

[1541] Step 5:

[1542] Emergency response

[1543] The server calls emergency services if no response is received from the user within a certain time.

[1544] Input: Parsed response result.

[1545] Output: Emergency contact is made.

[1546] Specific behavior: If there is no response from the user within a certain period of time, the server will automatically contact pre-defined emergency contacts (e.g., emergency services or family members) and report the emergency situation.

[1547] Step 6:

[1548] Daily support

[1549] The terminal provides daily support to the user in the form of voice dialogue.

[1550] Input: The user's voice command.

[1551] Output: Audio feedback.

[1552] Specific operation: When a user speaks to the device, for example, "Please tell me what my schedule is for today," the device processes the question using a voice recognition API and responds with appropriate information (such as the schedule) via voice.

[1553] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1554] This system receives data from multiple sensors installed in the home, monitors the user's living situation and health status, and automatically takes appropriate action if an abnormality is detected. The system is combined with an emotion engine that recognizes the user's emotions and adjusts daily support, enabling more personalized responses. The system consists of three main components: a server, a terminal, and the user.

[1555] System Configuration and Operation

[1556] Sensor placement and data collection

[1557] Server: Receives data in real time from various sensors installed in the house (motion sensor, temperature sensor, heart rate sensor, etc.). The server centrally manages this data and stores it with a timestamp. For example, the server receives data such as "no_movement" from the motion sensor, "60 BPM" from the heart rate sensor, and "22°C" from the temperature sensor.

[1558] Data analysis

[1559] Server: Analyzes the received sensor data and runs algorithms to detect inactivity and abnormal vital signs. Iactivity detection compares the current time with the time of the last detected movement to determine whether the person has been inactive for a certain period of time. It also determines an abnormality if the heart rate is outside the set normal range.

[1560] Anomaly detection and user notification

[1561] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?" The terminal will use voice recognition technology and an emotion engine to analyze the user's response and evaluate their emotional state. If the user responds, it will determine that there is no abnormality and provide feedback according to their emotional state.

[1562] Emergency response

[1563] Server: If no response is received from the user within a certain time, the server will automatically initiate action to call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[1564] Daily support

[1565] Terminal: Provides daily support through voice dialogue. For example, responds to user questions such as "What are your plans for today?" with appropriate information. Analyzes the user's emotions using an emotion engine and adjusts the support content according to their emotional state.

[1566] Specific Examples

[1567] Example 1: Daily support

[1568] 1. User: Says to the device, "What's on my schedule for today?"

[1569] 2. Device: Recognizes the user's question and uses an emotion engine to analyze the tone and pace of the user's voice. If it determines that the user is stressed, it notifies the user, "You have a regular checkup at 3 PM today, but we recommend that you take some time to relax." If the user is in a normal state, it notifies the user, "You have a regular checkup at 3 PM today."

[1570] Example 2: Emergency response

[1571] 1. Server: Receives data from sensors and detects inactivity for more than two hours.

[1572] 2. Terminal: Notifies the user by voice, "Please respond. Are you OK?". Analyzes the user's response using the emotion engine to determine their emotional state.

[1573] 3. User: No response.

[1574] 4. Server: No response within a certain time, so call emergency services.

[1575] Example 3: Detecting abnormalities in vital signs

[1576] 1. Server: Receives abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[1577] 2. Server: Analyzes the abnormality and determines that emergency action is required.

[1578] 3. Terminal: Notifies the user, "Please respond. Are you OK?". Analyzes the user's response using the emotion engine to determine their emotional state.

[1579] 4. User: No response.

[1580] 5. Server: Calls emergency services after no response within a certain time.

[1581] Example 4: Daily support based on emotional state

[1582] 1. User: Says to the device, "I'm feeling a little tired today."

[1583] 2. Terminal: Recognizes the user's speech and analyzes the user's level of fatigue using an emotion engine.

[1584] 3. Device: Notify: "Would you like to schedule more time for relaxation today?"

[1585] As described above, the system of the present invention uses sensors to monitor the living conditions and health status of residents in real time, and by combining it with an emotion engine, it individualizes responses when abnormalities are detected and daily support, providing an environment in which users can live with peace of mind.

