System

Abstract

A system is provided.SOLUTION: The system includes a means for monitoring the behavior of the pet, a means for recording the bark of the pet, a means for collecting these data and transmitting them to a server, a means for analyzing the data in the server and estimating the state of the pet, a means for generating a report based on the analysis result and notifying a user, and a means for controlling a specific device based on the analysis result.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] Pet owners face the challenge of accurately understanding their pets' behavior and health. This is especially true when owners are unable to keep an eye on their pets for extended periods due to work or other outings. This makes it difficult to properly manage their pets' health and meet their needs. In these situations, there's a high chance that pets' cries and behaviors will be overlooked, potentially causing stress and health problems for the pets. Therefore, there's a need for a system that can monitor pet behavior and health in real time and provide owners with information in a format that's easy to understand. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. Specifically, the present invention provides a system including a means for monitoring pet behavior, a means for recording pet sounds, a means for collecting and transmitting this data to a server, a means for analyzing the data on the server and estimating the pet's condition, a means for generating a report based on the analysis results and notifying the user, and a means for controlling specific devices based on the analysis results. This system allows pet owners to accurately understand their pet's behavior and health condition and quickly take necessary measures. For example, by automatically controlling a pet food management device or a massage device based on the analysis results, it is possible to provide care that meets the pet's needs.

[0006] "Behavior monitoring means" refers to devices such as cameras and sensors used to record and collect information about pet movements and behavior.

[0007] The "means for recording sounds" refers to a device such as a microphone or audio recorder used to record sounds made by pets.

[0008] The "means for collecting and transmitting data to the server" refers to a communication device or software for acquiring pet behavior data and vocalization data and transferring them to the server.

[0009] "Means for analyzing data on a server and inferring the pet's condition" refers to AI models and analysis programs that analyze collected data and infer the pet's health condition and emotions.

[0010] "Means for generating a report and notifying the user" refers to software or communication functions for creating a report based on the data analysis results and notifying the user of the report on their terminal.

[0011] The "means for controlling a specific device" refers to a control device or control program for operating and adjusting a pet device (a food management device or a massage device) based on the analysis results.

[0012] "Status inference" refers to the process or algorithm used to analyze collected data and determine a pet's emotional or health state.

[0013] A "report" is an information document that summarizes the analysis results regarding your pet's behavior and health.

[0014] A "server" is a high-performance computer used to analyze and manage data and provide information. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] This invention is a system for monitoring pet behavior and health status and providing pet owners with information in a format that is easy to understand. The system includes a pet behavior monitoring device, a pet vocalization recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, and means for controlling the pet device as needed.

[0037] 1. Collecting behavior and calls

[0038] First, the device records the pet's behavior and sounds. The behavior data is acquired using cameras and sensors, and the sound data is recorded using a microphone. This data is acquired in real time or periodically.

[0039] 2. Data transmission

[0040] The collected behavioral and vocalization data is sent from the device to a server, allowing for centralized data management.

[0041] 3. Data Analysis

[0042] The server inputs the received data into an AI model for analysis. The AI ​​model infers the pet's health and emotions from its behavior and cries. The analysis uses data such as the pet's movements, characteristics of its cries, and environmental data.

[0043] 4. Reporting and Notifications

[0044] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition and mood, as well as recommended measures. The generated report is then sent from the server to the user's device. The user can use this report to understand the pet's condition and take any necessary measures.

[0045] 5. Automatic Device Control

[0046] If necessary, the server controls a pet food management device or a massage device based on the analysis results. For example, if the analysis indicates that the pet is hungry, the server instructs the food management device to provide food. If the pet is feeling stressed, the server instructs the massage device to start.

[0047] Specific examples

[0048] For example, the device collects data on the pet's behavior and cries and sends it to a server. The server inputs the received data into an AI model and analyzes it to determine that the pet is hungry. Based on this analysis result, the server sends a report to the user stating that the pet is hungry. At the same time, based on the analysis result, the server instructs the food management device to provide food to the pet. Ultimately, the user can check the pet's condition through the received report and feel at ease.

[0049] This system allows owners to keep track of their pets' conditions at all times and take prompt and appropriate action. In particular, it allows owners to manage their pets' health even when they are away from home or at work for long periods of time, reducing the burden on owners and improving the happiness of their pets.

[0050] The processing flow will be explained below.

[0051] Step 1:

[0052] The device collects pet behavior data using cameras and sensors. The camera captures images of the room in real time, and the sensors collect pet movements and environmental data (temperature, humidity, etc.).

[0053] Step 2:

[0054] The device will record your pet's cries with a microphone. The microphone will record your pet's cries for a set period of time (e.g., 10 seconds).

[0055] Step 3:

[0056] The device sends the collected behavioral and vocalization data to a server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0057] Step 4:

[0058] The server archives the received data, stores it in a database, and prepares it for later analysis.

[0059] Step 5:

[0060] The server inputs the saved data into the AI ​​model, which then inputs the behavioral data, sensor data, and bird call data all at once and begins analysis.

[0061] Step 6:

[0062] The server receives the analysis results from the AI ​​model, which then infers the pet's health and emotions from its behavior and cries, and returns the results.

[0063] Step 7:

[0064] The server generates a report based on the analysis, including the pet's current health and mood, as well as recommended actions to take.

[0065] Step 8:

[0066] The server notifies the user of the generated report via push notification, email, or other means so that the user can check it immediately.

[0067] Step 9:

[0068] The user checks the received report, understands the pet's condition through the report content, and considers what action to take if necessary.

[0069] Step 10:

[0070] The server controls specific devices based on the analysis results, for example, instructing a pet food management device to provide food or issuing a command to activate a massage device.

[0071] Step 11:

[0072] The terminal controls the food management device and massage device based on instructions from the server, allowing care to be automatically provided according to the pet's needs.

[0073] Example 1

[0074] 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."

[0075] In modern society, pet owners often find it difficult to manage their pets' health due to long periods of time away from home or at work. A method for properly monitoring pet behavior and health status and responding quickly is needed. In particular, there is a need for early detection of pet hunger and stress and appropriate measures to be taken.

[0076] 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.

[0077] In this invention, the server includes means for monitoring the behavior of the pet, means for recording the sounds of the pet, means for collecting and transmitting this data to the server, means for analyzing the data in the server and estimating the pet's condition using a generative AI model, means for inputting the data into the generative AI model using a prompt sentence, means for generating a report based on the analysis result and notifying the user, and means for controlling a specific device based on the analysis result, thereby enabling the owner to always be aware of the pet's condition and respond quickly and appropriately.

[0078] "Means for monitoring pet behavior" refers to devices or technologies for detecting and recording pet movements, including cameras and sensors.

[0079] "Means for recording pet sounds" refers to devices or technologies for recording pet sounds as audio data, including highly sensitive microphones.

[0080] "Means for collecting and transmitting this data to a server" refers to devices and technologies for transmitting the collected behavioral data and vocalization data to a central server via a network, including wireless communication technologies such as Wi-Fi and Bluetooth.

[0081] "Means for analyzing data on a server and using a generative AI model to infer a pet's condition" refers to technology that analyzes data received on a server and uses an AI model to infer a pet's health condition and emotions.

[0082] "Means for inputting data into a generative AI model using prompt sentences" refers to a technology in which a server inputs specific prompt sentences into a generative AI model and performs analysis.

[0083] "Means of generating a report based on the analysis results and notifying the user" refers to technology that creates a report based on the results of data analysis and notifies the user via email or a dedicated app.

[0084] "Means for controlling specific devices based on the analysis results" refers to technology for remotely controlling specific devices for pets based on the results of data analysis. Specifically, this includes feeding devices and massage devices.

[0085] This invention is a system for monitoring the behavior and health of pets and providing information to owners in a format that is easy to understand. This system includes the following components:

[0086] Hardware Configuration

[0087] The device uses a camera, sensors, and microphone to record your pet's behavior and sounds. The camera monitors your pet's movements, assisted by accelerometers and gyro sensors. The microphone records your pet's sounds. This data is then sent to a server using wireless communication technologies such as Wi-Fi or Bluetooth.

[0088] Software Configuration

[0089] The server inputs the received data into an AI model for analysis. The AI ​​model used here is trained using frameworks such as TensorFlow and PyTorch, which are developed in Python. The AI ​​model infers the pet's health status and emotions based on its behavior and vocalizations. Based on the analysis results, the server generates a report and notifies the user via email or a dedicated app.

[0090] The server also controls specific pet devices as needed. For example, if the server determines that the pet is hungry, it will instruct a feeding device to provide food. If the server determines that the pet is stressed, it will instruct a massage device to start.

[0091] Specific examples

[0092] For example, a device collects data on a pet's behavior and vocalizations and sends it to a server via Wi-Fi. The server preprocesses the received data using a Python script and inputs it into an AI model trained with TensorFlow. The required prompt is, "Please analyze the current state of your pet based on this behavior and vocalization data."

[0093] If the AI ​​model determines that the pet is hungry, the server generates a report and notifies the user that the pet is hungry. At the same time, it instructs the feeder to provide food. The user checks the email notification and confirms that the feeder has automatically provided food after returning home.

[0094] This system allows owners to keep track of their pets' conditions at all times and take prompt and appropriate action. In particular, it allows owners to manage their pets' health even when they are away from home or at work for long periods of time, reducing the burden on owners and improving the happiness of their pets.

[0095] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0096] Step 1: Collecting behaviors and sounds

[0097] The device collects pet behavior and vocalization data. The input is real-time data from the camera, sensors, and microphone. The device acquires this data at regular intervals and stores it locally. Specifically, the device takes video with the camera, detects movement with the sensor, and records audio with the microphone. The output is files of behavior and vocalization data.

[0098] Step 2: Sending data

[0099] The device sends the collected behavioral data and call data to the server. The input is the data file generated in step 1. The device uses Wi-Fi or Bluetooth to send an HTTP POST request to the server. Specifically, the device compresses the data files and uploads them to the server via the network. The output is the behavioral data and call data stored on the server.

[0100] Step 3: Data Preprocessing

[0101] The server preprocesses the received data. The input is the raw data received in step 2. The server denoises the data and extracts the required features. Specifically, it cleans and standardizes the data using a Python script. The output is the preprocessed data.

[0102] Step 4: Data analysis

[0103] The server inputs data into the generated AI model for analysis. The input is the data preprocessed in step 3 and a prompt saying, "Please analyze your pet's current state based on this behavioral data and vocalization data." The server passes the data to the TensorFlow model and classifies the pet's state. Specifically, the server invokes the model through an API and performs inference. The output is the analysis result of the pet's state (e.g., hunger, stress, contentment, etc.).

[0104] Step 5: Reporting and Notifications

[0105] The server generates a report based on the analysis results and notifies the user. The input is the analysis results obtained in step 4. The server generates the report in HTML or PDF format and sends a notification via email or a dedicated app. Specifically, the server creates the report using a template engine and sends it via email using an SMTP server. The output is the report sent to the user.

[0106] Step 6: Device Control

[0107] The server controls a specific device based on the analysis results. The input is the analysis results obtained in step 4. The server makes API calls to the feeding device or massage device to issue the necessary instructions. Specifically, the server sends an HTTP request to the device's API endpoint. The output is the execution result of the action (e.g., feeding, massage) performed by the specific device.

[0108] In this way, it is possible to monitor a pet's behavior and cries, understand the pet's health condition based on the analysis results, and prompt the owner to take appropriate action.

[0109] (Application example 1)

[0110] 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."

[0111] Conventional pet management systems make it difficult for owners to understand their pets' health conditions and emotions in real time. Furthermore, physical stores such as pet shops lack a means for customers to immediately check the health status of pets they are considering purchasing. Therefore, there is a need for a new system to manage pet health and support customers' purchasing decisions.

[0112] 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.

[0113] In this invention, the server includes means for monitoring the behavior of the pet, means for recording the sounds the pet makes, means for collecting this data and transmitting it to the server, means for analyzing the data in the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for notifying the user's communication terminal of the analyzed pet's health condition in real time, and means for customers to easily understand the pet's health condition in a physical store such as a pet shop. This allows owners to remotely understand the health condition and emotions of their pet, and enables customers in a physical store to check the pet's health condition in detail when considering a purchase.

[0114] A "means for monitoring behavior" is a device that records a pet's movements using a camera or motion sensor.

[0115] The "means for recording sounds" is a microphone device that collects the sounds and voices of pets.

[0116] The "means for collecting and transmitting data to a server" is a communication device that transmits behavioral data and sound data obtained from a pet to a server via the Internet.

[0117] "Means for analyzing data and inferring status" refers to a method of analyzing collected data using AI models or other methods to infer a pet's health condition and emotions.

[0118] The "means for generating a report and notifying the user" refers to an application or system for creating a report based on the analysis results and notifying the communication terminal.

[0119] The "means for controlling a specific device" is a mechanism for remotely controlling devices such as pet food management devices and massage devices based on the analysis results.

[0120] The "means of notifying a communication terminal in real time" is a system that instantly sends information about a pet's health condition to the user's smartphone or tablet.

[0121] "Means for understanding pet health conditions in physical stores" refers to interfaces or applications that allow customers at pet shops and other locations to easily check the health conditions of their pets.

[0122] In order to implement this invention, the following systems and processes must be established.

[0123] First, cameras and motion sensors to monitor pet behavior and microphones to record sounds are installed in the pet's environment. These devices are connected to a communication device (e.g., a Wi-Fi module) that collects behavioral and sound data from the pet and transmits it to a server via the Internet.

[0124] On the server side, the received data is analyzed using a generative AI model. The AI ​​model uses machine learning frameworks such as TensorFlow and PyTorch. The AI ​​model analyzes behavioral and vocalization data to predict the pet's health and emotions. The analysis uses the pet's movements, vocalization characteristics, and environmental data. For example, if the pet moves little or vocalizes frequently, it may be determined that the pet is unwell or stressed.

[0125] Based on the analysis results, the server generates a report and notifies the user in real time on their communication device. The user's communication device is a smartphone or tablet with a notification application installed. The notification application displays a report based on the analysis results, allowing the user to immediately check the status of their pet.

[0126] Furthermore, the server controls specific devices such as a food management device and a massage device as needed. For example, if the server determines that the pet is hungry, it issues an instruction to the food management device to provide food. If the server determines that the pet is stressed, it activates the massage device.

[0127] This system can also be applied in brick-and-mortar stores such as pet shops. Pet shop managers use monitoring devices installed in the store to monitor the behavior and sounds of pets. When customers want to check on their pet's health, an interface or application is used to provide that information in real time. This allows customers to have a detailed understanding of their pet's health when considering a purchase.

[0128] Specific examples

[0129] For example, when a pet shop manager sends data collected on a device to a server, the server begins analysis using an AI model. Based on the analysis results, a report is generated stating, "This pet is healthy and active. It has been playing a lot recently and is eating well." This report can be viewed by customers on their smartphones.

[0130] Prompt Sentence Examples

[0131] "Analyze this pet's current health and emotional state based on its behavioral and vocalization data and generate a report. Behavior data: [data format], Vocalization data: [data format]."

[0132] The above is the basic system configuration and processing method for implementing this invention. This system allows pet owners and pet shop customers to understand the health status of their pets in real time and take appropriate measures.

[0133] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0134] Step 1:

[0135] The device collects the pet's behavior and sounds. Specifically, it records the pet's movements with a camera and motion sensors, and records the pet's sounds with a microphone. These input data are behavior data and sound data, and are collected in real time or periodically.

[0136] Step 2:

[0137] The terminal sends the collected data to a server. Specifically, it uses a communication device such as a Wi-Fi module to upload the collected behavioral data and bird call data to the server via the Internet. The server receives this data and manages it centrally.

[0138] Step 3:

[0139] The data received by the server is analyzed using an AI model. Specifically, using machine learning frameworks such as TensorFlow and PyTorch, behavioral data and vocalization data are input into the model to predict the pet's health and emotions. This process determines the pet's condition from its movement patterns and vocalization characteristics. For example, abnormalities such as low activity or excessive vocalizations can be detected.

[0140] Step 4:

[0141] The server generates a report based on the analysis results. Specifically, it creates a report based on the health status and emotions obtained from the analysis results and summarizes it in an easy-to-understand format for the user. The report includes a specific explanation of the situation and recommended measures.

[0142] Step 5:

[0143] The server sends the generated report to the communication device. Specifically, the report is pushed to a smartphone or tablet in real time. The user can receive this notification and check the status of their pet.

[0144] Step 6:

[0145] The server controls specific devices as needed. Specifically, it sends instructions to devices such as a food management device and a massage device based on the analysis results. For example, if the analysis indicates that the pet is hungry, the server instructs the food management device to provide food. If the server determines that the pet is feeling stressed, it will activate a massage device.

[0146] Step 7:

[0147] The user checks the report on the communication terminal and takes necessary action regarding the pet's condition. Specifically, the user opens the notification application and checks the contents of the report. Based on this information, the owner can take care of the pet. In addition, customers at pet shops can understand the health condition of their pets and make purchasing decisions.

[0148] This is the specific flow of processing in this system, which allows pet owners and pet shop customers to understand the health status of their pets in real time and take appropriate measures.

[0149] 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.

[0150] This invention is a system that monitors the behavior and health status of pets and provides information to owners in a format that is easy to understand, in addition to combining it with an emotion engine that recognizes the user's emotions. The system includes a pet behavior monitoring device, a bark recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, specific device control means, and an emotion engine that recognizes the user's emotions.

