System

Abstract

A system is provided.SOLUTION: An apparatus for monitoring behavior of a pet, comprising: means for capturing motion of the pet in real time using a camera and a motion sensor; means for compressing and converting the captured data into a communicable format; means for transmitting the converted data to a server via a communication line; means for analyzing the data received by the server and estimating a behavior pattern of the pet; and means for transmitting a notification to a user's terminal based on the estimated behavior pattern.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] When keeping pets at home, there is a demand for efficient monitoring of the pet's behavior and health condition. Conventional methods have made it difficult to constantly check the pet's behavior and health condition, making it difficult to quickly respond to abnormalities or concerns about the pet's safety. Furthermore, tracking the pet's location information requires the preparation of multiple dedicated devices, which creates issues with cost and complicated operation. The present invention aims to solve these issues and provide a system for centrally managing pet behavior, health condition, and location information. [Means for solving the problem]

[0005] The present invention provides a device equipped with a camera and motion sensor for monitoring pet behavior, using these to capture pet movements in real time. The device also includes means for compressing the captured data, converting it into a communicable format, and transmitting it to a server. The server analyzes the received data, estimates the pet's behavioral patterns, and notifies the user's device. The device also includes sensors for measuring body temperature and heart rate to monitor the pet's health, and means for periodically storing this data in local memory and transmitting it to the server. Furthermore, the device also provides means for tracking the pet's location by using a GPS module to acquire location information, transmitting it to a server, and displaying the analyzed location information on the user's device. This allows users to centrally manage their pet's behavior, health, and location information, enabling quick and effective response.

[0006] A "behavior monitoring device" is a device that has the function of capturing a pet's behavior in real time and transmitting that information to another device.

[0007] A "camera" is a device for capturing images of pets and storing or transmitting them as digital data.

[0008] A "motion sensor" is a sensor that detects the movement of a pet and collects data related to the movement.

[0009] The "means for compressing data and converting it into a format that can be transmitted" refers to a means that has the function of converting the captured data into a format that can be transmitted to other devices or servers while reducing the volume of the data.

[0010] The "means for transmitting the converted data" is a means having a function for transmitting the processed data to a server via a communication line.

[0011] A "server" is an information processing device that analyzes received data and sends notifications to other devices as necessary.

[0012] The "means for estimating behavioral patterns" is a means that has the function of analyzing and recognizing the behavior of a pet based on the received data and identifying the specific behavior.

[0013] The "means for sending a notification to a user's terminal" refers to a means having a function for notifying information such as analysis results to a device used by a user.

[0014] A "health monitoring device" is a device that has the function of measuring data that indicates a pet's health (such as body temperature and heart rate) and transmitting that information to other devices.

[0015] The "sensor for measuring body temperature and heart rate" is a sensor for detecting a pet's body temperature and heart rate and collecting that data.

[0016] The "means for saving in local memory" is a storage means for temporarily saving measurement data.

[0017] The "means for detecting abnormalities" refers to means that has the function of analyzing measurement data and detecting abnormal values.

[0018] A "GPS module" is a location information acquisition device that identifies the current location of a pet.

[0019] The "means for acquiring location information" is a means that has the function of acquiring pet location data using a GPS module.

[0020] The "means for analyzing location information" refers to a means having the function of processing the acquired location data and identifying the specific current location.

[0021] The "means for displaying location information" is a means having a function for displaying analyzed location data so that the user can visually confirm it. [Brief explanation of the drawings]

[0022] [Figure 1]1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0023] 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.

[0024] First, the terms used in the following description will be explained.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 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.

[0033] 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).

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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."

[0043] The present invention provides a system for comprehensively monitoring pet behavior, health status, and location information. Specific embodiments of the present invention will be described below.

[0044] System Configuration

[0045] The system consists of the following main components:

[0046] 1. Device (terminal) for monitoring pet behavior

[0047] 2. Server that analyzes and manages data

[0048] 3. User's information device (smartphone or tablet)

[0049] Terminal (device for monitoring pet behavior)

[0050] Camera: A device for capturing video of your pet.

[0051] Motion sensor: A sensor for detecting pet movement.

[0052] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate).

[0053] GPS module: A module for determining the current location of your pet.

[0054] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth.

[0055] Local memory: A storage device for temporarily storing data.

[0056] server

[0057] Data analysis function: Has the ability to analyze received data and estimate your pet's behavioral patterns and health condition.

[0058] Notification function: Has the ability to send information and alerts to user devices based on analysis results.

[0059] Database: Includes a database for recording and managing pet behavior history and health status.

[0060] User terminal

[0061] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[0062] Program processing

[0063] The program processing performed by each device in the system will be explained below in natural language.

[0064] Pet behavior monitoring

[0065] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[0066] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it can identify behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via push notifications to the user's smartphone app.

[0067] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[0068] Health monitoring

[0069] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[0070] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[0071] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[0072] Location tracking

[0073] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[0074] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[0075] Users can check their pet's current location and past routes using a smartphone app.

[0076] Specific examples

[0077] Examples of behavioral monitoring

[0078] 1. The device uses its camera to capture video of a dog playing in the yard.

[0079] 2. The terminal compresses the video data and sends it to the server via the communication module.

[0080] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[0081] 4. The server notifies the user of the results via their smartphone app.

[0082] 5. The user uses the app to confirm that the dog is playing happily.

[0083] Health monitoring examples

[0084] 1. The device measures the dog's temperature as 36.8 degrees.

[0085] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[0086] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[0087] 4. The server notifies the user of the results via their smartphone app.

[0088] 5. The user uses the app to ensure their pet is in good health.

[0089] Examples of location tracking

[0090] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[0091] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[0092] 3. The server compares the received location information with map information to determine the dog's current location.

[0093] 4. The server displays the results on the user's smartphone app.

[0094] 5. The user uses the app to confirm that the dog is currently at the park.

[0095] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and provides users with the information they need.

[0096] The processing flow will be explained below.

[0097] Pet behavior monitoring

[0098] Step 1: Data Capture

[0099] The device uses a camera and motion sensors to capture footage and movements of your pet in real time.

[0100] The device stores the captured video data and motion data in temporary memory.

[0101] Step 2: Data processing

[0102] The terminal compresses the captured data and converts it into a suitable format to save communication bandwidth.

[0103] The terminal organizes the processed data as batch data.

[0104] Step 3: Sending data

[0105] The device sends the processed data to the server via Wi-Fi or Bluetooth.

[0106] The terminal confirms the success of the transmission and receives an acknowledgement.

[0107] Step 4: Analyze the data

[0108] The server analyzes the received data and applies behavior recognition algorithms to detect the pet's behavior patterns.

[0109] The server records information such as "pet is running" or "pet is sleeping" in the behavior log.

[0110] Step 5: Sending notifications

[0111] The server sends analysis results such as "your pet is running" or "your pet is sleeping" to the user's smartphone app as a push notification.

[0112] Users can check their pet's current behavior using a smartphone app.

[0113] Health monitoring

[0114] Step 1: Data collection

[0115] The device uses sensors to measure your pet's body temperature and heart rate every 10 minutes.

[0116] The terminal temporarily stores the measurement data in a local memory.

[0117] Step 2: Send data

[0118] The terminal transmits the measurement data to the server.

[0119] The terminal adjusts its periodic data transmission schedule to optimize power consumption.

[0120] Step 3: Data analysis

[0121] The server analyzes the received data in real time and evaluates whether it is within the normal range.

[0122] If the server detects an anomaly, it generates an alert to the user.

[0123] Step 4: Sending notifications

[0124] The server sends the results of abnormality detection and regular health status reports to the user's smartphone via push notifications.

[0125] Users can check notifications about their pet's health status on their smartphone and take necessary measures.

[0126] Location tracking

[0127] Step 1: Obtaining location information

[0128] The device periodically obtains the pet's location information using the built-in GPS module.

[0129] The terminal stores the acquired location information in a local memory.

[0130] Step 2: Send data

[0131] The terminal transmits the location information data to the server.

[0132] The terminal confirms the success of the transmission and receives an acknowledgement.

[0133] Step 3: Data analysis

[0134] The server compares the location data with map information to determine the pet's current location.

[0135] The server records the location information as the pet's movement history.

[0136] Step 4: View location information

[0137] The server sends map data to the user's smartphone app to display the pet's current location.

[0138] Users can check their pet's current location and past routes using a smartphone app.

[0139] Example 1

[0140] 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."

[0141] There is a demand for a system that can comprehensively monitor pet behavior, health status, and location information, and allow users to obtain the information they need in real time. Conventional systems often collect and manage this information separately, making it difficult for users to use and providing information in a centralized manner.

[0142] 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.

[0143] In this invention, the server includes means for capturing the movements of the pet in real time using a camera and a motion sensor, means for compressing the captured data and converting it into a communicable format, means for transmitting the converted data to the server via a communication line, means for analyzing the data received by the server using a generative model and estimating the behavioral patterns of the pet, and means for transmitting notifications to the user's terminal based on the estimated behavioral patterns. This allows the user to centrally manage the behavior, health condition, and location information of the pet and obtain this information in real time.

[0144] A "camera" is a device for capturing images of pets.

[0145] A "motion sensor" is a sensor that detects the movement of a pet.

[0146] "Compression" is a process for reducing the size of captured data.

[0147] "Communicable format" refers to the process of converting data into a format that can be sent and received.

[0148] A "communication line" is a network for transmitting data.

[0149] A "server" is a central computer that analyzes and manages data.

[0150] A "generative model" is an algorithm for analyzing data and recognizing specific patterns.

[0151] A "behavioral pattern" is a series of movements that characterize a pet's behavior.

[0152] "Notification" is a message to inform the user of the analysis results.

[0153] A "terminal" is a device through which a user receives information.

[0154] "Health indicators" are data on body temperature and heart rate that indicate the pet's health condition.

[0155] "Local memory" is a storage device that temporarily stores data within a device.

[0156] An "abnormal alert" is a warning message that occurs when data outside the normal range is detected.

[0157] A "GPS module" is a device used to determine a pet's current location.

[0158] "Location information" is data that indicates the current location of the pet.

[0159] "Map information" is information for visually displaying location data.

[0160] "Tracking" is the act of continuously monitoring a pet's location.

[0161] The present invention is a system for comprehensively monitoring the behavior, health status, and location information of pets. Specific embodiments for carrying out the present invention will be described below.

[0162] System Configuration

[0163] The system consists of the following main components:

[0164] 1. A device that monitors your pet's behavior

[0165] 2. Server that analyzes and manages data

[0166] 3. User's information device (smartphone or tablet)

[0167] Terminal (device for monitoring pet behavior)

[0168] Camera: A device for recording video of your pet. The camera captures video in high resolution at 30 frames per second.

[0169] Motion Sensor: This is a sensor that detects pet movements. The sensor captures movements in real time.

[0170] Body Temperature and Heart Rate Sensor: A sensor that measures your pet's body temperature and heart rate. The measurement results are stored in local memory.

[0171] GPS module: This module identifies the current location of your pet. Location information is acquired periodically.

[0172] Communication module: A module that transmits data to a server using Wi-Fi or Bluetooth. The communication module supports IEEE 802.11ac and Bluetooth Low Energy (BLE).

[0173] Local memory: A storage device that temporarily stores data.

[0174] server

[0175] Data analysis function: The system analyzes the received data and estimates the pet's behavioral patterns and health condition. TensorFlow models and generative models are used for the analysis.

[0176] Notification function: Has the ability to send information and alerts to user devices based on analysis results. Uses Firebase Cloud Messaging (FCM).

[0177] Database: Includes a database for recording and managing pet behavior history and health status.

[0178] User terminal

[0179] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[0180] Program processing

[0181] The program processing performed by each device in the system will be explained below in natural language.

[0182] Pet behavior monitoring

[0183] The device uses a camera and motion sensors to capture video and movement data in real time, then compresses it using the H.264 codec and converts it into a format suitable for communication, before transmitting it to a server via Wi-Fi.

[0184] The server analyzes the received data using a TensorFlow model to estimate the pet's behavioral patterns. For example, it identifies behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are then pushed to the user's device in real time.

[0185] Users can check their pet's current activities through a smartphone app, and the app's dashboard displays messages such as "Your pet is playing happily."

[0186] Health monitoring

[0187] The device periodically measures your pet's health using built-in temperature and heart rate sensors, and the measurement data is stored in local memory and transmitted to a server at regular intervals using Bluetooth Low Energy (BLE).

[0188] The server analyzes the received health data in real time and detects abnormalities. For example, if the body temperature exceeds the normal range, it generates a "high body temperature alert." The generated alert is sent to the user's device.

[0189] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures, such as displaying messages like "Temperature is within normal range."

[0190] Location tracking

[0191] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in local memory and sent to the server via Wi-Fi.

[0192] The server compares the received location information with map data to determine the pet's current location, and uses the Geocoding API to convert the location coordinates into a specific address or place name.

[0193] Users can check their pet's current location and past routes on a smartphone app, which displays their pet's location in real time as it moves around the park.

[0194] Specific examples

[0195] Examples of behavioral monitoring

[0196] 1. The device uses its camera to capture video of a pet playing in the yard.

[0197] 2. The device compresses the video data using H.264 and sends it to the server via Wi-Fi.

[0198] 3. The server analyzes the received data using a TensorFlow model and determines that a pet is running in the yard.

[0199] 4. The server notifies the user's smartphone app of the results using Firebase Cloud Messaging.

[0200] 5. The user uses the app to confirm that their pet is playing happily.

[0201] Health monitoring examples

[0202] 1. The device measures the pet's temperature as 36.8 degrees.

[0203] 2. The device stores the measurement data in its local memory and periodically transmits it to the server using Bluetooth Low Energy.

[0204] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[0205] 4. The server notifies the user of the analysis results via their smartphone app.

[0206] 5. The user uses the app to ensure their pet is in good health.

[0207] Examples of location tracking

[0208] 1. The device uses the GPS module to obtain the location information of pets in the park.

[0209] 2. The device stores the location data in its local memory and transmits it to the server via Wi-Fi.

[0210] 3. The server analyzes the received location information using the Geocoding API to determine the pet's current location.

[0211] 4. The server displays the analysis results on the user's smartphone app.

[0212] 5. The user uses the app to confirm that their pet is currently at the park.

[0213] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and provides users with the information they need in real time.

[0214] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0215] Pet behavior monitoring process flow

[0216] Step 1: Capture behavioral data

[0217] The device uses a built-in camera and motion sensors to capture footage and movements of your pet.

[0218] Input: Real-time video and motion data.

[0219] Processing: The camera captures video at 30 frames per second, and the motion sensor detects movement.

[0220] Output: High resolution video and motion data.

[0221] Step 2: Compress and format the data

[0222] The device compresses the captured video data using the H.264 codec and converts the motion data into CSV format.

[0223] Input: High-resolution video and motion data.

[0224] Processing: Video data is compressed using H.264 and motion data is converted to CSV format.

[0225] Output: Compressed video data and motion data in CSV format.

[0226] Step 3: Sending data

[0227] The device transmits compressed video and motion data to a server via Wi-Fi.

[0228] Input: Compressed video and motion data.

[0229] Processing: Transmit data using IEEE 802.11ac.

[0230] Output: The data sent to the server.

[0231] Step 4: Analyze behavioral patterns

[0232] The server analyzes the received data using a TensorFlow model.

[0233] Input: Received video and motion data.

[0234] Processing: Activity recognition algorithms analyze the video frames and identify activities (e.g., "running" or "sleeping").

[0235] Output: Analyzed behavioral patterns.

[0236] Step 5: Generate and send notifications

[0237] The server sends a notification to the user's smartphone app based on the analysis results.

[0238] Input: Analyzed behavioral patterns.

[0239] Processing: Generate and send notifications using Firebase Cloud Messaging (FCM).

[0240] Output: A push notification is sent to the user's smartphone app.

[0241] Step 6: Confirm your actions

[0242] Users can check their pet's current behavior using a smartphone app.

[0243] Input: The notification sent by the server.

[0244] Action: Display behavioral information on the app dashboard.

[0245] Output: The user confirms the pet's behavior.

[0246] Pet health monitoring process flow

[0247] Step 1: Measuring health data

[0248] The device regularly measures your pet's health indicators using temperature and heart rate sensors.

[0249] Inputs: Real-time body temperature and heart rate.

[0250] Processing: The sensor measures the information and stores it temporarily in local memory.

[0251] Output: Measured body temperature and heart rate data.

[0252] Step 2: Storing and sending data

[0253] The terminal stores the measurement data in its local memory and transmits it to the server at regular intervals.

[0254] Input: Measured body temperature and heart rate data.

[0255] Processing: Transmit data using Bluetooth Low Energy (BLE).

[0256] Output: Measurement data sent to the server.

[0257] Step 3: Anomaly detection and alerting

[0258] The server analyzes the received health data and detects any abnormalities.

[0259] Input: Received temperature and heart rate data.

[0260] Action: Generate an abnormality alert if the normal range is exceeded (e.g., if the body temperature is above 39 degrees).

[0261] Output: The anomaly alert generated.

[0262] Step 4: Health Alert Notifications

[0263] The server sends the generated alert to the user's smartphone app.

[0264] Input: The generated anomaly alert.

[0265] Processing: Send notifications using Firebase Cloud Messaging (FCM).

[0266] Output: An alert is sent to the user's smartphone app.

[0267] Step 5: Health Check

[0268] Users can check their pet's health status via a smartphone app.

[0269] Input: The alert notification sent from the server.

[0270] Processing: Display health information and action suggestions within the app.

[0271] Output: The user checks his health status and takes necessary measures.

[0272] Pet location tracking process flow

[0273] Step 1: Capturing location data

[0274] The device periodically obtains your pet's location information using the built-in GPS module.

[0275] Input: Real-time location information.

[0276] Processing: The GPS module captures location information and stores it in local memory.

[0277] Output: The captured location data.

[0278] Step 2: Storing and sending data

[0279] The device stores the location data in its local memory and transmits it to a server via Wi-Fi.

[0280] Input: The captured location data.

[0281] Processing: Send data using Wi-Fi.

[0282] Output: The location data sent to the server.

[0283] Step 3: Analyze and match location information

[0284] The server compares the received location information with map data to determine the pet's current location.

[0285] Input: Received location data.

[0286] Processing: Use the Geocoding API to convert location coordinates into specific addresses or place names.

[0287] Output: The determined location.

[0288] Step 4: Notification of location data

[0289] The server sends the analysis results to the user's smartphone app.

[0290] Input: Parsed location information.

[0291] Processing: Send location information using Firebase Cloud Messaging (FCM).

[0292] Output: Location information is sent to the user's smartphone app.

[0293] Step 5: Locate and track

[0294] Users can check their pet's current location and past routes using a smartphone app.

[0295] Input: Location information sent from the server.

[0296] Processing: Display location on a map within the app and visualize past travel routes.

[0297] Output: The user sees the pet's current location and its route.

[0298] (Application example 1)

[0299] 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."

[0300] Real-time monitoring of pet safety and health in autonomous vehicles is an important issue for many pet owners. Normally, when pets are left in a car, it is difficult to properly monitor their behavior and health, which can lead to stress and health problems. There is also a risk that pets may become anxious or excited, causing problems inside the vehicle. Therefore, a reliable system is needed to ensure the safe management of pets in autonomous vehicles.

[0301] 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.

[0302] In this invention, the server is a device for monitoring the behavior of a pet, and includes means for capturing the movements of the pet in real time using a camera and a motion sensor, a device for monitoring the health condition of the pet, and means for measuring the body temperature and heart rate of the pet using a sensor, and a device for tracking the location information of the pet, and means for periodically acquiring the location information of the pet using a GPS module. This makes it possible to monitor the behavior, health condition, and location information of the pet in real time so that the pet can stay safe and comfortable inside the autonomous vehicle.

[0303] A "device for monitoring pet behavior" is a device that uses a camera or motion sensor to capture pet movements in real time.

[0304] "Means of capturing in real time" refers to the ability to instantly obtain current situations and activities, and record and analyze that data.

[0305] The "means for converting into a communicable format" is a function for converting data into an appropriate format so that it can be sent to other devices or servers via a communication line.

[0306] "Means for sending to server" refers to the function of sending data to the server via a communication line.

[0307] The "means for estimating pet behavior patterns" is a function for analyzing received data and estimating patterns of pet movement and behavior.

[0308] "Means for sending notifications to the user's device" refers to a function that sends analysis results and alerts to the user's device, such as a smartphone or tablet.

[0309] "Means for monitoring pet behavior inside an autonomous vehicle" refers to a function that monitors pet behavior inside an autonomous vehicle in real time and notifies the user if any abnormalities are detected.

[0310] A "device for monitoring the health of a pet" is a device that measures the health of a pet using temperature and heart rate sensors.

[0311] The "means for saving the measured data in a local memory" refers to a storage device for temporarily saving the measured data.

[0312] "Means for detecting abnormalities" is a function that detects abnormal conditions from analyzed data.

[0313] "Means of notifying the user terminal inside the self-driving vehicle" refers to a function that notifies the user terminal in real time of any abnormalities or behavior of pets inside the car.

[0314] "Means for obtaining pet location information" refers to a function that periodically identifies the pet's location using a GPS module.

[0315] "Means for confirming that a pet is in a safe area" refers to a function for confirming whether a pet is within a pre-defined safe area within an autonomous vehicle.

[0316] The present invention provides a system for comprehensively monitoring the behavior, health status, and location information of pets in an autonomous vehicle. Specific embodiments of the present invention will be described below.

[0317] System Configuration

[0318] Terminal (device for monitoring pet behavior)

[0319] The terminal contains the following main components:

[0320] Camera: Installed to capture video of your pet. Captures video data in real time.

[0321] Motion sensor: A sensor that detects pet movement and collects pet behavior data.

[0322] Body temperature and heart rate sensors: Regularly measure your pet's health indicators and obtain health status data.