[1586] The processing flow will be explained below.

[1587] Step 1:

[1588] Server: Receives data from various sensors (motion sensor, temperature sensor, heart rate sensor, etc.) in real time and stores it with a timestamp. For example, it receives data such as "Motion sensor: no_movement", "Heart rate sensor: 60 BPM", and "Temperature sensor: 22°C".

[1589] Step 2:

[1590] Server: Analyzes the received sensor data. To detect inactivity, it compares the current time with the time of the last detected movement to determine whether there has been inactivity for a certain period of time. It also determines that there is an abnormality if the heart rate is outside the set normal range.

[1591] Step 3:

[1592] Server: If an abnormality is detected based on the analysis results, proceed to the next step. If the condition is normal, switch to the daily support function. For example, if the user wants to know "today's schedule," provide schedule information.

[1593] Step 4:

[1594] Terminal: If an abnormality is detected, the terminal will notify the user by voice, "Please respond. Are you OK?". The emotion engine will analyze the user's response and evaluate their emotional state. If the user responds, it will be determined that there is no abnormality.

[1595] Step 5:

[1596] Server: If the user does not respond within a certain time frame, the server automatically calls emergency services, which can include pre-defined contacts (ambulance services, family, security companies, etc.).

[1597] Step 6:

[1598] Server: When calling emergency services, the server attempts to contact the emergency service as quickly as possible using multiple methods (telephone, email, SMS, etc.) and accurately communicates details of the emergency (e.g., "inactivity for more than two hours" or "heart rate below 50 BPM").

[1599] Step 7:

[1600] Terminal: Responds to user requests as a daily support function. When a user says, "Tell me what's on my schedule for today," the terminal retrieves schedule information from the server and notifies them by voice.

[1601] Step 8:

[1602] Emotion engine: Analyzes the tone, pace, and intonation of the user's voice to assess their emotional state. For example, if it determines that the user is stressed, it will offer advice on how to relax.

[1603] Step 9:

[1604] Device: Adjust daily support based on the results of the emotion engine. For example, if a user says, "I'm a little tired today," the device will notify them, "When adjusting your schedule for today, would you like us to suggest more time for relaxation?"

[1605] Step 10:

[1606] User: Use the daily support features to check their schedule and medication times. For example, they can say, "What's my schedule for today?" and receive notifications from the device. They can also respond to notifications from the device in the event of an emergency.

[1607] Specific Examples

[1608] Example 1: Daily support

[1609] Step 1: The user speaks to the device, "What's on my schedule for today?"

[1610] Step 2: The device recognizes the user's question and uses an emotion engine to analyze the tone and pace of the user's voice.

[1611] Step 8: If the device determines that the user is stressed, it notifies the user, "You have a regular checkup at 3 PM today, but we recommend that you take some time to relax." If the user is in a normal state, it notifies the user, "You have a regular checkup at 3 PM today."

[1612] Example 2: Emergency response

[1613] Step 1: The server receives data from the sensors and detects inactivity for more than two hours.

[1614] Step 4: The device notifies the user by voice, "Please respond. Are you OK?" The emotion engine analyzes the user's response and determines their emotional state.

[1615] Step 5: The user does not respond.

[1616] Step 6: The server does not respond within a certain time, so emergency services are called.

[1617] Example 3: Detecting abnormalities in vital signs

[1618] Step 1: The server receives an abnormal heart rate (e.g., below 50 BPM) from the heart rate sensor.

[1619] Step 2: The server analyzes the anomaly and determines that emergency action is required.

[1620] Step 4: The device notifies the user, "Please respond. Are you OK?" The emotion engine analyzes the user's response and determines their emotional state.

[1621] Step 5: The user does not respond.

[1622] Step 6: The server does not respond within a certain time, so emergency services are called.

[1623] Example 4: Daily support based on emotional state

[1624] Step 1: The user says to the device, "I'm feeling a little tired today."

[1625] Step 8: The device recognizes the user's speech and uses an emotion engine to analyze the user's level of fatigue.

