system

Abstract

We provide the system. [Solution] A means for recording data received from a device for acquiring biological information, A means for generating a three-dimensional model of an animal based on the aforementioned data, Means for displaying the three-dimensional model through augmented reality or virtual reality, A system that includes this.

Description

Technical Field

[0005] ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, pet health management has been emphasized, but with conventional methods, it is difficult for pet owners to grasp the health status of their pets in detail in real time, and there is a problem that they cannot detect early the poor physical condition or behavioral changes of their pets. Furthermore, a lot of time and specialized knowledge are required to establish an exercise plan suitable for a pet, which is a high hurdle for ordinary pet owners. To solve these problems, there is a need for a system that can grasp the health status of a pet in real time and automatically generate an appropriate training plan.

Means for Solving the Problems

[0005] The present invention solves the above problems by providing a system that records data received from a device for acquiring biological information, generates a three-dimensional model of an animal based on that data, and displays the three-dimensional model through augmented reality or virtual reality. Furthermore, by including means for analyzing the data and evaluating the animal's health condition, and means for generating an exercise plan based on the evaluation, the present invention enables pet owners to easily obtain an appropriate training plan while keeping track of their pet's health condition in real time.

[0006] A "device for acquiring biometric information" refers to a wearable device or sensor equipment that senses biometric information such as an animal's heart rate, body temperature, location, and activity level, and transmits it as data.

[0007] "Means for recording data" refers to storage devices and database systems that store acquired biometric data in digital format and make it accessible for analysis and reference as needed.

[0008] "Means for generating three-dimensional models" refers to software or algorithms that create a three-dimensional visual model of an animal as a digital twin on a computer based on acquired biological data.

[0009] "Means of displaying through augmented reality or virtual reality" refers to display devices or headsets for visually presenting three-dimensional models, and technologies for integrating them into augmented reality (AR) or virtual reality (VR) environments.

[0010] "Means of data analysis" refers to software or data analysis algorithms used to process collected biological information data and evaluate the health status and behavioral patterns of animals.

[0011] "Means for evaluating health status" refer to criteria and methods for diagnosing the current health status and presence or absence of abnormalities in animals based on analyzed data.

[0012] "Means for generating exercise plans" refers to algorithms or systems that automatically create optimal exercise and training plans based on an animal's biological information and health condition. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the 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.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0027] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention relates to an animal health management system, and specific embodiments are described below. This system is mainly operated using a wearable device, a server that analyzes biometric information, a terminal that receives and displays information, and a user.

[0035] First, the server receives biometric information via Bluetooth® from a wearable device attached to the animal. This device measures important health indicators such as heart rate, body temperature, and activity level. The received data is stored in the server's database in real time, including a timestamp at the time of each measurement.

[0036] Next, the server generates a three-dimensional model of the animal based on the collected data. This model generation uses computer graphics (CG) technology to faithfully reproduce the animal's appearance and movements, employing algorithms designed to instantly identify any abnormal behavior or conditions.

[0037] This three-dimensional model is displayed via augmented reality (AR) or virtual reality (VR) media depending on the device. Users can view this 3D model using devices such as smartphones and tablets, and intuitively understand the animal's movements and health condition.

[0038] In addition to displaying the model, the device also presents the data analysis results sent from the server. This allows the user to receive real-time notifications about the animal's health status, and any abnormalities detected are immediately presented as alarms. For example, if a pet's body temperature exceeds the standard range, the device warns the user by displaying it in red.

[0039] Furthermore, the server has a function that analyzes past data and uses artificial intelligence (AI) to generate an optimal exercise plan for each individual animal. This AI automatically creates a training plan based on the animal's age, weight, and health information, and sends it to the terminal. The user can manage the animal's exercise and activity based on the received training plan and provide feedback on the results to the server.

[0040] In this way, the system comprehensively manages the health status of animals and helps users quickly understand their pets' health and provide appropriate care. This embodiment can effectively solve the various problems associated with pet care.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The server periodically receives data from the wearable device via Bluetooth. This data includes the pet's heart rate, body temperature, and activity level. The received data is instantly stored in a database, and each data entry is timestamped.

[0044] Step 2:

[0045] The server performs analysis to assess the pet's health status based on the stored data. By using anomaly detection algorithms to identify data that deviates from the pet's normal health patterns, it enables real-time monitoring of the pet's health status.

[0046] Step 3:

[0047] The server uses the analyzed data to generate or update a three-dimensional model of the pet. Using computer graphics (CG) technology, the model faithfully reproduces the animal's appearance and movements, and visually highlights any abnormalities that may be detected.

[0048] Step 4:

[0049] The server sends the updated 3D model and health assessment results to the terminal. The data sent here also includes detailed information about the pet's recent health status.

[0050] Step 5:

[0051] The device displays a model of the pet in an augmented reality (AR) or virtual reality (VR) environment based on the received 3D model and health data. Through the application, users can view real-time visual feedback on the pet's movements and health.

[0052] Step 6:

[0053] The device will display alerts to the user if any abnormalities or warnings are generated. For example, if a pet's body temperature rises rapidly, a red warning will be displayed on the device screen.

[0054] Step 7:

[0055] The server analyzes collected historical data and uses AI to generate the optimal training plan for your pet. This plan is tailored based on the pet's age, health condition, and past activity level.

[0056] Step 8:

[0057] The server sends the generated training plan to the terminal. The terminal presents the plan to the user through the application and provides specific instructions for execution.

[0058] Step 9:

[0059] Users can use their devices to implement training plans and check their pet's reactions and progress. They can also send feedback to the server after implementation, which is used to generate future training plans.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] For pet owners, quickly and accurately understanding their animals' health is a crucial concern. However, conventional health management systems have struggled to detect abnormal health conditions early and respond appropriately. Furthermore, the automatic generation of exercise plans optimized for individual animals has been insufficient. Therefore, there is a need for a means to monitor and analyze animals' health in real time.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for recording information received from a device for acquiring biological information, means for generating a three-dimensional shape of an animal based on the information, means for displaying the three-dimensional shape through visualization technology, and means for analyzing the information and setting an anomaly detection flag. This makes it possible to monitor the health status of animals in real time and to quickly warn if an anomaly is detected. Furthermore, it enables the automatic generation of an optimal exercise plan for each individual animal, thereby achieving more effective health management.

[0065] "Biometric information" refers to data that indicates an animal's health status, such as heart rate, body temperature, and activity level.

[0066] A "device" is a piece of equipment attached to an animal to acquire biological information.

[0067] "Means of recording" refers to methods or devices for storing received biological information.

[0068] "Information" refers to data such as biometric measurements and analysis results obtained from the device.

[0069] A "three-dimensional shape" is a three-dimensional digital model created to reproduce the posture and movement of an animal.

[0070] "Means of generation" refers to processes and devices for analyzing biological information to create three-dimensional digital models.

[0071] "Visualization technology" refers to the technology of displaying three-dimensional digital models using augmented reality (AR) or virtual reality (VR) methods.

[0072] "Means of analysis" refer to methods and devices for evaluating biological information and detecting abnormal values ​​or diagnosing health conditions.

[0073] An "anomaly detection flag" is an indicator set to identify abnormal data or conditions within biometric information.

[0074] To implement this invention, it is necessary for the server, terminals, and users to all cooperate in building an animal health management system.

[0075] The server receives biometric information via Bluetooth from wearable devices attached to animals. These devices can measure health indicators such as heart rate, body temperature, and activity level in real time. The server records the received information in a database and sets an anomaly detection flag as needed. When analyzing the information, algorithms are used to quickly identify abnormal data and conditions.

[0076] Furthermore, the server uses computer graphics (CG) technology to generate a three-dimensional digital model based on the collected information. This model faithfully reproduces the animal's actual appearance and movements. The generated three-dimensional model is useful for simulating abnormalities or the animal's movements as needed.

[0077] The terminal receives 3D models and analysis results from the server and displays them to the user. The terminal successfully uses AR and VR technology to display the models, helping users intuitively understand the animal's health status. The terminal also provides visual and audible alerts based on anomaly detection, ensuring users receive timely information.

[0078] Users can monitor the animal's health and provide appropriate care based on information provided through their device. They can also review exercise plans generated by the server and plan actions to maintain the animal's health. Specifically, users can receive an appropriate exercise plan from the generating AI model by entering prompts such as "Tell me the appropriate amount of exercise."

[0079] In this way, this invention provides a series of technical means for the comprehensive management of animal health. It is designed to provide animal-appropriate health management and to enable users to respond quickly and appropriately.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The server receives biometric information via Bluetooth communication from wearable devices attached to animals. It receives data such as heart rate, body temperature, and activity levels as input and records them in a database in real time. If the connection to the device is lost, it attempts to reconnect and constantly monitors the connection status. The output is a collection of organized biometric information.

[0083] Step 2:

[0084] The server analyzes the received biometric data and detects abnormal values. The input is the biometric data received in step 1. During the analysis process, an alert flag is set if the heart rate or body temperature exceeds the standard value. The output is the analysis result, which includes information on whether an abnormality was detected.

[0085] Step 3:

[0086] The server generates a three-dimensional digital model of an animal based on its biological information and analysis results. The input is the analyzed biological information and the analysis results at that time. Using computer graphics (CG) technology, the server reproduces the animal's appearance and movements in real time, particularly highlighting abnormal behaviors. The output is a three-dimensional model that can be updated in real time.

[0087] Step 4:

[0088] The terminal receives a 3D model and analysis results sent from the server. The input consists of 3D model data and analysis results generated by the server. The terminal uses AR or VR to visually display the model, allowing the user to interact with it and check the animal's health status from various viewpoints. The output consists of the visualized 3D model and warning displays in case of abnormalities.

[0089] Step 5:

[0090] The user monitors the animal's health based on a three-dimensional model and analysis results displayed on the terminal. Inputs are the information and analysis results presented on the terminal. Based on the information reviewed, the user decides on the animal's care and management methods. Outputs are specific care and management actions for the animal.

[0091] Step 6:

[0092] The server uses a generative AI model based on historical data to generate an optimal exercise plan for the animal. The input consists of the animal's past health data and user prompts. The AI ​​model generates an appropriate exercise plan based on the animal's age and health condition, and the output is the exercise plan data.

[0093] Step 7:

[0094] The terminal receives the exercise plan from the server and notifies the user. The input is the exercise plan generated by the server. The exercise plan is displayed on the terminal screen and provided in a format that is easy for the user to understand. The output is a display of the exercise plan that the user can easily follow.

[0095] Step 8:

[0096] The user guides the animal's exercise based on the provided exercise plan and provides feedback to the server on the results and problems encountered. Inputs include the animal's responses and results during exercise, as well as the user's observations. Based on this feedback, the server further optimizes the next exercise plan. Output is the feedback information.

[0097] (Application Example 1)

[0098] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0099] Efficiently monitoring the health and activity of animals, and responding immediately when abnormalities occur, is a challenge in animal safety management. Especially in environments where multiple animals need to be monitored simultaneously, such as zoos and farms, rapid information gathering and notification systems for abnormal situations are essential.

[0100] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0101] In this invention, the server includes means for storing data received from a device for acquiring biological information, means for generating a three-dimensional model of an organism based on the data, means for displaying the three-dimensional model through augmented reality or virtual reality, means for comparing the data and model with predictive data to detect anomalies, and means for notifying a notification terminal of the detected anomaly. This makes it possible to immediately detect abnormal movements or health conditions of animals and to take appropriate action quickly.

[0102] A "device for acquiring biometric information" is a device designed to measure and collect biometric data from animals, such as heart rate, body temperature, and activity level.

[0103] A "three-dimensional model" is a digital representation that visualizes the appearance and movement of an animal in three dimensions, and is usually generated using computer graphics technology.

[0104] Augmented reality or virtual reality refers to technologies that overlay digital information onto a physical reality environment or technologies that create a completely virtual environment.

[0105] "Predictive data" refers to reference information used to predict specific anomalies based on data collected in the past.

[0106] "Means of notifying a notification terminal" refers to a method of sending information about an anomaly to a device accessible to the user to alert them.

[0107] This invention is an integrated monitoring system that enables immediate detection of abnormalities in animals and appropriate responses. This system is mainly composed of four core components: a biometric information collection device, a server, a notification terminal, and a user.

[0108] The server receives data via Bluetooth from a device that acquires biometric information. This device is equipped with a heart rate monitor, temperature sensor, and other sensors, and accumulates data tailored to the individual characteristics of each animal. The server then analyzes the received data and generates a three-dimensional model based on the animal's health status. Computer graphics technology such as Unity is used to generate this model, reproducing the animal's three-dimensional appearance and movements.

[0109] The terminal displays this three-dimensional model in augmented reality or virtual reality format, allowing the user to intuitively understand the animal's posture and activity. The system further detects anomalies by comparing them with previously collected predictive data and immediately notifies the notification terminal of the results. This allows the user to detect animal abnormalities in a timely manner and take prompt action.

[0110] As a concrete example, consider its use in a zoo. Suppose this system detects that one elephant is moving around more than usual at night. The server identifies this as an anomaly and notifies a terminal, allowing staff to quickly go to the scene. This significantly contributes to monitoring the animals' health and improving the safety of the facility.

