System

Abstract

A system is provided.SOLUTION: A system for managing a physical condition and an action of a dog, comprising: means for measuring an activity amount, a heart rate, and position information of an animal using a sensor; terminal means for receiving data acquired from the sensor; server means for analyzing the data received from the terminal means and evaluating a health condition of the animal; and means for notifying a user of an analysis result of the server means via the terminal means.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] Traditionally, managing a dog's health and monitoring its behavior required a great deal of effort from the owner, and there was a high possibility that signs of illness or stress would be overlooked. Furthermore, determining the appropriate care method for each dog's individual characteristics was not easy, and incorrect judgment often led to health risks. There was a need for a method that would solve these problems and allow owners to efficiently manage their dog's health and behavior. [Means for solving the problem]

[0005] The present invention is a system for managing the physical condition and behavior of a pet dog, and includes the following elements: means for measuring the animal's activity level, heart rate, and location information using sensors; terminal means for receiving data obtained from the sensors; server means for analyzing the data received from the terminal means and evaluating the animal's health condition; and means for notifying the user of the analysis results from the server means via the terminal means. The present invention further includes means for estimating the animal's stress level and generating advice on appropriate care methods, and means for suggesting to the user the timing of walking the animal and the amount of exercise based on the analysis results, making it easier for owners to provide appropriate care for their pet dogs.

[0006] "Sensor" refers to a measuring device used to measure an animal's activity, heart rate, and location information.

[0007] The "terminal means" is an electronic device that has the function of receiving data acquired from the sensor and transmitting it to the server.

[0008] The "server means" is a computer system for analyzing data received from the terminal and evaluating the health status of the animals.

[0009] The "analysis results" are evaluation information regarding the health condition and behavior of the animals obtained after the server means analyzes the data.

[0010] "User" refers to the owner of a pet dog or the person in charge of managing the dog.

[0011] The "notification means" is a function used to notify the user of the analysis results of the server means, and is performed via the terminal.

[0012] "Stress level" is an estimated degree of stress based on the psychological and physiological state of an animal.

[0013] "Care Advice" is a suggestion provided to owners on how to properly care for their dog based on their stress level and health condition.

[0014] "Walk timing" refers to the best time of day to give your dog the exercise it needs.

[0015] "Exercise volume" is a measure of the level of activity your dog engages in over a certain period of time. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention is a system for managing the physical condition and behavior of pet dogs, which includes sensors, terminals, a server, and notification means. This system allows owners to understand the health condition of their pet dogs in real time and provide appropriate care.

[0038] System Configuration

[0039] 1. Sensor

[0040] It is incorporated into your dog's collar or harness.

[0041] Measures activity (acceleration), heart rate, and location information.

[0042] Data is collected at regular intervals and sent to the terminal.

[0043] 2. Terminal

[0044] A device owned by the user, such as a smartphone or tablet.

[0045] It receives the data collected from the sensors and sends the data to the server.

[0046] Receives analysis results from the server and notifies the user.

[0047] 3. Server

[0048] A computer system for analyzing the received data.

[0049] Analyzes activity, heart rate, and location information to assess health and stress levels.

[0050] Generate the necessary advice and send it to the device.

[0051] 4. Means of notification

[0052] Analysis results and advice are notified to the user via the device.

[0053] Use pop-up notifications, in-app messages, and push notifications.

[0054] Program processing

[0055] sensor

[0056] The sensor measures your dog's activity, heart rate, and location information at regular intervals and sends the data to the device. For example, the sensor measures your dog's movement every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location using a GPS sensor.

[0057] Terminal

[0058] The device sends the data received from the sensor to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The sent data includes a timestamp, making it clear when the measurement was made.

[0059] server

[0060] The server works with an AI model to analyze the received data and estimate stress levels and health status based on the collected data. Specifically, the server performs time-series analysis of activity data to assess whether the dog is getting enough exercise. It statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It also uses location data to generate advice on the frequency and range of walks.

[0061] Notification means

[0062] The device that receives the analysis results notifies the user of the results. For example, when the device receives the analysis results from the server, it will notify the user with specific advice such as "Take a walk for at least 30 minutes today." If the heart rate is abnormally high, it will warn the user that "Your heart rate is high, so we recommend that you take your pet to the veterinarian."

[0063] The system of the present invention further includes a means for estimating the stress level of an animal and generating advice on appropriate care methods, and a means for suggesting to the user the timing of walking the animal and the amount of exercise based on the analysis results, making it easier for pet owners to provide appropriate care for their pets. In this way, pet owners can efficiently manage their pet's health and improve the quality of life for both the owner and their pet dog.

[0064] The processing flow will be explained below.

[0065] Step 1:

[0066] Data collection by sensors

[0067] The sensor is built into your dog's collar or harness and measures your dog's activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor) every minute. This data is temporarily stored in the sensor's internal memory.

[0068] Step 2:

[0069] Send data to the device

[0070] The sensor transmits the collected data via Bluetooth to the device, which receives the data and clears it from the sensor's internal memory.

[0071] Step 3:

[0072] Sending data from the device to the server

[0073] The device sends the received data to the server in real time, including a timestamp to clarify when the measurement was made.

[0074] Step 4:

[0075] Data analysis by server

[0076] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[0077] Step 5:

[0078] Generate analysis results

[0079] The server uses the analysis results to assess the dog's stress level and health condition, and generates appropriate care advice, including specific suggestions such as "Take a walk for at least 30 minutes today" or "Your heart rate is high, so we recommend you take your dog to the vet."

[0080] Step 6:

[0081] Sending analysis results to the device

[0082] The server sends the generated analysis results to the terminal, which receives the results and prepares to notify the user.

[0083] Step 7:

[0084] User Notification

[0085] The device will notify the user of the analysis results from the server via pop-up displays, in-app messages, push notifications, etc. The user can then take care of their dog based on the notification and provide feedback as needed.

[0086] Step 8:

[0087] Get feedback and learn

[0088] Users provide feedback through their devices, such as by sending a comment like, "Today's walking advice was helpful." The server receives this feedback and incorporates it into the AI ​​model to help improve analysis accuracy.

[0089] The above processing steps realize a system that manages the physical condition and behavior of pet dogs in real time and provides advice to owners on how to provide appropriate care.

[0090] Example 1

[0091] 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."

[0092] When it comes to pet health management, it is difficult for owners to monitor their dog's physical condition and behavior in real time. Also, there may be delays in noticing that their dog is stressed or their health is deteriorating. Therefore, an effective system is needed to provide prompt and appropriate care.

[0093] 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.

[0094] In this invention, the server includes: means for measuring the activity level, heart rate, and location information of the animal using a sensor; terminal means for receiving data obtained from the sensor via Bluetooth and transmitting the time-stamped data to the server in real time; means for analyzing the data received from the terminal means, evaluating the health condition and stress level of the animal, and generating appropriate care advice; and means for notifying the user of the analysis results of the server means as a push notification or an in-app message. This makes it possible to monitor the activity level, heart rate, and location information of a pet dog in real time, quickly evaluate the health condition, and provide appropriate care advice as needed.

[0095] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[0096] The "terminal means" is a device that receives data acquired from the sensor via Bluetooth and transmits the data with a timestamp to the server in real time.

[0097] The "server means" is a computer system that serves to analyze data received from the terminal means, evaluate the health condition and stress level of the animal, and generate appropriate care advice.

[0098] "Analysis results" refers to evaluations and diagnostic information obtained by processing data received by the server means.

[0099] "Push notification" is a function that displays analysis results and advice to users in real time via their device.

[0100] "Activity" is a measurement that indicates the degree of movement or activity of an animal.

[0101] "Heart rate" is a measurement of the number of times an animal's heart beats within a given period of time.

[0102] "Location information" is geographical data that indicates the current location of an animal.

[0103] "Bluetooth" is a short-range wireless communication technology used to send and receive data between sensors and terminal devices.

[0104] A "timestamp" is information that indicates the date and time when data was collected or transmitted.

[0105] "Care advice" refers to recommendations and warnings regarding animal health care that are generated by the server means based on the analysis results.

[0106] "Health status" is a collection of indicators that indicate the degree of physical and mental well-being of an animal.

[0107] "Stress level" is an index that evaluates the degree of stress an animal is experiencing.

[0108] The present invention is a system for managing the physical condition and behavior of a pet dog in real time, and its main components include a sensor, a terminal, a server, and a notification means. The details of each component and their operation will be explained below.

[0109] sensor

[0110] The sensors are attached to your dog's collar or harness and measure activity, heart rate, and location information. For example, an acceleration sensor detects your dog's movements, a heart rate sensor measures its heart rate, and a GPS sensor obtains its location information. These data are measured every minute and sent to your device via Bluetooth. Specific sensor hardware includes an acceleration sensor, heart rate sensor, and GPS sensor.

[0111] Terminal

[0112] The device is a smartphone or tablet owned by the user. The device receives data acquired from the sensor via Bluetooth and transmits it to the server in real time using an HTTP POST request. The transmitted data includes a timestamp, making it clear when the data was measured. The device's software includes an application that receives data from the sensor and a communication module that transmits the data to the server.

[0113] server

[0114] The server analyzes the data received from the device and evaluates the dog's health condition and stress level. It uses an AI model to analyze activity data, heart rate data, and location data to evaluate the animal's movement patterns and heart rate trends and detect abnormalities. Based on the analysis results, it generates appropriate care advice and sends it to the device. The server software includes an AI model for data analysis and logic for generating care advice.

[0115] Notification means

[0116] Once the device receives the analysis results from the server, it immediately displays them to the user as a push notification or in-app message. For example, if today's walk time is short, the device will display advice such as "Try to take a walk for at least 30 minutes today." If the heart rate is abnormally high, the device will display a warning such as "Your heart rate is high. We recommend that you take your pet to the vet."

[0117] Specific examples

[0118] A specific scenario for actually using a dog health management system is as follows: A sensor is attached to the dog's collar, and the dog starts walking. The sensor measures the dog's activity level, heart rate, and location every minute and sends the data to the device. The device receives this data via Bluetooth and sends it to the server in real time. The server analyzes the received data and determines that the dog's stress level is high. The server generates advice such as "Your dog's stress level is high, so we recommend continuing your walk a little longer" and sends it to the device. The device then notifies the user of this advice via push notification.

[0119] Prompt Sentence Examples

[0120] We have developed a health management system for your pet dog. This system consists of sensors, terminals, a server, and a notification method, and measures your dog's activity level, heart rate, and location information, and analyzes it in real time to provide appropriate advice.

[0121] Sensor (e.g. attached to your dog's collar):

[0122] Activity (acceleration), heart rate, and location information are measured every minute.

[0123] Device (e.g. user's smartphone):

[0124] The data from the sensor is received via Bluetooth and sent to the server via an HTTP POST request.

[0125] server:

[0126] The received data is analyzed using an AI model to assess your dog's stress level and health condition.

[0127] Generate the necessary advice and send it to your device.

[0128] Notification method:

[0129] The device will then send a push notification to the user with the analysis results (e.g., "Please take a walk of at least 30 minutes today").

[0130] This system allows you to monitor your dog's health in real time and provide appropriate care.

[0131] In such an embodiment, the present invention can efficiently manage the health of pet dogs, improving the quality of life for owners and their pet dogs.

[0132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0133] Step 1:

[0134] Data Measurement

[0135] The sensor measures your dog's activity (acceleration), heart rate, and location information every minute. The sensor inputs are your dog's movements, heart rate, and geographic location, and processes the data based on these inputs to generate measurement results. Specifically, the acceleration sensor collects activity data, the heart rate sensor measures heart rate data, and the GPS sensor obtains location data. These measurement results are obtained as output.

[0136] Step 2:

[0137] Data transmission

[0138] The sensor sends the measured data to the terminal via Bluetooth. The sensor input is the measurement results obtained in step 1, and the data is packaged using Bluetooth communication and sent to the terminal. Specifically, the sensor aggregates the measurement data every minute and sends it to the terminal via Bluetooth. The terminal receives this data.

[0139] Step 3:

[0140] Data reception

[0141] The device receives data sent from the sensor via Bluetooth. The device inputs data packets from the sensor, which are converted into an internal data format for processing. Specifically, the device analyzes the received data packets and stores them as activity data, heart rate data, and location information data.

[0142] Step 4:

[0143] Data transmission (server)

[0144] The terminal sends the received data to the server in real time using an HTTP POST request. The input to the terminal is the data received in step 3, which is time-stamped and sent to the server. Specifically, the terminal analyzes the data packets received from the sensor, generates an HTTP POST request, and sends it to the server. The server receives this data.

[0145] Step 5:

[0146] Data analysis

[0147] The server analyzes the data received from the device. The server's input is the data sent from the device, and it uses an AI model to analyze this data. Specifically, it analyzes activity data, heart rate data, and location data to evaluate health status and stress levels and detect any abnormalities. The output is the analysis results and appropriate care advice.

[0148] Step 6:

[0149] Advice Generation

[0150] The server generates appropriate care advice based on the results of the data analysis. The input is the analysis result from step 5, and advice and warning messages are generated based on this. Specifically, the server evaluates the analysis result, generates the necessary care advice and warning, and creates a data packet to send to the terminal.

[0151] Step 7:

[0152] Receive advice

[0153] The terminal receives the analysis results and advice sent from the server. The terminal inputs data packets from the server, which it analyzes and prepares to notify the user. Specifically, the terminal analyzes the data packets received in the HTTP response and generates the notification content.

[0154] Step 8:

[0155] User Notification

[0156] The device notifies the user of the analysis results and care advice. The input is the data received in step 7, which is displayed to the user as a push notification or in-app message. Specifically, the device sets a push notification to notify the user of advice such as "Please take your pet for a walk for at least 30 minutes today" or "Your pet's heart rate is high, so we recommend you take it to the vet."

[0157] This process allows you to monitor your dog's health in real time and provide appropriate care advice quickly.

[0158] (Application example 1)

[0159] 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."

[0160] Currently, there are limited means for understanding the health status and behavior of pet owners in real time, making it difficult for owners to provide appropriate care. Furthermore, because there is no connection with pet care services offered at physical stores, it is difficult for users to find the optimal care method. The present invention aims to provide a system for efficiently managing the health of pets and facilitating the provision of services at physical stores.

[0161] 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.

[0162] In this invention, the server includes: means for measuring the activity level, heart rate, and location information of the animal using a sensor; terminal means for receiving data acquired from the sensor; means for analyzing the data received from the terminal means and evaluating the animal's health condition; means for notifying the user of the analysis results of the server means via the terminal means; means for generating recommendations for providing services at a physical store; and means for notifying the user of the recommendations. This allows users to understand the health condition of their beloved dog in real time and provide appropriate care. Furthermore, by linking with pet care services at physical stores, owners can receive optimal services.

[0163] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[0164] A "terminal" is a device that receives data obtained from a sensor and transmits it to a server.

[0165] The "server" is a computer system that analyzes data received from the terminal means, evaluates the health condition of the animal, and notifies the results of the analysis.

[0166] A "physical store" is a place that users can visit in person, and is a facility where pet care services and the like are provided.

[0167] "Recommendations" are useful advice or suggestions for users that are generated based on the results of analysis on the server.

[0168] "Notification means" refers to a method for communicating analysis results and recommendations to users via their devices.

[0169] The present invention is a system for managing the physical condition and behavior of a pet dog, and includes a sensor, a terminal, a server, and a notification means. Specific embodiments of the system are described below.

[0170] System Configuration

[0171] 1. Sensor

[0172] The sensors attached to your dog's collar or harness measure activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor). The sensors collect data at regular intervals (for example, every minute) and send it to your device via Bluetooth.

[0173] 2. Terminal

[0174] The user's smartphone or tablet receives data from the sensor and transmits it to the server in real time. The transmitted data includes a timestamp to indicate when the measurement was made. The device sends the data to the server using an HTTP POST request.

[0175] 3. Server

[0176] The server is a computer system located in the cloud that analyzes the received data. Using AI models (time series analysis model, anomaly detection model), stress levels and health conditions are estimated based on the collected data. For example, activity data is analyzed over time to determine whether the dog is getting enough exercise. Heart rate data is statistically analyzed and compared with normal heart rates to detect abnormalities. Location data is used to generate advice on the frequency and range of walks.

[0177] 4. Means of notification

[0178] The device receives the analysis results from the server and notifies the user of the results. Specifically, when the device receives the analysis results from the server, it will notify the user of specific advice such as "Take a walk for at least 30 minutes today." If the heart rate is abnormally high, it will warn the user, "Your heart rate is high, so we recommend that you take your pet to the veterinarian."

[0179] Specific examples

[0180] For example, if your dog is not getting enough exercise, the server will generate instructions such as "Set today's walking time to at least 30 minutes." If the dog's heart rate is higher than normal, the server will send a notification to the user saying, "Your dog's heart rate is higher than normal. We recommend that you see a veterinarian." Based on these results, users can efficiently manage their dog's health.

[0181] Prompt Sentence Examples

[0182] prompt:

[0183] Please analyze my dog's activity data (acceleration 34.5, heart rate 115, location information: 35.6895, 139.6917). Please tell me the health condition and proper care method.

[0184] Expected answer:

[0185] Analysis of your dog's activity data has revealed that his heart rate is higher than normal, indicating signs of stress. It's possible that he's not getting enough exercise, so we recommend increasing your walk time. If the heart rate persists, we recommend consulting a veterinarian.

[0186] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0187] Step 1:

[0188] The sensor measures your dog's activity level, heart rate, and location at regular intervals and transmits the data to your device via Bluetooth.

[0189] Input: Data collected from accelerometer, heart rate sensor, and GPS sensor

[0190] Output: Measurement data sent to the device

[0191] Specific operation: The sensor measures your dog's movements every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location information using a GPS sensor.

[0192] Step 2:

[0193] The device transmits the data received from the sensor to the server in real time.

[0194] Input: Measurement data sent from the sensor via Bluetooth

[0195] Output: Data sent to the server as an HTTP POST request

[0196] Specific operation: The device receives activity, heart rate, and location information from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The data includes a timestamp to clarify the timing of the measurement.

[0197] Step 3:

[0198] The server works with an AI model to analyze the received data and estimate stress levels and health status based on the collected data.

[0199] Input: Measurement data sent from the device

[0200] Output: Health status assessment and stress level estimation results

[0201] How it works: The server performs time-series analysis of activity data to assess whether your dog is getting enough exercise. It statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It uses location data to generate advice on the frequency and range of walks.