[0151] 1. Collecting behavior and calls

[0152] First, the device collects data on your pet's behavior using cameras and sensors. The camera captures images of the room in real time, and the sensors collect data on your pet's movements and the environment (temperature, humidity, etc.). Additionally, the device uses a microphone to record your pet's cries. This data is collected in real time or periodically.

[0153] 2. Data transmission

[0154] The collected behavioral and vocalization data is sent from the device to a server, where it is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0155] 3. Data Analysis

[0156] The server inputs the received data into an AI model for analysis. The AI ​​model analyzes behavioral data, sensor data, and vocalization data to predict the pet's health and emotions. The analysis takes into account the pet's movements, vocalization characteristics, and environmental data.

[0157] 4. Use of Emotion Engine

[0158] The server uses an emotion engine that recognizes the user's emotions. The emotion engine reads emotions from the user's voice, facial expressions, messages, etc. and incorporates them into the analysis data. This allows the user's emotions to be used as a basis for decision-making throughout the system.

[0159] 5. Reporting and Notifications

[0160] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition, emotions, and recommended measures. The report content and notification method are also adjusted taking into account the user's emotional information. The generated report is sent from the server to the user's device. The user can understand the pet's condition through this report and take any necessary measures.

[0161] 6. Automatic Device Control

[0162] Based on the analysis results, the server controls specific devices. For example, it can instruct a pet food management device to provide food or start a massage device. The control content can also be adjusted taking into account the user's emotional information.

[0163] Specific examples

[0164] For example, the device collects data on the pet's behavior and cries and sends it to a server. The server then uses an AI model to analyze the received data and obtains the result that "your pet is hungry." At the same time, the emotion engine analyzes the user's voice message and recognizes that the user is currently feeling stressed. Based on this information, the server notifies the user with a report such as "your pet is hungry, but please consider giving it a massage to relieve stress." The server also issues instructions to a food management device to provide food and to activate a massage device, thereby automatically caring for the pet.

[0165] This system allows owners to quickly understand their pet's condition and take optimal measures based on their own emotional state, which is particularly useful when they are away from home or at work for long periods of time, increasing the happiness of both pets and their owners.

[0166] The processing flow will be explained below.

[0167] Step 1:

[0168] The device collects pet behavior data using cameras and sensors. The camera captures images of the room in real time, and the sensors collect pet movements and environmental data (temperature, humidity, etc.).

[0169] Step 2:

[0170] The device will record your pet's cries with a microphone. The microphone will record your pet's cries for a set period of time (e.g., 10 seconds).

[0171] Step 3:

[0172] The device sends the collected behavioral and vocalization data to the server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0173] Step 4:

[0174] The server archives the received data, stores it in a database, and prepares it for later analysis.

[0175] Step 5:

[0176] The server inputs the saved data into the AI ​​model, which then inputs the behavioral data, sensor data, and bird call data all at once and begins analysis.

[0177] Step 6:

[0178] The server receives the analysis results from the AI ​​model, which then infers the pet's health and emotions from its behavior and cries, and returns the results.

[0179] Step 7:

[0180] The server uses an emotion engine to recognize the user's emotions. The emotion engine reads emotions from the user's voice, facial expressions, messages, etc., and incorporates this data into the analysis data.

[0181] Step 8:

[0182] The server generates a report based on the analysis results, including the pet's current health status, mood, and recommended actions, as well as the user's emotional information.

[0183] Step 9:

[0184] The server notifies the user of the generated report via push notification, email, or other means so that the user can check it immediately.

[0185] Step 10:

[0186] The user checks the received report, understands the pet's condition through the report content, and considers what action is necessary.

[0187] Step 11:

[0188] The server controls specific devices based on the analysis results. For example, if the analysis indicates that the pet is hungry, it will instruct the food management device to provide food. If the pet is feeling stressed, it will issue a command to activate a massage device. These instructions are given taking into account the user's emotional information.

[0189] Step 12:

[0190] The terminal controls the food management device and massage device based on instructions from the server, allowing care to be automatically provided according to the pet's needs.

[0191] Example 2

[0192] 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."

[0193] Conventional pet monitoring systems have difficulty accurately understanding the health and emotions of pets, and do not provide measures that take into account the emotions of owners, making it impossible to optimize the happiness of both pets and owners.

[0194] 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.

[0195] In this invention, the server includes means for inputting the received data into an AI model and analyzing the behavioral data, environmental data, and bark data to estimate the pet's health condition and emotions, means for recognizing the user's emotions and incorporating them into the analysis data, and means for generating a report based on the analysis results and notifying the user. This makes it possible to grasp the pet's condition in detail and take optimal measures taking the user's emotions into consideration.

[0196] "Behavior monitoring means" refers to devices such as cameras and sensors that detect and record the movements of pets.

[0197] A "means for recording pet sounds" is a microphone or recording device for recording pet sounds.

[0198] The "means for collecting and transmitting data to a server" refers to a communication device and a network interface for transmitting behavioral data and vocalization data to a server.

[0199] "Means for inputting data into an AI model and analyzing it" refers to a processor and algorithm for inputting received data into an artificial intelligence model and analyzing it.

[0200] "Means for recognizing user emotions" refers to analytical software and hardware for reading emotions from the user's voice, messages, facial expressions, etc.

[0201] The "means for generating a report and notifying the user" refers to a system and interface for automatically generating a report based on the analysis results and notifying the user.

[0202] The "means for controlling a specific device" refers to a control device and software for automatically operating or managing a pet-related device based on the analysis results.

[0203] This invention is a system that monitors the behavior and health status of pets and provides information to owners in a format that is easy to understand, in addition to combining it with an emotion engine that recognizes the user's emotions. The system includes a pet behavior monitoring device, a bark recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, specific device control means, and an emotion engine that recognizes the user's emotions.

[0204] First, the device collects pet behavior data using a camera or sensor. The camera captures video of the room in real time, and the sensor collects pet movements and environmental data (temperature, humidity, etc.). Specific hardware examples include the Logitech C920 camera and DHT22 sensor. Additionally, the device records the pet's cries using a microphone (e.g., Blue Yeti). This data is collected in real time or periodically.

[0205] The collected behavioral and vocalization data is sent from the device to a server. The data is appropriately packetized and transmitted over a communication network (e.g., Wi-Fi). The device is based on, for example, a Raspberry Pi, and the data is sent using the Python requests library via an HTTP POST request.

[0206] The server inputs the received data into an AI model for analysis. The AI ​​model analyzes behavioral data, sensor data, and vocalization data to predict the pet's health and emotions. The specific software used is an AI model that uses TensorFlow and PyTorch. The analysis results can determine, for example, whether the pet is in a "stressed," "hungry," or "relaxed" state.

[0207] The server then uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's voice and text messages using Google Cloud's Natural Language API to determine whether the user is feeling stressed or relaxed.

[0208] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition, emotions, and recommended measures. The report content and notification method are also adjusted taking into account the user's emotional information. For example, a template engine (e.g., Jinja2) can be used to generate a PDF report and send it to an Android or iOS app. Important information can also be sent to the user via SMS or push notification.

[0209] The server then controls specific devices based on the analysis, such as sending a command to a Furbo dog camera to dispense treats or remotely activating a Lurvig pet massager.

[0210] Examples of prompt statements

[0211] markdown

[0212] Prompt statement

[0213] Analyze the following data to infer the pet's health and emotions, generate a report with recommendations for the owner, and control the device appropriately, taking into account the user's emotions.

[0214] Pet behavior data (movement, temperature, humidity)

[0215] Pet sound data

[0216] User emotion data (voice, message)

[0217] Example data

[0218] Movement: Almost no movement

[0219] Temperature: 22°C

[0220] Humidity: 45%

[0221] Call: A series of high-pitched sounds

[0222] User emotion: Feeling stressed (analyzed from messages)

[0223] output

[0224] This system allows owners to quickly understand their pet's condition and take optimal measures based on their own emotional state, which is particularly useful when they are away from home or at work for long periods of time, increasing the happiness of both pets and their owners.

[0225] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0226] Step 1:

[0227] First, the device collects pet behavior data using a camera (e.g., Logitech C920) or a sensor (e.g., DHT22). The camera captures video of the room in real time, and the sensor collects pet movements and environmental data (temperature, humidity, etc.). The device then records the pet's cries using a microphone (e.g., Blue Yeti).

[0228] Input: Real-time data on pet behavior and environment, barks

[0229] Output: behavioral data, vocalization data, environmental data

[0230] What it does: The device collects data from the camera and sensors and temporarily stores it locally. Every time motion is detected, the camera image is updated and the sensors record temperature and humidity data. Every time sound is detected, the audio recording is updated.

[0231] Step 2:

[0232] The device sends the collected behavioral data and vocalization data to the server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0233] Input: behavioral data, vocalization data, environmental data

[0234] Output: Packet data sent to the server

[0235] How it works: The device splits the collected data into packets, encrypts them, and then sends them to the cloud server via Wi-Fi, using the Python requests library to make an HTTP POST request.

[0236] Step 3:

[0237] The server inputs the received data into an AI model for analysis, which then analyzes the behavioral, sensor, and vocalization data to predict the pet's health and emotions.

[0238] Input: Data received from the terminal

[0239] Output: Health status and emotion predictions

[0240] How it works: After verifying the format of the received data, the server inputs it into an AI model trained with TensorFlow and PyTorch. The AI ​​model analyzes the data and classifies the pet's state, for example, determining whether it is "stressed," "hungry," or "relaxed."

[0241] Step 4:

[0242] The server recognizes the user's emotions using an emotion engine, which analyzes the user's voice messages and text messages to read the user's emotions.

[0243] Input: User's voice message, text message

[0244] Output: User's emotional state

[0245] How it works: The server uses Google Cloud's Natural Language API to analyze voice and text messages received from users. Based on the analysis results, it determines the user's emotional state, such as whether they are "stressed" or "relaxed."

[0246] Step 5:

[0247] The server then uses the analysis results to generate a report for the owner, which includes the pet's current health and mood, as well as recommended treatments.

[0248] Input: Health status, emotional predictions, and user emotional state

[0249] Output: Report for owner

[0250] Specific operation: The server uses a template engine (e.g., Jinja2) to automatically generate a PDF report based on the analysis results. The generated report is sent to the user via an Android or iOS app. Important notifications are also sent via SMS or push notification.

[0251] Step 6:

[0252] The server controls specific devices based on the analysis results, for example, instructing a pet food management device to provide food or starting a massage device.

[0253] Input: Health and emotional predictions, and the user's emotional state

[0254] Output: Device control instructions

[0255] Specific operation: Based on the analysis results, the server sends an instruction to the Furbo dog camera to distribute treats, and also sends a remote activation signal to the Lurvig pet massager.

[0256] The above is the flow of processing by the system.

[0257] (Application example 2)

[0258] 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."

[0259] While systems that monitor pet behavior and health already exist, they do not take into account the owner's mental state, making it difficult to provide appropriate care based on the owner's emotional state. Furthermore, there is a lack of systems that automatically suggest food delivery or special services based on the pet's condition. This places a heavy burden on owners in caring for their pets, making them prone to stress.

[0260] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0261] In this invention, the server includes means for monitoring the pet's behavior, means for recording the pet's cries, means for collecting and transmitting this data to the server, means for analyzing the data in the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for using an emotion engine that recognizes the user's emotions, and means for proposing recommended measures and food delivery in consideration of the pet's health condition and the user's emotional state. This allows for optimal care and response by taking into account not only the pet's condition but also the owner's emotional state. Furthermore, by proposing food delivery according to the pet's condition, it is possible to reduce the owner's burden and increase the happiness of both the pet and the owner.

[0262] "Means for monitoring pet behavior" refers to devices or systems that use cameras or motion sensors to record and understand pet movements and locations in real time.

[0263] A "means for recording pet cries" is a device or system that uses a microphone to collect the voices and cries of pets and save them as audio data.

[0264] The "means for collecting and transmitting this data to the server" refers to a communication device or system for transferring the monitored behavior data and recorded animal vocalization data to the server via a network.

[0265] "Means for analyzing data on a server and inferring a pet's condition" refers to a system that uses AI programs and algorithms on a server to analyze collected data and infer a pet's health and behavioral status.

[0266] The "means for generating a report based on the analysis results and notifying the user" refers to a device or system for creating a report on the pet's condition based on the analyzed data and notifying the user of the report.

[0267] The "means for controlling a specific device based on the analysis results" is a system for remotely operating and controlling a pet device (e.g., a food management device or a massage device) based on the analysis results.

[0268] The "means for using an emotion engine that recognizes the user's emotions" refers to software or hardware for reading and analyzing emotions from the user's voice, facial expressions, and messages.

[0269] "A means for proposing recommended measures and food delivery taking into consideration the pet's health condition and the user's emotional state" is a system that comprehensively assesses the pet's analysis results and the user's emotional state to provide appropriate measures (e.g., special food suggestions and delivery).

[0270] This invention is a system for monitoring the behavior and health condition of a pet and providing appropriate information and responses to the owner. The system includes means for monitoring the behavior of the pet, means for recording the pet's cries, means for collecting this data and sending it to a server, means for analyzing the data on the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for using an emotion engine that recognizes the user's emotions, and means for suggesting recommended measures and food delivery in consideration of the pet's health condition and the user's emotional state.

[0271] An embodiment of this system is described in detail below.

[0272] Hardware and Software Configuration

[0273] Hardware:

[0274] 1. Smart cameras (e.g. Nest Cam): Monitor and record your pet's behavior in real time.

[0275] 2. Microphone (e.g. smartphone built-in microphone): Record your pet's cries.

[0276] 3. Communication terminal (e.g., smartphone): A device used to send collected data to a server.

[0277] software:

[0278] 1. OpenCV: Analyzes camera footage and detects pet movements.

[0279] 2. EmotionEngine: Recognizes emotions from user voice and messages.

[0280] 3. FoodDeliveryService: A service for arranging food delivery.

[0281] 4. Requests: HTTP request library for data communication.

[0282] Data collection and transmission

[0283] The smart camera captures images of your pet and analyzes the pet's behavior data using OpenCV. This records the pet's movements and behavior patterns. At the same time, the microphone records the pet's barks and saves them as audio data. This data is then sent to the server via the communication terminal.

[0284] Data analysis and inference

[0285] The server inputs the collected behavioral and vocalization data into an AI model to analyze the pet's health and emotions. The analysis uses behavioral patterns, vocalization characteristics, and environmental data. It also uses the user's emotion engine to recognize emotions from the user's voice and messages and incorporate them into the analysis data. This allows for a comprehensive evaluation of the condition of both the pet and the user.

[0286] Reporting and Notifications

[0287] Based on the analysis results, the server generates a report for the owner, which includes the pet's health status, emotions, and recommended measures. The report also takes into account the user's emotional information and adjusts the report content and notification method. The generated report is sent to a communication device, allowing the owner to understand the pet's condition and take any necessary measures.

[0288] Device control and food delivery proposals

[0289] Based on the analysis results, the server controls specific devices. For example, it can instruct a pet food management device to provide food or activate a massage device. It can also suggest the delivery of appropriate food or stress-relieving items depending on the user's emotional state. This allows optimal care even when the owner is feeling stressed.

[0290] Specific examples

[0291] For example, if the analysis results show that the pet is tired and the user is also feeling stressed, the server will suggest special nutritious food through the food delivery service, along with relaxing items, allowing both pet and owner to live a happy and healthy life.

[0292] Example prompt sentence:

[0293] "Pet is lying on the floor," "Pet is not making much noise," "User is feeling stressed"

[0294] Based on this, the system generates a report suggesting "feeding the pet special nutritious food" and "delivering relaxation items to the user."

[0295] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0296] Step 1:

[0297] Data collection

[0298] The device uses a smart camera and microphone to collect data on pet behavior and barks in real time. The smart camera captures the pet's movements and position as video and analyzes and digitizes it using OpenCV. The microphone records the pet's barks and stores them as audio data.

[0299] Input: Real-time video of pet, pet barking

[0300] Output: behavioral data, audio data

[0301] Step 2:

[0302] Sending data

[0303] The device sends the collected behavioral data and vocalization data to the server via a communication network (e.g., Wi-Fi). The data is properly packetized and securely transferred to the server.

[0304] Input: behavioral data, audio data

[0305] Output: Data sent to the server

[0306] Step 3:

[0307] Data analysis

[0308] The server inputs the received data into an AI model that analyzes the pet's health and emotions. The AI ​​model then comprehensively assesses behavioral patterns, vocalization characteristics, environmental data, and other factors to predict the pet's condition.

[0309] Input: Received data (behavioral data, voice data)

[0310] Output: Analysis of pet's health and emotional state

[0311] Step 4:

[0312] User sentiment analysis

[0313] The server uses an emotion engine to recognize emotions from the user's voice and messages. The user's emotional state data is integrated with the analysis results and becomes the basis for the system's overall decision-making.

[0314] Input: User's voice message

[0315] Output: User's emotional state

[0316] Step 5:

[0317] Reporting and Notifications

[0318] The server generates a report based on the pet's analysis results and the user's emotional state. The report includes the pet's current health condition and emotions, as well as recommended measures. The generated report is sent to the communication device.

[0319] Input: Analysis results of pet health and emotional state, user emotional state

[0320] Output: Report for owner

[0321] Step 6:

[0322] Device control and food delivery suggestions

[0323] Based on the analysis results, the server controls specific devices (e.g., food management devices, massage devices), and, if necessary, suggests suitable food and relaxation items for pets through a food delivery service.

[0324] Input: Analysis results of pets, reports based on the user's emotional state

[0325] Output: Device control instructions, food delivery suggestions

[0326] Example: If the analysis shows that the pet is tired and the user is perceived as stressed, the server will suggest the delivery of nutritious food and relaxation items.