[0111] An example of a prompt might be: "Design a system that detects abnormal behavior and provides real-time notifications based on animal biometric data and time-series data of its movements." Using this prompt, the generative AI model can support system development.

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] The server receives biometric data such as heart rate, body temperature, and activity level from biometric acquisition devices via Bluetooth. The input is the wearable device, and the output is the data stored in a database on the server. At this time, the data is timestamped, enabling real-time monitoring.

[0115] Step 2:

[0116] The server generates three-dimensional models of animals based on accumulated biometric data. The input is biometric data stored in a database, and the output is a three-dimensional model generated using Unity. The processing accurately reproduces the animal's body shape and movements.

[0117] Step 3:

[0118] The terminal displays a 3D model generated on the server using augmented or virtual reality. The input is 3D model data, and the output is a visual representation on the user's terminal. The terminal uses this information to allow the user to intuitively check the animal's health status and behavior.

[0119] Step 4:

[0120] The server detects anomalies in biometric data by comparing it with historical predictive data. The input is real-time biometric data and predictive data, and the output is the anomaly detection result. This uses a machine learning model to identify patterns of abnormal behavior.

[0121] Step 5:

[0122] If an anomaly is detected, the server immediately notifies the notification terminal. The input is the anomaly detection result, and the output is a notification message to the user. The terminal receives this notification and promptly alerts the user by displaying a warning or alert.

[0123] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0124] This invention relates to a system that comprehensively analyzes animal health management and user emotions to improve interaction with pets, and a specific embodiment thereof is described below. This system mainly consists of a wearable device, a server that analyzes biometric information, a terminal that displays the information, and an emotion engine that identifies the user's emotions.

[0125] First, the server receives biometric data in real time from wearable devices attached to the pet via Bluetooth or Wi-Fi. This data includes the pet's heart rate, body temperature, and activity level, and is immediately recorded in a database.

[0126] Next, the server analyzes the received data and assesses the pet's current health status. This process includes an anomaly detection algorithm that can quickly identify values ​​outside the normal range. The analysis results are used to generate a three-dimensional model of the animal as a digital twin, which the server then transmits to the terminal.

[0127] The device displays the received 3D model on an augmented reality (AR) or virtual reality (VR) platform, allowing users to visually check the animal's health status. This enables users to intuitively understand their pet's behavior and health indicators.

[0128] Furthermore, the system incorporates an emotion engine that recognizes the user's emotions. The device is equipped with a camera and microphone, and the emotion engine analyzes the user's facial expressions and tone of voice from this input data to determine the user's mental state. For example, if the user is worried about their pet's condition, the emotion engine will sense this and adjust the system to provide more detailed information about the pet's health.

[0129] The emotional data obtained by the emotion engine is also used to adjust the pet's exercise plan. The server dynamically changes the exercise plan according to the user's emotional state, working to improve satisfaction for both the user and the pet. The user can then exercise and manage their pet's health based on this plan and provide the results as feedback to the system.

[0130] In this form, the present invention is expected to enable deeper and more efficient pet health management and user interaction, thereby supporting the development of a good relationship between pets and their owners.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The server receives biometric information from the wearable device via Bluetooth. This information includes heart rate, body temperature, and activity level, and this data is recorded in a database.

[0134] Step 2:

[0135] The server analyzes recorded biometric data to assess the pet's health. Anomaly detection algorithms are used to identify data that exceeds normal limits. Detected anomalies are categorized into separate datasets to facilitate rapid response.

[0136] Step 3:

[0137] The server generates a three-dimensional model based on the analyzed data, visualizing the pet's current health status. The generated model is dynamically rendered using a three-dimensional graphics engine.

[0138] Step 4:

[0139] The device receives a 3D model and health information transmitted from the server and displays it in an augmented reality (AR) or virtual reality (VR) environment. This display allows the user to monitor the pet's movements and health status in real time.

[0140] Step 5:

[0141] The device uses its built-in camera and microphone to activate an emotion engine that analyzes the user's facial expressions and voice. The emotion engine infers the user's emotional state from this data and sends it to the server.

[0142] Step 6:

[0143] The server dynamically adjusts the pet's exercise plan based on data received from the emotion engine. During this process, an algorithm is applied that modifies the frequency and content of exercise to reflect the user's emotions.

[0144] Step 7:

[0145] The device displays a customized exercise plan to the user and provides specific action guidelines. The user interacts with their pet according to the displayed exercise plan.

[0146] Step 8:

[0147] Users provide feedback by entering the results of their interaction with their pet into their device. This feedback is then sent back to the server and used for subsequent data analysis and exercise plan generation.

[0148] This process facilitates the smooth provision of pet health management and exercise plans based on user emotions, optimizing interaction with pets.

[0149] (Example 2)

[0150] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0151] Conventional animal health management systems have faced challenges in real-time monitoring of animal biometric information and in implementing dynamic interactions to improve the relationship between users and animals. In particular, the optimization of interactions with animals that take user emotions into consideration has been insufficient, limiting the improvement of the user experience.

[0152] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0153] In this invention, the server includes means for recording information received from a device for acquiring biological information, means for generating a three-dimensional digital representation of an animal based on the information, means for displaying the three-dimensional digital representation through augmented reality or virtual reality, and emotion analysis means for recognizing the user's emotions and using this information to improve interaction with the animal. This enables real-time monitoring of biological information and optimization of dynamic interactions based on user emotions.

[0154] A "biological information acquisition device" is a device that acquires biological data such as heart rate, body temperature, and activity level from animals.

[0155] "Means of recording" refers to a system or process for storing received biometric data periodically or in real time.

[0156] "Three-dimensional digital representation" refers to a digital model that visualizes and reproduces the health condition of an animal in three dimensions.

[0157] Augmented reality and virtual reality are technologies that use digital information to present information in real or virtual environments.

[0158] "User emotion recognition" is the process of analyzing a user's facial expressions and tone of voice to determine their mental state.

[0159] A "emotion analysis tool" is a system that estimates the user's emotions and adjusts the interaction with animals accordingly.

[0160] An "exercise plan" is a schedule or program of exercise aimed at maintaining the animal's health and improving its interaction with the user.

[0161] "Dynamic adjustment" refers to the act or ability to modify plans or processes in real time or at near time intervals in response to circumstances.

[0162] To implement this invention, a specific hardware configuration and software process are required. This system consists of a wearable device, a server for analyzing biometric information, a terminal for displaying the information, and an emotion engine for identifying the user's emotions.

[0163] The server receives biometric data in real time via Bluetooth or Wi-Fi from wearable devices attached to animals. These devices are equipped with sensors for heart rate, body temperature, and other metrics, and the data is immediately recorded in a database on the server. The server then analyzes the data and uses anomaly detection algorithms to assess the pet's health. The detected information is generated on the server as a three-dimensional digital representation of the animal, which is then transmitted to the terminal.

[0164] The device receives digital representations transmitted from the server and displays them on an augmented reality (AR) or virtual reality (VR) platform. This feature allows users to intuitively understand their pet's health status. The device also includes an emotion engine that analyzes the user's facial expressions and voice through the camera and microphone to recognize emotions. Based on this information, the server dynamically adjusts exercise plans and health information to ensure the user feels at ease.

[0165] For example, if a user is worried about their pet while concentrating on work, the emotion engine will sense the user's concern, and the server will request the generative AI model to "suggest the best way for the user to interact with their pet to help them relax."

[0166] In this configuration, the system can perform advanced animal health management and enrich the user experience.

[0167] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0168] Step 1:

[0169] The server receives biometric data from wearable devices via Bluetooth or Wi-Fi. Inputs include biometric information such as heart rate, body temperature, and activity level. The server receives this data and immediately records it in a database. This process outputs the foundational data necessary for subsequent analysis.

[0170] Step 2:

[0171] The server analyzes the recorded biometric data and evaluates the animal's health status. The input includes the biometric data obtained in step 1, and an anomaly detection algorithm identifies data outside the normal range. The output generates a health assessment result, and an anomaly alert is issued as needed.

[0172] Step 3:

[0173] The server generates a three-dimensional digital representation of the animal based on the analysis results. The health assessment results obtained in Step 2 serve as input. This digital representation provides an output that reproduces the animal's current health status and behavior in real time. The created model is designed to be easily understood visually.

[0174] Step 4:

[0175] The server transmits a three-dimensional digital representation to the terminal. The three-dimensional model generated in step 3 is used as input. The terminal receives this output model and uses it in the next display step.

[0176] Step 5:

[0177] The device displays the received three-dimensional digital representation on an augmented reality (AR) or virtual reality (VR) platform. Input includes a digital model transmitted from a server, and output is provided that allows the user to visually check the pet's health status. Through this, the user can intuitively understand the pet's condition.

[0178] Step 6:

[0179] The device uses its camera and microphone to capture the user's facial expressions and voice tone. The input includes real-time user data. The emotion engine analyzes this data and generates an output that determines the user's psychological state. This enables responses based on the user's emotions.

[0180] Step 7:

[0181] The server generates and dynamically adjusts an exercise plan using the analysis results from the emotion engine. Inputs include the user's emotional state obtained in step 6 and the health assessment from step 2. The generating AI model provides an output suggesting the necessary exercise plan based on the prompt "Suggest the optimal way for the user to interact with their pet to relax." This plan improves the satisfaction of both the pet and the user.

[0182] (Application Example 2)

[0183] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0184] In conventional factory work environments, it is difficult to understand the psychological state of workers in real time and provide appropriate support for their work, making improvements in safety and work efficiency a challenge. Furthermore, there is a need to reduce worker stress and provide an environment where workers can work with peace of mind.

[0185] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0186] In this invention, the server includes means for recording data received from a device for acquiring biological information, means for generating a three-dimensional model of an animal based on the data, means for displaying the three-dimensional model through augmented reality or virtual reality, means for analyzing the psychological state of a person in the workplace, and means for adjusting work assistance based on the psychological state. This makes it possible to analyze the psychological state of a worker in real time and provide appropriate work assistance.

[0187] "Biometric information" refers to data that indicates the physical state of animals and humans, such as heart rate, body temperature, and activity level.

[0188] A "three-dimensional model" is a digital model that represents the shape of an object or living organism in three-dimensional space.

[0189] Augmented reality is a technology that overlays virtual information onto images of the real world.

[0190] "Virtual reality" is a technology that allows users to immerse themselves in a computer-generated three-dimensional space and experience an artificially created environment.

[0191] "Psychological state" refers to the state of a person's consciousness and emotions, and includes factors such as stress levels and relaxation levels.

[0192] "Work assistance" refers to support and assistance provided to ensure that work is performed efficiently and safely.

[0193] "Analysis" is the process of examining data to extract information and deepen understanding.

[0194] To realize this invention, it is necessary to develop a system that monitors the work environment within a factory, analyzes the psychological state of workers, and provides work support based on that analysis. For this purpose, the following hardware and software are recommended.

[0195] First, the server receives data from a device that acquires biometric information and records that data in real time. This uses wearable devices that acquire data using Bluetooth or Wi-Fi. The received data includes heart rate, body temperature, and other similar information.

[0196] Next, based on the received biometric data, the server generates a three-dimensional model of the animal. This model undergoes motion analysis using OpenCV and other tools, and also performs emotion analysis using a machine learning model with TENSORFLOW®.

[0197] The terminal is equipped with a function to display the aforementioned three-dimensional model in an augmented reality or virtual reality environment. This allows users to visually check the health status of animals and the psychological state of workers. The terminal is equipped with a camera and microphone, and analyzes the worker's facial expressions and voice to determine their psychological state.

[0198] Furthermore, the system incorporates a function that adjusts work assistance based on the user's psychological state. For example, if a worker is experiencing excessive stress, the software will automatically play relaxing music. It can also suggest necessary breaks by displaying warning messages on the screen.

[0199] For example, if the system detects that a worker is concentrating on a task for an extended period, it analyzes the situation, displays a message such as "Please consider pausing your work," and plays soothing music in the background.

[0200] An example of a prompt message might be: "Determine the emotions of the workers from the facial images input to the image data analysis model and monitor their stress levels in real time. Based on the results, decide whether to automatically play relaxing music." This can reduce the psychological burden on workers and provide a more efficient work environment.

[0201] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0202] Step 1:

[0203] The server receives data via Bluetooth or Wi-Fi from a device that acquires biometric information. This data includes heart rate and body temperature, and the server records this as input in a database. This enables real-time, continuous monitoring.

[0204] Step 2:

[0205] The server analyzes received biometric data and generates a three-dimensional model of the animal or worker. The input is biometric data, and the output is a three-dimensional model. OpenCV is used to analyze the motion and build a model for visualizing each data point.

[0206] Step 3:

[0207] The device displays the generated three-dimensional model in an augmented reality or virtual reality environment. Here, it receives a three-dimensional model as input and outputs a visual AR / VR display. This display allows the user to intuitively check their health status and movements.

[0208] Step 4:

[0209] The server analyzes the psychological state of the worker using facial and audio data acquired via the terminal's camera and microphone. The input consists of visual and audio data, and the output is an index of the analyzed psychological state. TensorFlow is used to analyze emotions from this data.

