system

Abstract

We provide the system. [Solution] A means for measuring the biological information of a pet and detecting abnormalities based on said biological information, A means for notifying the user of an alert based on the anomaly, A means for automatically generating a pet's nutrition plan based on the said biological information, Automated machines available for use in the home provide a means to collect data in real time and analyze anomalies, Means for providing the nutrition plan to the user, Means for notifying the user using audio output or visual display, A system that includes this.

Description

Technical Field

[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, including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to the description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Although it is important for pet owners to appropriately manage the health status of their pets, it is not easy to do so in the midst of daily busyness. In particular, early detection of pet health problems and formulation of a nutrition plan suitable for the pet are issues that many pet owners face. Also, there is a lack of information that can quickly respond when an abnormality occurs, which is also a problem. There is a need for a system that solves these problems and improves the health and well-being of pets.

Means for Solving the Problems

[0005] This invention solves this problem by providing a means to accurately measure a pet's biological information and detect abnormalities. Based on the detected abnormalities, alerts are sent to the user in real time, enabling a quick response. Furthermore, by automatically generating a nutrition plan based on the pet's biological information and providing that plan to the user, optimal nutritional management for each individual pet is achieved. This reduces the burden on pet owners and enables efficient maintenance of their pets' health.

[0006] The term "pet" refers to all animals kept as pets in a home, including dogs, cats, birds, reptiles, and other similar animals.

[0007] "Biometric information" refers to various physiological data that indicates a pet's health status, such as heart rate, body temperature, and activity level.

[0008] "Measurement" refers to the process of collecting, quantifying, or recording a pet's biological information.

[0009] An "abnormality" refers to a value or condition that deviates from the normal range of biological information, and is an indicator that suggests a potential health problem.

[0010] "Detection" refers to the process of analyzing biological information and identifying and revealing abnormalities within it.

[0011] An "alert" refers to a warning or notification sent to a user based on a detected anomaly.

[0012] A "user" refers to a person who uses this system to manage the health of their pet, primarily the pet owner.

[0013] "Notifying" refers to the act of sending alerts or information to a user's communication device to prompt them to take notice.

[0014] A "nutritional plan" refers to a meal plan that combines the appropriate diet and balance of nutrients for your pet's health condition.

[0015] "To provide" means to make the automatically generated nutrition plan available for the user to view, mainly through digital devices.

Brief Description of the Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of the data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of the data processing device and the smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of the data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of the data processing device and the smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of the data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of the data processing device and the headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of the data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of the data processing device and the robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [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.

Embodiment for Carrying Out the Invention

[0017] 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.

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

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

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

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0031] 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.

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

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] As an embodiment of this invention, the pet health management system is configured as follows: The system is mainly operated using a server, a terminal attached to the pet, and a user's communication terminal.

[0038] The device is equipped with sensors that continuously measure multiple biometric data points, such as the pet's heart rate, body temperature, and activity level. The device periodically transmits the measurement data to a server via a protocol. Data transmission is essentially real-time, and the device incorporates a filtering function to minimize errors during data transmission.

[0039] The server compares the received biometric information with a statistical model and performs analysis using an algorithm that detects anomalies. If an anomaly is detected, the server generates an alert. For example, if a pet's heart rate significantly exceeds a certain threshold, the server sends a notification to the user's communication device, indicating potential stress or health problems.

[0040] Furthermore, the server uses an AI engine to automatically generate a nutrition plan optimized for each pet's health condition. This nutrition plan is created based on past health and activity data and is proposed to the user via a communication terminal. For example, the nutrition plan is presented in the form of a specific meal menu, offering choices of ingredients containing specific nutrients.

[0041] Users can receive alerts, nutritional plans, and exercise suggestions from the server via their own communication devices and implement them into their pet's life. The system also supports emergency response for pets by providing users with a function to check medical history and instructions for first aid in case of abnormalities.

[0042] In this way, the system comprehensively manages pet health information, allowing users to constantly monitor their pet's current health status and providing peace of mind. As an example of specific measures, for pets with reduced activity levels, the server suggests an appropriate exercise plan and supports users in implementing it. Through these functions, the system significantly reduces the burden on pet owners in managing their pets' health.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The device measures the pet's heart rate, body temperature, and activity level in real time and stores this data in a buffer. At regular intervals, it prepares to upload the stored data to the server.

[0046] Step 2:

[0047] Data sent from the terminal is received by the server. The server checks the data's integrity and stores it in the database. This ensures the data quality necessary for the next analysis process.