[1626] Step 9: Your device will notify you, "Would you like us to suggest more time for relaxation for your schedule today?"

[1627] The above are the specific processing steps of the system of the present invention. At each step, the server, terminal, and user work in cooperation to safely and effectively support the lives of residents.

[1628] Example 2

[1629] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1630] In modern residential environments, there is a need to understand the living conditions and health status of residents in real time and respond quickly when abnormalities occur, but conventional systems have difficulty meeting these requirements. Furthermore, when it comes to supporting users' daily lives, they lack the ability to respond in detail to individual situations and emotions. Therefore, providing an environment where residents can live with peace of mind has become a challenge.

[1631] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving data such as movement, temperature, and heart rate from sensors installed in the house; means for centrally managing the received data and saving it with a timestamp; means for analyzing the received data and detecting inactivity or abnormal vital signs; means for issuing a voice notification when an abnormality is detected and analyzing the user's response using an emotion engine; means for calling emergency services when there is no response from the user; and means for providing support for daily life in the form of voice dialogue and using the emotion engine to provide support according to the user's emotional state. This makes it possible to provide an environment in which the user can live with peace of mind by monitoring the user's living situation and health condition in real time and taking necessary measures promptly.

[1632] A "sensor" is a device that is installed inside a home and collects data such as movement, temperature, and heart rate.

[1633] A "centralized management system" is a system that manages received data in one place and stores it with a timestamp.

[1634] The "analysis means" is a function that uses the received data to execute an algorithm for detecting immobility or abnormal vital signs.

[1635] An "emotion engine" is a technology that analyzes a user's emotional state and determines the appropriate response based on that.

[1636] "Emergency services" are contacts that are automatically contacted if there is no response from the user, and include ambulance services, family, security companies, etc.

[1637] "Voice notification" is a function that notifies the user by voice when an abnormality is detected.

[1638] "Voice interaction" refers to a format in which information is exchanged between a user and a system using voice.

[1639] MODE FOR CARRYING OUT THE INVENTION

[1640] This invention is a system that monitors the user's living situation and health status based on data from sensors installed in the home, and automatically responds if an abnormality is detected. This system consists of three main components: a server, a terminal, and the user.

[1641] Hardware or software used

[1642] The main hardware and software required to implement this system are as follows:

[1643] 1. Sensors: Multiple types of sensors, such as motion sensors, temperature sensors, heart rate sensors, etc.

[1644] 2. Server: A central device that receives, analyzes, stores, detects anomalies, and handles emergency responses.

[1645] 3. Terminal: A device that provides voice notifications, voice interaction, emotion engine analysis, and support for daily life.

[1646] Data processing and calculation

[1647] 1. Data Collection:

[1648] The server receives real-time data such as temperature and heart rate from various sensors installed inside the home and stores it in a centralized management system with a timestamp.

[1649] 2. Data Analysis:

[1650] The server runs an analysis algorithm based on the received data to detect inactivity or abnormal vital signs. To detect inactivity, it compares the current time with the time of the last detected movement and determines whether the person has been inactive for a certain period of time (e.g., two hours). It also determines an abnormality if the heart rate exceeds a set range (e.g., 50 BPM to 100 BPM).

[1651] 3. User response analysis:

[1652] The device has a means for issuing a voice notification when an abnormality is detected, and uses an emotion engine to analyze the user's response and evaluate their emotional state. For example, if the user responds "Yes, I'm fine," the emotion engine evaluates whether the user is calm.

[1653] 4. Emergency Response:

[1654] The server has a mechanism to automatically call emergency services if no response is received from the user within a certain time (e.g., 5 minutes), and has the ability to contact pre-defined contacts (e.g., emergency services, family, security companies, etc.).

[1655] 5. Daily support:

[1656] The device provides support for the user's daily life through voice dialogue, and uses an emotion engine to provide appropriate information according to the user's emotional state. For example, if a user says, "What are your plans for today?", the emotion engine analyzes the tone and pace of the user's voice. If it determines that the user is stressed, it will notify the user, "You have a regular checkup at 3:00 p.m. today, but we recommend that you take some time to relax."

