system

Abstract

Provide a system. A method for collecting real-time data from a sensor; means for transmitting the collected data to a server; A means for analyzing the received data on the server and detecting a dangerous situation; means for generating an audible warning based on the detected hazardous condition; a means for notifying a parent's device of the detected dangerous situation; 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] Children approaching dangerous places or objects within the home is a major source of anxiety for parents. Because unexpected accidents can occur the moment parents are not paying attention, effective measures to ensure safety are needed. Existing safety measures are limited, and parents often have to constantly monitor their children directly. Furthermore, many existing warning systems only function after danger has occurred, and are unable to prevent it in advance. Therefore, there is a need for a system that can automatically detect when a child approaches a dangerous place or object and immediately issue a warning. Furthermore, it is expected that systems with the ability to learn children's behavioral patterns and predict danger in advance will provide even greater safety. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means. First, a means is provided for collecting data in real time from sensors in the home. This allows for accurate understanding of the child's location and the surrounding environmental conditions. Next, a means is provided for transmitting the collected data to a server. This allows for centralized data management and makes analysis easier. Furthermore, a means is provided for analyzing the received data on the server and detecting whether the child is approaching a dangerous place or object. By providing a means for generating an alarm based on the detected dangerous situation, a warning can be issued to the child immediately. In addition, by providing a means for notifying the parent's terminal of the detected dangerous situation, the parent can grasp the child's situation even remotely and respond quickly. This provides a system that increases parents' sense of security and ensures the safety of their children.

[0006] A "sensor" is a device that detects the environment, movement, position, temperature, humidity, etc. of objects and acquires the data.

[0007] "Real-time data" refers to the latest data collected and provided by sensors immediately based on the current situation.

[0008] A "server" is a computer system that receives and analyzes the collected data.

[0009] "Analysis" is the process of evaluating collected data to recognize specific conditions or patterns.

[0010] A "dangerous situation" refers to a situation in which a child is near a potentially dangerous place or object.

[0011] An "alert sound" is an acoustic signal, such as a voice message or beep, that is generated to indicate a particular condition.

[0012] A "parent device" is a smartphone, tablet, or other communication device for receiving notifications.

[0013] A "notification" is a message or alert that notifies the user (parent) of a particular event or situation. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

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

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] The system of the present invention consists of multiple sensors installed in the home, a server that processes and analyzes the data, and a device (parent's smartphone or tablet) that receives notifications. This system collects data in real time to ensure the safety of children, detects dangerous situations, and generates an alarm to notify parents.

[0036] Sensor installation and operation

[0037] The sensors included in the device consist of a camera, motion sensors, and environmental sensors. The camera captures video data in real time and tracks the child's movements. The motion sensor detects whether the child is approaching a specific dangerous area (e.g., the kitchen or stairs). The environmental sensor collects environmental data such as temperature and humidity to monitor whether the child is in a safe environment.

[0038] Data collection and transmission

[0039] The device collects data from these sensors in real time and transmits it to a server at regular intervals. The collected data includes the child's location, movement, temperature, humidity, etc. This data is converted into a format that the server can understand and transmitted via a communication module.

[0040] Data analysis and risk detection

[0041] The server analyzes the received data. This analysis involves comparing the child's current location with past behavioral patterns. Specifically, if the child stays in a specific area for a certain amount of time or repeats a certain behavior, the server compares this with past data to predict danger.

[0042] For example, if a child is near an electrical outlet, the server analyzes their location information and determines the danger based on similar behavior patterns in the past. In this case, before the child actually touches the outlet, the server detects the danger and sends a warning signal to the device.

[0043] Warning sound generation

[0044] The device immediately generates a warning sound based on the warning signal received from the server. This warning sound may be a voice message or a beep to warn the child of the danger. For example, a voice message saying "Do not touch the outlet" is played.

[0045] Parental Notification

[0046] At the same time, the server generates a message to notify the parent of the danger. This message is sent to the smartphone or tablet in the form of an app notification or email. For example, a warning message saying "Your child is approaching an electrical outlet" can be sent, allowing the parent to take immediate action.

[0047] Specific examples

[0048] Example 1: What to do if a child approaches an electrical outlet

[0049] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0050] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0051] 3. The server recognizes the danger and sends a command to the terminal to generate an alarm sound.

[0052] 4. The device will emit a warning sound saying "Do not touch the power outlet."

[0053] 5. The server sends a notification to the parent's device saying, "Your child is approaching an outlet."

[0054] Example 2: What to do if a child tries to open a window

[0055] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0056] 2. The device sends the collected data to the server.

[0057] 3. The server analyzes the data and determines that the child is trying to open the window.

[0058] 4. The server sends a command to the terminal to generate an alarm sound.

[0059] 5. The device will emit a warning sound saying "Do not open the window."

[0060] 6. The server sends a notification to the parent's device saying, "Your child is trying to open a window."

[0061] Such systems will dramatically improve the safety of children and allow parents to go about their daily lives with peace of mind.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] The device initializes the sensors and checks that the camera, motion sensor, and environmental sensor are working properly, so the sensors are ready to work properly.

[0065] Step 2:

[0066] The device receives real-time data from initialized sensors: a camera detects the child's location, motion sensors detect surrounding movement, and environmental sensors measure temperature and humidity.

[0067] Step 3:

[0068] The device formats the acquired real-time data for transmission to the server, including the child's location, movement, temperature, and humidity.

[0069] Step 4:

[0070] The terminal sends the formatted data to the server via a communication module, so that the collected data reaches the server for analysis.

[0071] Step 5:

[0072] The server receives data transmitted from the terminal, including the child's location information, movement information, and environmental data.

[0073] Step 6:

[0074] The server analyzes the received data to determine if a dangerous situation is occurring, which involves matching the child's current location with past behavioral patterns.

[0075] Step 7:

[0076] The server sends a command to the terminal to generate an alarm when a danger is detected.

[0077] Step 8:

[0078] The terminal receives the warning command from the server and generates a designated warning sound, which includes a voice message such as "Do not touch the outlet."

[0079] Step 9:

[0080] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email.

[0081] Step 10:

[0082] The user (parent) receives the notification from the server, checks the child's current status, and takes appropriate action. For example, the parent who receives the notification may go and check on the child in person.

[0083] Example 1

[0084] 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."

[0085] Conventional child safety monitoring systems have limitations in ensuring safety due to the difficulty of detecting danger in real time and notifying parents promptly. In particular, they are unable to predict danger based on specific behavioral patterns or environmental data, which can delay parents from taking appropriate action.

[0086] 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.

[0087] In this invention, the server includes a means for transmitting data collected by the terminal to the server at regular intervals, a means for converting the data received by the server into an understandable format, and a means for comparing past behavioral patterns with real-time location information in data analysis, thereby enabling real-time danger detection and prompt notification.

[0088] "Sensors" are devices for detecting specific conditions within the home, including cameras, motion sensors, and environmental sensors.

[0089] "Real-time data" refers to data on the current situation or environment obtained by sensors, which is processed and transmitted immediately.

[0090] "Server" means a device or system that receives and analyzes data sent from a terminal and issues alerts based on specific conditions.

[0091] "Warning sounds" are sounds used to warn users, such as voice messages or beeps, that are generated when a dangerous situation is detected.

[0092] A "parent device" is a device that receives alert notifications about the child's status, and refers to a smartphone or tablet owned by the parent.

[0093] "Data transmission" is the communication process of transferring collected data from the terminal to the server.

[0094] "Data reformatting" is the process of converting data received at a server into a format that can be parsed.

[0095] "Data analysis" is the process of identifying specific patterns or situations based on received data and detecting dangers.

[0096] "Dangerous situations" refer to situations in which a child approaches a dangerous area or performs a dangerous action.

[0097] An "interval" refers to a fixed time interval set when transmitting or processing data.

[0098] "Behavioral patterns" refer to a child's tendency to move and perform a series of actions, analyzed based on past data.

[0099] A "warning signal" is a signal generated by a server and sent to a terminal to notify it of a dangerous situation.

[0100] The system of the present invention consists of multiple sensor devices installed in the home, a server that processes and analyzes the data, and a terminal (parent's smartphone or tablet) for receiving notifications. The main purpose of this system is to ensure the safety of children, collecting data in real time, detecting dangerous situations, and notifying parents with an alarm.

[0101] Sensor installation and operation

[0102] The device manages sensors installed in the home. These sensors include cameras, motion sensors, and environmental sensors. Specifically, the camera sensors capture video data in real time and track children's movements. The motion sensors detect whether children are approaching specific dangerous areas (e.g., the kitchen or stairs), and the environmental sensors capture environmental data such as temperature and humidity.

[0103] Data collection and transmission

[0104] The device collects data from sensors in real time and transmits it to a server at regular intervals. The data includes the child's location, movement, and environmental data, and is transferred to the server via a communication module.

[0105] Receiving and formatting data

[0106] The server receives the data sent from the device and converts it into a format that can be analyzed. For example, video data is converted into a format that can be analyzed using an image processing algorithm.

[0107] Data analysis

[0108] The server then analyzes the received data. This analysis involves comparing real-time location information with past behavioral patterns. Specific examples include determining whether a person has stayed in a specific area for a certain amount of time or whether they have repeatedly performed a specific action.

[0109] Hazard detection and warning signal transmission

[0110] If the server detects a dangerous situation based on the data analysis, it will send a warning signal to the device. For example, if a child stays near an electrical outlet for a certain period of time, the server will generate a warning signal based on this information.

[0111] Warning sound generation

[0112] The device immediately generates a warning sound based on the warning signal received from the server. The warning sound is a voice message or a beep to warn the child of the danger. For example, a voice message saying "Do not touch the outlet" is played.

[0113] Parental Notification

[0114] When a danger is detected, the server sends a notification to the parent's device. The notification can be sent via push notification in the app or via email. For example, a warning message saying "your child is approaching an electrical outlet" can be sent to the parent's smartphone or tablet, allowing the parent to take prompt action.

[0115] Specific examples

[0116] Example 1: What to do if a child approaches an electrical outlet

[0117] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0118] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0119] 3. The server recognizes the danger and sends a command to the terminal to generate an alarm sound.

[0120] 4. The device will emit a warning sound saying "Do not touch the power outlet."

[0121] 5. The server sends a notification to the parent's device saying, "Your child is approaching an outlet."

[0122] Example 2: What to do if a child tries to open a window

[0123] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0124] 2. The device sends the collected data to the server.

[0125] 3. The server analyzes the data and determines that the child is trying to open the window.

[0126] 4. The server sends a command to the terminal to generate an alarm sound.

[0127] 5. The device will emit a warning sound saying "Do not open the window."

[0128] 6. The server sends a notification to the parent's device saying, "Your child is trying to open a window."

[0129] Prompt Sentence Examples

[0130] Example prompts to input to a generative AI model:

[0131] "Please explain the program process for a system that uses sensors installed in the home to monitor child safety. The sensors are cameras, motion sensors, and environmental sensors. A server analyzes the data and sends a notification to the parent's device if a danger is detected. As a concrete example, please explain the processing flow when a child approaches an electrical outlet and when they try to open a window."

[0132] In this way, the present invention ensures the safety of children and provides an environment in which parents can live with peace of mind.

[0133] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0134] Step 1: Acquiring data from the sensor

[0135] The device collects real-time data from various sensors (cameras, motion sensors, and environmental sensors) installed in the home. For example, the camera sensor collects video data, and the motion sensor detects when a child approaches a specific dangerous area. The environmental sensor measures the temperature and humidity inside the room. The input includes raw data from the sensors, and the output is formatted data. Specifically, the video data is saved frame by frame, and the motion sensor data is saved as location information.

[0136] Step 2: Sending data

[0137] The terminal transmits the acquired data to the server at regular intervals. The input is the formatted data acquired from the sensor, and the output is the transmitted data sent to the server. Specifically, a communication module is used to transfer the data to the server in JSON format or similar. Each piece of data is given a timestamp to maintain consistency.

[0138] Step 3: Receiving and formatting data

[0139] The server receives data sent from the device. The received data includes location information, motion information, temperature, humidity, etc. The input is the raw data sent from the device, and the output is data formatted into an analyzable format. Specifically, the data is temporarily stored and formatted as needed using image processing algorithms and data analysis algorithms.

[0140] Step 4: Analyze the data

[0141] The server analyzes the received data. The input is formatted data, and the output is analysis results. Specifically, it compares real-time location information with past behavioral patterns to identify specific behavioral patterns and environmental conditions. Examples include when an individual has stayed in the same area for a certain period of time, or when environmental data has reached a dangerous value.

[0142] Step 5: Detect danger and send a warning signal

[0143] If the server detects a dangerous situation as a result of data analysis, it sends a warning signal to the device. The analysis results are input, and a warning signal is generated as output. Specifically, if a child stays near an electrical outlet for a long time, for example, a warning signal is generated and sent to the device.

[0144] Step 6: Sound the alarm

[0145] The terminal immediately generates a warning sound based on the warning signal received from the server. The received warning signal is the input, and the generated warning sound is the output. For example, a voice message saying "Do not touch the outlet" is played to warn children.

[0146] Step 7: Parental Notification

[0147] The server sends a notification to the parent's device when a danger is detected. The input is the detection result, and the output is a warning message sent to the parent's smartphone or tablet. Specifically, a message such as "Your child is approaching an outlet" is sent immediately, allowing the parent to check the situation and take prompt action.

[0148] This is the flow of the program processing for this system. In this way, the system is able to detect danger in real time and respond quickly, ensuring the safety of children.

[0149] (Application example 1)

[0150] 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."

[0151] Conventional home security systems lack the real-time and multifaceted capabilities to ensure children's safety. In particular, notifying parents alone when an abnormality occurs often results in delayed response, which is a major problem when response is required outside the home. Therefore, there is a need to develop a system that utilizes home sensors to instantly detect abnormalities and notify parents and a security center.

[0152] 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.

[0153] In this invention, the server includes means for collecting real-time data from the sensors, means for transmitting the collected data to the server, means for analyzing the received data on the server and detecting dangerous situations, means for generating an alarm based on the detected dangerous situation, and means for notifying the parent's terminal and the security center of the detected dangerous situation. This allows the parent and the security center to be notified simultaneously when an abnormality occurs, enabling a rapid and multifaceted response.

[0154] A "sensor" is a device that detects physical conditions or changes and collects that data.

[0155] "Real-time data" refers to data that is collected continuously by sensors and is immediate and has no time delay.

[0156] A "server" is a central computer system for collecting, analyzing, processing, and transmitting data.

[0157] A "dangerous situation" is a situation that is detected by a sensor and analyzed by a server, and determines that there is a potential risk to a child or the home.

[0158] A "warning sound" is an alert that is generated as a voice or beep when a dangerous situation is detected.

[0159] A "parent device" is a device, such as a smartphone or tablet, that is owned by the parent and used to receive notifications.

[0160] A "security center" is a specialized institution that handles security measures outside the home, and is a facility that responds quickly upon receiving notification of an abnormality.

[0161] "Notification" is a communication that informs the parent's device or security center of a dangerous situation detected by the server.

[0162] As an embodiment of the present invention, the following system is constructed. First, multiple sensors are installed in a home. These sensors include cameras, motion sensors, and environmental sensors. As a specific example, the cameras track children's movements and collect video data in real time. The motion sensors detect when a child approaches a specific dangerous area (e.g., the kitchen or stairs). The environmental sensors acquire environmental data such as temperature and humidity, and monitor whether the child is living in a safe environment.

[0163] The collected data is transmitted to a server via a Wi-Fi module. The server is equipped with data analysis software that includes a Python®-based machine learning model, which analyzes the transmitted data in real time. This analysis uses an anomaly detection algorithm to detect an anomaly when a specified condition is met (e.g., a child getting too close to the door).

[0164] If an abnormality is detected, the server simultaneously sends a warning signal to the parent device (smartphone or tablet) and the security center. The parent device immediately displays a notification and generates an audible warning (voice message or beep) based on the received warning signal. The security center displays an abnormality notification on its web dashboard, allowing an operator to initiate response procedures.

[0165] For example, here is a specific example of a child trying to open a door:

[0166] 1. In-home sensors detect children's movements and collect data on their approach to the door.

[0167] 2. The sensor sends the data to the server.

[0168] 3. The server analyzes the data and determines that a child is trying to open the door.

[0169] 4. The server sends a command to the parent's smartphone to generate an alarm sound and simultaneously sends an alert to the security center.

[0170] 5. A parent's smartphone will emit a warning sound saying "Do not open the door."

[0171] 6. The security center will have an operator respond (e.g., check the camera footage and dispatch security guards).

[0172] Additionally, to perform anomaly analysis using a generative AI model, the following prompts can be used:

[0173] Example prompt sentence:

[0174] “Your child is opening a door in your home, please analyze the information below and provide safety measures.

[0175] Child's current location: Living room

[0176] Operational Information: Standing upright near the door

[0177] Environmental data: 19°C, 40% humidity

[0178] Video feed: [Real-time video URL]

[0179] Required actions:

[0180] 1. Send a warning message to the parent's smartphone

[0181] 2. Send an alert to the Security Center

[0182] 3. Triggering an audio warning

[0183] Such a system will strengthen security within the home and enable rapid and multifaceted response in the event of an emergency.

[0184] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0185] Step 1:

[0186] In-home sensors collect real-time data on children's behavior and environment. Specifically, cameras monitor children's movements and record the footage as digital data. Motion sensors detect approach to specific danger areas, and environmental sensors measure temperature and humidity. This data is temporarily stored in local storage.

[0187] Input: Child's movement information, environmental data

[0188] Output: Collected real-time data (video data, motion data, environmental data)

[0189] Step 2:

[0190] The collected real-time data is sent to a server via a home communication module. Specifically, the data is sent in bulk in packet format using a Wi-Fi module. During this process, the data is reformatted (for example, converted to JSON format).

[0191] Input: Collected real-time data (video data, behavior data, environmental data)

[0192] Output: Data packets sent to the server

[0193] Step 3:

[0194] The server analyzes the received data. It uses a Python-based machine learning model to execute an anomaly detection algorithm. Specifically, it compares current data with past data to detect abnormal patterns (such as a child approaching a door). Data processing includes time series analysis and clustering.

[0195] Input: Data packet sent to the server

[0196] Output: Detected abnormal patterns

[0197] Step 4:

[0198] If the server detects an abnormal pattern, it generates a warning signal, which includes details of the abnormal situation (e.g., a child trying to open a door), and generates an appropriate countermeasure by inputting a prompt sentence into the generative AI model.

[0199] Input: Detected abnormal pattern

[0200] Output: Warning signal, action to be taken based on the prompt

[0201] Step 5:

[0202] The server sends the generated warning signal and countermeasures to the parent device and the security center. The parent device displays a warning message and an alarm sound. At the same time, an alert is sent to the security center and displayed on the center's dashboard.

[0203] Input: Warning signals, countermeasures based on prompts

[0204] Output: Notifications on parent's device, Security Center alerts

[0205] Step 6:

[0206] When the parent device receives the warning message, the user can take action based on the message. At the same time, security center operators also check the dashboard and take action, such as dispatching security guards to the scene, if necessary.

[0207] Input: Parental device notifications, Security Center alerts

[0208] Output: User response, Security Center action

[0209] This process allows parents and security centers to respond quickly and effectively when a child faces a dangerous situation at home.

[0210] 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.

[0211] This invention provides a system for ensuring children's safety at home, and is composed of sensors, a server, a terminal, and an emotion engine. This system detects dangerous situations for children based on real-time data obtained from the sensors, generates an alarm, and notifies parents. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, the system has the function of adjusting the alarm sound and notification content according to the user's emotional state.