[0323] GPS module: A module for obtaining pet location information.

[0324] Communication module: A Wi-Fi or Bluetooth module for sending data to the server.

[0325] Local memory: A storage device for temporarily storing acquired data.

[0326] server

[0327] The server has the following features:

[0328] Data analysis function: Analyzes data sent from the device to estimate your pet's behavior and health condition.

[0329] Notification function: Sends information and alerts to the user's device based on the analysis results.

[0330] Database: Records and manages pet behavior history and health status.

[0331] User terminal

[0332] A smartphone app with the following functions is installed on the user's device:

[0333] Real-time display function: Displays your pet's behavior, health status, and location information in real time.

[0334] Notification function: Notifies users of alerts and information from the server.

[0335] History reference function: You can refer to past data history.

[0336] Program processing

[0337] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[0338] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it identifies behaviors such as "pet is running" or "pet is sleeping." Depending on the analysis results, a push notification is sent to the user's smartphone app.

[0339] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[0340] Health monitoring

[0341] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[0342] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[0343] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[0344] Location tracking

[0345] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[0346] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[0347] Users can check their pet's current location and past routes using a smartphone app.

[0348] Specific examples

[0349] 1. Examples of behavioral monitoring:

[0350] The device uses a camera to capture real-time footage of a dog playing in the yard.

[0351] The terminal compresses the video data and sends it to the server via the communication module.

[0352] The server analyzes the received data and determines that a dog is running in the yard.

[0353] The server notifies the user of the results via their smartphone app.

[0354] Users can use the app to see that their dog is playing happily.

[0355] 2. Examples of health monitoring:

[0356] The device measures the dog's temperature as 36.8 degrees.

[0357] The device stores the measurement data in its local memory and periodically transmits it to the server.

[0358] The server analyzes the received data and determines that the body temperature is within the normal range.

[0359] The server notifies the user of the results via their smartphone app.

[0360] Users can use the app to ensure their pets are in good health.

[0361] 3. Examples of location tracking:

[0362] The device uses a GPS module to obtain the location information of dogs in the park.

[0363] The device stores the acquired location data in its local memory and periodically transmits it to the server.

[0364] The server compares the received location information with map information to determine the dog's current location.

[0365] The server displays the results on the user's smartphone app.

[0366] The user uses the app to confirm that the dog's current location is in the park.

[0367] Example prompt sentence:

[0368] "Temperature sensor data: 36.5 degrees, heart rate: 80 bpm, GPS location information: latitude 35.6895, longitude 139.6917, pet activity: running"

[0369] These methods allow users to continuously monitor the safety and health of their pets while in an autonomous vehicle.

[0370] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0371] Step 1:

[0372] The device uses a camera and motion sensor to capture video and movements of your pet in real time. The input is the camera image and motion sensor data, and the output is the captured video data and movement data. Specifically, the camera takes video and the motion sensor detects movement.

[0373] Step 2:

[0374] The terminal compresses the captured video and motion data and converts it into a format that can be transmitted. The input is the captured raw data, and the output is the compressed data. A data compression algorithm (e.g., H.264) is used for this process. Specifically, the data compression algorithm efficiently compresses the video data.

[0375] Step 3:

[0376] The terminal sends the converted data to the server through the communication module. The input is the compressed data, and the output is the data sent to the server. Specifically, the data is sent to the server via Wi-Fi or Bluetooth communication.

[0377] Step 4:

[0378] The server analyzes the received data and estimates the pet's behavioral patterns. The input is compressed data received from the device, and the output is the estimated behavioral pattern. Specifically, a machine learning algorithm analyzes the data and identifies behaviors such as "running" or "sleeping."

[0379] Step 5:

[0380] The server sends a notification to the user's device based on the estimated behavioral pattern. The input is the estimated behavioral pattern, and the output is a notification to the user's device. Specifically, the notification system sends a push notification to the user's smartphone.

[0381] Step 6:

[0382] The device periodically uses the body temperature and heart rate sensors to measure the pet's health indicators. The input is the body temperature and heart rate measurement data, and the output is the health indicator data. Specifically, the sensors measure the body temperature and heart rate and obtain the data.

[0383] Step 7:

[0384] The terminal stores the measurement data in its local memory and transmits it to the server at regular intervals. The input is the measurement data, and the output is the stored data and transmitted data. Specifically, the data is stored in the local memory and periodically transmitted to the server.

[0385] Step 8:

[0386] The server analyzes the received health data and detects abnormalities. The input is the health status measurement data, and the output is the anomaly detection result. Specifically, the analysis algorithm analyzes the data and determines whether there is an abnormality in the health status.

[0387] Step 9:

[0388] The server sends an alert to the user's device based on the detected anomaly. The input is the anomaly detection result, and the output is an alert notification to the user's device. Specifically, the notification system sends an alert to the user's smartphone.

[0389] Step 10:

[0390] The device periodically obtains the pet's location information using the built-in GPS module. The input is GPS data and the output is location information. Specifically, the GPS module identifies the location information and obtains the data.

[0391] Step 11:

[0392] The terminal stores the acquired location information in its local memory and periodically transmits it to the server. The input is location information data, and the output is the stored data and transmitted data. Specifically, the data is stored in the local memory and then transmitted to the server.

[0393] Step 12:

[0394] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The input is location data, and the output is the analyzed location information. Specifically, the map analysis algorithm analyzes the location information and determines the exact location.

[0395] Step 13:

[0396] The server displays the analyzed location information on the user's smartphone app, allowing them to check their pet's current location and past movement routes. The input is the analyzed location information, and the output is the display of the location information on the user's device. Specifically, the location information is displayed on the user's app.

[0397] Example prompt sentence:

[0398] "Temperature sensor data: 36.5 degrees, heart rate: 80 bpm, GPS location information: latitude 35.6895, longitude 139.6917, pet activity: running"

[0399] 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.

[0400] The present invention provides a system that combines a system for comprehensively monitoring pet behavior, health status, and location information with an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention will be described below.

[0401] System Configuration

[0402] The system consists of the following main components:

[0403] 1. Device (terminal) for monitoring pet behavior

[0404] 2. Server that analyzes and manages data

[0405] 3. User's information device (smartphone or tablet)

[0406] 4. Emotion engine that recognizes user emotions

[0407] Terminal (device for monitoring pet behavior)

[0408] Camera: A device for capturing video of your pet.

[0409] Motion sensor: A sensor for detecting pet movement.

[0410] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate).

[0411] GPS module: A module for determining the current location of your pet.

[0412] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth.

[0413] Local memory: A storage device for temporarily storing data.

[0414] server

[0415] Data analysis function: Has the ability to analyze received data and estimate your pet's behavioral patterns and health condition.

[0416] Notification function: Has the ability to send information and alerts to user devices based on analysis results.

[0417] Database: Includes a database for recording and managing pet behavior history and health status.

[0418] Emotion engine: Has the ability to analyze the user's emotions and generate appropriate feedback based on the results.

[0419] User terminal

[0420] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[0421] Program processing

[0422] The program processing performed by each device in the system will be explained below in natural language.

[0423] Pet behavior monitoring

[0424] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[0425] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it can identify behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via push notifications to the user's smartphone app.

[0426] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[0427] Health monitoring

[0428] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[0429] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[0430] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[0431] Location tracking

[0432] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[0433] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[0434] Users can check their pet's current location and past routes using a smartphone app.

[0435] Adding an Emotion Engine

[0436] The server analyzes the user's emotions using an emotion engine, which analyzes the user's emotional state in real time based on data collected from the user's device (e.g., user input information, voice, facial expressions, etc.).

[0437] If the user is feeling stressed, the emotion engine analyzes the pet's behavioral data and generates feedback to encourage therapeutic behavior, such as sending a notification to the user's smartphone to "take some time to relax with your pet."

[0438] If the user is relaxed, the emotion engine generates feedback to encourage positive behavior in the pet, such as sending a notification to the user's smartphone saying, "Praise your pet for being good."

[0439] Specific examples

[0440] Examples of behavioral monitoring

[0441] 1. The device uses its camera to capture video of a dog playing in the yard.

[0442] 2. The terminal compresses the video data and sends it to the server via the communication module.

[0443] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[0444] 4. The server notifies the user of the results via their smartphone app.

[0445] 5. The user uses the app to confirm that the dog is playing happily.

[0446] Health monitoring examples

[0447] 1. The device measures the dog's temperature as 36.8 degrees.

[0448] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[0449] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[0450] 4. The server notifies the user of the results via their smartphone app.

[0451] 5. The user uses the app to ensure their pet is in good health.

[0452] Examples of location tracking

[0453] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[0454] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[0455] 3. The server compares the received location information with map information to determine the dog's current location.

[0456] 4. The server displays the results on the user's smartphone app.

[0457] 5. The user uses the app to confirm that the dog is currently at the park.

[0458] Examples of emotion engines

[0459] 1. The server receives voice data from the user's smartphone.

[0460] 2. The emotion engine analyzes the voice data and determines that the user is feeling stressed.

[0461] 3. The server generates a notification to encourage the pet to engage in therapeutic behavior and sends it to the user's smartphone.

[0462] 4. The user uses the app to view therapeutic behaviors and relax with their pet.

[0463] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and also provides appropriate feedback according to the user's emotional state.

[0464] The processing flow will be explained below.

[0465] Behavioral monitoring

[0466] Step 1: Data Capture

[0467] The device uses a camera and motion sensors to capture video and movements of your pet in real time.

[0468] The device stores the captured video data and motion data in temporary memory.

[0469] Step 2: Data processing

[0470] The terminal compresses the captured data and converts it into a format that can be communicated.

[0471] The terminal organizes the processed data as batch data.

[0472] Step 3: Sending data

[0473] The device sends the processed data to the server via Wi-Fi or Bluetooth.

[0474] The terminal confirms the success of the transmission and receives an acknowledgement.

[0475] Step 4: Analyze the data

[0476] The server analyzes the received data and applies behavior recognition algorithms to detect the pet's behavior patterns.

[0477] The server records information such as "pet is running" or "pet is sleeping" in the behavior log.

[0478] Step 5: Sending notifications

[0479] The server sends analysis results such as "your pet is running" or "your pet is sleeping" to the user's smartphone app as a push notification.

[0480] Users can check their pet's current behavior using a smartphone app.

[0481] Health monitoring

[0482] Step 1: Data collection

[0483] The device uses sensors to measure your pet's body temperature and heart rate every 10 minutes.

[0484] The terminal temporarily stores the measurement data in a local memory.

[0485] Step 2: Send data

[0486] The terminal transmits the measurement data to the server.

[0487] The terminal adjusts its periodic data transmission schedule to optimize power consumption.

[0488] Step 3: Data analysis

[0489] The server analyzes the received data in real time and evaluates whether it is within the normal range.

[0490] If the server detects an anomaly, it generates an alert to the user.

[0491] Step 4: Sending notifications

[0492] The server sends the results of abnormality detection and regular health status reports to the user's smartphone via push notifications.

[0493] Users can check notifications about their pet's health status on their smartphone and take necessary measures.

[0494] Location Tracking

[0495] Step 1: Obtaining location information

[0496] The device periodically obtains your pet's location information using the built-in GPS module.

[0497] The terminal stores the acquired location information in a local memory.

[0498] Step 2: Send data

[0499] The terminal transmits the location information data to the server.

[0500] The terminal confirms the success of the transmission and receives an acknowledgement.

[0501] Step 3: Data analysis

[0502] The server compares the location data with map information to determine the pet's current location.

[0503] The server records the location information as the pet's movement history.

[0504] Step 4: View location information

[0505] The server sends map data to the user's smartphone app to display the pet's current location.

[0506] Users can check their pet's current location and past routes using a smartphone app.

[0507] Adding an Emotion Engine

[0508] Step 1: Collecting emotion data

[0509] The user's terminal collects the user's voice, facial expressions, and input information.

[0510] The terminal transmits the collected emotion data to the server.

[0511] Step 2: Analyze the emotion data

[0512] The server uses an emotion engine to analyze the received emotion data and estimate the user's emotional state.

[0513] The server classifies the emotional state as "stressed" or "relaxed," etc.

[0514] Step 3: Generate feedback

[0515] The emotion engine analyzes pet behavior data and generates notifications to prompt therapeutic behaviors if the user is experiencing stress.

[0516] The emotion engine generates notifications to encourage positive behavior for pets when the user is relaxed.

[0517] Step 4: Submit your feedback

[0518] The server transmits the generated feedback to the user's smartphone.

[0519] Users receive notifications on their smartphone app and spend appropriate time with their pets.

[0520] Specific examples

[0521] Examples of behavioral monitoring

[0522] Step 1:

[0523] The device uses a camera to capture footage of a dog playing in the yard.

[0524] Step 2:

[0525] The terminal compresses the video data and transmits it to the server via the communication module.

[0526] Step 3:

[0527] The server analyzes the received data and determines that "a dog is running in the yard."

[0528] Step 4:

[0529] The server notifies the user of the results via their smartphone app.

[0530] Step 5:

[0531] The user uses the app to confirm that the dog is playing happily.

[0532] Health monitoring examples

[0533] Step 1:

[0534] The device measures the dog's temperature as 36.8 degrees.

[0535] Step 2:

[0536] The terminal stores the measurement data in a local memory and periodically transmits it to a server.

[0537] Step 3:

[0538] The server analyzes the received data and determines that the body temperature is within the normal range.

[0539] Step 4:

[0540] The server notifies the user of the results via their smartphone app.

[0541] Step 5:

[0542] Users use the app to ensure their pets are in good health.

[0543] Examples of location tracking

[0544] Step 1:

[0545] The device uses a GPS module to obtain the location information of dogs in the park.

[0546] Step 2:

[0547] The terminal stores the acquired location data in a local memory and periodically transmits it to a server.

[0548] Step 3:

[0549] The server compares the received location information with map information to determine the dog's current location.

[0550] Step 4:

[0551] The server displays the results on the user's smartphone app.

[0552] Step 5:

[0553] The user uses the app to confirm that the dog's current location is at the park.

[0554] Examples of emotion engines

[0555] Step 1:

[0556] The user's terminal collects the user's voice data.

[0557] Step 2:

[0558] The terminal transmits the collected voice data to the server.

[0559] Step 3:

[0560] The emotion engine analyzes the voice data and determines that the user is feeling stressed.

[0561] Step 4:

[0562] The server generates notifications to prompt therapeutic behavior and sends them to the user's smartphone.

[0563] Step 5:

[0564] Users use the app to view therapeutic behaviors and relax with their pet.

[0565] Example 2

[0566] 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."

[0567] Comprehensive and real-time monitoring of pet behavior, health, and location information is difficult without error. Furthermore, there are no systems that provide appropriate feedback taking into account the user's emotional state. This makes it challenging to properly monitor pet status and provide appropriate responses in conjunction with the user's emotional state.

[0568] 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.

[0569] In this invention, the server includes: means for capturing the movements of the pet in real time using a camera and a motion sensor; means for compressing the captured data and converting it into a communicable format; means for transmitting the converted data to the server via a communication line; means for analyzing the data received by the server and estimating the behavioral pattern of the pet; means for sending a notification to the user's terminal based on the estimated behavioral pattern; means for measuring the pet's body temperature and heart rate using a sensor; means for periodically saving the measured data in a local memory; means for transmitting the saved data to the server; means for analyzing the data received by the server and detecting anomalies; means for sending an alert to the user's terminal based on the detected anomaly; means for periodically acquiring location information of the pet using a GPS module; means for saving the acquired location information in a local memory; means for transmitting the saved location information to the server; means for analyzing the location information received by the server based on map information; This makes it possible to comprehensively monitor a pet's behavior, health, and location, while also providing appropriate feedback based on the user's emotional state.

[0570] A "camera" is a device for capturing video data.

[0571] A "motion sensor" is a sensor for detecting the movement of an object.

[0572] "Pet" refers to an animal kept in the home.

[0573] "Real-time" means processing data immediately with minimal delay.

[0574] "Data compression" is the process of transforming data using a certain algorithm to reduce the amount of data.

[0575] A "communicable format" is a format used to transmit data, designed to facilitate data exchange.

[0576] A "communications line" is a network infrastructure for transmitting data to a remote location.

[0577] A "server" is a computer system that provides services over a network.

[0578] "Analysis" is a method for processing data and understanding its meaning and structure.

[0579] "Behavioral patterns" are information that indicates a series of behaviors and habits of a pet.

[0580] A "notification" is a message or alert that conveys information to the user.

[0581] A "sensor" is a device that measures physical quantities and outputs them as data.

[0582] "Body temperature" is an indicator of the internal temperature of a living organism.

[0583] "Heart rate" is an index that indicates the number of heartbeats per unit time.

[0584] "Local memory" is a storage device for temporarily storing data.

[0585] "Abnormal" refers to a state or value that is outside the normal range.

[0586] An "alert" is a warning notification that notifies the user of an abnormal situation.

[0587] A "GPS module" is a device for acquiring location information.

[0588] "Location information" is data that indicates the geographical location of an object.

[0589] "Map information" is data for visually displaying geographical locations.

[0590] An "emotion engine" is a software system for analyzing a user's emotional state and generating feedback based on that.

[0591] "Emotion" is information that indicates the user's psychological state or mood.

[0592] "Feedback" is advice or feedback provided to the user.

[0593] This invention is a system that comprehensively monitors pet behavior, health status, and location information, and provides appropriate feedback according to the user's emotional state. This system consists of the following main components: a device (terminal) that monitors pet behavior, a server that analyzes and manages the data, the user's information terminal (smartphone or tablet), and an emotion engine that recognizes the user's emotions.

[0594] System Configuration

[0595] Terminal (device for monitoring pet behavior)

[0596] Camera: A device for taking pictures of pets, for example capturing footage of a dog playing in the yard.

[0597] Motion sensor: A sensor that detects the movement of your pet, such as when your pet is running or sleeping.

[0598] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate). Detects whether the body temperature is within the normal range.

[0599] GPS module: A module for determining the current location of pets. Obtains location information of pets in the park.

[0600] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth. Compressed data is sent to the server.

[0601] Local memory: A storage device for temporarily storing data. It temporarily stores measurement data and location information.

[0602] server

[0603] Data analysis function: The system has the ability to analyze received data and estimate the behavioral patterns and health status of pets. For example, it can analyze received video data and determine that "a dog is running in the yard."

[0604] Notification function: The system has the ability to send information and alerts to the user's device based on the analysis results, informing the user of any abnormalities in behavioral patterns or health conditions.

[0605] Database: Includes a database for recording and managing pet behavior history and health status. Stores past behavioral data and health data.

[0606] Emotion engine: This engine analyzes the user's emotions and generates appropriate feedback based on the results. For example, it can determine from voice data that the user is feeling stressed.

[0607] User terminal

[0608] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[0609] Specific examples

[0610] The operation of the system will be explained using a specific example.

[0611] Examples of behavioral monitoring

[0612] 1. The device uses its camera to capture video of a dog playing in the yard.

[0613] 2. The terminal compresses the video data and sends it to the server via the communication module.

[0614] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[0615] 4. The server notifies the user of the results via their smartphone app.

[0616] 5. The user uses the app to confirm that the dog is playing happily.

[0617] Health monitoring examples

[0618] 1. The device measures the dog's temperature as 36.8 degrees.

[0619] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[0620] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[0621] 4. The server notifies the user of the results via their smartphone app.

[0622] 5. The user uses the app to ensure their pet is in good health.

[0623] Examples of location tracking

[0624] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[0625] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[0626] 3. The server compares the received location information with map information to determine the dog's current location.

[0627] 4. The server displays the results on the user's smartphone app.

[0628] 5. The user uses the app to confirm that the dog is currently at the park.

[0629] Examples of emotion engines

[0630] 1. The server receives voice data from the user's smartphone.

[0631] 2. The emotion engine analyzes the voice data and determines that the user is feeling stressed.

[0632] 3. The server generates a notification to encourage the pet to engage in therapeutic behavior and sends it to the user's smartphone.

[0633] 4. The user uses the app to view therapeutic behaviors and relax with their pet.

[0634] Prompt Sentence Examples

[0635] "Please explain how the program checks to see if a dog's temperature is normal."

[0636] "Describe how your system works to track your pet's location."

[0637] "Please explain in detail how to generate notifications based on user emotions."

[0638] This makes it possible to comprehensively monitor a pet's behavior, health, and location, while also providing appropriate feedback based on the user's emotional state.

[0639] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0640] Program processing flow

[0641] Pet behavior monitoring

[0642] Step 1:

[0643] The device activates the camera to capture the pet's video in real time, and simultaneously activates the motion sensor to detect the pet's movements. The input is the pet's movements and video, and the output is the captured video data and movement data.

[0644] Step 2:

[0645] The device compresses the captured video data and movement data and converts them into a format that can be communicated. Specifically, the video data is compressed into JPEG format, and the movement data is converted into JSON format. The input is the captured data, and the output is the compressed data.

[0646] Step 3:

[0647] The device sends the compressed data to the server via Wi-Fi or Bluetooth. The input is the compressed data, and the output is the data sent to the server.

[0648] Step 4:

[0649] The server analyzes the received data and estimates the pet's behavioral patterns in real time. The video data is processed by image analysis software, and the movement data is processed by motion analysis algorithms. The input is the received data, and the output is the estimated behavioral patterns.

[0650] Step 5:

[0651] The server identifies the pet's behavior based on the analysis results and sends a push notification of that information to the user's smartphone app. The input is the analyzed behavior pattern, and the output is notification information.

[0652] Step 6:

[0653] The user receives a notification on the smartphone app and checks the current behavior of their pet. The input is the notification information, and the output is the user's confirmation action.

[0654] Health monitoring

[0655] Step 1:

[0656] The device activates the temperature and heart rate sensors to measure the pet's temperature and heart rate. The measurement results are stored in the internal memory. The input is the sensor data, and the output is the measurement results.