[0202] Step 4:

[0203] The server generates recommendations for providing services in physical stores based on the analysis results.

[0204] Input: Health status assessment and stress level estimation results

[0205] Output: Recommendations

[0206] Specific operation: Based on the analysis results, the server generates recommendations to suggest pet care services and products that can be provided in physical stores.

[0207] Step 5:

[0208] The server sends the recommendations to the device and provides them to the user through notifications.

[0209] Input: Recommendations

[0210] Output: Recommendations communicated to the user

[0211] Specific behavior: The server sends the generated recommendations to the device, and the device provides the recommendations to the user via a pop-up or push notification, such as specific advice such as "Take a walk for at least 30 minutes today" or a warning such as "Your heart rate is high, so we recommend you see a veterinarian."

[0212] 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.

[0213] This invention combines a system for managing a pet dog's physical condition and behavior with an emotion engine that recognizes the user's emotions. This system allows owners to understand their pet's health and behavior in real time, and also provides appropriate care advice according to the owner's emotional state.

[0214] System Configuration

[0215] 1. Sensor

[0216] It is incorporated into your dog's collar or harness.

[0217] Measures activity level (acceleration sensor), heart rate (heart rate sensor), and location information (GPS sensor).

[0218] Data is collected at regular intervals and sent to the terminal.

[0219] 2. Terminal

[0220] A device owned by the user, such as a smartphone or tablet.

[0221] It receives the data collected from the sensors and sends the data to the server.

[0222] Receives analysis results from the server and notifies the user.

[0223] 3. Server

[0224] A computer system for analyzing the received data.

[0225] Analyzes activity, heart rate, and location information to assess health and stress levels.

[0226] Generate the necessary advice and send it to the device.

[0227] Advice is tailored using user emotional information obtained from the emotion engine.

[0228] 4. Emotion Engine

[0229] An engine that recognizes the user's voice and facial expressions and analyzes their emotional state.

[0230] The information is received by the terminal and transmitted to the server.

[0231] 5. Means of notification

[0232] Analysis results and advice are notified to the user via the device.

[0233] Use pop-up notifications, in-app messages, and push notifications.

[0234] Program processing

[0235] sensor

[0236] The sensor measures your dog's activity, heart rate, and location information at regular intervals and sends the data to the device. For example, the sensor measures your dog's movement every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location using a GPS sensor.

[0237] Terminal

[0238] The device sends the data received from the sensor to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The sent data includes a timestamp, making it clear when the measurement was made.

[0239] server

[0240] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[0241] Emotion Engine

[0242] The emotion engine recognizes emotions from the user's voice and facial expressions and receives that information on the device. For example, the emotion engine analyzes the user's tone of voice and facial expressions while they are speaking through the camera to assess whether they are feeling stressed.

[0243] Server-based analysis results generation and adjustment

[0244] The server adjusts the content and tone of the advice based on the user's emotional information obtained from the emotion engine. For example, if the user is feeling stressed, the server will suggest simple care methods to reduce stress.

[0245] Notification means

[0246] The device that receives the analysis results notifies the user of the results. For example, when the device receives the analysis results from the server, it will notify the user with specific advice such as, "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[0247] The above processing steps realize a system that provides more appropriate and effective care by taking into consideration the owner's emotional state in addition to the dog's physical condition and behavioral management.

[0248] The processing flow will be explained below.

[0249] Step 1:

[0250] Data collection by sensors

[0251] The sensor is built into your dog's collar or harness and measures your dog's activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor) every minute. This data is temporarily stored in the sensor's internal memory.

[0252] Step 2:

[0253] Send data to the device

[0254] The sensor transmits the collected data via Bluetooth to the device, which receives the data and clears the data from the sensor's internal memory.

[0255] Step 3:

[0256] Sending data from the device to the server

[0257] The device transmits the received data to the server in real time, and the transmitted data includes a timestamp to clarify when the measurement was made.

[0258] Step 4:

[0259] Data analysis by server

[0260] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[0261] Step 5:

[0262] Recognizing user emotions with an emotion engine

[0263] The emotion engine uses the device's camera and microphone to recognize the user's emotions. For example, the emotion engine analyzes the user's voice tone to assess their emotional state, such as stress or fatigue. It also uses facial expression recognition technology to read emotions from the user's facial expressions.

[0264] Step 6:

[0265] Server-generated analysis results and advice

[0266] The server adjusts the analysis results based on the user's emotional information obtained from the emotion engine, combined with the dog's health data, and if the user is feeling stressed, it will include simple care methods to relieve stress.

[0267] Step 7:

[0268] Sending analysis results to the device

[0269] The server then sends the generated analysis results to the device, which include advice based on the user's emotional state.

[0270] Step 8:

[0271] User Notification

[0272] The device receives the analysis results from the server and notifies the user. Notifications are displayed as pop-ups, in-app messages, or push notifications. For example, the device provides specific advice such as, "We recommend that you take a walk of at least 30 minutes. You seem tired, so please take regular breaks."

[0273] Step 9:

[0274] Getting user feedback

[0275] Users can provide feedback on the usefulness of the advice through their device, for example by sending a comment such as "Today's advice was helpful."

[0276] Step 10:

[0277] Server-based feedback learning

[0278] The server receives feedback from users and incorporates it into the AI ​​model, helping to improve the accuracy of analysis and the quality of advice in future sessions.

[0279] The above processing steps realize a system that provides care advice that takes into account the user's emotional state as well as the dog's physical condition and behavior management, enabling owners to provide more effective and appropriate care for their pets.

[0280] Example 2

[0281] 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."

[0282] Conventional animal health management systems simply monitor the animal's activity level, heart rate, and location, and are unable to provide care advice that takes into account the owner's psychological state, such as emotions and stress. As a result, the system does not properly reflect the owner's own stress or fatigue, and therefore sometimes does not provide optimal care advice.

[0283] 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.

[0284] In this invention, the server includes: means for measuring activity level, heart rate, and location information using sensors for managing the animal's physical condition and behavior; an information processing terminal for receiving data acquired from the sensors; means for analyzing the data received from the information processing terminal and evaluating the animal's health condition; means for notifying the user of the analysis results of the server device via the information processing terminal; an emotion analysis engine for analyzing the user's voice and facial expressions to grasp their emotional state; and means for adjusting the analysis results and advice content based on the emotion information acquired by the emotion analysis engine. This makes it possible to provide more appropriate and effective care advice by taking into account the owner's emotional state in addition to the animal's physical condition and behavior management.

[0285] "Animal" refers to any living creature kept as a domestic animal or pet, including, but not limited to, a pet dog.

[0286] "Sensor" refers to a measuring device for measuring data such as an animal's activity level, heart rate, and location information.

[0287] "Activity level" is data that indicates the degree of movement or movement that an animal underwent within a certain period of time.

[0288] "Heart rate" is data indicating the number of heartbeats an animal has within a certain period of time.

[0289] "Location information" is data about an animal's current location and movement route obtained using GPS and other devices.

[0290] An "information processing terminal" is a device that receives data collected from sensors and transmits it to a server, and includes smartphones, tablets, etc.

[0291] The "server device" is a computer system that analyzes data sent from the information processing terminal, evaluates the health condition of the animals, and generates analysis results.

[0292] An "emotion analysis engine" is a system that analyzes a user's voice and facial expressions to understand their emotional state.

[0293] The "analysis results" are the output results of evaluations and diagnoses made by the server device based on data acquired from sensors and emotion analysis engines.

[0294] "Means of notification" refers to the method used to notify users of analysis results and advice, including pop-up notifications, in-app messages, and push notifications.

[0295] This invention is a system for managing the physical condition and behavior of animals, and uses the following hardware and software to acquire, analyze, and notify data.

[0296] Hardware Configuration

[0297] 1. Sensor

[0298] Various sensors are incorporated into the animal's collar or harness.

[0299] The sensors used include an acceleration sensor that measures activity, a heart rate sensor that measures heart rate, and a GPS sensor that obtains location information.

[0300] These sensors collect data at regular intervals and transmit it to an information processing terminal.

[0301] 2. Information processing terminal

[0302] It is a device such as a smartphone or tablet that the user owns.

[0303] The data collected from the sensors is received via Bluetooth and sent to the server in real time using HTTP POST requests.

[0304] 3. Server Device

[0305] The server device is a powerful computer system for analyzing the received data.

[0306] The server uses AI models to perform time series analysis of activity data, statistical analysis of heart rate data, and geographic information analysis of location data.

[0307] 4. Sentiment Analysis Engine

[0308] An emotion analysis engine is a system for analyzing a user's voice and facial expressions.

[0309] A microphone is used for voice analysis and a camera for facial expression analysis.

[0310] The obtained emotion information is transmitted to the server via the information processing terminal.

[0311] Program processing

[0312] Sensor Processing

[0313] The sensor measures the animal's activity, heart rate, and location information at regular intervals and sends the data to an information processing terminal. For example, the sensor measures the dog's activity every minute with an acceleration sensor, records the heart rate with a heart rate sensor, and obtains location information with a GPS sensor.

[0314] Terminal Processing

[0315] The device receives data from the sensor and sends it to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and sends it to the server via an HTTP POST request. The data includes a timestamp to clarify the timing of the measurement.

[0316] Server Processing

[0317] The server analyzes the received data using an AI model. Specifically, it performs time-series analysis of activity data to evaluate whether the amount of exercise is appropriate, statistically analyzes heart rate data to detect abnormalities, and generates advice on the frequency and range of walks based on location data.

[0318] Sentiment Analysis Engine

[0319] The emotion analysis engine recognizes emotions from the user's voice and facial expressions, for example, by analyzing the user's tone of voice and facial expressions through the camera when they speak, and assessing the user's stress level.

[0320] Server-based analysis results generation and adjustment

[0321] The server adjusts the content and tone of the advice based on the user's emotional information obtained from the emotion analysis engine. For example, if the user is feeling stressed, it generates simple care advice to reduce stress. Examples of specific advice include, "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[0322] Notification means

[0323] The device receives the analysis results from the server and notifies the user using pop-up notifications, in-app messages, and push notifications, and displays specific advice such as "Your dog needs at least a 30-minute walk today."

[0324] Examples and prompts

[0325] Specific examples

[0326] The sensor measures your dog's activity every minute and sends the data to an information processing terminal.

[0327] The device sends the received data to a server, which then analyzes the data using an AI model.

[0328] The emotion analysis engine analyzes the user's voice and facial expressions and sends emotional information to the server.

[0329] The server adjusts the advice based on the analysis results, and the device notifies the user of the analysis results.

[0330] Prompt Sentence Examples

[0331] "What advice would be effective on how to care for a user's dog if they are stressed?"

[0332] "How can I analyze my dog's activity and heart rate data to assess his health?"

[0333] In this way, a system is realized that manages the physical condition and behavior of a beloved dog while providing appropriate care advice that also takes into account the user's emotional state.

[0334] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0335] Step 1:

[0336] Sensor data acquisition

[0337] The sensor acquires the animal's activity, heart rate, and location information at regular intervals. The sensor's inputs are the animal's physical activity, location, and heart rate. The sensor measures these inputs and generates activity data, heart rate data, and location data. This data is temporarily stored in the sensor and then sent to an information processing device. For example, an acceleration sensor measures the animal's movement over one minute, a heart rate sensor simultaneously records the heart rate, and a GPS sensor identifies the animal's location.

[0338] Step 2:

[0339] Sending data to the device

[0340] The data acquired by the sensor is sent to the information processing terminal. The input to the terminal is data from the sensor, and the output is data sent to the server. The terminal receives activity level, heart rate, and location information from the sensor using Bluetooth, and sends this information along with the received timestamp to the server via an HTTP POST request. Here, the terminal formats the data and converts it into a format that is easy for the server to analyze. Specifically, the terminal compiles the data received from the sensor and sends it to the server every minute.

[0341] Step 3:

[0342] Data analysis by server

[0343] The server receives and analyzes the data sent from the device. The server's inputs are activity data, heart rate data, and location data sent from the device. The server analyzes this data using an AI model and generates an output that evaluates the animal's health, as well as analytical results on exercise volume and stress levels. Specifically, the server performs a time series analysis of the activity data to evaluate whether exercise is being performed appropriately. It also statistically analyzes the heart rate data to detect abnormalities. The location data is used to evaluate the frequency and range of walks using geographic information analysis.

[0344] Step 4:

[0345] Emotion analysis using an emotion analysis engine

[0346] The emotion analysis engine analyzes the user's voice and facial expressions to understand their emotional state. The emotion analysis engine's input is the user's voice data and facial expression data, and its output is information about their emotional state. The engine uses a microphone and camera to analyze the user's tone of voice and facial expressions. For example, the analysis results may evaluate whether the user is feeling stressed. This information is sent to the information processing terminal and then to the server.

[0347] Step 5:

[0348] Server-based analysis results generation and adjustment

[0349] The server receives the user's emotional information obtained from the emotion analysis engine and adjusts the analysis results and advice content. The server receives data based on the animal's health assessment and the user's emotional information. The server integrates this data and generates care advice based on the user's stress level. For example, if the user is feeling stressed, the server will generate advice such as, "We recommend taking a short walk to reduce stress."

[0350] Step 6:

[0351] User notification via information processing terminal

[0352] The device receives analysis results and advice from the server and notifies the user. The input to the device is the analysis results and advice sent from the server, and the output is the notification to the user. Notification methods include pop-up notifications, in-app messages, and push notifications. For example, a notification may be sent to the user saying, "Your dog needs to be walked for at least 30 minutes today."

[0353] Through these steps, the system is able to provide appropriate care advice that takes into account not only the animal's physical condition and behavior, but also the user's emotional state.

[0354] (Application example 2)

[0355] 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."

[0356] Conventional pet dog health management systems only provide general care advice based on the dog's health condition, without taking into account the owner's emotional state. As a result, it is difficult to provide appropriate advice when the owner is stressed or in a specific emotional state. Thus, there is a need for a system that provides more appropriate care methods that take into account the owner's emotional state.

[0357] The identification process 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 analyzing data acquired from the sensor and evaluating the health condition of the animal, means including an emotion engine for analyzing the emotional state of the user, and means for generating advice based on the analysis results of the server means and the user's emotional information and notifying the user via the terminal means. This makes it possible to provide advice that takes the owner's emotional state into consideration.

[0358] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[0359] The "terminal means" is a device that receives data acquired from the sensor and transmits the data to the server means.

[0360] The "server means" is a computer system for analyzing data received from the terminal means and evaluating the health status of the animals.

[0361] An "emotion engine" is a device or system for analyzing a user's emotional state, and determines the user's emotions based on data such as voice and facial expressions.

[0362] The "analysis results" are information about the health condition and stress level of the animal that is generated by the server means by analyzing the data received from the sensor.

[0363] The "means for generating advice" is a device or computer program that allows the server means to create advice on appropriate care methods based on the analysis results and the user's emotional information.

[0364] The "notifying means" is a device or function for notifying the user of the generated advice via the terminal means.

[0365] This invention is a system for managing the physical condition and behavior of a pet dog, and is implemented using the following devices and software.

[0366] The system includes the following main components: a sensor, a terminal means, a server means, an emotion engine, and a notification means.

[0367] sensor

[0368] The sensors worn by pet dogs are measuring devices that measure the animal's activity, heart rate, and location information. Examples include acceleration sensors, heart rate sensors, and GPS sensors. These sensors are incorporated into the dog's collar or harness, and collect data at regular intervals and transmit it to a terminal via Bluetooth.

[0369] Terminal means

[0370] The terminal means is a device such as a smartphone or tablet that receives data from the sensor in real time and transmits it to the server means. For example, the terminal means transmits the amount of activity, heart rate, and location information received from the sensor via Bluetooth to the server using an HTTP POST request.

[0371] Server Means

[0372] The server means is a computer system for analyzing the received data. The specific analysis is performed as follows:

[0373] Activity data is analyzed over time to evaluate your dog's physical activity.

[0374] Heart rate data is statistically analyzed and compared with normal heart rates to detect abnormalities.

[0375] Advice is generated regarding the frequency and range of walks based on location data.

[0376] The server means adjusts the content and tone of advice based on the user's emotional information obtained from the emotion engine.

[0377] Emotion Engine

[0378] An emotion engine is a device or system for analyzing a user's voice and facial expressions to assess their emotional state. For example, an emotion engine may analyze a user's voice tone and facial expressions through a camera while they are speaking to assess whether they are feeling stressed.

[0379] Notification means

[0380] The notification means has a function to notify the user of the analysis results and advice. Information is notified to the user via the terminal means as push notifications or in-app messages. For example, when the terminal receives the analysis results from the server, it notifies the user with specific advice such as "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[0381] Specific examples

[0382] For example, if your dog is healthy but doesn't get enough exercise, you'll receive a notification saying, "Your dog is healthy, but needs more exercise." If your emotional state is analyzed as "stressed," you'll receive a notification saying, "Your dog is healthy, but needs more exercise. Please take some time to relax."

[0383] Prompt Sentence Examples

[0384] "It analyzes the user's vocal tone and facial expressions to assess their current emotional state. If the emotional state is stress, it will add a message to your dog's health advice about taking time to relax."

[0385] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0386] Step 1:

[0387] The sensor measures your dog's activity, heart rate, and location. The sensor collects this data at regular intervals and sends it to the device via Bluetooth. The input is the measured data, and the output is the data sent to the device.

[0388] Step 2:

[0389] The device receives data from the sensor and sends it to the server in real time. The device receives data via Bluetooth and sends it to the server using an HTTP POST request. The input is the data received from the sensor and the output is the data sent to the server.

[0390] Step 3:

[0391] The server analyzes the received data. The server performs time-series analysis of the activity data, statistical analysis of the heart rate data, and evaluates the frequency and range of walks based on the location data. The input is the data sent from the device, and the output is the analysis results.

[0392] Step 4:

[0393] The emotion engine analyzes the user's voice and facial expressions to evaluate their emotional state. For example, the emotion engine analyzes the user's tone of voice and facial expressions through a camera while they are speaking. The input is audio and video data, and the output is analyzed emotional information.

[0394] Step 5:

[0395] The server generates advice based on the analysis results and emotional information. The server creates advice with appropriate content and tone, taking into account the user's emotional state. The input is the analysis results and emotional information, and the output is the generated advice.

[0396] Step 6:

[0397] The device receives advice from the server and notifies the user. The device provides specific advice to the user using push notifications or in-app messages. The input is the advice sent from the server, and the output is the message notified to the user.