[0212] Sensor installation and operation

[0213] The device is equipped with a camera, motion sensors, and environmental sensors. The camera captures images of the child in real time, the motion sensors detect the child's proximity and movement, and the environmental sensors measure temperature and humidity. The data collected by these sensors is important information for keeping children safe.

[0214] Data collection and transmission

[0215] The device sends data collected in real time from the sensors to a server, including the child's location, movement, temperature, humidity, etc. The collected data is sent to the server at regular intervals for analysis.

[0216] Data analysis and risk detection

[0217] The server receives and analyzes the data sent from the device. This analysis includes evaluating the child's current location and movements and determining whether the situation is dangerous. If danger is detected, the server immediately sends a command to the device to sound an alarm.

[0218] Emotion Engine Operation

[0219] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine uses a camera and microphone to analyze emotions from the user's facial expressions and voice. For example, by reading a parent's facial expression with the camera and analyzing the tone of their voice with the microphone, it can determine whether the parent is feeling stressed or relieved.

[0220] Warning sound generation and adjustment

[0221] When the device receives a warning command from the server, it generates a warning sound. The content and volume of the warning sound are adjusted based on the user's emotional state analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume of the warning sound will be lowered and a more gentle voice message will be played.

[0222] Parental Notification

[0223] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email, allowing the parent to immediately understand their child's current situation and respond accordingly. In addition, the emotion engine adjusts the content and urgency of the notification according to the user's emotional state.

[0224] Specific examples

[0225] Example 1: When a child approaches an outlet

[0226] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0227] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0228] 3. The server recognizes the danger and sends a command to the terminal to sound an alarm.

[0229] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0230] 5. The device will emit a warning sound saying "Do not touch the power outlet."

[0231] 6. The server sends a notification to the parent's device saying "Your child is approaching an outlet," and the content of the notification is adjusted according to the parent's emotional state.

[0232] Example 2: A child is trying to open a window

[0233] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0234] 2. The device sends the collected data to the server.

[0235] 3. The server analyzes the data and determines that the child is trying to open the window.

[0236] 4. The server sends a command to the device to sound an alarm.

[0237] 5. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0238] 6. The device will emit a warning sound saying "Do not open the window."

[0239] 7. The server sends a notification to the parent's device saying "Your child is trying to open the window," and the content of the notification is adjusted according to the parent's emotional state.

[0240] This system improves the safety of children at home and allows parents to live their daily lives with peace of mind. The introduction of an emotion engine allows the system to respond more flexibly to parents' needs and also contributes to reducing stress.

[0241] The processing flow will be explained below.

[0242] Step 1:

[0243] The device initializes the camera, motion sensors, and environmental sensors, ensuring that each sensor is ready to operate normally.

[0244] Step 2:

[0245] The device receives real-time data from initialized sensors: the camera detects the child's location, the motion sensor detects surrounding movement, and the environmental sensors measure temperature and humidity.

[0246] Step 3:

[0247] The device formats the acquired real-time data and sends it to the server, including the child's location, movement, temperature, and humidity.

[0248] Step 4:

[0249] The server receives the data transmitted from the device, including the child's location information, movement information, and environmental data.

[0250] Step 5:

[0251] The server analyzes the received data to determine if a dangerous situation is occurring, by evaluating the child's current location and movements, and immediately setting a danger flag if a danger is detected.

[0252] Step 6:

[0253] If a danger is detected, the server sends a command to the terminal to sound an alarm, including the type and content of the alarm sound.

[0254] Step 7:

[0255] The device receives warning commands from the server and uses its built-in emotion engine to assess the user's emotional state, analyzing facial expressions with a camera and tone of voice with a microphone.

[0256] Step 8:

[0257] The device adjusts the content and volume of the warning sound based on the user's emotional state obtained from the emotion engine. For example, if the user is feeling stressed, a calm voice message will be selected.

[0258] Step 9:

[0259] The device will emit a tailored warning sound, such as a voice message saying "Do not touch the outlet" or a beep.

[0260] Step 10:

[0261] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email.

[0262] Step 11:

[0263] The server adjusts the content and urgency of notifications based on the user's emotional state analyzed by the emotion engine. For example, if the user is relaxed, the notification will be more gentle.

[0264] Step 12:

[0265] The user (parent) receives the notification from the server and checks the child's current status. For example, the parent who received the notification may take action such as going to check on the child in person.

[0266] Example 2

[0267] 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."

[0268] In conventional systems for ensuring child safety at home, the warning sounds and notification content that are emitted when danger is detected are uniform and are not adjusted according to the emotional state of the parent, which can be stressful.In addition, there is room for improvement in the accuracy of danger detection and notification, and therefore, ensuring the safety of children at home is insufficient.

[0269] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0270] In this invention, the server includes means for collecting real-time data from the sensors, means for transmitting the collected data to the server, means for analyzing the received data on the server to detect dangerous situations, means for generating an alarm sound based on the detected dangerous situation, means for analyzing the emotional state of the user using emotion analysis means, means for adjusting the alarm sound and notification content according to the emotional state of the user, and means for notifying the parent's terminal of the detected dangerous situation. This enables the system for keeping children safe at home to respond flexibly to the emotional state of the parents and respond quickly while reducing stress.

[0271] A "sensor" is a device that detects physical or chemical changes in the environment and outputs the data.

[0272] "Real-time data" is data obtained from sensors or devices that is immediately available.

[0273] A "server" is a computing device that provides functions such as data management, analysis, and storage.

[0274] "Emotion analysis means" refers to technologies and algorithms that analyze a user's facial expressions, tone of voice, etc. to determine the user's emotional state.

[0275] A "warning sound" is an audio signal that is generated to alert the user when a danger is detected.

[0276] "Parent's device" refers to an electronic device such as a smartphone or tablet owned by the parent.

[0277] A "notification" is a message or alert sent to inform a user of specific information.

[0278] A "camera" is a device that uses an optical lens to capture video or images.

[0279] A "motion sensor" is a device for detecting the movement of an object.

[0280] An "environmental sensor" is a device that measures environmental conditions such as temperature, humidity, and air pressure.

[0281] The present invention relates to a system for ensuring children's safety at home. This system includes sensors, a server, a terminal, and an emotion engine. This system monitors the child's situation in real time and generates an alarm if a dangerous situation is detected. The system also has a function for sending notifications to parents, and by using the emotion engine, the content of the notifications and alarms can be adjusted according to the parent's emotional state.

[0282] Hardware Configuration

[0283] The device is equipped with the following sensors:

[0284] Camera: Captures real-time footage of your child.

[0285] Motion sensor: Detects the proximity and movement of children.

[0286] Environmental sensors: measure temperature and humidity.

[0287] These sensors provide important information to keep children safe.

[0288] Data collection and transmission

[0289] The device collects real-time data from the sensors and transmits it to a server at regular intervals, including the child's location, movement, temperature, humidity, and other information.

[0290] Data analysis and risk detection

[0291] The server receives and analyzes the data sent from the device. This analysis includes evaluating the child's current location and movements and determining whether the situation is dangerous. If danger is detected, the server immediately sends a command to the device to generate an alarm.

[0292] Emotion Engine Operation

[0293] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine uses a camera and microphone to analyze emotions from the user's facial expressions and voice. For example, by reading a parent's facial expression with the camera and analyzing the tone of their voice with the microphone, it can determine whether the parent is feeling stressed or relieved.

[0294] Warning sound generation and adjustment

[0295] The device generates a warning sound based on a warning command from the server. The content and volume of the warning sound are adjusted based on the user's emotional state analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume of the warning sound will be lowered and a more gentle voice message will be played.

[0296] Parental Notification

[0297] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email, allowing the parent to immediately understand their child's current situation and respond accordingly. In addition, the emotion engine adjusts the content and urgency of the notification according to the user's emotional state.

[0298] Specific examples

[0299] Example 1: When a child approaches an outlet

[0300] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0301] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0302] 3. The server recognizes the danger and sends a command to the terminal to sound an alarm.

[0303] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0304] 5. The device will emit a warning sound saying "Do not touch the power outlet."

[0305] 6. The server sends a notification to the parent's device saying "Your child is approaching an outlet," and the content of the notification is adjusted according to the parent's emotional state.

[0306] Example 2: A child is trying to open a window

[0307] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0308] 2. The device sends the collected data to the server.

[0309] 3. The server analyzes the data and determines that the child is trying to open the window.

[0310] 4. The server sends a command to the device to sound an alarm.

[0311] 5. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0312] 6. The device will emit a warning sound saying "Do not open the window."

[0313] 7. The server sends a notification to the parent's device saying "Your child is trying to open the window," and the content of the notification is adjusted according to the parent's emotional state.

[0314] Prompt Sentence Examples

[0315] Prompt example 1

[0316] "Please explain in detail how this system works when a child approaches an electrical outlet. Please be specific about each step: sensor, server, device, and emotion engine."

[0317] Prompt example 2

[0318] "Please explain specifically how the system will sound an alarm and notify parents if a child tries to open a window."

[0319] As a result, the system of the present invention increases the safety of children and reduces stress for parents, allowing them to live their daily lives with peace of mind.In this way, by incorporating emotion analysis, we can improve the shortcomings of conventional systems and provide a more flexible and adaptable system.

[0320] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0321] Step 1:

[0322] Sensor data acquisition

[0323] Input: Physical changes from the surrounding environment (child's movement, temperature, humidity, etc.)

[0324] Processing: Cameras capture footage, motion sensors detect the child's movements, and environmental sensors measure temperature and humidity.

[0325] Output: Child's video data, movement data, environmental data

[0326] How it works: The device's built-in camera captures real-time footage of the child, the motion sensor captures the child's movements and proximity, and the environmental sensor measures the indoor temperature and humidity, temporarily storing this data internally.

[0327] Step 2:

[0328] Sending data

[0329] Input: Child's video data, movement data, environmental data

[0330] Processing: The device sends the collected data to the server at a specified interval (e.g., every 5 seconds).

[0331] Output: Data collected from the sensor is sent to the server

[0332] Specific operation: A program on the terminal stores the collected data in temporary memory and sends it to the server via the network as data packets at regular intervals.

[0333] Step 3:

[0334] Data reception and analysis

[0335] Input: Data packets sent from the sensor

[0336] Processing: The server receives the data, checks its integrity, stores it in a database in the correct format, and uses analysis algorithms to determine whether it poses a risk.

[0337] Output: Analysis results, whether there is a risk

[0338] Specific operation: The server receives the data packet, verifies the data integrity, and stores it in the database. It then uses an analysis algorithm to analyze the child's location and movements to assess whether there is any danger.

[0339] Step 4:

[0340] Hazard detection

[0341] Input: Server analysis results

[0342] Processing: The server evaluates the analysis results and flags any detected dangers, as well as identifying the type and location of the danger.

[0343] Output: Danger detection flag, type of danger and location information

[0344] Specific operation: The server searches for specific patterns (e.g., near an outlet or near a window) based on the results of the analysis algorithm, and if a danger is identified, it sets a danger flag and prepares information to proceed to the next step.

[0345] Step 5:

[0346] Sending a warning order

[0347] Input: Danger detection flag, type of danger and location information

[0348] Processing: If a danger is detected, the server sends a warning command to the device, including the type of danger and its location.

[0349] Output: Warning command for terminal

[0350] Specific operation: The server generates an appropriate warning signal and sends it to the device via the network. The warning signal contains the type of danger recognized and its location.

[0351] Step 6:

[0352] Emotion analysis using an emotion engine

[0353] Input: Parent's facial expression data, voice data

[0354] Processing: The emotion engine installed on the device analyzes the parent's emotional state using the camera and microphone.

[0355] Output: Parent's emotional state information

[0356] Specific operation: The device's camera captures the parent's facial expressions and the microphone records the tone of their voice. The emotion engine analyzes this data to determine the parent's emotional state.

[0357] Step 7:

[0358] Warning sound generation and adjustment

[0359] Input: Warning command, parent's emotional state information

[0360] Processing: The device generates a warning sound based on the warning command, and adjusts the content and volume of the warning sound based on the parent's emotional state.

[0361] Output: Audible warning sound

[0362] What it does: Plays an appropriate warning sound through the device speaker. Based on the results of the emotion engine, for example, if the parent is stressed, it lowers the volume and plays a softer message.

[0363] Step 8:

[0364] Parental Notification

[0365] Input: Danger detection flag, parent's emotional state information

[0366] Processing: The server notifies the parent's device that a danger has been detected. The content and urgency of the notification are adjusted according to the parent's emotional state.

[0367] Output: Notification message to parent device

[0368] Specific operation: The server sends warning information to the parent's device in the form of an app notification or email. Based on the results of the emotion engine, for example, if the parent is feeling stressed, the server will send a soft-spoken notification.

[0369] (Application example 2)

[0370] 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."

[0371] Conventional home monitoring systems have a means of detecting danger to ensure child safety, but they uniformly issue warning sounds without considering the parent's emotional state, which can increase parental stress. Furthermore, even if a parent is busy and unable to respond immediately, important notifications may not be properly delivered. The present invention aims to solve these problems and provide a more flexible and effective child monitoring system.

[0372] 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.

[0373] In this invention, the server includes a means for collecting real-time data, a means for transmitting the collected data, and a means for analyzing the received data and detecting a dangerous situation, which makes it possible to combine an emotion recognition means for analyzing the user's emotion with a means for adjusting the content and volume of the warning sound based on the emotion recognition result.

[0374] "Sensors" are devices such as cameras, motion sensors, and environmental sensors that collect data in real time.

[0375] "Real-time data" refers to data obtained from sensors and information that is sent to a server immediately without any time delay.

[0376] A "server" is a computer system that receives and analyzes the collected data.

[0377] A "danger situation" is a condition that indicates a child is in a dangerous place or situation.

[0378] A "warning sound" is a notification sound such as a voice message or a beep that is generated based on a detected dangerous situation.

[0379] A "parent's device" is an electronic device such as a smartphone or tablet that is owned by the parent.

[0380] "Emotion recognition means" is a technology that analyzes a user's facial expressions and voice to determine their emotional state.

[0381] The "adjustment means" is a mechanism for changing the content and volume of the warning sound based on the emotion recognition result.

[0382] System Overview

[0383] This invention is a monitoring system designed to keep children safe at home. The system is composed of multiple elements, including sensors, a server, a terminal, and an emotion engine that recognizes the user's emotions. The sensors include cameras, motion sensors, and environmental sensors, and real-time data acquired from these sensors is sent to the server. The server analyzes the data, detects dangerous situations, and sends a command to the terminal to issue an alert. The system also has the function of analyzing the user's emotional state to adjust the content and volume of the alert sound.

[0384] Hardware and software used

[0385] Sensors: Camera, motion sensors, environmental sensors

[0386] Server: A computer system that collects and analyzes data.

[0387] Device: Electronic devices such as smartphones and tablets owned by parents

[0388] Emotion engine: Software for recognizing user emotions (e.g., EmotionRecognizer)

[0389] Communications: Internet connection for data transmission and notifications

[0390] System operation explanation

[0391] Data collection

[0392] Sensors are installed in each room of the home to monitor the child's location and movements. Cameras capture images in real time, motion sensors detect the child's proximity and movement, and environmental sensors measure temperature and humidity. Data collected from these sensors is immediately sent to a server.

[0393] Data analysis

[0394] The server analyzes the received data and evaluates the child's current location and movements. For example, if a child approaches an electrical outlet, it combines data from the motion sensor with camera footage to detect a dangerous situation. Based on the analysis results, it immediately sends a command to the device to sound an alarm.

[0395] emotion recognition

[0396] The device is equipped with an emotion engine that recognizes the user's emotions and uses a camera and microphone to analyze the user's facial expressions and voice to determine their emotions. For example, by reading a parent's facial expression and analyzing their tone of voice, the device can determine whether they are feeling stressed or relieved.

[0397] Adjust alert sounds and notifications

[0398] Upon receiving a command from the server, the device will emit an alert sound. The content and volume of the alert sound will be adjusted based on the user's emotional state as analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume will be lowered and a calming voice message will be played. In addition, a notification will be sent to the parent's device to provide information to help them understand their child's current situation.

[0399] Specific examples

[0400] Proximity to electrical outlets

[0401] 1. The sensor detects when a child approaches an outlet and sends the data to the server.

[0402] 2. The server analyzes the data and recognizes the danger.

[0403] 3. The server sends a command to the device to generate an alarm sound.

[0404] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0405] 5. A warning sound will be emitted saying "Do not touch the outlet."

[0406] 6. A notification will be sent to the parent's device saying "Your child is approaching an outlet."

[0407] Approaching the window

[0408] 1. The sensor detects the child's approach to the window and sends the data to the server.

[0409] 2. The server analyzes the data and recognizes the danger.

[0410] 3. The server sends a command to the device to generate an alarm sound.

[0411] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0412] 5. A warning sound will be emitted, such as "Do not open the window."

[0413] 6. A notification will be sent to the parent's device saying "Your child is trying to open a window."

[0414] Example prompts for generative AI models

[0415] Image-based hazard detection:

[0416] Use image analysis to detect danger when a child approaches an electrical outlet.

[0417] Emotion recognition:

[0418] Please judge the parent's emotional state as indicated by this image and adjust the notification content and volume accordingly.

[0419] As described above, the present invention makes it possible to flexibly adjust the warning sound in accordance with the emotional state of the parent, thereby ensuring the safety of the child.

[0420] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0421] Step 1:

[0422] Sensors detect the child's location and movements in real time.

[0423] Input: Camera footage, motion sensor data, environmental sensor data

[0424] Data processing: Extract the child's location from the camera footage, analyze the child's movements from the motion sensor data, and obtain temperature and humidity from the environmental sensor data.

[0425] Output: Parsed child's position, movement, and environment information

[0426] Step 2:

[0427] The terminal transmits the collected data to the server.

[0428] Input: Parsed child location, movement, and environment information

[0429] Data processing: Convert the data into JSON format and send it to the server.

[0430] Output: Data sent to the server

[0431] Step 3:

[0432] The server analyzes the received data and detects dangerous situations.

[0433] Input: Data sent to the server (child's location, movements, and environmental information)

[0434] Data Calculation: Analyzes the data and performs rule-based analysis to determine whether a child is in a dangerous location. For example, if a child approaches an electrical outlet, it is considered a dangerous situation.

[0435] Output: Judgment result (presence or absence of dangerous situation)

[0436] Step 4:

[0437] If the server detects danger, it sends a command to the terminal to sound an alarm.

[0438] Input: Judgment result (danger situation)

[0439] Data processing: Based on the judgment result, a message is generated to send to the terminal an instruction to issue an alarm.

[0440] Output: Warning sound generation command

[0441] Step 5:

[0442] The terminal receives the instruction to generate an alert sound and analyzes the user's emotional state.

[0443] Input: Sound alarm command

[0444] Data calculation: Using the device's camera and microphone, the user's facial expressions and voice are captured and their emotions are analyzed using an emotion recognition model (e.g., EmotionRecognizer).

[0445] Output: User's emotional state

[0446] Step 6:

[0447] The device adjusts the content and volume of the warning sound based on the emotion recognition results.

[0448] Input: User's emotional state, command to sound an alert

[0449] Data calculation: Analyzes the user's emotional state and determines the appropriate alert content and volume settings. For example, if the user is stressed, lower the volume and select a calm voice message.

[0450] Output: Adjusted warning sound settings

[0451] Step 7:

[0452] The device will emit an alert and send a notification to the parent device.

[0453] Input: Adjusted warning sound settings, judgment result

[0454] Data processing: Generates an alarm sound and plays it through the speaker. Also generates and sends a notification message to the parent's device to inform them of the current situation.