[1657] Prompt Sentence Examples

[1658] Examples of prompts to input to a generative AI model include:

[1659] "Analyze the data from the sensors and explain how you will respond if there are any abnormalities."

[1660] "Recognize the user's emotions and tell me how to provide support based on those emotions."

[1661] The system of the present invention, which includes the above functions, makes it possible to monitor a user's living situation and health condition in real time and take necessary measures quickly, thereby providing an environment in which the user can live with peace of mind.

[1662] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1663] Step 1: Collect sensor data

[1664] The server receives real-time data from sensors installed in the home, such as movement, temperature, and heart rate. The input is the data sent from each sensor (e.g., "no_movement," "22°C," "60 BPM"), and the output is to store this data with a timestamp in a centralized management system. Specifically, the sensors send their measurements to the server, which receives the data and stores it in a database.

[1665] Step 2: Analyze the data

[1666] The server analyzes the collected data. The input is the stored sensor data with a timestamp, and the output is the detection of inactivity or abnormal vital signs. Specifically, the server compares the timestamps of the motion sensor data and checks whether inactivity has continued for a certain period of time (for example, two hours). It also analyzes whether the heart rate data is within a set range (50 BPM to 100 BPM).

[1667] Step 3: Anomaly detection

[1668] The server detects abnormalities based on the analysis results. The input is the analyzed data, and the output is information that an abnormality has been detected. Specifically, if inactivity or an abnormal heart rate is detected, the server records that information and determines that this is an abnormal condition that requires proceeding to the next processing step.

[1669] Step 4: User Notification

[1670] If an abnormality is detected, the device will notify the user by voice. The input is notification data from the server indicating the abnormality, and the output is the voice notification and a response from the user. Specifically, the device will notify by voice, "Please respond. Are you OK?", receive the user's response via the microphone, convert it into text data, and pass it to the emotion engine.

[1671] Step 5: User response analysis

[1672] The device uses an emotion engine to analyze the user's response. The input is text data converted from the user's voice response, and the output is the user's emotional state. Specifically, the device inputs the text data analyzed from the voice into the emotion engine, which evaluates whether the user is calm or stressed.

[1673] Step 6: Emergency response

[1674] If the server does not receive a response from the user within a certain time (e.g., 5 minutes), it automatically calls emergency services. The input is the user's no-response information, and the output is a call to emergency services. Specifically, the server automatically calls and sends messages to pre-defined contacts (e.g., 119, family, security company).

[1675] Step 7: Daily support

[1676] The device provides support for daily life through voice dialogue. The input is questions or requests from the user, and the output is appropriate information or advice. In concrete terms, when a user says, "What are your plans for today?", the device uses an emotion engine to analyze the tone and pace of the user's voice and assess whether they are feeling stressed. If they are feeling stressed, the device will notify them, "You have a regular checkup at 3:00 PM today, but we recommend that you take some time to relax," and if they are feeling normal, it will notify them, "You have a regular checkup at 3:00 PM today."

[1677] As described above, by performing specific data processing or calculations based on the input data at each step and passing the output to the next step, it is possible to monitor the user's living situation and health condition in real time and take any necessary measures quickly.

[1678] (Application example 2)

[1679] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1680] In modern living environments and brick-and-mortar stores, real-time monitoring systems for the health and safety of residents, store staff, and customers are important, but current technology often cannot adequately address these issues. There is a particular need for emergency response and daily life support that is tailored to each individual. In addition to monitoring, there is also a need for personalized responses using emotion engines.

[1681] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1682] In this invention, the server includes means for receiving data such as movement, temperature, and heart rate from sensors installed in the home or store, means for analyzing the received data and detecting inactivity or abnormal vital signs, means for calling emergency services if there is no response from the user, means for providing support for daily life in the form of voice dialogue, means for receiving data from sensors installed in the store and monitoring the behavior of store staff and customers, means for analyzing the received data to detect abnormalities and notifying store staff, and means for analyzing and evaluating the emotions of store staff using an emotion engine along with responses.This improves the safety and health of users, store staff, and customers, and enables individually tailored support and emergency responses.