[0398] 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.

[0399] 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.

[0400] 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.

[0401] [Second embodiment]

[0402] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0403] 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.

[0404] 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).

[0405] 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.

[0406] 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.

[0407] 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).

[0408] 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.

[0409] 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.

[0410] 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.

[0411] 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.

[0412] 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.

[0413] 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."

[0414] The present invention is a system for managing the physical condition and behavior of pet dogs, which includes sensors, terminals, a server, and notification means. This system allows owners to understand the health condition of their pet dogs in real time and provide appropriate care.

[0415] System Configuration

[0416] 1. Sensor

[0417] It is incorporated into your dog's collar or harness.

[0418] Measures activity (acceleration), heart rate, and location information.

[0419] Data is collected at regular intervals and sent to the terminal.

[0420] 2. Terminal

[0421] A device owned by the user, such as a smartphone or tablet.

[0422] It receives the data collected from the sensors and sends the data to the server.

[0423] Receives analysis results from the server and notifies the user.

[0424] 3. Server

[0425] A computer system for analyzing the received data.

[0426] Analyzes activity, heart rate, and location information to assess health and stress levels.

[0427] Generate the necessary advice and send it to the device.

[0428] 4. Means of notification

[0429] Analysis results and advice are notified to the user via the device.

[0430] Use pop-up notifications, in-app messages, and push notifications.

[0431] Program processing

[0432] sensor

[0433] The sensor measures your dog's activity, heart rate, and location information at regular intervals and sends the data to the device. For example, the sensor measures your dog's movement every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location using a GPS sensor.

[0434] Terminal

[0435] The device sends the data received from the sensor to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The sent data includes a timestamp, making it clear when the measurement was made.

[0436] server

[0437] The server works with an AI model to analyze the received data and estimate stress levels and health status based on the collected data. Specifically, the server performs time-series analysis of activity data to assess whether the dog is getting enough exercise. It statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It also uses location data to generate advice on the frequency and range of walks.

[0438] Notification means

[0439] The device that receives the analysis results notifies the user of the results. For example, when the device receives the analysis results from the server, it will notify the user with specific advice such as "Take a walk for at least 30 minutes today." If the heart rate is abnormally high, it will warn the user that "Your heart rate is high, so we recommend that you take your pet to the veterinarian."

[0440] The system of the present invention further includes a means for estimating the stress level of an animal and generating advice on appropriate care methods, and a means for suggesting to the user the timing of walking the animal and the amount of exercise based on the analysis results, making it easier for pet owners to provide appropriate care for their pets. In this way, pet owners can efficiently manage their pet's health and improve the quality of life for both the owner and their pet dog.

[0441] The processing flow will be explained below.

[0442] Step 1:

[0443] Data collection by sensors

[0444] The sensor is built into your dog's collar or harness and measures your dog's activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor) every minute. This data is temporarily stored in the sensor's internal memory.

[0445] Step 2:

[0446] Send data to the device

[0447] The sensor transmits the collected data via Bluetooth to the device, which receives the data and clears it from the sensor's internal memory.

[0448] Step 3:

[0449] Sending data from the device to the server

[0450] The device sends the received data to the server in real time, including a timestamp to clarify when the measurement was made.

[0451] Step 4:

[0452] Data analysis by server

[0453] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[0454] Step 5:

[0455] Generate analysis results

[0456] The server uses the analysis results to assess the dog's stress level and health condition, and generates appropriate care advice, including specific suggestions such as "Take a walk for at least 30 minutes today" or "Your heart rate is high, so we recommend you take your dog to the vet."

[0457] Step 6:

[0458] Sending analysis results to the device

[0459] The server sends the generated analysis results to the terminal, which receives the results and prepares to notify the user.

[0460] Step 7:

[0461] User Notification

[0462] The device will notify the user of the analysis results from the server via pop-up displays, in-app messages, push notifications, etc. The user can then take care of their dog based on the notification and provide feedback as needed.

[0463] Step 8:

[0464] Get feedback and learn

[0465] Users provide feedback through their devices, such as by sending a comment like, "Today's walking advice was helpful." The server receives this feedback and incorporates it into the AI ​​model to help improve analysis accuracy.

[0466] The above processing steps realize a system that manages the physical condition and behavior of pet dogs in real time and provides advice to owners on how to provide appropriate care.

[0467] Example 1

[0468] 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."

[0469] When it comes to pet health management, it is difficult for owners to monitor their dog's physical condition and behavior in real time. Also, there may be delays in noticing that their dog is stressed or their health is deteriorating. Therefore, an effective system is needed to provide prompt and appropriate care.

[0470] 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.

[0471] In this invention, the server includes: means for measuring the activity level, heart rate, and location information of the animal using a sensor; terminal means for receiving data obtained from the sensor via Bluetooth and transmitting the time-stamped data to the server in real time; means for analyzing the data received from the terminal means, evaluating the health condition and stress level of the animal, and generating appropriate care advice; and means for notifying the user of the analysis results of the server means as a push notification or an in-app message. This makes it possible to monitor the activity level, heart rate, and location information of a pet dog in real time, quickly evaluate the health condition, and provide appropriate care advice as needed.

[0472] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[0473] The "terminal means" is a device that receives data acquired from the sensor via Bluetooth and transmits the data with a timestamp to the server in real time.

[0474] The "server means" is a computer system that serves to analyze data received from the terminal means, evaluate the health condition and stress level of the animal, and generate appropriate care advice.

[0475] "Analysis results" refers to evaluations and diagnostic information obtained by processing data received by the server means.

[0476] "Push notification" is a function that displays analysis results and advice to users in real time via their device.

[0477] "Activity" is a measurement that indicates the degree of movement or activity of an animal.

[0478] "Heart rate" is a measurement of the number of times an animal's heart beats within a given period of time.

[0479] "Location information" is geographical data that indicates the current location of an animal.

[0480] "Bluetooth" is a short-range wireless communication technology used to send and receive data between sensors and terminal devices.

[0481] A "timestamp" is information that indicates the date and time when data was collected or transmitted.

[0482] "Care advice" refers to recommendations and warnings regarding animal health care that are generated by the server means based on the analysis results.

[0483] "Health status" is a collection of indicators that indicate the degree of physical and mental well-being of an animal.

[0484] "Stress level" is an index that evaluates the degree of stress an animal is experiencing.

[0485] The present invention is a system for managing the physical condition and behavior of a pet dog in real time, and its main components include a sensor, a terminal, a server, and a notification means. The details of each component and their operation will be explained below.

[0486] sensor

[0487] The sensors are attached to your dog's collar or harness and measure activity, heart rate, and location information. For example, an acceleration sensor detects your dog's movements, a heart rate sensor measures its heart rate, and a GPS sensor obtains its location information. These data are measured every minute and sent to your device via Bluetooth. Specific sensor hardware includes an acceleration sensor, heart rate sensor, and GPS sensor.

[0488] Terminal

[0489] The device is a smartphone or tablet owned by the user. The device receives data acquired from the sensor via Bluetooth and transmits it to the server in real time using an HTTP POST request. The transmitted data includes a timestamp, making it clear when the data was measured. The device's software includes an application that receives data from the sensor and a communication module that transmits the data to the server.

[0490] server

[0491] The server analyzes the data received from the device and evaluates the dog's health condition and stress level. It uses an AI model to analyze activity data, heart rate data, and location data to evaluate the animal's movement patterns and heart rate trends and detect abnormalities. Based on the analysis results, it generates appropriate care advice and sends it to the device. The server software includes an AI model for data analysis and logic for generating care advice.

[0492] Notification means

[0493] Once the device receives the analysis results from the server, it immediately displays them to the user as a push notification or in-app message. For example, if today's walk time is short, the device will display advice such as "Try to take a walk for at least 30 minutes today." If the heart rate is abnormally high, the device will display a warning such as "Your heart rate is high. We recommend that you take your pet to the vet."

[0494] Specific examples

[0495] A specific scenario for actually using a dog health management system is as follows: A sensor is attached to the dog's collar, and the dog starts walking. The sensor measures the dog's activity level, heart rate, and location every minute and sends the data to the device. The device receives this data via Bluetooth and sends it to the server in real time. The server analyzes the received data and determines that the dog's stress level is high. The server generates advice such as "Your dog's stress level is high, so we recommend continuing your walk a little longer" and sends it to the device. The device then notifies the user of this advice via push notification.

[0496] Prompt Sentence Examples

[0497] We have developed a health management system for your pet dog. This system consists of sensors, terminals, a server, and a notification method, and measures your dog's activity level, heart rate, and location information, and analyzes it in real time to provide appropriate advice.

[0498] Sensor (e.g. attached to your dog's collar):

[0499] Activity (acceleration), heart rate, and location information are measured every minute.

[0500] Device (e.g. user's smartphone):

[0501] The data from the sensor is received via Bluetooth and sent to the server via an HTTP POST request.

[0502] server:

[0503] The received data is analyzed using an AI model to assess your dog's stress level and health condition.

[0504] Generate the necessary advice and send it to your device.

[0505] Notification method:

[0506] The device will then send a push notification to the user with the analysis results (e.g., "Please take a walk of at least 30 minutes today").

[0507] This system allows you to monitor your dog's health in real time and provide appropriate care.

[0508] In such an embodiment, the present invention can efficiently manage the health of pet dogs, improving the quality of life for owners and their pet dogs.

[0509] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0510] Step 1:

[0511] Data Measurement

[0512] The sensor measures your dog's activity (acceleration), heart rate, and location information every minute. The sensor inputs are your dog's movements, heart rate, and geographic location, and processes the data based on these inputs to generate measurement results. Specifically, the acceleration sensor collects activity data, the heart rate sensor measures heart rate data, and the GPS sensor obtains location data. These measurement results are obtained as output.

[0513] Step 2:

[0514] Data transmission

[0515] The sensor sends the measured data to the terminal via Bluetooth. The sensor input is the measurement results obtained in step 1, and the data is packaged using Bluetooth communication and sent to the terminal. Specifically, the sensor aggregates the measurement data every minute and sends it to the terminal via Bluetooth. The terminal receives this data.

[0516] Step 3:

[0517] Data reception

[0518] The device receives data sent from the sensor via Bluetooth. The device inputs data packets from the sensor, which are converted into an internal data format for processing. Specifically, the device analyzes the received data packets and stores them as activity data, heart rate data, and location information data.

[0519] Step 4:

[0520] Data transmission (server)

[0521] The terminal sends the received data to the server in real time using an HTTP POST request. The input to the terminal is the data received in step 3, which is time-stamped and sent to the server. Specifically, the terminal analyzes the data packets received from the sensor, generates an HTTP POST request, and sends it to the server. The server receives this data.

[0522] Step 5:

[0523] Data analysis

[0524] The server analyzes the data received from the device. The server's input is the data sent from the device, and it uses an AI model to analyze this data. Specifically, it analyzes activity data, heart rate data, and location data to evaluate health status and stress levels and detect any abnormalities. The output is the analysis results and appropriate care advice.

[0525] Step 6:

[0526] Advice Generation

[0527] The server generates appropriate care advice based on the results of the data analysis. The input is the analysis result from step 5, and advice and warning messages are generated based on this. Specifically, the server evaluates the analysis result, generates the necessary care advice and warning, and creates a data packet to send to the terminal.

[0528] Step 7:

[0529] Receive advice

[0530] The terminal receives the analysis results and advice sent from the server. The terminal inputs data packets from the server, which it analyzes and prepares to notify the user. Specifically, the terminal analyzes the data packets received in the HTTP response and generates the notification content.

[0531] Step 8:

[0532] User Notification

[0533] The device notifies the user of the analysis results and care advice. The input is the data received in step 7, which is displayed to the user as a push notification or in-app message. Specifically, the device sets a push notification to notify the user of advice such as "Please take your pet for a walk for at least 30 minutes today" or "Your pet's heart rate is high, so we recommend you take it to the vet."

[0534] This process allows you to monitor your dog's health in real time and provide appropriate care advice quickly.

[0535] (Application example 1)

[0536] 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."

[0537] Currently, there are limited means for understanding the health status and behavior of pet owners in real time, making it difficult for owners to provide appropriate care. Furthermore, because there is no connection with pet care services offered at physical stores, it is difficult for users to find the optimal care method. The present invention aims to provide a system for efficiently managing the health of pets and facilitating the provision of services at physical stores.

[0538] 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.

[0539] In this invention, the server includes: means for measuring the activity level, heart rate, and location information of the animal using a sensor; terminal means for receiving data acquired from the sensor; means for analyzing the data received from the terminal means and evaluating the animal's health condition; means for notifying the user of the analysis results of the server means via the terminal means; means for generating recommendations for providing services at a physical store; and means for notifying the user of the recommendations. This allows users to understand the health condition of their beloved dog in real time and provide appropriate care. Furthermore, by linking with pet care services at physical stores, owners can receive optimal services.

[0540] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[0541] A "terminal" is a device that receives data obtained from a sensor and transmits it to a server.

[0542] The "server" is a computer system that analyzes data received from the terminal means, evaluates the health condition of the animal, and notifies the results of the analysis.

[0543] A "physical store" is a place that users can visit in person, and is a facility where pet care services and the like are provided.

[0544] "Recommendations" are useful advice or suggestions for users that are generated based on the results of analysis on the server.

[0545] "Notification means" refers to a method for communicating analysis results and recommendations to users via their devices.

[0546] The present invention is a system for managing the physical condition and behavior of a pet dog, and includes a sensor, a terminal, a server, and a notification means. Specific embodiments of the system are described below.

[0547] System Configuration

[0548] 1. Sensor

[0549] The sensors attached to your dog's collar or harness measure activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor). The sensors collect data at regular intervals (for example, every minute) and send it to your device via Bluetooth.

[0550] 2. Terminal

[0551] The user's smartphone or tablet receives data from the sensor and transmits it to the server in real time. The transmitted data includes a timestamp to indicate when the measurement was made. The device sends the data to the server using an HTTP POST request.

[0552] 3. Server

[0553] The server is a computer system located in the cloud that analyzes the received data. Using AI models (time series analysis model, anomaly detection model), stress levels and health conditions are estimated based on the collected data. For example, activity data is analyzed over time to determine whether the dog is getting enough exercise. Heart rate data is statistically analyzed and compared with normal heart rates to detect abnormalities. Location data is used to generate advice on the frequency and range of walks.

[0554] 4. Means of notification

[0555] The device receives the analysis results from the server and notifies the user of the results. Specifically, when the device receives the analysis results from the server, it will notify the user of specific advice such as "Take a walk for at least 30 minutes today." If the heart rate is abnormally high, it will warn the user, "Your heart rate is high, so we recommend that you take your pet to the veterinarian."

[0556] Specific examples

[0557] For example, if your dog is not getting enough exercise, the server will generate instructions such as "Set today's walking time to at least 30 minutes." If the dog's heart rate is higher than normal, the server will send a notification to the user saying, "Your dog's heart rate is higher than normal. We recommend that you see a veterinarian." Based on these results, users can efficiently manage their dog's health.

[0558] Prompt Sentence Examples

[0559] prompt:

[0560] Please analyze my dog's activity data (acceleration 34.5, heart rate 115, location information: 35.6895, 139.6917). Please tell me the health condition and proper care method.

[0561] Expected answer:

[0562] Analysis of your dog's activity data has revealed that his heart rate is higher than normal, indicating signs of stress. It's possible that he's not getting enough exercise, so we recommend increasing your walk time. If the heart rate persists, we recommend consulting a veterinarian.

[0563] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0564] Step 1:

[0565] The sensor measures your dog's activity level, heart rate, and location at regular intervals and transmits the data to your device via Bluetooth.

[0566] Input: Data collected from accelerometer, heart rate sensor, and GPS sensor

[0567] Output: Measurement data sent to the device

[0568] Specific operation: The sensor measures your dog's movements every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location information using a GPS sensor.

[0569] Step 2:

[0570] The device transmits the data received from the sensor to the server in real time.

[0571] Input: Measurement data sent from the sensor via Bluetooth

[0572] Output: Data sent to the server as an HTTP POST request

[0573] Specific operation: The device receives activity, heart rate, and location information from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The data includes a timestamp to clarify the timing of the measurement.

[0574] Step 3:

[0575] The server works with an AI model to analyze the received data and estimate stress levels and health status based on the collected data.

[0576] Input: Measurement data sent from the device

[0577] Output: Health status assessment and stress level estimation results

[0578] How it works: The server performs time-series analysis of activity data to assess whether your dog is getting enough exercise. It statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It uses location data to generate advice on the frequency and range of walks.

[0579] Step 4:

[0580] The server generates recommendations for providing services in physical stores based on the analysis results.

[0581] Input: Health status assessment and stress level estimation results

[0582] Output: Recommendations

[0583] Specific operation: Based on the analysis results, the server generates recommendations to suggest pet care services and products that can be provided in physical stores.

[0584] Step 5:

[0585] The server sends the recommendations to the device and provides them to the user through notifications.

[0586] Input: Recommendations

[0587] Output: Recommendations communicated to the user

[0588] Specific behavior: The server sends the generated recommendations to the device, and the device provides the recommendations to the user via a pop-up or push notification, such as specific advice such as "Take a walk for at least 30 minutes today" or a warning such as "Your heart rate is high, so we recommend you see a veterinarian."

[0589] 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.

[0590] This invention combines a system for managing a pet dog's physical condition and behavior with an emotion engine that recognizes the user's emotions. This system allows owners to understand their pet's health and behavior in real time, and also provides appropriate care advice according to the owner's emotional state.

[0591] System Configuration

[0592] 1. Sensor

[0593] It is incorporated into your dog's collar or harness.

[0594] Measures activity level (acceleration sensor), heart rate (heart rate sensor), and location information (GPS sensor).

[0595] Data is collected at regular intervals and sent to the terminal.

[0596] 2. Terminal

[0597] A device owned by the user, such as a smartphone or tablet.

[0598] It receives the data collected from the sensors and sends the data to the server.

[0599] Receives analysis results from the server and notifies the user.

[0600] 3. Server

[0601] A computer system for analyzing the received data.

[0602] Analyzes activity, heart rate, and location information to assess health and stress levels.

[0603] Generate the necessary advice and send it to the device.

[0604] Advice is tailored using user emotional information obtained from the emotion engine.

[0605] 4. Emotion Engine

[0606] An engine that recognizes the user's voice and facial expressions and analyzes their emotional state.