[0455] Output: generated alerts, sent notification messages

[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 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.

[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] The system of the present invention consists of multiple sensors installed in the home, a server that processes and analyzes the data, and a device (parent's smartphone or tablet) that receives notifications. This system collects data in real time to ensure the safety of children, detects dangerous situations, and generates an alarm to notify parents.

[0473] Sensor installation and operation

[0474] The sensors included in the device consist of a camera, motion sensors, and environmental sensors. The camera captures video data in real time and tracks the child's movements. The motion sensor detects whether the child is approaching a specific dangerous area (e.g., the kitchen or stairs). The environmental sensor collects environmental data such as temperature and humidity to monitor whether the child is in a safe environment.

[0475] Data collection and transmission

[0476] The device collects data from these sensors in real time and transmits it to a server at regular intervals. The collected data includes the child's location, movement, temperature, humidity, etc. This data is converted into a format that the server can understand and transmitted via a communication module.

[0477] Data analysis and risk detection

[0478] The server analyzes the received data. This analysis involves comparing the child's current location with past behavioral patterns. Specifically, if the child stays in a specific area for a certain amount of time or repeats a certain behavior, the server compares this with past data to predict danger.

[0479] For example, if a child is near an electrical outlet, the server analyzes their location information and determines the danger based on similar behavior patterns in the past. In this case, before the child actually touches the outlet, the server detects the danger and sends a warning signal to the device.

[0480] Warning sound generation

[0481] The device immediately generates a warning sound based on the warning signal received from the server. This warning sound may be a voice message or a beep to warn the child of the danger. For example, a voice message saying "Do not touch the outlet" is played.

[0482] Parental Notification

[0483] At the same time, the server generates a message to notify the parent of the danger. This message is sent to the smartphone or tablet in the form of an app notification or email. For example, a warning message saying "Your child is approaching an electrical outlet" can be sent, allowing the parent to take immediate action.

[0484] Specific examples

[0485] Example 1: What to do if a child approaches an electrical outlet

[0486] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0487] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0488] 3. The server recognizes the danger and sends a command to the terminal to generate an alarm sound.

[0489] 4. The device will emit a warning sound saying "Do not touch the power outlet."

[0490] 5. The server sends a notification to the parent's device saying, "Your child is approaching an outlet."

[0491] Example 2: What to do if a child tries to open a window

[0492] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0493] 2. The device sends the collected data to the server.

[0494] 3. The server analyzes the data and determines that the child is trying to open the window.

[0495] 4. The server sends a command to the terminal to generate an alarm sound.

[0496] 5. The device will emit a warning sound saying "Do not open the window."

[0497] 6. The server sends a notification to the parent's device saying, "Your child is trying to open a window."

[0498] Such systems will dramatically improve the safety of children and allow parents to go about their daily lives with peace of mind.

[0499] The processing flow will be explained below.

[0500] Step 1:

[0501] The device initializes the sensors and checks that the camera, motion sensor, and environmental sensor are working properly, so the sensors are ready to work properly.

[0502] Step 2:

[0503] The device receives real-time data from initialized sensors: a camera detects the child's location, motion sensors detect surrounding movement, and environmental sensors measure temperature and humidity.

[0504] Step 3:

[0505] The device formats the acquired real-time data for transmission to the server, including the child's location, movement, temperature, and humidity.

[0506] Step 4:

[0507] The terminal sends the formatted data to the server via a communication module, so that the collected data reaches the server for analysis.

[0508] Step 5:

[0509] The server receives data transmitted from the terminal, including the child's location information, movement information, and environmental data.

[0510] Step 6:

[0511] The server analyzes the received data to determine if a dangerous situation is occurring, which involves matching the child's current location with past behavioral patterns.

[0512] Step 7:

[0513] The server sends a command to the terminal to generate an alarm when a danger is detected.

[0514] Step 8:

[0515] The terminal receives the warning command from the server and generates a designated warning sound, which includes a voice message such as "Do not touch the outlet."

[0516] Step 9:

[0517] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email.

[0518] Step 10:

[0519] The user (parent) receives the notification from the server, checks the child's current status, and takes appropriate action. For example, the parent who receives the notification may go and check on the child in person.

[0520] Example 1

[0521] 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."

[0522] Conventional child safety monitoring systems have limitations in ensuring safety due to the difficulty of detecting danger in real time and notifying parents promptly. In particular, they are unable to predict danger based on specific behavioral patterns or environmental data, which can delay parents from taking appropriate action.

[0523] 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.

[0524] In this invention, the server includes a means for transmitting data collected by the terminal to the server at regular intervals, a means for converting the data received by the server into an understandable format, and a means for comparing past behavioral patterns with real-time location information in data analysis, thereby enabling real-time danger detection and prompt notification.

[0525] "Sensors" are devices for detecting specific conditions within the home, including cameras, motion sensors, and environmental sensors.

[0526] "Real-time data" refers to data on the current situation or environment obtained by sensors, which is processed and transmitted immediately.

[0527] "Server" means a device or system that receives and analyzes data sent from a terminal and issues alerts based on specific conditions.

[0528] "Warning sounds" are sounds used to warn users, such as voice messages or beeps, that are generated when a dangerous situation is detected.

[0529] A "parent device" is a device that receives alert notifications about the child's status, and refers to a smartphone or tablet owned by the parent.

[0530] "Data transmission" is the communication process of transferring collected data from the terminal to the server.

[0531] "Data reformatting" is the process of converting data received at a server into a format that can be parsed.

[0532] "Data analysis" is the process of identifying specific patterns or situations based on received data and detecting dangers.

[0533] "Dangerous situations" refer to situations in which a child approaches a dangerous area or performs a dangerous action.

[0534] An "interval" refers to a fixed time interval set when transmitting or processing data.

[0535] "Behavioral patterns" refer to a child's tendency to move and perform a series of actions, analyzed based on past data.

[0536] A "warning signal" is a signal generated by a server and sent to a terminal to notify it of a dangerous situation.

[0537] The system of the present invention consists of multiple sensor devices installed in the home, a server that processes and analyzes the data, and a terminal (parent's smartphone or tablet) for receiving notifications. The main purpose of this system is to ensure the safety of children, collecting data in real time, detecting dangerous situations, and notifying parents with an alarm.

[0538] Sensor installation and operation

[0539] The device manages sensors installed in the home. These sensors include cameras, motion sensors, and environmental sensors. Specifically, the camera sensors capture video data in real time and track children's movements. The motion sensors detect whether children are approaching specific dangerous areas (e.g., the kitchen or stairs), and the environmental sensors capture environmental data such as temperature and humidity.

[0540] Data collection and transmission

[0541] The device collects data from sensors in real time and transmits it to a server at regular intervals. The data includes the child's location, movement, and environmental data, and is transferred to the server via a communication module.

[0542] Receiving and formatting data

[0543] The server receives the data sent from the device and converts it into a format that can be analyzed. For example, video data is converted into a format that can be analyzed using an image processing algorithm.

[0544] Data analysis

[0545] The server then analyzes the received data. This analysis involves comparing real-time location information with past behavioral patterns. Specific examples include determining whether a person has stayed in a specific area for a certain amount of time or whether they have repeatedly performed a specific action.

[0546] Hazard detection and warning signal transmission

[0547] If the server detects a dangerous situation based on the data analysis, it will send a warning signal to the device. For example, if a child stays near an electrical outlet for a certain period of time, the server will generate a warning signal based on this information.

[0548] Warning sound generation

[0549] The device immediately generates a warning sound based on the warning signal received from the server. The warning sound is a voice message or a beep to warn the child of the danger. For example, a voice message saying "Do not touch the outlet" is played.

[0550] Parental Notification

[0551] When a danger is detected, the server sends a notification to the parent's device. The notification can be sent via push notification in the app or via email. For example, a warning message saying "your child is approaching an electrical outlet" can be sent to the parent's smartphone or tablet, allowing the parent to take prompt action.

[0552] Specific examples

[0553] Example 1: What to do if a child approaches an electrical outlet

[0554] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0555] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0556] 3. The server recognizes the danger and sends a command to the terminal to generate an alarm sound.

[0557] 4. The device will emit a warning sound saying "Do not touch the power outlet."

[0558] 5. The server sends a notification to the parent's device saying, "Your child is approaching an outlet."

[0559] Example 2: What to do if a child tries to open a window

[0560] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0561] 2. The device sends the collected data to the server.

[0562] 3. The server analyzes the data and determines that the child is trying to open the window.

[0563] 4. The server sends a command to the terminal to generate an alarm sound.

[0564] 5. The device will emit a warning sound saying "Do not open the window."

[0565] 6. The server sends a notification to the parent's device saying, "Your child is trying to open a window."

[0566] Prompt Sentence Examples

[0567] Example prompts to input to a generative AI model:

[0568] "Please explain the program process for a system that uses sensors installed in the home to monitor child safety. The sensors are cameras, motion sensors, and environmental sensors. A server analyzes the data and sends a notification to the parent's device if a danger is detected. As a concrete example, please explain the processing flow when a child approaches an electrical outlet and when they try to open a window."

[0569] In this way, the present invention ensures the safety of children and provides an environment in which parents can live with peace of mind.

[0570] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0571] Step 1: Acquiring data from the sensor

[0572] The device collects real-time data from various sensors (cameras, motion sensors, and environmental sensors) installed in the home. For example, the camera sensor collects video data, and the motion sensor detects when a child approaches a specific dangerous area. The environmental sensor measures the temperature and humidity inside the room. The input includes raw data from the sensors, and the output is formatted data. Specifically, the video data is saved frame by frame, and the motion sensor data is saved as location information.

[0573] Step 2: Sending data

[0574] The terminal transmits the acquired data to the server at regular intervals. The input is the formatted data acquired from the sensor, and the output is the transmitted data sent to the server. Specifically, a communication module is used to transfer the data to the server in JSON format or similar. Each piece of data is given a timestamp to maintain consistency.

[0575] Step 3: Receiving and formatting data

[0576] The server receives data sent from the device. The received data includes location information, motion information, temperature, humidity, etc. The input is the raw data sent from the device, and the output is data formatted into an analyzable format. Specifically, the data is temporarily stored and formatted as needed using image processing algorithms and data analysis algorithms.

[0577] Step 4: Analyze the data

[0578] The server analyzes the received data. The input is formatted data, and the output is analysis results. Specifically, it compares real-time location information with past behavioral patterns to identify specific behavioral patterns and environmental conditions. Examples include when an individual has stayed in the same area for a certain period of time, or when environmental data has reached a dangerous value.

[0579] Step 5: Detect danger and send a warning signal

[0580] If the server detects a dangerous situation as a result of data analysis, it sends a warning signal to the device. The analysis results are input, and a warning signal is generated as output. Specifically, if a child stays near an electrical outlet for a long time, for example, a warning signal is generated and sent to the device.

[0581] Step 6: Sound the alarm

[0582] The terminal immediately generates a warning sound based on the warning signal received from the server. The received warning signal is the input, and the generated warning sound is the output. For example, a voice message saying "Do not touch the outlet" is played to warn children.

[0583] Step 7: Parental Notification

[0584] The server sends a notification to the parent's device when a danger is detected. The input is the detection result, and the output is a warning message sent to the parent's smartphone or tablet. Specifically, a message such as "Your child is approaching an outlet" is sent immediately, allowing the parent to check the situation and take prompt action.

[0585] This is the flow of the program processing for this system. In this way, the system is able to detect danger in real time and respond quickly, ensuring the safety of children.

[0586] (Application example 1)

[0587] 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."

[0588] Conventional home security systems lack the real-time and multifaceted capabilities to ensure children's safety. In particular, notifying parents alone when an abnormality occurs often results in delayed response, which is a major problem when response is required outside the home. Therefore, there is a need to develop a system that utilizes home sensors to instantly detect abnormalities and notify parents and a security center.

[0589] 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.

[0590] In this invention, the server includes means for collecting real-time data from the sensors, means for transmitting the collected data to the server, means for analyzing the received data on the server and detecting dangerous situations, means for generating an alarm based on the detected dangerous situation, and means for notifying the parent's terminal and the security center of the detected dangerous situation. This allows the parent and the security center to be notified simultaneously when an abnormality occurs, enabling a rapid and multifaceted response.

[0591] A "sensor" is a device that detects physical conditions or changes and collects that data.

[0592] "Real-time data" refers to data that is collected continuously by sensors and is immediate and has no time delay.

[0593] A "server" is a central computer system for collecting, analyzing, processing, and transmitting data.

[0594] A "dangerous situation" is a situation that is detected by a sensor and analyzed by a server, and determines that there is a potential risk to a child or the home.

[0595] A "warning sound" is an alert that is generated as a voice or beep when a dangerous situation is detected.

[0596] A "parent device" is a device, such as a smartphone or tablet, that is owned by the parent and used to receive notifications.

[0597] A "security center" is a specialized institution that handles security measures outside the home, and is a facility that responds quickly upon receiving notification of an abnormality.

[0598] "Notification" is a communication that informs the parent's device or security center of a dangerous situation detected by the server.

[0599] As an embodiment of the present invention, the following system is constructed. First, multiple sensors are installed in a home. These sensors include cameras, motion sensors, and environmental sensors. As a specific example, the cameras track children's movements and collect video data in real time. The motion sensors detect when a child approaches a specific dangerous area (e.g., the kitchen or stairs). The environmental sensors acquire environmental data such as temperature and humidity, and monitor whether the child is living in a safe environment.

[0600] The collected data is sent to a server via a Wi-Fi module. The server is equipped with data analysis software that includes a Python-based machine learning model, which analyzes the data in real time. This analysis uses an anomaly detection algorithm to detect an anomaly if a specified condition is met (e.g., a child getting too close to the door).

[0601] If an abnormality is detected, the server simultaneously sends a warning signal to the parent device (smartphone or tablet) and the security center. The parent device immediately displays a notification and generates an audible warning (voice message or beep) based on the received warning signal. The security center displays an abnormality notification on its web dashboard, allowing an operator to initiate response procedures.

[0602] For example, here is a specific example of a child trying to open a door:

[0603] 1. In-home sensors detect children's movements and collect data on their approach to the door.

[0604] 2. The sensor sends the data to the server.

[0605] 3. The server analyzes the data and determines that a child is trying to open the door.

[0606] 4. The server sends a command to the parent's smartphone to generate an alarm sound and simultaneously sends an alert to the security center.

[0607] 5. A parent's smartphone will emit a warning sound saying "Do not open the door."

[0608] 6. The security center will have an operator respond (e.g., check the camera footage and dispatch security guards).

[0609] Additionally, to perform anomaly analysis using a generative AI model, the following prompts can be used:

[0610] Example prompt sentence:

[0611] “Your child is opening a door in your home, please analyze the information below and provide safety measures.

[0612] Child's current location: Living room

[0613] Operational Information: Standing upright near the door

[0614] Environmental data: 19°C, 40% humidity

[0615] Video feed: [Real-time video URL]

[0616] Required actions:

[0617] 1. Send a warning message to the parent's smartphone

[0618] 2. Send an alert to the Security Center

[0619] 3. Triggering an audio warning

[0620] Such a system will strengthen security within the home and enable rapid and multifaceted response in the event of an emergency.

[0621] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0622] Step 1:

[0623] In-home sensors collect real-time data on children's behavior and environment. Specifically, cameras monitor children's movements and record the footage as digital data. Motion sensors detect approach to specific danger areas, and environmental sensors measure temperature and humidity. This data is temporarily stored in local storage.

[0624] Input: Child's movement information, environmental data

[0625] Output: Collected real-time data (video data, motion data, environmental data)

[0626] Step 2:

[0627] The collected real-time data is sent to a server via a home communication module. Specifically, the data is sent in bulk in packet format using a Wi-Fi module. During this process, the data is reformatted (for example, converted to JSON format).

[0628] Input: Collected real-time data (video data, behavior data, environmental data)

[0629] Output: Data packets sent to the server

[0630] Step 3:

[0631] The server analyzes the received data. It uses a Python-based machine learning model to execute an anomaly detection algorithm. Specifically, it compares current data with past data to detect abnormal patterns (such as a child approaching a door). Data processing includes time series analysis and clustering.

[0632] Input: Data packet sent to the server

[0633] Output: Detected abnormal patterns

[0634] Step 4:

[0635] If the server detects an abnormal pattern, it generates a warning signal, which includes details of the abnormal situation (e.g., a child trying to open a door), and generates an appropriate countermeasure by inputting a prompt sentence into the generative AI model.

[0636] Input: Detected abnormal pattern

[0637] Output: Warning signal, action to be taken based on the prompt

[0638] Step 5:

[0639] The server sends the generated warning signal and countermeasures to the parent device and the security center. The parent device displays a warning message and an alarm sound. At the same time, an alert is sent to the security center and displayed on the center's dashboard.

[0640] Input: Warning signals, countermeasures based on prompts

[0641] Output: Notifications on parent's device, Security Center alerts

[0642] Step 6:

[0643] When the parent device receives the warning message, the user can take action based on the message. At the same time, security center operators also check the dashboard and take action, such as dispatching security guards to the scene, if necessary.

[0644] Input: Parental device notifications, Security Center alerts

[0645] Output: User response, Security Center action

[0646] This process allows parents and security centers to respond quickly and effectively when a child faces a dangerous situation at home.

[0647] 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.

[0648] This invention provides a system for ensuring children's safety at home, and is composed of sensors, a server, a terminal, and an emotion engine. This system detects dangerous situations for children based on real-time data obtained from the sensors, generates an alarm, and notifies parents. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, the system has the function of adjusting the alarm sound and notification content according to the user's emotional state.

[0649] Sensor installation and operation

[0650] The device is equipped with a camera, motion sensors, and environmental sensors. The camera captures images of the child in real time, the motion sensors detect the child's proximity and movement, and the environmental sensors measure temperature and humidity. The data collected by these sensors is important information for keeping children safe.

[0651] Data collection and transmission

[0652] The device sends data collected in real time from the sensors to a server, including the child's location, movement, temperature, humidity, etc. The collected data is sent to the server at regular intervals for analysis.

[0653] Data analysis and risk detection

[0654] The server receives and analyzes the data sent from the device. This analysis includes evaluating the child's current location and movements and determining whether the situation is dangerous. If danger is detected, the server immediately sends a command to the device to sound an alarm.

[0655] Emotion Engine Operation

[0656] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine uses a camera and microphone to analyze emotions from the user's facial expressions and voice. For example, by reading a parent's facial expression with the camera and analyzing the tone of their voice with the microphone, it can determine whether the parent is feeling stressed or relieved.

[0657] Warning sound generation and adjustment

[0658] When the device receives a warning command from the server, it generates a warning sound. The content and volume of the warning sound are adjusted based on the user's emotional state analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume of the warning sound will be lowered and a more gentle voice message will be played.

[0659] Parental Notification

[0660] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email, allowing the parent to immediately understand their child's current situation and respond accordingly. In addition, the emotion engine adjusts the content and urgency of the notification according to the user's emotional state.

[0661] Specific examples

[0662] Example 1: When a child approaches an outlet

[0663] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0664] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0665] 3. The server recognizes the danger and sends a command to the terminal to sound an alarm.

[0666] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0667] 5. The device will emit a warning sound saying "Do not touch the power outlet."

[0668] 6. The server sends a notification to the parent's device saying "Your child is approaching an outlet," and the content of the notification is adjusted according to the parent's emotional state.

[0669] Example 2: A child is trying to open a window

[0670] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0671] 2. The device sends the collected data to the server.

[0672] 3. The server analyzes the data and determines that the child is trying to open the window.