[0327] Example prompt sentence:

[0328] "Pet is lying on the floor," "Pet is not making much noise," "User is feeling stressed"

[0329] 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.

[0330] 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.

[0331] 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.

[0332] [Second embodiment]

[0333] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0334] 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.

[0335] 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).

[0336] 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.

[0337] 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.

[0338] 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).

[0339] 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.

[0340] 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.

[0341] 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.

[0342] 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.

[0343] 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.

[0344] 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."

[0345] This invention is a system for monitoring pet behavior and health status and providing pet owners with information in a format that is easy to understand. The system includes a pet behavior monitoring device, a pet vocalization recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, and means for controlling the pet device as needed.

[0346] 1. Collecting behavior and calls

[0347] First, the device records the pet's behavior and sounds. The behavior data is acquired using cameras and sensors, and the sound data is recorded using a microphone. This data is acquired in real time or periodically.

[0348] 2. Data transmission

[0349] The collected behavioral and vocalization data is sent from the device to a server, allowing for centralized data management.

[0350] 3. Data Analysis

[0351] The server inputs the received data into an AI model for analysis. The AI ​​model infers the pet's health and emotions from its behavior and cries. The analysis uses data such as the pet's movements, characteristics of its cries, and environmental data.

[0352] 4. Reporting and Notifications

[0353] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition and mood, as well as recommended measures. The generated report is then sent from the server to the user's device. The user can use this report to understand the pet's condition and take any necessary measures.

[0354] 5. Automatic Device Control

[0355] If necessary, the server controls a pet food management device or a massage device based on the analysis results. For example, if the analysis indicates that the pet is hungry, the server instructs the food management device to provide food. If the pet is feeling stressed, the server instructs the massage device to start.

[0356] Specific examples

[0357] For example, the device collects data on the pet's behavior and cries and sends it to a server. The server inputs the received data into an AI model and analyzes it to determine that the pet is hungry. Based on this analysis result, the server sends a report to the user stating that the pet is hungry. At the same time, based on the analysis result, the server instructs the food management device to provide food to the pet. Ultimately, the user can check the pet's condition through the received report and feel at ease.

[0358] This system allows owners to keep track of their pets' conditions at all times and take prompt and appropriate action. In particular, it allows owners to manage their pets' health even when they are away from home or at work for long periods of time, reducing the burden on owners and improving the happiness of their pets.

[0359] The processing flow will be explained below.

[0360] Step 1:

[0361] The device collects pet behavior data using cameras and sensors. The camera captures images of the room in real time, and the sensors collect pet movements and environmental data (temperature, humidity, etc.).

[0362] Step 2:

[0363] The device will record your pet's cries with a microphone. The microphone will record your pet's cries for a set period of time (e.g., 10 seconds).

[0364] Step 3:

[0365] The device sends the collected behavioral and vocalization data to a server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0366] Step 4:

[0367] The server archives the received data, stores it in a database, and prepares it for later analysis.

[0368] Step 5:

[0369] The server inputs the saved data into the AI ​​model, which then inputs the behavioral data, sensor data, and bird call data all at once and begins analysis.

[0370] Step 6:

[0371] The server receives the analysis results from the AI ​​model, which then infers the pet's health and emotions from its behavior and cries, and returns the results.

[0372] Step 7:

[0373] The server generates a report based on the analysis, including the pet's current health and mood, as well as recommended actions to take.

[0374] Step 8:

[0375] The server notifies the user of the generated report via push notification, email, or other means so that the user can check it immediately.

[0376] Step 9:

[0377] The user checks the received report, understands the pet's condition through the report content, and considers what action to take if necessary.

[0378] Step 10:

[0379] The server controls specific devices based on the analysis results, for example, instructing a pet food management device to provide food or issuing a command to activate a massage device.

[0380] Step 11:

[0381] The terminal controls the food management device and massage device based on instructions from the server, allowing care to be automatically provided according to the pet's needs.

[0382] Example 1

[0383] 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."

[0384] In modern society, pet owners often find it difficult to manage their pets' health due to long periods of time away from home or at work. A method for properly monitoring pet behavior and health status and responding quickly is needed. In particular, there is a need for early detection of pet hunger and stress and appropriate measures to be taken.

[0385] 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.

[0386] In this invention, the server includes means for monitoring the behavior of the pet, means for recording the sounds of the pet, means for collecting and transmitting this data to the server, means for analyzing the data in the server and estimating the pet's condition using a generative AI model, means for inputting the data into the generative AI model using a prompt sentence, means for generating a report based on the analysis result and notifying the user, and means for controlling a specific device based on the analysis result, thereby enabling the owner to always be aware of the pet's condition and respond quickly and appropriately.

[0387] "Means for monitoring pet behavior" refers to devices or technologies for detecting and recording pet movements, including cameras and sensors.

[0388] "Means for recording pet sounds" refers to devices or technologies for recording pet sounds as audio data, including highly sensitive microphones.

[0389] "Means for collecting and transmitting this data to a server" refers to devices and technologies for transmitting the collected behavioral data and vocalization data to a central server via a network, including wireless communication technologies such as Wi-Fi and Bluetooth.

[0390] "Means for analyzing data on a server and using a generative AI model to infer a pet's condition" refers to technology that analyzes data received on a server and uses an AI model to infer a pet's health condition and emotions.

[0391] "Means for inputting data into a generative AI model using prompt sentences" refers to a technology in which a server inputs specific prompt sentences into a generative AI model and performs analysis.

[0392] "Means of generating a report based on the analysis results and notifying the user" refers to technology that creates a report based on the results of data analysis and notifies the user via email or a dedicated app.

[0393] "Means for controlling specific devices based on the analysis results" refers to technology for remotely controlling specific devices for pets based on the results of data analysis. Specifically, this includes feeding devices and massage devices.

[0394] This invention is a system for monitoring the behavior and health of pets and providing information to owners in a format that is easy to understand. This system includes the following components:

[0395] Hardware Configuration

[0396] The device uses a camera, sensors, and microphone to record your pet's behavior and sounds. The camera monitors your pet's movements, assisted by accelerometers and gyro sensors. The microphone records your pet's sounds. This data is then sent to a server using wireless communication technologies such as Wi-Fi or Bluetooth.

[0397] Software Configuration

[0398] The server inputs the received data into an AI model for analysis. The AI ​​model used here is trained using frameworks such as TensorFlow and PyTorch, which are developed in Python. The AI ​​model infers the pet's health status and emotions based on its behavior and vocalizations. Based on the analysis results, the server generates a report and notifies the user via email or a dedicated app.

[0399] The server also controls specific pet devices as needed. For example, if the server determines that the pet is hungry, it will instruct a feeding device to provide food. If the server determines that the pet is stressed, it will instruct a massage device to start.

[0400] Specific examples

[0401] For example, a device collects data on a pet's behavior and vocalizations and sends it to a server via Wi-Fi. The server preprocesses the received data using a Python script and inputs it into an AI model trained with TensorFlow. The required prompt is, "Please analyze the current state of your pet based on this behavior and vocalization data."

[0402] If the AI ​​model determines that the pet is hungry, the server generates a report and notifies the user that the pet is hungry. At the same time, it instructs the feeder to provide food. The user checks the email notification and confirms that the feeder has automatically provided food after returning home.

[0403] This system allows owners to keep track of their pets' conditions at all times and take prompt and appropriate action. In particular, it allows owners to manage their pets' health even when they are away from home or at work for long periods of time, reducing the burden on owners and improving the happiness of their pets.

[0404] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0405] Step 1: Collecting behaviors and sounds

[0406] The device collects pet behavior and vocalization data. The input is real-time data from the camera, sensors, and microphone. The device acquires this data at regular intervals and stores it locally. Specifically, the device takes video with the camera, detects movement with the sensor, and records audio with the microphone. The output is files of behavior and vocalization data.

[0407] Step 2: Sending data

[0408] The device sends the collected behavioral data and call data to the server. The input is the data file generated in step 1. The device uses Wi-Fi or Bluetooth to send an HTTP POST request to the server. Specifically, the device compresses the data files and uploads them to the server via the network. The output is the behavioral data and call data stored on the server.

[0409] Step 3: Data Preprocessing

[0410] The server preprocesses the received data. The input is the raw data received in step 2. The server denoises the data and extracts the required features. Specifically, it cleans and standardizes the data using a Python script. The output is the preprocessed data.

[0411] Step 4: Data analysis

[0412] The server inputs data into the generated AI model for analysis. The input is the data preprocessed in step 3 and a prompt saying, "Please analyze your pet's current state based on this behavioral data and vocalization data." The server passes the data to the TensorFlow model and classifies the pet's state. Specifically, the server invokes the model through an API and performs inference. The output is the analysis result of the pet's state (e.g., hunger, stress, contentment, etc.).

[0413] Step 5: Reporting and Notifications

[0414] The server generates a report based on the analysis results and notifies the user. The input is the analysis results obtained in step 4. The server generates the report in HTML or PDF format and sends a notification via email or a dedicated app. Specifically, the server creates the report using a template engine and sends it via email using an SMTP server. The output is the report sent to the user.

[0415] Step 6: Device Control

[0416] The server controls a specific device based on the analysis results. The input is the analysis results obtained in step 4. The server makes API calls to the feeding device or massage device to issue the necessary instructions. Specifically, the server sends an HTTP request to the device's API endpoint. The output is the execution result of the action (e.g., feeding, massage) performed by the specific device.

[0417] In this way, it is possible to monitor a pet's behavior and cries, understand the pet's health condition based on the analysis results, and prompt the owner to take appropriate action.

[0418] (Application example 1)

[0419] 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."

[0420] Conventional pet management systems make it difficult for owners to understand their pets' health conditions and emotions in real time. Furthermore, physical stores such as pet shops lack a means for customers to immediately check the health status of pets they are considering purchasing. Therefore, there is a need for a new system to manage pet health and support customers' purchasing decisions.

[0421] 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.

[0422] In this invention, the server includes means for monitoring the behavior of the pet, means for recording the sounds the pet makes, means for collecting this data and transmitting it to the server, means for analyzing the data in the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for notifying the user's communication terminal of the analyzed pet's health condition in real time, and means for customers to easily understand the pet's health condition in a physical store such as a pet shop. This allows owners to remotely understand the health condition and emotions of their pet, and enables customers in a physical store to check the pet's health condition in detail when considering a purchase.

[0423] A "means for monitoring behavior" is a device that records a pet's movements using a camera or motion sensor.

[0424] The "means for recording sounds" is a microphone device that collects the sounds and voices of pets.

[0425] The "means for collecting and transmitting data to a server" is a communication device that transmits behavioral data and sound data obtained from a pet to a server via the Internet.

[0426] "Means for analyzing data and inferring status" refers to a method of analyzing collected data using AI models or other methods to infer a pet's health condition and emotions.

[0427] The "means for generating a report and notifying the user" refers to an application or system for creating a report based on the analysis results and notifying the communication terminal.

[0428] The "means for controlling a specific device" is a mechanism for remotely controlling devices such as pet food management devices and massage devices based on the analysis results.

[0429] The "means of notifying a communication terminal in real time" is a system that instantly sends information about a pet's health condition to the user's smartphone or tablet.

[0430] "Means for understanding pet health conditions in physical stores" refers to interfaces or applications that allow customers at pet shops and other locations to easily check the health conditions of their pets.

[0431] In order to implement this invention, the following systems and processes must be established.

[0432] First, cameras and motion sensors to monitor pet behavior and microphones to record sounds are installed in the pet's environment. These devices are connected to a communication device (e.g., a Wi-Fi module) that collects behavioral and sound data from the pet and transmits it to a server via the Internet.

[0433] On the server side, the received data is analyzed using a generative AI model. The AI ​​model uses machine learning frameworks such as TensorFlow and PyTorch. The AI ​​model analyzes behavioral and vocalization data to predict the pet's health and emotions. The analysis uses the pet's movements, vocalization characteristics, and environmental data. For example, if the pet moves little or vocalizes frequently, it may be determined that the pet is unwell or stressed.

[0434] Based on the analysis results, the server generates a report and notifies the user in real time on their communication device. The user's communication device is a smartphone or tablet with a notification application installed. The notification application displays a report based on the analysis results, allowing the user to immediately check the status of their pet.

[0435] Furthermore, the server controls specific devices such as a food management device and a massage device as needed. For example, if the server determines that the pet is hungry, it issues an instruction to the food management device to provide food. If the server determines that the pet is stressed, it activates the massage device.

[0436] This system can also be applied in brick-and-mortar stores such as pet shops. Pet shop managers use monitoring devices installed in the store to monitor the behavior and sounds of pets. When customers want to check on their pet's health, an interface or application is used to provide that information in real time. This allows customers to have a detailed understanding of their pet's health when considering a purchase.

[0437] Specific examples

[0438] For example, when a pet shop manager sends data collected on a device to a server, the server begins analysis using an AI model. Based on the analysis results, a report is generated stating, "This pet is healthy and active. It has been playing a lot recently and is eating well." This report can be viewed by customers on their smartphones.

[0439] Prompt Sentence Examples

[0440] "Analyze this pet's current health and emotional state based on its behavioral and vocalization data and generate a report. Behavior data: [data format], Vocalization data: [data format]."

[0441] The above is the basic system configuration and processing method for implementing this invention. This system allows pet owners and pet shop customers to understand the health status of their pets in real time and take appropriate measures.

[0442] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0443] Step 1:

[0444] The device collects the pet's behavior and sounds. Specifically, it records the pet's movements with a camera and motion sensors, and records the pet's sounds with a microphone. These input data are behavior data and sound data, and are collected in real time or periodically.

[0445] Step 2:

[0446] The terminal sends the collected data to a server. Specifically, it uses a communication device such as a Wi-Fi module to upload the collected behavioral data and bird call data to the server via the Internet. The server receives this data and manages it centrally.

[0447] Step 3:

[0448] The data received by the server is analyzed using an AI model. Specifically, using machine learning frameworks such as TensorFlow and PyTorch, behavioral data and vocalization data are input into the model to predict the pet's health and emotions. This process determines the pet's condition from its movement patterns and vocalization characteristics. For example, abnormalities such as low activity or excessive vocalizations can be detected.

[0449] Step 4:

[0450] The server generates a report based on the analysis results. Specifically, it creates a report based on the health status and emotions obtained from the analysis results and summarizes it in an easy-to-understand format for the user. The report includes a specific explanation of the situation and recommended measures.

[0451] Step 5:

[0452] The server sends the generated report to the communication device. Specifically, the report is pushed to a smartphone or tablet in real time. The user can receive this notification and check the status of their pet.

[0453] Step 6:

[0454] The server controls specific devices as needed. Specifically, it sends instructions to devices such as a food management device and a massage device based on the analysis results. For example, if the analysis indicates that the pet is hungry, the server instructs the food management device to provide food. If the server determines that the pet is feeling stressed, it will activate a massage device.

[0455] Step 7:

[0456] The user checks the report on the communication terminal and takes necessary action regarding the pet's condition. Specifically, the user opens the notification application and checks the contents of the report. Based on this information, the owner can take care of the pet. In addition, customers at pet shops can understand the health condition of their pets and make purchasing decisions.

[0457] This is the specific flow of processing in this system, which allows pet owners and pet shop customers to understand the health status of their pets in real time and take appropriate measures.

[0458] 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.

[0459] This invention is a system that monitors the behavior and health status of pets and provides information to owners in a format that is easy to understand, in addition to combining it with an emotion engine that recognizes the user's emotions. The system includes a pet behavior monitoring device, a bark recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, specific device control means, and an emotion engine that recognizes the user's emotions.

[0460] 1. Collecting behavior and calls

[0461] First, the device collects data on your pet's behavior using cameras and sensors. The camera captures images of the room in real time, and the sensors collect data on your pet's movements and the environment (temperature, humidity, etc.). Additionally, the device uses a microphone to record your pet's cries. This data is collected in real time or periodically.

[0462] 2. Data transmission

[0463] The collected behavioral and vocalization data is sent from the device to a server, where it is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0464] 3. Data Analysis

[0465] The server inputs the received data into an AI model for analysis. The AI ​​model analyzes behavioral data, sensor data, and vocalization data to predict the pet's health and emotions. The analysis takes into account the pet's movements, vocalization characteristics, and environmental data.

[0466] 4. Use of Emotion Engine

[0467] The server uses an emotion engine that recognizes the user's emotions. The emotion engine reads emotions from the user's voice, facial expressions, messages, etc. and incorporates them into the analysis data. This allows the user's emotions to be used as a basis for decision-making throughout the system.

[0468] 5. Reporting and Notifications

[0469] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition, emotions, and recommended measures. The report content and notification method are also adjusted taking into account the user's emotional information. The generated report is sent from the server to the user's device. The user can understand the pet's condition through this report and take any necessary measures.

[0470] 6. Automatic Device Control

[0471] Based on the analysis results, the server controls specific devices. For example, it can instruct a pet food management device to provide food or start a massage device. The control content can also be adjusted taking into account the user's emotional information.

[0472] Specific examples

[0473] For example, the device collects data on the pet's behavior and cries and sends it to a server. The server then uses an AI model to analyze the received data and obtains the result that "your pet is hungry." At the same time, the emotion engine analyzes the user's voice message and recognizes that the user is currently feeling stressed. Based on this information, the server notifies the user with a report such as "your pet is hungry, but please consider giving it a massage to relieve stress." The server also issues instructions to a food management device to provide food and to activate a massage device, thereby automatically caring for the pet.