[0048] Step 3:

[0049] The server analyzes the accumulated biometric data by comparing it with a statistical model. In this process, it identifies outliers that deviate from the normal range and evaluates the type and degree of the anomaly.

[0050] Step 4:

[0051] When the server detects an anomaly, it generates an alert related to that anomaly. The alert includes details of the biometric information in which the anomaly was detected and recommended countermeasures.

[0052] Step 5:

[0053] The generated alerts are sent from the server to the user's communication device. The user receives the alerts through the application and can immediately check the health status of their pet.

[0054] Step 6:

[0055] The server automatically generates a nutrition plan using the pet's biometric information and activity data. This nutrition plan is optimized for the pet's current health condition and also utilizes past data.

[0056] Step 7:

[0057] Users can check the nutrition plan provided on their communication terminal and manage their pet's diet based on specific meal menus and nutrient suggestions.

[0058] Step 8:

[0059] The server continuously optimizes the health management process based on user feedback and new data. This adaptive feedback loop ensures the system is always up-to-date and optimal.

[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] There is a challenge in continuously and efficiently monitoring a pet's health, quickly detecting abnormalities, and notifying the user. Furthermore, there is a need to automatically create and provide users with nutritional plans and activity suggestions tailored to each individual pet. In conventional systems, these processes are often complex and burdensome for users.

[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 collecting biometric data and transmitting it to a central processing unit via a communication protocol, means for analyzing the biometric data using a statistical model and detecting anomalies, means for immediately distributing the generated warnings to a user communication device, and an artificial intelligence engine that generates personalized nutrition and activity programs based on past biometric data. This enables real-time monitoring of the pet's health status, early detection of anomalies, and the suggestion of countermeasures.

[0065] A "pet device" is a device attached to a pet to collect biometric data, and its role is to measure data such as heart rate, body temperature, and activity level in real time.

[0066] A "communication protocol" is a set of communication rules used by pet devices to transmit data to a central processing unit. It is a system that uses technologies such as Bluetooth and Wi-Fi to transmit data safely and efficiently.

[0067] The "Central Processing Unit" is a device that collects and analyzes biometric data transmitted from pet devices, and is the main component that detects abnormalities and generates warnings based on the analysis results.

[0068] A "statistical model" is a mathematical model used by a central processing unit when analyzing biological data, providing a standard for detecting anomalies by comparing them with past data.

[0069] An "artificial intelligence engine" is a computing system used to learn from past biological data and automatically generate personalized nutrition plans and activity programs.

[0070] A "user communication device" refers to a device that notifies the user of generated warnings and nutrition plans, and includes communication-enabled mobile terminals such as smartphones and tablets.

[0071] In an embodiment for carrying out this invention, the pet health management system consists of a pet device, a central processing unit (server), and a user communication device.

[0072] The pet device is equipped with various sensors to continuously collect biometric data such as heart rate, body temperature, and activity level. These sensors can record the pet's biometric information in real time, and for example, they can measure changes in heart rate when the pet is exercising.

[0073] The server receives biometric data collected from pet devices and analyzes this data using statistical models. Data analysis tools such as Python and R can be used for the analysis. If an anomaly is detected, the server immediately generates a warning and sends a notification to the user's communication device. Furthermore, the server uses a generative AI model to create personalized nutrition and activity plans based on past biometric data. These plans provide specific guidance for maintaining the pet's health.

[0074] Users can receive notifications and suggestions from the server via their communication devices. For example, if a pet's heart rate is abnormal, the user will receive a warning such as, "Your pet's heart rate is high. It may be experiencing stress." This allows the user to take prompt action. Furthermore, specific nutritional plans are provided, such as, "A diet including chicken is recommended to increase protein intake."

[0075] For example, if a pet's activity level decreases, the server will immediately generate an exercise plan such as, "Your pet's activity level has decreased. Let's add a 30-minute walk today," and notify the user.

[0076] Examples of prompt messages include the following:

[0077] "Please describe an AI system that monitors a pet's health and issues warnings when abnormalities are detected. Also, please explain how it suggests optimal nutrition and exercise plans for pets."

[0078] In this way, the system can comprehensively support the daily health of pets.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The device collects biometric data such as heart rate, body temperature, and activity level using sensors attached to the pet. This data is recorded in real time and stored in internal memory at regular intervals. The input is biometric data, and the output is filtered data. Through filtering, noise and errors are removed.

[0082] Step 2:

[0083] The device transmits collected biometric data to a server via a communication protocol (e.g., Bluetooth, Wi-Fi). Data transmission occurs in real time; the input is filtered data, and the output is the data sent to the server. To ensure the stability of data transmission, signal strength and connection status are monitored.