[0657] Step 2:

[0658] The device temporarily stores the measurement data in its local memory and sends it to the server at regular intervals. The data is converted to CSV format and sent via Wi-Fi. The input is the measurement data, and the output is the data sent to the server.

[0659] Step 3:

[0660] The server analyzes the received health data in real time to detect abnormalities. It uses an anomaly detection algorithm to generate an alert if the body temperature exceeds the normal range. The input is the received health data, and the output is the presence or absence of abnormalities.

[0661] Step 4:

[0662] If the server detects an anomaly, it generates an alert based on that information and sends it to the user's smartphone app. The input is the anomaly detection result, and the output is the alert information.

[0663] Step 5:

[0664] Users receive anomaly alerts via a smartphone app and take necessary measures. The input is the alert information, and the output is the corrective action.

[0665] Location tracking

[0666] Step 1:

[0667] The device uses the built-in GPS module to acquire pet location information. The location data is stored in the internal memory. The input is GPS data, and the output is location data.

[0668] Step 2:

[0669] The device stores the acquired location data in its local memory and periodically sends it to the server. The data is converted to NMEA format and sent via Wi-Fi. The input is the location data, and the output is the data sent to the server.

[0670] Step 3:

[0671] The server analyzes the received location information and locates the pet's current location by comparing it with map information. It uses a location analysis algorithm, whose input is the received location information and whose output is the determined current location.

[0672] Step 4:

[0673] The server sends location information based on the analysis results to the user's smartphone app. The input is the identified current location, and the output is a location notification.

[0674] Step 5:

[0675] Users can check real-time location information on a smartphone app and check their pet's current location and past movement routes. The input is location information notification, and the output is the user's confirmation behavior.

[0676] Adding an Emotion Engine

[0677] Step 1:

[0678] The server receives voice data and facial expression data from the user's smartphone. This data is processed in real time. The input is the user's emotional data, and the output is the received data.

[0679] Step 2:

[0680] The emotion engine analyzes the collected data and determines the user's emotion in real time. It uses voice recognition software to analyze the emotional state. The input is the received emotion data, and the output is the emotion analysis result.

[0681] Step 3:

[0682] The server generates a notification to encourage therapeutic behavior for the pet based on the analysis results of the emotion engine and sends it to the user's smartphone. The input is the emotion analysis result, and the output is the therapeutic behavior notification.

[0683] Step 4:

[0684] The emotion engine generates notifications to encourage positive behaviors for pets when the user is relaxed. The input is the emotion analysis result, and the output is the positive behavior notification.

[0685] Step 5:

[0686] The user checks the notification on the smartphone app and takes time to relax with their pet. The input is the notification information, and the output is the user's behavior.

[0687] This makes it possible to comprehensively monitor a pet's behavior, health, and location, while also providing appropriate feedback based on the user's emotional state.

[0688] (Application example 2)

[0689] 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."

[0690] Conventional pet monitoring systems focus on monitoring pet behavior, health, and location information, but none take into account the user's emotional state. Furthermore, in autonomous vehicles, there is a lack of technology that provides appropriate driving assistance based on pet safety management and the user's emotions. The present invention aims to solve these problems.

[0691] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for determining the user's emotional state using an emotion engine that analyzes the user's emotional state, means for generating corresponding feedback based on the user's emotional state and notifying the user terminal of the feedback, and means for providing driving assistance that takes the user's emotional state into consideration using the emotion engine that analyzes the user's emotional state. This makes it possible to provide driving assistance that corresponds to the user's emotional state while managing the safety of pets in an autonomous vehicle.

[0692] A "device for monitoring pet behavior" is a device that uses a camera or motion sensor to monitor pet movements in real time and transmits the data to a server.

[0693] "Capture" is the act of collecting motion and video using cameras and sensors.

[0694] "Means for converting into a communicable format" refers to a device or process that compresses the captured data and converts it into a form that can be sent to a server.

[0695] A "server" is a central computer system that analyzes received data and sends notifications to user terminals based on the results of various analyses.

[0696] The "means for estimating the behavioral patterns of a pet" refers to an algorithm or program that analyzes the data received on the server and determines the specific behavior of the pet.

[0697] "Means for sending notifications to user terminals" refers to a communications system for sending information and alerts from a server to a user's smartphone or tablet.

[0698] An "emotion engine" is a software engine that analyzes the user's voice, facial expressions, input information, etc. to determine the user's emotional state.

[0699] The "means for determining the emotional state of a user" refers to a process and system that uses an emotion engine to analyze and determine the emotion of a user.

[0700] The "means for generating corresponding feedback and notifying the user terminal" is a mechanism for generating appropriate feedback based on the emotional state of the user determined by the emotion engine and transmitting that feedback to the user terminal.

[0701] The "device for monitoring the health condition of a pet" is a device that measures the health indicators of a pet using body temperature and heart rate sensors and transmits the results to a server.

[0702] The "means for detecting anomalies" is a system that analyzes the health data received on the server and identifies data points that are out of the ordinary.

[0703] A "device for tracking pet location information" is a device that periodically acquires pet location information using a GPS module and transmits it to a server.

[0704] "Driving Assist" is a system that provides driving assistance based on the user's emotional state and notifies and suggests the driver via a smartphone or in-car display.

[0705] The present invention relates to a system that comprehensively monitors the behavior, health status, and location information of a pet, and further provides appropriate feedback according to the emotional state of the user. Specific embodiments for carrying out the present invention will be described in detail below.

[0706] System Configuration

[0707] The system consists of the following main components:

[0708] 1. Device (terminal) for monitoring pet behavior

[0709] 2. Server that analyzes and manages data

[0710] 3. User's information device (smartphone or tablet)

[0711] 4. Emotion engine that recognizes user emotions

[0712] Terminal

[0713] The device has the following features to monitor your pet's behavior, health and location:

[0714] Camera: Capture footage of your pet.

[0715] Motion sensor: Detects pet movements in real time.

[0716] Body temperature and heart rate sensors: measure your pet's health indicators.

[0717] GPS module: Identify your pet's location.

[0718] Communication module: Sends data to the server using Wi-Fi or Bluetooth.

[0719] Local memory: temporarily stores data.

[0720] server

[0721] The server has the following features:

[0722] Data analysis function: Analyzes received data and estimates your pet's behavioral patterns and health condition.

[0723] Notification function: Sends information and alerts to user devices based on analysis results.

[0724] Database: Records and manages pet behavior history and health status.

[0725] Emotion engine: Analyzes the user's emotions and generates appropriate feedback based on the results.

[0726] User terminal

[0727] The user terminal has the following features:

[0728] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[0729] Program processing

[0730] The program processing performed by each device will be explained below.

[0731] Pet behavior monitoring

[0732] The device uses a camera and motion sensors to capture video and movements of the pet in real time. The captured video and motion data is compressed and converted into a format that can be communicated. The converted data is then sent to a server via a communications module. The server analyzes the received data and estimates the pet's behavioral patterns. For example, it identifies behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via a push notification to the user's smartphone app. The user can then check their pet's current behavior on the smartphone app.

[0733] Health monitoring

[0734] The device periodically measures the pet's health indicators using the body temperature and heart rate sensors. The measurement data is stored in local memory and sent to the server at regular intervals. The server analyzes the received health data in real time and detects abnormalities. For example, if the body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app. The user receives notifications of the pet's health status via the smartphone app and can take necessary measures.

[0735] Location tracking

[0736] The device periodically obtains the pet's location information using the built-in GPS module. The obtained location information is stored in local memory and periodically sent to the server. The server analyzes the received location information and compares it with map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app. The user can then check the pet's current location and past movement routes on the smartphone app.

[0737] Adding an Emotion Engine

[0738] The server uses an emotion engine to analyze the user's emotions. The emotion engine analyzes the user's emotional state in real time based on data collected from the user's device (e.g., user input information, voice, facial expressions, etc.). If the user is feeling stressed, the emotion engine analyzes the pet's behavioral data and generates therapeutic feedback. For example, it sends a notification to the user's smartphone, such as "Take some time to relax with your pet." If the user is relaxed, the emotion engine generates feedback to encourage the pet's positive behavior. For example, it sends a notification to the user's smartphone, such as "Praise your pet for being well-behaved."

[0739] Examples of specific examples and prompts

[0740] Examples of behavioral monitoring

[0741] The device uses a camera to capture video of a dog playing in the yard. The device compresses the video data and sends it to the server via the communication module. The server analyzes the received data and determines that "the dog is running in the yard." The server notifies the user of the result via a smartphone app. The user then uses the app to confirm that "the dog is playing happily."

[0742] Health monitoring examples

[0743] The device measures the dog's temperature as 36.8°C. The device stores the measurement data in its local memory and periodically sends it to the server. The server analyzes the received data and determines that the body temperature is within the normal range. The server then notifies the user of the result via a smartphone app. The user can then use the app to confirm that their pet's health is normal.

[0744] Examples of location tracking

[0745] The device uses a GPS module to obtain the location information of the dog in the park. The device stores the obtained location data in its local memory and periodically sends it to the server. The server compares the received location information with map information to determine the dog's current location. The server displays the result on the user's smartphone app. The user then uses the app to confirm that the dog's current location is in the park.

[0746] Examples of emotion engines

[0747] The server receives voice data from the user's smartphone. The emotion engine analyzes the voice data and determines that the user is feeling stressed. The server generates a notification to prompt the pet to engage in therapeutic behavior and sends it to the user's smartphone. The user then uses the app to confirm the therapeutic behavior and relax with their pet.

[0748] Prompt Sentence Examples

[0749] Analyze the given audio data and generate feedback including playing relaxing music and notifying the pet's status if the user is stressed.

[0750] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and also provides appropriate feedback according to the user's emotional state.

[0751] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0752] Step 1:

[0753] The device uses a camera to capture images of the pet in real time. The motion sensor also detects the pet's movements at the same time. The input is the pet's video data and motion data, which are obtained by capturing these. The output is the video data and motion data. These data are temporarily stored in local memory.

[0754] Step 2:

[0755] The terminal compresses the captured data and converts it into a format that can be communicated. The input is the video data and motion data obtained in step 1. The data is compressed using a compression algorithm and format conversion is performed. The output is the compressed and converted data. This data is ready to be sent to the server via the communication module.

[0756] Step 3:

[0757] The terminal sends the converted data to the server through the communication module. The input is the compressed and converted data obtained in step 2. The data is sent to the server using a transmission protocol (e.g., Wi-Fi or Bluetooth). The output is the data that arrives at the server.

[0758] Step 4:

[0759] The server analyzes the received data and infers the pet's behavioral patterns. The input is the data that arrived at the server in step 3. It uses a machine learning algorithm (e.g., a generative AI model) to analyze the data and infer what the pet is doing. The output is information about the pet's behavioral patterns.

[0760] Step 5:

[0761] The server sends notifications to the user's device based on the estimated behavioral patterns. The input is the information about the behavioral patterns obtained in step 4. An appropriate notification is generated using a notification generation algorithm. The output is the notification sent to the user's device.

[0762] Step 6:

[0763] The device periodically measures the pet's health indicators using the body temperature and heart rate sensors. The input is the pet's body temperature and heart rate data. These data are obtained by measuring them. The output is the measurement data. This data is stored in the local memory.

[0764] Step 7:

[0765] The terminal sends the measurement data to the server using the communication module. The input is the measurement data obtained in step 6. The data is sent to the server using a transmission protocol. The output is the data that arrives at the server.

[0766] Step 8:

[0767] The server analyzes the received health data in real time and detects abnormalities. The input is the health data that arrived at the server in step 7. Anomalies are detected using data analysis algorithms. The output is alert information regarding the presence or absence of abnormalities.

[0768] Step 9:

[0769] The server sends an alert to the user terminal based on the detected anomaly. The input is the alert information obtained in step 8. The alert is generated using a notification generation algorithm. The output is the alert sent to the user terminal.

[0770] Step 10:

[0771] The device periodically obtains the pet's location information using the built-in GPS module. The input is the pet's current location information. This is obtained by obtaining it. The output is the location data. This data is stored in the local memory.

[0772] Step 11:

[0773] The terminal transmits the acquired location information to the server using the communication module. The input is the location data obtained in step 10. The data is transmitted to the server using a transmission protocol. The output is the data that arrives at the server.

[0774] Step 12:

[0775] The server compares the received location information with map information to determine the current location of the pet. The input is the location information received by the server in step 11. The server compares this with map information to determine the current location of the pet. The output is information about the current location of the pet.

[0776] Step 13:

[0777] The server notifies the user's smartphone app of the analysis results. The input is the current location information obtained in step 12. A notification is generated using the notification generation algorithm. The output is a notification sent to the user device.

[0778] Step 14:

[0779] The server receives voice data from the user's smartphone. The input is the user's voice data. This is obtained by receiving it. The output is the voice data that arrives at the server.

[0780] Step 15:

[0781] The emotion engine analyzes the speech data to determine the user's emotional state. The input is the speech data received by the server in step 14. The generative AI model is used to analyze the speech data and infer the user's emotional state. The output is information about the user's emotional state.

[0782] Step 16:

[0783] The server generates corresponding feedback based on the user's emotional state and notifies the user terminal. The input is the emotional state information obtained in step 15. The server generates the feedback using a notification generation algorithm. The output is the feedback sent to the user terminal.

[0784] Step 17:

[0785] The server provides driving assistance that takes into account the user's emotional state. The input is the emotional state information obtained in step 15. A driving assistance algorithm is used to generate appropriate driving assistance suggestions. The output is driving assistance information displayed on the in-vehicle display.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] [Second embodiment]

[0790] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0791] 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.

[0792] 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).

[0793] 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.

[0794] 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.

[0795] 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).

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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."

[0802] The present invention provides a system for comprehensively monitoring pet behavior, health status, and location information. Specific embodiments of the present invention will be described below.

[0803] System Configuration

[0804] The system consists of the following main components:

[0805] 1. Device (terminal) for monitoring pet behavior

[0806] 2. Server that analyzes and manages data

[0807] 3. User's information device (smartphone or tablet)

[0808] Terminal (device for monitoring pet behavior)

[0809] Camera: A device for capturing video of your pet.

[0810] Motion sensor: A sensor for detecting pet movement.

[0811] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate).

[0812] GPS module: A module for determining the current location of your pet.

[0813] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth.

[0814] Local memory: A storage device for temporarily storing data.

[0815] server

[0816] Data analysis function: Has the ability to analyze received data and estimate your pet's behavioral patterns and health condition.

[0817] Notification function: Has the ability to send information and alerts to user devices based on analysis results.

[0818] Database: Includes a database for recording and managing pet behavior history and health status.

[0819] User terminal

[0820] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[0821] Program processing

[0822] The program processing performed by each device in the system will be explained below in natural language.

[0823] Pet behavior monitoring

[0824] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[0825] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it can identify behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via push notifications to the user's smartphone app.

[0826] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[0827] Health monitoring

[0828] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[0829] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[0830] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[0831] Location tracking

[0832] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[0833] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[0834] Users can check their pet's current location and past routes using a smartphone app.

[0835] Specific examples

[0836] Examples of behavioral monitoring

[0837] 1. The device uses its camera to capture video of a dog playing in the yard.

[0838] 2. The terminal compresses the video data and sends it to the server via the communication module.

[0839] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[0840] 4. The server notifies the user of the results via their smartphone app.

[0841] 5. The user uses the app to confirm that the dog is playing happily.

[0842] Health monitoring examples

[0843] 1. The device measures the dog's temperature as 36.8 degrees.

[0844] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[0845] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[0846] 4. The server notifies the user of the results via their smartphone app.

[0847] 5. The user uses the app to ensure their pet is in good health.

[0848] Examples of location tracking

[0849] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[0850] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[0851] 3. The server compares the received location information with map information to determine the dog's current location.

[0852] 4. The server displays the results on the user's smartphone app.

[0853] 5. The user uses the app to confirm that the dog is currently at the park.

[0854] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and provides users with the information they need.

[0855] The processing flow will be explained below.

[0856] Pet behavior monitoring

[0857] Step 1: Data Capture

[0858] The device uses a camera and motion sensors to capture footage and movements of your pet in real time.

[0859] The device stores the captured video data and motion data in temporary memory.

[0860] Step 2: Data processing

[0861] The terminal compresses the captured data and converts it into a suitable format to save communication bandwidth.

[0862] The terminal organizes the processed data as batch data.

[0863] Step 3: Sending data

[0864] The device sends the processed data to the server via Wi-Fi or Bluetooth.

[0865] The terminal confirms the success of the transmission and receives an acknowledgement.

[0866] Step 4: Analyze the data

[0867] The server analyzes the received data and applies behavior recognition algorithms to detect the pet's behavior patterns.

[0868] The server records information such as "pet is running" or "pet is sleeping" in the behavior log.

[0869] Step 5: Sending notifications

[0870] The server sends analysis results such as "your pet is running" or "your pet is sleeping" to the user's smartphone app as a push notification.

[0871] Users can check their pet's current behavior using a smartphone app.

[0872] Health monitoring

[0873] Step 1: Data collection

[0874] The device uses sensors to measure your pet's body temperature and heart rate every 10 minutes.

[0875] The terminal temporarily stores the measurement data in a local memory.

[0876] Step 2: Send data

[0877] The terminal transmits the measurement data to the server.

[0878] The terminal adjusts its periodic data transmission schedule to optimize power consumption.

[0879] Step 3: Data analysis

[0880] The server analyzes the received data in real time and evaluates whether it is within the normal range.

[0881] If the server detects an anomaly, it generates an alert to the user.

[0882] Step 4: Sending notifications

[0883] The server sends the results of abnormality detection and regular health status reports to the user's smartphone via push notifications.

[0884] Users can check notifications about their pet's health status on their smartphone and take necessary measures.

[0885] Location tracking

[0886] Step 1: Obtaining location information

[0887] The device periodically obtains the pet's location information using the built-in GPS module.

[0888] The terminal stores the acquired location information in a local memory.

[0889] Step 2: Send data

[0890] The terminal transmits the location information data to the server.

[0891] The terminal confirms the success of the transmission and receives an acknowledgement.

[0892] Step 3: Data analysis

[0893] The server compares the location data with map information to determine the pet's current location.

[0894] The server records the location information as the pet's movement history.

[0895] Step 4: View location information

[0896] The server sends map data to the user's smartphone app to display the pet's current location.

[0897] Users can check their pet's current location and past routes using a smartphone app.

[0898] Example 1

[0899] 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."

[0900] There is a demand for a system that can comprehensively monitor pet behavior, health status, and location information, and allow users to obtain the information they need in real time. Conventional systems often collect and manage this information separately, making it difficult for users to use and providing information in a centralized manner.

[0901] 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.

[0902] In this invention, the server includes means for capturing the movements of the pet in real time using a camera and a motion sensor, means for compressing the captured data and converting it into a communicable format, means for transmitting the converted data to the server via a communication line, means for analyzing the data received by the server using a generative model and estimating the behavioral patterns of the pet, and means for transmitting notifications to the user's terminal based on the estimated behavioral patterns. This allows the user to centrally manage the behavior, health condition, and location information of the pet and obtain this information in real time.

[0903] A "camera" is a device for capturing images of pets.

[0904] A "motion sensor" is a sensor that detects the movement of a pet.

[0905] "Compression" is a process for reducing the size of captured data.

[0906] "Communicable format" refers to the process of converting data into a format that can be sent and received.

[0907] A "communication line" is a network for transmitting data.

[0908] A "server" is a central computer that analyzes and manages data.

[0909] A "generative model" is an algorithm for analyzing data and recognizing specific patterns.

[0910] A "behavioral pattern" is a series of movements that characterize a pet's behavior.

[0911] "Notification" is a message to inform the user of the analysis results.

[0912] A "terminal" is a device through which a user receives information.

[0913] "Health indicators" are data on body temperature and heart rate that indicate the pet's health condition.

[0914] "Local memory" is a storage device that temporarily stores data within a device.

[0915] An "abnormal alert" is a warning message that occurs when data outside the normal range is detected.

[0916] A "GPS module" is a device used to determine a pet's current location.

[0917] "Location information" is data that indicates the current location of the pet.

[0918] "Map information" is information for visually displaying location data.

[0919] "Tracking" is the act of continuously monitoring a pet's location.

[0920] The present invention is a system for comprehensively monitoring the behavior, health status, and location information of pets. Specific embodiments for carrying out the present invention will be described below.

[0921] System Configuration

[0922] The system consists of the following main components:

[0923] 1. A device that monitors your pet's behavior

[0924] 2. Server that analyzes and manages data

[0925] 3. User's information device (smartphone or tablet)

[0926] Terminal (device for monitoring pet behavior)

[0927] Camera: A device for recording video of your pet. The camera captures video in high resolution at 30 frames per second.

[0928] Motion Sensor: This is a sensor that detects pet movements. The sensor captures movements in real time.

[0929] Body Temperature and Heart Rate Sensor: A sensor that measures your pet's body temperature and heart rate. The measurement results are stored in local memory.

[0930] GPS module: This module identifies the current location of your pet. Location information is acquired periodically.

[0931] Communication module: A module that transmits data to a server using Wi-Fi or Bluetooth. The communication module supports IEEE 802.11ac and Bluetooth Low Energy (BLE).

[0932] Local memory: A storage device that temporarily stores data.

[0933] server

[0934] Data analysis function: The system analyzes the received data and estimates the pet's behavioral patterns and health condition. TensorFlow models and generative models are used for the analysis.

[0935] Notification function: Has the ability to send information and alerts to user devices based on analysis results. Uses Firebase Cloud Messaging (FCM).

[0936] Database: Includes a database for recording and managing pet behavior history and health status.

[0937] User terminal

[0938] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[0939] Program processing

[0940] The program processing performed by each device in the system will be explained below in natural language.