[0210] Step 5:

[0211] The server adjusts work assistance based on the analyzed psychological state. Inputs include indicators of psychological state, and outputs include playing relaxing music or displaying warning messages on the screen. Specifically, it automatically selects appropriate actions and provides feedback to the user.

[0212] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0213] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0214] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0215] [Second Embodiment]

[0216] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0217] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0218] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0219] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0220] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0221] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0222] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0223] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0224] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0225] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0226] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0227] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0228] This invention relates to an animal health management system, and specific embodiments are described below. This system is mainly operated using a wearable device, a server that analyzes biometric information, a terminal that receives and displays information, and a user.

[0229] First, the server receives biometric information via Bluetooth from a wearable device attached to the animal. This device measures important health indicators such as heart rate, body temperature, and activity level. The received data is stored in the server's database in real time, including a timestamp at the time of each measurement.

[0230] Next, the server generates a three-dimensional model of the animal based on the collected data. This model generation uses computer graphics (CG) technology to faithfully reproduce the animal's appearance and movements, employing algorithms designed to instantly identify any abnormal behavior or conditions.

[0231] This three-dimensional model is displayed via augmented reality (AR) or virtual reality (VR) media depending on the device. Users can view this 3D model using devices such as smartphones and tablets, and intuitively understand the animal's movements and health condition.

[0232] In addition to displaying the model, the device also presents the data analysis results sent from the server. This allows the user to receive real-time notifications about the animal's health status, and any abnormalities detected are immediately presented as alarms. For example, if a pet's body temperature exceeds the standard range, the device warns the user by displaying it in red.

[0233] Furthermore, the server has a function that analyzes past data and uses artificial intelligence (AI) to generate an optimal exercise plan for each individual animal. This AI automatically creates a training plan based on the animal's age, weight, and health information, and sends it to the terminal. The user can manage the animal's exercise and activity based on the received training plan and provide feedback on the results to the server.

[0234] In this way, the system comprehensively manages the health status of animals and helps users quickly understand their pets' health and provide appropriate care. This embodiment can effectively solve the various problems associated with pet care.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] The server periodically receives data from the wearable device via Bluetooth. This data includes the pet's heart rate, body temperature, and activity level. The received data is instantly stored in a database, and each data entry is timestamped.

[0238] Step 2:

[0239] The server performs analysis to assess the pet's health status based on the stored data. By using anomaly detection algorithms to identify data that deviates from the pet's normal health patterns, it enables real-time monitoring of the pet's health status.

[0240] Step 3:

[0241] The server uses the analyzed data to generate or update a three-dimensional model of the pet. Using computer graphics (CG) technology, the model faithfully reproduces the animal's appearance and movements, and visually highlights any abnormalities that may be detected.

[0242] Step 4:

[0243] The server sends the updated 3D model and health assessment results to the terminal. The data sent here also includes detailed information about the pet's recent health status.

[0244] Step 5:

[0245] The device displays a model of the pet in an augmented reality (AR) or virtual reality (VR) environment based on the received 3D model and health data. Through the application, users can view real-time visual feedback on the pet's movements and health.

[0246] Step 6:

[0247] The device will display alerts to the user if any abnormalities or warnings are generated. For example, if a pet's body temperature rises rapidly, a red warning will be displayed on the device screen.

[0248] Step 7:

[0249] The server analyzes collected historical data and uses AI to generate the optimal training plan for your pet. This plan is tailored based on the pet's age, health condition, and past activity level.

[0250] Step 8:

[0251] The server sends the generated training plan to the terminal. The terminal presents the plan to the user through the application and provides specific instructions for execution.

[0252] Step 9:

[0253] Users can use their devices to implement training plans and check their pet's reactions and progress. They can also send feedback to the server after implementation, which is used to generate future training plans.

[0254] (Example 1)

[0255] Next, we will describe Example 1. 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".

[0256] For pet owners, quickly and accurately understanding their animals' health is a crucial concern. However, conventional health management systems have struggled to detect abnormal health conditions early and respond appropriately. Furthermore, the automatic generation of exercise plans optimized for individual animals has been insufficient. Therefore, there is a need for a means to monitor and analyze animals' health in real time.

[0257] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0258] In this invention, the server includes means for recording information received from a device for acquiring biological information, means for generating a three-dimensional shape of an animal based on the information, means for displaying the three-dimensional shape through visualization technology, and means for analyzing the information and setting an anomaly detection flag. This makes it possible to monitor the health status of animals in real time and to quickly warn if an anomaly is detected. Furthermore, it enables the automatic generation of an optimal exercise plan for each individual animal, thereby achieving more effective health management.

[0259] "Biometric information" refers to data that indicates an animal's health status, such as heart rate, body temperature, and activity level.

[0260] A "device" is a piece of equipment attached to an animal to acquire biological information.

[0261] "Means of recording" refers to methods or devices for storing received biological information.

[0262] "Information" refers to data such as biometric measurements and analysis results obtained from the device.

[0263] A "three-dimensional shape" is a three-dimensional digital model created to reproduce the posture and movement of an animal.

[0264] "Means of generation" refers to processes and devices for analyzing biological information to create three-dimensional digital models.

[0265] "Visualization technology" refers to the technology of displaying three-dimensional digital models using augmented reality (AR) or virtual reality (VR) methods.

[0266] "Means of analysis" refer to methods and devices for evaluating biological information and detecting abnormal values ​​or diagnosing health conditions.

[0267] An "anomaly detection flag" is an indicator set to identify abnormal data or conditions within biometric information.

[0268] To implement this invention, it is necessary for the server, terminals, and users to all cooperate in building an animal health management system.

[0269] The server receives biometric information via Bluetooth from wearable devices attached to animals. These devices can measure health indicators such as heart rate, body temperature, and activity level in real time. The server records the received information in a database and sets an anomaly detection flag as needed. When analyzing the information, algorithms are used to quickly identify abnormal data and conditions.

[0270] Furthermore, the server uses computer graphics (CG) technology to generate a three-dimensional digital model based on the collected information. This model faithfully reproduces the animal's actual appearance and movements. The generated three-dimensional model is useful for simulating abnormalities or the animal's movements as needed.

[0271] The terminal receives 3D models and analysis results from the server and displays them to the user. The terminal successfully uses AR and VR technology to display the models, helping users intuitively understand the animal's health status. The terminal also provides visual and audible alerts based on anomaly detection, ensuring users receive timely information.

[0272] Users can monitor the animal's health and provide appropriate care based on information provided through their device. They can also review exercise plans generated by the server and plan actions to maintain the animal's health. Specifically, users can receive an appropriate exercise plan from the generating AI model by entering prompts such as "Tell me the appropriate amount of exercise."

[0273] In this way, this invention provides a series of technical means for the comprehensive management of animal health. It is designed to provide animal-appropriate health management and to enable users to respond quickly and appropriately.

[0274] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0275] Step 1:

[0276] The server receives biometric information via Bluetooth communication from wearable devices attached to animals. It receives data such as heart rate, body temperature, and activity levels as input and records them in a database in real time. If the connection to the device is lost, it attempts to reconnect and constantly monitors the connection status. The output is a collection of organized biometric information.

[0277] Step 2:

[0278] The server analyzes the received biometric data and detects abnormal values. The input is the biometric data received in step 1. During the analysis process, an alert flag is set if the heart rate or body temperature exceeds the standard value. The output is the analysis result, which includes information on whether an abnormality was detected.

[0279] Step 3:

[0280] The server generates a three-dimensional digital model of an animal based on its biological information and analysis results. The input is the analyzed biological information and the analysis results at that time. Using computer graphics (CG) technology, the server reproduces the animal's appearance and movements in real time, particularly highlighting abnormal behaviors. The output is a three-dimensional model that can be updated in real time.

[0281] Step 4:

[0282] The terminal receives the three-dimensional model and the analysis result sent from the server. The input is the three-dimensional model data and the analysis result generated by the server. The terminal visually displays the model using AR or VR, and the user can check the health status of the animal from various viewpoints by operating it. The output is the visualized three-dimensional model and the warning display when an abnormality occurs.

[0283] Step 5:

[0284] Based on the three-dimensional model and the analysis result displayed on the terminal, the user monitors the health status of the animal. The input is the information presented on the terminal and the analysis result. Based on the information confirmed, the user determines the care and management methods for the animal. The output is the specific care and management actions for the animal.

[0285] Step 6:

[0286] The server uses the generated AI model by leveraging past data to generate an optimal exercise plan for the animal. The input is the past health data of the animal and the user's prompt sentence. The AI model generates an appropriate exercise plan according to the age and health status of the animal, and the output is the data of the exercise plan.

[0287] Step 7:

[0288] The terminal receives the exercise plan from the server and notifies the user. The input is the exercise plan generated by the server. The exercise plan is displayed on the screen of the terminal and provided in a user-friendly format. The output is the display of the exercise plan that the user can easily follow.

[0289] Step 8:

[0290] Based on the presented exercise plan, the user guides the animal's exercise and feedbacks the obtained results and problems to the server. The input is the reaction and results of the animal during exercise, and the user's observations. Thereby, the server further optimizes the next exercise plan based on the feedback. The output is the feedback information.

[0291] (Application Example 1)

[0292] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0293] Efficiently monitoring the health and activity of animals, and responding immediately when abnormalities occur, is a challenge in animal safety management. Especially in environments where multiple animals need to be monitored simultaneously, such as zoos and farms, rapid information gathering and notification systems for abnormal situations are essential.

[0294] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0295] In this invention, the server includes means for storing data received from a device for acquiring biological information, means for generating a three-dimensional model of an organism based on the data, means for displaying the three-dimensional model through augmented reality or virtual reality, means for comparing the data and model with predictive data to detect anomalies, and means for notifying a notification terminal of the detected anomaly. This makes it possible to immediately detect abnormal movements or health conditions of animals and to take appropriate action quickly.

[0296] A "device for acquiring biometric information" is a device designed to measure and collect biometric data from animals, such as heart rate, body temperature, and activity level.

[0297] A "three-dimensional model" is a digital representation that visualizes the appearance and movement of an animal in three dimensions, and is usually generated using computer graphics technology.

[0298] Augmented reality or virtual reality refers to technologies that overlay digital information onto a physical reality environment or technologies that create a completely virtual environment.

[0299] "Predictive data" refers to reference information used to predict specific anomalies based on data collected in the past.

[0300] "Means of notifying a notification terminal" refers to a method of sending information about an anomaly to a device accessible to the user to alert them.

[0301] This invention is an integrated monitoring system that enables immediate detection of abnormalities in animals and appropriate responses. This system is mainly composed of four core components: a biometric information collection device, a server, a notification terminal, and a user.

[0302] The server receives data via Bluetooth from a device that acquires biometric information. This device is equipped with a heart rate monitor, temperature sensor, and other sensors, and accumulates data tailored to the individual characteristics of each animal. The server then analyzes the received data and generates a three-dimensional model based on the animal's health status. Computer graphics technology such as Unity is used to generate this model, reproducing the animal's three-dimensional appearance and movements.

[0303] The terminal displays this three-dimensional model in augmented reality or virtual reality format, allowing the user to intuitively understand the animal's posture and activity. The system further detects anomalies by comparing them with previously collected predictive data and immediately notifies the notification terminal of the results. This allows the user to detect animal abnormalities in a timely manner and take prompt action.

[0304] As a concrete example, consider its use in a zoo. Suppose this system detects that one elephant is moving around more than usual at night. The server identifies this as an anomaly and notifies a terminal, allowing staff to quickly go to the scene. This significantly contributes to monitoring the animals' health and improving the safety of the facility.

[0305] As an example of a prompt sentence, a format such as "Please design a system that detects abnormal movements and notifies in real time based on biological data and time-series data of movements of animals." can be considered. By using this prompt, it is possible for the generative AI model to support system development.

[0306] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0307] Step 1:

[0308] The server receives biological data such as heart rate, body temperature, and activity level from the biological information acquisition device via Bluetooth. The input is a wearable device, and the data is accumulated in the database within the server as output. At this time, the data is given a timestamp, enabling real-time monitoring.

[0309] Step 2:

[0310] The server generates a three-dimensional model of the animal based on the accumulated biological data. The input is the biological data stored in the database, and the output is the three-dimensional model generated using Unity. In the process, the body shape information of the animal and the accurate reproduction of movements are performed.

[0311] Step 3:

[0312] The terminal displays the three-dimensional model generated by the server in augmented reality or virtual reality. The input is the three-dimensional model data, and the output is the visual representation on the user terminal. The terminal uses this information to enable the user to intuitively confirm the health status and behavior of the animal.

[0313] Step 4:

[0314] The server compares with past omen data and detects abnormalities in the biological data. The input is the real-time biological data and omen data, and the output is the abnormality detection result. A machine learning model is used for this to identify the patterns of abnormal movements.

[0315] Step 5:

[0316] If an anomaly is detected, the server immediately notifies the notification terminal. The input is the anomaly detection result, and the output is a notification message to the user. The terminal receives this notification and promptly alerts the user by displaying a warning or alert.