[0607] The information is received by the terminal and transmitted to the server.

[0608] 5. Means of notification

[0609] Analysis results and advice are notified to the user via the device.

[0610] Use pop-up notifications, in-app messages, and push notifications.

[0611] Program processing

[0612] sensor

[0613] The sensor measures your dog's activity, heart rate, and location information at regular intervals and sends the data to the device. For example, the sensor measures your dog's movement every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location using a GPS sensor.

[0614] Terminal

[0615] The device sends the data received from the sensor to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The sent data includes a timestamp, making it clear when the measurement was made.

[0616] server

[0617] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[0618] Emotion Engine

[0619] The emotion engine recognizes emotions from the user's voice and facial expressions and receives that information on the device. For example, the emotion engine analyzes the user's tone of voice and facial expressions while they are speaking through the camera to assess whether they are feeling stressed.

[0620] Server-based analysis results generation and adjustment

[0621] The server adjusts the content and tone of the advice based on the user's emotional information obtained from the emotion engine. For example, if the user is feeling stressed, the server will suggest simple care methods to reduce stress.

[0622] Notification means

[0623] The device that receives the analysis results notifies the user of the results. For example, when the device receives the analysis results from the server, it will notify the user with specific advice such as, "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[0624] The above processing steps realize a system that provides more appropriate and effective care by taking into consideration the owner's emotional state in addition to the dog's physical condition and behavioral management.

[0625] The processing flow will be explained below.

[0626] Step 1:

[0627] Data collection by sensors

[0628] The sensor is built into your dog's collar or harness and measures your dog's activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor) every minute. This data is temporarily stored in the sensor's internal memory.

[0629] Step 2:

[0630] Send data to the device

[0631] The sensor transmits the collected data via Bluetooth to the device, which receives the data and clears the data from the sensor's internal memory.

[0632] Step 3:

[0633] Sending data from the device to the server

[0634] The device transmits the received data to the server in real time, and the transmitted data includes a timestamp to clarify when the measurement was made.

[0635] Step 4:

[0636] Data analysis by server

[0637] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[0638] Step 5:

[0639] Recognizing user emotions with an emotion engine

[0640] The emotion engine uses the device's camera and microphone to recognize the user's emotions. For example, the emotion engine analyzes the user's voice tone to assess their emotional state, such as stress or fatigue. It also uses facial expression recognition technology to read emotions from the user's facial expressions.

[0641] Step 6:

[0642] Server-generated analysis results and advice

[0643] The server adjusts the analysis results based on the user's emotional information obtained from the emotion engine, combined with the dog's health data, and if the user is feeling stressed, it will include simple care methods to relieve stress.

[0644] Step 7:

[0645] Sending analysis results to the device

[0646] The server then sends the generated analysis results to the device, which include advice based on the user's emotional state.

[0647] Step 8:

[0648] User Notification

[0649] The device receives the analysis results from the server and notifies the user. Notifications are displayed as pop-ups, in-app messages, or push notifications. For example, the device provides specific advice such as, "We recommend that you take a walk of at least 30 minutes. You seem tired, so please take regular breaks."

[0650] Step 9:

[0651] Getting user feedback

[0652] Users can provide feedback on the usefulness of the advice through their device, for example by sending a comment such as "Today's advice was helpful."

[0653] Step 10:

[0654] Server-based feedback learning

[0655] The server receives feedback from users and incorporates it into the AI ​​model, helping to improve the accuracy of analysis and the quality of advice in future sessions.

[0656] The above processing steps realize a system that provides care advice that takes into account the user's emotional state as well as the dog's physical condition and behavior management, enabling owners to provide more effective and appropriate care for their pets.

[0657] Example 2

[0658] 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."

[0659] Conventional animal health management systems simply monitor the animal's activity level, heart rate, and location, and are unable to provide care advice that takes into account the owner's psychological state, such as emotions and stress. As a result, the system does not properly reflect the owner's own stress or fatigue, and therefore sometimes does not provide optimal care advice.

[0660] 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.

[0661] In this invention, the server includes: means for measuring activity level, heart rate, and location information using sensors for managing the animal's physical condition and behavior; an information processing terminal for receiving data acquired from the sensors; means for analyzing the data received from the information processing terminal and evaluating the animal's health condition; means for notifying the user of the analysis results of the server device via the information processing terminal; an emotion analysis engine for analyzing the user's voice and facial expressions to grasp their emotional state; and means for adjusting the analysis results and advice content based on the emotion information acquired by the emotion analysis engine. This makes it possible to provide more appropriate and effective care advice by taking into account the owner's emotional state in addition to the animal's physical condition and behavior management.

[0662] "Animal" refers to any living creature kept as a domestic animal or pet, including, but not limited to, a pet dog.

[0663] "Sensor" refers to a measuring device for measuring data such as an animal's activity level, heart rate, and location information.

[0664] "Activity level" is data that indicates the degree of movement or movement that an animal underwent within a certain period of time.

[0665] "Heart rate" is data indicating the number of heartbeats an animal has within a certain period of time.

[0666] "Location information" is data about an animal's current location and movement route obtained using GPS and other devices.

[0667] An "information processing terminal" is a device that receives data collected from sensors and transmits it to a server, and includes smartphones, tablets, etc.

[0668] The "server device" is a computer system that analyzes data sent from the information processing terminal, evaluates the health condition of the animals, and generates analysis results.

[0669] An "emotion analysis engine" is a system that analyzes a user's voice and facial expressions to understand their emotional state.

[0670] The "analysis results" are the output results of evaluations and diagnoses made by the server device based on data acquired from sensors and emotion analysis engines.

[0671] "Means of notification" refers to the method used to notify users of analysis results and advice, including pop-up notifications, in-app messages, and push notifications.

[0672] This invention is a system for managing the physical condition and behavior of animals, and uses the following hardware and software to acquire, analyze, and notify data.

[0673] Hardware Configuration

[0674] 1. Sensor

[0675] Various sensors are incorporated into the animal's collar or harness.

[0676] The sensors used include an acceleration sensor that measures activity, a heart rate sensor that measures heart rate, and a GPS sensor that obtains location information.

[0677] These sensors collect data at regular intervals and transmit it to an information processing terminal.

[0678] 2. Information processing terminal

[0679] It is a device such as a smartphone or tablet that the user owns.

[0680] The data collected from the sensors is received via Bluetooth and sent to the server in real time using HTTP POST requests.

[0681] 3. Server Device

[0682] The server device is a powerful computer system for analyzing the received data.

[0683] The server uses AI models to perform time series analysis of activity data, statistical analysis of heart rate data, and geographic information analysis of location data.

[0684] 4. Sentiment Analysis Engine

[0685] An emotion analysis engine is a system for analyzing a user's voice and facial expressions.

[0686] A microphone is used for voice analysis and a camera for facial expression analysis.

[0687] The obtained emotion information is transmitted to the server via the information processing terminal.

[0688] Program processing

[0689] Sensor Processing

[0690] The sensor measures the animal's activity, heart rate, and location information at regular intervals and sends the data to an information processing terminal. For example, the sensor measures the dog's activity every minute with an acceleration sensor, records the heart rate with a heart rate sensor, and obtains location information with a GPS sensor.

[0691] Terminal Processing

[0692] The device receives data from the sensor and sends it to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and sends it to the server via an HTTP POST request. The data includes a timestamp to clarify the timing of the measurement.

[0693] Server Processing

[0694] The server analyzes the received data using an AI model. Specifically, it performs time-series analysis of activity data to evaluate whether the amount of exercise is appropriate, statistically analyzes heart rate data to detect abnormalities, and generates advice on the frequency and range of walks based on location data.

[0695] Sentiment Analysis Engine

[0696] The emotion analysis engine recognizes emotions from the user's voice and facial expressions, for example, by analyzing the user's tone of voice and facial expressions through the camera when they speak, and assessing the user's stress level.

[0697] Server-based analysis results generation and adjustment

[0698] The server adjusts the content and tone of the advice based on the user's emotional information obtained from the emotion analysis engine. For example, if the user is feeling stressed, it generates simple care advice to reduce stress. Examples of specific advice include, "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[0699] Notification means

[0700] The device receives the analysis results from the server and notifies the user using pop-up notifications, in-app messages, and push notifications, and displays specific advice such as "Your dog needs at least a 30-minute walk today."

[0701] Examples and prompts

[0702] Specific examples

[0703] The sensor measures your dog's activity every minute and sends the data to an information processing terminal.

[0704] The device sends the received data to a server, which then analyzes the data using an AI model.

[0705] The emotion analysis engine analyzes the user's voice and facial expressions and sends emotional information to the server.

[0706] The server adjusts the advice based on the analysis results, and the device notifies the user of the analysis results.

[0707] Prompt Sentence Examples

[0708] "What advice would be effective on how to care for a user's dog if they are stressed?"

[0709] "How can I analyze my dog's activity and heart rate data to assess his health?"

[0710] In this way, a system is realized that manages the physical condition and behavior of a beloved dog while providing appropriate care advice that also takes into account the user's emotional state.

[0711] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0712] Step 1:

[0713] Sensor data acquisition

[0714] The sensor acquires the animal's activity, heart rate, and location information at regular intervals. The sensor's inputs are the animal's physical activity, location, and heart rate. The sensor measures these inputs and generates activity data, heart rate data, and location data. This data is temporarily stored in the sensor and then sent to an information processing device. For example, an acceleration sensor measures the animal's movement over one minute, a heart rate sensor simultaneously records the heart rate, and a GPS sensor identifies the animal's location.

[0715] Step 2:

[0716] Sending data to the device

[0717] The data acquired by the sensor is sent to the information processing terminal. The input to the terminal is data from the sensor, and the output is data sent to the server. The terminal receives activity level, heart rate, and location information from the sensor using Bluetooth, and sends this information along with the received timestamp to the server via an HTTP POST request. Here, the terminal formats the data and converts it into a format that is easy for the server to analyze. Specifically, the terminal compiles the data received from the sensor and sends it to the server every minute.

[0718] Step 3:

[0719] Data analysis by server

[0720] The server receives and analyzes the data sent from the device. The server's inputs are activity data, heart rate data, and location data sent from the device. The server analyzes this data using an AI model and generates an output that evaluates the animal's health, as well as analytical results on exercise volume and stress levels. Specifically, the server performs a time series analysis of the activity data to evaluate whether exercise is being performed appropriately. It also statistically analyzes the heart rate data to detect abnormalities. The location data is used to evaluate the frequency and range of walks using geographic information analysis.

[0721] Step 4:

[0722] Emotion analysis using an emotion analysis engine

[0723] The emotion analysis engine analyzes the user's voice and facial expressions to understand their emotional state. The emotion analysis engine's input is the user's voice data and facial expression data, and its output is information about their emotional state. The engine uses a microphone and camera to analyze the user's tone of voice and facial expressions. For example, the analysis results may evaluate whether the user is feeling stressed. This information is sent to the information processing terminal and then to the server.

[0724] Step 5:

[0725] Server-based analysis results generation and adjustment

[0726] The server receives the user's emotional information obtained from the emotion analysis engine and adjusts the analysis results and advice content. The server receives data based on the animal's health assessment and the user's emotional information. The server integrates this data and generates care advice based on the user's stress level. For example, if the user is feeling stressed, the server will generate advice such as, "We recommend taking a short walk to reduce stress."

[0727] Step 6:

[0728] User notification via information processing terminal

[0729] The device receives analysis results and advice from the server and notifies the user. The input to the device is the analysis results and advice sent from the server, and the output is the notification to the user. Notification methods include pop-up notifications, in-app messages, and push notifications. For example, a notification may be sent to the user saying, "Your dog needs to be walked for at least 30 minutes today."

[0730] Through these steps, the system is able to provide appropriate care advice that takes into account not only the animal's physical condition and behavior, but also the user's emotional state.

[0731] (Application example 2)

[0732] 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."

[0733] Conventional pet dog health management systems only provide general care advice based on the dog's health condition, without taking into account the owner's emotional state. As a result, it is difficult to provide appropriate advice when the owner is stressed or in a specific emotional state. Thus, there is a need for a system that provides more appropriate care methods that take into account the owner's emotional state.

[0734] The identification process 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 analyzing data acquired from the sensor and evaluating the health condition of the animal, means including an emotion engine for analyzing the emotional state of the user, and means for generating advice based on the analysis results of the server means and the user's emotional information and notifying the user via the terminal means. This makes it possible to provide advice that takes the owner's emotional state into consideration.

[0735] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[0736] The "terminal means" is a device that receives data acquired from the sensor and transmits the data to the server means.

[0737] The "server means" is a computer system for analyzing data received from the terminal means and evaluating the health status of the animals.

[0738] An "emotion engine" is a device or system for analyzing a user's emotional state, and determines the user's emotions based on data such as voice and facial expressions.

[0739] The "analysis results" are information about the health condition and stress level of the animal that is generated by the server means by analyzing the data received from the sensor.

[0740] The "means for generating advice" is a device or computer program that allows the server means to create advice on appropriate care methods based on the analysis results and the user's emotional information.

[0741] The "notifying means" is a device or function for notifying the user of the generated advice via the terminal means.

[0742] This invention is a system for managing the physical condition and behavior of a pet dog, and is implemented using the following devices and software.

[0743] The system includes the following main components: a sensor, a terminal means, a server means, an emotion engine, and a notification means.

[0744] sensor

[0745] The sensors worn by pet dogs are measuring devices that measure the animal's activity, heart rate, and location information. Examples include acceleration sensors, heart rate sensors, and GPS sensors. These sensors are incorporated into the dog's collar or harness, and collect data at regular intervals and transmit it to a terminal via Bluetooth.

[0746] Terminal means

[0747] The terminal means is a device such as a smartphone or tablet that receives data from the sensor in real time and transmits it to the server means. For example, the terminal means transmits the amount of activity, heart rate, and location information received from the sensor via Bluetooth to the server using an HTTP POST request.

[0748] Server Means

[0749] The server means is a computer system for analyzing the received data. The specific analysis is performed as follows:

[0750] Activity data is analyzed over time to evaluate your dog's physical activity.

[0751] Heart rate data is statistically analyzed and compared with normal heart rates to detect abnormalities.

[0752] Advice is generated regarding the frequency and range of walks based on location data.

[0753] The server means adjusts the content and tone of advice based on the user's emotional information obtained from the emotion engine.

[0754] Emotion Engine

[0755] An emotion engine is a device or system for analyzing a user's voice and facial expressions to assess their emotional state. For example, an emotion engine may analyze a user's voice tone and facial expressions through a camera while they are speaking to assess whether they are feeling stressed.

[0756] Notification means

[0757] The notification means has a function to notify the user of the analysis results and advice. Information is notified to the user via the terminal means as push notifications or in-app messages. For example, when the terminal receives the analysis results from the server, it notifies the user with specific advice such as "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[0758] Specific examples

[0759] For example, if your dog is healthy but doesn't get enough exercise, you'll receive a notification saying, "Your dog is healthy, but needs more exercise." If your emotional state is analyzed as "stressed," you'll receive a notification saying, "Your dog is healthy, but needs more exercise. Please take some time to relax."

[0760] Prompt Sentence Examples

[0761] "It analyzes the user's vocal tone and facial expressions to assess their current emotional state. If the emotional state is stress, it will add a message to your dog's health advice about taking time to relax."

[0762] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0763] Step 1:

[0764] The sensor measures your dog's activity, heart rate, and location. The sensor collects this data at regular intervals and sends it to the device via Bluetooth. The input is the measured data, and the output is the data sent to the device.

[0765] Step 2:

[0766] The device receives data from the sensor and sends it to the server in real time. The device receives data via Bluetooth and sends it to the server using an HTTP POST request. The input is the data received from the sensor and the output is the data sent to the server.

[0767] Step 3:

[0768] The server analyzes the received data. The server performs time-series analysis of the activity data, statistical analysis of the heart rate data, and evaluates the frequency and range of walks based on the location data. The input is the data sent from the device, and the output is the analysis results.

[0769] Step 4:

[0770] The emotion engine analyzes the user's voice and facial expressions to evaluate their emotional state. For example, the emotion engine analyzes the user's tone of voice and facial expressions through a camera while they are speaking. The input is audio and video data, and the output is analyzed emotional information.

[0771] Step 5:

[0772] The server generates advice based on the analysis results and emotional information. The server creates advice with appropriate content and tone, taking into account the user's emotional state. The input is the analysis results and emotional information, and the output is the generated advice.

[0773] Step 6:

[0774] The device receives advice from the server and notifies the user. The device provides specific advice to the user using push notifications or in-app messages. The input is the advice sent from the server, and the output is the message notified to the user.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] [Third embodiment]

[0779] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0780] 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.

[0781] 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).

[0782] 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.

[0783] 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.

[0784] 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).

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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."

[0791] The present invention is a system for managing the physical condition and behavior of pet dogs, which includes sensors, terminals, a server, and notification means. This system allows owners to understand the health condition of their pet dogs in real time and provide appropriate care.

[0792] System Configuration

[0793] 1. Sensor

[0794] It is incorporated into your dog's collar or harness.

[0795] Measures activity (acceleration), heart rate, and location information.

[0796] Data is collected at regular intervals and sent to the terminal.

[0797] 2. Terminal

[0798] A device owned by the user, such as a smartphone or tablet.

[0799] It receives the data collected from the sensors and sends the data to the server.

[0800] Receives analysis results from the server and notifies the user.

[0801] 3. Server

[0802] A computer system for analyzing the received data.

[0803] Analyzes activity, heart rate, and location information to assess health and stress levels.

[0804] Generate the necessary advice and send it to the device.

[0805] 4. Means of notification

[0806] Analysis results and advice are notified to the user via the device.

[0807] Use pop-up notifications, in-app messages, and push notifications.

[0808] Program processing

[0809] sensor

[0810] The sensor measures your dog's activity, heart rate, and location information at regular intervals and sends the data to the device. For example, the sensor measures your dog's movement every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location using a GPS sensor.

[0811] Terminal

[0812] The device sends the data received from the sensor to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The sent data includes a timestamp, making it clear when the measurement was made.

[0813] server

[0814] The server works with an AI model to analyze the received data and estimate stress levels and health status based on the collected data. Specifically, the server performs time-series analysis of activity data to assess whether the dog is getting enough exercise. It statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It also uses location data to generate advice on the frequency and range of walks.