[0941] Pet behavior monitoring

[0942] The device uses a camera and motion sensors to capture video and movement data in real time, then compresses it using the H.264 codec and converts it into a format suitable for communication, before transmitting it to a server via Wi-Fi.

[0943] The server analyzes the received data using a TensorFlow model to estimate the pet's behavioral patterns. For example, it identifies behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are then pushed to the user's device in real time.

[0944] Users can check their pet's current activities through a smartphone app, and the app's dashboard displays messages such as "Your pet is playing happily."

[0945] Health monitoring

[0946] The device periodically measures your pet's health using built-in temperature and heart rate sensors, and the measurement data is stored in local memory and transmitted to a server at regular intervals using Bluetooth Low Energy (BLE).

[0947] The server analyzes the received health data in real time and detects abnormalities. For example, if the body temperature exceeds the normal range, it generates a "high body temperature alert." The generated alert is sent to the user's device.

[0948] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures, such as displaying messages like "Temperature is within normal range."

[0949] Location tracking

[0950] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in local memory and sent to the server via Wi-Fi.

[0951] The server compares the received location information with map data to determine the pet's current location, and uses the Geocoding API to convert the location coordinates into a specific address or place name.

[0952] Users can check their pet's current location and past routes on a smartphone app, which displays their pet's location in real time as it moves around the park.

[0953] Specific examples

[0954] Examples of behavioral monitoring

[0955] 1. The device uses its camera to capture video of a pet playing in the yard.

[0956] 2. The device compresses the video data using H.264 and sends it to the server via Wi-Fi.

[0957] 3. The server analyzes the received data using a TensorFlow model and determines that a pet is running in the yard.

[0958] 4. The server notifies the user's smartphone app of the results using Firebase Cloud Messaging.

[0959] 5. The user uses the app to confirm that their pet is playing happily.

[0960] Health monitoring examples

[0961] 1. The device measures the pet's temperature as 36.8 degrees.

[0962] 2. The device stores the measurement data in its local memory and periodically transmits it to the server using Bluetooth Low Energy.

[0963] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[0964] 4. The server notifies the user of the analysis results via their smartphone app.

[0965] 5. The user uses the app to ensure their pet is in good health.

[0966] Examples of location tracking

[0967] 1. The device uses the GPS module to obtain the location information of pets in the park.

[0968] 2. The device stores the location data in its local memory and transmits it to the server via Wi-Fi.

[0969] 3. The server analyzes the received location information using the Geocoding API to determine the pet's current location.

[0970] 4. The server displays the analysis results on the user's smartphone app.

[0971] 5. The user uses the app to confirm that their pet is currently at the park.

[0972] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and provides users with the information they need in real time.

[0973] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0974] Pet behavior monitoring process flow

[0975] Step 1: Capture behavioral data

[0976] The device uses a built-in camera and motion sensors to capture footage and movements of your pet.

[0977] Input: Real-time video and motion data.

[0978] Processing: The camera captures video at 30 frames per second, and the motion sensor detects movement.

[0979] Output: High resolution video and motion data.

[0980] Step 2: Compress and format the data

[0981] The device compresses the captured video data using the H.264 codec and converts the motion data into CSV format.

[0982] Input: High-resolution video and motion data.

[0983] Processing: Video data is compressed using H.264 and motion data is converted to CSV format.

[0984] Output: Compressed video data and motion data in CSV format.

[0985] Step 3: Sending data

[0986] The device transmits compressed video and motion data to a server via Wi-Fi.

[0987] Input: Compressed video and motion data.

[0988] Processing: Transmit data using IEEE 802.11ac.

[0989] Output: The data sent to the server.

[0990] Step 4: Analyze behavioral patterns

[0991] The server analyzes the received data using a TensorFlow model.

[0992] Input: Received video and motion data.

[0993] Processing: Activity recognition algorithms analyze the video frames and identify activities (e.g., "running" or "sleeping").

[0994] Output: Analyzed behavioral patterns.

[0995] Step 5: Generate and send notifications

[0996] The server sends a notification to the user's smartphone app based on the analysis results.

[0997] Input: Analyzed behavioral patterns.

[0998] Processing: Generate and send notifications using Firebase Cloud Messaging (FCM).

[0999] Output: A push notification is sent to the user's smartphone app.

[1000] Step 6: Confirm your actions

[1001] Users can check their pet's current behavior using a smartphone app.

[1002] Input: The notification sent by the server.

[1003] Action: Display behavioral information on the app dashboard.

[1004] Output: The user confirms the pet's behavior.

[1005] Pet health monitoring process flow

[1006] Step 1: Measuring health data

[1007] The device regularly measures your pet's health indicators using temperature and heart rate sensors.

[1008] Inputs: Real-time body temperature and heart rate.

[1009] Processing: The sensor measures the information and stores it temporarily in local memory.

[1010] Output: Measured body temperature and heart rate data.

[1011] Step 2: Storing and sending data

[1012] The terminal stores the measurement data in its local memory and transmits it to the server at regular intervals.

[1013] Input: Measured body temperature and heart rate data.

[1014] Processing: Transmit data using Bluetooth Low Energy (BLE).

[1015] Output: Measurement data sent to the server.

[1016] Step 3: Anomaly detection and alerting

[1017] The server analyzes the received health data and detects any abnormalities.

[1018] Input: Received temperature and heart rate data.

[1019] Action: Generate an abnormality alert if the normal range is exceeded (e.g., if the body temperature is above 39 degrees).

[1020] Output: The anomaly alert generated.

[1021] Step 4: Health Alert Notifications

[1022] The server sends the generated alert to the user's smartphone app.

[1023] Input: The generated anomaly alert.

[1024] Processing: Send notifications using Firebase Cloud Messaging (FCM).

[1025] Output: An alert is sent to the user's smartphone app.

[1026] Step 5: Health Check

[1027] Users can check their pet's health status via a smartphone app.

[1028] Input: The alert notification sent from the server.

[1029] Processing: Display health information and action suggestions within the app.

[1030] Output: The user checks his health status and takes necessary measures.

[1031] Pet location tracking process flow

[1032] Step 1: Capturing location data

[1033] The device periodically obtains your pet's location information using the built-in GPS module.

[1034] Input: Real-time location information.

[1035] Processing: The GPS module captures location information and stores it in local memory.

[1036] Output: The captured location data.

[1037] Step 2: Storing and sending data

[1038] The device stores the location data in its local memory and transmits it to a server via Wi-Fi.

[1039] Input: The captured location data.

[1040] Processing: Send data using Wi-Fi.

[1041] Output: The location data sent to the server.

[1042] Step 3: Analyze and match location information

[1043] The server compares the received location information with map data to determine the pet's current location.

[1044] Input: Received location data.

[1045] Processing: Use the Geocoding API to convert location coordinates into specific addresses or place names.

[1046] Output: The determined location.

[1047] Step 4: Notification of location data

[1048] The server sends the analysis results to the user's smartphone app.

[1049] Input: Parsed location information.

[1050] Processing: Send location information using Firebase Cloud Messaging (FCM).

[1051] Output: Location information is sent to the user's smartphone app.

[1052] Step 5: Locate and track

[1053] Users can check their pet's current location and past routes using a smartphone app.

[1054] Input: Location information sent from the server.

[1055] Processing: Display location on a map within the app and visualize past travel routes.

[1056] Output: The user sees the pet's current location and its route.

[1057] (Application example 1)

[1058] 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."

[1059] Real-time monitoring of pet safety and health in autonomous vehicles is an important issue for many pet owners. Normally, when pets are left in a car, it is difficult to properly monitor their behavior and health, which can lead to stress and health problems. There is also a risk that pets may become anxious or excited, causing problems inside the vehicle. Therefore, a reliable system is needed to ensure the safe management of pets in autonomous vehicles.

[1060] 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.

[1061] In this invention, the server is a device for monitoring the behavior of a pet, and includes means for capturing the movements of the pet in real time using a camera and a motion sensor, a device for monitoring the health condition of the pet, and means for measuring the body temperature and heart rate of the pet using a sensor, and a device for tracking the location information of the pet, and means for periodically acquiring the location information of the pet using a GPS module. This makes it possible to monitor the behavior, health condition, and location information of the pet in real time so that the pet can stay safe and comfortable inside the autonomous vehicle.

[1062] A "device for monitoring pet behavior" is a device that uses a camera or motion sensor to capture pet movements in real time.

[1063] "Means of capturing in real time" refers to the ability to instantly obtain current situations and activities, and record and analyze that data.

[1064] The "means for converting into a communicable format" is a function for converting data into an appropriate format so that it can be sent to other devices or servers via a communication line.

[1065] "Means for sending to server" refers to the function of sending data to the server via a communication line.

[1066] The "means for estimating pet behavior patterns" is a function for analyzing received data and estimating patterns of pet movement and behavior.

[1067] "Means for sending notifications to the user's device" refers to a function that sends analysis results and alerts to the user's device, such as a smartphone or tablet.

[1068] "Means for monitoring pet behavior inside an autonomous vehicle" refers to a function that monitors pet behavior inside an autonomous vehicle in real time and notifies the user if any abnormalities are detected.

[1069] A "device for monitoring the health of a pet" is a device that measures the health of a pet using temperature and heart rate sensors.

[1070] The "means for saving the measured data in a local memory" refers to a storage device for temporarily saving the measured data.

[1071] "Means for detecting abnormalities" is a function that detects abnormal conditions from analyzed data.

[1072] "Means of notifying the user terminal inside the self-driving vehicle" refers to a function that notifies the user terminal in real time of any abnormalities or behavior of pets inside the car.

[1073] "Means for obtaining pet location information" refers to a function that periodically identifies the pet's location using a GPS module.

[1074] "Means for confirming that a pet is in a safe area" refers to a function for confirming whether a pet is within a pre-defined safe area within an autonomous vehicle.

[1075] The present invention provides a system for comprehensively monitoring the behavior, health status, and location information of pets in an autonomous vehicle. Specific embodiments of the present invention will be described below.

[1076] System Configuration

[1077] Terminal (device for monitoring pet behavior)

[1078] The terminal contains the following main components:

[1079] Camera: Installed to capture video of your pet. Captures video data in real time.

[1080] Motion sensor: A sensor that detects pet movement and collects pet behavior data.

[1081] Body temperature and heart rate sensors: Regularly measure your pet's health indicators and obtain health status data.

[1082] GPS module: A module for obtaining pet location information.

[1083] Communication module: A Wi-Fi or Bluetooth module for sending data to the server.

[1084] Local memory: A storage device for temporarily storing acquired data.

[1085] server

[1086] The server has the following features:

[1087] Data analysis function: Analyzes data sent from the device to estimate your pet's behavior and health condition.

[1088] Notification function: Sends information and alerts to the user's device based on the analysis results.

[1089] Database: Records and manages pet behavior history and health status.

[1090] User terminal

[1091] A smartphone app with the following functions is installed on the user's device:

[1092] Real-time display function: Displays your pet's behavior, health status, and location information in real time.

[1093] Notification function: Notifies users of alerts and information from the server.

[1094] History reference function: You can refer to past data history.

[1095] Program processing

[1096] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[1097] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it identifies behaviors such as "pet is running" or "pet is sleeping." Depending on the analysis results, a push notification is sent to the user's smartphone app.

[1098] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[1099] Health monitoring

[1100] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[1101] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[1102] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[1103] Location tracking

[1104] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[1105] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[1106] Users can check their pet's current location and past routes using a smartphone app.

[1107] Specific examples

[1108] 1. Examples of behavioral monitoring:

[1109] The device uses a camera to capture real-time footage of a dog playing in the yard.

[1110] The terminal compresses the video data and sends it to the server via the communication module.

[1111] The server analyzes the received data and determines that a dog is running in the yard.

[1112] The server notifies the user of the results via their smartphone app.

[1113] Users can use the app to see that their dog is playing happily.

[1114] 2. Examples of health monitoring:

[1115] The device measures the dog's temperature as 36.8 degrees.

[1116] The device stores the measurement data in its local memory and periodically transmits it to the server.

[1117] The server analyzes the received data and determines that the body temperature is within the normal range.

[1118] The server notifies the user of the results via their smartphone app.

[1119] Users can use the app to ensure their pets are in good health.

[1120] 3. Examples of location tracking:

[1121] The device uses a GPS module to obtain the location information of dogs in the park.

[1122] The device stores the acquired location data in its local memory and periodically transmits it to the server.

[1123] The server compares the received location information with map information to determine the dog's current location.

[1124] The server displays the results on the user's smartphone app.

[1125] The user uses the app to confirm that the dog's current location is in the park.

[1126] Example prompt sentence:

[1127] "Temperature sensor data: 36.5 degrees, heart rate: 80 bpm, GPS location information: latitude 35.6895, longitude 139.6917, pet activity: running"

[1128] These methods allow users to continuously monitor the safety and health of their pets while in an autonomous vehicle.

[1129] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1130] Step 1:

[1131] The device uses a camera and motion sensor to capture video and movements of your pet in real time. The input is the camera image and motion sensor data, and the output is the captured video data and movement data. Specifically, the camera takes video and the motion sensor detects movement.

[1132] Step 2:

[1133] The terminal compresses the captured video and motion data and converts it into a format that can be transmitted. The input is the captured raw data, and the output is the compressed data. A data compression algorithm (e.g., H.264) is used for this process. Specifically, the data compression algorithm efficiently compresses the video data.

[1134] Step 3:

[1135] The terminal sends the converted data to the server through the communication module. The input is the compressed data, and the output is the data sent to the server. Specifically, the data is sent to the server via Wi-Fi or Bluetooth communication.

[1136] Step 4:

[1137] The server analyzes the received data and estimates the pet's behavioral patterns. The input is compressed data received from the device, and the output is the estimated behavioral pattern. Specifically, a machine learning algorithm analyzes the data and identifies behaviors such as "running" or "sleeping."

[1138] Step 5:

[1139] The server sends a notification to the user's device based on the estimated behavioral pattern. The input is the estimated behavioral pattern, and the output is a notification to the user's device. Specifically, the notification system sends a push notification to the user's smartphone.

[1140] Step 6:

[1141] The device periodically uses the body temperature and heart rate sensors to measure the pet's health indicators. The input is the body temperature and heart rate measurement data, and the output is the health indicator data. Specifically, the sensors measure the body temperature and heart rate and obtain the data.

[1142] Step 7:

[1143] The terminal stores the measurement data in its local memory and transmits it to the server at regular intervals. The input is the measurement data, and the output is the stored data and transmitted data. Specifically, the data is stored in the local memory and periodically transmitted to the server.

[1144] Step 8:

[1145] The server analyzes the received health data and detects abnormalities. The input is the health status measurement data, and the output is the anomaly detection result. Specifically, the analysis algorithm analyzes the data and determines whether there is an abnormality in the health status.

[1146] Step 9:

[1147] The server sends an alert to the user's device based on the detected anomaly. The input is the anomaly detection result, and the output is an alert notification to the user's device. Specifically, the notification system sends an alert to the user's smartphone.

[1148] Step 10:

[1149] The device periodically obtains the pet's location information using the built-in GPS module. The input is GPS data and the output is location information. Specifically, the GPS module identifies the location information and obtains the data.

[1150] Step 11:

[1151] The terminal stores the acquired location information in its local memory and periodically transmits it to the server. The input is location information data, and the output is the stored data and transmitted data. Specifically, the data is stored in the local memory and then transmitted to the server.

[1152] Step 12:

[1153] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The input is location data, and the output is the analyzed location information. Specifically, the map analysis algorithm analyzes the location information and determines the exact location.

[1154] Step 13:

[1155] The server displays the analyzed location information on the user's smartphone app, allowing them to check their pet's current location and past movement routes. The input is the analyzed location information, and the output is the display of the location information on the user's device. Specifically, the location information is displayed on the user's app.

[1156] Example prompt sentence:

[1157] "Temperature sensor data: 36.5 degrees, heart rate: 80 bpm, GPS location information: latitude 35.6895, longitude 139.6917, pet activity: running"

[1158] 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.

[1159] The present invention provides a system that combines a system for comprehensively monitoring pet behavior, health status, and location information with an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention will be described below.

[1160] System Configuration

[1161] The system consists of the following main components:

[1162] 1. Device (terminal) for monitoring pet behavior

[1163] 2. Server that analyzes and manages data

[1164] 3. User's information device (smartphone or tablet)

[1165] 4. Emotion engine that recognizes user emotions

[1166] Terminal (device for monitoring pet behavior)

[1167] Camera: A device for capturing video of your pet.

[1168] Motion sensor: A sensor for detecting pet movement.

[1169] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate).

[1170] GPS module: A module for determining the current location of your pet.

[1171] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth.

[1172] Local memory: A storage device for temporarily storing data.

[1173] server

[1174] Data analysis function: Has the ability to analyze received data and estimate your pet's behavioral patterns and health condition.

[1175] Notification function: Has the ability to send information and alerts to user devices based on analysis results.

[1176] Database: Includes a database for recording and managing pet behavior history and health status.

[1177] Emotion engine: Has the ability to analyze the user's emotions and generate appropriate feedback based on the results.

[1178] User terminal

[1179] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[1180] Program processing

[1181] The program processing performed by each device in the system will be explained below in natural language.

[1182] Pet behavior monitoring

[1183] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[1184] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it can identify behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via push notifications to the user's smartphone app.

[1185] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[1186] Health monitoring

[1187] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[1188] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[1189] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[1190] Location tracking

[1191] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[1192] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[1193] Users can check their pet's current location and past routes using a smartphone app.

[1194] Adding an Emotion Engine

[1195] The server analyzes the user's emotions using an emotion engine, which analyzes the user's emotional state in real time based on data collected from the user's device (e.g., user input information, voice, facial expressions, etc.).

[1196] If the user is feeling stressed, the emotion engine analyzes the pet's behavioral data and generates feedback to encourage therapeutic behavior, such as sending a notification to the user's smartphone to "take some time to relax with your pet."

[1197] If the user is relaxed, the emotion engine generates feedback to encourage positive behavior in the pet, such as sending a notification to the user's smartphone saying, "Praise your pet for being good."

[1198] Specific examples

[1199] Examples of behavioral monitoring

[1200] 1. The device uses its camera to capture video of a dog playing in the yard.

[1201] 2. The terminal compresses the video data and sends it to the server via the communication module.

[1202] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[1203] 4. The server notifies the user of the results via their smartphone app.

[1204] 5. The user uses the app to confirm that the dog is playing happily.

[1205] Health monitoring examples

[1206] 1. The device measures the dog's temperature as 36.8 degrees.

[1207] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[1208] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[1209] 4. The server notifies the user of the results via their smartphone app.

[1210] 5. The user uses the app to ensure their pet is in good health.

[1211] Examples of location tracking

[1212] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[1213] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[1214] 3. The server compares the received location information with map information to determine the dog's current location.

[1215] 4. The server displays the results on the user's smartphone app.

[1216] 5. The user uses the app to confirm that the dog is currently at the park.

[1217] Examples of emotion engines

[1218] 1. The server receives voice data from the user's smartphone.

[1219] 2. The emotion engine analyzes the voice data and determines that the user is feeling stressed.

[1220] 3. The server generates a notification to encourage the pet to engage in therapeutic behavior and sends it to the user's smartphone.

[1221] 4. The user uses the app to view therapeutic behaviors and relax with their pet.

[1222] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and also provides appropriate feedback according to the user's emotional state.

[1223] The processing flow will be explained below.

[1224] Behavioral monitoring

[1225] Step 1: Data Capture

[1226] The device uses a camera and motion sensors to capture video and movements of your pet in real time.

[1227] The device stores the captured video data and motion data in temporary memory.

[1228] Step 2: Data processing

[1229] The terminal compresses the captured data and converts it into a format that can be communicated.

[1230] The terminal organizes the processed data as batch data.

[1231] Step 3: Sending data

[1232] The device sends the processed data to the server via Wi-Fi or Bluetooth.

[1233] The terminal confirms the success of the transmission and receives an acknowledgement.

[1234] Step 4: Analyze the data

[1235] The server analyzes the received data and applies behavior recognition algorithms to detect the pet's behavior patterns.

[1236] The server records information such as "pet is running" or "pet is sleeping" in the behavior log.

[1237] Step 5: Sending notifications

[1238] The server sends analysis results such as "your pet is running" or "your pet is sleeping" to the user's smartphone app as a push notification.

[1239] Users can check their pet's current behavior using a smartphone app.

[1240] Health monitoring

[1241] Step 1: Data collection

[1242] The device uses sensors to measure your pet's body temperature and heart rate every 10 minutes.

[1243] The terminal temporarily stores the measurement data in a local memory.

[1244] Step 2: Send data

[1245] The terminal transmits the measurement data to the server.

[1246] The terminal adjusts its periodic data transmission schedule to optimize power consumption.

[1247] Step 3: Data analysis

[1248] The server analyzes the received data in real time and evaluates whether it is within the normal range.

[1249] If the server detects an anomaly, it generates an alert to the user.

[1250] Step 4: Sending notifications

[1251] The server sends the results of abnormality detection and regular health status reports to the user's smartphone via push notifications.

[1252] Users can check notifications about their pet's health status on their smartphone and take necessary measures.

[1253] Location Tracking

[1254] Step 1: Obtaining location information

[1255] The device periodically obtains your pet's location information using the built-in GPS module.

[1256] The terminal stores the acquired location information in a local memory.

[1257] Step 2: Send data

[1258] The terminal transmits the location information data to the server.

[1259] The terminal confirms the success of the transmission and receives an acknowledgement.

[1260] Step 3: Data analysis

[1261] The server compares the location data with map information to determine the pet's current location.

[1262] The server records the location information as the pet's movement history.

[1263] Step 4: View location information

[1264] The server sends map data to the user's smartphone app to display the pet's current location.