[1683] "Sensors installed inside the home" refers to various sensors installed inside the home, which are devices for collecting data such as movement, temperature, and heart rate.

[1684] A "motion sensor" is a sensor used to detect motion and to monitor inactivity.

[1685] A "temperature sensor" is a sensor for detecting the ambient temperature and for monitoring changes in the temperature of the environment.

[1686] A "heart rate sensor" is a sensor that measures an individual's heart rate and is used to monitor vital signs.

[1687] A "means for receiving data" is a method or device for acquiring data sent from a sensor.

[1688] A "means for analyzing data" is a method or device for processing received data and detecting abnormal conditions or patterns.

[1689] "Means for invoking emergency services" means a method or device for notifying emergency services or relevant authorities when an abnormality is detected and there is no response from the user.

[1690] The "means for providing in the form of voice interaction" refers to a method or device for interacting with a user using voice to provide support for daily life.

[1691] "Sensors installed in stores" refer to various sensors installed in commercial facilities, and are devices for monitoring the movements and status of store staff and customers.

[1692] An "emotion engine" is an algorithm or device that analyzes the emotional state of users and store clerks and makes appropriate evaluations.

[1693] The "means for notifying a store clerk" is a method or device for notifying a store clerk when an abnormality is detected.

[1694] "Means for analyzing and evaluating emotions" refers to a method or device for analyzing and evaluating the emotional state of a user or store clerk.

[1695] This invention is a system that receives data from multiple sensors installed in homes and stores, monitors the user's living situation and health status, and automatically takes appropriate action if an abnormality is detected. Furthermore, by combining it with an emotion engine, it can recognize the emotions of users, store clerks, and customers and provide individually tailored daily support and emergency responses.

[1696] Hardware and Software Configuration

[1697] 1. Sensor System

[1698] Various sensors (such as motion sensors, temperature sensors, and heart rate sensors) are placed in homes and stores to monitor the environment and personal vital signs in real time.

[1699] 2. Server

[1700] The server receives and centralizes data from various sensors, stores it with a timestamp, analyzes the data, and runs algorithms to detect inactivity or abnormal vital signs. If an abnormality is detected, the server can call emergency services as an appropriate response.

[1701] 3. Terminal

[1702] The terminal provides daily support to users and store staff through voice interaction, utilizing voice recognition technology (e.g., Google Speech-to-Text API) and emotion engines (e.g., Emotion API) to analyze the user's responses and emotional state and provide appropriate feedback.

[1703] System Operation

[1704] Receiving and storing data

[1705] The server receives real-time data from each sensor in a home or store and manages it centrally. For example, it receives data such as "no_movement" from a motion sensor, "22°C" from a temperature sensor, and "60 BPM" from a heart rate sensor. This data is saved with a timestamp.

[1706] Data analysis and anomaly detection

[1707] The server analyzes the received data and detects an abnormality, for example, if the device is inactive for a certain period of time or if the heart rate is outside the normal range.

[1708] Notification and Response

[1709] If an abnormality is detected, the device will notify the user or store clerk by voice, saying, "Please respond. Are you OK?" The device will use an emotion engine to analyze the user's or store clerk's response and evaluate their emotional state. If the user or store clerk responds, it will provide appropriate feedback based on their response.

[1710] Emergency response

[1711] If no response is received from the user or store staff within a certain time frame, the server will automatically call emergency services, which may include pre-defined contacts (ambulance services, family, security companies, etc.).

[1712] Specific examples

[1713] When a user says to the device, "I feel a little tired today," the device will recognize the voice, analyze the user's level of fatigue using an emotion engine, and notify the user, "Would you like us to suggest that you increase your relaxation time when adjusting your schedule for today?"

[1714] If the store's motion sensors detect inactivity for more than two hours, the device will issue a voice message saying, "Please respond. Are you OK?" and will call emergency services if there is no response.

[1715] Prompt Sentence Examples

[1716] "How can we build a system that uses data from sensors in the home to monitor the user's health and take appropriate action if an abnormality is detected?"

[1717] As a result, this system improves the safety and health of users, store staff, and customers, and enables individually tailored support and rapid emergency response.