[0815] Notification means

[0816] The device that receives the analysis results notifies the user of the results. For example, when the device receives the analysis results from the server, it will notify the user with specific advice such as "Take a walk for at least 30 minutes today." If the heart rate is abnormally high, it will warn the user that "Your heart rate is high, so we recommend that you take your pet to the veterinarian."

[0817] The system of the present invention further includes a means for estimating the stress level of an animal and generating advice on appropriate care methods, and a means for suggesting to the user the timing of walking the animal and the amount of exercise based on the analysis results, making it easier for pet owners to provide appropriate care for their pets. In this way, pet owners can efficiently manage their pet's health and improve the quality of life for both the owner and their pet dog.

[0818] The processing flow will be explained below.

[0819] Step 1:

[0820] Data collection by sensors

[0821] The sensor is built into your dog's collar or harness and measures your dog's activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor) every minute. This data is temporarily stored in the sensor's internal memory.

[0822] Step 2:

[0823] Send data to the device

[0824] The sensor transmits the collected data via Bluetooth to the device, which receives the data and clears it from the sensor's internal memory.

[0825] Step 3:

[0826] Sending data from the device to the server

[0827] The device sends the received data to the server in real time, including a timestamp to clarify when the measurement was made.

[0828] Step 4:

[0829] Data analysis by server

[0830] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[0831] Step 5:

[0832] Generate analysis results

[0833] The server uses the analysis results to assess the dog's stress level and health condition, and generates appropriate care advice, including specific suggestions such as "Take a walk for at least 30 minutes today" or "Your heart rate is high, so we recommend you take your dog to the vet."

[0834] Step 6:

[0835] Sending analysis results to the device

[0836] The server sends the generated analysis results to the terminal, which receives the results and prepares to notify the user.

[0837] Step 7:

[0838] User Notification

[0839] The device will notify the user of the analysis results from the server via pop-up displays, in-app messages, push notifications, etc. The user can then take care of their dog based on the notification and provide feedback as needed.

[0840] Step 8:

[0841] Get feedback and learn

[0842] Users provide feedback through their devices, such as by sending a comment like, "Today's walking advice was helpful." The server receives this feedback and incorporates it into the AI ​​model to help improve analysis accuracy.

[0843] The above processing steps realize a system that manages the physical condition and behavior of pet dogs in real time and provides advice to owners on how to provide appropriate care.

[0844] Example 1

[0845] 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."

[0846] When it comes to pet health management, it is difficult for owners to monitor their dog's physical condition and behavior in real time. Also, there may be delays in noticing that their dog is stressed or their health is deteriorating. Therefore, an effective system is needed to provide prompt and appropriate care.

[0847] 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.

[0848] In this invention, the server includes: means for measuring the activity level, heart rate, and location information of the animal using a sensor; terminal means for receiving data obtained from the sensor via Bluetooth and transmitting the time-stamped data to the server in real time; means for analyzing the data received from the terminal means, evaluating the health condition and stress level of the animal, and generating appropriate care advice; and means for notifying the user of the analysis results of the server means as a push notification or an in-app message. This makes it possible to monitor the activity level, heart rate, and location information of a pet dog in real time, quickly evaluate the health condition, and provide appropriate care advice as needed.

[0849] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[0850] The "terminal means" is a device that receives data acquired from the sensor via Bluetooth and transmits the data with a timestamp to the server in real time.

[0851] The "server means" is a computer system that serves to analyze data received from the terminal means, evaluate the health condition and stress level of the animal, and generate appropriate care advice.

[0852] "Analysis results" refers to evaluations and diagnostic information obtained by processing data received by the server means.

[0853] "Push notification" is a function that displays analysis results and advice to users in real time via their device.

[0854] "Activity" is a measurement that indicates the degree of movement or activity of an animal.

[0855] "Heart rate" is a measurement of the number of times an animal's heart beats within a given period of time.

[0856] "Location information" is geographical data that indicates the current location of an animal.

[0857] "Bluetooth" is a short-range wireless communication technology used to send and receive data between sensors and terminal devices.

[0858] A "timestamp" is information that indicates the date and time when data was collected or transmitted.

[0859] "Care advice" refers to recommendations and warnings regarding animal health care that are generated by the server means based on the analysis results.

[0860] "Health status" is a collection of indicators that indicate the degree of physical and mental well-being of an animal.

[0861] "Stress level" is an index that evaluates the degree of stress an animal is experiencing.

[0862] The present invention is a system for managing the physical condition and behavior of a pet dog in real time, and its main components include a sensor, a terminal, a server, and a notification means. The details of each component and their operation will be explained below.

[0863] sensor

[0864] The sensors are attached to your dog's collar or harness and measure activity, heart rate, and location information. For example, an acceleration sensor detects your dog's movements, a heart rate sensor measures its heart rate, and a GPS sensor obtains its location information. These data are measured every minute and sent to your device via Bluetooth. Specific sensor hardware includes an acceleration sensor, heart rate sensor, and GPS sensor.

[0865] Terminal

[0866] The device is a smartphone or tablet owned by the user. The device receives data acquired from the sensor via Bluetooth and transmits it to the server in real time using an HTTP POST request. The transmitted data includes a timestamp, making it clear when the data was measured. The device's software includes an application that receives data from the sensor and a communication module that transmits the data to the server.

[0867] server

[0868] The server analyzes the data received from the device and evaluates the dog's health condition and stress level. It uses an AI model to analyze activity data, heart rate data, and location data to evaluate the animal's movement patterns and heart rate trends and detect abnormalities. Based on the analysis results, it generates appropriate care advice and sends it to the device. The server software includes an AI model for data analysis and logic for generating care advice.

[0869] Notification means

[0870] Once the device receives the analysis results from the server, it immediately displays them to the user as a push notification or in-app message. For example, if today's walk time is short, the device will display advice such as "Try to take a walk for at least 30 minutes today." If the heart rate is abnormally high, the device will display a warning such as "Your heart rate is high. We recommend that you take your pet to the vet."

[0871] Specific examples

[0872] A specific scenario for actually using a dog health management system is as follows: A sensor is attached to the dog's collar, and the dog starts walking. The sensor measures the dog's activity level, heart rate, and location every minute and sends the data to the device. The device receives this data via Bluetooth and sends it to the server in real time. The server analyzes the received data and determines that the dog's stress level is high. The server generates advice such as "Your dog's stress level is high, so we recommend continuing your walk a little longer" and sends it to the device. The device then notifies the user of this advice via push notification.

[0873] Prompt Sentence Examples

[0874] We have developed a health management system for your pet dog. This system consists of sensors, terminals, a server, and a notification method, and measures your dog's activity level, heart rate, and location information, and analyzes it in real time to provide appropriate advice.

[0875] Sensor (e.g. attached to your dog's collar):

[0876] Activity (acceleration), heart rate, and location information are measured every minute.

[0877] Device (e.g. user's smartphone):

[0878] The data from the sensor is received via Bluetooth and sent to the server via an HTTP POST request.

[0879] server:

[0880] The received data is analyzed using an AI model to assess your dog's stress level and health condition.

[0881] Generate the necessary advice and send it to your device.

[0882] Notification method:

[0883] The device will then send a push notification to the user with the analysis results (e.g., "Please take a walk of at least 30 minutes today").

[0884] This system allows you to monitor your dog's health in real time and provide appropriate care.

[0885] In such an embodiment, the present invention can efficiently manage the health of pet dogs, improving the quality of life for owners and their pet dogs.

[0886] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0887] Step 1:

[0888] Data Measurement

[0889] The sensor measures your dog's activity (acceleration), heart rate, and location information every minute. The sensor inputs are your dog's movements, heart rate, and geographic location, and processes the data based on these inputs to generate measurement results. Specifically, the acceleration sensor collects activity data, the heart rate sensor measures heart rate data, and the GPS sensor obtains location data. These measurement results are obtained as output.

[0890] Step 2:

[0891] Data transmission

[0892] The sensor sends the measured data to the terminal via Bluetooth. The sensor input is the measurement results obtained in step 1, and the data is packaged using Bluetooth communication and sent to the terminal. Specifically, the sensor aggregates the measurement data every minute and sends it to the terminal via Bluetooth. The terminal receives this data.

[0893] Step 3:

[0894] Data reception

[0895] The device receives data sent from the sensor via Bluetooth. The device inputs data packets from the sensor, which are converted into an internal data format for processing. Specifically, the device analyzes the received data packets and stores them as activity data, heart rate data, and location information data.

[0896] Step 4:

[0897] Data transmission (server)

[0898] The terminal sends the received data to the server in real time using an HTTP POST request. The input to the terminal is the data received in step 3, which is time-stamped and sent to the server. Specifically, the terminal analyzes the data packets received from the sensor, generates an HTTP POST request, and sends it to the server. The server receives this data.

[0899] Step 5:

[0900] Data analysis

[0901] The server analyzes the data received from the device. The server's input is the data sent from the device, and it uses an AI model to analyze this data. Specifically, it analyzes activity data, heart rate data, and location data to evaluate health status and stress levels and detect any abnormalities. The output is the analysis results and appropriate care advice.

[0902] Step 6:

[0903] Advice Generation

[0904] The server generates appropriate care advice based on the results of the data analysis. The input is the analysis result from step 5, and advice and warning messages are generated based on this. Specifically, the server evaluates the analysis result, generates the necessary care advice and warning, and creates a data packet to send to the terminal.

[0905] Step 7:

[0906] Receive advice

[0907] The terminal receives the analysis results and advice sent from the server. The terminal inputs data packets from the server, which it analyzes and prepares to notify the user. Specifically, the terminal analyzes the data packets received in the HTTP response and generates the notification content.

[0908] Step 8:

[0909] User Notification

[0910] The device notifies the user of the analysis results and care advice. The input is the data received in step 7, which is displayed to the user as a push notification or in-app message. Specifically, the device sets a push notification to notify the user of advice such as "Please take your pet for a walk for at least 30 minutes today" or "Your pet's heart rate is high, so we recommend you take it to the vet."

[0911] This process allows you to monitor your dog's health in real time and provide appropriate care advice quickly.

[0912] (Application example 1)

[0913] 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."

[0914] Currently, there are limited means for understanding the health status and behavior of pet owners in real time, making it difficult for owners to provide appropriate care. Furthermore, because there is no connection with pet care services offered at physical stores, it is difficult for users to find the optimal care method. The present invention aims to provide a system for efficiently managing the health of pets and facilitating the provision of services at physical stores.

[0915] 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.

[0916] In this invention, the server includes: means for measuring the activity level, heart rate, and location information of the animal using a sensor; terminal means for receiving data acquired from the sensor; means for analyzing the data received from the terminal means and evaluating the animal's health condition; means for notifying the user of the analysis results of the server means via the terminal means; means for generating recommendations for providing services at a physical store; and means for notifying the user of the recommendations. This allows users to understand the health condition of their beloved dog in real time and provide appropriate care. Furthermore, by linking with pet care services at physical stores, owners can receive optimal services.

[0917] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[0918] A "terminal" is a device that receives data obtained from a sensor and transmits it to a server.

[0919] The "server" is a computer system that analyzes data received from the terminal means, evaluates the health condition of the animal, and notifies the results of the analysis.

[0920] A "physical store" is a place that users can visit in person, and is a facility where pet care services and the like are provided.

[0921] "Recommendations" are useful advice or suggestions for users that are generated based on the results of analysis on the server.

[0922] "Notification means" refers to a method for communicating analysis results and recommendations to users via their devices.

[0923] The present invention is a system for managing the physical condition and behavior of a pet dog, and includes a sensor, a terminal, a server, and a notification means. Specific embodiments of the system are described below.

[0924] System Configuration

[0925] 1. Sensor

[0926] The sensors attached to your dog's collar or harness measure activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor). The sensors collect data at regular intervals (for example, every minute) and send it to your device via Bluetooth.

[0927] 2. Terminal

[0928] The user's smartphone or tablet receives data from the sensor and transmits it to the server in real time. The transmitted data includes a timestamp to indicate when the measurement was made. The device sends the data to the server using an HTTP POST request.

[0929] 3. Server

[0930] The server is a computer system located in the cloud that analyzes the received data. Using AI models (time series analysis model, anomaly detection model), stress levels and health conditions are estimated based on the collected data. For example, activity data is analyzed over time to determine whether the dog is getting enough exercise. Heart rate data is statistically analyzed and compared with normal heart rates to detect abnormalities. Location data is used to generate advice on the frequency and range of walks.

[0931] 4. Means of notification

[0932] The device receives the analysis results from the server and notifies the user of the results. Specifically, when the device receives the analysis results from the server, it will notify the user of specific advice such as "Take a walk for at least 30 minutes today." If the heart rate is abnormally high, it will warn the user, "Your heart rate is high, so we recommend that you take your pet to the veterinarian."

[0933] Specific examples

[0934] For example, if your dog is not getting enough exercise, the server will generate instructions such as "Set today's walking time to at least 30 minutes." If the dog's heart rate is higher than normal, the server will send a notification to the user saying, "Your dog's heart rate is higher than normal. We recommend that you see a veterinarian." Based on these results, users can efficiently manage their dog's health.

[0935] Prompt Sentence Examples

[0936] prompt:

[0937] Please analyze my dog's activity data (acceleration 34.5, heart rate 115, location information: 35.6895, 139.6917). Please tell me the health condition and proper care method.

[0938] Expected answer:

[0939] Analysis of your dog's activity data has revealed that his heart rate is higher than normal, indicating signs of stress. It's possible that he's not getting enough exercise, so we recommend increasing your walk time. If the heart rate persists, we recommend consulting a veterinarian.

[0940] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0941] Step 1:

[0942] The sensor measures your dog's activity level, heart rate, and location at regular intervals and transmits the data to your device via Bluetooth.

[0943] Input: Data collected from accelerometer, heart rate sensor, and GPS sensor

[0944] Output: Measurement data sent to the device

[0945] Specific operation: The sensor measures your dog's movements every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location information using a GPS sensor.

[0946] Step 2:

[0947] The device transmits the data received from the sensor to the server in real time.

[0948] Input: Measurement data sent from the sensor via Bluetooth

[0949] Output: Data sent to the server as an HTTP POST request

[0950] Specific operation: The device receives activity, heart rate, and location information from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The data includes a timestamp to clarify the timing of the measurement.

[0951] Step 3:

[0952] The server works with an AI model to analyze the received data and estimate stress levels and health status based on the collected data.

[0953] Input: Measurement data sent from the device

[0954] Output: Health status assessment and stress level estimation results

[0955] How it works: The server performs time-series analysis of activity data to assess whether your dog is getting enough exercise. It statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It uses location data to generate advice on the frequency and range of walks.

[0956] Step 4:

[0957] The server generates recommendations for providing services in physical stores based on the analysis results.

[0958] Input: Health status assessment and stress level estimation results

[0959] Output: Recommendations

[0960] Specific operation: Based on the analysis results, the server generates recommendations to suggest pet care services and products that can be provided in physical stores.

[0961] Step 5:

[0962] The server sends the recommendations to the device and provides them to the user through notifications.

[0963] Input: Recommendations

[0964] Output: Recommendations communicated to the user

[0965] Specific behavior: The server sends the generated recommendations to the device, and the device provides the recommendations to the user via a pop-up or push notification, such as specific advice such as "Take a walk for at least 30 minutes today" or a warning such as "Your heart rate is high, so we recommend you see a veterinarian."

[0966] 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.

[0967] This invention combines a system for managing a pet dog's physical condition and behavior with an emotion engine that recognizes the user's emotions. This system allows owners to understand their pet's health and behavior in real time, and also provides appropriate care advice according to the owner's emotional state.

[0968] System Configuration

[0969] 1. Sensor

[0970] It is incorporated into your dog's collar or harness.

[0971] Measures activity level (acceleration sensor), heart rate (heart rate sensor), and location information (GPS sensor).

[0972] Data is collected at regular intervals and sent to the terminal.

[0973] 2. Terminal

[0974] A device owned by the user, such as a smartphone or tablet.

[0975] It receives the data collected from the sensors and sends the data to the server.

[0976] Receives analysis results from the server and notifies the user.

[0977] 3. Server

[0978] A computer system for analyzing the received data.

[0979] Analyzes activity, heart rate, and location information to assess health and stress levels.

[0980] Generate the necessary advice and send it to the device.

[0981] Advice is tailored using user emotional information obtained from the emotion engine.

[0982] 4. Emotion Engine

[0983] An engine that recognizes the user's voice and facial expressions and analyzes their emotional state.

[0984] The information is received by the terminal and transmitted to the server.

[0985] 5. Means of notification

[0986] Analysis results and advice are notified to the user via the device.

[0987] Use pop-up notifications, in-app messages, and push notifications.

[0988] Program processing

[0989] sensor

[0990] The sensor measures your dog's activity, heart rate, and location information at regular intervals and sends the data to the device. For example, the sensor measures your dog's movement every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location using a GPS sensor.

[0991] Terminal

[0992] The device sends the data received from the sensor to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The sent data includes a timestamp, making it clear when the measurement was made.

[0993] server

[0994] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[0995] Emotion Engine

[0996] The emotion engine recognizes emotions from the user's voice and facial expressions and receives that information on the device. For example, the emotion engine analyzes the user's tone of voice and facial expressions while they are speaking through the camera to assess whether they are feeling stressed.

[0997] Server-based analysis results generation and adjustment

[0998] The server adjusts the content and tone of the advice based on the user's emotional information obtained from the emotion engine. For example, if the user is feeling stressed, the server will suggest simple care methods to reduce stress.

[0999] Notification means

[1000] The device that receives the analysis results notifies the user of the results. For example, when the device receives the analysis results from the server, it will notify the user with specific advice such as, "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[1001] The above processing steps realize a system that provides more appropriate and effective care by taking into consideration the owner's emotional state in addition to the dog's physical condition and behavioral management.

[1002] The processing flow will be explained below.

[1003] Step 1:

[1004] Data collection by sensors

[1005] The sensor is built into your dog's collar or harness and measures your dog's activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor) every minute. This data is temporarily stored in the sensor's internal memory.

[1006] Step 2:

[1007] Send data to the device

[1008] The sensor transmits the collected data via Bluetooth to the device, which receives the data and clears the data from the sensor's internal memory.

[1009] Step 3:

[1010] Sending data from the device to the server

[1011] The device transmits the received data to the server in real time, and the transmitted data includes a timestamp to clarify when the measurement was made.