[1265] Users can check their pet's current location and past routes using a smartphone app.

[1266] Adding an Emotion Engine

[1267] Step 1: Collecting emotion data

[1268] The user's terminal collects the user's voice, facial expressions, and input information.

[1269] The terminal transmits the collected emotion data to the server.

[1270] Step 2: Analyze the emotion data

[1271] The server uses an emotion engine to analyze the received emotion data and estimate the user's emotional state.

[1272] The server classifies the emotional state as "stressed" or "relaxed," etc.

[1273] Step 3: Generate feedback

[1274] The emotion engine analyzes pet behavior data and generates notifications to prompt therapeutic behaviors if the user is experiencing stress.

[1275] The emotion engine generates notifications to encourage positive behavior for pets when the user is relaxed.

[1276] Step 4: Submit your feedback

[1277] The server transmits the generated feedback to the user's smartphone.

[1278] Users receive notifications on their smartphone app and spend appropriate time with their pets.

[1279] Specific examples

[1280] Examples of behavioral monitoring

[1281] Step 1:

[1282] The device uses a camera to capture footage of a dog playing in the yard.

[1283] Step 2:

[1284] The terminal compresses the video data and transmits it to the server via the communication module.

[1285] Step 3:

[1286] The server analyzes the received data and determines that "a dog is running in the yard."

[1287] Step 4:

[1288] The server notifies the user of the results via their smartphone app.

[1289] Step 5:

[1290] The user uses the app to confirm that the dog is playing happily.

[1291] Health monitoring examples

[1292] Step 1:

[1293] The device measures the dog's temperature as 36.8 degrees.

[1294] Step 2:

[1295] The terminal stores the measurement data in a local memory and periodically transmits it to a server.

[1296] Step 3:

[1297] The server analyzes the received data and determines that the body temperature is within the normal range.

[1298] Step 4:

[1299] The server notifies the user of the results via their smartphone app.

[1300] Step 5:

[1301] Users use the app to ensure their pets are in good health.

[1302] Examples of location tracking

[1303] Step 1:

[1304] The device uses a GPS module to obtain the location information of dogs in the park.

[1305] Step 2:

[1306] The terminal stores the acquired location data in a local memory and periodically transmits it to a server.

[1307] Step 3:

[1308] The server compares the received location information with map information to determine the dog's current location.

[1309] Step 4:

[1310] The server displays the results on the user's smartphone app.

[1311] Step 5:

[1312] The user uses the app to confirm that the dog's current location is at the park.

[1313] Examples of emotion engines

[1314] Step 1:

[1315] The user's terminal collects the user's voice data.

[1316] Step 2:

[1317] The terminal transmits the collected voice data to the server.

[1318] Step 3:

[1319] The emotion engine analyzes the voice data and determines that the user is feeling stressed.

[1320] Step 4:

[1321] The server generates notifications to prompt therapeutic behavior and sends them to the user's smartphone.

[1322] Step 5:

[1323] Users use the app to view therapeutic behaviors and relax with their pet.

[1324] Example 2

[1325] 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."

[1326] Comprehensive and real-time monitoring of pet behavior, health, and location information is difficult without error. Furthermore, there are no systems that provide appropriate feedback taking into account the user's emotional state. This makes it challenging to properly monitor pet status and provide appropriate responses in conjunction with the user's emotional state.

[1327] 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.

[1328] In this invention, the server includes: means for capturing the movements of the pet in real time using a camera and a motion sensor; means for compressing the captured data and converting it into a communicable format; means for transmitting the converted data to the server via a communication line; means for analyzing the data received by the server and estimating the behavioral pattern of the pet; means for sending a notification to the user's terminal based on the estimated behavioral pattern; means for measuring the pet's body temperature and heart rate using a sensor; means for periodically saving the measured data in a local memory; means for transmitting the saved data to the server; means for analyzing the data received by the server and detecting anomalies; means for sending an alert to the user's terminal based on the detected anomaly; means for periodically acquiring location information of the pet using a GPS module; means for saving the acquired location information in a local memory; means for transmitting the saved location information to the server; means for analyzing the location information received by the server based on map information; This makes it possible to comprehensively monitor a pet's behavior, health, and location, while also providing appropriate feedback based on the user's emotional state.

[1329] A "camera" is a device for capturing video data.

[1330] A "motion sensor" is a sensor for detecting the movement of an object.

[1331] "Pet" refers to an animal kept in the home.

[1332] "Real-time" means processing data immediately with minimal delay.

[1333] "Data compression" is the process of transforming data using a certain algorithm to reduce the amount of data.

[1334] A "communicable format" is a format used to transmit data, designed to facilitate data exchange.

[1335] A "communications line" is a network infrastructure for transmitting data to a remote location.

[1336] A "server" is a computer system that provides services over a network.

[1337] "Analysis" is a method for processing data and understanding its meaning and structure.

[1338] "Behavioral patterns" are information that indicates a series of behaviors and habits of a pet.

[1339] A "notification" is a message or alert that conveys information to the user.

[1340] A "sensor" is a device that measures physical quantities and outputs them as data.

[1341] "Body temperature" is an indicator of the internal temperature of a living organism.

[1342] "Heart rate" is an index that indicates the number of heartbeats per unit time.

[1343] "Local memory" is a storage device for temporarily storing data.

[1344] "Abnormal" refers to a state or value that is outside the normal range.

[1345] An "alert" is a warning notification that notifies the user of an abnormal situation.

[1346] A "GPS module" is a device for acquiring location information.

[1347] "Location information" is data that indicates the geographical location of an object.

[1348] "Map information" is data for visually displaying geographical locations.

[1349] An "emotion engine" is a software system for analyzing a user's emotional state and generating feedback based on that.

[1350] "Emotion" is information that indicates the user's psychological state or mood.

[1351] "Feedback" is advice or feedback provided to the user.

[1352] This invention is a system that comprehensively monitors pet behavior, health status, and location information, and provides appropriate feedback according to the user's emotional state. This system consists of the following main components: a device (terminal) that monitors pet behavior, a server that analyzes and manages the data, the user's information terminal (smartphone or tablet), and an emotion engine that recognizes the user's emotions.

[1353] System Configuration

[1354] Terminal (device for monitoring pet behavior)

[1355] Camera: A device for taking pictures of pets, for example capturing footage of a dog playing in the yard.

[1356] Motion sensor: A sensor that detects the movement of your pet, such as when your pet is running or sleeping.

[1357] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate). Detects whether the body temperature is within the normal range.

[1358] GPS module: A module for determining the current location of pets. Obtains location information of pets in the park.

[1359] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth. Compressed data is sent to the server.

[1360] Local memory: A storage device for temporarily storing data. It temporarily stores measurement data and location information.

[1361] server

[1362] Data analysis function: The system has the ability to analyze received data and estimate the behavioral patterns and health status of pets. For example, it can analyze received video data and determine that "a dog is running in the yard."

[1363] Notification function: The system has the ability to send information and alerts to the user's device based on the analysis results, informing the user of any abnormalities in behavioral patterns or health conditions.

[1364] Database: Includes a database for recording and managing pet behavior history and health status. Stores past behavioral data and health data.

[1365] Emotion engine: This engine analyzes the user's emotions and generates appropriate feedback based on the results. For example, it can determine from voice data that the user is feeling stressed.

[1366] User terminal

[1367] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[1368] Specific examples

[1369] The operation of the system will be explained using a specific example.

[1370] Examples of behavioral monitoring

[1371] 1. The device uses its camera to capture video of a dog playing in the yard.

[1372] 2. The terminal compresses the video data and sends it to the server via the communication module.

[1373] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[1374] 4. The server notifies the user of the results via their smartphone app.

[1375] 5. The user uses the app to confirm that the dog is playing happily.

[1376] Health monitoring examples

[1377] 1. The device measures the dog's temperature as 36.8 degrees.

[1378] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[1379] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[1380] 4. The server notifies the user of the results via their smartphone app.

[1381] 5. The user uses the app to ensure their pet is in good health.

[1382] Examples of location tracking

[1383] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[1384] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[1385] 3. The server compares the received location information with map information to determine the dog's current location.

[1386] 4. The server displays the results on the user's smartphone app.

[1387] 5. The user uses the app to confirm that the dog is currently at the park.

[1388] Examples of emotion engines

[1389] 1. The server receives voice data from the user's smartphone.

[1390] 2. The emotion engine analyzes the voice data and determines that the user is feeling stressed.

[1391] 3. The server generates a notification to encourage the pet to engage in therapeutic behavior and sends it to the user's smartphone.

[1392] 4. The user uses the app to view therapeutic behaviors and relax with their pet.

[1393] Prompt Sentence Examples

[1394] "Please explain how the program checks to see if a dog's temperature is normal."

[1395] "Describe how your system works to track your pet's location."

[1396] "Please explain in detail how to generate notifications based on user emotions."

[1397] This makes it possible to comprehensively monitor a pet's behavior, health, and location, while also providing appropriate feedback based on the user's emotional state.

[1398] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1399] Program processing flow

[1400] Pet behavior monitoring

[1401] Step 1:

[1402] The device activates the camera to capture the pet's video in real time, and simultaneously activates the motion sensor to detect the pet's movements. The input is the pet's movements and video, and the output is the captured video data and movement data.

[1403] Step 2:

[1404] The device compresses the captured video data and movement data and converts them into a format that can be communicated. Specifically, the video data is compressed into JPEG format, and the movement data is converted into JSON format. The input is the captured data, and the output is the compressed data.

[1405] Step 3:

[1406] The device sends the compressed data to the server via Wi-Fi or Bluetooth. The input is the compressed data, and the output is the data sent to the server.

[1407] Step 4:

[1408] The server analyzes the received data and estimates the pet's behavioral patterns in real time. The video data is processed by image analysis software, and the movement data is processed by motion analysis algorithms. The input is the received data, and the output is the estimated behavioral patterns.

[1409] Step 5:

[1410] The server identifies the pet's behavior based on the analysis results and sends a push notification of that information to the user's smartphone app. The input is the analyzed behavior pattern, and the output is notification information.

[1411] Step 6:

[1412] The user receives a notification on the smartphone app and checks the current behavior of their pet. The input is the notification information, and the output is the user's confirmation action.

[1413] Health monitoring

[1414] Step 1:

[1415] The device activates the temperature and heart rate sensors to measure the pet's temperature and heart rate. The measurement results are stored in the internal memory. The input is the sensor data, and the output is the measurement results.

[1416] Step 2:

[1417] The device temporarily stores the measurement data in its local memory and sends it to the server at regular intervals. The data is converted to CSV format and sent via Wi-Fi. The input is the measurement data, and the output is the data sent to the server.

[1418] Step 3:

[1419] The server analyzes the received health data in real time to detect abnormalities. It uses an anomaly detection algorithm to generate an alert if the body temperature exceeds the normal range. The input is the received health data, and the output is the presence or absence of abnormalities.

[1420] Step 4:

[1421] If the server detects an anomaly, it generates an alert based on that information and sends it to the user's smartphone app. The input is the anomaly detection result, and the output is the alert information.

[1422] Step 5:

[1423] Users receive anomaly alerts via a smartphone app and take necessary measures. The input is the alert information, and the output is the corrective action.

[1424] Location tracking

[1425] Step 1:

[1426] The device uses the built-in GPS module to acquire pet location information. The location data is stored in the internal memory. The input is GPS data, and the output is location data.

[1427] Step 2:

[1428] The device stores the acquired location data in its local memory and periodically sends it to the server. The data is converted to NMEA format and sent via Wi-Fi. The input is the location data, and the output is the data sent to the server.

[1429] Step 3:

[1430] The server analyzes the received location information and locates the pet's current location by comparing it with map information. It uses a location analysis algorithm, whose input is the received location information and whose output is the determined current location.

[1431] Step 4:

[1432] The server sends location information based on the analysis results to the user's smartphone app. The input is the identified current location, and the output is a location notification.

[1433] Step 5:

[1434] Users can check real-time location information on a smartphone app and check their pet's current location and past movement routes. The input is location information notification, and the output is the user's confirmation behavior.

[1435] Adding an Emotion Engine

[1436] Step 1:

[1437] The server receives voice data and facial expression data from the user's smartphone. This data is processed in real time. The input is the user's emotional data, and the output is the received data.

[1438] Step 2:

[1439] The emotion engine analyzes the collected data and determines the user's emotion in real time. It uses voice recognition software to analyze the emotional state. The input is the received emotion data, and the output is the emotion analysis result.

[1440] Step 3:

[1441] The server generates a notification to encourage therapeutic behavior for the pet based on the analysis results of the emotion engine and sends it to the user's smartphone. The input is the emotion analysis result, and the output is the therapeutic behavior notification.

[1442] Step 4:

[1443] The emotion engine generates notifications to encourage positive behaviors for pets when the user is relaxed. The input is the emotion analysis result, and the output is the positive behavior notification.

[1444] Step 5:

[1445] The user checks the notification on the smartphone app and takes time to relax with their pet. The input is the notification information, and the output is the user's behavior.

[1446] This makes it possible to comprehensively monitor a pet's behavior, health, and location, while also providing appropriate feedback based on the user's emotional state.

[1447] (Application example 2)

[1448] 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."

[1449] Conventional pet monitoring systems focus on monitoring pet behavior, health, and location information, but none take into account the user's emotional state. Furthermore, in autonomous vehicles, there is a lack of technology that provides appropriate driving assistance based on pet safety management and the user's emotions. The present invention aims to solve these problems.

[1450] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for determining the user's emotional state using an emotion engine that analyzes the user's emotional state, means for generating corresponding feedback based on the user's emotional state and notifying the user terminal of the feedback, and means for providing driving assistance that takes the user's emotional state into consideration using the emotion engine that analyzes the user's emotional state. This makes it possible to provide driving assistance that corresponds to the user's emotional state while managing the safety of pets in an autonomous vehicle.

[1451] A "device for monitoring pet behavior" is a device that uses a camera or motion sensor to monitor pet movements in real time and transmits the data to a server.

[1452] "Capture" is the act of collecting motion and video using cameras and sensors.

[1453] "Means for converting into a communicable format" refers to a device or process that compresses the captured data and converts it into a form that can be sent to a server.

[1454] A "server" is a central computer system that analyzes received data and sends notifications to user terminals based on the results of various analyses.

[1455] The "means for estimating the behavioral patterns of a pet" refers to an algorithm or program that analyzes the data received on the server and determines the specific behavior of the pet.

[1456] "Means for sending notifications to user terminals" refers to a communications system for sending information and alerts from a server to a user's smartphone or tablet.

[1457] An "emotion engine" is a software engine that analyzes the user's voice, facial expressions, input information, etc. to determine the user's emotional state.

[1458] The "means for determining the emotional state of a user" refers to a process and system that uses an emotion engine to analyze and determine the emotion of a user.

[1459] The "means for generating corresponding feedback and notifying the user terminal" is a mechanism for generating appropriate feedback based on the emotional state of the user determined by the emotion engine and transmitting that feedback to the user terminal.

[1460] The "device for monitoring the health condition of a pet" is a device that measures the health indicators of a pet using body temperature and heart rate sensors and transmits the results to a server.

[1461] The "means for detecting anomalies" is a system that analyzes the health data received on the server and identifies data points that are out of the ordinary.

[1462] A "device for tracking pet location information" is a device that periodically acquires pet location information using a GPS module and transmits it to a server.

[1463] "Driving Assist" is a system that provides driving assistance based on the user's emotional state and notifies and suggests the driver via a smartphone or in-car display.

[1464] The present invention relates to a system that comprehensively monitors the behavior, health status, and location information of a pet, and further provides appropriate feedback according to the emotional state of the user. Specific embodiments for carrying out the present invention will be described in detail below.

[1465] System Configuration

[1466] The system consists of the following main components:

[1467] 1. Device (terminal) for monitoring pet behavior

[1468] 2. Server that analyzes and manages data

[1469] 3. User's information device (smartphone or tablet)

[1470] 4. Emotion engine that recognizes user emotions

[1471] Terminal

[1472] The device has the following features to monitor your pet's behavior, health and location:

[1473] Camera: Capture footage of your pet.

[1474] Motion sensor: Detects pet movements in real time.

[1475] Body temperature and heart rate sensors: measure your pet's health indicators.

[1476] GPS module: Identify your pet's location.

[1477] Communication module: Sends data to the server using Wi-Fi or Bluetooth.

[1478] Local memory: temporarily stores data.

[1479] server

[1480] The server has the following features:

[1481] Data analysis function: Analyzes received data and estimates your pet's behavioral patterns and health condition.

[1482] Notification function: Sends information and alerts to user devices based on analysis results.

[1483] Database: Records and manages pet behavior history and health status.

[1484] Emotion engine: Analyzes the user's emotions and generates appropriate feedback based on the results.

[1485] User terminal

[1486] The user terminal has the following features:

[1487] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[1488] Program processing

[1489] The program processing performed by each device will be explained below.

[1490] Pet behavior monitoring

[1491] The device uses a camera and motion sensors to capture video and movements of the pet in real time. The captured video and motion data is compressed and converted into a format that can be communicated. The converted data is then sent to a server via a communications module. The server analyzes the received data and estimates the pet's behavioral patterns. For example, it identifies behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via a push notification to the user's smartphone app. The user can then check their pet's current behavior on the smartphone app.

[1492] Health monitoring

[1493] The device periodically measures the pet's health indicators using the body temperature and heart rate sensors. The measurement data is stored in local memory and sent to the server at regular intervals. The server analyzes the received health data in real time and detects abnormalities. For example, if the body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app. The user receives notifications of the pet's health status via the smartphone app and can take necessary measures.

[1494] Location tracking

[1495] The device periodically obtains the pet's location information using the built-in GPS module. The obtained location information is stored in local memory and periodically sent to the server. The server analyzes the received location information and compares it with map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app. The user can then check the pet's current location and past movement routes on the smartphone app.

[1496] Adding an Emotion Engine

[1497] The server uses an emotion engine to analyze the user's emotions. The emotion engine analyzes the user's emotional state in real time based on data collected from the user's device (e.g., user input information, voice, facial expressions, etc.). If the user is feeling stressed, the emotion engine analyzes the pet's behavioral data and generates therapeutic feedback. For example, it sends a notification to the user's smartphone, such as "Take some time to relax with your pet." If the user is relaxed, the emotion engine generates feedback to encourage the pet's positive behavior. For example, it sends a notification to the user's smartphone, such as "Praise your pet for being well-behaved."

[1498] Examples of specific examples and prompts

[1499] Examples of behavioral monitoring

[1500] The device uses a camera to capture video of a dog playing in the yard. The device compresses the video data and sends it to the server via the communication module. The server analyzes the received data and determines that "the dog is running in the yard." The server notifies the user of the result via a smartphone app. The user then uses the app to confirm that "the dog is playing happily."

[1501] Health monitoring examples

[1502] The device measures the dog's temperature as 36.8°C. The device stores the measurement data in its local memory and periodically sends it to the server. The server analyzes the received data and determines that the body temperature is within the normal range. The server then notifies the user of the result via a smartphone app. The user can then use the app to confirm that their pet's health is normal.

[1503] Examples of location tracking

[1504] The device uses a GPS module to obtain the location information of the dog in the park. The device stores the obtained location data in its local memory and periodically sends it to the server. The server compares the received location information with map information to determine the dog's current location. The server displays the result on the user's smartphone app. The user then uses the app to confirm that the dog's current location is in the park.

[1505] Examples of emotion engines

[1506] The server receives voice data from the user's smartphone. The emotion engine analyzes the voice data and determines that the user is feeling stressed. The server generates a notification to prompt the pet to engage in therapeutic behavior and sends it to the user's smartphone. The user then uses the app to confirm the therapeutic behavior and relax with their pet.

[1507] Prompt Sentence Examples

[1508] Analyze the given audio data and generate feedback including playing relaxing music and notifying the pet's status if the user is stressed.

[1509] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and also provides appropriate feedback according to the user's emotional state.

[1510] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1511] Step 1:

[1512] The device uses a camera to capture images of the pet in real time. The motion sensor also detects the pet's movements at the same time. The input is the pet's video data and motion data, which are obtained by capturing these. The output is the video data and motion data. These data are temporarily stored in local memory.

[1513] Step 2:

[1514] The terminal compresses the captured data and converts it into a format that can be communicated. The input is the video data and motion data obtained in step 1. The data is compressed using a compression algorithm and format conversion is performed. The output is the compressed and converted data. This data is ready to be sent to the server via the communication module.

[1515] Step 3:

[1516] The terminal sends the converted data to the server through the communication module. The input is the compressed and converted data obtained in step 2. The data is sent to the server using a transmission protocol (e.g., Wi-Fi or Bluetooth). The output is the data that arrives at the server.

[1517] Step 4:

[1518] The server analyzes the received data and infers the pet's behavioral patterns. The input is the data that arrived at the server in step 3. It uses a machine learning algorithm (e.g., a generative AI model) to analyze the data and infer what the pet is doing. The output is information about the pet's behavioral patterns.

[1519] Step 5:

[1520] The server sends notifications to the user's device based on the estimated behavioral patterns. The input is the information about the behavioral patterns obtained in step 4. An appropriate notification is generated using a notification generation algorithm. The output is the notification sent to the user's device.

[1521] Step 6:

[1522] The device periodically measures the pet's health indicators using the body temperature and heart rate sensors. The input is the pet's body temperature and heart rate data. These data are obtained by measuring them. The output is the measurement data. This data is stored in the local memory.

[1523] Step 7:

[1524] The terminal sends the measurement data to the server using the communication module. The input is the measurement data obtained in step 6. The data is sent to the server using a transmission protocol. The output is the data that arrives at the server.

[1525] Step 8:

[1526] The server analyzes the received health data in real time and detects abnormalities. The input is the health data that arrived at the server in step 7. Anomalies are detected using data analysis algorithms. The output is alert information regarding the presence or absence of abnormalities.