[0673] 4. The server sends a command to the device to sound an alarm.

[0674] 5. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0675] 6. The device will emit a warning sound saying "Do not open the window."

[0676] 7. The server sends a notification to the parent's device saying "Your child is trying to open the window," and the content of the notification is adjusted according to the parent's emotional state.

[0677] This system improves the safety of children at home and allows parents to live their daily lives with peace of mind. The introduction of an emotion engine allows the system to respond more flexibly to parents' needs and also contributes to reducing stress.

[0678] The processing flow will be explained below.

[0679] Step 1:

[0680] The device initializes the camera, motion sensors, and environmental sensors, ensuring that each sensor is ready to operate normally.

[0681] Step 2:

[0682] The device receives real-time data from initialized sensors: the camera detects the child's location, the motion sensor detects surrounding movement, and the environmental sensors measure temperature and humidity.

[0683] Step 3:

[0684] The device formats the acquired real-time data and sends it to the server, including the child's location, movement, temperature, and humidity.

[0685] Step 4:

[0686] The server receives the data transmitted from the device, including the child's location information, movement information, and environmental data.

[0687] Step 5:

[0688] The server analyzes the received data to determine if a dangerous situation is occurring, by evaluating the child's current location and movements, and immediately setting a danger flag if a danger is detected.

[0689] Step 6:

[0690] If a danger is detected, the server sends a command to the terminal to sound an alarm, including the type and content of the alarm sound.

[0691] Step 7:

[0692] The device receives warning commands from the server and uses its built-in emotion engine to assess the user's emotional state, analyzing facial expressions with a camera and tone of voice with a microphone.

[0693] Step 8:

[0694] The device adjusts the content and volume of the warning sound based on the user's emotional state obtained from the emotion engine. For example, if the user is feeling stressed, a calm voice message will be selected.

[0695] Step 9:

[0696] The device will emit a tailored warning sound, such as a voice message saying "Do not touch the outlet" or a beep.

[0697] Step 10:

[0698] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email.

[0699] Step 11:

[0700] The server adjusts the content and urgency of notifications based on the user's emotional state analyzed by the emotion engine. For example, if the user is relaxed, the notification will be more gentle.

[0701] Step 12:

[0702] The user (parent) receives the notification from the server and checks the child's current status. For example, the parent who received the notification may take action such as going to check on the child in person.

[0703] Example 2

[0704] 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."

[0705] In conventional systems for ensuring child safety at home, the warning sounds and notification content that are emitted when danger is detected are uniform and are not adjusted according to the emotional state of the parent, which can be stressful.In addition, there is room for improvement in the accuracy of danger detection and notification, and therefore, ensuring the safety of children at home is insufficient.

[0706] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0707] In this invention, the server includes means for collecting real-time data from the sensors, means for transmitting the collected data to the server, means for analyzing the received data on the server to detect dangerous situations, means for generating an alarm sound based on the detected dangerous situation, means for analyzing the emotional state of the user using emotion analysis means, means for adjusting the alarm sound and notification content according to the emotional state of the user, and means for notifying the parent's terminal of the detected dangerous situation. This enables the system for keeping children safe at home to respond flexibly to the emotional state of the parents and respond quickly while reducing stress.

[0708] A "sensor" is a device that detects physical or chemical changes in the environment and outputs the data.

[0709] "Real-time data" is data obtained from sensors or devices that is immediately available.

[0710] A "server" is a computing device that provides functions such as data management, analysis, and storage.

[0711] "Emotion analysis means" refers to technologies and algorithms that analyze a user's facial expressions, tone of voice, etc. to determine the user's emotional state.

[0712] A "warning sound" is an audio signal that is generated to alert the user when a danger is detected.

[0713] "Parent's device" refers to an electronic device such as a smartphone or tablet owned by the parent.

[0714] A "notification" is a message or alert sent to inform a user of specific information.

[0715] A "camera" is a device that uses an optical lens to capture video or images.

[0716] A "motion sensor" is a device for detecting the movement of an object.

[0717] An "environmental sensor" is a device that measures environmental conditions such as temperature, humidity, and air pressure.

[0718] The present invention relates to a system for ensuring children's safety at home. This system includes sensors, a server, a terminal, and an emotion engine. This system monitors the child's situation in real time and generates an alarm if a dangerous situation is detected. The system also has a function for sending notifications to parents, and by using the emotion engine, the content of the notifications and alarms can be adjusted according to the parent's emotional state.

[0719] Hardware Configuration

[0720] The device is equipped with the following sensors:

[0721] Camera: Captures real-time footage of your child.

[0722] Motion sensor: Detects the proximity and movement of children.

[0723] Environmental sensors: measure temperature and humidity.

[0724] These sensors provide important information to keep children safe.

[0725] Data collection and transmission

[0726] The device collects real-time data from the sensors and transmits it to a server at regular intervals, including the child's location, movement, temperature, humidity, and other information.

[0727] Data analysis and risk detection

[0728] The server receives and analyzes the data sent from the device. This analysis includes evaluating the child's current location and movements and determining whether the situation is dangerous. If danger is detected, the server immediately sends a command to the device to generate an alarm.

[0729] Emotion Engine Operation

[0730] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine uses a camera and microphone to analyze emotions from the user's facial expressions and voice. For example, by reading a parent's facial expression with the camera and analyzing the tone of their voice with the microphone, it can determine whether the parent is feeling stressed or relieved.

[0731] Warning sound generation and adjustment

[0732] The device generates a warning sound based on a warning command from the server. The content and volume of the warning sound are adjusted based on the user's emotional state analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume of the warning sound will be lowered and a more gentle voice message will be played.

[0733] Parental Notification

[0734] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email, allowing the parent to immediately understand their child's current situation and respond accordingly. In addition, the emotion engine adjusts the content and urgency of the notification according to the user's emotional state.

[0735] Specific examples

[0736] Example 1: When a child approaches an outlet

[0737] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0738] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0739] 3. The server recognizes the danger and sends a command to the terminal to sound an alarm.

[0740] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0741] 5. The device will emit a warning sound saying "Do not touch the power outlet."

[0742] 6. The server sends a notification to the parent's device saying "Your child is approaching an outlet," and the content of the notification is adjusted according to the parent's emotional state.

[0743] Example 2: A child is trying to open a window

[0744] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0745] 2. The device sends the collected data to the server.

[0746] 3. The server analyzes the data and determines that the child is trying to open the window.

[0747] 4. The server sends a command to the device to sound an alarm.

[0748] 5. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0749] 6. The device will emit a warning sound saying "Do not open the window."

[0750] 7. The server sends a notification to the parent's device saying "Your child is trying to open the window," and the content of the notification is adjusted according to the parent's emotional state.

[0751] Prompt Sentence Examples

[0752] Prompt example 1

[0753] "Please explain in detail how this system works when a child approaches an electrical outlet. Please be specific about each step: sensor, server, device, and emotion engine."

[0754] Prompt example 2

[0755] "Please explain specifically how the system will sound an alarm and notify parents if a child tries to open a window."

[0756] As a result, the system of the present invention increases the safety of children and reduces stress for parents, allowing them to live their daily lives with peace of mind.In this way, by incorporating emotion analysis, we can improve the shortcomings of conventional systems and provide a more flexible and adaptable system.

[0757] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0758] Step 1:

[0759] Sensor data acquisition

[0760] Input: Physical changes from the surrounding environment (child's movement, temperature, humidity, etc.)

[0761] Processing: Cameras capture footage, motion sensors detect the child's movements, and environmental sensors measure temperature and humidity.

[0762] Output: Child's video data, movement data, environmental data

[0763] How it works: The device's built-in camera captures real-time footage of the child, the motion sensor captures the child's movements and proximity, and the environmental sensor measures the indoor temperature and humidity, temporarily storing this data internally.

[0764] Step 2:

[0765] Sending data

[0766] Input: Child's video data, movement data, environmental data

[0767] Processing: The device sends the collected data to the server at a specified interval (e.g., every 5 seconds).

[0768] Output: Data collected from the sensor is sent to the server

[0769] Specific operation: A program on the terminal stores the collected data in temporary memory and sends it to the server via the network as data packets at regular intervals.

[0770] Step 3:

[0771] Data reception and analysis

[0772] Input: Data packets sent from the sensor

[0773] Processing: The server receives the data, checks its integrity, stores it in a database in the correct format, and uses analysis algorithms to determine whether it poses a risk.

[0774] Output: Analysis results, whether there is a risk

[0775] Specific operation: The server receives the data packet, verifies the data integrity, and stores it in the database. It then uses an analysis algorithm to analyze the child's location and movements to assess whether there is any danger.

[0776] Step 4:

[0777] Hazard detection

[0778] Input: Server analysis results

[0779] Processing: The server evaluates the analysis results and flags any detected dangers, as well as identifying the type and location of the danger.

[0780] Output: Danger detection flag, type of danger and location information

[0781] Specific operation: The server searches for specific patterns (e.g., near an outlet or near a window) based on the results of the analysis algorithm, and if a danger is identified, it sets a danger flag and prepares information to proceed to the next step.

[0782] Step 5:

[0783] Sending a warning order

[0784] Input: Danger detection flag, type of danger and location information

[0785] Processing: If a danger is detected, the server sends a warning command to the device, including the type of danger and its location.

[0786] Output: Warning command for terminal

[0787] Specific operation: The server generates an appropriate warning signal and sends it to the device via the network. The warning signal contains the type of danger recognized and its location.

[0788] Step 6:

[0789] Emotion analysis using an emotion engine

[0790] Input: Parent's facial expression data, voice data

[0791] Processing: The emotion engine installed on the device analyzes the parent's emotional state using the camera and microphone.

[0792] Output: Parent's emotional state information

[0793] Specific operation: The device's camera captures the parent's facial expressions and the microphone records the tone of their voice. The emotion engine analyzes this data to determine the parent's emotional state.

[0794] Step 7:

[0795] Warning sound generation and adjustment

[0796] Input: Warning command, parent's emotional state information

[0797] Processing: The device generates a warning sound based on the warning command, and adjusts the content and volume of the warning sound based on the parent's emotional state.

[0798] Output: Audible warning sound

[0799] What it does: Plays an appropriate warning sound through the device speaker. Based on the results of the emotion engine, for example, if the parent is stressed, it lowers the volume and plays a softer message.

[0800] Step 8:

[0801] Parental Notification

[0802] Input: Danger detection flag, parent's emotional state information

[0803] Processing: The server notifies the parent's device that a danger has been detected. The content and urgency of the notification are adjusted according to the parent's emotional state.

[0804] Output: Notification message to parent device

[0805] Specific operation: The server sends warning information to the parent's device in the form of an app notification or email. Based on the results of the emotion engine, for example, if the parent is feeling stressed, the server will send a soft-spoken notification.

[0806] (Application example 2)

[0807] 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."

[0808] Conventional home monitoring systems have a means of detecting danger to ensure child safety, but they uniformly issue warning sounds without considering the parent's emotional state, which can increase parental stress. Furthermore, even if a parent is busy and unable to respond immediately, important notifications may not be properly delivered. The present invention aims to solve these problems and provide a more flexible and effective child monitoring system.

[0809] 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.

[0810] In this invention, the server includes a means for collecting real-time data, a means for transmitting the collected data, and a means for analyzing the received data and detecting a dangerous situation, which makes it possible to combine an emotion recognition means for analyzing the user's emotion with a means for adjusting the content and volume of the warning sound based on the emotion recognition result.

[0811] "Sensors" are devices such as cameras, motion sensors, and environmental sensors that collect data in real time.

[0812] "Real-time data" refers to data obtained from sensors and information that is sent to a server immediately without any time delay.

[0813] A "server" is a computer system that receives and analyzes the collected data.

[0814] A "danger situation" is a condition that indicates a child is in a dangerous place or situation.

[0815] A "warning sound" is a notification sound such as a voice message or a beep that is generated based on a detected dangerous situation.

[0816] A "parent's device" is an electronic device such as a smartphone or tablet that is owned by the parent.

[0817] "Emotion recognition means" is a technology that analyzes a user's facial expressions and voice to determine their emotional state.

[0818] The "adjustment means" is a mechanism for changing the content and volume of the warning sound based on the emotion recognition result.

[0819] System Overview

[0820] This invention is a monitoring system designed to keep children safe at home. The system is composed of multiple elements, including sensors, a server, a terminal, and an emotion engine that recognizes the user's emotions. The sensors include cameras, motion sensors, and environmental sensors, and real-time data acquired from these sensors is sent to the server. The server analyzes the data, detects dangerous situations, and sends a command to the terminal to issue an alert. The system also has the function of analyzing the user's emotional state to adjust the content and volume of the alert sound.

[0821] Hardware and software used

[0822] Sensors: Camera, motion sensors, environmental sensors

[0823] Server: A computer system that collects and analyzes data.

[0824] Device: Electronic devices such as smartphones and tablets owned by parents

[0825] Emotion engine: Software for recognizing user emotions (e.g., EmotionRecognizer)

[0826] Communications: Internet connection for data transmission and notifications

[0827] System operation explanation

[0828] Data collection

[0829] Sensors are installed in each room of the home to monitor the child's location and movements. Cameras capture images in real time, motion sensors detect the child's proximity and movement, and environmental sensors measure temperature and humidity. Data collected from these sensors is immediately sent to a server.

[0830] Data analysis

[0831] The server analyzes the received data and evaluates the child's current location and movements. For example, if a child approaches an electrical outlet, it combines data from the motion sensor with camera footage to detect a dangerous situation. Based on the analysis results, it immediately sends a command to the device to sound an alarm.

[0832] emotion recognition

[0833] The device is equipped with an emotion engine that recognizes the user's emotions and uses a camera and microphone to analyze the user's facial expressions and voice to determine their emotions. For example, by reading a parent's facial expression and analyzing their tone of voice, the device can determine whether they are feeling stressed or relieved.

[0834] Adjust alert sounds and notifications

[0835] Upon receiving a command from the server, the device will emit an alert sound. The content and volume of the alert sound will be adjusted based on the user's emotional state as analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume will be lowered and a calming voice message will be played. In addition, a notification will be sent to the parent's device to provide information to help them understand their child's current situation.

[0836] Specific examples

[0837] Proximity to electrical outlets

[0838] 1. The sensor detects when a child approaches an outlet and sends the data to the server.

[0839] 2. The server analyzes the data and recognizes the danger.

[0840] 3. The server sends a command to the device to generate an alarm sound.

[0841] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0842] 5. A warning sound will be emitted saying "Do not touch the outlet."

[0843] 6. A notification will be sent to the parent's device saying "Your child is approaching an outlet."

[0844] Approaching the window

[0845] 1. The sensor detects the child's approach to the window and sends the data to the server.

[0846] 2. The server analyzes the data and recognizes the danger.

[0847] 3. The server sends a command to the device to generate an alarm sound.

[0848] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[0849] 5. A warning sound will be emitted, such as "Do not open the window."

[0850] 6. A notification will be sent to the parent's device saying "Your child is trying to open a window."

[0851] Example prompts for generative AI models

[0852] Image-based hazard detection:

[0853] Use image analysis to detect danger when a child approaches an electrical outlet.

[0854] Emotion recognition:

[0855] Please judge the parent's emotional state as indicated by this image and adjust the notification content and volume accordingly.

[0856] As described above, the present invention makes it possible to flexibly adjust the warning sound in accordance with the emotional state of the parent, thereby ensuring the safety of the child.

[0857] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0858] Step 1:

[0859] Sensors detect the child's location and movements in real time.

[0860] Input: Camera footage, motion sensor data, environmental sensor data

[0861] Data processing: Extract the child's location from the camera footage, analyze the child's movements from the motion sensor data, and obtain temperature and humidity from the environmental sensor data.

[0862] Output: Parsed child's position, movement, and environment information

[0863] Step 2:

[0864] The terminal transmits the collected data to the server.

[0865] Input: Parsed child location, movement, and environment information

[0866] Data processing: Convert the data into JSON format and send it to the server.

[0867] Output: Data sent to the server

[0868] Step 3:

[0869] The server analyzes the received data and detects dangerous situations.

[0870] Input: Data sent to the server (child's location, movements, and environmental information)

[0871] Data Calculation: Analyzes the data and performs rule-based analysis to determine whether a child is in a dangerous location. For example, if a child approaches an electrical outlet, it is considered a dangerous situation.

[0872] Output: Judgment result (presence or absence of dangerous situation)

[0873] Step 4:

[0874] If the server detects danger, it sends a command to the terminal to sound an alarm.

[0875] Input: Judgment result (danger situation)

[0876] Data processing: Based on the judgment result, a message is generated to send to the terminal an instruction to issue an alarm.

[0877] Output: Warning sound generation command

[0878] Step 5:

[0879] The terminal receives the instruction to generate an alert sound and analyzes the user's emotional state.

[0880] Input: Sound alarm command

[0881] Data calculation: Using the device's camera and microphone, the user's facial expressions and voice are captured and their emotions are analyzed using an emotion recognition model (e.g., EmotionRecognizer).

[0882] Output: User's emotional state

[0883] Step 6:

[0884] The device adjusts the content and volume of the warning sound based on the emotion recognition results.

[0885] Input: User's emotional state, command to sound an alert

[0886] Data calculation: Analyzes the user's emotional state and determines the appropriate alert content and volume settings. For example, if the user is stressed, lower the volume and select a calm voice message.

[0887] Output: Adjusted warning sound settings

[0888] Step 7:

[0889] The device will emit an alert and send a notification to the parent device.

[0890] Input: Adjusted warning sound settings, judgment result

[0891] Data processing: Generates an alarm sound and plays it through the speaker. Also generates and sends a notification message to the parent's device to inform them of the current situation.

[0892] Output: generated alerts, sent notification messages

[0893] 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.

[0894] 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.

[0895] 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.

[0896] [Third embodiment]

[0897] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0898] 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.

[0899] 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).

[0900] 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.

[0901] 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.

[0902] 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).

[0903] 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.

[0904] 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.

[0905] 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.

[0906] 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.

[0907] 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.

[0908] 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."

[0909] The system of the present invention consists of multiple sensors installed in the home, a server that processes and analyzes the data, and a device (parent's smartphone or tablet) that receives notifications. This system collects data in real time to ensure the safety of children, detects dangerous situations, and generates an alarm to notify parents.

[0910] Sensor installation and operation

[0911] The sensors included in the device consist of a camera, motion sensors, and environmental sensors. The camera captures video data in real time and tracks the child's movements. The motion sensor detects whether the child is approaching a specific dangerous area (e.g., the kitchen or stairs). The environmental sensor collects environmental data such as temperature and humidity to monitor whether the child is in a safe environment.

[0912] Data collection and transmission

[0913] The device collects data from these sensors in real time and transmits it to a server at regular intervals. The collected data includes the child's location, movement, temperature, humidity, etc. This data is converted into a format that the server can understand and transmitted via a communication module.

[0914] Data analysis and risk detection

[0915] The server analyzes the received data. This analysis involves comparing the child's current location with past behavioral patterns. Specifically, if the child stays in a specific area for a certain amount of time or repeats a certain behavior, the server compares this with past data to predict danger.

[0916] For example, if a child is near an electrical outlet, the server analyzes their location information and determines the danger based on similar behavior patterns in the past. In this case, before the child actually touches the outlet, the server detects the danger and sends a warning signal to the device.

[0917] Warning sound generation

[0918] The device immediately generates a warning sound based on the warning signal received from the server. This warning sound may be a voice message or a beep to warn the child of the danger. For example, a voice message saying "Do not touch the outlet" is played.