[0474] This system allows owners to quickly understand their pet's condition and take optimal measures based on their own emotional state, which is particularly useful when they are away from home or at work for long periods of time, increasing the happiness of both pets and their owners.

[0475] The processing flow will be explained below.

[0476] Step 1:

[0477] The device collects pet behavior data using cameras and sensors. The camera captures images of the room in real time, and the sensors collect pet movements and environmental data (temperature, humidity, etc.).

[0478] Step 2:

[0479] The device will record your pet's cries with a microphone. The microphone will record your pet's cries for a set period of time (e.g., 10 seconds).

[0480] Step 3:

[0481] The device sends the collected behavioral and vocalization data to the server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0482] Step 4:

[0483] The server archives the received data, stores it in a database, and prepares it for later analysis.

[0484] Step 5:

[0485] The server inputs the saved data into the AI ​​model, which then inputs the behavioral data, sensor data, and bird call data all at once and begins analysis.

[0486] Step 6:

[0487] The server receives the analysis results from the AI ​​model, which then infers the pet's health and emotions from its behavior and cries, and returns the results.

[0488] Step 7:

[0489] The server uses an emotion engine to recognize the user's emotions. The emotion engine reads emotions from the user's voice, facial expressions, messages, etc., and incorporates this data into the analysis data.

[0490] Step 8:

[0491] The server generates a report based on the analysis results, including the pet's current health status, mood, and recommended actions, as well as the user's emotional information.

[0492] Step 9:

[0493] The server notifies the user of the generated report via push notification, email, or other means so that the user can check it immediately.

[0494] Step 10:

[0495] The user checks the received report, understands the pet's condition through the report content, and considers what action is necessary.

[0496] Step 11:

[0497] The server controls specific devices based on the analysis results. For example, if the analysis indicates that the pet is hungry, it will instruct the food management device to provide food. If the pet is feeling stressed, it will issue a command to activate a massage device. These instructions are given taking into account the user's emotional information.

[0498] Step 12:

[0499] The terminal controls the food management device and massage device based on instructions from the server, allowing care to be automatically provided according to the pet's needs.

[0500] Example 2

[0501] 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."

[0502] Conventional pet monitoring systems have difficulty accurately understanding the health and emotions of pets, and do not provide measures that take into account the emotions of owners, making it impossible to optimize the happiness of both pets and owners.

[0503] 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.

[0504] In this invention, the server includes means for inputting the received data into an AI model and analyzing the behavioral data, environmental data, and bark data to estimate the pet's health condition and emotions, means for recognizing the user's emotions and incorporating them into the analysis data, and means for generating a report based on the analysis results and notifying the user. This makes it possible to grasp the pet's condition in detail and take optimal measures taking the user's emotions into consideration.

[0505] "Behavior monitoring means" refers to devices such as cameras and sensors that detect and record the movements of pets.

[0506] A "means for recording pet sounds" is a microphone or recording device for recording pet sounds.

[0507] The "means for collecting and transmitting data to a server" refers to a communication device and a network interface for transmitting behavioral data and vocalization data to a server.

[0508] "Means for inputting data into an AI model and analyzing it" refers to a processor and algorithm for inputting received data into an artificial intelligence model and analyzing it.

[0509] "Means for recognizing user emotions" refers to analytical software and hardware for reading emotions from the user's voice, messages, facial expressions, etc.

[0510] The "means for generating a report and notifying the user" refers to a system and interface for automatically generating a report based on the analysis results and notifying the user.

[0511] The "means for controlling a specific device" refers to a control device and software for automatically operating or managing a pet-related device based on the analysis results.

[0512] This invention is a system that monitors the behavior and health status of pets and provides information to owners in a format that is easy to understand, in addition to combining it with an emotion engine that recognizes the user's emotions. The system includes a pet behavior monitoring device, a bark recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, specific device control means, and an emotion engine that recognizes the user's emotions.

[0513] First, the device collects pet behavior data using a camera or sensor. The camera captures video of the room in real time, and the sensor collects pet movements and environmental data (temperature, humidity, etc.). Specific hardware examples include the Logitech C920 camera and DHT22 sensor. Additionally, the device records the pet's cries using a microphone (e.g., Blue Yeti). This data is collected in real time or periodically.

[0514] The collected behavioral and vocalization data is sent from the device to a server. The data is appropriately packetized and transmitted over a communication network (e.g., Wi-Fi). The device is based on, for example, a Raspberry Pi, and the data is sent using the Python requests library via an HTTP POST request.

[0515] The server inputs the received data into an AI model for analysis. The AI ​​model analyzes behavioral data, sensor data, and vocalization data to predict the pet's health and emotions. The specific software used is an AI model that uses TensorFlow and PyTorch. The analysis results can determine, for example, whether the pet is in a "stressed," "hungry," or "relaxed" state.

[0516] The server then uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's voice and text messages using Google Cloud's Natural Language API to determine whether the user is feeling stressed or relaxed.

[0517] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition, emotions, and recommended measures. The report content and notification method are also adjusted taking into account the user's emotional information. For example, a template engine (e.g., Jinja2) can be used to generate a PDF report and send it to an Android or iOS app. Important information can also be sent to the user via SMS or push notification.

[0518] The server then controls specific devices based on the analysis, such as sending a command to a Furbo dog camera to dispense treats or remotely activating a Lurvig pet massager.

[0519] Examples of prompt statements

[0520] markdown

[0521] Prompt statement

[0522] Analyze the following data to infer the pet's health and emotions, generate a report with recommendations for the owner, and control the device appropriately, taking into account the user's emotions.

[0523] Pet behavior data (movement, temperature, humidity)

[0524] Pet sound data

[0525] User emotion data (voice, message)

[0526] Example data

[0527] Movement: Almost no movement

[0528] Temperature: 22°C

[0529] Humidity: 45%

[0530] Call: A series of high-pitched sounds

[0531] User emotion: Feeling stressed (analyzed from messages)

[0532] output

[0533] This system allows owners to quickly understand their pet's condition and take optimal measures based on their own emotional state, which is particularly useful when they are away from home or at work for long periods of time, increasing the happiness of both pets and their owners.

[0534] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0535] Step 1:

[0536] First, the device collects pet behavior data using a camera (e.g., Logitech C920) or a sensor (e.g., DHT22). The camera captures video of the room in real time, and the sensor collects pet movements and environmental data (temperature, humidity, etc.). The device then records the pet's cries using a microphone (e.g., Blue Yeti).

[0537] Input: Real-time data on pet behavior and environment, barks

[0538] Output: behavioral data, vocalization data, environmental data

[0539] What it does: The device collects data from the camera and sensors and temporarily stores it locally. Every time motion is detected, the camera image is updated and the sensors record temperature and humidity data. Every time sound is detected, the audio recording is updated.

[0540] Step 2:

[0541] The device sends the collected behavioral data and vocalization data to the server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0542] Input: behavioral data, vocalization data, environmental data

[0543] Output: Packet data sent to the server

[0544] How it works: The device splits the collected data into packets, encrypts them, and then sends them to the cloud server via Wi-Fi, using the Python requests library to make an HTTP POST request.

[0545] Step 3:

[0546] The server inputs the received data into an AI model for analysis, which then analyzes the behavioral, sensor, and vocalization data to predict the pet's health and emotions.

[0547] Input: Data received from the terminal

[0548] Output: Health status and emotion predictions

[0549] How it works: After verifying the format of the received data, the server inputs it into an AI model trained with TensorFlow and PyTorch. The AI ​​model analyzes the data and classifies the pet's state, for example, determining whether it is "stressed," "hungry," or "relaxed."

[0550] Step 4:

[0551] The server recognizes the user's emotions using an emotion engine, which analyzes the user's voice messages and text messages to read the user's emotions.

[0552] Input: User's voice message, text message

[0553] Output: User's emotional state

[0554] How it works: The server uses Google Cloud's Natural Language API to analyze voice and text messages received from users. Based on the analysis results, it determines the user's emotional state, such as whether they are "stressed" or "relaxed."

[0555] Step 5:

[0556] The server then uses the analysis results to generate a report for the owner, which includes the pet's current health and mood, as well as recommended treatments.

[0557] Input: Health status, emotional predictions, and user emotional state

[0558] Output: Report for owner

[0559] Specific operation: The server uses a template engine (e.g., Jinja2) to automatically generate a PDF report based on the analysis results. The generated report is sent to the user via an Android or iOS app. Important notifications are also sent via SMS or push notification.

[0560] Step 6:

[0561] The server controls specific devices based on the analysis results, for example, instructing a pet food management device to provide food or starting a massage device.

[0562] Input: Health and emotional predictions, and the user's emotional state

[0563] Output: Device control instructions

[0564] Specific operation: Based on the analysis results, the server sends an instruction to the Furbo dog camera to distribute treats, and also sends a remote activation signal to the Lurvig pet massager.

[0565] The above is the flow of processing by the system.

[0566] (Application example 2)

[0567] 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."

[0568] While systems that monitor pet behavior and health already exist, they do not take into account the owner's mental state, making it difficult to provide appropriate care based on the owner's emotional state. Furthermore, there is a lack of systems that automatically suggest food delivery or special services based on the pet's condition. This places a heavy burden on owners in caring for their pets, making them prone to stress.

[0569] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0570] In this invention, the server includes means for monitoring the pet's behavior, means for recording the pet's cries, means for collecting and transmitting this data to the server, means for analyzing the data in the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for using an emotion engine that recognizes the user's emotions, and means for proposing recommended measures and food delivery in consideration of the pet's health condition and the user's emotional state. This allows for optimal care and response by taking into account not only the pet's condition but also the owner's emotional state. Furthermore, by proposing food delivery according to the pet's condition, it is possible to reduce the owner's burden and increase the happiness of both the pet and the owner.

[0571] "Means for monitoring pet behavior" refers to devices or systems that use cameras or motion sensors to record and understand pet movements and locations in real time.

[0572] A "means for recording pet cries" is a device or system that uses a microphone to collect the voices and cries of pets and save them as audio data.

[0573] The "means for collecting and transmitting this data to the server" refers to a communication device or system for transferring the monitored behavior data and recorded animal vocalization data to the server via a network.

[0574] "Means for analyzing data on a server and inferring a pet's condition" refers to a system that uses AI programs and algorithms on a server to analyze collected data and infer a pet's health and behavioral status.

[0575] The "means for generating a report based on the analysis results and notifying the user" refers to a device or system for creating a report on the pet's condition based on the analyzed data and notifying the user of the report.

[0576] The "means for controlling a specific device based on the analysis results" is a system for remotely operating and controlling a pet device (e.g., a food management device or a massage device) based on the analysis results.

[0577] The "means for using an emotion engine that recognizes the user's emotions" refers to software or hardware for reading and analyzing emotions from the user's voice, facial expressions, and messages.

[0578] "A means for proposing recommended measures and food delivery taking into consideration the pet's health condition and the user's emotional state" is a system that comprehensively assesses the pet's analysis results and the user's emotional state to provide appropriate measures (e.g., special food suggestions and delivery).

[0579] This invention is a system for monitoring the behavior and health condition of a pet and providing appropriate information and responses to the owner. The system includes means for monitoring the behavior of the pet, means for recording the pet's cries, means for collecting this data and sending it to a server, means for analyzing the data on the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for using an emotion engine that recognizes the user's emotions, and means for suggesting recommended measures and food delivery in consideration of the pet's health condition and the user's emotional state.

[0580] An embodiment of this system is described in detail below.

[0581] Hardware and Software Configuration

[0582] Hardware:

[0583] 1. Smart cameras (e.g. Nest Cam): Monitor and record your pet's behavior in real time.

[0584] 2. Microphone (e.g. smartphone built-in microphone): Record your pet's cries.

[0585] 3. Communication terminal (e.g., smartphone): A device used to send collected data to a server.

[0586] software:

[0587] 1. OpenCV: Analyzes camera footage and detects pet movements.

[0588] 2. EmotionEngine: Recognizes emotions from user voice and messages.

[0589] 3. FoodDeliveryService: A service for arranging food delivery.

[0590] 4. Requests: HTTP request library for data communication.

[0591] Data collection and transmission

[0592] The smart camera captures images of your pet and analyzes the pet's behavior data using OpenCV. This records the pet's movements and behavior patterns. At the same time, the microphone records the pet's barks and saves them as audio data. This data is then sent to the server via the communication terminal.

[0593] Data analysis and inference

[0594] The server inputs the collected behavioral and vocalization data into an AI model to analyze the pet's health and emotions. The analysis uses behavioral patterns, vocalization characteristics, and environmental data. It also uses the user's emotion engine to recognize emotions from the user's voice and messages and incorporate them into the analysis data. This allows for a comprehensive evaluation of the condition of both the pet and the user.

[0595] Reporting and Notifications

[0596] Based on the analysis results, the server generates a report for the owner, which includes the pet's health status, emotions, and recommended measures. The report also takes into account the user's emotional information and adjusts the report content and notification method. The generated report is sent to a communication device, allowing the owner to understand the pet's condition and take any necessary measures.

[0597] Device control and food delivery proposals

[0598] Based on the analysis results, the server controls specific devices. For example, it can instruct a pet food management device to provide food or activate a massage device. It can also suggest the delivery of appropriate food or stress-relieving items depending on the user's emotional state. This allows optimal care even when the owner is feeling stressed.

[0599] Specific examples

[0600] For example, if the analysis results show that the pet is tired and the user is also feeling stressed, the server will suggest special nutritious food through the food delivery service, along with relaxing items, allowing both pet and owner to live a happy and healthy life.

[0601] Example prompt sentence:

[0602] "Pet is lying on the floor," "Pet is not making much noise," "User is feeling stressed"

[0603] Based on this, the system generates a report suggesting "feeding the pet special nutritious food" and "delivering relaxation items to the user."

[0604] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0605] Step 1:

[0606] Data collection

[0607] The device uses a smart camera and microphone to collect data on pet behavior and barks in real time. The smart camera captures the pet's movements and position as video and analyzes and digitizes it using OpenCV. The microphone records the pet's barks and stores them as audio data.

[0608] Input: Real-time video of pet, pet barking

[0609] Output: behavioral data, audio data

[0610] Step 2:

[0611] Sending data

[0612] The device sends the collected behavioral data and vocalization data to the server via a communication network (e.g., Wi-Fi). The data is properly packetized and securely transferred to the server.

[0613] Input: behavioral data, audio data

[0614] Output: Data sent to the server

[0615] Step 3:

[0616] Data analysis

[0617] The server inputs the received data into an AI model that analyzes the pet's health and emotions. The AI ​​model then comprehensively assesses behavioral patterns, vocalization characteristics, environmental data, and other factors to predict the pet's condition.

[0618] Input: Received data (behavioral data, voice data)

[0619] Output: Analysis of pet's health and emotional state

[0620] Step 4:

[0621] User sentiment analysis

[0622] The server uses an emotion engine to recognize emotions from the user's voice and messages. The user's emotional state data is integrated with the analysis results and becomes the basis for the system's overall decision-making.

[0623] Input: User's voice message

[0624] Output: User's emotional state

[0625] Step 5:

[0626] Reporting and Notifications

[0627] The server generates a report based on the pet's analysis results and the user's emotional state. The report includes the pet's current health condition and emotions, as well as recommended measures. The generated report is sent to the communication device.

[0628] Input: Analysis results of pet health and emotional state, user emotional state

[0629] Output: Report for owner

[0630] Step 6:

[0631] Device control and food delivery suggestions

[0632] Based on the analysis results, the server controls specific devices (e.g., food management devices, massage devices), and, if necessary, suggests suitable food and relaxation items for pets through a food delivery service.

[0633] Input: Analysis results of pets, reports based on the user's emotional state

[0634] Output: Device control instructions, food delivery suggestions

[0635] Example: If the analysis shows that the pet is tired and the user is perceived as stressed, the server will suggest the delivery of nutritious food and relaxation items.

[0636] Example prompt sentence:

[0637] "Pet is lying on the floor," "Pet is not making much noise," "User is feeling stressed"

[0638] 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.

[0639] 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.

[0640] 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.

[0641] [Third embodiment]

[0642] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0643] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0644] 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).

[0645] 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.

[0646] 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.

[0647] 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).

[0648] 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.

[0649] 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.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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."

[0654] This invention is a system for monitoring pet behavior and health status and providing pet owners with information in a format that is easy to understand. The system includes a pet behavior monitoring device, a pet vocalization recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, and means for controlling the pet device as needed.

[0655] 1. Collecting behavior and calls

[0656] First, the device records the pet's behavior and sounds. The behavior data is acquired using cameras and sensors, and the sound data is recorded using a microphone. This data is acquired in real time or periodically.

[0657] 2. Data transmission

[0658] The collected behavioral and vocalization data is sent from the device to a server, allowing for centralized data management.

[0659] 3. Data Analysis

[0660] The server inputs the received data into an AI model for analysis. The AI ​​model infers the pet's health and emotions from its behavior and cries. The analysis uses data such as the pet's movements, characteristics of its cries, and environmental data.

[0661] 4. Reporting and Notifications

[0662] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition and mood, as well as recommended measures. The generated report is then sent from the server to the user's device. The user can use this report to understand the pet's condition and take any necessary measures.

[0663] 5. Automatic Device Control

[0664] If necessary, the server controls a pet food management device or a massage device based on the analysis results. For example, if the analysis indicates that the pet is hungry, the server instructs the food management device to provide food. If the pet is feeling stressed, the server instructs the massage device to start.