[0084] Step 3:

[0085] The server analyzes biometric data received from the terminal. The input is biometric data transmitted from the terminal, and anomalies are detected using a statistical model; the output is the analysis result. For example, if the heart rate exceeds the normal range, it is flagged as an anomaly.

[0086] Step 4:

[0087] The server generates a warning if an anomaly is detected based on the analysis results. The input is the analysis results of the anomaly data, and the output is the generated warning message. This message may include content such as, "Your pet's heart rate is high. Stress is a possible cause."

[0088] Step 5:

[0089] The server utilizes a generative AI model to automatically generate pet nutrition and activity plans based on historical data. Input is historical biometric and activity data, and output is an individually optimized plan. The nutrition plan includes specific advice such as, "A diet with increased protein is recommended."

[0090] Step 6:

[0091] Users receive warnings and nutritional plans from the server via a communication terminal. The input consists of warning messages and plans sent from the server, and the output is used by the user to manage their pet's health. This allows users to take appropriate action immediately.

[0092] (Application Example 1)

[0093] 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."

[0094] One challenge in pet health management is the difficulty for owners to monitor their pet's health in real time and take appropriate action quickly based on that information. Conventional systems lacked sufficient integration of biometric data measurement and analysis, leading to delays in detecting abnormalities and suggesting preventative measures, which could cause anxiety regarding pet health management. Furthermore, busy owners may find it difficult to frequently check their communication devices, increasing the risk of overlooking their pet's condition.

[0095] 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.

[0096] In this invention, the server includes means for aggregating data in real time and analyzing anomalies using automated machinery available in the home, means for automatically generating a nutrition plan based on biometric information, and means for notifying the user using voice output or visual display. This makes it possible for pet owners to receive important notifications and suggestions regarding their pet's health without having to directly check a communication terminal.

[0097] "Biometric information" refers to various data indicating a pet's health status, such as heart rate, body temperature, and activity level.

[0098] "Abnormal" refers to a state or pattern in which biological information deviates from the set normal range.

[0099] An "alert" is a notification that is triggered when an anomaly is detected, and it is a means of informing the user about the status of their pet.

[0100] A "nutritional plan" is a plan that consists of a meal menu and nutrient recommendations optimized for a pet based on its biological information.

[0101] An "automated machine" is a device that operates in the home and collects, analyzes, and notifies users of biometric information to support pet health management.

[0102] "Audio output or visual display" refers to a means of communicating information to a user, and is a method of presenting alerts or suggestions visually or audibly.

[0103] This invention constructs a system that uses automated household machinery to monitor a pet's health in real time. The server continuously collects data such as heart rate, body temperature, and activity level from biometric sensors attached to the pet. This information is transmitted to the server via a robotic operating system (ROS). The server receives this data and performs analysis to detect anomalies in real time. If an anomaly is detected, the AI ​​engine automatically generates a personalized nutrition plan and notifies the user of the alert through voice output and visual display.

[0104] Specifically, the server utilizes a data analysis module implemented using Python and an AI-powered nutrition plan generation model using TENSORFLOW®. This enables the simultaneous detection of anomalies and the provision of real-time advice tailored to the pet's health condition. For example, if a pet's activity level decreases, the AI-generated nutrition plan will suggest, "Since your pet is less active, let's add some foods to increase its energy."

[0105] By receiving notifications from the system, users can understand their pet's health status and provide more appropriate care. Leveraging the features of the generative AI model, a more specific and practical plan can be provided by using a prompt such as, "Generate a nutrition plan for when the dog's activity level decreases."

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The device collects biometric information (heart rate, body temperature, activity level) from the pet using sensors. The input is the pet's biometric data. The device filters this data and formats it to minimize errors. The output is the formatted biometric data.

[0109] Step 2:

[0110] The terminal sends the formatted biometric data to the server via a communication protocol. The input is the formatted biometric data. The terminal packets the data and performs the transmission process. The output is the packets forwarded to the server.

[0111] Step 3:

[0112] The server analyzes biometric data received from the terminal. The input is the biometric data received from the terminal. The server analyzes the data in real time and uses a statistical model to detect anomalies. The output is a determination of whether or not an anomaly was detected.

[0113] Step 4:

[0114] If an anomaly is detected, the server uses an AI engine to generate a customized nutrition plan. The input is the biometric data in which the anomaly was detected. The AI ​​engine references past health data to generate the optimal nutrition plan. The output is the generated nutrition plan.