[1012] Step 4:

[1013] Data analysis by server

[1014] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[1015] Step 5:

[1016] Recognizing user emotions with an emotion engine

[1017] The emotion engine uses the device's camera and microphone to recognize the user's emotions. For example, the emotion engine analyzes the user's voice tone to assess their emotional state, such as stress or fatigue. It also uses facial expression recognition technology to read emotions from the user's facial expressions.

[1018] Step 6:

[1019] Server-generated analysis results and advice

[1020] The server adjusts the analysis results based on the user's emotional information obtained from the emotion engine, combined with the dog's health data, and if the user is feeling stressed, it will include simple care methods to relieve stress.

[1021] Step 7:

[1022] Sending analysis results to the device

[1023] The server then sends the generated analysis results to the device, which include advice based on the user's emotional state.

[1024] Step 8:

[1025] User Notification

[1026] The device receives the analysis results from the server and notifies the user. Notifications are displayed as pop-ups, in-app messages, or push notifications. For example, the device provides specific advice such as, "We recommend that you take a walk of at least 30 minutes. You seem tired, so please take regular breaks."

[1027] Step 9:

[1028] Getting user feedback

[1029] Users can provide feedback on the usefulness of the advice through their device, for example by sending a comment such as "Today's advice was helpful."

[1030] Step 10:

[1031] Server-based feedback learning

[1032] The server receives feedback from users and incorporates it into the AI ​​model, helping to improve the accuracy of analysis and the quality of advice in future sessions.

[1033] The above processing steps realize a system that provides care advice that takes into account the user's emotional state as well as the dog's physical condition and behavior management, enabling owners to provide more effective and appropriate care for their pets.

[1034] Example 2

[1035] 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."

[1036] Conventional animal health management systems simply monitor the animal's activity level, heart rate, and location, and are unable to provide care advice that takes into account the owner's psychological state, such as emotions and stress. As a result, the system does not properly reflect the owner's own stress or fatigue, and therefore sometimes does not provide optimal care advice.

[1037] 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.

[1038] In this invention, the server includes: means for measuring activity level, heart rate, and location information using sensors for managing the animal's physical condition and behavior; an information processing terminal for receiving data acquired from the sensors; means for analyzing the data received from the information processing terminal and evaluating the animal's health condition; means for notifying the user of the analysis results of the server device via the information processing terminal; an emotion analysis engine for analyzing the user's voice and facial expressions to grasp their emotional state; and means for adjusting the analysis results and advice content based on the emotion information acquired by the emotion analysis engine. This makes it possible to provide more appropriate and effective care advice by taking into account the owner's emotional state in addition to the animal's physical condition and behavior management.

[1039] "Animal" refers to any living creature kept as a domestic animal or pet, including, but not limited to, a pet dog.

[1040] "Sensor" refers to a measuring device for measuring data such as an animal's activity level, heart rate, and location information.

[1041] "Activity level" is data that indicates the degree of movement or movement that an animal underwent within a certain period of time.

[1042] "Heart rate" is data indicating the number of heartbeats an animal has within a certain period of time.

[1043] "Location information" is data about an animal's current location and movement route obtained using GPS and other devices.

[1044] An "information processing terminal" is a device that receives data collected from sensors and transmits it to a server, and includes smartphones, tablets, etc.

[1045] The "server device" is a computer system that analyzes data sent from the information processing terminal, evaluates the health condition of the animals, and generates analysis results.

[1046] An "emotion analysis engine" is a system that analyzes a user's voice and facial expressions to understand their emotional state.

[1047] The "analysis results" are the output results of evaluations and diagnoses made by the server device based on data acquired from sensors and emotion analysis engines.

[1048] "Means of notification" refers to the method used to notify users of analysis results and advice, including pop-up notifications, in-app messages, and push notifications.

[1049] This invention is a system for managing the physical condition and behavior of animals, and uses the following hardware and software to acquire, analyze, and notify data.

[1050] Hardware Configuration

[1051] 1. Sensor

[1052] Various sensors are incorporated into the animal's collar or harness.

[1053] The sensors used include an acceleration sensor that measures activity, a heart rate sensor that measures heart rate, and a GPS sensor that obtains location information.

[1054] These sensors collect data at regular intervals and transmit it to an information processing terminal.

[1055] 2. Information processing terminal

[1056] It is a device such as a smartphone or tablet that the user owns.

[1057] The data collected from the sensors is received via Bluetooth and sent to the server in real time using HTTP POST requests.

[1058] 3. Server Device

[1059] The server device is a powerful computer system for analyzing the received data.

[1060] The server uses AI models to perform time series analysis of activity data, statistical analysis of heart rate data, and geographic information analysis of location data.

[1061] 4. Sentiment Analysis Engine

[1062] An emotion analysis engine is a system for analyzing a user's voice and facial expressions.

[1063] A microphone is used for voice analysis and a camera for facial expression analysis.

[1064] The obtained emotion information is transmitted to the server via the information processing terminal.

[1065] Program processing

[1066] Sensor Processing

[1067] The sensor measures the animal's activity, heart rate, and location information at regular intervals and sends the data to an information processing terminal. For example, the sensor measures the dog's activity every minute with an acceleration sensor, records the heart rate with a heart rate sensor, and obtains location information with a GPS sensor.

[1068] Terminal Processing

[1069] The device receives data from the sensor and sends it to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and sends it to the server via an HTTP POST request. The data includes a timestamp to clarify the timing of the measurement.

[1070] Server Processing

[1071] The server analyzes the received data using an AI model. Specifically, it performs time-series analysis of activity data to evaluate whether the amount of exercise is appropriate, statistically analyzes heart rate data to detect abnormalities, and generates advice on the frequency and range of walks based on location data.

[1072] Sentiment Analysis Engine

[1073] The emotion analysis engine recognizes emotions from the user's voice and facial expressions, for example, by analyzing the user's tone of voice and facial expressions through the camera when they speak, and assessing the user's stress level.

[1074] Server-based analysis results generation and adjustment

[1075] The server adjusts the content and tone of the advice based on the user's emotional information obtained from the emotion analysis engine. For example, if the user is feeling stressed, it generates simple care advice to reduce stress. Examples of specific advice include, "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[1076] Notification means

[1077] The device receives the analysis results from the server and notifies the user using pop-up notifications, in-app messages, and push notifications, and displays specific advice such as "Your dog needs at least a 30-minute walk today."

[1078] Examples and prompts

[1079] Specific examples

[1080] The sensor measures your dog's activity every minute and sends the data to an information processing terminal.

[1081] The device sends the received data to a server, which then analyzes the data using an AI model.

[1082] The emotion analysis engine analyzes the user's voice and facial expressions and sends emotional information to the server.

[1083] The server adjusts the advice based on the analysis results, and the device notifies the user of the analysis results.

[1084] Prompt Sentence Examples

[1085] "What advice would be effective on how to care for a user's dog if they are stressed?"

[1086] "How can I analyze my dog's activity and heart rate data to assess his health?"

[1087] In this way, a system is realized that manages the physical condition and behavior of a beloved dog while providing appropriate care advice that also takes into account the user's emotional state.

[1088] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1089] Step 1:

[1090] Sensor data acquisition

[1091] The sensor acquires the animal's activity, heart rate, and location information at regular intervals. The sensor's inputs are the animal's physical activity, location, and heart rate. The sensor measures these inputs and generates activity data, heart rate data, and location data. This data is temporarily stored in the sensor and then sent to an information processing device. For example, an acceleration sensor measures the animal's movement over one minute, a heart rate sensor simultaneously records the heart rate, and a GPS sensor identifies the animal's location.

[1092] Step 2:

[1093] Sending data to the device

[1094] The data acquired by the sensor is sent to the information processing terminal. The input to the terminal is data from the sensor, and the output is data sent to the server. The terminal receives activity level, heart rate, and location information from the sensor using Bluetooth, and sends this information along with the received timestamp to the server via an HTTP POST request. Here, the terminal formats the data and converts it into a format that is easy for the server to analyze. Specifically, the terminal compiles the data received from the sensor and sends it to the server every minute.

[1095] Step 3:

[1096] Data analysis by server

[1097] The server receives and analyzes the data sent from the device. The server's inputs are activity data, heart rate data, and location data sent from the device. The server analyzes this data using an AI model and generates an output that evaluates the animal's health, as well as analytical results on exercise volume and stress levels. Specifically, the server performs a time series analysis of the activity data to evaluate whether exercise is being performed appropriately. It also statistically analyzes the heart rate data to detect abnormalities. The location data is used to evaluate the frequency and range of walks using geographic information analysis.

[1098] Step 4:

[1099] Emotion analysis using an emotion analysis engine

[1100] The emotion analysis engine analyzes the user's voice and facial expressions to understand their emotional state. The emotion analysis engine's input is the user's voice data and facial expression data, and its output is information about their emotional state. The engine uses a microphone and camera to analyze the user's tone of voice and facial expressions. For example, the analysis results may evaluate whether the user is feeling stressed. This information is sent to the information processing terminal and then to the server.

[1101] Step 5:

[1102] Server-based analysis results generation and adjustment

[1103] The server receives the user's emotional information obtained from the emotion analysis engine and adjusts the analysis results and advice content. The server receives data based on the animal's health assessment and the user's emotional information. The server integrates this data and generates care advice based on the user's stress level. For example, if the user is feeling stressed, the server will generate advice such as, "We recommend taking a short walk to reduce stress."

[1104] Step 6:

[1105] User notification via information processing terminal

[1106] The device receives analysis results and advice from the server and notifies the user. The input to the device is the analysis results and advice sent from the server, and the output is the notification to the user. Notification methods include pop-up notifications, in-app messages, and push notifications. For example, a notification may be sent to the user saying, "Your dog needs to be walked for at least 30 minutes today."

[1107] Through these steps, the system is able to provide appropriate care advice that takes into account not only the animal's physical condition and behavior, but also the user's emotional state.

[1108] (Application example 2)

[1109] 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."

[1110] Conventional pet dog health management systems only provide general care advice based on the dog's health condition, without taking into account the owner's emotional state. As a result, it is difficult to provide appropriate advice when the owner is stressed or in a specific emotional state. Thus, there is a need for a system that provides more appropriate care methods that take into account the owner's emotional state.

[1111] The identification process 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 analyzing data acquired from the sensor and evaluating the health condition of the animal, means including an emotion engine for analyzing the emotional state of the user, and means for generating advice based on the analysis results of the server means and the user's emotional information and notifying the user via the terminal means. This makes it possible to provide advice that takes the owner's emotional state into consideration.

[1112] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[1113] The "terminal means" is a device that receives data acquired from the sensor and transmits the data to the server means.

[1114] The "server means" is a computer system for analyzing data received from the terminal means and evaluating the health status of the animals.

[1115] An "emotion engine" is a device or system for analyzing a user's emotional state, and determines the user's emotions based on data such as voice and facial expressions.

[1116] The "analysis results" are information about the health condition and stress level of the animal that is generated by the server means by analyzing the data received from the sensor.

[1117] The "means for generating advice" is a device or computer program that allows the server means to create advice on appropriate care methods based on the analysis results and the user's emotional information.

[1118] The "notifying means" is a device or function for notifying the user of the generated advice via the terminal means.

[1119] This invention is a system for managing the physical condition and behavior of a pet dog, and is implemented using the following devices and software.

[1120] The system includes the following main components: a sensor, a terminal means, a server means, an emotion engine, and a notification means.

[1121] sensor

[1122] The sensors worn by pet dogs are measuring devices that measure the animal's activity, heart rate, and location information. Examples include acceleration sensors, heart rate sensors, and GPS sensors. These sensors are incorporated into the dog's collar or harness, and collect data at regular intervals and transmit it to a terminal via Bluetooth.

[1123] Terminal means

[1124] The terminal means is a device such as a smartphone or tablet that receives data from the sensor in real time and transmits it to the server means. For example, the terminal means transmits the amount of activity, heart rate, and location information received from the sensor via Bluetooth to the server using an HTTP POST request.

[1125] Server Means

[1126] The server means is a computer system for analyzing the received data. The specific analysis is performed as follows:

[1127] Activity data is analyzed over time to evaluate your dog's physical activity.

[1128] Heart rate data is statistically analyzed and compared with normal heart rates to detect abnormalities.

[1129] Advice is generated regarding the frequency and range of walks based on location data.

[1130] The server means adjusts the content and tone of advice based on the user's emotional information obtained from the emotion engine.

[1131] Emotion Engine

[1132] An emotion engine is a device or system for analyzing a user's voice and facial expressions to assess their emotional state. For example, an emotion engine may analyze a user's voice tone and facial expressions through a camera while they are speaking to assess whether they are feeling stressed.

[1133] Notification means

[1134] The notification means has a function to notify the user of the analysis results and advice. Information is notified to the user via the terminal means as push notifications or in-app messages. For example, when the terminal receives the analysis results from the server, it notifies the user with specific advice such as "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[1135] Specific examples

[1136] For example, if your dog is healthy but doesn't get enough exercise, you'll receive a notification saying, "Your dog is healthy, but needs more exercise." If your emotional state is analyzed as "stressed," you'll receive a notification saying, "Your dog is healthy, but needs more exercise. Please take some time to relax."

[1137] Prompt Sentence Examples

[1138] "It analyzes the user's vocal tone and facial expressions to assess their current emotional state. If the emotional state is stress, it will add a message to your dog's health advice about taking time to relax."

[1139] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1140] Step 1:

[1141] The sensor measures your dog's activity, heart rate, and location. The sensor collects this data at regular intervals and sends it to the device via Bluetooth. The input is the measured data, and the output is the data sent to the device.

[1142] Step 2:

[1143] The device receives data from the sensor and sends it to the server in real time. The device receives data via Bluetooth and sends it to the server using an HTTP POST request. The input is the data received from the sensor and the output is the data sent to the server.

[1144] Step 3:

[1145] The server analyzes the received data. The server performs time-series analysis of the activity data, statistical analysis of the heart rate data, and evaluates the frequency and range of walks based on the location data. The input is the data sent from the device, and the output is the analysis results.

[1146] Step 4:

[1147] The emotion engine analyzes the user's voice and facial expressions to evaluate their emotional state. For example, the emotion engine analyzes the user's tone of voice and facial expressions through a camera while they are speaking. The input is audio and video data, and the output is analyzed emotional information.

[1148] Step 5:

[1149] The server generates advice based on the analysis results and emotional information. The server creates advice with appropriate content and tone, taking into account the user's emotional state. The input is the analysis results and emotional information, and the output is the generated advice.

[1150] Step 6:

[1151] The device receives advice from the server and notifies the user. The device provides specific advice to the user using push notifications or in-app messages. The input is the advice sent from the server, and the output is the message notified to the user.

[1152] 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.

[1153] 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.

[1154] 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.

[1155] [Fourth embodiment]

[1156] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1157] 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.

[1158] 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).

[1159] 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.

[1160] 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.

[1161] 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).

[1162] 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.

[1163] 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.

[1164] 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.

[1165] 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.

[1166] 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.

[1167] 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.

[1168] 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."

[1169] The present invention is a system for managing the physical condition and behavior of pet dogs, which includes sensors, terminals, a server, and notification means. This system allows owners to understand the health condition of their pet dogs in real time and provide appropriate care.

[1170] System Configuration

[1171] 1. Sensor

[1172] It is incorporated into your dog's collar or harness.

[1173] Measures activity (acceleration), heart rate, and location information.

[1174] Data is collected at regular intervals and sent to the terminal.

[1175] 2. Terminal

[1176] A device owned by the user, such as a smartphone or tablet.

[1177] It receives the data collected from the sensors and sends the data to the server.

[1178] Receives analysis results from the server and notifies the user.

[1179] 3. Server

[1180] A computer system for analyzing the received data.

[1181] Analyzes activity, heart rate, and location information to assess health and stress levels.

[1182] Generate the necessary advice and send it to the device.

[1183] 4. Means of notification

[1184] Analysis results and advice are notified to the user via the device.

[1185] Use pop-up notifications, in-app messages, and push notifications.

[1186] Program processing

[1187] sensor

[1188] The sensor measures your dog's activity, heart rate, and location information at regular intervals and sends the data to the device. For example, the sensor measures your dog's movement every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location using a GPS sensor.

[1189] Terminal

[1190] The device sends the data received from the sensor to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The sent data includes a timestamp, making it clear when the measurement was made.

[1191] server

[1192] The server works with an AI model to analyze the received data and estimate stress levels and health status based on the collected data. Specifically, the server performs time-series analysis of activity data to assess whether the dog is getting enough exercise. It statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It also uses location data to generate advice on the frequency and range of walks.

[1193] Notification means

[1194] The device that receives the analysis results notifies the user of the results. For example, when the device receives the analysis results from the server, it will notify the user with specific advice such as "Take a walk for at least 30 minutes today." If the heart rate is abnormally high, it will warn the user that "Your heart rate is high, so we recommend that you take your pet to the veterinarian."

[1195] The system of the present invention further includes a means for estimating the stress level of an animal and generating advice on appropriate care methods, and a means for suggesting to the user the timing of walking the animal and the amount of exercise based on the analysis results, making it easier for pet owners to provide appropriate care for their pets. In this way, pet owners can efficiently manage their pet's health and improve the quality of life for both the owner and their pet dog.

[1196] The processing flow will be explained below.

[1197] Step 1:

[1198] Data collection by sensors

[1199] The sensor is built into your dog's collar or harness and measures your dog's activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor) every minute. This data is temporarily stored in the sensor's internal memory.

[1200] Step 2:

[1201] Send data to the device

[1202] The sensor transmits the collected data via Bluetooth to the device, which receives the data and clears it from the sensor's internal memory.

[1203] Step 3:

[1204] Sending data from the device to the server

[1205] The device sends the received data to the server in real time, including a timestamp to clarify when the measurement was made.

[1206] Step 4:

[1207] Data analysis by server

[1208] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[1209] Step 5:

[1210] Generate analysis results

[1211] The server uses the analysis results to assess the dog's stress level and health condition, and generates appropriate care advice, including specific suggestions such as "Take a walk for at least 30 minutes today" or "Your heart rate is high, so we recommend you take your dog to the vet."

[1212] Step 6:

[1213] Sending analysis results to the device

[1214] The server sends the generated analysis results to the terminal, which receives the results and prepares to notify the user.

[1215] Step 7:

[1216] User Notification

[1217] The device will notify the user of the analysis results from the server via pop-up displays, in-app messages, push notifications, etc. The user can then take care of their dog based on the notification and provide feedback as needed.