[1527] Step 9:

[1528] The server sends an alert to the user terminal based on the detected anomaly. The input is the alert information obtained in step 8. The alert is generated using a notification generation algorithm. The output is the alert sent to the user terminal.

[1529] Step 10:

[1530] The device periodically obtains the pet's location information using the built-in GPS module. The input is the pet's current location information. This is obtained by obtaining it. The output is the location data. This data is stored in the local memory.

[1531] Step 11:

[1532] The terminal transmits the acquired location information to the server using the communication module. The input is the location data obtained in step 10. The data is transmitted to the server using a transmission protocol. The output is the data that arrives at the server.

[1533] Step 12:

[1534] The server compares the received location information with map information to determine the current location of the pet. The input is the location information received by the server in step 11. The server compares this with map information to determine the current location of the pet. The output is information about the current location of the pet.

[1535] Step 13:

[1536] The server notifies the user's smartphone app of the analysis results. The input is the current location information obtained in step 12. A notification is generated using the notification generation algorithm. The output is a notification sent to the user device.

[1537] Step 14:

[1538] The server receives voice data from the user's smartphone. The input is the user's voice data. This is obtained by receiving it. The output is the voice data that arrives at the server.

[1539] Step 15:

[1540] The emotion engine analyzes the speech data to determine the user's emotional state. The input is the speech data received by the server in step 14. The generative AI model is used to analyze the speech data and infer the user's emotional state. The output is information about the user's emotional state.

[1541] Step 16:

[1542] The server generates corresponding feedback based on the user's emotional state and notifies the user terminal. The input is the emotional state information obtained in step 15. The server generates the feedback using a notification generation algorithm. The output is the feedback sent to the user terminal.

[1543] Step 17:

[1544] The server provides driving assistance that takes into account the user's emotional state. The input is the emotional state information obtained in step 15. A driving assistance algorithm is used to generate appropriate driving assistance suggestions. The output is driving assistance information displayed on the in-vehicle display.

[1545] 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.

[1546] 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.

[1547] 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.

[1548] [Third embodiment]

[1549] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1550] 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.

[1551] 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).

[1552] 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.

[1553] 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.

[1554] 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).

[1555] 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.

[1556] 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.

[1557] 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.

[1558] 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.

[1559] 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.

[1560] 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."

[1561] The present invention provides a system for comprehensively monitoring pet behavior, health status, and location information. Specific embodiments of the present invention will be described below.

[1562] System Configuration

[1563] The system consists of the following main components:

[1564] 1. Device (terminal) for monitoring pet behavior

[1565] 2. Server that analyzes and manages data

[1566] 3. User's information device (smartphone or tablet)

[1567] Terminal (device for monitoring pet behavior)

[1568] Camera: A device for capturing video of your pet.

[1569] Motion sensor: A sensor for detecting pet movement.

[1570] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate).

[1571] GPS module: A module for determining the current location of your pet.

[1572] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth.

[1573] Local memory: A storage device for temporarily storing data.

[1574] server

[1575] Data analysis function: Has the ability to analyze received data and estimate your pet's behavioral patterns and health condition.

[1576] Notification function: Has the ability to send information and alerts to user devices based on analysis results.

[1577] Database: Includes a database for recording and managing pet behavior history and health status.

[1578] User terminal

[1579] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[1580] Program processing

[1581] The program processing performed by each device in the system will be explained below in natural language.

[1582] Pet behavior monitoring

[1583] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[1584] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it can identify behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via push notifications to the user's smartphone app.

[1585] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[1586] Health monitoring

[1587] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[1588] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[1589] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[1590] Location tracking

[1591] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[1592] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[1593] Users can check their pet's current location and past routes using a smartphone app.

[1594] Specific examples

[1595] Examples of behavioral monitoring

[1596] 1. The device uses its camera to capture video of a dog playing in the yard.

[1597] 2. The terminal compresses the video data and sends it to the server via the communication module.

[1598] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[1599] 4. The server notifies the user of the results via their smartphone app.

[1600] 5. The user uses the app to confirm that the dog is playing happily.

[1601] Health monitoring examples

[1602] 1. The device measures the dog's temperature as 36.8 degrees.

[1603] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[1604] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[1605] 4. The server notifies the user of the results via their smartphone app.

[1606] 5. The user uses the app to ensure their pet is in good health.

[1607] Examples of location tracking

[1608] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[1609] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[1610] 3. The server compares the received location information with map information to determine the dog's current location.

[1611] 4. The server displays the results on the user's smartphone app.

[1612] 5. The user uses the app to confirm that the dog is currently at the park.

[1613] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and provides users with the information they need.

[1614] The processing flow will be explained below.

[1615] Pet behavior monitoring

[1616] Step 1: Data Capture

[1617] The device uses a camera and motion sensors to capture footage and movements of your pet in real time.

[1618] The device stores the captured video data and motion data in temporary memory.

[1619] Step 2: Data processing

[1620] The terminal compresses the captured data and converts it into a suitable format to save communication bandwidth.

[1621] The terminal organizes the processed data as batch data.

[1622] Step 3: Sending data

[1623] The device sends the processed data to the server via Wi-Fi or Bluetooth.

[1624] The terminal confirms the success of the transmission and receives an acknowledgement.

[1625] Step 4: Analyze the data

[1626] The server analyzes the received data and applies behavior recognition algorithms to detect the pet's behavior patterns.

[1627] The server records information such as "pet is running" or "pet is sleeping" in the behavior log.

[1628] Step 5: Sending notifications

[1629] The server sends analysis results such as "your pet is running" or "your pet is sleeping" to the user's smartphone app as a push notification.

[1630] Users can check their pet's current behavior using a smartphone app.

[1631] Health monitoring

[1632] Step 1: Data collection

[1633] The device uses sensors to measure your pet's body temperature and heart rate every 10 minutes.

[1634] The terminal temporarily stores the measurement data in a local memory.

[1635] Step 2: Send data

[1636] The terminal transmits the measurement data to the server.

[1637] The terminal adjusts its periodic data transmission schedule to optimize power consumption.

[1638] Step 3: Data analysis

[1639] The server analyzes the received data in real time and evaluates whether it is within the normal range.

[1640] If the server detects an anomaly, it generates an alert to the user.

[1641] Step 4: Sending notifications

[1642] The server sends the results of abnormality detection and regular health status reports to the user's smartphone via push notifications.

[1643] Users can check notifications about their pet's health status on their smartphone and take necessary measures.

[1644] Location tracking

[1645] Step 1: Obtaining location information

[1646] The device periodically obtains the pet's location information using the built-in GPS module.

[1647] The terminal stores the acquired location information in a local memory.

[1648] Step 2: Send data

[1649] The terminal transmits the location information data to the server.

[1650] The terminal confirms the success of the transmission and receives an acknowledgement.

[1651] Step 3: Data analysis

[1652] The server compares the location data with map information to determine the pet's current location.

[1653] The server records the location information as the pet's movement history.

[1654] Step 4: View location information

[1655] The server sends map data to the user's smartphone app to display the pet's current location.

[1656] Users can check their pet's current location and past routes using a smartphone app.

[1657] Example 1

[1658] 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."

[1659] There is a demand for a system that can comprehensively monitor pet behavior, health status, and location information, and allow users to obtain the information they need in real time. Conventional systems often collect and manage this information separately, making it difficult for users to use and providing information in a centralized manner.

[1660] 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.

[1661] In this invention, the server includes means for capturing the movements of the pet in real time using a camera and a motion sensor, means for compressing the captured data and converting it into a communicable format, means for transmitting the converted data to the server via a communication line, means for analyzing the data received by the server using a generative model and estimating the behavioral patterns of the pet, and means for transmitting notifications to the user's terminal based on the estimated behavioral patterns. This allows the user to centrally manage the behavior, health condition, and location information of the pet and obtain this information in real time.

[1662] A "camera" is a device for capturing images of pets.

[1663] A "motion sensor" is a sensor that detects the movement of a pet.

[1664] "Compression" is a process for reducing the size of captured data.

[1665] "Communicable format" refers to the process of converting data into a format that can be sent and received.

[1666] A "communication line" is a network for transmitting data.

[1667] A "server" is a central computer that analyzes and manages data.

[1668] A "generative model" is an algorithm for analyzing data and recognizing specific patterns.

[1669] A "behavioral pattern" is a series of movements that characterize a pet's behavior.

[1670] "Notification" is a message to inform the user of the analysis results.

[1671] A "terminal" is a device through which a user receives information.

[1672] "Health indicators" are data on body temperature and heart rate that indicate the pet's health condition.

[1673] "Local memory" is a storage device that temporarily stores data within a device.

[1674] An "abnormal alert" is a warning message that occurs when data outside the normal range is detected.

[1675] A "GPS module" is a device used to determine a pet's current location.

[1676] "Location information" is data that indicates the current location of the pet.

[1677] "Map information" is information for visually displaying location data.

[1678] "Tracking" is the act of continuously monitoring a pet's location.

[1679] The present invention is a system for comprehensively monitoring the behavior, health status, and location information of pets. Specific embodiments for carrying out the present invention will be described below.

[1680] System Configuration

[1681] The system consists of the following main components:

[1682] 1. A device that monitors your pet's behavior

[1683] 2. Server that analyzes and manages data

[1684] 3. User's information device (smartphone or tablet)

[1685] Terminal (device for monitoring pet behavior)

[1686] Camera: A device for recording video of your pet. The camera captures video in high resolution at 30 frames per second.

[1687] Motion Sensor: This is a sensor that detects pet movements. The sensor captures movements in real time.

[1688] Body Temperature and Heart Rate Sensor: A sensor that measures your pet's body temperature and heart rate. The measurement results are stored in local memory.

[1689] GPS module: This module identifies the current location of your pet. Location information is acquired periodically.

[1690] Communication module: A module that transmits data to a server using Wi-Fi or Bluetooth. The communication module supports IEEE 802.11ac and Bluetooth Low Energy (BLE).

[1691] Local memory: A storage device that temporarily stores data.

[1692] server

[1693] Data analysis function: The system analyzes the received data and estimates the pet's behavioral patterns and health condition. TensorFlow models and generative models are used for the analysis.

[1694] Notification function: Has the ability to send information and alerts to user devices based on analysis results. Uses Firebase Cloud Messaging (FCM).

[1695] Database: Includes a database for recording and managing pet behavior history and health status.

[1696] User terminal

[1697] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[1698] Program processing

[1699] The program processing performed by each device in the system will be explained below in natural language.

[1700] Pet behavior monitoring

[1701] The device uses a camera and motion sensors to capture video and movement data in real time, then compresses it using the H.264 codec and converts it into a format suitable for communication, before transmitting it to a server via Wi-Fi.

[1702] The server analyzes the received data using a TensorFlow model to estimate the pet's behavioral patterns. For example, it identifies behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are then pushed to the user's device in real time.

[1703] Users can check their pet's current activities through a smartphone app, and the app's dashboard displays messages such as "Your pet is playing happily."

[1704] Health monitoring

[1705] The device periodically measures your pet's health using built-in temperature and heart rate sensors, and the measurement data is stored in local memory and transmitted to a server at regular intervals using Bluetooth Low Energy (BLE).

[1706] The server analyzes the received health data in real time and detects abnormalities. For example, if the body temperature exceeds the normal range, it generates a "high body temperature alert." The generated alert is sent to the user's device.

[1707] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures, such as displaying messages like "Temperature is within normal range."

[1708] Location tracking

[1709] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in local memory and sent to the server via Wi-Fi.

[1710] The server compares the received location information with map data to determine the pet's current location, and uses the Geocoding API to convert the location coordinates into a specific address or place name.

[1711] Users can check their pet's current location and past routes on a smartphone app, which displays their pet's location in real time as it moves around the park.

[1712] Specific examples

[1713] Examples of behavioral monitoring

[1714] 1. The device uses its camera to capture video of a pet playing in the yard.

[1715] 2. The device compresses the video data using H.264 and sends it to the server via Wi-Fi.

[1716] 3. The server analyzes the received data using a TensorFlow model and determines that a pet is running in the yard.

[1717] 4. The server notifies the user's smartphone app of the results using Firebase Cloud Messaging.

[1718] 5. The user uses the app to confirm that their pet is playing happily.

[1719] Health monitoring examples

[1720] 1. The device measures the pet's temperature as 36.8 degrees.

[1721] 2. The device stores the measurement data in its local memory and periodically transmits it to the server using Bluetooth Low Energy.

[1722] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[1723] 4. The server notifies the user of the analysis results via their smartphone app.

[1724] 5. The user uses the app to ensure their pet is in good health.

[1725] Examples of location tracking

[1726] 1. The device uses the GPS module to obtain the location information of pets in the park.

[1727] 2. The device stores the location data in its local memory and transmits it to the server via Wi-Fi.

[1728] 3. The server analyzes the received location information using the Geocoding API to determine the pet's current location.

[1729] 4. The server displays the analysis results on the user's smartphone app.

[1730] 5. The user uses the app to confirm that their pet is currently at the park.

[1731] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and provides users with the information they need in real time.

[1732] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1733] Pet behavior monitoring process flow

[1734] Step 1: Capture behavioral data

[1735] The device uses a built-in camera and motion sensors to capture footage and movements of your pet.

[1736] Input: Real-time video and motion data.

[1737] Processing: The camera captures video at 30 frames per second, and the motion sensor detects movement.

[1738] Output: High resolution video and motion data.

[1739] Step 2: Compress and format the data

[1740] The device compresses the captured video data using the H.264 codec and converts the motion data into CSV format.

[1741] Input: High-resolution video and motion data.

[1742] Processing: Video data is compressed using H.264 and motion data is converted to CSV format.

[1743] Output: Compressed video data and motion data in CSV format.

[1744] Step 3: Sending data

[1745] The device transmits compressed video and motion data to a server via Wi-Fi.

[1746] Input: Compressed video and motion data.

[1747] Processing: Transmit data using IEEE 802.11ac.

[1748] Output: The data sent to the server.

[1749] Step 4: Analyze behavioral patterns

[1750] The server analyzes the received data using a TensorFlow model.

[1751] Input: Received video and motion data.

[1752] Processing: Activity recognition algorithms analyze the video frames and identify activities (e.g., "running" or "sleeping").

[1753] Output: Analyzed behavioral patterns.

[1754] Step 5: Generate and send notifications

[1755] The server sends a notification to the user's smartphone app based on the analysis results.

[1756] Input: Analyzed behavioral patterns.

[1757] Processing: Generate and send notifications using Firebase Cloud Messaging (FCM).

[1758] Output: A push notification is sent to the user's smartphone app.

[1759] Step 6: Confirm your actions

[1760] Users can check their pet's current behavior using a smartphone app.

[1761] Input: The notification sent by the server.

[1762] Action: Display behavioral information on the app dashboard.

[1763] Output: The user confirms the pet's behavior.

[1764] Pet health monitoring process flow

[1765] Step 1: Measuring health data

[1766] The device regularly measures your pet's health indicators using temperature and heart rate sensors.

[1767] Inputs: Real-time body temperature and heart rate.

[1768] Processing: The sensor measures the information and stores it temporarily in local memory.

[1769] Output: Measured body temperature and heart rate data.

[1770] Step 2: Storing and sending data

[1771] The terminal stores the measurement data in its local memory and transmits it to the server at regular intervals.

[1772] Input: Measured body temperature and heart rate data.

[1773] Processing: Transmit data using Bluetooth Low Energy (BLE).

[1774] Output: Measurement data sent to the server.

[1775] Step 3: Anomaly detection and alerting

[1776] The server analyzes the received health data and detects any abnormalities.

[1777] Input: Received temperature and heart rate data.

[1778] Action: Generate an abnormality alert if the normal range is exceeded (e.g., if the body temperature is above 39 degrees).

[1779] Output: The anomaly alert generated.

[1780] Step 4: Health Alert Notifications

[1781] The server sends the generated alert to the user's smartphone app.

[1782] Input: The generated anomaly alert.

[1783] Processing: Send notifications using Firebase Cloud Messaging (FCM).

[1784] Output: An alert is sent to the user's smartphone app.

[1785] Step 5: Health Check

[1786] Users can check their pet's health status via a smartphone app.

[1787] Input: The alert notification sent from the server.

[1788] Processing: Display health information and action suggestions within the app.

[1789] Output: The user checks his health status and takes necessary measures.

[1790] Pet location tracking process flow

[1791] Step 1: Capturing location data

[1792] The device periodically obtains your pet's location information using the built-in GPS module.

[1793] Input: Real-time location information.

[1794] Processing: The GPS module captures location information and stores it in local memory.

[1795] Output: The captured location data.

[1796] Step 2: Storing and sending data

[1797] The device stores the location data in its local memory and transmits it to a server via Wi-Fi.

[1798] Input: The captured location data.

[1799] Processing: Send data using Wi-Fi.

[1800] Output: The location data sent to the server.

[1801] Step 3: Analyze and match location information

[1802] The server compares the received location information with map data to determine the pet's current location.

[1803] Input: Received location data.

[1804] Processing: Use the Geocoding API to convert location coordinates into specific addresses or place names.

[1805] Output: The determined location.

[1806] Step 4: Notification of location data

[1807] The server sends the analysis results to the user's smartphone app.

[1808] Input: Parsed location information.

[1809] Processing: Send location information using Firebase Cloud Messaging (FCM).

[1810] Output: Location information is sent to the user's smartphone app.

[1811] Step 5: Locate and track

[1812] Users can check their pet's current location and past routes using a smartphone app.

[1813] Input: Location information sent from the server.

[1814] Processing: Display location on a map within the app and visualize past travel routes.

[1815] Output: The user sees the pet's current location and its route.

[1816] (Application example 1)

[1817] 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."

[1818] Real-time monitoring of pet safety and health in autonomous vehicles is an important issue for many pet owners. Normally, when pets are left in a car, it is difficult to properly monitor their behavior and health, which can lead to stress and health problems. There is also a risk that pets may become anxious or excited, causing problems inside the vehicle. Therefore, a reliable system is needed to ensure the safe management of pets in autonomous vehicles.

[1819] 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.

[1820] In this invention, the server is a device for monitoring the behavior of a pet, and includes means for capturing the movements of the pet in real time using a camera and a motion sensor, a device for monitoring the health condition of the pet, and means for measuring the body temperature and heart rate of the pet using a sensor, and a device for tracking the location information of the pet, and means for periodically acquiring the location information of the pet using a GPS module. This makes it possible to monitor the behavior, health condition, and location information of the pet in real time so that the pet can stay safe and comfortable inside the autonomous vehicle.

[1821] A "device for monitoring pet behavior" is a device that uses a camera or motion sensor to capture pet movements in real time.

[1822] "Means of capturing in real time" refers to the ability to instantly obtain current situations and activities, and record and analyze that data.

[1823] The "means for converting into a communicable format" is a function for converting data into an appropriate format so that it can be sent to other devices or servers via a communication line.

[1824] "Means for sending to server" refers to the function of sending data to the server via a communication line.

[1825] The "means for estimating pet behavior patterns" is a function for analyzing received data and estimating patterns of pet movement and behavior.

[1826] "Means for sending notifications to the user's device" refers to a function that sends analysis results and alerts to the user's device, such as a smartphone or tablet.

[1827] "Means for monitoring pet behavior inside an autonomous vehicle" refers to a function that monitors pet behavior inside an autonomous vehicle in real time and notifies the user if any abnormalities are detected.

[1828] A "device for monitoring the health of a pet" is a device that measures the health of a pet using temperature and heart rate sensors.

[1829] The "means for saving the measured data in a local memory" refers to a storage device for temporarily saving the measured data.

[1830] "Means for detecting abnormalities" is a function that detects abnormal conditions from analyzed data.

[1831] "Means of notifying the user terminal inside the self-driving vehicle" refers to a function that notifies the user terminal in real time of any abnormalities or behavior of pets inside the car.

[1832] "Means for obtaining pet location information" refers to a function that periodically identifies the pet's location using a GPS module.

[1833] "Means for confirming that a pet is in a safe area" refers to a function for confirming whether a pet is within a pre-defined safe area within an autonomous vehicle.

[1834] The present invention provides a system for comprehensively monitoring the behavior, health status, and location information of pets in an autonomous vehicle. Specific embodiments of the present invention will be described below.

[1835] System Configuration

[1836] Terminal (device for monitoring pet behavior)

[1837] The terminal contains the following main components:

[1838] Camera: Installed to capture video of your pet. Captures video data in real time.

[1839] Motion sensor: A sensor that detects pet movement and collects pet behavior data.

[1840] Body temperature and heart rate sensors: Regularly measure your pet's health indicators and obtain health status data.

[1841] GPS module: A module for obtaining pet location information.

[1842] Communication module: A Wi-Fi or Bluetooth module for sending data to the server.

[1843] Local memory: A storage device for temporarily storing acquired data.

[1844] server

[1845] The server has the following features:

[1846] Data analysis function: Analyzes data sent from the device to estimate your pet's behavior and health condition.

[1847] Notification function: Sends information and alerts to the user's device based on the analysis results.

[1848] Database: Records and manages pet behavior history and health status.

[1849] User terminal

[1850] A smartphone app with the following functions is installed on the user's device:

[1851] Real-time display function: Displays your pet's behavior, health status, and location information in real time.

[1852] Notification function: Notifies users of alerts and information from the server.

[1853] History reference function: You can refer to past data history.

[1854] Program processing

[1855] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[1856] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it identifies behaviors such as "pet is running" or "pet is sleeping." Depending on the analysis results, a push notification is sent to the user's smartphone app.

[1857] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[1858] Health monitoring

[1859] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[1860] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[1861] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[1862] Location tracking

[1863] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[1864] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[1865] Users can check their pet's current location and past routes using a smartphone app.