[0115] Step 5:

[0116] The server notifies the user of the generated nutrition plan and provides audio or visual alerts. Inputs include the nutrition plan and information about any abnormalities. The server parses the data according to the notification format, performs speech synthesis or text generation, and sends it to the user's terminal. Output is a specific notification message to the user.

[0117] 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.

[0118] This invention relates to a system that, in addition to managing the health of pets, includes an engine that recognizes user emotions and optimizes the system's response. This system consists of a server, a terminal attached to the pet, and a user's communication terminal.

[0119] The device measures the pet's heart rate, body temperature, and activity level in real time and transmits this biometric information to a server. The server analyzes the transmitted biometric information, detects abnormalities, and generates alerts as needed. The server also takes the pet's past health data into consideration and automatically generates an optimal nutrition plan.

[0120] In addition, this system incorporates an emotion engine, which has the function of recognizing the user's emotions. This emotion engine analyzes voice and text data acquired from the user's communication terminal to estimate the user's current emotional state. For example, when a user receives an alert message, the emotion engine monitors the user's response to the message and, if it is estimated that the user is feeling stressed or anxious, can provide additional information and support to alleviate these feelings.

[0121] Specifically, when the emotion engine detects anxiety in a user who has received an urgent alert, the server can prioritize sending supplemental information and emergency response procedures to the user to provide reassurance. Furthermore, if the system determines that the user is relaxed, it can improve the user experience by providing simpler language and lighter advice.

[0122] Users can use a communication terminal to view nutrition plans and alerts optimized by the emotion engine. Furthermore, feedback based on emotional information allows the server to continuously improve its recommendations, supporting pet health management and reducing user stress. Therefore, the entire system provides comprehensive care that considers not only the pet's health but also the user's emotional well-being.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The device uses sensors to measure the pet's heart rate, body temperature, and activity level, and stores this data in a buffer. At regular intervals, this data is prepared to be sent to a server over the network.

[0126] Step 2:

[0127] The server receives biometric data transmitted from the terminal. The received data is stored in a database, and an integrity check is performed to confirm that there are no missing or abnormal values.

[0128] Step 3:

[0129] The server uses stored biometric data to compare with statistical models and detect anomalies. If heart rate, body temperature, or other parameters deviate from the normal range, it generates an alert and notifies the user.

[0130] Step 4:

[0131] The server uses an AI engine to automatically generate a nutrition plan, taking into account the pet's health status and past data. The generated plan is then provided to the user as specific meal suggestions and nutrient management.

[0132] Step 5:

[0133] The server retrieves emotion data from the user's communication device. By analyzing voice, text, or other user interactions, the emotion engine estimates the user's emotional state.

[0134] Step 6:

[0135] The emotion engine recognizes the user's emotions, and the server adjusts the tone of alerts and notifications based on that. For example, if the user is feeling stressed, an alert can be sent that is reassuring.

[0136] Step 7:

[0137] Users receive and review alerts, nutritional plans, and emotionally-tailored information via a communication device. Based on the received information, they manage their pet's health and adjust their lifestyle accordingly.

[0138] Step 8:

[0139] User feedback and new sentiment data are sent to the server. The server reflects this data and performs analysis to continuously improve the accuracy and usefulness of the entire system.

[0140] (Example 2)

[0141] 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".

[0142] Traditional pet management systems, while capable of monitoring the health of animals, lacked the ability to optimize responses based on the user's emotional state, resulting in insufficient reassurance and support for users. Furthermore, there was a need to simultaneously achieve pet health management and reduce the emotional burden on users.

[0143] 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.

[0144] In this invention, the server includes means for measuring the animal's biological information and detecting abnormalities, means for notifying the user of a warning based on the abnormality, and means for analyzing the user's emotional state using an emotion engine and optimizing the response. This enables monitoring of the animal's health status and providing accurate information in accordance with the user's emotions.

[0145] "Animals" refers to mammals, birds, and other living creatures kept as pets.

[0146] "Biometric information" refers to data about an animal's internal organs and behavior, such as heart rate, body temperature, and activity level.

[0147] An "abnormality" refers to a fluctuation in biological information that deviates from the normal range, indicating a possible health problem.

[0148] "Warning" refers to an alert message that notifies the user when an abnormality is detected in the animal's health condition.

[0149] A "nutritional plan" refers to a management plan that includes the type and amount of food an animal eats in order to maintain or improve its health.

[0150] "Users" refer to individuals who use this system to manage the health of animals and receive information.

[0151] "Communication devices" refer to electronic devices capable of sending and receiving information, such as smartphones and tablets.

[0152] An "emotion engine" refers to an algorithm or processing system that analyzes a user's voice or text to estimate their emotional state.