[1718] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1719] Step 1:

[1720] Receiving data

[1721] The server receives data in real time from various sensors (motion sensors, temperature sensors, heart rate sensors, etc.) installed in homes and stores.

[1722] (Input) Data from each sensor (e.g., movement sensor -> "no_movement", temperature sensor -> "22°C", heart rate sensor -> "60BPM")

[1723] (Output) Sensor data with timestamp

[1724] (Specific operation) The server receives data sent from each sensor through the interface and stores the data in a centralized database with a timestamp.

[1725] Step 2:

[1726] Data analysis

[1727] The server analyzes the received sensor data and executes algorithms to detect abnormal conditions, such as inactivity or abnormal vital signs.

[1728] (Input) Time-stamped sensor data

[1729] (Output) Anomaly detection result (e.g., "Normal", "Abnormal", "No operation", etc.)

[1730] (Specific operation) The server analyzes the sensor data using a preset anomaly detection algorithm (for example, determining periods of inactivity) and determines whether an anomaly has occurred.

[1731] Step 3:

[1732] Abnormal notification

[1733] If an abnormality is detected, the server sends a notification to the terminal, which then issues a voice message to the user or store clerk saying, "Please respond. Are you OK?"

[1734] (Input) Anomaly detection results

[1735] (Output) The execution status of the voice notification (e.g., "Notification sent").

[1736] (Specific Operation) When an abnormality is notified from the server, the terminal uses its voice synthesis function to generate a voice message and notifies the user or store clerk through the speaker.

[1737] Step 4:

[1738] User Response and Sentiment Analysis

[1739] When a user or a store clerk responds to the terminal, the terminal uses voice recognition technology to convert the response into text data and uses an emotion engine to analyze the emotion.

[1740] (Input) User or store clerk's voice response

[1741] (Output) Analyzed emotional state (e.g., "stressed," "normal," etc.)

[1742] (Specific operation) The device uses voice recognition technology such as the Google Speech-to-Text API to convert speech into text, and then inputs the text data into the Emotion API to analyze the emotional state.

[1743] Step 5:

[1744] Providing feedback

[1745] Based on the analysis results, the terminal provides appropriate feedback to the user or store clerk via voice.

[1746] (Input) Analyzed emotional state

[1747] (Output) Feedback message (e.g. "Relax" or "Everything is fine")

[1748] (Specific operation) The terminal selects a feedback message based on the analysis results, generates a voice message using the voice synthesis function, and transmits it to the user or store clerk through the speaker.

[1749] Step 6:

[1750] Emergency response

[1751] If the user or store attendant does not respond within a certain time, the server automatically calls emergency services.

[1752] (Input) Response waiting time and re-detection result

[1753] (Output) The execution status of the emergency call (e.g., "Emergency services called").

[1754] (Specific operation) The server confirms that the pre-set response waiting time has elapsed and automatically sends a notification to emergency contacts (emergency services, family, security company, etc.).

[1755] Through the above processing steps, this system improves the safety and health of users, store staff, and customers, and enables individually tailored support and rapid emergency response.

[1756] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1757] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1758] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1759] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1760] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1761] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1762] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1763] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1764] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1765] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1766] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1767] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1768] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1769] 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.

[1770] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1771] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1772] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1773] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1774] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1775] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1776] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1777] The following is further disclosed regarding the above embodiment.

[1778] Understood. Below are the draft claims, which are based on the core of the invention and its technical features.

[1779] (Claim 1)

[1780] A means for receiving data such as movement, temperature, and heart rate from sensors installed in the home;

[1781] A means for analyzing the received data and detecting inactivity or abnormal vital signs;

[1782] means for calling emergency services if there is no response from the user;

[1783] A means of providing support for daily life in the form of voice dialogue;

[1784] A system including:

[1785] (Claim 2)

[1786] 10. The system of claim 1, wherein the sensors include multiple types of sensors located at different locations.

[1787] (Claim 3)

[1788] 2. The system according to claim 1, wherein the analyzing means has an algorithm for determining an abnormality when no operation continues for a certain period of time.