[0665] Specific examples

[0666] For example, the device collects data on the pet's behavior and cries and sends it to a server. The server inputs the received data into an AI model and analyzes it to determine that the pet is hungry. Based on this analysis result, the server sends a report to the user stating that the pet is hungry. At the same time, based on the analysis result, the server instructs the food management device to provide food to the pet. Ultimately, the user can check the pet's condition through the received report and feel at ease.

[0667] This system allows owners to keep track of their pets' conditions at all times and take prompt and appropriate action. In particular, it allows owners to manage their pets' health even when they are away from home or at work for long periods of time, reducing the burden on owners and improving the happiness of their pets.

[0668] The processing flow will be explained below.

[0669] Step 1:

[0670] The device collects pet behavior data using cameras and sensors. The camera captures images of the room in real time, and the sensors collect pet movements and environmental data (temperature, humidity, etc.).

[0671] Step 2:

[0672] The device will record your pet's cries with a microphone. The microphone will record your pet's cries for a set period of time (e.g., 10 seconds).

[0673] Step 3:

[0674] The device sends the collected behavioral and vocalization data to a server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0675] Step 4:

[0676] The server archives the received data, stores it in a database, and prepares it for later analysis.

[0677] Step 5:

[0678] The server inputs the saved data into the AI ​​model, which then inputs the behavioral data, sensor data, and bird call data all at once and begins analysis.

[0679] Step 6:

[0680] The server receives the analysis results from the AI ​​model, which then infers the pet's health and emotions from its behavior and cries, and returns the results.

[0681] Step 7:

[0682] The server generates a report based on the analysis, including the pet's current health and mood, as well as recommended actions to take.

[0683] Step 8:

[0684] The server notifies the user of the generated report via push notification, email, or other means so that the user can check it immediately.

[0685] Step 9:

[0686] The user checks the received report, understands the pet's condition through the report content, and considers what action to take if necessary.

[0687] Step 10:

[0688] The server controls specific devices based on the analysis results, for example, instructing a pet food management device to provide food or issuing a command to activate a massage device.

[0689] Step 11:

[0690] The terminal controls the food management device and massage device based on instructions from the server, allowing care to be automatically provided according to the pet's needs.

[0691] Example 1

[0692] 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."

[0693] In modern society, pet owners often find it difficult to manage their pets' health due to long periods of time away from home or at work. A method for properly monitoring pet behavior and health status and responding quickly is needed. In particular, there is a need for early detection of pet hunger and stress and appropriate measures to be taken.

[0694] 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.

[0695] In this invention, the server includes means for monitoring the behavior of the pet, means for recording the sounds of the pet, means for collecting and transmitting this data to the server, means for analyzing the data in the server and estimating the pet's condition using a generative AI model, means for inputting the data into the generative AI model using a prompt sentence, means for generating a report based on the analysis result and notifying the user, and means for controlling a specific device based on the analysis result, thereby enabling the owner to always be aware of the pet's condition and respond quickly and appropriately.

[0696] "Means for monitoring pet behavior" refers to devices or technologies for detecting and recording pet movements, including cameras and sensors.

[0697] "Means for recording pet sounds" refers to devices or technologies for recording pet sounds as audio data, including highly sensitive microphones.

[0698] "Means for collecting and transmitting this data to a server" refers to devices and technologies for transmitting the collected behavioral data and vocalization data to a central server via a network, including wireless communication technologies such as Wi-Fi and Bluetooth.

[0699] "Means for analyzing data on a server and using a generative AI model to infer a pet's condition" refers to technology that analyzes data received on a server and uses an AI model to infer a pet's health condition and emotions.

[0700] "Means for inputting data into a generative AI model using prompt sentences" refers to a technology in which a server inputs specific prompt sentences into a generative AI model and performs analysis.

[0701] "Means of generating a report based on the analysis results and notifying the user" refers to technology that creates a report based on the results of data analysis and notifies the user via email or a dedicated app.

[0702] "Means for controlling specific devices based on the analysis results" refers to technology for remotely controlling specific devices for pets based on the results of data analysis. Specifically, this includes feeding devices and massage devices.

[0703] This invention is a system for monitoring the behavior and health of pets and providing information to owners in a format that is easy to understand. This system includes the following components:

[0704] Hardware Configuration

[0705] The device uses a camera, sensors, and microphone to record your pet's behavior and sounds. The camera monitors your pet's movements, assisted by accelerometers and gyro sensors. The microphone records your pet's sounds. This data is then sent to a server using wireless communication technologies such as Wi-Fi or Bluetooth.

[0706] Software Configuration

[0707] The server inputs the received data into an AI model for analysis. The AI ​​model used here is trained using frameworks such as TensorFlow and PyTorch, which are developed in Python. The AI ​​model infers the pet's health status and emotions based on its behavior and vocalizations. Based on the analysis results, the server generates a report and notifies the user via email or a dedicated app.

[0708] The server also controls specific pet devices as needed. For example, if the server determines that the pet is hungry, it will instruct a feeding device to provide food. If the server determines that the pet is stressed, it will instruct a massage device to start.

[0709] Specific examples

[0710] For example, a device collects data on a pet's behavior and vocalizations and sends it to a server via Wi-Fi. The server preprocesses the received data using a Python script and inputs it into an AI model trained with TensorFlow. The required prompt is, "Please analyze the current state of your pet based on this behavior and vocalization data."

[0711] If the AI ​​model determines that the pet is hungry, the server generates a report and notifies the user that the pet is hungry. At the same time, it instructs the feeder to provide food. The user checks the email notification and confirms that the feeder has automatically provided food after returning home.

[0712] This system allows owners to keep track of their pets' conditions at all times and take prompt and appropriate action. In particular, it allows owners to manage their pets' health even when they are away from home or at work for long periods of time, reducing the burden on owners and improving the happiness of their pets.

[0713] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0714] Step 1: Collecting behaviors and sounds

[0715] The device collects pet behavior and vocalization data. The input is real-time data from the camera, sensors, and microphone. The device acquires this data at regular intervals and stores it locally. Specifically, the device takes video with the camera, detects movement with the sensor, and records audio with the microphone. The output is files of behavior and vocalization data.

[0716] Step 2: Sending data

[0717] The device sends the collected behavioral data and call data to the server. The input is the data file generated in step 1. The device uses Wi-Fi or Bluetooth to send an HTTP POST request to the server. Specifically, the device compresses the data files and uploads them to the server via the network. The output is the behavioral data and call data stored on the server.

[0718] Step 3: Data Preprocessing

[0719] The server preprocesses the received data. The input is the raw data received in step 2. The server denoises the data and extracts the required features. Specifically, it cleans and standardizes the data using a Python script. The output is the preprocessed data.

[0720] Step 4: Data analysis

[0721] The server inputs data into the generated AI model for analysis. The input is the data preprocessed in step 3 and a prompt saying, "Please analyze your pet's current state based on this behavioral data and vocalization data." The server passes the data to the TensorFlow model and classifies the pet's state. Specifically, the server invokes the model through an API and performs inference. The output is the analysis result of the pet's state (e.g., hunger, stress, contentment, etc.).

[0722] Step 5: Reporting and Notifications

[0723] The server generates a report based on the analysis results and notifies the user. The input is the analysis results obtained in step 4. The server generates the report in HTML or PDF format and sends a notification via email or a dedicated app. Specifically, the server creates the report using a template engine and sends it via email using an SMTP server. The output is the report sent to the user.

[0724] Step 6: Device Control

[0725] The server controls a specific device based on the analysis results. The input is the analysis results obtained in step 4. The server makes API calls to the feeding device or massage device to issue the necessary instructions. Specifically, the server sends an HTTP request to the device's API endpoint. The output is the execution result of the action (e.g., feeding, massage) performed by the specific device.

[0726] In this way, it is possible to monitor a pet's behavior and cries, understand the pet's health condition based on the analysis results, and prompt the owner to take appropriate action.

[0727] (Application example 1)

[0728] 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."

[0729] Conventional pet management systems make it difficult for owners to understand their pets' health conditions and emotions in real time. Furthermore, physical stores such as pet shops lack a means for customers to immediately check the health status of pets they are considering purchasing. Therefore, there is a need for a new system to manage pet health and support customers' purchasing decisions.

[0730] 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.

[0731] In this invention, the server includes means for monitoring the behavior of the pet, means for recording the sounds the pet makes, means for collecting this data and transmitting it to the server, means for analyzing the data in the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for notifying the user's communication terminal of the analyzed pet's health condition in real time, and means for customers to easily understand the pet's health condition in a physical store such as a pet shop. This allows owners to remotely understand the health condition and emotions of their pet, and enables customers in a physical store to check the pet's health condition in detail when considering a purchase.

[0732] A "means for monitoring behavior" is a device that records a pet's movements using a camera or motion sensor.

[0733] The "means for recording sounds" is a microphone device that collects the sounds and voices of pets.

[0734] The "means for collecting and transmitting data to a server" is a communication device that transmits behavioral data and sound data obtained from a pet to a server via the Internet.

[0735] "Means for analyzing data and inferring status" refers to a method of analyzing collected data using AI models or other methods to infer a pet's health condition and emotions.

[0736] The "means for generating a report and notifying the user" refers to an application or system for creating a report based on the analysis results and notifying the communication terminal.

[0737] The "means for controlling a specific device" is a mechanism for remotely controlling devices such as pet food management devices and massage devices based on the analysis results.

[0738] The "means of notifying a communication terminal in real time" is a system that instantly sends information about a pet's health condition to the user's smartphone or tablet.

[0739] "Means for understanding pet health conditions in physical stores" refers to interfaces or applications that allow customers at pet shops and other locations to easily check the health conditions of their pets.

[0740] In order to implement this invention, the following systems and processes must be established.

[0741] First, cameras and motion sensors to monitor pet behavior and microphones to record sounds are installed in the pet's environment. These devices are connected to a communication device (e.g., a Wi-Fi module) that collects behavioral and sound data from the pet and transmits it to a server via the Internet.

[0742] On the server side, the received data is analyzed using a generative AI model. The AI ​​model uses machine learning frameworks such as TensorFlow and PyTorch. The AI ​​model analyzes behavioral and vocalization data to predict the pet's health and emotions. The analysis uses the pet's movements, vocalization characteristics, and environmental data. For example, if the pet moves little or vocalizes frequently, it may be determined that the pet is unwell or stressed.

[0743] Based on the analysis results, the server generates a report and notifies the user in real time on their communication device. The user's communication device is a smartphone or tablet with a notification application installed. The notification application displays a report based on the analysis results, allowing the user to immediately check the status of their pet.

[0744] Furthermore, the server controls specific devices such as a food management device and a massage device as needed. For example, if the server determines that the pet is hungry, it issues an instruction to the food management device to provide food. If the server determines that the pet is stressed, it activates the massage device.

[0745] This system can also be applied in brick-and-mortar stores such as pet shops. Pet shop managers use monitoring devices installed in the store to monitor the behavior and sounds of pets. When customers want to check on their pet's health, an interface or application is used to provide that information in real time. This allows customers to have a detailed understanding of their pet's health when considering a purchase.

[0746] Specific examples

[0747] For example, when a pet shop manager sends data collected on a device to a server, the server begins analysis using an AI model. Based on the analysis results, a report is generated stating, "This pet is healthy and active. It has been playing a lot recently and is eating well." This report can be viewed by customers on their smartphones.

[0748] Prompt Sentence Examples

[0749] "Analyze this pet's current health and emotional state based on its behavioral and vocalization data and generate a report. Behavior data: [data format], Vocalization data: [data format]."

[0750] The above is the basic system configuration and processing method for implementing this invention. This system allows pet owners and pet shop customers to understand the health status of their pets in real time and take appropriate measures.

[0751] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0752] Step 1:

[0753] The device collects the pet's behavior and sounds. Specifically, it records the pet's movements with a camera and motion sensors, and records the pet's sounds with a microphone. These input data are behavior data and sound data, and are collected in real time or periodically.

[0754] Step 2:

[0755] The terminal sends the collected data to a server. Specifically, it uses a communication device such as a Wi-Fi module to upload the collected behavioral data and bird call data to the server via the Internet. The server receives this data and manages it centrally.

[0756] Step 3:

[0757] The data received by the server is analyzed using an AI model. Specifically, using machine learning frameworks such as TensorFlow and PyTorch, behavioral data and vocalization data are input into the model to predict the pet's health and emotions. This process determines the pet's condition from its movement patterns and vocalization characteristics. For example, abnormalities such as low activity or excessive vocalizations can be detected.

[0758] Step 4:

[0759] The server generates a report based on the analysis results. Specifically, it creates a report based on the health status and emotions obtained from the analysis results and summarizes it in an easy-to-understand format for the user. The report includes a specific explanation of the situation and recommended measures.

[0760] Step 5:

[0761] The server sends the generated report to the communication device. Specifically, the report is pushed to a smartphone or tablet in real time. The user can receive this notification and check the status of their pet.

[0762] Step 6:

[0763] The server controls specific devices as needed. Specifically, it sends instructions to devices such as a food management device and a massage device based on the analysis results. For example, if the analysis indicates that the pet is hungry, the server instructs the food management device to provide food. If the server determines that the pet is feeling stressed, it will activate a massage device.

[0764] Step 7:

[0765] The user checks the report on the communication terminal and takes necessary action regarding the pet's condition. Specifically, the user opens the notification application and checks the contents of the report. Based on this information, the owner can take care of the pet. In addition, customers at pet shops can understand the health condition of their pets and make purchasing decisions.

[0766] This is the specific flow of processing in this system, which allows pet owners and pet shop customers to understand the health status of their pets in real time and take appropriate measures.

[0767] 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.

[0768] This invention is a system that monitors the behavior and health status of pets and provides information to owners in a format that is easy to understand, in addition to combining it with an emotion engine that recognizes the user's emotions. The system includes a pet behavior monitoring device, a bark recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, specific device control means, and an emotion engine that recognizes the user's emotions.

[0769] 1. Collecting behavior and calls

[0770] First, the device collects data on your pet's behavior using cameras and sensors. The camera captures images of the room in real time, and the sensors collect data on your pet's movements and the environment (temperature, humidity, etc.). Additionally, the device uses a microphone to record your pet's cries. This data is collected in real time or periodically.

[0771] 2. Data transmission

[0772] The collected behavioral and vocalization data is sent from the device to a server, where it is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0773] 3. Data Analysis

[0774] The server inputs the received data into an AI model for analysis. The AI ​​model analyzes behavioral data, sensor data, and vocalization data to predict the pet's health and emotions. The analysis takes into account the pet's movements, vocalization characteristics, and environmental data.

[0775] 4. Use of Emotion Engine

[0776] The server uses an emotion engine that recognizes the user's emotions. The emotion engine reads emotions from the user's voice, facial expressions, messages, etc. and incorporates them into the analysis data. This allows the user's emotions to be used as a basis for decision-making throughout the system.

[0777] 5. Reporting and Notifications

[0778] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition, emotions, and recommended measures. The report content and notification method are also adjusted taking into account the user's emotional information. The generated report is sent from the server to the user's device. The user can understand the pet's condition through this report and take any necessary measures.

[0779] 6. Automatic Device Control

[0780] Based on the analysis results, the server controls specific devices. For example, it can instruct a pet food management device to provide food or start a massage device. The control content can also be adjusted taking into account the user's emotional information.

[0781] Specific examples

[0782] For example, the device collects data on the pet's behavior and cries and sends it to a server. The server then uses an AI model to analyze the received data and obtains the result that "your pet is hungry." At the same time, the emotion engine analyzes the user's voice message and recognizes that the user is currently feeling stressed. Based on this information, the server notifies the user with a report such as "your pet is hungry, but please consider giving it a massage to relieve stress." The server also issues instructions to a food management device to provide food and to activate a massage device, thereby automatically caring for the pet.

[0783] This system allows owners to quickly understand their pet's condition and take optimal measures based on their own emotional state, which is particularly useful when they are away from home or at work for long periods of time, increasing the happiness of both pets and their owners.

[0784] The processing flow will be explained below.

[0785] Step 1:

[0786] The device collects pet behavior data using cameras and sensors. The camera captures images of the room in real time, and the sensors collect pet movements and environmental data (temperature, humidity, etc.).

[0787] Step 2:

[0788] The device will record your pet's cries with a microphone. The microphone will record your pet's cries for a set period of time (e.g., 10 seconds).

[0789] Step 3:

[0790] The device sends the collected behavioral and vocalization data to the server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0791] Step 4:

[0792] The server archives the received data, stores it in a database, and prepares it for later analysis.

[0793] Step 5:

[0794] The server inputs the saved data into the AI ​​model, which then inputs the behavioral data, sensor data, and bird call data all at once and begins analysis.

[0795] Step 6:

[0796] The server receives the analysis results from the AI ​​model, which then infers the pet's health and emotions from its behavior and cries, and returns the results.

[0797] Step 7:

[0798] The server uses an emotion engine to recognize the user's emotions. The emotion engine reads emotions from the user's voice, facial expressions, messages, etc., and incorporates this data into the analysis data.

[0799] Step 8:

[0800] The server generates a report based on the analysis results, including the pet's current health status, mood, and recommended actions, as well as the user's emotional information.

[0801] Step 9:

[0802] The server notifies the user of the generated report via push notification, email, or other means so that the user can check it immediately.

[0803] Step 10:

[0804] The user checks the received report, understands the pet's condition through the report content, and considers what action is necessary.

[0805] Step 11:

[0806] The server controls specific devices based on the analysis results. For example, if the analysis indicates that the pet is hungry, it will instruct the food management device to provide food. If the pet is feeling stressed, it will issue a command to activate a massage device. These instructions are given taking into account the user's emotional information.