[1218] Step 8:

[1219] Get feedback and learn

[1220] Users provide feedback through their devices, such as by sending a comment like, "Today's walking advice was helpful." The server receives this feedback and incorporates it into the AI ​​model to help improve analysis accuracy.

[1221] The above processing steps realize a system that manages the physical condition and behavior of pet dogs in real time and provides advice to owners on how to provide appropriate care.

[1222] Example 1

[1223] 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."

[1224] When it comes to pet health management, it is difficult for owners to monitor their dog's physical condition and behavior in real time. Also, there may be delays in noticing that their dog is stressed or their health is deteriorating. Therefore, an effective system is needed to provide prompt and appropriate care.

[1225] 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.

[1226] In this invention, the server includes: means for measuring the activity level, heart rate, and location information of the animal using a sensor; terminal means for receiving data obtained from the sensor via Bluetooth and transmitting the time-stamped data to the server in real time; means for analyzing the data received from the terminal means, evaluating the health condition and stress level of the animal, and generating appropriate care advice; and means for notifying the user of the analysis results of the server means as a push notification or an in-app message. This makes it possible to monitor the activity level, heart rate, and location information of a pet dog in real time, quickly evaluate the health condition, and provide appropriate care advice as needed.

[1227] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[1228] The "terminal means" is a device that receives data acquired from the sensor via Bluetooth and transmits the data with a timestamp to the server in real time.

[1229] The "server means" is a computer system that serves to analyze data received from the terminal means, evaluate the health condition and stress level of the animal, and generate appropriate care advice.

[1230] "Analysis results" refers to evaluations and diagnostic information obtained by processing data received by the server means.

[1231] "Push notification" is a function that displays analysis results and advice to users in real time via their device.

[1232] "Activity" is a measurement that indicates the degree of movement or activity of an animal.

[1233] "Heart rate" is a measurement of the number of times an animal's heart beats within a given period of time.

[1234] "Location information" is geographical data that indicates the current location of an animal.

[1235] "Bluetooth" is a short-range wireless communication technology used to send and receive data between sensors and terminal devices.

[1236] A "timestamp" is information that indicates the date and time when data was collected or transmitted.

[1237] "Care advice" refers to recommendations and warnings regarding animal health care that are generated by the server means based on the analysis results.

[1238] "Health status" is a collection of indicators that indicate the degree of physical and mental well-being of an animal.

[1239] "Stress level" is an index that evaluates the degree of stress an animal is experiencing.

[1240] The present invention is a system for managing the physical condition and behavior of a pet dog in real time, and its main components include a sensor, a terminal, a server, and a notification means. The details of each component and their operation will be explained below.

[1241] sensor

[1242] The sensors are attached to your dog's collar or harness and measure activity, heart rate, and location information. For example, an acceleration sensor detects your dog's movements, a heart rate sensor measures its heart rate, and a GPS sensor obtains its location information. These data are measured every minute and sent to your device via Bluetooth. Specific sensor hardware includes an acceleration sensor, heart rate sensor, and GPS sensor.

[1243] Terminal

[1244] The device is a smartphone or tablet owned by the user. The device receives data acquired from the sensor via Bluetooth and transmits it to the server in real time using an HTTP POST request. The transmitted data includes a timestamp, making it clear when the data was measured. The device's software includes an application that receives data from the sensor and a communication module that transmits the data to the server.

[1245] server

[1246] The server analyzes the data received from the device and evaluates the dog's health condition and stress level. It uses an AI model to analyze activity data, heart rate data, and location data to evaluate the animal's movement patterns and heart rate trends and detect abnormalities. Based on the analysis results, it generates appropriate care advice and sends it to the device. The server software includes an AI model for data analysis and logic for generating care advice.

[1247] Notification means

[1248] Once the device receives the analysis results from the server, it immediately displays them to the user as a push notification or in-app message. For example, if today's walk time is short, the device will display advice such as "Try to take a walk for at least 30 minutes today." If the heart rate is abnormally high, the device will display a warning such as "Your heart rate is high. We recommend that you take your pet to the vet."

[1249] Specific examples

[1250] A specific scenario for actually using a dog health management system is as follows: A sensor is attached to the dog's collar, and the dog starts walking. The sensor measures the dog's activity level, heart rate, and location every minute and sends the data to the device. The device receives this data via Bluetooth and sends it to the server in real time. The server analyzes the received data and determines that the dog's stress level is high. The server generates advice such as "Your dog's stress level is high, so we recommend continuing your walk a little longer" and sends it to the device. The device then notifies the user of this advice via push notification.

[1251] Prompt Sentence Examples

[1252] We have developed a health management system for your pet dog. This system consists of sensors, terminals, a server, and a notification method, and measures your dog's activity level, heart rate, and location information, and analyzes it in real time to provide appropriate advice.

[1253] Sensor (e.g. attached to your dog's collar):

[1254] Activity (acceleration), heart rate, and location information are measured every minute.

[1255] Device (e.g. user's smartphone):

[1256] The data from the sensor is received via Bluetooth and sent to the server via an HTTP POST request.

[1257] server:

[1258] The received data is analyzed using an AI model to assess your dog's stress level and health condition.

[1259] Generate the necessary advice and send it to your device.

[1260] Notification method:

[1261] The device will then send a push notification to the user with the analysis results (e.g., "Please take a walk of at least 30 minutes today").

[1262] This system allows you to monitor your dog's health in real time and provide appropriate care.

[1263] In such an embodiment, the present invention can efficiently manage the health of pet dogs, improving the quality of life for owners and their pet dogs.

[1264] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1265] Step 1:

[1266] Data Measurement

[1267] The sensor measures your dog's activity (acceleration), heart rate, and location information every minute. The sensor inputs are your dog's movements, heart rate, and geographic location, and processes the data based on these inputs to generate measurement results. Specifically, the acceleration sensor collects activity data, the heart rate sensor measures heart rate data, and the GPS sensor obtains location data. These measurement results are obtained as output.

[1268] Step 2:

[1269] Data transmission

[1270] The sensor sends the measured data to the terminal via Bluetooth. The sensor input is the measurement results obtained in step 1, and the data is packaged using Bluetooth communication and sent to the terminal. Specifically, the sensor aggregates the measurement data every minute and sends it to the terminal via Bluetooth. The terminal receives this data.

[1271] Step 3:

[1272] Data reception

[1273] The device receives data sent from the sensor via Bluetooth. The device inputs data packets from the sensor, which are converted into an internal data format for processing. Specifically, the device analyzes the received data packets and stores them as activity data, heart rate data, and location information data.

[1274] Step 4:

[1275] Data transmission (server)

[1276] The terminal sends the received data to the server in real time using an HTTP POST request. The input to the terminal is the data received in step 3, which is time-stamped and sent to the server. Specifically, the terminal analyzes the data packets received from the sensor, generates an HTTP POST request, and sends it to the server. The server receives this data.

[1277] Step 5:

[1278] Data analysis

[1279] The server analyzes the data received from the device. The server's input is the data sent from the device, and it uses an AI model to analyze this data. Specifically, it analyzes activity data, heart rate data, and location data to evaluate health status and stress levels and detect any abnormalities. The output is the analysis results and appropriate care advice.

[1280] Step 6:

[1281] Advice Generation

[1282] The server generates appropriate care advice based on the results of the data analysis. The input is the analysis result from step 5, and advice and warning messages are generated based on this. Specifically, the server evaluates the analysis result, generates the necessary care advice and warning, and creates a data packet to send to the terminal.

[1283] Step 7:

[1284] Receive advice

[1285] The terminal receives the analysis results and advice sent from the server. The terminal inputs data packets from the server, which it analyzes and prepares to notify the user. Specifically, the terminal analyzes the data packets received in the HTTP response and generates the notification content.

[1286] Step 8:

[1287] User Notification

[1288] The device notifies the user of the analysis results and care advice. The input is the data received in step 7, which is displayed to the user as a push notification or in-app message. Specifically, the device sets a push notification to notify the user of advice such as "Please take your pet for a walk for at least 30 minutes today" or "Your pet's heart rate is high, so we recommend you take it to the vet."

[1289] This process allows you to monitor your dog's health in real time and provide appropriate care advice quickly.

[1290] (Application example 1)

[1291] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1292] Currently, there are limited means for understanding the health status and behavior of pet owners in real time, making it difficult for owners to provide appropriate care. Furthermore, because there is no connection with pet care services offered at physical stores, it is difficult for users to find the optimal care method. The present invention aims to provide a system for efficiently managing the health of pets and facilitating the provision of services at physical stores.

[1293] 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.

[1294] In this invention, the server includes: means for measuring the activity level, heart rate, and location information of the animal using a sensor; terminal means for receiving data acquired from the sensor; means for analyzing the data received from the terminal means and evaluating the animal's health condition; means for notifying the user of the analysis results of the server means via the terminal means; means for generating recommendations for providing services at a physical store; and means for notifying the user of the recommendations. This allows users to understand the health condition of their beloved dog in real time and provide appropriate care. Furthermore, by linking with pet care services at physical stores, owners can receive optimal services.

[1295] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[1296] A "terminal" is a device that receives data obtained from a sensor and transmits it to a server.

[1297] The "server" is a computer system that analyzes data received from the terminal means, evaluates the health condition of the animal, and notifies the results of the analysis.

[1298] A "physical store" is a place that users can visit in person, and is a facility where pet care services and the like are provided.

[1299] "Recommendations" are useful advice or suggestions for users that are generated based on the results of analysis on the server.

[1300] "Notification means" refers to a method for communicating analysis results and recommendations to users via their devices.

[1301] The present invention is a system for managing the physical condition and behavior of a pet dog, and includes a sensor, a terminal, a server, and a notification means. Specific embodiments of the system are described below.

[1302] System Configuration

[1303] 1. Sensor

[1304] The sensors attached to your dog's collar or harness measure activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor). The sensors collect data at regular intervals (for example, every minute) and send it to your device via Bluetooth.

[1305] 2. Terminal

[1306] The user's smartphone or tablet receives data from the sensor and transmits it to the server in real time. The transmitted data includes a timestamp to indicate when the measurement was made. The device sends the data to the server using an HTTP POST request.

[1307] 3. Server

[1308] The server is a computer system located in the cloud that analyzes the received data. Using AI models (time series analysis model, anomaly detection model), stress levels and health conditions are estimated based on the collected data. For example, activity data is analyzed over time to determine whether the dog is getting enough exercise. Heart rate data is statistically analyzed and compared with normal heart rates to detect abnormalities. Location data is used to generate advice on the frequency and range of walks.

[1309] 4. Means of notification

[1310] The device receives the analysis results from the server and notifies the user of the results. Specifically, when the device receives the analysis results from the server, it will notify the user of specific advice such as "Take a walk for at least 30 minutes today." If the heart rate is abnormally high, it will warn the user, "Your heart rate is high, so we recommend that you take your pet to the veterinarian."

[1311] Specific examples

[1312] For example, if your dog is not getting enough exercise, the server will generate instructions such as "Set today's walking time to at least 30 minutes." If the dog's heart rate is higher than normal, the server will send a notification to the user saying, "Your dog's heart rate is higher than normal. We recommend that you see a veterinarian." Based on these results, users can efficiently manage their dog's health.

[1313] Prompt Sentence Examples

[1314] prompt:

[1315] Please analyze my dog's activity data (acceleration 34.5, heart rate 115, location information: 35.6895, 139.6917). Please tell me the health condition and proper care method.

[1316] Expected answer:

[1317] Analysis of your dog's activity data has revealed that his heart rate is higher than normal, indicating signs of stress. It's possible that he's not getting enough exercise, so we recommend increasing your walk time. If the heart rate persists, we recommend consulting a veterinarian.

[1318] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1319] Step 1:

[1320] The sensor measures your dog's activity level, heart rate, and location at regular intervals and transmits the data to your device via Bluetooth.

[1321] Input: Data collected from accelerometer, heart rate sensor, and GPS sensor

[1322] Output: Measurement data sent to the device

[1323] Specific operation: The sensor measures your dog's movements every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location information using a GPS sensor.

[1324] Step 2:

[1325] The device transmits the data received from the sensor to the server in real time.

[1326] Input: Measurement data sent from the sensor via Bluetooth

[1327] Output: Data sent to the server as an HTTP POST request

[1328] Specific operation: The device receives activity, heart rate, and location information from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The data includes a timestamp to clarify the timing of the measurement.

[1329] Step 3:

[1330] The server works with an AI model to analyze the received data and estimate stress levels and health status based on the collected data.

[1331] Input: Measurement data sent from the device

[1332] Output: Health status assessment and stress level estimation results

[1333] How it works: The server performs time-series analysis of activity data to assess whether your dog is getting enough exercise. It statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It uses location data to generate advice on the frequency and range of walks.

[1334] Step 4:

[1335] The server generates recommendations for providing services in physical stores based on the analysis results.

[1336] Input: Health status assessment and stress level estimation results

[1337] Output: Recommendations

[1338] Specific operation: Based on the analysis results, the server generates recommendations to suggest pet care services and products that can be provided in physical stores.

[1339] Step 5:

[1340] The server sends the recommendations to the device and provides them to the user through notifications.

[1341] Input: Recommendations

[1342] Output: Recommendations communicated to the user

[1343] Specific behavior: The server sends the generated recommendations to the device, and the device provides the recommendations to the user via a pop-up or push notification, such as specific advice such as "Take a walk for at least 30 minutes today" or a warning such as "Your heart rate is high, so we recommend you see a veterinarian."

[1344] 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.

[1345] This invention combines a system for managing a pet dog's physical condition and behavior with an emotion engine that recognizes the user's emotions. This system allows owners to understand their pet's health and behavior in real time, and also provides appropriate care advice according to the owner's emotional state.

[1346] System Configuration

[1347] 1. Sensor

[1348] It is incorporated into your dog's collar or harness.

[1349] Measures activity level (acceleration sensor), heart rate (heart rate sensor), and location information (GPS sensor).

[1350] Data is collected at regular intervals and sent to the terminal.

[1351] 2. Terminal

[1352] A device owned by the user, such as a smartphone or tablet.

[1353] It receives the data collected from the sensors and sends the data to the server.

[1354] Receives analysis results from the server and notifies the user.

[1355] 3. Server

[1356] A computer system for analyzing the received data.

[1357] Analyzes activity, heart rate, and location information to assess health and stress levels.

[1358] Generate the necessary advice and send it to the device.

[1359] Advice is tailored using user emotional information obtained from the emotion engine.

[1360] 4. Emotion Engine

[1361] An engine that recognizes the user's voice and facial expressions and analyzes their emotional state.

[1362] The information is received by the terminal and transmitted to the server.

[1363] 5. Means of notification

[1364] Analysis results and advice are notified to the user via the device.

[1365] Use pop-up notifications, in-app messages, and push notifications.

[1366] Program processing

[1367] sensor

[1368] The sensor measures your dog's activity, heart rate, and location information at regular intervals and sends the data to the device. For example, the sensor measures your dog's movement every minute using an acceleration sensor, records its heart rate using a heart rate sensor, and obtains its location using a GPS sensor.

[1369] Terminal

[1370] The device sends the data received from the sensor to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and immediately sends it to the server via an HTTP POST request. The sent data includes a timestamp, making it clear when the measurement was made.

[1371] server

[1372] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[1373] Emotion Engine

[1374] The emotion engine recognizes emotions from the user's voice and facial expressions and receives that information on the device. For example, the emotion engine analyzes the user's tone of voice and facial expressions while they are speaking through the camera to assess whether they are feeling stressed.

[1375] Server-based analysis results generation and adjustment

[1376] The server adjusts the content and tone of the advice based on the user's emotional information obtained from the emotion engine. For example, if the user is feeling stressed, the server will suggest simple care methods to reduce stress.

[1377] Notification means

[1378] The device that receives the analysis results notifies the user of the results. For example, when the device receives the analysis results from the server, it will notify the user with specific advice such as, "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[1379] The above processing steps realize a system that provides more appropriate and effective care by taking into consideration the owner's emotional state in addition to the dog's physical condition and behavioral management.

[1380] The processing flow will be explained below.

[1381] Step 1:

[1382] Data collection by sensors

[1383] The sensor is built into your dog's collar or harness and measures your dog's activity (accelerometer), heart rate (heart rate sensor), and location (GPS sensor) every minute. This data is temporarily stored in the sensor's internal memory.

[1384] Step 2:

[1385] Send data to the device

[1386] The sensor transmits the collected data via Bluetooth to the device, which receives the data and clears the data from the sensor's internal memory.

[1387] Step 3:

[1388] Sending data from the device to the server

[1389] The device transmits the received data to the server in real time, and the transmitted data includes a timestamp to clarify when the measurement was made.

[1390] Step 4:

[1391] Data analysis by server

[1392] The server analyzes the received data using an AI model. Specifically, it performs a time series analysis of activity data to assess whether the dog is getting enough exercise. It also statistically analyzes heart rate data and compares it with normal heart rates to detect abnormalities. It then generates advice on the frequency and range of walks based on the location data.

[1393] Step 5:

[1394] Recognizing user emotions with an emotion engine

[1395] The emotion engine uses the device's camera and microphone to recognize the user's emotions. For example, the emotion engine analyzes the user's voice tone to assess their emotional state, such as stress or fatigue. It also uses facial expression recognition technology to read emotions from the user's facial expressions.

[1396] Step 6:

[1397] Server-generated analysis results and advice

[1398] The server adjusts the analysis results based on the user's emotional information obtained from the emotion engine, combined with the dog's health data, and if the user is feeling stressed, it will include simple care methods to relieve stress.

[1399] Step 7:

[1400] Sending analysis results to the device

[1401] The server then sends the generated analysis results to the device, which include advice based on the user's emotional state.

[1402] Step 8:

[1403] User Notification

[1404] The device receives the analysis results from the server and notifies the user. Notifications are displayed as pop-ups, in-app messages, or push notifications. For example, the device provides specific advice such as, "We recommend that you take a walk of at least 30 minutes. You seem tired, so please take regular breaks."

[1405] Step 9:

[1406] Getting user feedback

[1407] Users can provide feedback on the usefulness of the advice through their device, for example by sending a comment such as "Today's advice was helpful."

[1408] Step 10:

[1409] Server-based feedback learning

[1410] The server receives feedback from users and incorporates it into the AI ​​model, helping to improve the accuracy of analysis and the quality of advice in future sessions.