[1789] "Example 1"

[1790] (Claim 1)

[1791] means for receiving data from a plurality of sensors installed within the home;

[1792] A means for analyzing the received data and detecting inactivity or abnormal vital signs;

[1793] a means for notifying a user by voice of a detected abnormality;

[1794] means for calling emergency services if there is no response from the user;

[1795] A means of providing support for daily life in the form of voice dialogue;

[1796] A system including:

[1797] (Claim 2)

[1798] 10. The system of claim 1, wherein the sensors include multiple types of sensors located at different locations.

[1799] (Claim 3)

[1800] 2. The system of claim 1, wherein the analysis means comprises an algorithm for determining periods of inactivity or abnormal vital signs.

[1801] "Application Example 1"

[1802] (Claim 1)

[1803] A means for receiving data such as movement, temperature, and heart rate from sensors installed in the home;

[1804] A means for analyzing the received data and detecting inactivity or abnormal vital signs;

[1805] means for calling emergency services if there is no response from the user;

[1806] A means of providing support for daily life in the form of voice dialogue;

[1807] A means to monitor data from sensors in real time and send an alarm notification to a smartphone when an abnormality is detected.

[1808] means for analyzing a response using voice recognition technology if the user does not respond to the voice notification;

[1809] A means for automatically contacting emergency personnel if the user does not respond;

[1810] A system including:

[1811] (Claim 2)

[1812] 10. The system of claim 1, wherein the sensors include multiple types of sensors located at different locations.

[1813] (Claim 3)

[1814] 2. The system according to claim 1, wherein the analyzing means has an algorithm for determining an abnormality when no operation continues for a certain period of time.

[1815] "Example 2: Combining Emotion Engines"

[1816] (Claim 1)

[1817] A means for receiving data such as movement, temperature, and heart rate from sensors installed in the home;

[1818] A means to centrally manage received data and store it with a timestamp,

[1819] A means for analyzing the received data and detecting inactivity or abnormal vital signs;

[1820] means for issuing a voice notification when an abnormality is detected and analyzing the user's response using an emotion engine;

[1821] means for calling emergency services if there is no response from the user;

[1822] A means for providing support for daily life in the form of voice dialogue and providing support according to the emotional state of the user using an emotion engine;

[1823] A system including:

[1824] (Claim 2)

[1825] 10. The system of claim 1, wherein the sensors include multiple types of sensors located at different locations.

[1826] (Claim 3)

[1827] 2. The system according to claim 1, wherein the analysis means has an algorithm for determining an abnormality when no movement continues for a certain period of time, and detects an abnormality even when the heart rate is outside a set range.

[1828] "Application example 2 when combining emotion engines"

[1829] (Claim 1)

[1830] A means for receiving data such as movement, temperature, and heart rate from sensors installed in the home;

[1831] A means for analyzing the received data and detecting inactivity or abnormal vital signs;

[1832] means for calling emergency services if there is no response from the user;

[1833] A means of providing support for daily life in the form of voice dialogue;

[1834] A means for receiving data from sensors installed in the store and monitoring the behavior of store staff and customers;

[1835] A means for analyzing the received data to detect abnormalities and notify store staff;

[1836] A means for analyzing and evaluating the emotions of the store clerk using an emotion engine along with the response;

[1837] A system including:

[1838] (Claim 2)

[1839] 10. The system of claim 1, wherein the sensors include multiple types of sensors located at different locations.

[1840] (Claim 3)

[1841] 2. The system according to claim 1, wherein the analyzing means has an algorithm for determining an abnormality when no operation continues for a certain period of time. [Explanation of symbols]

[1842] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving data such as movement, temperature, and heart rate from sensors installed in the home; A means for analyzing the received data and detecting inactivity or abnormal vital signs; means for calling emergency services if there is no response from the user; A means of providing support for daily life in the form of voice dialogue; A system including:

2. The system of claim 1 , wherein the sensor comprises multiple types of sensors located at different locations.

3. 2. The system according to claim 1, wherein said analyzing means has an algorithm for determining an abnormality when no operation continues for a certain period of time.

Images