[0807] Step 12:

[0808] The terminal controls the food management device and massage device based on instructions from the server, allowing care to be automatically provided according to the pet's needs.

[0809] Example 2

[0810] 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."

[0811] Conventional pet monitoring systems have difficulty accurately understanding the health and emotions of pets, and do not provide measures that take into account the emotions of owners, making it impossible to optimize the happiness of both pets and owners.

[0812] 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.

[0813] In this invention, the server includes means for inputting the received data into an AI model and analyzing the behavioral data, environmental data, and bark data to estimate the pet's health condition and emotions, means for recognizing the user's emotions and incorporating them into the analysis data, and means for generating a report based on the analysis results and notifying the user. This makes it possible to grasp the pet's condition in detail and take optimal measures taking the user's emotions into consideration.

[0814] "Behavior monitoring means" refers to devices such as cameras and sensors that detect and record the movements of pets.

[0815] A "means for recording pet sounds" is a microphone or recording device for recording pet sounds.

[0816] The "means for collecting and transmitting data to a server" refers to a communication device and a network interface for transmitting behavioral data and vocalization data to a server.

[0817] "Means for inputting data into an AI model and analyzing it" refers to a processor and algorithm for inputting received data into an artificial intelligence model and analyzing it.

[0818] "Means for recognizing user emotions" refers to analytical software and hardware for reading emotions from the user's voice, messages, facial expressions, etc.

[0819] The "means for generating a report and notifying the user" refers to a system and interface for automatically generating a report based on the analysis results and notifying the user.

[0820] The "means for controlling a specific device" refers to a control device and software for automatically operating or managing a pet-related device based on the analysis results.

[0821] This invention is a system that monitors the behavior and health status of pets and provides information to owners in a format that is easy to understand, in addition to combining it with an emotion engine that recognizes the user's emotions. The system includes a pet behavior monitoring device, a bark recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, specific device control means, and an emotion engine that recognizes the user's emotions.

[0822] First, the device collects pet behavior data using a camera or sensor. The camera captures video of the room in real time, and the sensor collects pet movements and environmental data (temperature, humidity, etc.). Specific hardware examples include the Logitech C920 camera and DHT22 sensor. Additionally, the device records the pet's cries using a microphone (e.g., Blue Yeti). This data is collected in real time or periodically.

[0823] The collected behavioral and vocalization data is sent from the device to a server. The data is appropriately packetized and transmitted over a communication network (e.g., Wi-Fi). The device is based on, for example, a Raspberry Pi, and the data is sent using the Python requests library via an HTTP POST request.

[0824] The server inputs the received data into an AI model for analysis. The AI ​​model analyzes behavioral data, sensor data, and vocalization data to predict the pet's health and emotions. The specific software used is an AI model that uses TensorFlow and PyTorch. The analysis results can determine, for example, whether the pet is in a "stressed," "hungry," or "relaxed" state.

[0825] The server then uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's voice and text messages using Google Cloud's Natural Language API to determine whether the user is feeling stressed or relaxed.

[0826] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition, emotions, and recommended measures. The report content and notification method are also adjusted taking into account the user's emotional information. For example, a template engine (e.g., Jinja2) can be used to generate a PDF report and send it to an Android or iOS app. Important information can also be sent to the user via SMS or push notification.

[0827] The server then controls specific devices based on the analysis, such as sending a command to a Furbo dog camera to dispense treats or remotely activating a Lurvig pet massager.

[0828] Examples of prompt statements

[0829] markdown

[0830] Prompt statement

[0831] Analyze the following data to infer the pet's health and emotions, generate a report with recommendations for the owner, and control the device appropriately, taking into account the user's emotions.

[0832] Pet behavior data (movement, temperature, humidity)

[0833] Pet sound data

[0834] User emotion data (voice, message)

[0835] Example data

[0836] Movement: Almost no movement

[0837] Temperature: 22°C

[0838] Humidity: 45%

[0839] Call: A series of high-pitched sounds

[0840] User emotion: Feeling stressed (analyzed from messages)

[0841] output

[0842] This system allows owners to quickly understand their pet's condition and take optimal measures based on their own emotional state, which is particularly useful when they are away from home or at work for long periods of time, increasing the happiness of both pets and their owners.

[0843] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0844] Step 1:

[0845] First, the device collects pet behavior data using a camera (e.g., Logitech C920) or a sensor (e.g., DHT22). The camera captures video of the room in real time, and the sensor collects pet movements and environmental data (temperature, humidity, etc.). The device then records the pet's cries using a microphone (e.g., Blue Yeti).

[0846] Input: Real-time data on pet behavior and environment, barks

[0847] Output: behavioral data, vocalization data, environmental data

[0848] What it does: The device collects data from the camera and sensors and temporarily stores it locally. Every time motion is detected, the camera image is updated and the sensors record temperature and humidity data. Every time sound is detected, the audio recording is updated.

[0849] Step 2:

[0850] The device sends the collected behavioral data and vocalization data to the server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0851] Input: behavioral data, vocalization data, environmental data

[0852] Output: Packet data sent to the server

[0853] How it works: The device splits the collected data into packets, encrypts them, and then sends them to the cloud server via Wi-Fi, using the Python requests library to make an HTTP POST request.

[0854] Step 3:

[0855] The server inputs the received data into an AI model for analysis, which then analyzes the behavioral, sensor, and vocalization data to predict the pet's health and emotions.

[0856] Input: Data received from the terminal

[0857] Output: Health status and emotion predictions

[0858] How it works: After verifying the format of the received data, the server inputs it into an AI model trained with TensorFlow and PyTorch. The AI ​​model analyzes the data and classifies the pet's state, for example, determining whether it is "stressed," "hungry," or "relaxed."

[0859] Step 4:

[0860] The server recognizes the user's emotions using an emotion engine, which analyzes the user's voice messages and text messages to read the user's emotions.

[0861] Input: User's voice message, text message

[0862] Output: User's emotional state

[0863] How it works: The server uses Google Cloud's Natural Language API to analyze voice and text messages received from users. Based on the analysis results, it determines the user's emotional state, such as whether they are "stressed" or "relaxed."

[0864] Step 5:

[0865] The server then uses the analysis results to generate a report for the owner, which includes the pet's current health and mood, as well as recommended treatments.

[0866] Input: Health status, emotional predictions, and user emotional state

[0867] Output: Report for owner

[0868] Specific operation: The server uses a template engine (e.g., Jinja2) to automatically generate a PDF report based on the analysis results. The generated report is sent to the user via an Android or iOS app. Important notifications are also sent via SMS or push notification.

[0869] Step 6:

[0870] The server controls specific devices based on the analysis results, for example, instructing a pet food management device to provide food or starting a massage device.

[0871] Input: Health and emotional predictions, and the user's emotional state

[0872] Output: Device control instructions

[0873] Specific operation: Based on the analysis results, the server sends an instruction to the Furbo dog camera to distribute treats, and also sends a remote activation signal to the Lurvig pet massager.

[0874] The above is the flow of processing by the system.

[0875] (Application example 2)

[0876] 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."

[0877] While systems that monitor pet behavior and health already exist, they do not take into account the owner's mental state, making it difficult to provide appropriate care based on the owner's emotional state. Furthermore, there is a lack of systems that automatically suggest food delivery or special services based on the pet's condition. This places a heavy burden on owners in caring for their pets, making them prone to stress.

[0878] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0879] In this invention, the server includes means for monitoring the pet's behavior, means for recording the pet's cries, means for collecting and transmitting this data to the server, means for analyzing the data in the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for using an emotion engine that recognizes the user's emotions, and means for proposing recommended measures and food delivery in consideration of the pet's health condition and the user's emotional state. This allows for optimal care and response by taking into account not only the pet's condition but also the owner's emotional state. Furthermore, by proposing food delivery according to the pet's condition, it is possible to reduce the owner's burden and increase the happiness of both the pet and the owner.

[0880] "Means for monitoring pet behavior" refers to devices or systems that use cameras or motion sensors to record and understand pet movements and locations in real time.

[0881] A "means for recording pet cries" is a device or system that uses a microphone to collect the voices and cries of pets and save them as audio data.

[0882] The "means for collecting and transmitting this data to the server" refers to a communication device or system for transferring the monitored behavior data and recorded animal vocalization data to the server via a network.

[0883] "Means for analyzing data on a server and inferring a pet's condition" refers to a system that uses AI programs and algorithms on a server to analyze collected data and infer a pet's health and behavioral status.

[0884] The "means for generating a report based on the analysis results and notifying the user" refers to a device or system for creating a report on the pet's condition based on the analyzed data and notifying the user of the report.

[0885] The "means for controlling a specific device based on the analysis results" is a system for remotely operating and controlling a pet device (e.g., a food management device or a massage device) based on the analysis results.

[0886] The "means for using an emotion engine that recognizes the user's emotions" refers to software or hardware for reading and analyzing emotions from the user's voice, facial expressions, and messages.

[0887] "A means for proposing recommended measures and food delivery taking into consideration the pet's health condition and the user's emotional state" is a system that comprehensively assesses the pet's analysis results and the user's emotional state to provide appropriate measures (e.g., special food suggestions and delivery).

[0888] This invention is a system for monitoring the behavior and health condition of a pet and providing appropriate information and responses to the owner. The system includes means for monitoring the behavior of the pet, means for recording the pet's cries, means for collecting this data and sending it to a server, means for analyzing the data on the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for using an emotion engine that recognizes the user's emotions, and means for suggesting recommended measures and food delivery in consideration of the pet's health condition and the user's emotional state.

[0889] An embodiment of this system is described in detail below.

[0890] Hardware and Software Configuration

[0891] Hardware:

[0892] 1. Smart cameras (e.g. Nest Cam): Monitor and record your pet's behavior in real time.

[0893] 2. Microphone (e.g. smartphone built-in microphone): Record your pet's cries.

[0894] 3. Communication terminal (e.g., smartphone): A device used to send collected data to a server.

[0895] software:

[0896] 1. OpenCV: Analyzes camera footage and detects pet movements.

[0897] 2. EmotionEngine: Recognizes emotions from user voice and messages.

[0898] 3. FoodDeliveryService: A service for arranging food delivery.

[0899] 4. Requests: HTTP request library for data communication.

[0900] Data collection and transmission

[0901] The smart camera captures images of your pet and analyzes the pet's behavior data using OpenCV. This records the pet's movements and behavior patterns. At the same time, the microphone records the pet's barks and saves them as audio data. This data is then sent to the server via the communication terminal.

[0902] Data analysis and inference

[0903] The server inputs the collected behavioral and vocalization data into an AI model to analyze the pet's health and emotions. The analysis uses behavioral patterns, vocalization characteristics, and environmental data. It also uses the user's emotion engine to recognize emotions from the user's voice and messages and incorporate them into the analysis data. This allows for a comprehensive evaluation of the condition of both the pet and the user.

[0904] Reporting and Notifications

[0905] Based on the analysis results, the server generates a report for the owner, which includes the pet's health status, emotions, and recommended measures. The report also takes into account the user's emotional information and adjusts the report content and notification method. The generated report is sent to a communication device, allowing the owner to understand the pet's condition and take any necessary measures.

[0906] Device control and food delivery proposals

[0907] Based on the analysis results, the server controls specific devices. For example, it can instruct a pet food management device to provide food or activate a massage device. It can also suggest the delivery of appropriate food or stress-relieving items depending on the user's emotional state. This allows optimal care even when the owner is feeling stressed.

[0908] Specific examples

[0909] For example, if the analysis results show that the pet is tired and the user is also feeling stressed, the server will suggest special nutritious food through the food delivery service, along with relaxing items, allowing both pet and owner to live a happy and healthy life.

[0910] Example prompt sentence:

[0911] "Pet is lying on the floor," "Pet is not making much noise," "User is feeling stressed"

[0912] Based on this, the system generates a report suggesting "feeding the pet special nutritious food" and "delivering relaxation items to the user."

[0913] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0914] Step 1:

[0915] Data collection

[0916] The device uses a smart camera and microphone to collect data on pet behavior and barks in real time. The smart camera captures the pet's movements and position as video and analyzes and digitizes it using OpenCV. The microphone records the pet's barks and stores them as audio data.

[0917] Input: Real-time video of pet, pet barking

[0918] Output: behavioral data, audio data

[0919] Step 2:

[0920] Sending data

[0921] The device sends the collected behavioral data and vocalization data to the server via a communication network (e.g., Wi-Fi). The data is properly packetized and securely transferred to the server.

[0922] Input: behavioral data, audio data

[0923] Output: Data sent to the server

[0924] Step 3:

[0925] Data analysis

[0926] The server inputs the received data into an AI model that analyzes the pet's health and emotions. The AI ​​model then comprehensively assesses behavioral patterns, vocalization characteristics, environmental data, and other factors to predict the pet's condition.

[0927] Input: Received data (behavioral data, voice data)

[0928] Output: Analysis of pet's health and emotional state

[0929] Step 4:

[0930] User sentiment analysis

[0931] The server uses an emotion engine to recognize emotions from the user's voice and messages. The user's emotional state data is integrated with the analysis results and becomes the basis for the system's overall decision-making.

[0932] Input: User's voice message

[0933] Output: User's emotional state

[0934] Step 5:

[0935] Reporting and Notifications

[0936] The server generates a report based on the pet's analysis results and the user's emotional state. The report includes the pet's current health condition and emotions, as well as recommended measures. The generated report is sent to the communication device.

[0937] Input: Analysis results of pet health and emotional state, user emotional state

[0938] Output: Report for owner

[0939] Step 6:

[0940] Device control and food delivery suggestions

[0941] Based on the analysis results, the server controls specific devices (e.g., food management devices, massage devices), and, if necessary, suggests suitable food and relaxation items for pets through a food delivery service.

[0942] Input: Analysis results of pets, reports based on the user's emotional state

[0943] Output: Device control instructions, food delivery suggestions

[0944] Example: If the analysis shows that the pet is tired and the user is perceived as stressed, the server will suggest the delivery of nutritious food and relaxation items.

[0945] Example prompt sentence:

[0946] "Pet is lying on the floor," "Pet is not making much noise," "User is feeling stressed"

[0947] 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.

[0948] 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.

[0949] 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.

[0950] [Fourth embodiment]

[0951] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0952] 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.

[0953] 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).

[0954] 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.

[0955] 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.

[0956] 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).

[0957] 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.

[0958] 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.

[0959] 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.

[0960] 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.

[0961] 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.

[0962] 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.

[0963] 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."

[0964] This invention is a system for monitoring pet behavior and health status and providing pet owners with information in a format that is easy to understand. The system includes a pet behavior monitoring device, a pet vocalization recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, and means for controlling the pet device as needed.

[0965] 1. Collecting behavior and calls

[0966] First, the device records the pet's behavior and sounds. The behavior data is acquired using cameras and sensors, and the sound data is recorded using a microphone. This data is acquired in real time or periodically.

[0967] 2. Data transmission

[0968] The collected behavioral and vocalization data is sent from the device to a server, allowing for centralized data management.

[0969] 3. Data Analysis

[0970] The server inputs the received data into an AI model for analysis. The AI ​​model infers the pet's health and emotions from its behavior and cries. The analysis uses data such as the pet's movements, characteristics of its cries, and environmental data.

[0971] 4. Reporting and Notifications

[0972] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition and mood, as well as recommended measures. The generated report is then sent from the server to the user's device. The user can use this report to understand the pet's condition and take any necessary measures.

[0973] 5. Automatic Device Control

[0974] If necessary, the server controls a pet food management device or a massage device based on the analysis results. For example, if the analysis indicates that the pet is hungry, the server instructs the food management device to provide food. If the pet is feeling stressed, the server instructs the massage device to start.

[0975] Specific examples

[0976] For example, the device collects data on the pet's behavior and cries and sends it to a server. The server inputs the received data into an AI model and analyzes it to determine that the pet is hungry. Based on this analysis result, the server sends a report to the user stating that the pet is hungry. At the same time, based on the analysis result, the server instructs the food management device to provide food to the pet. Ultimately, the user can check the pet's condition through the received report and feel at ease.

[0977] This system allows owners to keep track of their pets' conditions at all times and take prompt and appropriate action. In particular, it allows owners to manage their pets' health even when they are away from home or at work for long periods of time, reducing the burden on owners and improving the happiness of their pets.

[0978] The processing flow will be explained below.

[0979] Step 1:

[0980] The device collects pet behavior data using cameras and sensors. The camera captures images of the room in real time, and the sensors collect pet movements and environmental data (temperature, humidity, etc.).

[0981] Step 2:

[0982] The device will record your pet's cries with a microphone. The microphone will record your pet's cries for a set period of time (e.g., 10 seconds).

[0983] Step 3:

[0984] The device sends the collected behavioral and vocalization data to a server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[0985] Step 4:

[0986] The server archives the received data, stores it in a database, and prepares it for later analysis.

[0987] Step 5:

[0988] The server inputs the saved data into the AI ​​model, which then inputs the behavioral data, sensor data, and bird call data all at once and begins analysis.

[0989] Step 6:

[0990] The server receives the analysis results from the AI ​​model, which then infers the pet's health and emotions from its behavior and cries, and returns the results.

[0991] Step 7:

[0992] The server generates a report based on the analysis, including the pet's current health and mood, as well as recommended actions to take.

[0993] Step 8:

[0994] The server notifies the user of the generated report via push notification, email, or other means so that the user can check it immediately.

[0995] Step 9:

[0996] The user checks the received report, understands the pet's condition through the report content, and considers what action to take if necessary.