[1866] Specific examples

[1867] 1. Examples of behavioral monitoring:

[1868] The device uses a camera to capture real-time footage of a dog playing in the yard.

[1869] The terminal compresses the video data and sends it to the server via the communication module.

[1870] The server analyzes the received data and determines that a dog is running in the yard.

[1871] The server notifies the user of the results via their smartphone app.

[1872] Users can use the app to see that their dog is playing happily.

[1873] 2. Examples of health monitoring:

[1874] The device measures the dog's temperature as 36.8 degrees.

[1875] The device stores the measurement data in its local memory and periodically transmits it to the server.

[1876] The server analyzes the received data and determines that the body temperature is within the normal range.

[1877] The server notifies the user of the results via their smartphone app.

[1878] Users can use the app to ensure their pets are in good health.

[1879] 3. Examples of location tracking:

[1880] The device uses a GPS module to obtain the location information of dogs in the park.

[1881] The device stores the acquired location data in its local memory and periodically transmits it to the server.

[1882] The server compares the received location information with map information to determine the dog's current location.

[1883] The server displays the results on the user's smartphone app.

[1884] The user uses the app to confirm that the dog's current location is in the park.

[1885] Example prompt sentence:

[1886] "Temperature sensor data: 36.5 degrees, heart rate: 80 bpm, GPS location information: latitude 35.6895, longitude 139.6917, pet activity: running"

[1887] These methods allow users to continuously monitor the safety and health of their pets while in an autonomous vehicle.

[1888] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1889] Step 1:

[1890] The device uses a camera and motion sensor to capture video and movements of your pet in real time. The input is the camera image and motion sensor data, and the output is the captured video data and movement data. Specifically, the camera takes video and the motion sensor detects movement.

[1891] Step 2:

[1892] The terminal compresses the captured video and motion data and converts it into a format that can be transmitted. The input is the captured raw data, and the output is the compressed data. A data compression algorithm (e.g., H.264) is used for this process. Specifically, the data compression algorithm efficiently compresses the video data.

[1893] Step 3:

[1894] The terminal sends the converted data to the server through the communication module. The input is the compressed data, and the output is the data sent to the server. Specifically, the data is sent to the server via Wi-Fi or Bluetooth communication.

[1895] Step 4:

[1896] The server analyzes the received data and estimates the pet's behavioral patterns. The input is compressed data received from the device, and the output is the estimated behavioral pattern. Specifically, a machine learning algorithm analyzes the data and identifies behaviors such as "running" or "sleeping."

[1897] Step 5:

[1898] The server sends a notification to the user's device based on the estimated behavioral pattern. The input is the estimated behavioral pattern, and the output is a notification to the user's device. Specifically, the notification system sends a push notification to the user's smartphone.

[1899] Step 6:

[1900] The device periodically uses the body temperature and heart rate sensors to measure the pet's health indicators. The input is the body temperature and heart rate measurement data, and the output is the health indicator data. Specifically, the sensors measure the body temperature and heart rate and obtain the data.

[1901] Step 7:

[1902] The terminal stores the measurement data in its local memory and transmits it to the server at regular intervals. The input is the measurement data, and the output is the stored data and transmitted data. Specifically, the data is stored in the local memory and periodically transmitted to the server.

[1903] Step 8:

[1904] The server analyzes the received health data and detects abnormalities. The input is the health status measurement data, and the output is the anomaly detection result. Specifically, the analysis algorithm analyzes the data and determines whether there is an abnormality in the health status.

[1905] Step 9:

[1906] The server sends an alert to the user's device based on the detected anomaly. The input is the anomaly detection result, and the output is an alert notification to the user's device. Specifically, the notification system sends an alert to the user's smartphone.

[1907] Step 10:

[1908] The device periodically obtains the pet's location information using the built-in GPS module. The input is GPS data and the output is location information. Specifically, the GPS module identifies the location information and obtains the data.

[1909] Step 11:

[1910] The terminal stores the acquired location information in its local memory and periodically transmits it to the server. The input is location information data, and the output is the stored data and transmitted data. Specifically, the data is stored in the local memory and then transmitted to the server.

[1911] Step 12:

[1912] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The input is location data, and the output is the analyzed location information. Specifically, the map analysis algorithm analyzes the location information and determines the exact location.

[1913] Step 13:

[1914] The server displays the analyzed location information on the user's smartphone app, allowing them to check their pet's current location and past movement routes. The input is the analyzed location information, and the output is the display of the location information on the user's device. Specifically, the location information is displayed on the user's app.

[1915] Example prompt sentence:

[1916] "Temperature sensor data: 36.5 degrees, heart rate: 80 bpm, GPS location information: latitude 35.6895, longitude 139.6917, pet activity: running"

[1917] 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.

[1918] The present invention provides a system that combines a system for comprehensively monitoring pet behavior, health status, and location information with an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention will be described below.

[1919] System Configuration

[1920] The system consists of the following main components:

[1921] 1. Device (terminal) for monitoring pet behavior

[1922] 2. Server that analyzes and manages data

[1923] 3. User's information device (smartphone or tablet)

[1924] 4. Emotion engine that recognizes user emotions

[1925] Terminal (device for monitoring pet behavior)

[1926] Camera: A device for capturing video of your pet.

[1927] Motion sensor: A sensor for detecting pet movement.

[1928] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate).

[1929] GPS module: A module for determining the current location of your pet.

[1930] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth.

[1931] Local memory: A storage device for temporarily storing data.

[1932] server

[1933] Data analysis function: Has the ability to analyze received data and estimate your pet's behavioral patterns and health condition.

[1934] Notification function: Has the ability to send information and alerts to user devices based on analysis results.

[1935] Database: Includes a database for recording and managing pet behavior history and health status.

[1936] Emotion engine: Has the ability to analyze the user's emotions and generate appropriate feedback based on the results.

[1937] User terminal

[1938] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[1939] Program processing

[1940] The program processing performed by each device in the system will be explained below in natural language.

[1941] Pet behavior monitoring

[1942] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[1943] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it can identify behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via push notifications to the user's smartphone app.

[1944] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[1945] Health monitoring

[1946] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[1947] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[1948] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[1949] Location tracking

[1950] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[1951] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[1952] Users can check their pet's current location and past routes using a smartphone app.

[1953] Adding an Emotion Engine

[1954] The server analyzes the user's emotions using an emotion engine, which analyzes the user's emotional state in real time based on data collected from the user's device (e.g., user input information, voice, facial expressions, etc.).

[1955] If the user is feeling stressed, the emotion engine analyzes the pet's behavioral data and generates feedback to encourage therapeutic behavior, such as sending a notification to the user's smartphone to "take some time to relax with your pet."

[1956] If the user is relaxed, the emotion engine generates feedback to encourage positive behavior in the pet, such as sending a notification to the user's smartphone saying, "Praise your pet for being good."

[1957] Specific examples

[1958] Examples of behavioral monitoring

[1959] 1. The device uses its camera to capture video of a dog playing in the yard.

[1960] 2. The terminal compresses the video data and sends it to the server via the communication module.

[1961] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[1962] 4. The server notifies the user of the results via their smartphone app.

[1963] 5. The user uses the app to confirm that the dog is playing happily.

[1964] Health monitoring examples

[1965] 1. The device measures the dog's temperature as 36.8 degrees.

[1966] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[1967] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[1968] 4. The server notifies the user of the results via their smartphone app.

[1969] 5. The user uses the app to ensure their pet is in good health.

[1970] Examples of location tracking

[1971] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[1972] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[1973] 3. The server compares the received location information with map information to determine the dog's current location.

[1974] 4. The server displays the results on the user's smartphone app.

[1975] 5. The user uses the app to confirm that the dog is currently at the park.

[1976] Examples of emotion engines

[1977] 1. The server receives voice data from the user's smartphone.

[1978] 2. The emotion engine analyzes the voice data and determines that the user is feeling stressed.

[1979] 3. The server generates a notification to encourage the pet to engage in therapeutic behavior and sends it to the user's smartphone.

[1980] 4. The user uses the app to view therapeutic behaviors and relax with their pet.

[1981] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and also provides appropriate feedback according to the user's emotional state.

[1982] The processing flow will be explained below.

[1983] Behavioral monitoring

[1984] Step 1: Data Capture

[1985] The device uses a camera and motion sensors to capture video and movements of your pet in real time.

[1986] The device stores the captured video data and motion data in temporary memory.

[1987] Step 2: Data processing

[1988] The terminal compresses the captured data and converts it into a format that can be communicated.

[1989] The terminal organizes the processed data as batch data.

[1990] Step 3: Sending data

[1991] The device sends the processed data to the server via Wi-Fi or Bluetooth.

[1992] The terminal confirms the success of the transmission and receives an acknowledgement.

[1993] Step 4: Analyze the data

[1994] The server analyzes the received data and applies behavior recognition algorithms to detect the pet's behavior patterns.

[1995] The server records information such as "pet is running" or "pet is sleeping" in the behavior log.

[1996] Step 5: Sending notifications

[1997] The server sends analysis results such as "your pet is running" or "your pet is sleeping" to the user's smartphone app as a push notification.

[1998] Users can check their pet's current behavior using a smartphone app.

[1999] Health monitoring

[2000] Step 1: Data collection

[2001] The device uses sensors to measure your pet's body temperature and heart rate every 10 minutes.

[2002] The terminal temporarily stores the measurement data in a local memory.

[2003] Step 2: Send data

[2004] The terminal transmits the measurement data to the server.

[2005] The terminal adjusts its periodic data transmission schedule to optimize power consumption.

[2006] Step 3: Data analysis

[2007] The server analyzes the received data in real time and evaluates whether it is within the normal range.

[2008] If the server detects an anomaly, it generates an alert to the user.

[2009] Step 4: Sending notifications

[2010] The server sends the results of abnormality detection and regular health status reports to the user's smartphone via push notifications.

[2011] Users can check notifications about their pet's health status on their smartphone and take necessary measures.

[2012] Location Tracking

[2013] Step 1: Obtaining location information

[2014] The device periodically obtains your pet's location information using the built-in GPS module.

[2015] The terminal stores the acquired location information in a local memory.

[2016] Step 2: Send data

[2017] The terminal transmits the location information data to the server.

[2018] The terminal confirms the success of the transmission and receives an acknowledgement.

[2019] Step 3: Data analysis

[2020] The server compares the location data with map information to determine the pet's current location.

[2021] The server records the location information as the pet's movement history.

[2022] Step 4: View location information

[2023] The server sends map data to the user's smartphone app to display the pet's current location.

[2024] Users can check their pet's current location and past routes using a smartphone app.

[2025] Adding an Emotion Engine

[2026] Step 1: Collecting emotion data

[2027] The user's terminal collects the user's voice, facial expressions, and input information.

[2028] The terminal transmits the collected emotion data to the server.

[2029] Step 2: Analyze the emotion data

[2030] The server uses an emotion engine to analyze the received emotion data and estimate the user's emotional state.

[2031] The server classifies the emotional state as "stressed" or "relaxed," etc.

[2032] Step 3: Generate feedback

[2033] The emotion engine analyzes pet behavior data and generates notifications to prompt therapeutic behaviors if the user is experiencing stress.

[2034] The emotion engine generates notifications to encourage positive behavior for pets when the user is relaxed.

[2035] Step 4: Submit your feedback

[2036] The server transmits the generated feedback to the user's smartphone.

[2037] Users receive notifications on their smartphone app and spend appropriate time with their pets.

[2038] Specific examples

[2039] Examples of behavioral monitoring

[2040] Step 1:

[2041] The device uses a camera to capture footage of a dog playing in the yard.

[2042] Step 2:

[2043] The terminal compresses the video data and transmits it to the server via the communication module.

[2044] Step 3:

[2045] The server analyzes the received data and determines that "a dog is running in the yard."

[2046] Step 4:

[2047] The server notifies the user of the results via their smartphone app.

[2048] Step 5:

[2049] The user uses the app to confirm that the dog is playing happily.

[2050] Health monitoring examples

[2051] Step 1:

[2052] The device measures the dog's temperature as 36.8 degrees.

[2053] Step 2:

[2054] The terminal stores the measurement data in a local memory and periodically transmits it to a server.

[2055] Step 3:

[2056] The server analyzes the received data and determines that the body temperature is within the normal range.

[2057] Step 4:

[2058] The server notifies the user of the results via their smartphone app.

[2059] Step 5:

[2060] Users use the app to ensure their pets are in good health.

[2061] Examples of location tracking

[2062] Step 1:

[2063] The device uses a GPS module to obtain the location information of dogs in the park.

[2064] Step 2:

[2065] The terminal stores the acquired location data in a local memory and periodically transmits it to a server.

[2066] Step 3:

[2067] The server compares the received location information with map information to determine the dog's current location.

[2068] Step 4:

[2069] The server displays the results on the user's smartphone app.

[2070] Step 5:

[2071] The user uses the app to confirm that the dog's current location is at the park.

[2072] Examples of emotion engines

[2073] Step 1:

[2074] The user's terminal collects the user's voice data.

[2075] Step 2:

[2076] The terminal transmits the collected voice data to the server.

[2077] Step 3:

[2078] The emotion engine analyzes the voice data and determines that the user is feeling stressed.

[2079] Step 4:

[2080] The server generates notifications to prompt therapeutic behavior and sends them to the user's smartphone.

[2081] Step 5:

[2082] Users use the app to view therapeutic behaviors and relax with their pet.

[2083] Example 2

[2084] 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."

[2085] Comprehensive and real-time monitoring of pet behavior, health, and location information is difficult without error. Furthermore, there are no systems that provide appropriate feedback taking into account the user's emotional state. This makes it challenging to properly monitor pet status and provide appropriate responses in conjunction with the user's emotional state.

[2086] 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.

[2087] In this invention, the server includes: means for capturing the movements of the pet in real time using a camera and a motion sensor; means for compressing the captured data and converting it into a communicable format; means for transmitting the converted data to the server via a communication line; means for analyzing the data received by the server and estimating the behavioral pattern of the pet; means for sending a notification to the user's terminal based on the estimated behavioral pattern; means for measuring the pet's body temperature and heart rate using a sensor; means for periodically saving the measured data in a local memory; means for transmitting the saved data to the server; means for analyzing the data received by the server and detecting anomalies; means for sending an alert to the user's terminal based on the detected anomaly; means for periodically acquiring location information of the pet using a GPS module; means for saving the acquired location information in a local memory; means for transmitting the saved location information to the server; means for analyzing the location information received by the server based on map information; This makes it possible to comprehensively monitor a pet's behavior, health, and location, while also providing appropriate feedback based on the user's emotional state.

[2088] A "camera" is a device for capturing video data.

[2089] A "motion sensor" is a sensor for detecting the movement of an object.

[2090] "Pet" refers to an animal kept in the home.

[2091] "Real-time" means processing data immediately with minimal delay.

[2092] "Data compression" is the process of transforming data using a certain algorithm to reduce the amount of data.

[2093] A "communicable format" is a format used to transmit data, designed to facilitate data exchange.

[2094] A "communications line" is a network infrastructure for transmitting data to a remote location.

[2095] A "server" is a computer system that provides services over a network.

[2096] "Analysis" is a method for processing data and understanding its meaning and structure.

[2097] "Behavioral patterns" are information that indicates a series of behaviors and habits of a pet.

[2098] A "notification" is a message or alert that conveys information to the user.

[2099] A "sensor" is a device that measures physical quantities and outputs them as data.

[2100] "Body temperature" is an indicator of the internal temperature of a living organism.

[2101] "Heart rate" is an index that indicates the number of heartbeats per unit time.

[2102] "Local memory" is a storage device for temporarily storing data.

[2103] "Abnormal" refers to a state or value that is outside the normal range.

[2104] An "alert" is a warning notification that notifies the user of an abnormal situation.

[2105] A "GPS module" is a device for acquiring location information.

[2106] "Location information" is data that indicates the geographical location of an object.

[2107] "Map information" is data for visually displaying geographical locations.

[2108] An "emotion engine" is a software system for analyzing a user's emotional state and generating feedback based on that.

[2109] "Emotion" is information that indicates the user's psychological state or mood.

[2110] "Feedback" is advice or feedback provided to the user.

[2111] This invention is a system that comprehensively monitors pet behavior, health status, and location information, and provides appropriate feedback according to the user's emotional state. This system consists of the following main components: a device (terminal) that monitors pet behavior, a server that analyzes and manages the data, the user's information terminal (smartphone or tablet), and an emotion engine that recognizes the user's emotions.

[2112] System Configuration

[2113] Terminal (device for monitoring pet behavior)

[2114] Camera: A device for taking pictures of pets, for example capturing footage of a dog playing in the yard.

[2115] Motion sensor: A sensor that detects the movement of your pet, such as when your pet is running or sleeping.

[2116] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate). Detects whether the body temperature is within the normal range.

[2117] GPS module: A module for determining the current location of pets. Obtains location information of pets in the park.

[2118] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth. Compressed data is sent to the server.

[2119] Local memory: A storage device for temporarily storing data. It temporarily stores measurement data and location information.

[2120] server

[2121] Data analysis function: The system has the ability to analyze received data and estimate the behavioral patterns and health status of pets. For example, it can analyze received video data and determine that "a dog is running in the yard."

[2122] Notification function: The system has the ability to send information and alerts to the user's device based on the analysis results, informing the user of any abnormalities in behavioral patterns or health conditions.

[2123] Database: Includes a database for recording and managing pet behavior history and health status. Stores past behavioral data and health data.

[2124] Emotion engine: This engine analyzes the user's emotions and generates appropriate feedback based on the results. For example, it can determine from voice data that the user is feeling stressed.

[2125] User terminal

[2126] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[2127] Specific examples

[2128] The operation of the system will be explained using a specific example.

[2129] Examples of behavioral monitoring

[2130] 1. The device uses its camera to capture video of a dog playing in the yard.

[2131] 2. The terminal compresses the video data and sends it to the server via the communication module.

[2132] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[2133] 4. The server notifies the user of the results via their smartphone app.

[2134] 5. The user uses the app to confirm that the dog is playing happily.

[2135] Health monitoring examples

[2136] 1. The device measures the dog's temperature as 36.8 degrees.

[2137] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[2138] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[2139] 4. The server notifies the user of the results via their smartphone app.

[2140] 5. The user uses the app to ensure their pet is in good health.

[2141] Examples of location tracking

[2142] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[2143] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[2144] 3. The server compares the received location information with map information to determine the dog's current location.

[2145] 4. The server displays the results on the user's smartphone app.

[2146] 5. The user uses the app to confirm that the dog is currently at the park.

[2147] Examples of emotion engines

[2148] 1. The server receives voice data from the user's smartphone.

[2149] 2. The emotion engine analyzes the voice data and determines that the user is feeling stressed.

[2150] 3. The server generates a notification to encourage the pet to engage in therapeutic behavior and sends it to the user's smartphone.

[2151] 4. The user uses the app to view therapeutic behaviors and relax with their pet.

[2152] Prompt Sentence Examples

[2153] "Please explain how the program checks to see if a dog's temperature is normal."

[2154] "Describe how your system works to track your pet's location."

[2155] "Please explain in detail how to generate notifications based on user emotions."

[2156] This makes it possible to comprehensively monitor a pet's behavior, health, and location, while also providing appropriate feedback based on the user's emotional state.

[2157] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2158] Program processing flow

[2159] Pet behavior monitoring

[2160] Step 1:

[2161] The device activates the camera to capture the pet's video in real time, and simultaneously activates the motion sensor to detect the pet's movements. The input is the pet's movements and video, and the output is the captured video data and movement data.

[2162] Step 2:

[2163] The device compresses the captured video data and movement data and converts them into a format that can be communicated. Specifically, the video data is compressed into JPEG format, and the movement data is converted into JSON format. The input is the captured data, and the output is the compressed data.

[2164] Step 3:

[2165] The device sends the compressed data to the server via Wi-Fi or Bluetooth. The input is the compressed data, and the output is the data sent to the server.

[2166] Step 4:

[2167] The server analyzes the received data and estimates the pet's behavioral patterns in real time. The video data is processed by image analysis software, and the movement data is processed by motion analysis algorithms. The input is the received data, and the output is the estimated behavioral patterns.

[2168] Step 5:

[2169] The server identifies the pet's behavior based on the analysis results and sends a push notification of that information to the user's smartphone app. The input is the analyzed behavior pattern, and the output is notification information.

[2170] Step 6:

[2171] The user receives a notification on the smartphone app and checks the current behavior of their pet. The input is the notification information, and the output is the user's confirmation action.

[2172] Health monitoring

[2173] Step 1:

[2174] The device activates the temperature and heart rate sensors to measure the pet's temperature and heart rate. The measurement results are stored in the internal memory. The input is the sensor data, and the output is the measurement results.

[2175] Step 2:

[2176] The device temporarily stores the measurement data in its local memory and sends it to the server at regular intervals. The data is converted to CSV format and sent via Wi-Fi. The input is the measurement data, and the output is the data sent to the server.

[2177] Step 3:

[2178] The server analyzes the received health data in real time to detect abnormalities. It uses an anomaly detection algorithm to generate an alert if the body temperature exceeds the normal range. The input is the received health data, and the output is the presence or absence of abnormalities.

[2179] Step 4:

[2180] If the server detects an anomaly, it generates an alert based on that information and sends it to the user's smartphone app. The input is the anomaly detection result, and the output is the alert information.

[2181] Step 5:

[2182] Users receive anomaly alerts via a smartphone app and take necessary measures. The input is the alert information, and the output is the corrective action.

[2183] Location tracking

[2184] Step 1:

[2185] The device uses the built-in GPS module to acquire pet location information. The location data is stored in the internal memory. The input is GPS data, and the output is location data.

[2186] Step 2:

[2187] The device stores the acquired location data in its local memory and periodically sends it to the server. The data is converted to NMEA format and sent via Wi-Fi. The input is the location data, and the output is the data sent to the server.