[0919] Parental Notification

[0920] At the same time, the server generates a message to notify the parent of the danger. This message is sent to the smartphone or tablet in the form of an app notification or email. For example, a warning message saying "Your child is approaching an electrical outlet" can be sent, allowing the parent to take immediate action.

[0921] Specific examples

[0922] Example 1: What to do if a child approaches an electrical outlet

[0923] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0924] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0925] 3. The server recognizes the danger and sends a command to the terminal to generate an alarm sound.

[0926] 4. The device will emit a warning sound saying "Do not touch the power outlet."

[0927] 5. The server sends a notification to the parent's device saying, "Your child is approaching an outlet."

[0928] Example 2: What to do if a child tries to open a window

[0929] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0930] 2. The device sends the collected data to the server.

[0931] 3. The server analyzes the data and determines that the child is trying to open the window.

[0932] 4. The server sends a command to the terminal to generate an alarm sound.

[0933] 5. The device will emit a warning sound saying "Do not open the window."

[0934] 6. The server sends a notification to the parent's device saying, "Your child is trying to open a window."

[0935] Such systems will dramatically improve the safety of children and allow parents to go about their daily lives with peace of mind.

[0936] The processing flow will be explained below.

[0937] Step 1:

[0938] The device initializes the sensors and checks that the camera, motion sensor, and environmental sensor are working properly, so the sensors are ready to work properly.

[0939] Step 2:

[0940] The device receives real-time data from initialized sensors: a camera detects the child's location, motion sensors detect surrounding movement, and environmental sensors measure temperature and humidity.

[0941] Step 3:

[0942] The device formats the acquired real-time data for transmission to the server, including the child's location, movement, temperature, and humidity.

[0943] Step 4:

[0944] The terminal sends the formatted data to the server via a communication module, so that the collected data reaches the server for analysis.

[0945] Step 5:

[0946] The server receives data transmitted from the terminal, including the child's location information, movement information, and environmental data.

[0947] Step 6:

[0948] The server analyzes the received data to determine if a dangerous situation is occurring, which involves matching the child's current location with past behavioral patterns.

[0949] Step 7:

[0950] The server sends a command to the terminal to generate an alarm when a danger is detected.

[0951] Step 8:

[0952] The terminal receives the warning command from the server and generates a designated warning sound, which includes a voice message such as "Do not touch the outlet."

[0953] Step 9:

[0954] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email.

[0955] Step 10:

[0956] The user (parent) receives the notification from the server, checks the child's current status, and takes appropriate action. For example, the parent who receives the notification may go and check on the child in person.

[0957] Example 1

[0958] 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."

[0959] Conventional child safety monitoring systems have limitations in ensuring safety due to the difficulty of detecting danger in real time and notifying parents promptly. In particular, they are unable to predict danger based on specific behavioral patterns or environmental data, which can delay parents from taking appropriate action.

[0960] 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.

[0961] In this invention, the server includes a means for transmitting data collected by the terminal to the server at regular intervals, a means for converting the data received by the server into an understandable format, and a means for comparing past behavioral patterns with real-time location information in data analysis, thereby enabling real-time danger detection and prompt notification.

[0962] "Sensors" are devices for detecting specific conditions within the home, including cameras, motion sensors, and environmental sensors.

[0963] "Real-time data" refers to data on the current situation or environment obtained by sensors, which is processed and transmitted immediately.

[0964] "Server" means a device or system that receives and analyzes data sent from a terminal and issues alerts based on specific conditions.

[0965] "Warning sounds" are sounds used to warn users, such as voice messages or beeps, that are generated when a dangerous situation is detected.

[0966] A "parent device" is a device that receives alert notifications about the child's status, and refers to a smartphone or tablet owned by the parent.

[0967] "Data transmission" is the communication process of transferring collected data from the terminal to the server.

[0968] "Data reformatting" is the process of converting data received at a server into a format that can be parsed.

[0969] "Data analysis" is the process of identifying specific patterns or situations based on received data and detecting dangers.

[0970] "Dangerous situations" refer to situations in which a child approaches a dangerous area or performs a dangerous action.

[0971] An "interval" refers to a fixed time interval set when transmitting or processing data.

[0972] "Behavioral patterns" refer to a child's tendency to move and perform a series of actions, analyzed based on past data.

[0973] A "warning signal" is a signal generated by a server and sent to a terminal to notify it of a dangerous situation.

[0974] The system of the present invention consists of multiple sensor devices installed in the home, a server that processes and analyzes the data, and a terminal (parent's smartphone or tablet) for receiving notifications. The main purpose of this system is to ensure the safety of children, collecting data in real time, detecting dangerous situations, and notifying parents with an alarm.

[0975] Sensor installation and operation

[0976] The device manages sensors installed in the home. These sensors include cameras, motion sensors, and environmental sensors. Specifically, the camera sensors capture video data in real time and track children's movements. The motion sensors detect whether children are approaching specific dangerous areas (e.g., the kitchen or stairs), and the environmental sensors capture environmental data such as temperature and humidity.

[0977] Data collection and transmission

[0978] The device collects data from sensors in real time and transmits it to a server at regular intervals. The data includes the child's location, movement, and environmental data, and is transferred to the server via a communication module.

[0979] Receiving and formatting data

[0980] The server receives the data sent from the device and converts it into a format that can be analyzed. For example, video data is converted into a format that can be analyzed using an image processing algorithm.

[0981] Data analysis

[0982] The server then analyzes the received data. This analysis involves comparing real-time location information with past behavioral patterns. Specific examples include determining whether a person has stayed in a specific area for a certain amount of time or whether they have repeatedly performed a specific action.

[0983] Hazard detection and warning signal transmission

[0984] If the server detects a dangerous situation based on the data analysis, it will send a warning signal to the device. For example, if a child stays near an electrical outlet for a certain period of time, the server will generate a warning signal based on this information.

[0985] Warning sound generation

[0986] The device immediately generates a warning sound based on the warning signal received from the server. The warning sound is a voice message or a beep to warn the child of the danger. For example, a voice message saying "Do not touch the outlet" is played.

[0987] Parental Notification

[0988] When a danger is detected, the server sends a notification to the parent's device. The notification can be sent via push notification in the app or via email. For example, a warning message saying "your child is approaching an electrical outlet" can be sent to the parent's smartphone or tablet, allowing the parent to take prompt action.

[0989] Specific examples

[0990] Example 1: What to do if a child approaches an electrical outlet

[0991] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[0992] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[0993] 3. The server recognizes the danger and sends a command to the terminal to generate an alarm sound.

[0994] 4. The device will emit a warning sound saying "Do not touch the power outlet."

[0995] 5. The server sends a notification to the parent's device saying, "Your child is approaching an outlet."

[0996] Example 2: What to do if a child tries to open a window

[0997] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[0998] 2. The device sends the collected data to the server.

[0999] 3. The server analyzes the data and determines that the child is trying to open the window.

[1000] 4. The server sends a command to the terminal to generate an alarm sound.

[1001] 5. The device will emit a warning sound saying "Do not open the window."

[1002] 6. The server sends a notification to the parent's device saying, "Your child is trying to open a window."

[1003] Prompt Sentence Examples

[1004] Example prompts to input to a generative AI model:

[1005] "Please explain the program process for a system that uses sensors installed in the home to monitor child safety. The sensors are cameras, motion sensors, and environmental sensors. A server analyzes the data and sends a notification to the parent's device if a danger is detected. As a concrete example, please explain the processing flow when a child approaches an electrical outlet and when they try to open a window."

[1006] In this way, the present invention ensures the safety of children and provides an environment in which parents can live with peace of mind.

[1007] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1008] Step 1: Acquiring data from the sensor

[1009] The device collects real-time data from various sensors (cameras, motion sensors, and environmental sensors) installed in the home. For example, the camera sensor collects video data, and the motion sensor detects when a child approaches a specific dangerous area. The environmental sensor measures the temperature and humidity inside the room. The input includes raw data from the sensors, and the output is formatted data. Specifically, the video data is saved frame by frame, and the motion sensor data is saved as location information.

[1010] Step 2: Sending data

[1011] The terminal transmits the acquired data to the server at regular intervals. The input is the formatted data acquired from the sensor, and the output is the transmitted data sent to the server. Specifically, a communication module is used to transfer the data to the server in JSON format or similar. Each piece of data is given a timestamp to maintain consistency.

[1012] Step 3: Receiving and formatting data

[1013] The server receives data sent from the device. The received data includes location information, motion information, temperature, humidity, etc. The input is the raw data sent from the device, and the output is data formatted into an analyzable format. Specifically, the data is temporarily stored and formatted as needed using image processing algorithms and data analysis algorithms.

[1014] Step 4: Analyze the data

[1015] The server analyzes the received data. The input is formatted data, and the output is analysis results. Specifically, it compares real-time location information with past behavioral patterns to identify specific behavioral patterns and environmental conditions. Examples include when an individual has stayed in the same area for a certain period of time, or when environmental data has reached a dangerous value.

[1016] Step 5: Detect danger and send a warning signal

[1017] If the server detects a dangerous situation as a result of data analysis, it sends a warning signal to the device. The analysis results are input, and a warning signal is generated as output. Specifically, if a child stays near an electrical outlet for a long time, for example, a warning signal is generated and sent to the device.

[1018] Step 6: Sound the alarm

[1019] The terminal immediately generates a warning sound based on the warning signal received from the server. The received warning signal is the input, and the generated warning sound is the output. For example, a voice message saying "Do not touch the outlet" is played to warn children.

[1020] Step 7: Parental Notification

[1021] The server sends a notification to the parent's device when a danger is detected. The input is the detection result, and the output is a warning message sent to the parent's smartphone or tablet. Specifically, a message such as "Your child is approaching an outlet" is sent immediately, allowing the parent to check the situation and take prompt action.

[1022] This is the flow of the program processing for this system. In this way, the system is able to detect danger in real time and respond quickly, ensuring the safety of children.

[1023] (Application example 1)

[1024] 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."

[1025] Conventional home security systems lack the real-time and multifaceted capabilities to ensure children's safety. In particular, notifying parents alone when an abnormality occurs often results in delayed response, which is a major problem when response is required outside the home. Therefore, there is a need to develop a system that utilizes home sensors to instantly detect abnormalities and notify parents and a security center.

[1026] 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.

[1027] In this invention, the server includes means for collecting real-time data from the sensors, means for transmitting the collected data to the server, means for analyzing the received data on the server and detecting dangerous situations, means for generating an alarm based on the detected dangerous situation, and means for notifying the parent's terminal and the security center of the detected dangerous situation. This allows the parent and the security center to be notified simultaneously when an abnormality occurs, enabling a rapid and multifaceted response.

[1028] A "sensor" is a device that detects physical conditions or changes and collects that data.

[1029] "Real-time data" refers to data that is collected continuously by sensors and is immediate and has no time delay.

[1030] A "server" is a central computer system for collecting, analyzing, processing, and transmitting data.

[1031] A "dangerous situation" is a situation that is detected by a sensor and analyzed by a server, and determines that there is a potential risk to a child or the home.

[1032] A "warning sound" is an alert that is generated as a voice or beep when a dangerous situation is detected.

[1033] A "parent device" is a device, such as a smartphone or tablet, that is owned by the parent and used to receive notifications.

[1034] A "security center" is a specialized institution that handles security measures outside the home, and is a facility that responds quickly upon receiving notification of an abnormality.

[1035] "Notification" is a communication that informs the parent's device or security center of a dangerous situation detected by the server.

[1036] As an embodiment of the present invention, the following system is constructed. First, multiple sensors are installed in a home. These sensors include cameras, motion sensors, and environmental sensors. As a specific example, the cameras track children's movements and collect video data in real time. The motion sensors detect when a child approaches a specific dangerous area (e.g., the kitchen or stairs). The environmental sensors acquire environmental data such as temperature and humidity, and monitor whether the child is living in a safe environment.

[1037] The collected data is sent to a server via a Wi-Fi module. The server is equipped with data analysis software that includes a Python-based machine learning model, which analyzes the data in real time. This analysis uses an anomaly detection algorithm to detect an anomaly if a specified condition is met (e.g., a child getting too close to the door).

[1038] If an abnormality is detected, the server simultaneously sends a warning signal to the parent device (smartphone or tablet) and the security center. The parent device immediately displays a notification and generates an audible warning (voice message or beep) based on the received warning signal. The security center displays an abnormality notification on its web dashboard, allowing an operator to initiate response procedures.

[1039] For example, here is a specific example of a child trying to open a door:

[1040] 1. In-home sensors detect children's movements and collect data on their approach to the door.

[1041] 2. The sensor sends the data to the server.

[1042] 3. The server analyzes the data and determines that a child is trying to open the door.

[1043] 4. The server sends a command to the parent's smartphone to generate an alarm sound and simultaneously sends an alert to the security center.

[1044] 5. A parent's smartphone will emit a warning sound saying "Do not open the door."

[1045] 6. The security center will have an operator respond (e.g., check the camera footage and dispatch security guards).

[1046] Additionally, to perform anomaly analysis using a generative AI model, the following prompts can be used:

[1047] Example prompt sentence:

[1048] “Your child is opening a door in your home, please analyze the information below and provide safety measures.

[1049] Child's current location: Living room

[1050] Operational Information: Standing upright near the door

[1051] Environmental data: 19°C, 40% humidity

[1052] Video feed: [Real-time video URL]

[1053] Required actions:

[1054] 1. Send a warning message to the parent's smartphone

[1055] 2. Send an alert to the Security Center

[1056] 3. Triggering an audio warning

[1057] Such a system will strengthen security within the home and enable rapid and multifaceted response in the event of an emergency.

[1058] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1059] Step 1:

[1060] In-home sensors collect real-time data on children's behavior and environment. Specifically, cameras monitor children's movements and record the footage as digital data. Motion sensors detect approach to specific danger areas, and environmental sensors measure temperature and humidity. This data is temporarily stored in local storage.

[1061] Input: Child's movement information, environmental data

[1062] Output: Collected real-time data (video data, motion data, environmental data)

[1063] Step 2:

[1064] The collected real-time data is sent to a server via a home communication module. Specifically, the data is sent in bulk in packet format using a Wi-Fi module. During this process, the data is reformatted (for example, converted to JSON format).

[1065] Input: Collected real-time data (video data, behavior data, environmental data)

[1066] Output: Data packets sent to the server

[1067] Step 3:

[1068] The server analyzes the received data. It uses a Python-based machine learning model to execute an anomaly detection algorithm. Specifically, it compares current data with past data to detect abnormal patterns (such as a child approaching a door). Data processing includes time series analysis and clustering.

[1069] Input: Data packet sent to the server

[1070] Output: Detected abnormal patterns

[1071] Step 4:

[1072] If the server detects an abnormal pattern, it generates a warning signal, which includes details of the abnormal situation (e.g., a child trying to open a door), and generates an appropriate countermeasure by inputting a prompt sentence into the generative AI model.

[1073] Input: Detected abnormal pattern

[1074] Output: Warning signal, action to be taken based on the prompt

[1075] Step 5:

[1076] The server sends the generated warning signal and countermeasures to the parent device and the security center. The parent device displays a warning message and an alarm sound. At the same time, an alert is sent to the security center and displayed on the center's dashboard.

[1077] Input: Warning signals, countermeasures based on prompts

[1078] Output: Notifications on parent's device, Security Center alerts

[1079] Step 6:

[1080] When the parent device receives the warning message, the user can take action based on the message. At the same time, security center operators also check the dashboard and take action, such as dispatching security guards to the scene, if necessary.

[1081] Input: Parental device notifications, Security Center alerts

[1082] Output: User response, Security Center action

[1083] This process allows parents and security centers to respond quickly and effectively when a child faces a dangerous situation at home.

[1084] 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.

[1085] This invention provides a system for ensuring children's safety at home, and is composed of sensors, a server, a terminal, and an emotion engine. This system detects dangerous situations for children based on real-time data obtained from the sensors, generates an alarm, and notifies parents. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, the system has the function of adjusting the alarm sound and notification content according to the user's emotional state.

[1086] Sensor installation and operation

[1087] The device is equipped with a camera, motion sensors, and environmental sensors. The camera captures images of the child in real time, the motion sensors detect the child's proximity and movement, and the environmental sensors measure temperature and humidity. The data collected by these sensors is important information for keeping children safe.

[1088] Data collection and transmission

[1089] The device sends data collected in real time from the sensors to a server, including the child's location, movement, temperature, humidity, etc. The collected data is sent to the server at regular intervals for analysis.

[1090] Data analysis and risk detection

[1091] The server receives and analyzes the data sent from the device. This analysis includes evaluating the child's current location and movements and determining whether the situation is dangerous. If danger is detected, the server immediately sends a command to the device to sound an alarm.

[1092] Emotion Engine Operation

[1093] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine uses a camera and microphone to analyze emotions from the user's facial expressions and voice. For example, by reading a parent's facial expression with the camera and analyzing the tone of their voice with the microphone, it can determine whether the parent is feeling stressed or relieved.

[1094] Warning sound generation and adjustment

[1095] When the device receives a warning command from the server, it generates a warning sound. The content and volume of the warning sound are adjusted based on the user's emotional state analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume of the warning sound will be lowered and a more gentle voice message will be played.

[1096] Parental Notification

[1097] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email, allowing the parent to immediately understand their child's current situation and respond accordingly. In addition, the emotion engine adjusts the content and urgency of the notification according to the user's emotional state.

[1098] Specific examples

[1099] Example 1: When a child approaches an outlet

[1100] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[1101] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[1102] 3. The server recognizes the danger and sends a command to the terminal to sound an alarm.

[1103] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1104] 5. The device will emit a warning sound saying "Do not touch the power outlet."

[1105] 6. The server sends a notification to the parent's device saying "Your child is approaching an outlet," and the content of the notification is adjusted according to the parent's emotional state.

[1106] Example 2: A child is trying to open a window

[1107] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[1108] 2. The device sends the collected data to the server.

[1109] 3. The server analyzes the data and determines that the child is trying to open the window.

[1110] 4. The server sends a command to the device to sound an alarm.

[1111] 5. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1112] 6. The device will emit a warning sound saying "Do not open the window."

[1113] 7. The server sends a notification to the parent's device saying "Your child is trying to open the window," and the content of the notification is adjusted according to the parent's emotional state.

[1114] This system improves the safety of children at home and allows parents to live their daily lives with peace of mind. The introduction of an emotion engine allows the system to respond more flexibly to parents' needs and also contributes to reducing stress.

[1115] The processing flow will be explained below.

[1116] Step 1:

[1117] The device initializes the camera, motion sensors, and environmental sensors, ensuring that each sensor is ready to operate normally.

[1118] Step 2:

[1119] The device receives real-time data from initialized sensors: the camera detects the child's location, the motion sensor detects surrounding movement, and the environmental sensors measure temperature and humidity.

[1120] Step 3:

[1121] The device formats the acquired real-time data and sends it to the server, including the child's location, movement, temperature, and humidity.

[1122] Step 4:

[1123] The server receives the data transmitted from the device, including the child's location information, movement information, and environmental data.

[1124] Step 5:

[1125] The server analyzes the received data to determine if a dangerous situation is occurring, by evaluating the child's current location and movements, and immediately setting a danger flag if a danger is detected.

[1126] Step 6:

[1127] If a danger is detected, the server sends a command to the terminal to sound an alarm, including the type and content of the alarm sound.

[1128] Step 7:

[1129] The device receives warning commands from the server and uses its built-in emotion engine to assess the user's emotional state, analyzing facial expressions with a camera and tone of voice with a microphone.

[1130] Step 8:

[1131] The device adjusts the content and volume of the warning sound based on the user's emotional state obtained from the emotion engine. For example, if the user is feeling stressed, a calm voice message will be selected.