[0997] Step 10:

[0998] The server controls specific devices based on the analysis results, for example, instructing a pet food management device to provide food or issuing a command to activate a massage device.

[0999] Step 11:

[1000] The terminal controls the food management device and massage device based on instructions from the server, allowing care to be automatically provided according to the pet's needs.

[1001] Example 1

[1002] 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."

[1003] In modern society, pet owners often find it difficult to manage their pets' health due to long periods of time away from home or at work. A method for properly monitoring pet behavior and health status and responding quickly is needed. In particular, there is a need for early detection of pet hunger and stress and appropriate measures to be taken.

[1004] 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.

[1005] In this invention, the server includes means for monitoring the behavior of the pet, means for recording the sounds of the pet, means for collecting and transmitting this data to the server, means for analyzing the data in the server and estimating the pet's condition using a generative AI model, means for inputting the data into the generative AI model using a prompt sentence, means for generating a report based on the analysis result and notifying the user, and means for controlling a specific device based on the analysis result, thereby enabling the owner to always be aware of the pet's condition and respond quickly and appropriately.

[1006] "Means for monitoring pet behavior" refers to devices or technologies for detecting and recording pet movements, including cameras and sensors.

[1007] "Means for recording pet sounds" refers to devices or technologies for recording pet sounds as audio data, including highly sensitive microphones.

[1008] "Means for collecting and transmitting this data to a server" refers to devices and technologies for transmitting the collected behavioral data and vocalization data to a central server via a network, including wireless communication technologies such as Wi-Fi and Bluetooth.

[1009] "Means for analyzing data on a server and using a generative AI model to infer a pet's condition" refers to technology that analyzes data received on a server and uses an AI model to infer a pet's health condition and emotions.

[1010] "Means for inputting data into a generative AI model using prompt sentences" refers to a technology in which a server inputs specific prompt sentences into a generative AI model and performs analysis.

[1011] "Means of generating a report based on the analysis results and notifying the user" refers to technology that creates a report based on the results of data analysis and notifies the user via email or a dedicated app.

[1012] "Means for controlling specific devices based on the analysis results" refers to technology for remotely controlling specific devices for pets based on the results of data analysis. Specifically, this includes feeding devices and massage devices.

[1013] This invention is a system for monitoring the behavior and health of pets and providing information to owners in a format that is easy to understand. This system includes the following components:

[1014] Hardware Configuration

[1015] The device uses a camera, sensors, and microphone to record your pet's behavior and sounds. The camera monitors your pet's movements, assisted by accelerometers and gyro sensors. The microphone records your pet's sounds. This data is then sent to a server using wireless communication technologies such as Wi-Fi or Bluetooth.

[1016] Software Configuration

[1017] The server inputs the received data into an AI model for analysis. The AI ​​model used here is trained using frameworks such as TensorFlow and PyTorch, which are developed in Python. The AI ​​model infers the pet's health status and emotions based on its behavior and vocalizations. Based on the analysis results, the server generates a report and notifies the user via email or a dedicated app.

[1018] The server also controls specific pet devices as needed. For example, if the server determines that the pet is hungry, it will instruct a feeding device to provide food. If the server determines that the pet is stressed, it will instruct a massage device to start.

[1019] Specific examples

[1020] For example, a device collects data on a pet's behavior and vocalizations and sends it to a server via Wi-Fi. The server preprocesses the received data using a Python script and inputs it into an AI model trained with TensorFlow. The required prompt is, "Please analyze the current state of your pet based on this behavior and vocalization data."

[1021] If the AI ​​model determines that the pet is hungry, the server generates a report and notifies the user that the pet is hungry. At the same time, it instructs the feeder to provide food. The user checks the email notification and confirms that the feeder has automatically provided food after returning home.

[1022] This system allows owners to keep track of their pets' conditions at all times and take prompt and appropriate action. In particular, it allows owners to manage their pets' health even when they are away from home or at work for long periods of time, reducing the burden on owners and improving the happiness of their pets.

[1023] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1024] Step 1: Collecting behaviors and sounds

[1025] The device collects pet behavior and vocalization data. The input is real-time data from the camera, sensors, and microphone. The device acquires this data at regular intervals and stores it locally. Specifically, the device takes video with the camera, detects movement with the sensor, and records audio with the microphone. The output is files of behavior and vocalization data.

[1026] Step 2: Sending data

[1027] The device sends the collected behavioral data and call data to the server. The input is the data file generated in step 1. The device uses Wi-Fi or Bluetooth to send an HTTP POST request to the server. Specifically, the device compresses the data files and uploads them to the server via the network. The output is the behavioral data and call data stored on the server.

[1028] Step 3: Data Preprocessing

[1029] The server preprocesses the received data. The input is the raw data received in step 2. The server denoises the data and extracts the required features. Specifically, it cleans and standardizes the data using a Python script. The output is the preprocessed data.

[1030] Step 4: Data analysis

[1031] The server inputs data into the generated AI model for analysis. The input is the data preprocessed in step 3 and a prompt saying, "Please analyze your pet's current state based on this behavioral data and vocalization data." The server passes the data to the TensorFlow model and classifies the pet's state. Specifically, the server invokes the model through an API and performs inference. The output is the analysis result of the pet's state (e.g., hunger, stress, contentment, etc.).

[1032] Step 5: Reporting and Notifications

[1033] The server generates a report based on the analysis results and notifies the user. The input is the analysis results obtained in step 4. The server generates the report in HTML or PDF format and sends a notification via email or a dedicated app. Specifically, the server creates the report using a template engine and sends it via email using an SMTP server. The output is the report sent to the user.

[1034] Step 6: Device Control

[1035] The server controls a specific device based on the analysis results. The input is the analysis results obtained in step 4. The server makes API calls to the feeding device or massage device to issue the necessary instructions. Specifically, the server sends an HTTP request to the device's API endpoint. The output is the execution result of the action (e.g., feeding, massage) performed by the specific device.

[1036] In this way, it is possible to monitor a pet's behavior and cries, understand the pet's health condition based on the analysis results, and prompt the owner to take appropriate action.

[1037] (Application example 1)

[1038] 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."

[1039] Conventional pet management systems make it difficult for owners to understand their pets' health conditions and emotions in real time. Furthermore, physical stores such as pet shops lack a means for customers to immediately check the health status of pets they are considering purchasing. Therefore, there is a need for a new system to manage pet health and support customers' purchasing decisions.

[1040] 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.

[1041] In this invention, the server includes means for monitoring the behavior of the pet, means for recording the sounds the pet makes, means for collecting this data and transmitting it to the server, means for analyzing the data in the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for notifying the user's communication terminal of the analyzed pet's health condition in real time, and means for customers to easily understand the pet's health condition in a physical store such as a pet shop. This allows owners to remotely understand the health condition and emotions of their pet, and enables customers in a physical store to check the pet's health condition in detail when considering a purchase.

[1042] A "means for monitoring behavior" is a device that records a pet's movements using a camera or motion sensor.

[1043] The "means for recording sounds" is a microphone device that collects the sounds and voices of pets.

[1044] The "means for collecting and transmitting data to a server" is a communication device that transmits behavioral data and sound data obtained from a pet to a server via the Internet.

[1045] "Means for analyzing data and inferring status" refers to a method of analyzing collected data using AI models or other methods to infer a pet's health condition and emotions.

[1046] The "means for generating a report and notifying the user" refers to an application or system for creating a report based on the analysis results and notifying the communication terminal.

[1047] The "means for controlling a specific device" is a mechanism for remotely controlling devices such as pet food management devices and massage devices based on the analysis results.

[1048] The "means of notifying a communication terminal in real time" is a system that instantly sends information about a pet's health condition to the user's smartphone or tablet.

[1049] "Means for understanding pet health conditions in physical stores" refers to interfaces or applications that allow customers at pet shops and other locations to easily check the health conditions of their pets.

[1050] In order to implement this invention, the following systems and processes must be established.

[1051] First, cameras and motion sensors to monitor pet behavior and microphones to record sounds are installed in the pet's environment. These devices are connected to a communication device (e.g., a Wi-Fi module) that collects behavioral and sound data from the pet and transmits it to a server via the Internet.

[1052] On the server side, the received data is analyzed using a generative AI model. The AI ​​model uses machine learning frameworks such as TensorFlow and PyTorch. The AI ​​model analyzes behavioral and vocalization data to predict the pet's health and emotions. The analysis uses the pet's movements, vocalization characteristics, and environmental data. For example, if the pet moves little or vocalizes frequently, it may be determined that the pet is unwell or stressed.

[1053] Based on the analysis results, the server generates a report and notifies the user in real time on their communication device. The user's communication device is a smartphone or tablet with a notification application installed. The notification application displays a report based on the analysis results, allowing the user to immediately check the status of their pet.

[1054] Furthermore, the server controls specific devices such as a food management device and a massage device as needed. For example, if the server determines that the pet is hungry, it issues an instruction to the food management device to provide food. If the server determines that the pet is stressed, it activates the massage device.

[1055] This system can also be applied in brick-and-mortar stores such as pet shops. Pet shop managers use monitoring devices installed in the store to monitor the behavior and sounds of pets. When customers want to check on their pet's health, an interface or application is used to provide that information in real time. This allows customers to have a detailed understanding of their pet's health when considering a purchase.

[1056] Specific examples

[1057] For example, when a pet shop manager sends data collected on a device to a server, the server begins analysis using an AI model. Based on the analysis results, a report is generated stating, "This pet is healthy and active. It has been playing a lot recently and is eating well." This report can be viewed by customers on their smartphones.

[1058] Prompt Sentence Examples

[1059] "Analyze this pet's current health and emotional state based on its behavioral and vocalization data and generate a report. Behavior data: [data format], Vocalization data: [data format]."

[1060] The above is the basic system configuration and processing method for implementing this invention. This system allows pet owners and pet shop customers to understand the health status of their pets in real time and take appropriate measures.

[1061] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1062] Step 1:

[1063] The device collects the pet's behavior and sounds. Specifically, it records the pet's movements with a camera and motion sensors, and records the pet's sounds with a microphone. These input data are behavior data and sound data, and are collected in real time or periodically.

[1064] Step 2:

[1065] The terminal sends the collected data to a server. Specifically, it uses a communication device such as a Wi-Fi module to upload the collected behavioral data and bird call data to the server via the Internet. The server receives this data and manages it centrally.

[1066] Step 3:

[1067] The data received by the server is analyzed using an AI model. Specifically, using machine learning frameworks such as TensorFlow and PyTorch, behavioral data and vocalization data are input into the model to predict the pet's health and emotions. This process determines the pet's condition from its movement patterns and vocalization characteristics. For example, abnormalities such as low activity or excessive vocalizations can be detected.

[1068] Step 4:

[1069] The server generates a report based on the analysis results. Specifically, it creates a report based on the health status and emotions obtained from the analysis results and summarizes it in an easy-to-understand format for the user. The report includes a specific explanation of the situation and recommended measures.

[1070] Step 5:

[1071] The server sends the generated report to the communication device. Specifically, the report is pushed to a smartphone or tablet in real time. The user can receive this notification and check the status of their pet.

[1072] Step 6:

[1073] The server controls specific devices as needed. Specifically, it sends instructions to devices such as a food management device and a massage device based on the analysis results. For example, if the analysis indicates that the pet is hungry, the server instructs the food management device to provide food. If the server determines that the pet is feeling stressed, it will activate a massage device.

[1074] Step 7:

[1075] The user checks the report on the communication terminal and takes necessary action regarding the pet's condition. Specifically, the user opens the notification application and checks the contents of the report. Based on this information, the owner can take care of the pet. In addition, customers at pet shops can understand the health condition of their pets and make purchasing decisions.

[1076] This is the specific flow of processing in this system, which allows pet owners and pet shop customers to understand the health status of their pets in real time and take appropriate measures.

[1077] 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.

[1078] This invention is a system that monitors the behavior and health status of pets and provides information to owners in a format that is easy to understand, in addition to combining it with an emotion engine that recognizes the user's emotions. The system includes a pet behavior monitoring device, a bark recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, specific device control means, and an emotion engine that recognizes the user's emotions.

[1079] 1. Collecting behavior and calls

[1080] First, the device collects data on your pet's behavior using cameras and sensors. The camera captures images of the room in real time, and the sensors collect data on your pet's movements and the environment (temperature, humidity, etc.). Additionally, the device uses a microphone to record your pet's cries. This data is collected in real time or periodically.

[1081] 2. Data transmission

[1082] The collected behavioral and vocalization data is sent from the device to a server, where it is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[1083] 3. Data Analysis

[1084] The server inputs the received data into an AI model for analysis. The AI ​​model analyzes behavioral data, sensor data, and vocalization data to predict the pet's health and emotions. The analysis takes into account the pet's movements, vocalization characteristics, and environmental data.

[1085] 4. Use of Emotion Engine

[1086] The server uses an emotion engine that recognizes the user's emotions. The emotion engine reads emotions from the user's voice, facial expressions, messages, etc. and incorporates them into the analysis data. This allows the user's emotions to be used as a basis for decision-making throughout the system.

[1087] 5. Reporting and Notifications

[1088] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition, emotions, and recommended measures. The report content and notification method are also adjusted taking into account the user's emotional information. The generated report is sent from the server to the user's device. The user can understand the pet's condition through this report and take any necessary measures.

[1089] 6. Automatic Device Control

[1090] Based on the analysis results, the server controls specific devices. For example, it can instruct a pet food management device to provide food or start a massage device. The control content can also be adjusted taking into account the user's emotional information.

[1091] Specific examples

[1092] For example, the device collects data on the pet's behavior and cries and sends it to a server. The server then uses an AI model to analyze the received data and obtains the result that "your pet is hungry." At the same time, the emotion engine analyzes the user's voice message and recognizes that the user is currently feeling stressed. Based on this information, the server notifies the user with a report such as "your pet is hungry, but please consider giving it a massage to relieve stress." The server also issues instructions to a food management device to provide food and to activate a massage device, thereby automatically caring for the pet.

[1093] This system allows owners to quickly understand their pet's condition and take optimal measures based on their own emotional state, which is particularly useful when they are away from home or at work for long periods of time, increasing the happiness of both pets and their owners.

[1094] The processing flow will be explained below.

[1095] Step 1:

[1096] The device collects pet behavior data using cameras and sensors. The camera captures images of the room in real time, and the sensors collect pet movements and environmental data (temperature, humidity, etc.).

[1097] Step 2:

[1098] The device will record your pet's cries with a microphone. The microphone will record your pet's cries for a set period of time (e.g., 10 seconds).

[1099] Step 3:

[1100] The device sends the collected behavioral and vocalization data to the server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[1101] Step 4:

[1102] The server archives the received data, stores it in a database, and prepares it for later analysis.

[1103] Step 5:

[1104] The server inputs the saved data into the AI ​​model, which then inputs the behavioral data, sensor data, and bird call data all at once and begins analysis.

[1105] Step 6:

[1106] The server receives the analysis results from the AI ​​model, which then infers the pet's health and emotions from its behavior and cries, and returns the results.

[1107] Step 7:

[1108] The server uses an emotion engine to recognize the user's emotions. The emotion engine reads emotions from the user's voice, facial expressions, messages, etc., and incorporates this data into the analysis data.

[1109] Step 8:

[1110] The server generates a report based on the analysis results, including the pet's current health status, mood, and recommended actions, as well as the user's emotional information.

[1111] Step 9:

[1112] The server notifies the user of the generated report via push notification, email, or other means so that the user can check it immediately.

[1113] Step 10:

[1114] The user checks the received report, understands the pet's condition through the report content, and considers what action is necessary.

[1115] Step 11:

[1116] The server controls specific devices based on the analysis results. For example, if the analysis indicates that the pet is hungry, it will instruct the food management device to provide food. If the pet is feeling stressed, it will issue a command to activate a massage device. These instructions are given taking into account the user's emotional information.

[1117] Step 12:

[1118] The terminal controls the food management device and massage device based on instructions from the server, allowing care to be automatically provided according to the pet's needs.

[1119] Example 2

[1120] 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."

[1121] Conventional pet monitoring systems have difficulty accurately understanding the health and emotions of pets, and do not provide measures that take into account the emotions of owners, making it impossible to optimize the happiness of both pets and owners.

[1122] 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.

[1123] In this invention, the server includes means for inputting the received data into an AI model and analyzing the behavioral data, environmental data, and bark data to estimate the pet's health condition and emotions, means for recognizing the user's emotions and incorporating them into the analysis data, and means for generating a report based on the analysis results and notifying the user. This makes it possible to grasp the pet's condition in detail and take optimal measures taking the user's emotions into consideration.

[1124] "Behavior monitoring means" refers to devices such as cameras and sensors that detect and record the movements of pets.

[1125] A "means for recording pet sounds" is a microphone or recording device for recording pet sounds.

[1126] The "means for collecting and transmitting data to a server" refers to a communication device and a network interface for transmitting behavioral data and vocalization data to a server.

[1127] "Means for inputting data into an AI model and analyzing it" refers to a processor and algorithm for inputting received data into an artificial intelligence model and analyzing it.

[1128] "Means for recognizing user emotions" refers to analytical software and hardware for reading emotions from the user's voice, messages, facial expressions, etc.

[1129] The "means for generating a report and notifying the user" refers to a system and interface for automatically generating a report based on the analysis results and notifying the user.

[1130] The "means for controlling a specific device" refers to a control device and software for automatically operating or managing a pet-related device based on the analysis results.