[0317] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0318] This invention relates to a system that comprehensively analyzes animal health management and user emotions to improve interaction with pets, and a specific embodiment thereof is described below. This system mainly consists of a wearable device, a server that analyzes biometric information, a terminal that displays the information, and an emotion engine that identifies the user's emotions.

[0319] First, the server receives biometric data in real time from wearable devices attached to the pet via Bluetooth or Wi-Fi. This data includes the pet's heart rate, body temperature, and activity level, and is immediately recorded in a database.

[0320] Next, the server analyzes the received data and assesses the pet's current health status. This process includes an anomaly detection algorithm that can quickly identify values ​​outside the normal range. The analysis results are used to generate a three-dimensional model of the animal as a digital twin, which the server then transmits to the terminal.

[0321] The device displays the received 3D model on an augmented reality (AR) or virtual reality (VR) platform, allowing users to visually check the animal's health status. This enables users to intuitively understand their pet's behavior and health indicators.

[0322] Furthermore, the system incorporates an emotion engine that recognizes the user's emotions. The device is equipped with a camera and microphone, and the emotion engine analyzes the user's facial expressions and tone of voice from this input data to determine the user's mental state. For example, if the user is worried about their pet's condition, the emotion engine will sense this and adjust the system to provide more detailed information about the pet's health.

[0323] The emotional data obtained by the emotion engine is also used to adjust the pet's exercise plan. The server dynamically changes the exercise plan according to the user's emotional state, working to improve satisfaction for both the user and the pet. The user can then exercise and manage their pet's health based on this plan and provide the results as feedback to the system.

[0324] In this form, the present invention is expected to enable deeper and more efficient pet health management and user interaction, thereby supporting the development of a good relationship between pets and their owners.

[0325] The following describes the processing flow.

[0326] Step 1:

[0327] The server receives biometric information from the wearable device via Bluetooth. This information includes heart rate, body temperature, and activity level, and this data is recorded in a database.

[0328] Step 2:

[0329] The server analyzes recorded biometric data to assess the pet's health. Anomaly detection algorithms are used to identify data that exceeds normal limits. Detected anomalies are categorized into separate datasets to facilitate rapid response.

[0330] Step 3:

[0331] The server generates a three-dimensional model based on the analyzed data, visualizing the pet's current health status. The generated model is dynamically rendered using a three-dimensional graphics engine.

[0332] Step 4:

[0333] The device receives a 3D model and health information transmitted from the server and displays it in an augmented reality (AR) or virtual reality (VR) environment. This display allows the user to monitor the pet's movements and health status in real time.

[0334] Step 5:

[0335] The device uses its built-in camera and microphone to activate an emotion engine that analyzes the user's facial expressions and voice. The emotion engine infers the user's emotional state from this data and sends it to the server.

[0336] Step 6:

[0337] The server dynamically adjusts the pet's exercise plan based on data received from the emotion engine. During this process, an algorithm is applied that modifies the frequency and content of exercise to reflect the user's emotions.

[0338] Step 7:

[0339] The device displays a customized exercise plan to the user and provides specific action guidelines. The user interacts with their pet according to the displayed exercise plan.

[0340] Step 8:

[0341] Users provide feedback by entering the results of their interaction with their pet into their device. This feedback is then sent back to the server and used for subsequent data analysis and exercise plan generation.

[0342] This process facilitates the smooth provision of pet health management and exercise plans based on user emotions, optimizing interaction with pets.

[0343] (Example 2)

[0344] Next, we will describe Example 2. 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] Conventional animal health management systems have faced challenges in real-time monitoring of animal biometric information and in implementing dynamic interactions to improve the relationship between users and animals. In particular, the optimization of interactions with animals that take user emotions into consideration has been insufficient, limiting the improvement of the user experience.

[0346] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0347] In this invention, the server includes means for recording information received from a device for acquiring biological information, means for generating a three-dimensional digital representation of an animal based on the information, means for displaying the three-dimensional digital representation through augmented reality or virtual reality, and emotion analysis means for recognizing the user's emotions and using this information to improve interaction with the animal. This enables real-time monitoring of biological information and optimization of dynamic interactions based on user emotions.

[0348] A "biological information acquisition device" is a device that acquires biological data such as heart rate, body temperature, and activity level from animals.

[0349] "Means of recording" refers to a system or process for storing received biometric data periodically or in real time.

[0350] "Three-dimensional digital representation" refers to a digital model that visualizes and reproduces the health condition of an animal in three dimensions.

[0351] Augmented reality and virtual reality are technologies that use digital information to present information in real or virtual environments.

[0352] "User emotion recognition" is the process of analyzing a user's facial expressions and tone of voice to determine their mental state.

[0353] A "emotion analysis tool" is a system that estimates the user's emotions and adjusts the interaction with animals accordingly.

[0354] An "exercise plan" is a schedule or program of exercise aimed at maintaining the animal's health and improving its interaction with the user.

[0355] "Dynamic adjustment" refers to the act or ability to modify plans or processes in real time or at near time intervals in response to circumstances.

[0356] To implement this invention, a specific hardware configuration and software process are required. This system consists of a wearable device, a server for analyzing biometric information, a terminal for displaying the information, and an emotion engine for identifying the user's emotions.

[0357] The server receives biometric data in real time via Bluetooth or Wi-Fi from wearable devices attached to animals. These devices are equipped with sensors for heart rate, body temperature, and other metrics, and the data is immediately recorded in a database on the server. The server then analyzes the data and uses anomaly detection algorithms to assess the pet's health. The detected information is generated on the server as a three-dimensional digital representation of the animal, which is then transmitted to the terminal.

[0358] The device receives digital representations transmitted from the server and displays them on an augmented reality (AR) or virtual reality (VR) platform. This feature allows users to intuitively understand their pet's health status. The device also includes an emotion engine that analyzes the user's facial expressions and voice through the camera and microphone to recognize emotions. Based on this information, the server dynamically adjusts exercise plans and health information to ensure the user feels at ease.

[0359] For example, if a user is worried about their pet while concentrating on work, the emotion engine will sense the user's concern, and the server will request the generative AI model to "suggest the best way for the user to interact with their pet to help them relax."

[0360] In this configuration, the system can perform advanced animal health management and enrich the user experience.

[0361] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0362] Step 1:

[0363] The server receives biometric data from wearable devices via Bluetooth or Wi-Fi. Inputs include biometric information such as heart rate, body temperature, and activity level. The server receives this data and immediately records it in a database. This process outputs the foundational data necessary for subsequent analysis.

[0364] Step 2:

[0365] The server analyzes the recorded biometric data and evaluates the animal's health status. The input includes the biometric data obtained in step 1, and an anomaly detection algorithm identifies data outside the normal range. The output generates a health assessment result, and an anomaly alert is issued as needed.

[0366] Step 3:

[0367] The server generates a three-dimensional digital representation of the animal based on the analysis results. The health assessment results obtained in Step 2 serve as input. This digital representation provides an output that reproduces the animal's current health status and behavior in real time. The created model is designed to be easily understood visually.

[0368] Step 4:

[0369] The server transmits a three-dimensional digital representation to the terminal. The three-dimensional model generated in step 3 is used as input. The terminal receives this output model and uses it in the next display step.

[0370] Step 5:

[0371] The device displays the received three-dimensional digital representation on an augmented reality (AR) or virtual reality (VR) platform. Input includes a digital model transmitted from a server, and output is provided that allows the user to visually check the pet's health status. Through this, the user can intuitively understand the pet's condition.

[0372] Step 6:

[0373] The device uses its camera and microphone to capture the user's facial expressions and voice tone. The input includes real-time user data. The emotion engine analyzes this data and generates an output that determines the user's psychological state. This enables responses based on the user's emotions.

[0374] Step 7:

[0375] The server generates and dynamically adjusts an exercise plan using the analysis results from the emotion engine. Inputs include the user's emotional state obtained in step 6 and the health assessment from step 2. The generating AI model provides an output suggesting the necessary exercise plan based on the prompt "Suggest the optimal way for the user to interact with their pet to relax." This plan improves the satisfaction of both the pet and the user.

[0376] (Application Example 2)

[0377] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0378] In conventional factory work environments, it is difficult to understand the psychological state of workers in real time and provide appropriate support for their work, making improvements in safety and work efficiency a challenge. Furthermore, there is a need to reduce worker stress and provide an environment where workers can work with peace of mind.

[0379] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0380] In this invention, the server includes means for recording data received from a device for acquiring biological information, means for generating a three-dimensional model of an animal based on the data, means for displaying the three-dimensional model through augmented reality or virtual reality, means for analyzing the psychological state of a person in the workplace, and means for adjusting work assistance based on the psychological state. This makes it possible to analyze the psychological state of a worker in real time and provide appropriate work assistance.

[0381] "Biometric information" refers to data that indicates the physical state of animals and humans, such as heart rate, body temperature, and activity level.

[0382] A "three-dimensional model" is a digital model that represents the shape of an object or living organism in three-dimensional space.

[0383] Augmented reality is a technology that overlays virtual information onto images of the real world.

[0384] "Virtual reality" is a technology that allows users to immerse themselves in a computer-generated three-dimensional space and experience an artificially created environment.

[0385] "Psychological state" refers to the state of a person's consciousness and emotions, and includes factors such as stress levels and relaxation levels.

[0386] "Work assistance" refers to support and assistance provided to ensure that work is performed efficiently and safely.

[0387] "Analysis" is the process of examining data to extract information and deepen understanding.

[0388] To realize this invention, it is necessary to develop a system that monitors the work environment within a factory, analyzes the psychological state of workers, and provides work support based on that analysis. For this purpose, the following hardware and software are recommended.

[0389] First, the server receives data from a device that acquires biometric information and records that data in real time. This uses wearable devices that acquire data using Bluetooth or Wi-Fi. The received data includes heart rate, body temperature, and other similar information.

[0390] Next, based on the received biometric data, the server generates a three-dimensional model of the animal. This model undergoes motion analysis using OpenCV and other tools, and also performs emotion analysis using a machine learning model with TensorFlow.

[0391] The terminal is equipped with a function to display the aforementioned three-dimensional model in an augmented reality or virtual reality environment. This allows users to visually check the health status of animals and the psychological state of workers. The terminal is equipped with a camera and microphone, and analyzes the worker's facial expressions and voice to determine their psychological state.

[0392] Furthermore, the system incorporates a function that adjusts work assistance based on the user's psychological state. For example, if a worker is experiencing excessive stress, the software will automatically play relaxing music. It can also suggest necessary breaks by displaying warning messages on the screen.

[0393] For example, if the system detects that a worker is concentrating on a task for an extended period, it analyzes the situation, displays a message such as "Please consider pausing your work," and plays soothing music in the background.

[0394] An example of a prompt message might be: "Determine the emotions of the workers from the facial images input to the image data analysis model and monitor their stress levels in real time. Based on the results, decide whether to automatically play relaxing music." This can reduce the psychological burden on workers and provide a more efficient work environment.

[0395] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0396] Step 1:

[0397] The server receives data via Bluetooth or Wi-Fi from a device that acquires biometric information. This data includes heart rate and body temperature, and the server records this as input in a database. This enables real-time, continuous monitoring.

[0398] Step 2:

[0399] The server analyzes received biometric data and generates a three-dimensional model of the animal or worker. The input is biometric data, and the output is a three-dimensional model. OpenCV is used to analyze the motion and build a model for visualizing each data point.

[0400] Step 3:

[0401] The device displays the generated three-dimensional model in an augmented reality or virtual reality environment. Here, it receives a three-dimensional model as input and outputs a visual AR / VR display. This display allows the user to intuitively check their health status and movements.

[0402] Step 4:

[0403] The server analyzes the psychological state of the worker using facial and audio data acquired via the terminal's camera and microphone. The input consists of visual and audio data, and the output is an index of the analyzed psychological state. TensorFlow is used to analyze emotions from this data.

[0404] Step 5:

[0405] The server adjusts work assistance based on the analyzed psychological state. Inputs include indicators of psychological state, and outputs include playing relaxing music or displaying warning messages on the screen. Specifically, it automatically selects appropriate actions and provides feedback to the user.

[0406] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0407] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0408] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0409] [Third Embodiment]

[0410] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0411] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0412] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0413] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0414] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0415] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0416] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0417] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0418] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0419] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0420] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0421] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0422] This invention relates to an animal health management system, and specific embodiments are described below. This system is mainly operated using a wearable device, a server that analyzes biometric information, a terminal that receives and displays information, and a user.

[0423] First, the server receives biometric information via Bluetooth from a wearable device attached to the animal. This device measures important health indicators such as heart rate, body temperature, and activity level. The received data is stored in the server's database in real time, including a timestamp at the time of each measurement.

[0424] Next, the server generates a three-dimensional model of the animal based on the collected data. This model generation uses computer graphics (CG) technology to faithfully reproduce the animal's appearance and movements, employing algorithms designed to instantly identify any abnormal behavior or conditions.

[0425] This three-dimensional model is displayed via augmented reality (AR) or virtual reality (VR) media depending on the device. Users can view this 3D model using devices such as smartphones and tablets, and intuitively understand the animal's movements and health condition.