[1411] The above processing steps realize a system that provides care advice that takes into account the user's emotional state as well as the dog's physical condition and behavior management, enabling owners to provide more effective and appropriate care for their pets.

[1412] Example 2

[1413] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1414] Conventional animal health management systems simply monitor the animal's activity level, heart rate, and location, and are unable to provide care advice that takes into account the owner's psychological state, such as emotions and stress. As a result, the system does not properly reflect the owner's own stress or fatigue, and therefore sometimes does not provide optimal care advice.

[1415] 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.

[1416] In this invention, the server includes: means for measuring activity level, heart rate, and location information using sensors for managing the animal's physical condition and behavior; an information processing terminal for receiving data acquired from the sensors; means for analyzing the data received from the information processing terminal and evaluating the animal's health condition; means for notifying the user of the analysis results of the server device via the information processing terminal; an emotion analysis engine for analyzing the user's voice and facial expressions to grasp their emotional state; and means for adjusting the analysis results and advice content based on the emotion information acquired by the emotion analysis engine. This makes it possible to provide more appropriate and effective care advice by taking into account the owner's emotional state in addition to the animal's physical condition and behavior management.

[1417] "Animal" refers to any living creature kept as a domestic animal or pet, including, but not limited to, a pet dog.

[1418] "Sensor" refers to a measuring device for measuring data such as an animal's activity level, heart rate, and location information.

[1419] "Activity level" is data that indicates the degree of movement or movement that an animal underwent within a certain period of time.

[1420] "Heart rate" is data indicating the number of heartbeats an animal has within a certain period of time.

[1421] "Location information" is data about an animal's current location and movement route obtained using GPS and other devices.

[1422] An "information processing terminal" is a device that receives data collected from sensors and transmits it to a server, and includes smartphones, tablets, etc.

[1423] The "server device" is a computer system that analyzes data sent from the information processing terminal, evaluates the health condition of the animals, and generates analysis results.

[1424] An "emotion analysis engine" is a system that analyzes a user's voice and facial expressions to understand their emotional state.

[1425] The "analysis results" are the output results of evaluations and diagnoses made by the server device based on data acquired from sensors and emotion analysis engines.

[1426] "Means of notification" refers to the method used to notify users of analysis results and advice, including pop-up notifications, in-app messages, and push notifications.

[1427] This invention is a system for managing the physical condition and behavior of animals, and uses the following hardware and software to acquire, analyze, and notify data.

[1428] Hardware Configuration

[1429] 1. Sensor

[1430] Various sensors are incorporated into the animal's collar or harness.

[1431] The sensors used include an acceleration sensor that measures activity, a heart rate sensor that measures heart rate, and a GPS sensor that obtains location information.

[1432] These sensors collect data at regular intervals and transmit it to an information processing terminal.

[1433] 2. Information processing terminal

[1434] It is a device such as a smartphone or tablet that the user owns.

[1435] The data collected from the sensors is received via Bluetooth and sent to the server in real time using HTTP POST requests.

[1436] 3. Server Device

[1437] The server device is a powerful computer system for analyzing the received data.

[1438] The server uses AI models to perform time series analysis of activity data, statistical analysis of heart rate data, and geographic information analysis of location data.

[1439] 4. Sentiment Analysis Engine

[1440] An emotion analysis engine is a system for analyzing a user's voice and facial expressions.

[1441] A microphone is used for voice analysis and a camera for facial expression analysis.

[1442] The obtained emotion information is transmitted to the server via the information processing terminal.

[1443] Program processing

[1444] Sensor Processing

[1445] The sensor measures the animal's activity, heart rate, and location information at regular intervals and sends the data to an information processing terminal. For example, the sensor measures the dog's activity every minute with an acceleration sensor, records the heart rate with a heart rate sensor, and obtains location information with a GPS sensor.

[1446] Terminal Processing

[1447] The device receives data from the sensor and sends it to the server in real time. For example, the device receives activity data, heart rate data, and location data from the sensor via Bluetooth and sends it to the server via an HTTP POST request. The data includes a timestamp to clarify the timing of the measurement.

[1448] Server Processing

[1449] The server analyzes the received data using an AI model. Specifically, it performs time-series analysis of activity data to evaluate whether the amount of exercise is appropriate, statistically analyzes heart rate data to detect abnormalities, and generates advice on the frequency and range of walks based on location data.

[1450] Sentiment Analysis Engine

[1451] The emotion analysis engine recognizes emotions from the user's voice and facial expressions, for example, by analyzing the user's tone of voice and facial expressions through the camera when they speak, and assessing the user's stress level.

[1452] Server-based analysis results generation and adjustment

[1453] The server adjusts the content and tone of the advice based on the user's emotional information obtained from the emotion analysis engine. For example, if the user is feeling stressed, it generates simple care advice to reduce stress. Examples of specific advice include, "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[1454] Notification means

[1455] The device receives the analysis results from the server and notifies the user using pop-up notifications, in-app messages, and push notifications, and displays specific advice such as "Your dog needs at least a 30-minute walk today."

[1456] Examples and prompts

[1457] Specific examples

[1458] The sensor measures your dog's activity every minute and sends the data to an information processing terminal.

[1459] The device sends the received data to a server, which then analyzes the data using an AI model.

[1460] The emotion analysis engine analyzes the user's voice and facial expressions and sends emotional information to the server.

[1461] The server adjusts the advice based on the analysis results, and the device notifies the user of the analysis results.

[1462] Prompt Sentence Examples

[1463] "What advice would be effective on how to care for a user's dog if they are stressed?"

[1464] "How can I analyze my dog's activity and heart rate data to assess his health?"

[1465] In this way, a system is realized that manages the physical condition and behavior of a beloved dog while providing appropriate care advice that also takes into account the user's emotional state.

[1466] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1467] Step 1:

[1468] Sensor data acquisition

[1469] The sensor acquires the animal's activity, heart rate, and location information at regular intervals. The sensor's inputs are the animal's physical activity, location, and heart rate. The sensor measures these inputs and generates activity data, heart rate data, and location data. This data is temporarily stored in the sensor and then sent to an information processing device. For example, an acceleration sensor measures the animal's movement over one minute, a heart rate sensor simultaneously records the heart rate, and a GPS sensor identifies the animal's location.

[1470] Step 2:

[1471] Sending data to the device

[1472] The data acquired by the sensor is sent to the information processing terminal. The input to the terminal is data from the sensor, and the output is data sent to the server. The terminal receives activity level, heart rate, and location information from the sensor using Bluetooth, and sends this information along with the received timestamp to the server via an HTTP POST request. Here, the terminal formats the data and converts it into a format that is easy for the server to analyze. Specifically, the terminal compiles the data received from the sensor and sends it to the server every minute.

[1473] Step 3:

[1474] Data analysis by server

[1475] The server receives and analyzes the data sent from the device. The server's inputs are activity data, heart rate data, and location data sent from the device. The server analyzes this data using an AI model and generates an output that evaluates the animal's health, as well as analytical results on exercise volume and stress levels. Specifically, the server performs a time series analysis of the activity data to evaluate whether exercise is being performed appropriately. It also statistically analyzes the heart rate data to detect abnormalities. The location data is used to evaluate the frequency and range of walks using geographic information analysis.

[1476] Step 4:

[1477] Emotion analysis using an emotion analysis engine

[1478] The emotion analysis engine analyzes the user's voice and facial expressions to understand their emotional state. The emotion analysis engine's input is the user's voice data and facial expression data, and its output is information about their emotional state. The engine uses a microphone and camera to analyze the user's tone of voice and facial expressions. For example, the analysis results may evaluate whether the user is feeling stressed. This information is sent to the information processing terminal and then to the server.

[1479] Step 5:

[1480] Server-based analysis results generation and adjustment

[1481] The server receives the user's emotional information obtained from the emotion analysis engine and adjusts the analysis results and advice content. The server receives data based on the animal's health assessment and the user's emotional information. The server integrates this data and generates care advice based on the user's stress level. For example, if the user is feeling stressed, the server will generate advice such as, "We recommend taking a short walk to reduce stress."

[1482] Step 6:

[1483] User notification via information processing terminal

[1484] The device receives analysis results and advice from the server and notifies the user. The input to the device is the analysis results and advice sent from the server, and the output is the notification to the user. Notification methods include pop-up notifications, in-app messages, and push notifications. For example, a notification may be sent to the user saying, "Your dog needs to be walked for at least 30 minutes today."

[1485] Through these steps, the system is able to provide appropriate care advice that takes into account not only the animal's physical condition and behavior, but also the user's emotional state.

[1486] (Application example 2)

[1487] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1488] Conventional pet dog health management systems only provide general care advice based on the dog's health condition, without taking into account the owner's emotional state. As a result, it is difficult to provide appropriate advice when the owner is stressed or in a specific emotional state. Thus, there is a need for a system that provides more appropriate care methods that take into account the owner's emotional state.

[1489] The identification process 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 analyzing data acquired from the sensor and evaluating the health condition of the animal, means including an emotion engine for analyzing the emotional state of the user, and means for generating advice based on the analysis results of the server means and the user's emotional information and notifying the user via the terminal means. This makes it possible to provide advice that takes the owner's emotional state into consideration.

[1490] A "sensor" is a device for measuring an animal's activity, heart rate, and location information.

[1491] The "terminal means" is a device that receives data acquired from the sensor and transmits the data to the server means.

[1492] The "server means" is a computer system for analyzing data received from the terminal means and evaluating the health status of the animals.

[1493] An "emotion engine" is a device or system for analyzing a user's emotional state, and determines the user's emotions based on data such as voice and facial expressions.

[1494] The "analysis results" are information about the health condition and stress level of the animal that is generated by the server means by analyzing the data received from the sensor.

[1495] The "means for generating advice" is a device or computer program that allows the server means to create advice on appropriate care methods based on the analysis results and the user's emotional information.

[1496] The "notifying means" is a device or function for notifying the user of the generated advice via the terminal means.

[1497] This invention is a system for managing the physical condition and behavior of a pet dog, and is implemented using the following devices and software.

[1498] The system includes the following main components: a sensor, a terminal means, a server means, an emotion engine, and a notification means.

[1499] sensor

[1500] The sensors worn by pet dogs are measuring devices that measure the animal's activity, heart rate, and location information. Examples include acceleration sensors, heart rate sensors, and GPS sensors. These sensors are incorporated into the dog's collar or harness, and collect data at regular intervals and transmit it to a terminal via Bluetooth.

[1501] Terminal means

[1502] The terminal means is a device such as a smartphone or tablet that receives data from the sensor in real time and transmits it to the server means. For example, the terminal means transmits the amount of activity, heart rate, and location information received from the sensor via Bluetooth to the server using an HTTP POST request.

[1503] Server Means

[1504] The server means is a computer system for analyzing the received data. The specific analysis is performed as follows:

[1505] Activity data is analyzed over time to evaluate your dog's physical activity.

[1506] Heart rate data is statistically analyzed and compared with normal heart rates to detect abnormalities.

[1507] Advice is generated regarding the frequency and range of walks based on location data.

[1508] The server means adjusts the content and tone of advice based on the user's emotional information obtained from the emotion engine.

[1509] Emotion Engine

[1510] An emotion engine is a device or system for analyzing a user's voice and facial expressions to assess their emotional state. For example, an emotion engine may analyze a user's voice tone and facial expressions through a camera while they are speaking to assess whether they are feeling stressed.

[1511] Notification means

[1512] The notification means has a function to notify the user of the analysis results and advice. Information is notified to the user via the terminal means as push notifications or in-app messages. For example, when the terminal receives the analysis results from the server, it notifies the user with specific advice such as "Take a walk of at least 30 minutes today. You seem tired, so please take short breaks as well."

[1513] Specific examples

[1514] For example, if your dog is healthy but doesn't get enough exercise, you'll receive a notification saying, "Your dog is healthy, but needs more exercise." If your emotional state is analyzed as "stressed," you'll receive a notification saying, "Your dog is healthy, but needs more exercise. Please take some time to relax."

[1515] Prompt Sentence Examples

[1516] "It analyzes the user's vocal tone and facial expressions to assess their current emotional state. If the emotional state is stress, it will add a message to your dog's health advice about taking time to relax."

[1517] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1518] Step 1:

[1519] The sensor measures your dog's activity, heart rate, and location. The sensor collects this data at regular intervals and sends it to the device via Bluetooth. The input is the measured data, and the output is the data sent to the device.

[1520] Step 2:

[1521] The device receives data from the sensor and sends it to the server in real time. The device receives data via Bluetooth and sends it to the server using an HTTP POST request. The input is the data received from the sensor and the output is the data sent to the server.

[1522] Step 3:

[1523] The server analyzes the received data. The server performs time-series analysis of the activity data, statistical analysis of the heart rate data, and evaluates the frequency and range of walks based on the location data. The input is the data sent from the device, and the output is the analysis results.

[1524] Step 4:

[1525] The emotion engine analyzes the user's voice and facial expressions to evaluate their emotional state. For example, the emotion engine analyzes the user's tone of voice and facial expressions through a camera while they are speaking. The input is audio and video data, and the output is analyzed emotional information.

[1526] Step 5:

[1527] The server generates advice based on the analysis results and emotional information. The server creates advice with appropriate content and tone, taking into account the user's emotional state. The input is the analysis results and emotional information, and the output is the generated advice.

[1528] Step 6:

[1529] The device receives advice from the server and notifies the user. The device provides specific advice to the user using push notifications or in-app messages. The input is the advice sent from the server, and the output is the message notified to the user.

[1530] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1531] 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.

[1532] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1533] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1534] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1535] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1536] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1537] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1538] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1539] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1540] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1541] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1542] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1543] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1544] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1545] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1546] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1547] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1548] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1549] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1550] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1551] The following is further disclosed regarding the above embodiment.

[1552] (Claim 1)

[1553] A system for managing your dog's physical condition and behavior,

[1554] A means for measuring the activity level, heart rate, and location information of an animal using a sensor;

[1555] a terminal means for receiving data acquired from the sensor;

[1556] a server means for analyzing the data received from the terminal means and evaluating the health status of the animal;

[1557] means for notifying a user of the analysis result of said server means via a terminal means;

[1558] A system including:

[1559] (Claim 2)

[1560] 10. The system of claim 1, further comprising means for estimating the stress level of the animal and generating appropriate care advice.

[1561] (Claim 3)

[1562] The system according to claim 1, further comprising means for suggesting to the user the timing and amount of exercise for walking the animal based on the analysis results.

[1563] "Example 1"

[1564] (Claim 1)

[1565] A means for measuring the activity level, heart rate, and location information of an animal using a sensor;

[1566] a terminal means for receiving data acquired from the sensor via Bluetooth and transmitting the data with a time stamp to a server in real time;

[1567] a server means for analyzing the data received from the terminal means, assessing the health condition and stress level of the animal, and generating appropriate care advice;

[1568] means for notifying a user of the analysis result of the server means by a push notification or an in-app message;

[1569] A system including:

[1570] (Claim 2)

[1571] The system according to claim 1, further comprising means for evaluating trends in the animal's movement patterns and heart rate based on the analysis results and detecting abnormalities.

[1572] (Claim 3)

[1573] The system according to claim 1, further comprising means for suggesting to the user the timing and amount of exercise for walking the animal based on the analysis results.

[1574] "Application Example 1"

[1575] (Claim 1)

[1576] A means for measuring the activity level, heart rate, and location information of an animal using a sensor;

[1577] a terminal means for receiving data acquired from the sensor;

[1578] a server means for analyzing the data received from the terminal means and evaluating the health status of the animal;

[1579] means for notifying a user of the analysis result of said server means via a terminal means;

[1580] a means of generating recommendations for providing services in physical stores;

[1581] means for notifying a user of said recommendations;

[1582] A system including:

[1583] (Claim 2)

[1584] 10. The system of claim 1, further comprising means for estimating the stress level of the animal and generating appropriate care advice.

[1585] (Claim 3)

[1586] The system according to claim 1, further comprising means for suggesting to the user the timing and amount of exercise for walking the animal based on the analysis results.

[1587] "Example 2: Combining Emotion Engines"

[1588] (Claim 1)

[1589] A system for managing the physical condition and behavior of animals,

[1590] A means for measuring the activity level, heart rate, and location information of an animal using a sensor;

[1591] an information processing terminal that receives data acquired from the sensor;

[1592] a server device that analyzes the data received from the information processing terminal and evaluates the health condition of the animal;

[1593] means for notifying a user of the analysis result of the server device via an information processing terminal;

[1594] An emotion analysis engine that analyzes the user's voice and facial expressions to understand their emotional state,

[1595] a server device that adjusts the analysis results and the contents of advice based on the emotion information obtained by the emotion analysis engine;

[1596] A system including:

[1597] (Claim 2)

[1598] The system of claim 1, wherein the system estimates the stress level of the animal and generates advice on appropriate care methods.

[1599] (Claim 3)

[1600] 2. The system according to claim 1, which suggests to the user the timing and amount of exercise for walking the animal based on the analysis results.

[1601] "Application example 2 when combining emotion engines"

[1602] (Claim 1)

[1603] A system for managing your dog's physical condition and behavior,

[1604] A means for measuring the activity level, heart rate, and location information of an animal using a sensor;

[1605] a terminal means for receiving data acquired from the sensor;

[1606] a server means for analyzing the data received from the terminal means and evaluating the health status of the animal;

[1607] means including an emotion engine for analyzing an emotional state of a user;

[1608] means for generating advice based on the analysis results of the server means and the user's emotion information, and notifying the advice to the user via the terminal means;

[1609] A system including:

[1610] (Claim 2)

[1611] 10. The system of claim 1, further comprising means for estimating the stress level of the animal and generating appropriate care advice.

[1612] (Claim 3)

[1613] The system according to claim 1, further comprising means for suggesting to the user the timing and amount of exercise for walking the animal based on the analysis results. [Explanation of symbols]

[1614] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A system for managing your dog's physical condition and behavior, A means for measuring the activity level, heart rate, and location information of an animal using a sensor; a terminal means for receiving data acquired from the sensor; a server means for analyzing the data received from the terminal means and evaluating the health status of the animal; means for notifying a user of the analysis result of said server means via a terminal means; A system including:

2. 10. The system of claim 1, further comprising means for estimating the stress level of the animal and generating appropriate care advice.

3. The system according to claim 1 , further comprising means for suggesting to the user the timing and amount of exercise for walking the animal based on the analysis results.

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