[1132] Step 9:

[1133] The device will emit a tailored warning sound, such as a voice message saying "Do not touch the outlet" or a beep.

[1134] Step 10:

[1135] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email.

[1136] Step 11:

[1137] The server adjusts the content and urgency of notifications based on the user's emotional state analyzed by the emotion engine. For example, if the user is relaxed, the notification will be more gentle.

[1138] Step 12:

[1139] The user (parent) receives the notification from the server and checks the child's current status. For example, the parent who received the notification may take action such as going to check on the child in person.

[1140] Example 2

[1141] 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."

[1142] In conventional systems for ensuring child safety at home, the warning sounds and notification content that are emitted when danger is detected are uniform and are not adjusted according to the emotional state of the parent, which can be stressful.In addition, there is room for improvement in the accuracy of danger detection and notification, and therefore, ensuring the safety of children at home is insufficient.

[1143] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1144] In this invention, the server includes means for collecting real-time data from the sensors, means for transmitting the collected data to the server, means for analyzing the received data on the server to detect dangerous situations, means for generating an alarm sound based on the detected dangerous situation, means for analyzing the emotional state of the user using emotion analysis means, means for adjusting the alarm sound and notification content according to the emotional state of the user, and means for notifying the parent's terminal of the detected dangerous situation. This enables the system for keeping children safe at home to respond flexibly to the emotional state of the parents and respond quickly while reducing stress.

[1145] A "sensor" is a device that detects physical or chemical changes in the environment and outputs the data.

[1146] "Real-time data" is data obtained from sensors or devices that is immediately available.

[1147] A "server" is a computing device that provides functions such as data management, analysis, and storage.

[1148] "Emotion analysis means" refers to technologies and algorithms that analyze a user's facial expressions, tone of voice, etc. to determine the user's emotional state.

[1149] A "warning sound" is an audio signal that is generated to alert the user when a danger is detected.

[1150] "Parent's device" refers to an electronic device such as a smartphone or tablet owned by the parent.

[1151] A "notification" is a message or alert sent to inform a user of specific information.

[1152] A "camera" is a device that uses an optical lens to capture video or images.

[1153] A "motion sensor" is a device for detecting the movement of an object.

[1154] An "environmental sensor" is a device that measures environmental conditions such as temperature, humidity, and air pressure.

[1155] The present invention relates to a system for ensuring children's safety at home. This system includes sensors, a server, a terminal, and an emotion engine. This system monitors the child's situation in real time and generates an alarm if a dangerous situation is detected. The system also has a function for sending notifications to parents, and by using the emotion engine, the content of the notifications and alarms can be adjusted according to the parent's emotional state.

[1156] Hardware Configuration

[1157] The device is equipped with the following sensors:

[1158] Camera: Captures real-time footage of your child.

[1159] Motion sensor: Detects the proximity and movement of children.

[1160] Environmental sensors: measure temperature and humidity.

[1161] These sensors provide important information to keep children safe.

[1162] Data collection and transmission

[1163] The device collects real-time data from the sensors and transmits it to a server at regular intervals, including the child's location, movement, temperature, humidity, and other information.

[1164] Data analysis and risk detection

[1165] The server receives and analyzes the data sent from the device. This analysis includes evaluating the child's current location and movements and determining whether the situation is dangerous. If danger is detected, the server immediately sends a command to the device to generate an alarm.

[1166] Emotion Engine Operation

[1167] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine uses a camera and microphone to analyze emotions from the user's facial expressions and voice. For example, by reading a parent's facial expression with the camera and analyzing the tone of their voice with the microphone, it can determine whether the parent is feeling stressed or relieved.

[1168] Warning sound generation and adjustment

[1169] The device generates a warning sound based on a warning command from the server. The content and volume of the warning sound are adjusted based on the user's emotional state analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume of the warning sound will be lowered and a more gentle voice message will be played.

[1170] Parental Notification

[1171] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email, allowing the parent to immediately understand their child's current situation and respond accordingly. In addition, the emotion engine adjusts the content and urgency of the notification according to the user's emotional state.

[1172] Specific examples

[1173] Example 1: When a child approaches an outlet

[1174] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[1175] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[1176] 3. The server recognizes the danger and sends a command to the terminal to sound an alarm.

[1177] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1178] 5. The device will emit a warning sound saying "Do not touch the power outlet."

[1179] 6. The server sends a notification to the parent's device saying "Your child is approaching an outlet," and the content of the notification is adjusted according to the parent's emotional state.

[1180] Example 2: A child is trying to open a window

[1181] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[1182] 2. The device sends the collected data to the server.

[1183] 3. The server analyzes the data and determines that the child is trying to open the window.

[1184] 4. The server sends a command to the device to sound an alarm.

[1185] 5. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1186] 6. The device will emit a warning sound saying "Do not open the window."

[1187] 7. The server sends a notification to the parent's device saying "Your child is trying to open the window," and the content of the notification is adjusted according to the parent's emotional state.

[1188] Prompt Sentence Examples

[1189] Prompt example 1

[1190] "Please explain in detail how this system works when a child approaches an electrical outlet. Please be specific about each step: sensor, server, device, and emotion engine."

[1191] Prompt example 2

[1192] "Please explain specifically how the system will sound an alarm and notify parents if a child tries to open a window."

[1193] As a result, the system of the present invention increases the safety of children and reduces stress for parents, allowing them to live their daily lives with peace of mind.In this way, by incorporating emotion analysis, we can improve the shortcomings of conventional systems and provide a more flexible and adaptable system.

[1194] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1195] Step 1:

[1196] Sensor data acquisition

[1197] Input: Physical changes from the surrounding environment (child's movement, temperature, humidity, etc.)

[1198] Processing: Cameras capture footage, motion sensors detect the child's movements, and environmental sensors measure temperature and humidity.

[1199] Output: Child's video data, movement data, environmental data

[1200] How it works: The device's built-in camera captures real-time footage of the child, the motion sensor captures the child's movements and proximity, and the environmental sensor measures the indoor temperature and humidity, temporarily storing this data internally.

[1201] Step 2:

[1202] Sending data

[1203] Input: Child's video data, movement data, environmental data

[1204] Processing: The device sends the collected data to the server at a specified interval (e.g., every 5 seconds).

[1205] Output: Data collected from the sensor is sent to the server

[1206] Specific operation: A program on the terminal stores the collected data in temporary memory and sends it to the server via the network as data packets at regular intervals.

[1207] Step 3:

[1208] Data reception and analysis

[1209] Input: Data packets sent from the sensor

[1210] Processing: The server receives the data, checks its integrity, stores it in a database in the correct format, and uses analysis algorithms to determine whether it poses a risk.

[1211] Output: Analysis results, whether there is a risk

[1212] Specific operation: The server receives the data packet, verifies the data integrity, and stores it in the database. It then uses an analysis algorithm to analyze the child's location and movements to assess whether there is any danger.

[1213] Step 4:

[1214] Hazard detection

[1215] Input: Server analysis results

[1216] Processing: The server evaluates the analysis results and flags any detected dangers, as well as identifying the type and location of the danger.

[1217] Output: Danger detection flag, type of danger and location information

[1218] Specific operation: The server searches for specific patterns (e.g., near an outlet or near a window) based on the results of the analysis algorithm, and if a danger is identified, it sets a danger flag and prepares information to proceed to the next step.

[1219] Step 5:

[1220] Sending a warning order

[1221] Input: Danger detection flag, type of danger and location information

[1222] Processing: If a danger is detected, the server sends a warning command to the device, including the type of danger and its location.

[1223] Output: Warning command for terminal

[1224] Specific operation: The server generates an appropriate warning signal and sends it to the device via the network. The warning signal contains the type of danger recognized and its location.

[1225] Step 6:

[1226] Emotion analysis using an emotion engine

[1227] Input: Parent's facial expression data, voice data

[1228] Processing: The emotion engine installed on the device analyzes the parent's emotional state using the camera and microphone.

[1229] Output: Parent's emotional state information

[1230] Specific operation: The device's camera captures the parent's facial expressions and the microphone records the tone of their voice. The emotion engine analyzes this data to determine the parent's emotional state.

[1231] Step 7:

[1232] Warning sound generation and adjustment

[1233] Input: Warning command, parent's emotional state information

[1234] Processing: The device generates a warning sound based on the warning command, and adjusts the content and volume of the warning sound based on the parent's emotional state.

[1235] Output: Audible warning sound

[1236] What it does: Plays an appropriate warning sound through the device speaker. Based on the results of the emotion engine, for example, if the parent is stressed, it lowers the volume and plays a softer message.

[1237] Step 8:

[1238] Parental Notification

[1239] Input: Danger detection flag, parent's emotional state information

[1240] Processing: The server notifies the parent's device that a danger has been detected. The content and urgency of the notification are adjusted according to the parent's emotional state.

[1241] Output: Notification message to parent device

[1242] Specific operation: The server sends warning information to the parent's device in the form of an app notification or email. Based on the results of the emotion engine, for example, if the parent is feeling stressed, the server will send a soft-spoken notification.

[1243] (Application example 2)

[1244] 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."

[1245] Conventional home monitoring systems have a means of detecting danger to ensure child safety, but they uniformly issue warning sounds without considering the parent's emotional state, which can increase parental stress. Furthermore, even if a parent is busy and unable to respond immediately, important notifications may not be properly delivered. The present invention aims to solve these problems and provide a more flexible and effective child monitoring system.

[1246] 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.

[1247] In this invention, the server includes a means for collecting real-time data, a means for transmitting the collected data, and a means for analyzing the received data and detecting a dangerous situation, which makes it possible to combine an emotion recognition means for analyzing the user's emotion with a means for adjusting the content and volume of the warning sound based on the emotion recognition result.

[1248] "Sensors" are devices such as cameras, motion sensors, and environmental sensors that collect data in real time.

[1249] "Real-time data" refers to data obtained from sensors and information that is sent to a server immediately without any time delay.

[1250] A "server" is a computer system that receives and analyzes the collected data.

[1251] A "danger situation" is a condition that indicates a child is in a dangerous place or situation.

[1252] A "warning sound" is a notification sound such as a voice message or a beep that is generated based on a detected dangerous situation.

[1253] A "parent's device" is an electronic device such as a smartphone or tablet that is owned by the parent.

[1254] "Emotion recognition means" is a technology that analyzes a user's facial expressions and voice to determine their emotional state.

[1255] The "adjustment means" is a mechanism for changing the content and volume of the warning sound based on the emotion recognition result.

[1256] System Overview

[1257] This invention is a monitoring system designed to keep children safe at home. The system is composed of multiple elements, including sensors, a server, a terminal, and an emotion engine that recognizes the user's emotions. The sensors include cameras, motion sensors, and environmental sensors, and real-time data acquired from these sensors is sent to the server. The server analyzes the data, detects dangerous situations, and sends a command to the terminal to issue an alert. The system also has the function of analyzing the user's emotional state to adjust the content and volume of the alert sound.

[1258] Hardware and software used

[1259] Sensors: Camera, motion sensors, environmental sensors

[1260] Server: A computer system that collects and analyzes data.

[1261] Device: Electronic devices such as smartphones and tablets owned by parents

[1262] Emotion engine: Software for recognizing user emotions (e.g., EmotionRecognizer)

[1263] Communications: Internet connection for data transmission and notifications

[1264] System operation explanation

[1265] Data collection

[1266] Sensors are installed in each room of the home to monitor the child's location and movements. Cameras capture images in real time, motion sensors detect the child's proximity and movement, and environmental sensors measure temperature and humidity. Data collected from these sensors is immediately sent to a server.

[1267] Data analysis

[1268] The server analyzes the received data and evaluates the child's current location and movements. For example, if a child approaches an electrical outlet, it combines data from the motion sensor with camera footage to detect a dangerous situation. Based on the analysis results, it immediately sends a command to the device to sound an alarm.

[1269] emotion recognition

[1270] The device is equipped with an emotion engine that recognizes the user's emotions and uses a camera and microphone to analyze the user's facial expressions and voice to determine their emotions. For example, by reading a parent's facial expression and analyzing their tone of voice, the device can determine whether they are feeling stressed or relieved.

[1271] Adjust alert sounds and notifications

[1272] Upon receiving a command from the server, the device will emit an alert sound. The content and volume of the alert sound will be adjusted based on the user's emotional state as analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume will be lowered and a calming voice message will be played. In addition, a notification will be sent to the parent's device to provide information to help them understand their child's current situation.

[1273] Specific examples

[1274] Proximity to electrical outlets

[1275] 1. The sensor detects when a child approaches an outlet and sends the data to the server.

[1276] 2. The server analyzes the data and recognizes the danger.

[1277] 3. The server sends a command to the device to generate an alarm sound.

[1278] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1279] 5. A warning sound will be emitted saying "Do not touch the outlet."

[1280] 6. A notification will be sent to the parent's device saying "Your child is approaching an outlet."

[1281] Approaching the window

[1282] 1. The sensor detects the child's approach to the window and sends the data to the server.

[1283] 2. The server analyzes the data and recognizes the danger.

[1284] 3. The server sends a command to the device to generate an alarm sound.

[1285] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1286] 5. A warning sound will be emitted, such as "Do not open the window."

[1287] 6. A notification will be sent to the parent's device saying "Your child is trying to open a window."

[1288] Example prompts for generative AI models

[1289] Image-based hazard detection:

[1290] Use image analysis to detect danger when a child approaches an electrical outlet.

[1291] Emotion recognition:

[1292] Please judge the parent's emotional state as indicated by this image and adjust the notification content and volume accordingly.

[1293] As described above, the present invention makes it possible to flexibly adjust the warning sound in accordance with the emotional state of the parent, thereby ensuring the safety of the child.

[1294] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1295] Step 1:

[1296] Sensors detect the child's location and movements in real time.

[1297] Input: Camera footage, motion sensor data, environmental sensor data

[1298] Data processing: Extract the child's location from the camera footage, analyze the child's movements from the motion sensor data, and obtain temperature and humidity from the environmental sensor data.

[1299] Output: Parsed child's position, movement, and environment information

[1300] Step 2:

[1301] The terminal transmits the collected data to the server.

[1302] Input: Parsed child location, movement, and environment information

[1303] Data processing: Convert the data into JSON format and send it to the server.

[1304] Output: Data sent to the server

[1305] Step 3:

[1306] The server analyzes the received data and detects dangerous situations.

[1307] Input: Data sent to the server (child's location, movements, and environmental information)

[1308] Data Calculation: Analyzes the data and performs rule-based analysis to determine whether a child is in a dangerous location. For example, if a child approaches an electrical outlet, it is considered a dangerous situation.

[1309] Output: Judgment result (presence or absence of dangerous situation)

[1310] Step 4:

[1311] If the server detects danger, it sends a command to the terminal to sound an alarm.

[1312] Input: Judgment result (danger situation)

[1313] Data processing: Based on the judgment result, a message is generated to send to the terminal an instruction to issue an alarm.

[1314] Output: Warning sound generation command

[1315] Step 5:

[1316] The terminal receives the instruction to generate an alert sound and analyzes the user's emotional state.

[1317] Input: Sound alarm command

[1318] Data calculation: Using the device's camera and microphone, the user's facial expressions and voice are captured and their emotions are analyzed using an emotion recognition model (e.g., EmotionRecognizer).

[1319] Output: User's emotional state

[1320] Step 6:

[1321] The device adjusts the content and volume of the warning sound based on the emotion recognition results.

[1322] Input: User's emotional state, command to sound an alert

[1323] Data calculation: Analyzes the user's emotional state and determines the appropriate alert content and volume settings. For example, if the user is stressed, lower the volume and select a calm voice message.

[1324] Output: Adjusted warning sound settings

[1325] Step 7:

[1326] The device will emit an alert and send a notification to the parent device.

[1327] Input: Adjusted warning sound settings, judgment result

[1328] Data processing: Generates an alarm sound and plays it through the speaker. Also generates and sends a notification message to the parent's device to inform them of the current situation.

[1329] Output: generated alerts, sent notification messages

[1330] 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.

[1331] 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.

[1332] 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.

[1333] [Fourth embodiment]

[1334] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1335] 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.

[1336] 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).

[1337] 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.

[1338] 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.

[1339] 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).

[1340] 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.

[1341] 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.

[1342] 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.

[1343] 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.

[1344] 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.

[1345] 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.

[1346] 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."

[1347] The system of the present invention consists of multiple sensors installed in the home, a server that processes and analyzes the data, and a device (parent's smartphone or tablet) that receives notifications. This system collects data in real time to ensure the safety of children, detects dangerous situations, and generates an alarm to notify parents.

[1348] Sensor installation and operation

[1349] The sensors included in the device consist of a camera, motion sensors, and environmental sensors. The camera captures video data in real time and tracks the child's movements. The motion sensor detects whether the child is approaching a specific dangerous area (e.g., the kitchen or stairs). The environmental sensor collects environmental data such as temperature and humidity to monitor whether the child is in a safe environment.

[1350] Data collection and transmission

[1351] The device collects data from these sensors in real time and transmits it to a server at regular intervals. The collected data includes the child's location, movement, temperature, humidity, etc. This data is converted into a format that the server can understand and transmitted via a communication module.

[1352] Data analysis and risk detection

[1353] The server analyzes the received data. This analysis involves comparing the child's current location with past behavioral patterns. Specifically, if the child stays in a specific area for a certain amount of time or repeats a certain behavior, the server compares this with past data to predict danger.

[1354] For example, if a child is near an electrical outlet, the server analyzes their location information and determines the danger based on similar behavior patterns in the past. In this case, before the child actually touches the outlet, the server detects the danger and sends a warning signal to the device.

[1355] Warning sound generation

[1356] The device immediately generates a warning sound based on the warning signal received from the server. This warning sound may be a voice message or a beep to warn the child of the danger. For example, a voice message saying "Do not touch the outlet" is played.

[1357] Parental Notification

[1358] At the same time, the server generates a message to notify the parent of the danger. This message is sent to the smartphone or tablet in the form of an app notification or email. For example, a warning message saying "Your child is approaching an electrical outlet" can be sent, allowing the parent to take immediate action.

[1359] Specific examples

[1360] Example 1: What to do if a child approaches an electrical outlet

[1361] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[1362] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[1363] 3. The server recognizes the danger and sends a command to the terminal to generate an alarm sound.

[1364] 4. The device will emit a warning sound saying "Do not touch the power outlet."

[1365] 5. The server sends a notification to the parent's device saying, "Your child is approaching an outlet."

[1366] Example 2: What to do if a child tries to open a window

[1367] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[1368] 2. The device sends the collected data to the server.

[1369] 3. The server analyzes the data and determines that the child is trying to open the window.

[1370] 4. The server sends a command to the terminal to generate an alarm sound.

[1371] 5. The device will emit a warning sound saying "Do not open the window."

[1372] 6. The server sends a notification to the parent's device saying, "Your child is trying to open a window."

[1373] Such systems will dramatically improve the safety of children and allow parents to go about their daily lives with peace of mind.

[1374] The processing flow will be explained below.

[1375] Step 1:

[1376] The device initializes the sensors and checks that the camera, motion sensor, and environmental sensor are working properly, so the sensors are ready to work properly.

[1377] Step 2:

[1378] The device receives real-time data from initialized sensors: a camera detects the child's location, motion sensors detect surrounding movement, and environmental sensors measure temperature and humidity.

[1379] Step 3:

[1380] The device formats the acquired real-time data for transmission to the server, including the child's location, movement, temperature, and humidity.