[0426] In addition to displaying the model, the device also presents the data analysis results sent from the server. This allows the user to receive real-time notifications about the animal's health status, and any abnormalities detected are immediately presented as alarms. For example, if a pet's body temperature exceeds the standard range, the device warns the user by displaying it in red.

[0427] Furthermore, the server has a function that analyzes past data and uses artificial intelligence (AI) to generate an optimal exercise plan for each individual animal. This AI automatically creates a training plan based on the animal's age, weight, and health information, and sends it to the terminal. The user can manage the animal's exercise and activity based on the received training plan and provide feedback on the results to the server.

[0428] In this way, the system comprehensively manages the health status of animals and helps users quickly understand their pets' health and provide appropriate care. This embodiment can effectively solve the various problems associated with pet care.

[0429] The following describes the processing flow.

[0430] Step 1:

[0431] The server periodically receives data from the wearable device via Bluetooth. This data includes the pet's heart rate, body temperature, and activity level. The received data is instantly stored in a database, and each data entry is timestamped.

[0432] Step 2:

[0433] The server performs analysis to assess the pet's health status based on the stored data. By using anomaly detection algorithms to identify data that deviates from the pet's normal health patterns, it enables real-time monitoring of the pet's health status.

[0434] Step 3:

[0435] The server uses the analyzed data to generate or update a three-dimensional model of the pet. Using computer graphics (CG) technology, the model faithfully reproduces the animal's appearance and movements, and visually highlights any abnormalities that may be detected.

[0436] Step 4:

[0437] The server sends the updated 3D model and health assessment results to the terminal. The data sent here also includes detailed information about the pet's recent health status.

[0438] Step 5:

[0439] The device displays a model of the pet in an augmented reality (AR) or virtual reality (VR) environment based on the received 3D model and health data. Through the application, users can view real-time visual feedback on the pet's movements and health.

[0440] Step 6:

[0441] The device will display alerts to the user if any abnormalities or warnings are generated. For example, if a pet's body temperature rises rapidly, a red warning will be displayed on the device screen.

[0442] Step 7:

[0443] The server analyzes collected historical data and uses AI to generate the optimal training plan for your pet. This plan is tailored based on the pet's age, health condition, and past activity level.

[0444] Step 8:

[0445] The server sends the generated training plan to the terminal. The terminal presents the plan to the user through the application and provides specific instructions for execution.

[0446] Step 9:

[0447] Users can use their devices to implement training plans and check their pet's reactions and progress. They can also send feedback to the server after implementation, which is used to generate future training plans.

[0448] (Example 1)

[0449] Next, we will describe Example 1. 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."

[0450] For pet owners, quickly and accurately understanding their animals' health is a crucial concern. However, conventional health management systems have struggled to detect abnormal health conditions early and respond appropriately. Furthermore, the automatic generation of exercise plans optimized for individual animals has been insufficient. Therefore, there is a need for a means to monitor and analyze animals' health in real time.

[0451] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0452] In this invention, the server includes means for recording information received from a device for acquiring biological information, means for generating a three-dimensional shape of an animal based on the information, means for displaying the three-dimensional shape through visualization technology, and means for analyzing the information and setting an anomaly detection flag. This makes it possible to monitor the health status of animals in real time and to quickly warn if an anomaly is detected. Furthermore, it enables the automatic generation of an optimal exercise plan for each individual animal, thereby achieving more effective health management.

[0453] "Biometric information" refers to data that indicates an animal's health status, such as heart rate, body temperature, and activity level.

[0454] A "device" is a piece of equipment attached to an animal to acquire biological information.

[0455] "Means of recording" refers to methods or devices for storing received biological information.

[0456] "Information" refers to data such as biometric measurements and analysis results obtained from the device.

[0457] A "three-dimensional shape" is a three-dimensional digital model created to reproduce the posture and movement of an animal.

[0458] "Means of generation" refers to processes and devices for analyzing biological information to create three-dimensional digital models.

[0459] "Visualization technology" refers to the technology of displaying three-dimensional digital models using augmented reality (AR) or virtual reality (VR) methods.

[0460] "Means of analysis" refer to methods and devices for evaluating biological information and detecting abnormal values ​​or diagnosing health conditions.

[0461] An "anomaly detection flag" is an indicator set to identify abnormal data or conditions within biometric information.

[0462] To implement this invention, it is necessary for the server, terminals, and users to all cooperate in building an animal health management system.

[0463] The server receives biometric information via Bluetooth from wearable devices attached to animals. These devices can measure health indicators such as heart rate, body temperature, and activity level in real time. The server records the received information in a database and sets an anomaly detection flag as needed. When analyzing the information, algorithms are used to quickly identify abnormal data and conditions.

[0464] Furthermore, the server uses computer graphics (CG) technology to generate a three-dimensional digital model based on the collected information. This model faithfully reproduces the animal's actual appearance and movements. The generated three-dimensional model is useful for simulating abnormalities or the animal's movements as needed.

[0465] The terminal receives 3D models and analysis results from the server and displays them to the user. The terminal successfully uses AR and VR technology to display the models, helping users intuitively understand the animal's health status. The terminal also provides visual and audible alerts based on anomaly detection, ensuring users receive timely information.

[0466] Users can monitor the animal's health and provide appropriate care based on information provided through their device. They can also review exercise plans generated by the server and plan actions to maintain the animal's health. Specifically, users can receive an appropriate exercise plan from the generating AI model by entering prompts such as "Tell me the appropriate amount of exercise."

[0467] In this way, this invention provides a series of technical means for the comprehensive management of animal health. It is designed to provide animal-appropriate health management and to enable users to respond quickly and appropriately.

[0468] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0469] Step 1:

[0470] The server receives biometric information via Bluetooth communication from wearable devices attached to animals. It receives data such as heart rate, body temperature, and activity levels as input and records them in a database in real time. If the connection to the device is lost, it attempts to reconnect and constantly monitors the connection status. The output is a collection of organized biometric information.

[0471] Step 2:

[0472] The server analyzes the received biometric data and detects abnormal values. The input is the biometric data received in step 1. During the analysis process, an alert flag is set if the heart rate or body temperature exceeds the standard value. The output is the analysis result, which includes information on whether an abnormality was detected.

[0473] Step 3:

[0474] The server generates a three-dimensional digital model of an animal based on its biological information and analysis results. The input is the analyzed biological information and the analysis results at that time. Using computer graphics (CG) technology, the server reproduces the animal's appearance and movements in real time, particularly highlighting abnormal behaviors. The output is a three-dimensional model that can be updated in real time.

[0475] Step 4:

[0476] The terminal receives a 3D model and analysis results sent from the server. The input consists of 3D model data and analysis results generated by the server. The terminal uses AR or VR to visually display the model, allowing the user to interact with it and check the animal's health status from various viewpoints. The output consists of the visualized 3D model and warning displays in case of abnormalities.

[0477] Step 5:

[0478] The user monitors the animal's health based on a three-dimensional model and analysis results displayed on the terminal. Inputs are the information and analysis results presented on the terminal. Based on the information reviewed, the user decides on the animal's care and management methods. Outputs are specific care and management actions for the animal.

[0479] Step 6:

[0480] The server uses a generative AI model based on historical data to generate an optimal exercise plan for the animal. The input consists of the animal's past health data and user prompts. The AI ​​model generates an appropriate exercise plan based on the animal's age and health condition, and the output is the exercise plan data.

[0481] Step 7:

[0482] The terminal receives the exercise plan from the server and notifies the user. The input is the exercise plan generated by the server. The exercise plan is displayed on the terminal screen and provided in a format that is easy for the user to understand. The output is a display of the exercise plan that the user can easily follow.

[0483] Step 8:

[0484] The user guides the animal's exercise based on the provided exercise plan and provides feedback to the server on the results and problems encountered. Inputs include the animal's responses and results during exercise, as well as the user's observations. Based on this feedback, the server further optimizes the next exercise plan. Output is the feedback information.

[0485] (Application Example 1)

[0486] Next, we will explain Application Example 1. In the following explanation, 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."

[0487] Efficiently monitoring the health and activity of animals, and responding immediately when abnormalities occur, is a challenge in animal safety management. Especially in environments where multiple animals need to be monitored simultaneously, such as zoos and farms, rapid information gathering and notification systems for abnormal situations are essential.

[0488] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0489] In this invention, the server includes means for storing data received from a device for acquiring biological information, means for generating a three-dimensional model of an organism based on the data, means for displaying the three-dimensional model through augmented reality or virtual reality, means for comparing the data and model with predictive data to detect anomalies, and means for notifying a notification terminal of the detected anomaly. This makes it possible to immediately detect abnormal movements or health conditions of animals and to take appropriate action quickly.

[0490] A "device for acquiring biometric information" is a device designed to measure and collect biometric data from animals, such as heart rate, body temperature, and activity level.

[0491] A "three-dimensional model" is a digital representation that visualizes the appearance and movement of an animal in three dimensions, and is usually generated using computer graphics technology.

[0492] Augmented reality or virtual reality refers to technologies that overlay digital information onto a physical reality environment or technologies that create a completely virtual environment.

[0493] "Predictive data" refers to reference information used to predict specific anomalies based on data collected in the past.

[0494] "Means of notifying a notification terminal" refers to a method of sending information about an anomaly to a device accessible to the user to alert them.

[0495] This invention is an integrated monitoring system that enables immediate detection of abnormalities in animals and appropriate responses. This system is mainly composed of four core components: a biometric information collection device, a server, a notification terminal, and a user.

[0496] The server receives data via Bluetooth from a device that acquires biometric information. This device is equipped with a heart rate monitor, temperature sensor, and other sensors, and accumulates data tailored to the individual characteristics of each animal. The server then analyzes the received data and generates a three-dimensional model based on the animal's health status. Computer graphics technology such as Unity is used to generate this model, reproducing the animal's three-dimensional appearance and movements.

[0497] The terminal displays this three-dimensional model in augmented reality or virtual reality format, allowing the user to intuitively understand the animal's posture and activity. The system further detects anomalies by comparing them with previously collected predictive data and immediately notifies the notification terminal of the results. This allows the user to detect animal abnormalities in a timely manner and take prompt action.

[0498] As a concrete example, consider its use in a zoo. Suppose this system detects that one elephant is moving around more than usual at night. The server identifies this as an anomaly and notifies a terminal, allowing staff to quickly go to the scene. This significantly contributes to monitoring the animals' health and improving the safety of the facility.

[0499] An example of a prompt might be: "Design a system that detects abnormal behavior and provides real-time notifications based on animal biometric data and time-series data of its movements." Using this prompt, the generative AI model can support system development.

[0500] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0501] Step 1:

[0502] The server receives biometric data such as heart rate, body temperature, and activity level from biometric acquisition devices via Bluetooth. The input is the wearable device, and the output is the data stored in a database on the server. At this time, the data is timestamped, enabling real-time monitoring.

[0503] Step 2:

[0504] The server generates three-dimensional models of animals based on accumulated biometric data. The input is biometric data stored in a database, and the output is a three-dimensional model generated using Unity. The processing accurately reproduces the animal's body shape and movements.

[0505] Step 3:

[0506] The terminal displays a 3D model generated on the server using augmented or virtual reality. The input is 3D model data, and the output is a visual representation on the user's terminal. The terminal uses this information to allow the user to intuitively check the animal's health status and behavior.

[0507] Step 4:

[0508] The server detects anomalies in biometric data by comparing it with historical predictive data. The input is real-time biometric data and predictive data, and the output is the anomaly detection result. This uses a machine learning model to identify patterns of abnormal behavior.

[0509] Step 5:

[0510] If an anomaly is detected, the server immediately notifies the notification terminal. The input is the anomaly detection result, and the output is a notification message to the user. The terminal receives this notification and promptly alerts the user by displaying a warning or alert.

[0511] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0512] This invention relates to a system that comprehensively analyzes animal health management and user emotions to improve interaction with pets, and a specific embodiment thereof is described below. This system mainly consists of a wearable device, a server that analyzes biometric information, a terminal that displays the information, and an emotion engine that identifies the user's emotions.

[0513] First, the server receives biometric data in real time from wearable devices attached to the pet via Bluetooth or Wi-Fi. This data includes the pet's heart rate, body temperature, and activity level, and is immediately recorded in a database.

[0514] Next, the server analyzes the received data and assesses the pet's current health status. This process includes an anomaly detection algorithm that can quickly identify values ​​outside the normal range. The analysis results are used to generate a three-dimensional model of the animal as a digital twin, which the server then transmits to the terminal.

[0515] The device displays the received 3D model on an augmented reality (AR) or virtual reality (VR) platform, allowing users to visually check the animal's health status. This enables users to intuitively understand their pet's behavior and health indicators.

[0516] Furthermore, the system incorporates an emotion engine that recognizes the user's emotions. The device is equipped with a camera and microphone, and the emotion engine analyzes the user's facial expressions and tone of voice from this input data to determine the user's mental state. For example, if the user is worried about their pet's condition, the emotion engine will sense this and adjust the system to provide more detailed information about the pet's health.

[0517] The emotional data obtained by the emotion engine is also used to adjust the pet's exercise plan. The server dynamically changes the exercise plan according to the user's emotional state, working to improve satisfaction for both the user and the pet. The user can then exercise and manage their pet's health based on this plan and provide the results as feedback to the system.