[2188] Step 3:

[2189] The server analyzes the received location information and locates the pet's current location by comparing it with map information. It uses a location analysis algorithm, whose input is the received location information and whose output is the determined current location.

[2190] Step 4:

[2191] The server sends location information based on the analysis results to the user's smartphone app. The input is the identified current location, and the output is a location notification.

[2192] Step 5:

[2193] Users can check real-time location information on a smartphone app and check their pet's current location and past movement routes. The input is location information notification, and the output is the user's confirmation behavior.

[2194] Adding an Emotion Engine

[2195] Step 1:

[2196] The server receives voice data and facial expression data from the user's smartphone. This data is processed in real time. The input is the user's emotional data, and the output is the received data.

[2197] Step 2:

[2198] The emotion engine analyzes the collected data and determines the user's emotion in real time. It uses voice recognition software to analyze the emotional state. The input is the received emotion data, and the output is the emotion analysis result.

[2199] Step 3:

[2200] The server generates a notification to encourage therapeutic behavior for the pet based on the analysis results of the emotion engine and sends it to the user's smartphone. The input is the emotion analysis result, and the output is the therapeutic behavior notification.

[2201] Step 4:

[2202] The emotion engine generates notifications to encourage positive behaviors for pets when the user is relaxed. The input is the emotion analysis result, and the output is the positive behavior notification.

[2203] Step 5:

[2204] The user checks the notification on the smartphone app and takes time to relax with their pet. The input is the notification information, and the output is the user's behavior.

[2205] This makes it possible to comprehensively monitor a pet's behavior, health, and location, while also providing appropriate feedback based on the user's emotional state.

[2206] (Application example 2)

[2207] 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."

[2208] Conventional pet monitoring systems focus on monitoring pet behavior, health, and location information, but none take into account the user's emotional state. Furthermore, in autonomous vehicles, there is a lack of technology that provides appropriate driving assistance based on pet safety management and the user's emotions. The present invention aims to solve these problems.

[2209] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for determining the user's emotional state using an emotion engine that analyzes the user's emotional state, means for generating corresponding feedback based on the user's emotional state and notifying the user terminal of the feedback, and means for providing driving assistance that takes the user's emotional state into consideration using the emotion engine that analyzes the user's emotional state. This makes it possible to provide driving assistance that corresponds to the user's emotional state while managing the safety of pets in an autonomous vehicle.

[2210] A "device for monitoring pet behavior" is a device that uses a camera or motion sensor to monitor pet movements in real time and transmits the data to a server.

[2211] "Capture" is the act of collecting motion and video using cameras and sensors.

[2212] "Means for converting into a communicable format" refers to a device or process that compresses the captured data and converts it into a form that can be sent to a server.

[2213] A "server" is a central computer system that analyzes received data and sends notifications to user terminals based on the results of various analyses.

[2214] The "means for estimating the behavioral patterns of a pet" refers to an algorithm or program that analyzes the data received on the server and determines the specific behavior of the pet.

[2215] "Means for sending notifications to user terminals" refers to a communications system for sending information and alerts from a server to a user's smartphone or tablet.

[2216] An "emotion engine" is a software engine that analyzes the user's voice, facial expressions, input information, etc. to determine the user's emotional state.

[2217] The "means for determining the emotional state of a user" refers to a process and system that uses an emotion engine to analyze and determine the emotion of a user.

[2218] The "means for generating corresponding feedback and notifying the user terminal" is a mechanism for generating appropriate feedback based on the emotional state of the user determined by the emotion engine and transmitting that feedback to the user terminal.

[2219] The "device for monitoring the health condition of a pet" is a device that measures the health indicators of a pet using body temperature and heart rate sensors and transmits the results to a server.

[2220] The "means for detecting anomalies" is a system that analyzes the health data received on the server and identifies data points that are out of the ordinary.

[2221] A "device for tracking pet location information" is a device that periodically acquires pet location information using a GPS module and transmits it to a server.

[2222] "Driving Assist" is a system that provides driving assistance based on the user's emotional state and notifies and suggests the driver via a smartphone or in-car display.

[2223] The present invention relates to a system that comprehensively monitors the behavior, health status, and location information of a pet, and further provides appropriate feedback according to the emotional state of the user. Specific embodiments for carrying out the present invention will be described in detail below.

[2224] System Configuration

[2225] The system consists of the following main components:

[2226] 1. Device (terminal) for monitoring pet behavior

[2227] 2. Server that analyzes and manages data

[2228] 3. User's information device (smartphone or tablet)

[2229] 4. Emotion engine that recognizes user emotions

[2230] Terminal

[2231] The device has the following features to monitor your pet's behavior, health and location:

[2232] Camera: Capture footage of your pet.

[2233] Motion sensor: Detects pet movements in real time.

[2234] Body temperature and heart rate sensors: measure your pet's health indicators.

[2235] GPS module: Identify your pet's location.

[2236] Communication module: Sends data to the server using Wi-Fi or Bluetooth.

[2237] Local memory: temporarily stores data.

[2238] server

[2239] The server has the following features:

[2240] Data analysis function: Analyzes received data and estimates your pet's behavioral patterns and health condition.

[2241] Notification function: Sends information and alerts to user devices based on analysis results.

[2242] Database: Records and manages pet behavior history and health status.

[2243] Emotion engine: Analyzes the user's emotions and generates appropriate feedback based on the results.

[2244] User terminal

[2245] The user terminal has the following features:

[2246] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[2247] Program processing

[2248] The program processing performed by each device will be explained below.

[2249] Pet behavior monitoring

[2250] The device uses a camera and motion sensors to capture video and movements of the pet in real time. The captured video and motion data is compressed and converted into a format that can be communicated. The converted data is then sent to a server via a communications module. The server analyzes the received data and estimates the pet's behavioral patterns. For example, it identifies behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via a push notification to the user's smartphone app. The user can then check their pet's current behavior on the smartphone app.

[2251] Health monitoring

[2252] The device periodically measures the pet's health indicators using the body temperature and heart rate sensors. The measurement data is stored in local memory and sent to the server at regular intervals. The server analyzes the received health data in real time and detects abnormalities. For example, if the body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app. The user receives notifications of the pet's health status via the smartphone app and can take necessary measures.

[2253] Location tracking

[2254] The device periodically obtains the pet's location information using the built-in GPS module. The obtained location information is stored in local memory and periodically sent to the server. The server analyzes the received location information and compares it with map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app. The user can then check the pet's current location and past movement routes on the smartphone app.

[2255] Adding an Emotion Engine

[2256] The server uses an emotion engine to analyze the user's emotions. The emotion engine analyzes the user's emotional state in real time based on data collected from the user's device (e.g., user input information, voice, facial expressions, etc.). If the user is feeling stressed, the emotion engine analyzes the pet's behavioral data and generates therapeutic feedback. For example, it sends a notification to the user's smartphone, such as "Take some time to relax with your pet." If the user is relaxed, the emotion engine generates feedback to encourage the pet's positive behavior. For example, it sends a notification to the user's smartphone, such as "Praise your pet for being well-behaved."

[2257] Examples of specific examples and prompts

[2258] Examples of behavioral monitoring

[2259] The device uses a camera to capture video of a dog playing in the yard. The device compresses the video data and sends it to the server via the communication module. The server analyzes the received data and determines that "the dog is running in the yard." The server notifies the user of the result via a smartphone app. The user then uses the app to confirm that "the dog is playing happily."

[2260] Health monitoring examples

[2261] The device measures the dog's temperature as 36.8°C. The device stores the measurement data in its local memory and periodically sends it to the server. The server analyzes the received data and determines that the body temperature is within the normal range. The server then notifies the user of the result via a smartphone app. The user can then use the app to confirm that their pet's health is normal.

[2262] Examples of location tracking

[2263] The device uses a GPS module to obtain the location information of the dog in the park. The device stores the obtained location data in its local memory and periodically sends it to the server. The server compares the received location information with map information to determine the dog's current location. The server displays the result on the user's smartphone app. The user then uses the app to confirm that the dog's current location is in the park.

[2264] Examples of emotion engines

[2265] The server receives voice data from the user's smartphone. The emotion engine analyzes the voice data and determines that the user is feeling stressed. The server generates a notification to prompt the pet to engage in therapeutic behavior and sends it to the user's smartphone. The user then uses the app to confirm the therapeutic behavior and relax with their pet.

[2266] Prompt Sentence Examples

[2267] Analyze the given audio data and generate feedback including playing relaxing music and notifying the pet's status if the user is stressed.

[2268] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and also provides appropriate feedback according to the user's emotional state.

[2269] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2270] Step 1:

[2271] The device uses a camera to capture images of the pet in real time. The motion sensor also detects the pet's movements at the same time. The input is the pet's video data and motion data, which are obtained by capturing these. The output is the video data and motion data. These data are temporarily stored in local memory.

[2272] Step 2:

[2273] The terminal compresses the captured data and converts it into a format that can be communicated. The input is the video data and motion data obtained in step 1. The data is compressed using a compression algorithm and format conversion is performed. The output is the compressed and converted data. This data is ready to be sent to the server via the communication module.

[2274] Step 3:

[2275] The terminal sends the converted data to the server through the communication module. The input is the compressed and converted data obtained in step 2. The data is sent to the server using a transmission protocol (e.g., Wi-Fi or Bluetooth). The output is the data that arrives at the server.

[2276] Step 4:

[2277] The server analyzes the received data and infers the pet's behavioral patterns. The input is the data that arrived at the server in step 3. It uses a machine learning algorithm (e.g., a generative AI model) to analyze the data and infer what the pet is doing. The output is information about the pet's behavioral patterns.

[2278] Step 5:

[2279] The server sends notifications to the user's device based on the estimated behavioral patterns. The input is the information about the behavioral patterns obtained in step 4. An appropriate notification is generated using a notification generation algorithm. The output is the notification sent to the user's device.

[2280] Step 6:

[2281] The device periodically measures the pet's health indicators using the body temperature and heart rate sensors. The input is the pet's body temperature and heart rate data. These data are obtained by measuring them. The output is the measurement data. This data is stored in the local memory.

[2282] Step 7:

[2283] The terminal sends the measurement data to the server using the communication module. The input is the measurement data obtained in step 6. The data is sent to the server using a transmission protocol. The output is the data that arrives at the server.

[2284] Step 8:

[2285] The server analyzes the received health data in real time and detects abnormalities. The input is the health data that arrived at the server in step 7. Anomalies are detected using data analysis algorithms. The output is alert information regarding the presence or absence of abnormalities.

[2286] Step 9:

[2287] The server sends an alert to the user terminal based on the detected anomaly. The input is the alert information obtained in step 8. The alert is generated using a notification generation algorithm. The output is the alert sent to the user terminal.

[2288] Step 10:

[2289] The device periodically obtains the pet's location information using the built-in GPS module. The input is the pet's current location information. This is obtained by obtaining it. The output is the location data. This data is stored in the local memory.

[2290] Step 11:

[2291] The terminal transmits the acquired location information to the server using the communication module. The input is the location data obtained in step 10. The data is transmitted to the server using a transmission protocol. The output is the data that arrives at the server.

[2292] Step 12:

[2293] The server compares the received location information with map information to determine the current location of the pet. The input is the location information received by the server in step 11. The server compares this with map information to determine the current location of the pet. The output is information about the current location of the pet.

[2294] Step 13:

[2295] The server notifies the user's smartphone app of the analysis results. The input is the current location information obtained in step 12. A notification is generated using the notification generation algorithm. The output is a notification sent to the user device.

[2296] Step 14:

[2297] The server receives voice data from the user's smartphone. The input is the user's voice data. This is obtained by receiving it. The output is the voice data that arrives at the server.

[2298] Step 15:

[2299] The emotion engine analyzes the speech data to determine the user's emotional state. The input is the speech data received by the server in step 14. The generative AI model is used to analyze the speech data and infer the user's emotional state. The output is information about the user's emotional state.

[2300] Step 16:

[2301] The server generates corresponding feedback based on the user's emotional state and notifies the user terminal. The input is the emotional state information obtained in step 15. The server generates the feedback using a notification generation algorithm. The output is the feedback sent to the user terminal.

[2302] Step 17:

[2303] The server provides driving assistance that takes into account the user's emotional state. The input is the emotional state information obtained in step 15. A driving assistance algorithm is used to generate appropriate driving assistance suggestions. The output is driving assistance information displayed on the in-vehicle display.

[2304] 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.

[2305] 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.

[2306] 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.

[2307] [Fourth embodiment]

[2308] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2309] 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.

[2310] 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).

[2311] 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.

[2312] 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.

[2313] 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).

[2314] 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.

[2315] 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.

[2316] 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.

[2317] 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.

[2318] 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.

[2319] 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.

[2320] 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."

[2321] The present invention provides a system for comprehensively monitoring pet behavior, health status, and location information. Specific embodiments of the present invention will be described below.

[2322] System Configuration

[2323] The system consists of the following main components:

[2324] 1. Device (terminal) for monitoring pet behavior

[2325] 2. Server that analyzes and manages data

[2326] 3. User's information device (smartphone or tablet)

[2327] Terminal (device for monitoring pet behavior)

[2328] Camera: A device for capturing video of your pet.

[2329] Motion sensor: A sensor for detecting pet movement.

[2330] Body temperature and heart rate sensor: A sensor for measuring your pet's health condition (body temperature and heart rate).

[2331] GPS module: A module for determining the current location of your pet.

[2332] Communication module: A module for sending data to a server using Wi-Fi or Bluetooth.

[2333] Local memory: A storage device for temporarily storing data.

[2334] server

[2335] Data analysis function: Has the ability to analyze received data and estimate your pet's behavioral patterns and health condition.

[2336] Notification function: Has the ability to send information and alerts to user devices based on analysis results.

[2337] Database: Includes a database for recording and managing pet behavior history and health status.

[2338] User terminal

[2339] Smartphone app: An application for checking your pet's behavior, health, and location in real time. It also has notification and history viewing functions.

[2340] Program processing

[2341] The program processing performed by each device in the system will be explained below in natural language.

[2342] Pet behavior monitoring

[2343] The device uses a camera and motion sensors to capture video and movement data of the pet in real time, compresses the captured video and motion data, converts it into a format that can be transmitted, and then transmits the converted data to the server via a communication module.

[2344] The server analyzes the received data and estimates the pet's behavioral patterns. For example, it can identify behaviors such as "the pet is running" or "the pet is sleeping." The analysis results are sent in real time via push notifications to the user's smartphone app.

[2345] Users can check their pet's current behavior on a smartphone app, which receives notifications from the server and displays the pet's behavior.

[2346] Health monitoring

[2347] The device periodically measures the pet's health indicators using temperature and heart rate sensors, and the measurement data is stored in local memory and sent to the server at regular intervals.

[2348] The server analyzes the received health data in real time and detects abnormalities. For example, if a body temperature exceeds the normal range, an abnormality alert is generated. The generated alert is sent to the user's smartphone app.

[2349] Users can receive notifications about their pet's health status via a smartphone app and take necessary measures.

[2350] Location tracking

[2351] The device periodically acquires the pet's location information using the built-in GPS module, which is then stored in the local memory and periodically sent to the server.

[2352] The server analyzes the received location information and verifies it against map information to determine the pet's current location. The analysis results are displayed on the user's smartphone app.

[2353] Users can check their pet's current location and past routes using a smartphone app.

[2354] Specific examples

[2355] Examples of behavioral monitoring

[2356] 1. The device uses its camera to capture video of a dog playing in the yard.

[2357] 2. The terminal compresses the video data and sends it to the server via the communication module.

[2358] 3. The server analyzes the received data and determines that "a dog is running in the yard."

[2359] 4. The server notifies the user of the results via their smartphone app.

[2360] 5. The user uses the app to confirm that the dog is playing happily.

[2361] Health monitoring examples

[2362] 1. The device measures the dog's temperature as 36.8 degrees.

[2363] 2. The device stores the measurement data in its local memory and periodically transmits it to the server.

[2364] 3. The server analyzes the received data and determines that the body temperature is within the normal range.

[2365] 4. The server notifies the user of the results via their smartphone app.

[2366] 5. The user uses the app to ensure their pet is in good health.

[2367] Examples of location tracking

[2368] 1. The device uses the GPS module to obtain the location information of the dog in the park.

[2369] 2. The device stores the acquired location data in its local memory and periodically transmits it to the server.

[2370] 3. The server compares the received location information with map information to determine the dog's current location.

[2371] 4. The server displays the results on the user's smartphone app.

[2372] 5. The user uses the app to confirm that the dog is currently at the park.

[2373] In this way, the present invention realizes a system that comprehensively monitors pet behavior, health status, and location information, and provides users with the information they need.

[2374] The processing flow will be explained below.

[2375] Pet behavior monitoring

[2376] Step 1: Data Capture

[2377] The device uses a camera and motion sensors to capture footage and movements of your pet in real time.

[2378] The device stores the captured video data and motion data in temporary memory.

[2379] Step 2: Data processing

[2380] The terminal compresses the captured data and converts it into a suitable format to save communication bandwidth.

[2381] The terminal organizes the processed data as batch data.

[2382] Step 3: Sending data

[2383] The device sends the processed data to the server via Wi-Fi or Bluetooth.

[2384] The terminal confirms the success of the transmission and receives an acknowledgement.

[2385] Step 4: Analyze the data

[2386] The server analyzes the received data and applies behavior recognition algorithms to detect the pet's behavior patterns.

[2387] The server records information such as "pet is running" or "pet is sleeping" in the behavior log.

[2388] Step 5: Sending notifications

[2389] The server sends analysis results such as "your pet is running" or "your pet is sleeping" to the user's smartphone app as a push notification.

[2390] Users can check their pet's current behavior using a smartphone app.

[2391] Health monitoring

[2392] Step 1: Data collection

[2393] The device uses sensors to measure your pet's body temperature and heart rate every 10 minutes.

[2394] The terminal temporarily stores the measurement data in a local memory.

[2395] Step 2: Send data

[2396] The terminal transmits the measurement data to the server.

[2397] The terminal adjusts its periodic data transmission schedule to optimize power consumption.

[2398] Step 3: Data analysis

[2399] The server analyzes the received data in real time and evaluates whether it is within the normal range.

[2400] If the server detects an anomaly, it generates an alert to the user.

[2401] Step 4: Sending notifications

[2402] The server sends the results of abnormality detection and regular health status reports to the user's smartphone via push notifications.

[2403] Users can check notifications about their pet's health status on their smartphone and take necessary measures.

[2404] Location tracking

[2405] Step 1: Obtaining location information

[2406] The device periodically obtains the pet's location information using the built-in GPS module.

[2407] The terminal stores the acquired location information in a local memory.

[2408] Step 2: Send data

[2409] The terminal transmits the location information data to the server.

[2410] The terminal confirms the success of the transmission and receives an acknowledgement.

[2411] Step 3: Data analysis

[2412] The server compares the location data with map information to determine the pet's current location.

[2413] The server records the location information as the pet's movement history.

[2414] Step 4: View location information

[2415] The server sends map data to the user's smartphone app to display the pet's current location.

[2416] Users can check their pet's current location and past routes using a smartphone app.

[2417] Example 1

[2418] 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."

[2419] There is a demand for a system that can comprehensively monitor pet behavior, health status, and location information, and allow users to obtain the information they need in real time. Conventional systems often collect and manage this information separately, making it difficult for users to use and providing information in a centralized manner.

[2420] 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.

[2421] In this invention, the server includes means for capturing the movements of the pet in real time using a camera and a motion sensor, means for compressing the captured data and converting it into a communicable format, means for transmitting the converted data to the server via a communication line, means for analyzing the data received by the server using a generative model and estimating the behavioral patterns of the pet, and means for transmitting notifications to the user's terminal based on the estimated behavioral patterns. This allows the user to centrally manage the behavior, health condition, and location information of the pet and obtain this information in real time.

[2422] A "camera" is a device for capturing images of pets.

[2423] A "motion sensor" is a sensor that detects the movement of a pet.

[2424] "Compression" is a process for reducing the size of captured data.

[2425] "Communicable format" refers to the process of converting data into a format that can be sent and received.

[2426] A "communication line" is a network for transmitting data.

[2427] A "server" is a central computer that analyzes and manages data.

[2428] A "generative model" is an algorithm for analyzing data and recognizing specific patterns.

[2429] A "behavioral pattern" is a series of movements that characterize a pet's behavior.

[2430] "Notification" is a message to inform the user of the analysis results.

[2431] A "terminal" is a device through which a user receives information.

[2432] "Health indicators" are data on body temperature and heart rate that indicate the pet's health condition.

[2433] "Local memory" is a storage device that temporarily stores data within a device.

[2434] An "abnormal alert" is a warning message that occurs when data outside the normal range is detected.

[2435] A "GPS module" is a device used to determine a pet's current location....

Claims

1. A device for monitoring the behavior of a pet, comprising: A means to capture pet movements in real time using cameras and motion sensors; A means for compressing the captured data and converting it into a format that can be communicated; means for transmitting the converted data to a server via a communication line; A means for analyzing the data received by the server and estimating the behavioral patterns of the pet; means for sending a notification to a user's terminal based on the estimated behavioral pattern; A system including:

2. A device for monitoring the health of a pet, comprising: a means for measuring the pet's body temperature and heart rate using a sensor; a means for periodically saving the measured data to a local memory; means for transmitting the stored data to a server; A means for analyzing the data received by the server and detecting anomalies; means for sending an alert to a user's device based on the detected anomaly; The system of claim 1 , comprising:

3. A device for tracking location information of a pet, comprising: A means for periodically acquiring location information of a pet using a GPS module; a means for storing the acquired location information in a local memory; means for transmitting the stored location information to a server; A means for analyzing the location information received by the server based on map information; means for displaying the analyzed location information on a user's terminal; The system of claim 1 , comprising:

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