[1381] Step 4:

[1382] The terminal sends the formatted data to the server via a communication module, so that the collected data reaches the server for analysis.

[1383] Step 5:

[1384] The server receives data transmitted from the terminal, including the child's location information, movement information, and environmental data.

[1385] Step 6:

[1386] The server analyzes the received data to determine if a dangerous situation is occurring, which involves matching the child's current location with past behavioral patterns.

[1387] Step 7:

[1388] The server sends a command to the terminal to generate an alarm when a danger is detected.

[1389] Step 8:

[1390] The terminal receives the warning command from the server and generates a designated warning sound, which includes a voice message such as "Do not touch the outlet."

[1391] Step 9:

[1392] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email.

[1393] Step 10:

[1394] The user (parent) receives the notification from the server, checks the child's current status, and takes appropriate action. For example, the parent who receives the notification may go and check on the child in person.

[1395] Example 1

[1396] 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."

[1397] Conventional child safety monitoring systems have limitations in ensuring safety due to the difficulty of detecting danger in real time and notifying parents promptly. In particular, they are unable to predict danger based on specific behavioral patterns or environmental data, which can delay parents from taking appropriate action.

[1398] 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.

[1399] In this invention, the server includes a means for transmitting data collected by the terminal to the server at regular intervals, a means for converting the data received by the server into an understandable format, and a means for comparing past behavioral patterns with real-time location information in data analysis, thereby enabling real-time danger detection and prompt notification.

[1400] "Sensors" are devices for detecting specific conditions within the home, including cameras, motion sensors, and environmental sensors.

[1401] "Real-time data" refers to data on the current situation or environment obtained by sensors, which is processed and transmitted immediately.

[1402] "Server" means a device or system that receives and analyzes data sent from a terminal and issues alerts based on specific conditions.

[1403] "Warning sounds" are sounds used to warn users, such as voice messages or beeps, that are generated when a dangerous situation is detected.

[1404] A "parent device" is a device that receives alert notifications about the child's status, and refers to a smartphone or tablet owned by the parent.

[1405] "Data transmission" is the communication process of transferring collected data from the terminal to the server.

[1406] "Data reformatting" is the process of converting data received at a server into a format that can be parsed.

[1407] "Data analysis" is the process of identifying specific patterns or situations based on received data and detecting dangers.

[1408] "Dangerous situations" refer to situations in which a child approaches a dangerous area or performs a dangerous action.

[1409] An "interval" refers to a fixed time interval set when transmitting or processing data.

[1410] "Behavioral patterns" refer to a child's tendency to move and perform a series of actions, analyzed based on past data.

[1411] A "warning signal" is a signal generated by a server and sent to a terminal to notify it of a dangerous situation.

[1412] The system of the present invention consists of multiple sensor devices installed in the home, a server that processes and analyzes the data, and a terminal (parent's smartphone or tablet) for receiving notifications. The main purpose of this system is to ensure the safety of children, collecting data in real time, detecting dangerous situations, and notifying parents with an alarm.

[1413] Sensor installation and operation

[1414] The device manages sensors installed in the home. These sensors include cameras, motion sensors, and environmental sensors. Specifically, the camera sensors capture video data in real time and track children's movements. The motion sensors detect whether children are approaching specific dangerous areas (e.g., the kitchen or stairs), and the environmental sensors capture environmental data such as temperature and humidity.

[1415] Data collection and transmission

[1416] The device collects data from sensors in real time and transmits it to a server at regular intervals. The data includes the child's location, movement, and environmental data, and is transferred to the server via a communication module.

[1417] Receiving and formatting data

[1418] The server receives the data sent from the device and converts it into a format that can be analyzed. For example, video data is converted into a format that can be analyzed using an image processing algorithm.

[1419] Data analysis

[1420] The server then analyzes the received data. This analysis involves comparing real-time location information with past behavioral patterns. Specific examples include determining whether a person has stayed in a specific area for a certain amount of time or whether they have repeatedly performed a specific action.

[1421] Hazard detection and warning signal transmission

[1422] If the server detects a dangerous situation based on the data analysis, it will send a warning signal to the device. For example, if a child stays near an electrical outlet for a certain period of time, the server will generate a warning signal based on this information.

[1423] Warning sound generation

[1424] The device immediately generates a warning sound based on the warning signal received from the server. The warning sound is a voice message or a beep to warn the child of the danger. For example, a voice message saying "Do not touch the outlet" is played.

[1425] Parental Notification

[1426] When a danger is detected, the server sends a notification to the parent's device. The notification can be sent via push notification in the app or via email. For example, a warning message saying "your child is approaching an electrical outlet" can be sent to the parent's smartphone or tablet, allowing the parent to take prompt action.

[1427] Specific examples

[1428] Example 1: What to do if a child approaches an electrical outlet

[1429] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[1430] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[1431] 3. The server recognizes the danger and sends a command to the terminal to generate an alarm sound.

[1432] 4. The device will emit a warning sound saying "Do not touch the power outlet."

[1433] 5. The server sends a notification to the parent's device saying, "Your child is approaching an outlet."

[1434] Example 2: What to do if a child tries to open a window

[1435] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[1436] 2. The device sends the collected data to the server.

[1437] 3. The server analyzes the data and determines that the child is trying to open the window.

[1438] 4. The server sends a command to the terminal to generate an alarm sound.

[1439] 5. The device will emit a warning sound saying "Do not open the window."

[1440] 6. The server sends a notification to the parent's device saying, "Your child is trying to open a window."

[1441] Prompt Sentence Examples

[1442] Example prompts to input to a generative AI model:

[1443] "Please explain the program process for a system that uses sensors installed in the home to monitor child safety. The sensors are cameras, motion sensors, and environmental sensors. A server analyzes the data and sends a notification to the parent's device if a danger is detected. As a concrete example, please explain the processing flow when a child approaches an electrical outlet and when they try to open a window."

[1444] In this way, the present invention ensures the safety of children and provides an environment in which parents can live with peace of mind.

[1445] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1446] Step 1: Acquiring data from the sensor

[1447] The device collects real-time data from various sensors (cameras, motion sensors, and environmental sensors) installed in the home. For example, the camera sensor collects video data, and the motion sensor detects when a child approaches a specific dangerous area. The environmental sensor measures the temperature and humidity inside the room. The input includes raw data from the sensors, and the output is formatted data. Specifically, the video data is saved frame by frame, and the motion sensor data is saved as location information.

[1448] Step 2: Sending data

[1449] The terminal transmits the acquired data to the server at regular intervals. The input is the formatted data acquired from the sensor, and the output is the transmitted data sent to the server. Specifically, a communication module is used to transfer the data to the server in JSON format or similar. Each piece of data is given a timestamp to maintain consistency.

[1450] Step 3: Receiving and formatting data

[1451] The server receives data sent from the device. The received data includes location information, motion information, temperature, humidity, etc. The input is the raw data sent from the device, and the output is data formatted into an analyzable format. Specifically, the data is temporarily stored and formatted as needed using image processing algorithms and data analysis algorithms.

[1452] Step 4: Analyze the data

[1453] The server analyzes the received data. The input is formatted data, and the output is analysis results. Specifically, it compares real-time location information with past behavioral patterns to identify specific behavioral patterns and environmental conditions. Examples include when an individual has stayed in the same area for a certain period of time, or when environmental data has reached a dangerous value.

[1454] Step 5: Detect danger and send a warning signal

[1455] If the server detects a dangerous situation as a result of data analysis, it sends a warning signal to the device. The analysis results are input, and a warning signal is generated as output. Specifically, if a child stays near an electrical outlet for a long time, for example, a warning signal is generated and sent to the device.

[1456] Step 6: Sound the alarm

[1457] The terminal immediately generates a warning sound based on the warning signal received from the server. The received warning signal is the input, and the generated warning sound is the output. For example, a voice message saying "Do not touch the outlet" is played to warn children.

[1458] Step 7: Parental Notification

[1459] The server sends a notification to the parent's device when a danger is detected. The input is the detection result, and the output is a warning message sent to the parent's smartphone or tablet. Specifically, a message such as "Your child is approaching an outlet" is sent immediately, allowing the parent to check the situation and take prompt action.

[1460] This is the flow of the program processing for this system. In this way, the system is able to detect danger in real time and respond quickly, ensuring the safety of children.

[1461] (Application example 1)

[1462] 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."

[1463] Conventional home security systems lack the real-time and multifaceted capabilities to ensure children's safety. In particular, notifying parents alone when an abnormality occurs often results in delayed response, which is a major problem when response is required outside the home. Therefore, there is a need to develop a system that utilizes home sensors to instantly detect abnormalities and notify parents and a security center.

[1464] 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.

[1465] In this invention, the server includes means for collecting real-time data from the sensors, means for transmitting the collected data to the server, means for analyzing the received data on the server and detecting dangerous situations, means for generating an alarm based on the detected dangerous situation, and means for notifying the parent's terminal and the security center of the detected dangerous situation. This allows the parent and the security center to be notified simultaneously when an abnormality occurs, enabling a rapid and multifaceted response.

[1466] A "sensor" is a device that detects physical conditions or changes and collects that data.

[1467] "Real-time data" refers to data that is collected continuously by sensors and is immediate and has no time delay.

[1468] A "server" is a central computer system for collecting, analyzing, processing, and transmitting data.

[1469] A "dangerous situation" is a situation that is detected by a sensor and analyzed by a server, and determines that there is a potential risk to a child or the home.

[1470] A "warning sound" is an alert that is generated as a voice or beep when a dangerous situation is detected.

[1471] A "parent device" is a device, such as a smartphone or tablet, that is owned by the parent and used to receive notifications.

[1472] A "security center" is a specialized institution that handles security measures outside the home, and is a facility that responds quickly upon receiving notification of an abnormality.

[1473] "Notification" is a communication that informs the parent's device or security center of a dangerous situation detected by the server.

[1474] As an embodiment of the present invention, the following system is constructed. First, multiple sensors are installed in a home. These sensors include cameras, motion sensors, and environmental sensors. As a specific example, the cameras track children's movements and collect video data in real time. The motion sensors detect when a child approaches a specific dangerous area (e.g., the kitchen or stairs). The environmental sensors acquire environmental data such as temperature and humidity, and monitor whether the child is living in a safe environment.

[1475] The collected data is sent to a server via a Wi-Fi module. The server is equipped with data analysis software that includes a Python-based machine learning model, which analyzes the data in real time. This analysis uses an anomaly detection algorithm to detect an anomaly if a specified condition is met (e.g., a child getting too close to the door).

[1476] If an abnormality is detected, the server simultaneously sends a warning signal to the parent device (smartphone or tablet) and the security center. The parent device immediately displays a notification and generates an audible warning (voice message or beep) based on the received warning signal. The security center displays an abnormality notification on its web dashboard, allowing an operator to initiate response procedures.

[1477] For example, here is a specific example of a child trying to open a door:

[1478] 1. In-home sensors detect children's movements and collect data on their approach to the door.

[1479] 2. The sensor sends the data to the server.

[1480] 3. The server analyzes the data and determines that a child is trying to open the door.

[1481] 4. The server sends a command to the parent's smartphone to generate an alarm sound and simultaneously sends an alert to the security center.

[1482] 5. A parent's smartphone will emit a warning sound saying "Do not open the door."

[1483] 6. The security center will have an operator respond (e.g., check the camera footage and dispatch security guards).

[1484] Additionally, to perform anomaly analysis using a generative AI model, the following prompts can be used:

[1485] Example prompt sentence:

[1486] “Your child is opening a door in your home, please analyze the information below and provide safety measures.

[1487] Child's current location: Living room

[1488] Operational Information: Standing upright near the door

[1489] Environmental data: 19°C, 40% humidity

[1490] Video feed: [Real-time video URL]

[1491] Required actions:

[1492] 1. Send a warning message to the parent's smartphone

[1493] 2. Send an alert to the Security Center

[1494] 3. Triggering an audio warning

[1495] Such a system will strengthen security within the home and enable rapid and multifaceted response in the event of an emergency.

[1496] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1497] Step 1:

[1498] In-home sensors collect real-time data on children's behavior and environment. Specifically, cameras monitor children's movements and record the footage as digital data. Motion sensors detect approach to specific danger areas, and environmental sensors measure temperature and humidity. This data is temporarily stored in local storage.

[1499] Input: Child's movement information, environmental data

[1500] Output: Collected real-time data (video data, motion data, environmental data)

[1501] Step 2:

[1502] The collected real-time data is sent to a server via a home communication module. Specifically, the data is sent in bulk in packet format using a Wi-Fi module. During this process, the data is reformatted (for example, converted to JSON format).

[1503] Input: Collected real-time data (video data, behavior data, environmental data)

[1504] Output: Data packets sent to the server

[1505] Step 3:

[1506] The server analyzes the received data. It uses a Python-based machine learning model to execute an anomaly detection algorithm. Specifically, it compares current data with past data to detect abnormal patterns (such as a child approaching a door). Data processing includes time series analysis and clustering.

[1507] Input: Data packet sent to the server

[1508] Output: Detected abnormal patterns

[1509] Step 4:

[1510] If the server detects an abnormal pattern, it generates a warning signal, which includes details of the abnormal situation (e.g., a child trying to open a door), and generates an appropriate countermeasure by inputting a prompt sentence into the generative AI model.

[1511] Input: Detected abnormal pattern

[1512] Output: Warning signal, action to be taken based on the prompt

[1513] Step 5:

[1514] The server sends the generated warning signal and countermeasures to the parent device and the security center. The parent device displays a warning message and an alarm sound. At the same time, an alert is sent to the security center and displayed on the center's dashboard.

[1515] Input: Warning signals, countermeasures based on prompts

[1516] Output: Notifications on parent's device, Security Center alerts

[1517] Step 6:

[1518] When the parent device receives the warning message, the user can take action based on the message. At the same time, security center operators also check the dashboard and take action, such as dispatching security guards to the scene, if necessary.

[1519] Input: Parental device notifications, Security Center alerts

[1520] Output: User response, Security Center action

[1521] This process allows parents and security centers to respond quickly and effectively when a child faces a dangerous situation at home.

[1522] 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.

[1523] This invention provides a system for ensuring children's safety at home, and is composed of sensors, a server, a terminal, and an emotion engine. This system detects dangerous situations for children based on real-time data obtained from the sensors, generates an alarm, and notifies parents. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, the system has the function of adjusting the alarm sound and notification content according to the user's emotional state.

[1524] Sensor installation and operation

[1525] The device is equipped with a camera, motion sensors, and environmental sensors. The camera captures images of the child in real time, the motion sensors detect the child's proximity and movement, and the environmental sensors measure temperature and humidity. The data collected by these sensors is important information for keeping children safe.

[1526] Data collection and transmission

[1527] The device sends data collected in real time from the sensors to a server, including the child's location, movement, temperature, humidity, etc. The collected data is sent to the server at regular intervals for analysis.

[1528] Data analysis and risk detection

[1529] The server receives and analyzes the data sent from the device. This analysis includes evaluating the child's current location and movements and determining whether the situation is dangerous. If danger is detected, the server immediately sends a command to the device to sound an alarm.

[1530] Emotion Engine Operation

[1531] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine uses a camera and microphone to analyze emotions from the user's facial expressions and voice. For example, by reading a parent's facial expression with the camera and analyzing the tone of their voice with the microphone, it can determine whether the parent is feeling stressed or relieved.

[1532] Warning sound generation and adjustment

[1533] When the device receives a warning command from the server, it generates a warning sound. The content and volume of the warning sound are adjusted based on the user's emotional state analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume of the warning sound will be lowered and a more gentle voice message will be played.

[1534] Parental Notification

[1535] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email, allowing the parent to immediately understand their child's current situation and respond accordingly. In addition, the emotion engine adjusts the content and urgency of the notification according to the user's emotional state.

[1536] Specific examples

[1537] Example 1: When a child approaches an outlet

[1538] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[1539] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[1540] 3. The server recognizes the danger and sends a command to the terminal to sound an alarm.

[1541] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1542] 5. The device will emit a warning sound saying "Do not touch the power outlet."

[1543] 6. The server sends a notification to the parent's device saying "Your child is approaching an outlet," and the content of the notification is adjusted according to the parent's emotional state.

[1544] Example 2: A child is trying to open a window

[1545] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[1546] 2. The device sends the collected data to the server.

[1547] 3. The server analyzes the data and determines that the child is trying to open the window.

[1548] 4. The server sends a command to the device to sound an alarm.

[1549] 5. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1550] 6. The device will emit a warning sound saying "Do not open the window."

[1551] 7. The server sends a notification to the parent's device saying "Your child is trying to open the window," and the content of the notification is adjusted according to the parent's emotional state.

[1552] This system improves the safety of children at home and allows parents to live their daily lives with peace of mind. The introduction of an emotion engine allows the system to respond more flexibly to parents' needs and also contributes to reducing stress.

[1553] The processing flow will be explained below.

[1554] Step 1:

[1555] The device initializes the camera, motion sensors, and environmental sensors, ensuring that each sensor is ready to operate normally.

[1556] Step 2:

[1557] The device receives real-time data from initialized sensors: the camera detects the child's location, the motion sensor detects surrounding movement, and the environmental sensors measure temperature and humidity.

[1558] Step 3:

[1559] The device formats the acquired real-time data and sends it to the server, including the child's location, movement, temperature, and humidity.

[1560] Step 4:

[1561] The server receives the data transmitted from the device, including the child's location information, movement information, and environmental data.

[1562] Step 5:

[1563] The server analyzes the received data to determine if a dangerous situation is occurring, by evaluating the child's current location and movements, and immediately setting a danger flag if a danger is detected.

[1564] Step 6:

[1565] If a danger is detected, the server sends a command to the terminal to sound an alarm, including the type and content of the alarm sound.

[1566] Step 7:

[1567] The device receives warning commands from the server and uses its built-in emotion engine to assess the user's emotional state, analyzing facial expressions with a camera and tone of voice with a microphone.

[1568] Step 8:

[1569] The device adjusts the content and volume of the warning sound based on the user's emotional state obtained from the emotion engine. For example, if the user is feeling stressed, a calm voice message will be selected.

[1570] Step 9:

[1571] The device will emit a tailored warning sound, such as a voice message saying "Do not touch the outlet" or a beep.

[1572] Step 10:

[1573] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email.

[1574] Step 11:

[1575] The server adjusts the content and urgency of notifications based on the user's emotional state analyzed by the emotion engine. For example, if the user is relaxed, the notification will be more gentle.

[1576] Step 12:

[1577] The user (parent) receives the notification from the server and checks the child's current status. For example, the parent who received the notification may take action such as going to check on the child in person.

[1578] Example 2

[1579] 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."

[1580] In conventional systems for ensuring child safety at home, the warning sounds and notification content that are emitted when danger is detected are uniform and are not adjusted according to the emotional state of the parent, which can be stressful.In addition, there is room for improvement in the accuracy of danger detection and notification, and therefore, ensuring the safety of children at home is insufficient.

[1581] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1582] In this invention, the server includes means for collecting real-time data from the sensors, means for transmitting the collected data to the server, means for analyzing the received data on the server to detect dangerous situations, means for generating an alarm sound based on the detected dangerous situation, means for analyzing the emotional state of the user using emotion analysis means, means for adjusting the alarm sound and notification content according to the emotional state of the user, and means for notifying the parent's terminal of the detected dangerous situation. This enables the system for keeping children safe at home to respond flexibly to the emotional state of the parents and respond quickly while reducing stress.

[1583] A "sensor" is a device that detects physical or chemical changes in the environment and outputs the data.

[1584] "Real-time data" is data obtained from sensors or devices that is immediately available.