[0518] In this form, the present invention is expected to enable deeper and more efficient pet health management and user interaction, thereby supporting the development of a good relationship between pets and their owners.

[0519] The following describes the processing flow.

[0520] Step 1:

[0521] The server receives biometric information from the wearable device via Bluetooth. This information includes heart rate, body temperature, and activity level, and this data is recorded in a database.

[0522] Step 2:

[0523] The server analyzes recorded biometric data to assess the pet's health. Anomaly detection algorithms are used to identify data that exceeds normal limits. Detected anomalies are categorized into separate datasets to facilitate rapid response.

[0524] Step 3:

[0525] The server generates a three-dimensional model based on the analyzed data, visualizing the pet's current health status. The generated model is dynamically rendered using a three-dimensional graphics engine.

[0526] Step 4:

[0527] The device receives a 3D model and health information transmitted from the server and displays it in an augmented reality (AR) or virtual reality (VR) environment. This display allows the user to monitor the pet's movements and health status in real time.

[0528] Step 5:

[0529] The device uses its built-in camera and microphone to activate an emotion engine that analyzes the user's facial expressions and voice. The emotion engine infers the user's emotional state from this data and sends it to the server.

[0530] Step 6:

[0531] The server dynamically adjusts the pet's exercise plan based on data received from the emotion engine. During this process, an algorithm is applied that modifies the frequency and content of exercise to reflect the user's emotions.

[0532] Step 7:

[0533] The device displays a customized exercise plan to the user and provides specific action guidelines. The user interacts with their pet according to the displayed exercise plan.

[0534] Step 8:

[0535] Users provide feedback by entering the results of their interaction with their pet into their device. This feedback is then sent back to the server and used for subsequent data analysis and exercise plan generation.

[0536] This process facilitates the smooth provision of pet health management and exercise plans based on user emotions, optimizing interaction with pets.

[0537] (Example 2)

[0538] Next, we will describe Example 2. 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."

[0539] Conventional animal health management systems have faced challenges in real-time monitoring of animal biometric information and in implementing dynamic interactions to improve the relationship between users and animals. In particular, the optimization of interactions with animals that take user emotions into consideration has been insufficient, limiting the improvement of the user experience.

[0540] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0541] In this invention, the server includes means for recording information received from a device for acquiring biological information, means for generating a three-dimensional digital representation of an animal based on the information, means for displaying the three-dimensional digital representation through augmented reality or virtual reality, and emotion analysis means for recognizing the user's emotions and using this information to improve interaction with the animal. This enables real-time monitoring of biological information and optimization of dynamic interactions based on user emotions.

[0542] A "biological information acquisition device" is a device that acquires biological data such as heart rate, body temperature, and activity level from animals.

[0543] "Means of recording" refers to a system or process for storing received biometric data periodically or in real time.

[0544] "Three-dimensional digital representation" refers to a digital model that visualizes and reproduces the health condition of an animal in three dimensions.

[0545] Augmented reality and virtual reality are technologies that use digital information to present information in real or virtual environments.

[0546] "User emotion recognition" is the process of analyzing a user's facial expressions and tone of voice to determine their mental state.

[0547] A "emotion analysis tool" is a system that estimates the user's emotions and adjusts the interaction with animals accordingly.

[0548] An "exercise plan" is a schedule or program of exercise aimed at maintaining the animal's health and improving its interaction with the user.

[0549] "Dynamic adjustment" refers to the act or ability to modify plans or processes in real time or at near time intervals in response to circumstances.

[0550] To implement this invention, a specific hardware configuration and software process are required. This system consists of a wearable device, a server for analyzing biometric information, a terminal for displaying the information, and an emotion engine for identifying the user's emotions.

[0551] The server receives biometric data in real time via Bluetooth or Wi-Fi from wearable devices attached to animals. These devices are equipped with sensors for heart rate, body temperature, and other metrics, and the data is immediately recorded in a database on the server. The server then analyzes the data and uses anomaly detection algorithms to assess the pet's health. The detected information is generated on the server as a three-dimensional digital representation of the animal, which is then transmitted to the terminal.

[0552] The device receives digital representations transmitted from the server and displays them on an augmented reality (AR) or virtual reality (VR) platform. This feature allows users to intuitively understand their pet's health status. The device also includes an emotion engine that analyzes the user's facial expressions and voice through the camera and microphone to recognize emotions. Based on this information, the server dynamically adjusts exercise plans and health information to ensure the user feels at ease.

[0553] For example, if a user is worried about their pet while concentrating on work, the emotion engine will sense the user's concern, and the server will request the generative AI model to "suggest the best way for the user to interact with their pet to help them relax."

[0554] In this configuration, the system can perform advanced animal health management and enrich the user experience.

[0555] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0556] Step 1:

[0557] The server receives biometric data from wearable devices via Bluetooth or Wi-Fi. Inputs include biometric information such as heart rate, body temperature, and activity level. The server receives this data and immediately records it in a database. This process outputs the foundational data necessary for subsequent analysis.

[0558] Step 2:

[0559] The server analyzes the recorded biometric data and evaluates the animal's health status. The input includes the biometric data obtained in step 1, and an anomaly detection algorithm identifies data outside the normal range. The output generates a health assessment result, and an anomaly alert is issued as needed.

[0560] Step 3:

[0561] The server generates a three-dimensional digital representation of the animal based on the analysis results. The health assessment results obtained in Step 2 serve as input. This digital representation provides an output that reproduces the animal's current health status and behavior in real time. The created model is designed to be easily understood visually.

[0562] Step 4:

[0563] The server transmits a three-dimensional digital representation to the terminal. The three-dimensional model generated in step 3 is used as input. The terminal receives this output model and uses it in the next display step.

[0564] Step 5:

[0565] The device displays the received three-dimensional digital representation on an augmented reality (AR) or virtual reality (VR) platform. Input includes a digital model transmitted from a server, and output is provided that allows the user to visually check the pet's health status. Through this, the user can intuitively understand the pet's condition.

[0566] Step 6:

[0567] The device uses its camera and microphone to capture the user's facial expressions and voice tone. The input includes real-time user data. The emotion engine analyzes this data and generates an output that determines the user's psychological state. This enables responses based on the user's emotions.

[0568] Step 7:

[0569] The server generates and dynamically adjusts an exercise plan using the analysis results from the emotion engine. Inputs include the user's emotional state obtained in step 6 and the health assessment from step 2. The generating AI model provides an output suggesting the necessary exercise plan based on the prompt "Suggest the optimal way for the user to interact with their pet to relax." This plan improves the satisfaction of both the pet and the user.

[0570] (Application Example 2)

[0571] Next, we will explain application example 2. In the following explanation, 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."

[0572] In conventional factory work environments, it is difficult to understand the psychological state of workers in real time and provide appropriate support for their work, making improvements in safety and work efficiency a challenge. Furthermore, there is a need to reduce worker stress and provide an environment where workers can work with peace of mind.

[0573] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0574] In this invention, the server includes means for recording data received from a device for acquiring biological information, means for generating a three-dimensional model of an animal based on the data, means for displaying the three-dimensional model through augmented reality or virtual reality, means for analyzing the psychological state of a person in the workplace, and means for adjusting work assistance based on the psychological state. This makes it possible to analyze the psychological state of a worker in real time and provide appropriate work assistance.

[0575] "Biometric information" refers to data that indicates the physical state of animals and humans, such as heart rate, body temperature, and activity level.

[0576] A "three-dimensional model" is a digital model that represents the shape of an object or living organism in three-dimensional space.

[0577] Augmented reality is a technology that overlays virtual information onto images of the real world.

[0578] "Virtual reality" is a technology that allows users to immerse themselves in a computer-generated three-dimensional space and experience an artificially created environment.

[0579] "Psychological state" refers to the state of a person's consciousness and emotions, and includes factors such as stress levels and relaxation levels.

[0580] "Work assistance" refers to support and assistance provided to ensure that work is performed efficiently and safely.

[0581] "Analysis" is the process of examining data to extract information and deepen understanding.

[0582] To realize this invention, it is necessary to develop a system that monitors the work environment within a factory, analyzes the psychological state of workers, and provides work support based on that analysis. For this purpose, the following hardware and software are recommended.

[0583] First, the server receives data from a device that acquires biometric information and records that data in real time. This uses wearable devices that acquire data using Bluetooth or Wi-Fi. The received data includes heart rate, body temperature, and other similar information.

[0584] Next, based on the received biometric data, the server generates a three-dimensional model of the animal. This model undergoes motion analysis using OpenCV and other tools, and also performs emotion analysis using a machine learning model with TensorFlow.

[0585] The terminal is equipped with a function to display the aforementioned three-dimensional model in an augmented reality or virtual reality environment. This allows users to visually check the health status of animals and the psychological state of workers. The terminal is equipped with a camera and microphone, and analyzes the worker's facial expressions and voice to determine their psychological state.

[0586] Furthermore, the system incorporates a function that adjusts work assistance based on the user's psychological state. For example, if a worker is experiencing excessive stress, the software will automatically play relaxing music. It can also suggest necessary breaks by displaying warning messages on the screen.

[0587] For example, if the system detects that a worker is concentrating on a task for an extended period, it analyzes the situation, displays a message such as "Please consider pausing your work," and plays soothing music in the background.

[0588] An example of a prompt message might be: "Determine the emotions of the workers from the facial images input to the image data analysis model and monitor their stress levels in real time. Based on the results, decide whether to automatically play relaxing music." This can reduce the psychological burden on workers and provide a more efficient work environment.

[0589] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0590] Step 1:

[0591] The server receives data via Bluetooth or Wi-Fi from a device that acquires biometric information. This data includes heart rate and body temperature, and the server records this as input in a database. This enables real-time, continuous monitoring.

[0592] Step 2:

[0593] The server analyzes received biometric data and generates a three-dimensional model of the animal or worker. The input is biometric data, and the output is a three-dimensional model. OpenCV is used to analyze the motion and build a model for visualizing each data point.

[0594] Step 3:

[0595] The device displays the generated three-dimensional model in an augmented reality or virtual reality environment. Here, it receives a three-dimensional model as input and outputs a visual AR / VR display. This display allows the user to intuitively check their health status and movements.

[0596] Step 4:

[0597] The server analyzes the psychological state of the worker using facial and audio data acquired via the terminal's camera and microphone. The input consists of visual and audio data, and the output is an index of the analyzed psychological state. TensorFlow is used to analyze emotions from this data.

[0598] Step 5:

[0599] The server adjusts work assistance based on the analyzed psychological state. Inputs include indicators of psychological state, and outputs include playing relaxing music or displaying warning messages on the screen. Specifically, it automatically selects appropriate actions and provides feedback to the user.

[0600] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0601] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0602] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0603] [Fourth Embodiment]

[0604] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0605] As shown in Figure 7, the 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.

[0606] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0607] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0608] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0609] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0610] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0611] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0612] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0613] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0614] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0615] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0616] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0617] This invention relates to an animal health management system, and specific embodiments are described below. This system is mainly operated using a wearable device, a server that analyzes biometric information, a terminal that receives and displays information, and a user.

[0618] First, the server receives biometric information via Bluetooth from a wearable device attached to the animal. This device measures important health indicators such as heart rate, body temperature, and activity level. The received data is stored in the server's database in real time, including a timestamp at the time of each measurement.

[0619] Next, the server generates a three-dimensional model of the animal based on the collected data. This model generation uses computer graphics (CG) technology to faithfully reproduce the animal's appearance and movements, employing algorithms designed to instantly identify any abnormal behavior or conditions.

[0620] This three-dimensional model is displayed via augmented reality (AR) or virtual reality (VR) media depending on the device. Users can view this 3D model using devices such as smartphones and tablets, and intuitively understand the animal's movements and health condition.

[0621] In addition to displaying the model, the device also presents the data analysis results sent from the server. This allows the user to receive real-time notifications about the animal's health status, and any abnormalities detected are immediately presented as alarms. For example, if a pet's body temperature exceeds the standard range, the device warns the user by displaying it in red.

[0622] Furthermore, the server has a function that analyzes past data and uses artificial intelligence (AI) to generate an optimal exercise plan for each individual animal. This AI automatically creates a training plan based on the animal's age, weight, and health information, and sends it to the terminal. The user can manage the animal's exercise and activity based on the received training plan and provide feedback on the results to the server.

[0623] In this way, the system comprehensively manages the health status of animals and helps users quickly understand their pets' health and provide appropriate care. This embodiment can effectively solve the various problems associated with pet care.

[0624] The following describes the processing flow.

[0625] Step 1:

[0626] The server periodically receives data from the wearable device via Bluetooth. This data includes the pet's heart rate, body temperature, and activity level. The received data is instantly stored in a database, and each data entry is timestamped.

[0627] Step 2:

[0628] The server performs analysis to assess the pet's health status based on the stored data. By using anomaly detection algorithms to identify data that deviates from the pet's normal health patterns, it enables real-time monitoring of the pet's health status.