[1131] This invention is a system that monitors the behavior and health status of pets and provides information to owners in a format that is easy to understand, in addition to combining it with an emotion engine that recognizes the user's emotions. The system includes a pet behavior monitoring device, a bark recording device, a data collection and transmission device, a data analysis device, a report generation and notification device, specific device control means, and an emotion engine that recognizes the user's emotions.

[1132] First, the device collects pet behavior data using a camera or sensor. The camera captures video of the room in real time, and the sensor collects pet movements and environmental data (temperature, humidity, etc.). Specific hardware examples include the Logitech C920 camera and DHT22 sensor. Additionally, the device records the pet's cries using a microphone (e.g., Blue Yeti). This data is collected in real time or periodically.

[1133] The collected behavioral and vocalization data is sent from the device to a server. The data is appropriately packetized and transmitted over a communication network (e.g., Wi-Fi). The device is based on, for example, a Raspberry Pi, and the data is sent using the Python requests library via an HTTP POST request.

[1134] The server inputs the received data into an AI model for analysis. The AI ​​model analyzes behavioral data, sensor data, and vocalization data to predict the pet's health and emotions. The specific software used is an AI model that uses TensorFlow and PyTorch. The analysis results can determine, for example, whether the pet is in a "stressed," "hungry," or "relaxed" state.

[1135] The server then uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's voice and text messages using Google Cloud's Natural Language API to determine whether the user is feeling stressed or relaxed.

[1136] Based on the analysis results, the server generates a report for the owner. This report includes the pet's current health condition, emotions, and recommended measures. The report content and notification method are also adjusted taking into account the user's emotional information. For example, a template engine (e.g., Jinja2) can be used to generate a PDF report and send it to an Android or iOS app. Important information can also be sent to the user via SMS or push notification.

[1137] The server then controls specific devices based on the analysis, such as sending a command to a Furbo dog camera to dispense treats or remotely activating a Lurvig pet massager.

[1138] Examples of prompt statements

[1139] markdown

[1140] Prompt statement

[1141] Analyze the following data to infer the pet's health and emotions, generate a report with recommendations for the owner, and control the device appropriately, taking into account the user's emotions.

[1142] Pet behavior data (movement, temperature, humidity)

[1143] Pet sound data

[1144] User emotion data (voice, message)

[1145] Example data

[1146] Movement: Almost no movement

[1147] Temperature: 22°C

[1148] Humidity: 45%

[1149] Call: A series of high-pitched sounds

[1150] User emotion: Feeling stressed (analyzed from messages)

[1151] output

[1152] This system allows owners to quickly understand their pet's condition and take optimal measures based on their own emotional state, which is particularly useful when they are away from home or at work for long periods of time, increasing the happiness of both pets and their owners.

[1153] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1154] Step 1:

[1155] First, the device collects pet behavior data using a camera (e.g., Logitech C920) or a sensor (e.g., DHT22). The camera captures video of the room in real time, and the sensor collects pet movements and environmental data (temperature, humidity, etc.). The device then records the pet's cries using a microphone (e.g., Blue Yeti).

[1156] Input: Real-time data on pet behavior and environment, barks

[1157] Output: behavioral data, vocalization data, environmental data

[1158] What it does: The device collects data from the camera and sensors and temporarily stores it locally. Every time motion is detected, the camera image is updated and the sensors record temperature and humidity data. Every time sound is detected, the audio recording is updated.

[1159] Step 2:

[1160] The device sends the collected behavioral data and vocalization data to the server, where the data is appropriately packetized and transmitted via a communication network (e.g., Wi-Fi).

[1161] Input: behavioral data, vocalization data, environmental data

[1162] Output: Packet data sent to the server

[1163] How it works: The device splits the collected data into packets, encrypts them, and then sends them to the cloud server via Wi-Fi, using the Python requests library to make an HTTP POST request.

[1164] Step 3:

[1165] The server inputs the received data into an AI model for analysis, which then analyzes the behavioral, sensor, and vocalization data to predict the pet's health and emotions.

[1166] Input: Data received from the terminal

[1167] Output: Health status and emotion predictions

[1168] How it works: After verifying the format of the received data, the server inputs it into an AI model trained with TensorFlow and PyTorch. The AI ​​model analyzes the data and classifies the pet's state, for example, determining whether it is "stressed," "hungry," or "relaxed."

[1169] Step 4:

[1170] The server recognizes the user's emotions using an emotion engine, which analyzes the user's voice messages and text messages to read the user's emotions.

[1171] Input: User's voice message, text message

[1172] Output: User's emotional state

[1173] How it works: The server uses Google Cloud's Natural Language API to analyze voice and text messages received from users. Based on the analysis results, it determines the user's emotional state, such as whether they are "stressed" or "relaxed."

[1174] Step 5:

[1175] The server then uses the analysis results to generate a report for the owner, which includes the pet's current health and mood, as well as recommended treatments.

[1176] Input: Health status, emotional predictions, and user emotional state

[1177] Output: Report for owner

[1178] Specific operation: The server uses a template engine (e.g., Jinja2) to automatically generate a PDF report based on the analysis results. The generated report is sent to the user via an Android or iOS app. Important notifications are also sent via SMS or push notification.

[1179] Step 6:

[1180] The server controls specific devices based on the analysis results, for example, instructing a pet food management device to provide food or starting a massage device.

[1181] Input: Health and emotional predictions, and the user's emotional state

[1182] Output: Device control instructions

[1183] Specific operation: Based on the analysis results, the server sends an instruction to the Furbo dog camera to distribute treats, and also sends a remote activation signal to the Lurvig pet massager.

[1184] The above is the flow of processing by the system.

[1185] (Application example 2)

[1186] 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."

[1187] While systems that monitor pet behavior and health already exist, they do not take into account the owner's mental state, making it difficult to provide appropriate care based on the owner's emotional state. Furthermore, there is a lack of systems that automatically suggest food delivery or special services based on the pet's condition. This places a heavy burden on owners in caring for their pets, making them prone to stress.

[1188] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1189] In this invention, the server includes means for monitoring the pet's behavior, means for recording the pet's cries, means for collecting and transmitting this data to the server, means for analyzing the data in the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for using an emotion engine that recognizes the user's emotions, and means for proposing recommended measures and food delivery in consideration of the pet's health condition and the user's emotional state. This allows for optimal care and response by taking into account not only the pet's condition but also the owner's emotional state. Furthermore, by proposing food delivery according to the pet's condition, it is possible to reduce the owner's burden and increase the happiness of both the pet and the owner.

[1190] "Means for monitoring pet behavior" refers to devices or systems that use cameras or motion sensors to record and understand pet movements and locations in real time.

[1191] A "means for recording pet cries" is a device or system that uses a microphone to collect the voices and cries of pets and save them as audio data.

[1192] The "means for collecting and transmitting this data to the server" refers to a communication device or system for transferring the monitored behavior data and recorded animal vocalization data to the server via a network.

[1193] "Means for analyzing data on a server and inferring a pet's condition" refers to a system that uses AI programs and algorithms on a server to analyze collected data and infer a pet's health and behavioral status.

[1194] The "means for generating a report based on the analysis results and notifying the user" refers to a device or system for creating a report on the pet's condition based on the analyzed data and notifying the user of the report.

[1195] The "means for controlling a specific device based on the analysis results" is a system for remotely operating and controlling a pet device (e.g., a food management device or a massage device) based on the analysis results.

[1196] The "means for using an emotion engine that recognizes the user's emotions" refers to software or hardware for reading and analyzing emotions from the user's voice, facial expressions, and messages.

[1197] "A means for proposing recommended measures and food delivery taking into consideration the pet's health condition and the user's emotional state" is a system that comprehensively assesses the pet's analysis results and the user's emotional state to provide appropriate measures (e.g., special food suggestions and delivery).

[1198] This invention is a system for monitoring the behavior and health condition of a pet and providing appropriate information and responses to the owner. The system includes means for monitoring the behavior of the pet, means for recording the pet's cries, means for collecting this data and sending it to a server, means for analyzing the data on the server and estimating the pet's condition, means for generating a report based on the analysis results and notifying the user, means for controlling a specific device based on the analysis results, means for using an emotion engine that recognizes the user's emotions, and means for suggesting recommended measures and food delivery in consideration of the pet's health condition and the user's emotional state.

[1199] An embodiment of this system is described in detail below.

[1200] Hardware and Software Configuration

[1201] Hardware:

[1202] 1. Smart cameras (e.g. Nest Cam): Monitor and record your pet's behavior in real time.

[1203] 2. Microphone (e.g. smartphone built-in microphone): Record your pet's cries.

[1204] 3. Communication terminal (e.g., smartphone): A device used to send collected data to a server.

[1205] software:

[1206] 1. OpenCV: Analyzes camera footage and detects pet movements.

[1207] 2. EmotionEngine: Recognizes emotions from user voice and messages.

[1208] 3. FoodDeliveryService: A service for arranging food delivery.

[1209] 4. Requests: HTTP request library for data communication.

[1210] Data collection and transmission

[1211] The smart camera captures images of your pet and analyzes the pet's behavior data using OpenCV. This records the pet's movements and behavior patterns. At the same time, the microphone records the pet's barks and saves them as audio data. This data is then sent to the server via the communication terminal.

[1212] Data analysis and inference

[1213] The server inputs the collected behavioral and vocalization data into an AI model to analyze the pet's health and emotions. The analysis uses behavioral patterns, vocalization characteristics, and environmental data. It also uses the user's emotion engine to recognize emotions from the user's voice and messages and incorporate them into the analysis data. This allows for a comprehensive evaluation of the condition of both the pet and the user.

[1214] Reporting and Notifications

[1215] Based on the analysis results, the server generates a report for the owner, which includes the pet's health status, emotions, and recommended measures. The report also takes into account the user's emotional information and adjusts the report content and notification method. The generated report is sent to a communication device, allowing the owner to understand the pet's condition and take any necessary measures.

[1216] Device control and food delivery proposals

[1217] Based on the analysis results, the server controls specific devices. For example, it can instruct a pet food management device to provide food or activate a massage device. It can also suggest the delivery of appropriate food or stress-relieving items depending on the user's emotional state. This allows optimal care even when the owner is feeling stressed.

[1218] Specific examples

[1219] For example, if the analysis results show that the pet is tired and the user is also feeling stressed, the server will suggest special nutritious food through the food delivery service, along with relaxing items, allowing both pet and owner to live a happy and healthy life.

[1220] Example prompt sentence:

[1221] "Pet is lying on the floor," "Pet is not making much noise," "User is feeling stressed"

[1222] Based on this, the system generates a report suggesting "feeding the pet special nutritious food" and "delivering relaxation items to the user."

[1223] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1224] Step 1:

[1225] Data collection

[1226] The device uses a smart camera and microphone to collect data on pet behavior and barks in real time. The smart camera captures the pet's movements and position as video and analyzes and digitizes it using OpenCV. The microphone records the pet's barks and stores them as audio data.

[1227] Input: Real-time video of pet, pet barking

[1228] Output: behavioral data, audio data

[1229] Step 2:

[1230] Sending data

[1231] The device sends the collected behavioral data and vocalization data to the server via a communication network (e.g., Wi-Fi). The data is properly packetized and securely transferred to the server.

[1232] Input: behavioral data, audio data

[1233] Output: Data sent to the server

[1234] Step 3:

[1235] Data analysis

[1236] The server inputs the received data into an AI model that analyzes the pet's health and emotions. The AI ​​model then comprehensively assesses behavioral patterns, vocalization characteristics, environmental data, and other factors to predict the pet's condition.

[1237] Input: Received data (behavioral data, voice data)

[1238] Output: Analysis of pet's health and emotional state

[1239] Step 4:

[1240] User sentiment analysis

[1241] The server uses an emotion engine to recognize emotions from the user's voice and messages. The user's emotional state data is integrated with the analysis results and becomes the basis for the system's overall decision-making.

[1242] Input: User's voice message

[1243] Output: User's emotional state

[1244] Step 5:

[1245] Reporting and Notifications

[1246] The server generates a report based on the pet's analysis results and the user's emotional state. The report includes the pet's current health condition and emotions, as well as recommended measures. The generated report is sent to the communication device.

[1247] Input: Analysis results of pet health and emotional state, user emotional state

[1248] Output: Report for owner

[1249] Step 6:

[1250] Device control and food delivery suggestions

[1251] Based on the analysis results, the server controls specific devices (e.g., food management devices, massage devices), and, if necessary, suggests suitable food and relaxation items for pets through a food delivery service.

[1252] Input: Analysis results of pets, reports based on the user's emotional state

[1253] Output: Device control instructions, food delivery suggestions

[1254] Example: If the analysis shows that the pet is tired and the user is perceived as stressed, the server will suggest the delivery of nutritious food and relaxation items.

[1255] Example prompt sentence:

[1256] "Pet is lying on the floor," "Pet is not making much noise," "User is feeling stressed"

[1257] 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.

[1258] 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.

[1259] 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.

[1260] 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.

[1261] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1262] 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.

[1263] 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).

[1264] 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.

[1265] 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."

[1266] 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.

[1267] 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).

[1268] 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.

[1269] 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.

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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.

[1274] 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.

[1275] 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.

[1276] 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.

[1277] 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.

[1278] The following is further disclosed regarding the above embodiment.

[1279] (Claim 1)

[1280] A means of monitoring pet behavior;

[1281] A way to record your pet's cries,

[1282] means for collecting and transmitting this data to a server;

[1283] A method for analyzing data on the server and predicting the pet's condition,

[1284] A means for generating a report based on the analysis results and notifying the user of the report;

[1285] A means for controlling a specific device based on the analysis result;

[1286] A system including:

[1287] (Claim 2)

[1288] 2. The system according to claim 1, further comprising means for controlling the pet food management device based on the analysis results.

[1289] (Claim 3)

[1290] 10. The system according to claim 1, further comprising means for controlling a pet massage device based on the analysis results.

[1291] "Example 1"

[1292] (Claim 1)

[1293] A means of monitoring pet behavior;

[1294] A way to record your pet's cries,

[1295] means for collecting and transmitting this data to a server;

[1296] A method for analyzing data on a server and using a generative AI model to predict the state of the pet;

[1297] a means for inputting data into the generative AI model using prompt sentences;

[1298] A means for generating a report based on the analysis results and notifying the user of the report;

[1299] A means for controlling a specific device based on the analysis result;

[1300] A system including:

[1301] (Claim 2)

[1302] 10. The system of claim 1, further comprising means for controlling a pet feeding device based on the analysis results.

[1303] (Claim 3)

[1304] 10. The system according to claim 1, further comprising means for controlling a pet massage device based on the analysis results.

[1305] "Application Example 1"

[1306] (Claim 1)

[1307] A means of monitoring pet behavior;

[1308] A way to record your pet's cries,

[1309] means for collecting and transmitting this data to a server;

[1310] A method for analyzing data on the server and predicting the pet's condition,

[1311] A means for generating a report based on the analysis results and notifying the user of the report;

[1312] A means for controlling a specific device based on the analysis result;

[1313] means for notifying the user's communication terminal of the analyzed pet's health condition in real time;

[1314] A means for customers to easily understand the health status of their pets in physical stores such as pet shops,

[1315] A system including:

[1316] (Claim 2)

[1317] 2. The system according to claim 1, further comprising means for controlling the pet food management device based on the analysis results.

[1318] (Claim 3)

[1319] 10. The system according to claim 1, further comprising means for controlling a pet massage device based on the analysis results.

[1320] "Example 2: Combining Emotion Engines"

[1321] (Claim 1)

[1322] A means of monitoring pet behavior;

[1323] A way to record your pet's cries,

[1324] means for collecting and transmitting this data to a server;

[1325] The data received on the server is input into an AI model, and behavioral, environmental, and vocalization data is analyzed to predict the pet's health and emotions.

[1326] A means for recognizing user emotions and incorporating them into the analysis data;

[1327] A means for generating a report based on the analysis results and notifying the user of the report;

[1328] A means for controlling a specific device based on the analysis result;

[1329] A system including:

[1330] (Claim 2)

[1331] 2. The system according to claim 1, further comprising means for controlling the pet food management device based on the analysis results.

[1332] (Claim 3)

[1333] 10. The system according to claim 1, further comprising means for controlling a pet massage device based on the analysis results.

[1334] "Application example 2 when combining emotion engines"

[1335] (Claim 1)

[1336] A means of monitoring pet behavior;

[1337] A way to record your pet's cries,

[1338] means for collecting and transmitting this data to a server;

[1339] A method for analyzing data on the server and predicting the pet's condition,

[1340] A means for generating a report based on the analysis results and notifying the user of the report;

[1341] A means for controlling a specific device based on the analysis result;

[1342] means for using an emotion engine to recognize the emotion of a user;

[1343] A means of suggesting recommended measures and food delivery taking into account the pet's health condition and the user's emotional state;

[1344] A system including:

[1345] (Claim 2)

[1346] The system according to claim 1, further comprising means for controlling the pet food management device based on the analysis results and for suggesting optimal measures according to the user's emotional state.

[1347] (Claim 3)

[1348] 2. The system according to claim 1, further comprising means for controlling a pet massage device based on the analysis result and for suggesting relaxation items according to the emotional state of the user. [Explanation of symbols]

[1349] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of monitoring pet behavior; A way to record pet sounds, means for collecting and transmitting this data to a server; A method for analyzing data on the server and predicting the pet's condition, A means for generating a report based on the analysis results and notifying the user of the report; A means for controlling a specific device based on the analysis result; A system including:

2. The system according to claim 1, further comprising means for controlling the pet food management device based on the analysis results.

3. 2. The system according to claim 1, further comprising means for controlling a pet massage device based on the analysis results.

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