[1585] A "server" is a computing device that provides functions such as data management, analysis, and storage.

[1586] "Emotion analysis means" refers to technologies and algorithms that analyze a user's facial expressions, tone of voice, etc. to determine the user's emotional state.

[1587] A "warning sound" is an audio signal that is generated to alert the user when a danger is detected.

[1588] "Parent's device" refers to an electronic device such as a smartphone or tablet owned by the parent.

[1589] A "notification" is a message or alert sent to inform a user of specific information.

[1590] A "camera" is a device that uses an optical lens to capture video or images.

[1591] A "motion sensor" is a device for detecting the movement of an object.

[1592] An "environmental sensor" is a device that measures environmental conditions such as temperature, humidity, and air pressure.

[1593] The present invention relates to a system for ensuring children's safety at home. This system includes sensors, a server, a terminal, and an emotion engine. This system monitors the child's situation in real time and generates an alarm if a dangerous situation is detected. The system also has a function for sending notifications to parents, and by using the emotion engine, the content of the notifications and alarms can be adjusted according to the parent's emotional state.

[1594] Hardware Configuration

[1595] The device is equipped with the following sensors:

[1596] Camera: Captures real-time footage of your child.

[1597] Motion sensor: Detects the proximity and movement of children.

[1598] Environmental sensors: measure temperature and humidity.

[1599] These sensors provide important information to keep children safe.

[1600] Data collection and transmission

[1601] The device collects real-time data from the sensors and transmits it to a server at regular intervals, including the child's location, movement, temperature, humidity, and other information.

[1602] Data analysis and risk detection

[1603] The server receives and analyzes the data sent from the device. This analysis includes evaluating the child's current location and movements and determining whether the situation is dangerous. If danger is detected, the server immediately sends a command to the device to generate an alarm.

[1604] Emotion Engine Operation

[1605] The device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine uses a camera and microphone to analyze emotions from the user's facial expressions and voice. For example, by reading a parent's facial expression with the camera and analyzing the tone of their voice with the microphone, it can determine whether the parent is feeling stressed or relieved.

[1606] Warning sound generation and adjustment

[1607] The device generates a warning sound based on a warning command from the server. The content and volume of the warning sound are adjusted based on the user's emotional state analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume of the warning sound will be lowered and a more gentle voice message will be played.

[1608] Parental Notification

[1609] The server notifies the parent's device that a danger has been detected. The notification is sent via app notification or email, allowing the parent to immediately understand their child's current situation and respond accordingly. In addition, the emotion engine adjusts the content and urgency of the notification according to the user's emotional state.

[1610] Specific examples

[1611] Example 1: When a child approaches an outlet

[1612] 1. The device's motion sensor detects the child's proximity and sends the data to the server.

[1613] 2. The server analyzes the data and determines whether the child is near an electrical outlet.

[1614] 3. The server recognizes the danger and sends a command to the terminal to sound an alarm.

[1615] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1616] 5. The device will emit a warning sound saying "Do not touch the power outlet."

[1617] 6. The server sends a notification to the parent's device saying "Your child is approaching an outlet," and the content of the notification is adjusted according to the parent's emotional state.

[1618] Example 2: A child is trying to open a window

[1619] 1. The device's camera detects the child's movements and collects data on their approach to the window.

[1620] 2. The device sends the collected data to the server.

[1621] 3. The server analyzes the data and determines that the child is trying to open the window.

[1622] 4. The server sends a command to the device to sound an alarm.

[1623] 5. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1624] 6. The device will emit a warning sound saying "Do not open the window."

[1625] 7. The server sends a notification to the parent's device saying "Your child is trying to open the window," and the content of the notification is adjusted according to the parent's emotional state.

[1626] Prompt Sentence Examples

[1627] Prompt example 1

[1628] "Please explain in detail how this system works when a child approaches an electrical outlet. Please be specific about each step: sensor, server, device, and emotion engine."

[1629] Prompt example 2

[1630] "Please explain specifically how the system will sound an alarm and notify parents if a child tries to open a window."

[1631] As a result, the system of the present invention increases the safety of children and reduces stress for parents, allowing them to live their daily lives with peace of mind.In this way, by incorporating emotion analysis, we can improve the shortcomings of conventional systems and provide a more flexible and adaptable system.

[1632] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1633] Step 1:

[1634] Sensor data acquisition

[1635] Input: Physical changes from the surrounding environment (child's movement, temperature, humidity, etc.)

[1636] Processing: Cameras capture footage, motion sensors detect the child's movements, and environmental sensors measure temperature and humidity.

[1637] Output: Child's video data, movement data, environmental data

[1638] How it works: The device's built-in camera captures real-time footage of the child, the motion sensor captures the child's movements and proximity, and the environmental sensor measures the indoor temperature and humidity, temporarily storing this data internally.

[1639] Step 2:

[1640] Sending data

[1641] Input: Child's video data, movement data, environmental data

[1642] Processing: The device sends the collected data to the server at a specified interval (e.g., every 5 seconds).

[1643] Output: Data collected from the sensor is sent to the server

[1644] Specific operation: A program on the terminal stores the collected data in temporary memory and sends it to the server via the network as data packets at regular intervals.

[1645] Step 3:

[1646] Data reception and analysis

[1647] Input: Data packets sent from the sensor

[1648] Processing: The server receives the data, checks its integrity, stores it in a database in the correct format, and uses analysis algorithms to determine whether it poses a risk.

[1649] Output: Analysis results, whether there is a risk

[1650] Specific operation: The server receives the data packet, verifies the data integrity, and stores it in the database. It then uses an analysis algorithm to analyze the child's location and movements to assess whether there is any danger.

[1651] Step 4:

[1652] Hazard detection

[1653] Input: Server analysis results

[1654] Processing: The server evaluates the analysis results and flags any detected dangers, as well as identifying the type and location of the danger.

[1655] Output: Danger detection flag, type of danger and location information

[1656] Specific operation: The server searches for specific patterns (e.g., near an outlet or near a window) based on the results of the analysis algorithm, and if a danger is identified, it sets a danger flag and prepares information to proceed to the next step.

[1657] Step 5:

[1658] Sending a warning order

[1659] Input: Danger detection flag, type of danger and location information

[1660] Processing: If a danger is detected, the server sends a warning command to the device, including the type of danger and its location.

[1661] Output: Warning command for terminal

[1662] Specific operation: The server generates an appropriate warning signal and sends it to the device via the network. The warning signal contains the type of danger recognized and its location.

[1663] Step 6:

[1664] Emotion analysis using an emotion engine

[1665] Input: Parent's facial expression data, voice data

[1666] Processing: The emotion engine installed on the device analyzes the parent's emotional state using the camera and microphone.

[1667] Output: Parent's emotional state information

[1668] Specific operation: The device's camera captures the parent's facial expressions and the microphone records the tone of their voice. The emotion engine analyzes this data to determine the parent's emotional state.

[1669] Step 7:

[1670] Warning sound generation and adjustment

[1671] Input: Warning command, parent's emotional state information

[1672] Processing: The device generates a warning sound based on the warning command, and adjusts the content and volume of the warning sound based on the parent's emotional state.

[1673] Output: Audible warning sound

[1674] What it does: Plays an appropriate warning sound through the device speaker. Based on the results of the emotion engine, for example, if the parent is stressed, it lowers the volume and plays a softer message.

[1675] Step 8:

[1676] Parental Notification

[1677] Input: Danger detection flag, parent's emotional state information

[1678] Processing: The server notifies the parent's device that a danger has been detected. The content and urgency of the notification are adjusted according to the parent's emotional state.

[1679] Output: Notification message to parent device

[1680] Specific operation: The server sends warning information to the parent's device in the form of an app notification or email. Based on the results of the emotion engine, for example, if the parent is feeling stressed, the server will send a soft-spoken notification.

[1681] (Application example 2)

[1682] 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."

[1683] Conventional home monitoring systems have a means of detecting danger to ensure child safety, but they uniformly issue warning sounds without considering the parent's emotional state, which can increase parental stress. Furthermore, even if a parent is busy and unable to respond immediately, important notifications may not be properly delivered. The present invention aims to solve these problems and provide a more flexible and effective child monitoring system.

[1684] 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.

[1685] In this invention, the server includes a means for collecting real-time data, a means for transmitting the collected data, and a means for analyzing the received data and detecting a dangerous situation, which makes it possible to combine an emotion recognition means for analyzing the user's emotion with a means for adjusting the content and volume of the warning sound based on the emotion recognition result.

[1686] "Sensors" are devices such as cameras, motion sensors, and environmental sensors that collect data in real time.

[1687] "Real-time data" refers to data obtained from sensors and information that is sent to a server immediately without any time delay.

[1688] A "server" is a computer system that receives and analyzes the collected data.

[1689] A "danger situation" is a condition that indicates a child is in a dangerous place or situation.

[1690] A "warning sound" is a notification sound such as a voice message or a beep that is generated based on a detected dangerous situation.

[1691] A "parent's device" is an electronic device such as a smartphone or tablet that is owned by the parent.

[1692] "Emotion recognition means" is a technology that analyzes a user's facial expressions and voice to determine their emotional state.

[1693] The "adjustment means" is a mechanism for changing the content and volume of the warning sound based on the emotion recognition result.

[1694] System Overview

[1695] This invention is a monitoring system designed to keep children safe at home. The system is composed of multiple elements, including sensors, a server, a terminal, and an emotion engine that recognizes the user's emotions. The sensors include cameras, motion sensors, and environmental sensors, and real-time data acquired from these sensors is sent to the server. The server analyzes the data, detects dangerous situations, and sends a command to the terminal to issue an alert. The system also has the function of analyzing the user's emotional state to adjust the content and volume of the alert sound.

[1696] Hardware and software used

[1697] Sensors: Camera, motion sensors, environmental sensors

[1698] Server: A computer system that collects and analyzes data.

[1699] Device: Electronic devices such as smartphones and tablets owned by parents

[1700] Emotion engine: Software for recognizing user emotions (e.g., EmotionRecognizer)

[1701] Communications: Internet connection for data transmission and notifications

[1702] System operation explanation

[1703] Data collection

[1704] Sensors are installed in each room of the home to monitor the child's location and movements. Cameras capture images in real time, motion sensors detect the child's proximity and movement, and environmental sensors measure temperature and humidity. Data collected from these sensors is immediately sent to a server.

[1705] Data analysis

[1706] The server analyzes the received data and evaluates the child's current location and movements. For example, if a child approaches an electrical outlet, it combines data from the motion sensor with camera footage to detect a dangerous situation. Based on the analysis results, it immediately sends a command to the device to sound an alarm.

[1707] emotion recognition

[1708] The device is equipped with an emotion engine that recognizes the user's emotions and uses a camera and microphone to analyze the user's facial expressions and voice to determine their emotions. For example, by reading a parent's facial expression and analyzing their tone of voice, the device can determine whether they are feeling stressed or relieved.

[1709] Adjust alert sounds and notifications

[1710] Upon receiving a command from the server, the device will emit an alert sound. The content and volume of the alert sound will be adjusted based on the user's emotional state as analyzed by the emotion engine. For example, if a parent is feeling stressed, the volume will be lowered and a calming voice message will be played. In addition, a notification will be sent to the parent's device to provide information to help them understand their child's current situation.

[1711] Specific examples

[1712] Proximity to electrical outlets

[1713] 1. The sensor detects when a child approaches an outlet and sends the data to the server.

[1714] 2. The server analyzes the data and recognizes the danger.

[1715] 3. The server sends a command to the device to generate an alarm sound.

[1716] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1717] 5. A warning sound will be emitted saying "Do not touch the outlet."

[1718] 6. A notification will be sent to the parent's device saying "Your child is approaching an outlet."

[1719] Approaching the window

[1720] 1. The sensor detects the child's approach to the window and sends the data to the server.

[1721] 2. The server analyzes the data and recognizes the danger.

[1722] 3. The server sends a command to the device to generate an alarm sound.

[1723] 4. The device's emotion engine analyzes the parent's emotional state and adjusts the content and volume of the warning sound.

[1724] 5. A warning sound will be emitted, such as "Do not open the window."

[1725] 6. A notification will be sent to the parent's device saying "Your child is trying to open a window."

[1726] Example prompts for generative AI models

[1727] Image-based hazard detection:

[1728] Use image analysis to detect danger when a child approaches an electrical outlet.

[1729] Emotion recognition:

[1730] Please judge the parent's emotional state as indicated by this image and adjust the notification content and volume accordingly.

[1731] As described above, the present invention makes it possible to flexibly adjust the warning sound in accordance with the emotional state of the parent, thereby ensuring the safety of the child.

[1732] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1733] Step 1:

[1734] Sensors detect the child's location and movements in real time.

[1735] Input: Camera footage, motion sensor data, environmental sensor data

[1736] Data processing: Extract the child's location from the camera footage, analyze the child's movements from the motion sensor data, and obtain temperature and humidity from the environmental sensor data.

[1737] Output: Parsed child's position, movement, and environment information

[1738] Step 2:

[1739] The terminal transmits the collected data to the server.

[1740] Input: Parsed child location, movement, and environment information

[1741] Data processing: Convert the data into JSON format and send it to the server.

[1742] Output: Data sent to the server

[1743] Step 3:

[1744] The server analyzes the received data and detects dangerous situations.

[1745] Input: Data sent to the server (child's location, movements, and environmental information)

[1746] Data Calculation: Analyzes the data and performs rule-based analysis to determine whether a child is in a dangerous location. For example, if a child approaches an electrical outlet, it is considered a dangerous situation.

[1747] Output: Judgment result (presence or absence of dangerous situation)

[1748] Step 4:

[1749] If the server detects danger, it sends a command to the terminal to sound an alarm.

[1750] Input: Judgment result (danger situation)

[1751] Data processing: Based on the judgment result, a message is generated to send to the terminal an instruction to issue an alarm.

[1752] Output: Warning sound generation command

[1753] Step 5:

[1754] The terminal receives the instruction to generate an alert sound and analyzes the user's emotional state.

[1755] Input: Sound alarm command

[1756] Data calculation: Using the device's camera and microphone, the user's facial expressions and voice are captured and their emotions are analyzed using an emotion recognition model (e.g., EmotionRecognizer).

[1757] Output: User's emotional state

[1758] Step 6:

[1759] The device adjusts the content and volume of the warning sound based on the emotion recognition results.

[1760] Input: User's emotional state, command to sound an alert

[1761] Data calculation: Analyzes the user's emotional state and determines the appropriate alert content and volume settings. For example, if the user is stressed, lower the volume and select a calm voice message.

[1762] Output: Adjusted warning sound settings

[1763] Step 7:

[1764] The device will emit an alert and send a notification to the parent device.

[1765] Input: Adjusted warning sound settings, judgment result

[1766] Data processing: Generates an alarm sound and plays it through the speaker. Also generates and sends a notification message to the parent's device to inform them of the current situation.

[1767] Output: generated alerts, sent notification messages

[1768] 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.

[1769] 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.

[1770] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1771] 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.

[1772] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1773] 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.

[1774] 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).

[1775] 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.

[1776] 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."

[1777] 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.

[1778] 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).

[1779] 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.

[1780] 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.

[1781] 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.

[1782] 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.

[1783] 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.

[1784] 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.

[1785] 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.

[1786] 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.

[1787] 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.

[1788] 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.

[1789] The following is further disclosed regarding the above embodiment.

[1790] (Claim 1)

[1791] a means for collecting real-time data from the sensors;

[1792] means for transmitting the collected data to a server;

[1793] A means for analyzing the received data on the server and detecting a dangerous situation;

[1794] means for generating an audible warning based on the detected hazardous condition;

[1795] a means for notifying a parent's device of the detected dangerous situation;

[1796] A system including:

[1797] (Claim 2)

[1798] 10. The system of claim 1, further comprising means for using a camera, a motion sensor, and an environmental sensor as sensors.

[1799] (Claim 3)

[1800] 10. The system of claim 1, including means for using voice messages and beeps as audible warnings.

[1801] "Example 1"

[1802] (Claim 1)

[1803] a means for collecting real-time data from the sensors;

[1804] means for transmitting the collected data to a server;

[1805] A means for analyzing the received data on the server and detecting a dangerous situation;

[1806] means for generating an audible warning based on the detected hazardous condition;

[1807] a means for notifying a parent's device of the detected dangerous situation;

[1808] means for transmitting data collected by the terminal to a server at regular intervals;

[1809] means for formatting the data into an understandable format after receiving it at the server;

[1810] In data analysis, a means of comparing past behavioral patterns with real-time location information,

[1811] means for generating a warning signal by referring to a specific movement pattern based on the data analysis result by the server;

[1812] A system including:

[1813] (Claim 2)

[1814] 10. The system of claim 1, further comprising means for using a camera, a motion sensor, and an environmental sensor as sensors.

[1815] (Claim 3)

[1816] 10. The system of claim 1, including means for using voice messages and beeps as audible warnings.

[1817] "Application Example 1"

[1818] (Claim 1)

[1819] a means for collecting real-time data from the sensors;

[1820] means for transmitting the collected data to a server;

[1821] A means for analyzing the received data on the server and detecting a dangerous situation;

[1822] means for generating an audible warning based on the detected hazardous condition;

[1823] a means for notifying the parent's terminal and the security center of the detected dangerous situation;

[1824] A system including:

[1825] (Claim 2)

[1826] 10. The system of claim 1, further comprising means for using a camera, a motion sensor, and an environmental sensor as sensors.

[1827] (Claim 3)

[1828] 10. The system of claim 1, including means for using voice messages and beeps as audible warnings.

[1829] "Example 2: Combining Emotion Engines"

[1830] (Claim 1)

[1831] a means for collecting real-time data from the sensors;

[1832] means for transmitting the collected data to a server;

[1833] A means for analyzing received data on a server and detecting a dangerous situation;

[1834] means for generating an audible warning based on the detected hazardous condition;

[1835] means for analyzing the emotional state of a user using an emotion analysis means;

[1836] A means for adjusting the alert sound and notification content according to the user's emotional state;

[1837] a means for notifying a parent's device of the detected dangerous situation;

[1838] A system including:

[1839] (Claim 2)

[1840] 10. The system of claim 1, further comprising means for using a camera, a motion sensor, and an environmental sensor as sensors.

[1841] (Claim 3)

[1842] 10. The system of claim 1, including means for using voice messages and beeps as audible warnings.

[1843] "Application example 2 when combining emotion engines"

[1844] (Claim 1)

[1845] a means for collecting real-time data from the sensors;

[1846] means for transmitting the collected data to a server;

[1847] A means for analyzing the received data on the server and detecting a dangerous situation;

[1848] means for generating an audible warning based on the detected hazardous condition;

[1849] a means for notifying a parent's device of the detected dangerous situation;

[1850] emotion recognition means for analyzing the emotion of a user;

[1851] a means for adjusting the content and volume of the warning sound based on the emotion recognition result;

[1852] A system including:

[1853] (Claim 2)

[1854] 10. The system of claim 1, further comprising means for using a camera, a motion sensor, and an environmental sensor as sensors.

[1855] (Claim 3)

[1856] 10. The system of claim 1, including means for using voice messages and beeps as audible warnings. [Explanation of symbols]

[1857] 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 collecting real-time data from the sensors; means for transmitting the collected data to a server; A means for analyzing the received data on the server and detecting a dangerous situation; means for generating an audible warning based on the detected hazardous condition; a means for notifying a parent's device of the detected dangerous situation; A system including:

2. 10. The system of claim 1, further comprising means for using a camera, a motion sensor, and an environmental sensor as sensors.

3. 2. The system of claim 1, further comprising means for using voice messages and beeps as the audible warnings.

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