[0629] Step 3:

[0630] The server uses the analyzed data to generate or update a three-dimensional model of the pet. Using computer graphics (CG) technology, the model faithfully reproduces the animal's appearance and movements, and visually highlights any abnormalities that may be detected.

[0631] Step 4:

[0632] The server sends the updated 3D model and health assessment results to the terminal. The data sent here also includes detailed information about the pet's recent health status.

[0633] Step 5:

[0634] The device displays a model of the pet in an augmented reality (AR) or virtual reality (VR) environment based on the received 3D model and health data. Through the application, users can view real-time visual feedback on the pet's movements and health.

[0635] Step 6:

[0636] The device will display alerts to the user if any abnormalities or warnings are generated. For example, if a pet's body temperature rises rapidly, a red warning will be displayed on the device screen.

[0637] Step 7:

[0638] The server analyzes collected historical data and uses AI to generate the optimal training plan for your pet. This plan is tailored based on the pet's age, health condition, and past activity level.

[0639] Step 8:

[0640] The server sends the generated training plan to the terminal. The terminal presents the plan to the user through the application and provides specific instructions for execution.

[0641] Step 9:

[0642] Users can use their devices to implement training plans and check their pet's reactions and progress. They can also send feedback to the server after implementation, which is used to generate future training plans.

[0643] (Example 1)

[0644] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0645] For pet owners, quickly and accurately understanding their animals' health is a crucial concern. However, conventional health management systems have struggled to detect abnormal health conditions early and respond appropriately. Furthermore, the automatic generation of exercise plans optimized for individual animals has been insufficient. Therefore, there is a need for a means to monitor and analyze animals' health in real time.

[0646] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0647] In this invention, the server includes means for recording information received from a device for acquiring biological information, means for generating a three-dimensional shape of an animal based on the information, means for displaying the three-dimensional shape through visualization technology, and means for analyzing the information and setting an anomaly detection flag. This makes it possible to monitor the health status of animals in real time and to quickly warn if an anomaly is detected. Furthermore, it enables the automatic generation of an optimal exercise plan for each individual animal, thereby achieving more effective health management.

[0648] "Biometric information" refers to data that indicates an animal's health status, such as heart rate, body temperature, and activity level.

[0649] A "device" is a piece of equipment attached to an animal to acquire biological information.

[0650] "Means of recording" refers to methods or devices for storing received biological information.

[0651] "Information" refers to data such as biometric measurements and analysis results obtained from the device.

[0652] A "three-dimensional shape" is a three-dimensional digital model created to reproduce the posture and movement of an animal.

[0653] "Means of generation" refers to processes and devices for analyzing biological information to create three-dimensional digital models.

[0654] "Visualization technology" refers to the technology of displaying three-dimensional digital models using augmented reality (AR) or virtual reality (VR) methods.

[0655] "Means of analysis" refer to methods and devices for evaluating biological information and detecting abnormal values ​​or diagnosing health conditions.

[0656] An "anomaly detection flag" is an indicator set to identify abnormal data or conditions within biometric information.

[0657] To implement this invention, it is necessary for the server, terminals, and users to all cooperate in building an animal health management system.

[0658] The server receives biometric information via Bluetooth from wearable devices attached to animals. These devices can measure health indicators such as heart rate, body temperature, and activity level in real time. The server records the received information in a database and sets an anomaly detection flag as needed. When analyzing the information, algorithms are used to quickly identify abnormal data and conditions.

[0659] Furthermore, the server uses computer graphics (CG) technology to generate a three-dimensional digital model based on the collected information. This model faithfully reproduces the animal's actual appearance and movements. The generated three-dimensional model is useful for simulating abnormalities or the animal's movements as needed.

[0660] The terminal receives 3D models and analysis results from the server and displays them to the user. The terminal successfully uses AR and VR technology to display the models, helping users intuitively understand the animal's health status. The terminal also provides visual and audible alerts based on anomaly detection, ensuring users receive timely information.

[0661] Users can monitor the animal's health and provide appropriate care based on information provided through their device. They can also review exercise plans generated by the server and plan actions to maintain the animal's health. Specifically, users can receive an appropriate exercise plan from the generating AI model by entering prompts such as "Tell me the appropriate amount of exercise."

[0662] In this way, this invention provides a series of technical means for the comprehensive management of animal health. It is designed to provide animal-appropriate health management and to enable users to respond quickly and appropriately.

[0663] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0664] Step 1:

[0665] The server receives biometric information via Bluetooth communication from wearable devices attached to animals. It receives data such as heart rate, body temperature, and activity levels as input and records them in a database in real time. If the connection to the device is lost, it attempts to reconnect and constantly monitors the connection status. The output is a collection of organized biometric information.

[0666] Step 2:

[0667] The server analyzes the received biometric data and detects abnormal values. The input is the biometric data received in step 1. During the analysis process, an alert flag is set if the heart rate or body temperature exceeds the standard value. The output is the analysis result, which includes information on whether an abnormality was detected.

[0668] Step 3:

[0669] The server generates a three-dimensional digital model of an animal based on its biological information and analysis results. The input is the analyzed biological information and the analysis results at that time. Using computer graphics (CG) technology, the server reproduces the animal's appearance and movements in real time, particularly highlighting abnormal behaviors. The output is a three-dimensional model that can be updated in real time.

[0670] Step 4:

[0671] The terminal receives a 3D model and analysis results sent from the server. The input consists of 3D model data and analysis results generated by the server. The terminal uses AR or VR to visually display the model, allowing the user to interact with it and check the animal's health status from various viewpoints. The output consists of the visualized 3D model and warning displays in case of abnormalities.

[0672] Step 5:

[0673] The user monitors the animal's health based on a three-dimensional model and analysis results displayed on the terminal. Inputs are the information and analysis results presented on the terminal. Based on the information reviewed, the user decides on the animal's care and management methods. Outputs are specific care and management actions for the animal.

[0674] Step 6:

[0675] The server uses a generative AI model based on historical data to generate an optimal exercise plan for the animal. The input consists of the animal's past health data and user prompts. The AI ​​model generates an appropriate exercise plan based on the animal's age and health condition, and the output is the exercise plan data.

[0676] Step 7:

[0677] The terminal receives the exercise plan from the server and notifies the user. The input is the exercise plan generated by the server. The exercise plan is displayed on the terminal screen and provided in a format that is easy for the user to understand. The output is a display of the exercise plan that the user can easily follow.

[0678] Step 8:

[0679] The user guides the animal's exercise based on the provided exercise plan and provides feedback to the server on the results and problems encountered. Inputs include the animal's responses and results during exercise, as well as the user's observations. Based on this feedback, the server further optimizes the next exercise plan. Output is the feedback information.

[0680] (Application Example 1)

[0681] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0682] Efficiently monitoring the health and activity of animals, and responding immediately when abnormalities occur, is a challenge in animal safety management. Especially in environments where multiple animals need to be monitored simultaneously, such as zoos and farms, rapid information gathering and notification systems for abnormal situations are essential.

[0683] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0684] In this invention, the server includes means for storing data received from a device for acquiring biological information, means for generating a three-dimensional model of an organism based on the data, means for displaying the three-dimensional model through augmented reality or virtual reality, means for comparing the data and model with predictive data to detect anomalies, and means for notifying a notification terminal of the detected anomaly. This makes it possible to immediately detect abnormal movements or health conditions of animals and to take appropriate action quickly.

[0685] A "device for acquiring biometric information" is a device designed to measure and collect biometric data from animals, such as heart rate, body temperature, and activity level.

[0686] A "three-dimensional model" is a digital representation that visualizes the appearance and movement of an animal in three dimensions, and is usually generated using computer graphics technology.

[0687] Augmented reality or virtual reality refers to technologies that overlay digital information onto a physical reality environment or technologies that create a completely virtual environment.

[0688] "Predictive data" refers to reference information used to predict specific anomalies based on data collected in the past.

[0689] "Means of notifying a notification terminal" refers to a method of sending information about an anomaly to a device accessible to the user to alert them.

[0690] This invention is an integrated monitoring system that enables immediate detection of abnormalities in animals and appropriate responses. This system is mainly composed of four core components: a biometric information collection device, a server, a notification terminal, and a user.

[0691] The server receives data via Bluetooth from a device that acquires biometric information. This device is equipped with a heart rate monitor, temperature sensor, and other sensors, and accumulates data tailored to the individual characteristics of each animal. The server then analyzes the received data and generates a three-dimensional model based on the animal's health status. Computer graphics technology such as Unity is used to generate this model, reproducing the animal's three-dimensional appearance and movements.

[0692] The terminal displays this three-dimensional model in augmented reality or virtual reality format, allowing the user to intuitively understand the animal's posture and activity. The system further detects anomalies by comparing them with previously collected predictive data and immediately notifies the notification terminal of the results. This allows the user to detect animal abnormalities in a timely manner and take prompt action.

[0693] As a concrete example, consider its use in a zoo. Suppose this system detects that one elephant is moving around more than usual at night. The server identifies this as an anomaly and notifies a terminal, allowing staff to quickly go to the scene. This significantly contributes to monitoring the animals' health and improving the safety of the facility.

[0694] An example of a prompt might be: "Design a system that detects abnormal behavior and provides real-time notifications based on animal biometric data and time-series data of its movements." Using this prompt, the generative AI model can support system development.

[0695] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0696] Step 1:

[0697] The server receives biometric data such as heart rate, body temperature, and activity level from biometric acquisition devices via Bluetooth. The input is the wearable device, and the output is the data stored in a database on the server. At this time, the data is timestamped, enabling real-time monitoring.

[0698] Step 2:

[0699] The server generates three-dimensional models of animals based on accumulated biometric data. The input is biometric data stored in a database, and the output is a three-dimensional model generated using Unity. The processing accurately reproduces the animal's body shape and movements.

[0700] Step 3:

[0701] The terminal displays a 3D model generated on the server using augmented or virtual reality. The input is 3D model data, and the output is a visual representation on the user's terminal. The terminal uses this information to allow the user to intuitively check the animal's health status and behavior.

[0702] Step 4:

[0703] The server detects anomalies in biometric data by comparing it with historical predictive data. The input is real-time biometric data and predictive data, and the output is the anomaly detection result. This uses a machine learning model to identify patterns of abnormal behavior.

[0704] Step 5:

[0705] If an anomaly is detected, the server immediately notifies the notification terminal. The input is the anomaly detection result, and the output is a notification message to the user. The terminal receives this notification and promptly alerts the user by displaying a warning or alert.

[0706] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0707] This invention relates to a system that comprehensively analyzes animal health management and user emotions to improve interaction with pets, and a specific embodiment thereof is described below. This system mainly consists of a wearable device, a server that analyzes biometric information, a terminal that displays the information, and an emotion engine that identifies the user's emotions.

[0708] First, the server receives biometric data in real time from wearable devices attached to the pet via Bluetooth or Wi-Fi. This data includes the pet's heart rate, body temperature, and activity level, and is immediately recorded in a database.

[0709] Next, the server analyzes the received data and assesses the pet's current health status. This process includes an anomaly detection algorithm that can quickly identify values ​​outside the normal range. The analysis results are used to generate a three-dimensional model of the animal as a digital twin, which the server then transmits to the terminal.

[0710] The device displays the received 3D model on an augmented reality (AR) or virtual reality (VR) platform, allowing users to visually check the animal's health status. This enables users to intuitively understand their pet's behavior and health indicators.

[0711] Furthermore, the system incorporates an emotion engine that recognizes the user's emotions. The device is equipped with a camera and microphone, and the emotion engine analyzes the user's facial expressions and tone of voice from this input data to determine the user's mental state. For example, if the user is worried about their pet's condition, the emotion engine will sense this and adjust the system to provide more detailed information about the pet's health.

[0712] The emotional data obtained by the emotion engine is also used to adjust the pet's exercise plan. The server dynamically changes the exercise plan according to the user's emotional state, working to improve satisfaction for both the user and the pet. The user can then exercise and manage their pet's health based on this plan and provide the results as feedback to the system.

[0713] In this form, the present invention is expected to enable deeper and more efficient pet health management and user interaction, thereby supporting the development of a good relationship between pets and their owners.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] The server receives biometric information from the wearable device via Bluetooth. This information includes heart rate, body temperature, and activity level, and this data is recorded in a database.

[0717] Step 2:

[0718] The server analyzes recorded biometric data to assess the pet's health. Anomaly detection algorithms are used to identify data that exceeds normal limits. Detected anomalies are categorized into separate datasets to facilitate rapid response.

[0719] Step 3:

[0720] The server generates a three-dimensional model based on the analyzed data, visualizing the pet's current health status. The generated model is dynamically rendered using a three-dimensional graphics engine.

[0721] Step 4:

[0722] The device receives a 3D model and health information transmitted from the server and displays it in an augmented reality (AR) or virtual reality (VR) environment. This display allows the user to monitor the pet's movements and health status in real time.

[0723] Step 5:

[0724] The device uses its built-in camera and microphone to activate an emotion engine that analyzes the user's facial expressions and voice. The emotion engine infers the user's emotional state from this data and sends it to the server.

[0725] Step 6:

[0726] The server dynamically adjusts the pet's exercise plan based on data received from the emotion engine. During this process, an algorithm is applied that modifies the frequency and content of exercise to reflect the user's emotions.

[0727] Step 7:

[0728] The device displays a customized exercise plan to the user and provides specific action guidelines. The user interacts with their pet according to the displayed exercise plan.

[0729] Step 8:

[0730] Users provide feedback by entering the results of their interaction with their pet into their device. This feedback is then sent back to the server and used for subsequent data analysis and exercise plan generation.

[0731] This process facilitates the smooth provision of pet health management and exercise plans based on user emotions, optimizing interaction with pets.

[0732] (Example 2)

[0733] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0734] Conventional animal health management systems have faced challenges in real-time monitoring of animal biometric information and in implementing dynamic interactions to improve the relationship between users and animals. In particular, the optimization of interactions with animals that take user emotions into consideration has been insufficient, limiting the improvement of the user experience.

[0735] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0736] In this invention, the server includes means for recording information received from a device for acquiring biological information, means for generating a three-dimensional digital representation of an animal based on the information, means for displaying the three-dimensional digital representation through augmented reality or virtual reality, and emotion analysis means for recognizing the user's emotions and using this information to improve interaction with the animal. This enables real-time monitoring of biological information and optimization of dynamic interactions based on user emotions.

[0737] A "biological information acquisition device" is a device that acquires biological data such as heart rate, body temperature, and activity level from animals.

[0738] "Means of recording" refers to a system or process for storing received biometric data periodically or in real time.

[0739] "Three-dimensional digital representation" refers to a digital model that visualizes and reproduces the health condition of an animal in three dimensions.

[0740] Augmented reality and virtual reality are technologies that use digital information to present information in real or virtual environments.

[0741] "User emotion recognition" is the process of analyzing a user's facial expressions and tone of voice to determine their mental state.

[0742] A "emotion analysis tool" is a system that estimates the user's emotions and adjusts the interaction with animals accordingly.

[0743] An "exercise plan" is a schedule or program of exercise aimed at maintaining the animal's health and improving its interaction with the user.

[0744] "Dynamic adjustment" refers to the act or ability to modify plans or processes in real time or at near time intervals in response to circumstances.

[0745] To implement this invention, a specific hardware configuration and software process are required. This system consists of a wearable device, a server for analyzing biometric information, a terminal for displaying the information, and an emotion engine for identifying the user's emotions.

[0746] The server receives biometric data in real time via Bluetooth or Wi-Fi from wearable devices attached to animals. These devices are equipped with sensors for heart rate, body temperature, and other metrics, and the data is immediately recorded in a database on the server. The server then analyzes the data and uses anomaly detection algorithms to assess the pet's health. The detected information is generated on the server as a three-dimensional digital representation of the animal, which is then transmitted to the terminal.

[0747] The device receives digital representations transmitted from the server and displays them on an augmented reality (AR) or virtual reality (VR) platform. This feature allows users to intuitively understand their pet's health status. The device also includes an emotion engine that analyzes the user's facial expressions and voice through the camera and microphone to recognize emotions. Based on this information, the server dynamically adjusts exercise plans and health information to ensure the user feels at ease.

[0748] For example, if a user is worried about their pet while concentrating on work, the emotion engine will sense the user's concern, and the server will request the generative AI model to "suggest the best way for the user to interact with their pet to help them relax."

[0749] In this configuration, the system can perform advanced animal health management and enrich the user experience.

[0750] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0751] Step 1:

[0752] The server receives biometric data from wearable devices via Bluetooth or Wi-Fi. Inputs include biometric information such as heart rate, body temperature, and activity level. The server receives this data and immediately records it in a database. This process outputs the foundational data necessary for subsequent analysis.

[0753] Step 2:

[0754] The server analyzes the recorded biometric data and evaluates the animal's health status. The input includes the biometric data obtained in step 1, and an anomaly detection algorithm identifies data outside the normal range. The output generates a health assessment result, and an anomaly alert is issued as needed.

[0755] Step 3:

[0756] The server generates a three-dimensional digital representation of the animal based on the analysis results. The health assessment results obtained in Step 2 serve as input. This digital representation provides an output that reproduces the animal's current health status and behavior in real time. The created model is designed to be easily understood visually.

[0757] Step 4:

[0758] The server transmits a three-dimensional digital representation to the terminal. The three-dimensional model generated in step 3 is used as input. The terminal receives this output model and uses it in the next display step.

[0759] Step 5:

[0760] The device displays the received three-dimensional digital representation on an augmented reality (AR) or virtual reality (VR) platform. Input includes a digital model transmitted from a server, and output is provided that allows the user to visually check the pet's health status. Through this, the user can intuitively understand the pet's condition.

[0761] Step 6:

[0762] The device uses its camera and microphone to capture the user's facial expressions and voice tone. The input includes real-time user data. The emotion engine analyzes this data and generates an output that determines the user's psychological state. This enables responses based on the user's emotions.

[0763] Step 7:

[0764] The server generates and dynamically adjusts an exercise plan using the analysis results from the emotion engine. Inputs include the user's emotional state obtained in step 6 and the health assessment from step 2. The generating AI model provides an output suggesting the necessary exercise plan based on the prompt "Suggest the optimal way for the user to interact with their pet to relax." This plan improves the satisfaction of both the pet and the user.

[0765] (Application Example 2)

[0766] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0767] In conventional factory work environments, it is difficult to understand the psychological state of workers in real time and provide appropriate support for their work, making improvements in safety and work efficiency a challenge. Furthermore, there is a need to reduce worker stress and provide an environment where workers can work with peace of mind.

[0768] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0769] In this invention, the server includes means for recording data received from a device for acquiring biological information, means for generating a three-dimensional model of an animal based on the data, means for displaying the three-dimensional model through augmented reality or virtual reality, means for analyzing the psychological state of a person in the workplace, and means for adjusting work assistance based on the psychological state. This makes it possible to analyze the psychological state of a worker in real time and provide appropriate work assistance.

[0770] "Biometric information" refers to data that indicates the physical state of animals and humans, such as heart rate, body temperature, and activity level.

[0771] A "three-dimensional model" is a digital model that represents the shape of an object or living organism in three-dimensional space.

[0772] Augmented reality is a technology that overlays virtual information onto images of the real world.

[0773] "Virtual reality" is a technology that allows users to immerse themselves in a computer-generated three-dimensional space and experience an artificially created environment.

[0774] "Psychological state" refers to the state of a person's consciousness and emotions, and includes factors such as stress levels and relaxation levels.

[0775] "Work assistance" refers to support and assistance provided to ensure that work is performed efficiently and safely.

[0776] "Analysis" is the process of examining data to extract information and deepen understanding.

[0777] To realize this invention, it is necessary to develop a system that monitors the work environment within a factory, analyzes the psychological state of workers, and provides work support based on that analysis. For this purpose, the following hardware and software are recommended.

[0778] First, the server receives data from a device that acquires biometric information and records that data in real time. This uses wearable devices that acquire data using Bluetooth or Wi-Fi. The received data includes heart rate, body temperature, and other similar information.

[0779] Next, based on the received biometric data, the server generates a three-dimensional model of the animal. This model undergoes motion analysis using OpenCV and other tools, and also performs emotion analysis using a machine learning model with TensorFlow.

[0780] The terminal is equipped with a function to display the aforementioned three-dimensional model in an augmented reality or virtual reality environment. This allows users to visually check the health status of animals and the psychological state of workers. The terminal is equipped with a camera and microphone, and analyzes the worker's facial expressions and voice to determine their psychological state.

[0781] Furthermore, the system incorporates a function that adjusts work assistance based on the user's psychological state. For example, if a worker is experiencing excessive stress, the software will automatically play relaxing music. It can also suggest necessary breaks by displaying warning messages on the screen.

[0782] For example, if the system detects that a worker is concentrating on a task for an extended period, it analyzes the situation, displays a message such as "Please consider pausing your work," and plays soothing music in the background.

[0783] An example of a prompt message might be: "Determine the emotions of the workers from the facial images input to the image data analysis model and monitor their stress levels in real time. Based on the results, decide whether to automatically play relaxing music." This can reduce the psychological burden on workers and provide a more efficient work environment.

[0784] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0785] Step 1:

[0786] The server receives data via Bluetooth or Wi-Fi from a device that acquires biometric information. This data includes heart rate and body temperature, and the server records this as input in a database. This enables real-time, continuous monitoring.

[0787] Step 2:

[0788] The server analyzes received biometric data and generates a three-dimensional model of the animal or worker. The input is biometric data, and the output is a three-dimensional model. OpenCV is used to analyze the motion and build a model for visualizing each data point.

[0789] Step 3:

[0790] The device displays the generated three-dimensional model in an augmented reality or virtual reality environment. Here, it receives a three-dimensional model as input and outputs a visual AR / VR display. This display allows the user to intuitively check their health status and movements.

[0791] Step 4:

[0792] The server analyzes the psychological state of the worker using facial and audio data acquired via the terminal's camera and microphone. The input consists of visual and audio data, and the output is an index of the analyzed psychological state. TensorFlow is used to analyze emotions from this data.

[0793] Step 5:

[0794] The server adjusts work assistance based on the analyzed psychological state. Inputs include indicators of psychological state, and outputs include playing relaxing music or displaying warning messages on the screen. Specifically, it automatically selects appropriate actions and provides feedback to the user.

[0795] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0796] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0797] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0798] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0799] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0800] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0801] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0802] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0803] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0804] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0805] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0806] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0807] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0808] 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.

[0809] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0810] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0811] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0812] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0813] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0814] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0815] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0816] The following is further disclosed regarding the embodiments described above.

[0817] (Claim 1)

[0818] A means for recording data received from a device for acquiring biological information,

[0819] A means for generating a three-dimensional model of an animal based on the aforementioned data,

[0820] Means for displaying the three-dimensional model through augmented reality or virtual reality,

[0821] A system that includes this.

[0822] (Claim 2)

[0823] The system according to claim 1, further comprising means for analyzing the aforementioned data and evaluating the health status of the animals.

[0824] (Claim 3)

[0825] The system according to claim 1, further comprising means for generating an exercise plan based on the aforementioned evaluation.

[0826] "Example 1"

[0827] (Claim 1)

[0828] A means for recording information received from a device for acquiring biological information,

[0829] Means for generating the three-dimensional shape of an animal based on the aforementioned information,

[0830] Means for displaying the aforementioned three-dimensional shape through visualization technology,

[0831] A means for analyzing the aforementioned information and setting an anomaly detection flag,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, further comprising means for analyzing the aforementioned information and evaluating the health status of the animals.

[0835] (Claim 3)

[0836] The system according to claim 1, further comprising means for generating an exercise plan for an animal based on the aforementioned evaluation.

[0837] "Application Example 1"

[0838] (Claim 1)

[0839] A means for storing data received from a device for acquiring biometric information,

[0840] A means for generating a three-dimensional model of an organism based on the aforementioned data,

[0841] Means for displaying the three-dimensional model through augmented reality or virtual reality,

[0842] A means for detecting anomalies by comparing the aforementioned data and model with predictive data,

[0843] A means of notifying a notification terminal of the detected anomaly,

[0844] ...

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, further comprising means for analyzing the aforementioned data and comprehensively evaluating the health status and operation of the organism.

[0848] (Claim 3)

[0849] The system according to claim 1, further comprising means for generating an activity plan based on the aforementioned evaluation and transmitting it to an information terminal.

[0850] "Example 2 of combining an emotion engine"

[0851] (Claim 1)

[0852] A means for recording information received from equipment for acquiring biological information,

[0853] A means for generating a three-dimensional digital representation of an animal based on the aforementioned information,

[0854] Means for displaying the aforementioned three-dimensional digital representation through augmented reality or virtual reality,

[0855] A means of emotion analysis for recognizing user emotions and using this information to improve interaction with animals,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, further comprising means for analyzing the aforementioned information and evaluating the health status of the animals.

[0859] (Claim 3)

[0860] The system according to claim 1, further comprising means for generating an exercise plan based on the aforementioned evaluation and dynamically adjusting it in consideration of the user's emotional information.

[0861] "Application example 2 when combining with an emotional engine"

[0862] (Claim 1)

[0863] A means for recording data received from a device for acquiring biological information,

[0864] A means for generating a three-dimensional model of an animal based on the aforementioned data,

[0865] Means for displaying the three-dimensional model through augmented reality or virtual reality,

[0866] A means of analyzing the psychological state of people in the workplace,

[0867] Means for adjusting work assistance based on psychological state,

[0868] A system that includes this.

[0869] (Claim 2)

[0870] The system according to claim 1, further comprising means for analyzing the aforementioned data and evaluating the health status of the animals.

[0871] (Claim 3)

[0872] The system according to claim 1, further comprising means for generating an exercise plan based on the aforementioned evaluation. [Explanation of Symbols]

[0873] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for recording data received from a device for acquiring biological information, A means for generating a three-dimensional model of an animal based on the aforementioned data, Means for displaying the three-dimensional model through augmented reality or virtual reality, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing the aforementioned data and evaluating the health status of the animals.

3. The system according to claim 1, further comprising means for generating an exercise plan based on the aforementioned evaluation.

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