[0153] "Response optimization" refers to the process of taking into account the user's emotional state and providing appropriate responses and information.

[0154] This invention is a system that uses animal biological information to detect abnormalities and enables the provision of optimal information tailored to the user's emotional state. The system consists of a terminal, a server, and a user communication device.

[0155] The device is attached to the animal's body and is equipped with sensors to measure biometric information such as heart rate, body temperature, and activity level in real time. The device formats the measured data and transmits it to a server in an encrypted form using wireless communication.

[0156] The server immediately stores biometric data in a database upon receiving it. Simultaneously, it uses a real-time analysis engine to detect anomalies. This engine executes algorithms to identify data fluctuations that exceed a pre-defined normal range. If an anomaly is detected, it generates an alert and immediately notifies the user's communication device.

[0157] An emotion engine is also integrated into the server, analyzing voice and text data received from the user's communication device. This engine uses natural language processing technology to estimate the user's emotional state. Based on the results, it provides appropriate information and responses that are sensitive to the user's emotions. It also uses a generative AI model to generate prompts tailored to the user, customizing the system's responses.

[0158] As a concrete example of its operation, if the server determines that an animal is showing signs of inactivity, the AI ​​model will generate a message such as, "Your pet hasn't been moving around much lately. Would you like to take them for a walk?" and send it to the user. An example of a prompt message would be, "Your pet's body temperature is slightly elevated. How would you like to notify the user?"

[0159] In this way, the system can manage the health of the animals while providing comprehensive support that takes into account the user's feelings.

[0160] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0161] Step 1:

[0162] The device measures the animal's biological information in real time. Sensors capture heart rate, body temperature, and activity levels as input, and this data is formatted and output at regular intervals. Specifically, these sensors are attached to the animal's body, and the data is read and converted into digital signals.

[0163] Step 2:

[0164] The terminal encrypts the measured biometric information and transmits it to the server using a secure protocol. It uses formatted biometric information as input, protects the data with an encryption algorithm, and transmits the data to the server as output. Specifically, the terminal uses wireless communication to transfer data packets to the server.

[0165] Step 3:

[0166] The server stores the received biometric information in a database and detects anomalies using a real-time analysis engine. The input is biometric information transmitted from the terminal, and the anomaly detection algorithm is applied to obtain an anomaly determination result as output. The specific operations are recording to the database and executing the data analysis process.

[0167] Step 4:

[0168] When an anomaly is detected, the server generates an alert and immediately notifies the user's communication device. The input is the anomaly detection result, and based on the nature of the anomaly, it constructs an alert message and sends the alert to the communication device as output. Specifically, it uses automated email sending or push notifications.

[0169] Step 5:

[0170] The user's communication device records the user's response to received alerts. Inputs are voice and text data, which the emotion engine analyzes to estimate the user's emotional state. The system utilizes speech recognition and natural language processing for emotion analysis.

[0171] Step 6:

[0172] The server uses a generative AI model to generate prompt messages based on the estimated user's emotional state, providing the user with optimal information. The input is the user's emotional state, which the generative AI model analyzes and outputs as prompt messages. Specifically, its function is to provide supportive messages and advice aimed at reducing user stress.

[0173] (Application Example 2)

[0174] 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".

[0175] Pet health management is a crucial issue in modern times. However, it's necessary to go beyond simply measuring a pet's biological information and instead use that data to detect abnormalities early and automatically create nutritional plans for pets, thereby reducing the burden on owners. Furthermore, there is a lack of information provided that takes into account the emotional state of owners, so a comprehensive system is needed to alleviate owner stress and anxiety and to foster a smoother relationship with their pets.

[0176] 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.

[0177] In this invention, the server includes means for measuring the pet's biological information and detecting abnormalities based on said biological information; means for notifying the user of an alert based on said abnormality; means for automatically generating a pet's nutrition plan based on said biological information; and means for estimating the user's emotions using emotion analysis means and optimizing information based on said emotions. This makes it possible to provide optimal health management and psychological support for both the owner and the pet.

[0178] "Pet biometric information" refers to data measured to indicate the animal's health status, such as heart rate, body temperature, and activity level.

[0179] An "abnormality" refers to a state of health that is different from the normal state, as detected based on the pet's biological information.

[0180] An "alert" is a warning or cautionary message that is sent to the user when an abnormality is detected in the pet's health condition.

[0181] A "nutritional plan" is a recommended diet and nutrient plan automatically generated based on biological information, with the aim of maintaining the health of pets.

[0182] "Emotion analysis means" refers to a function that estimates a user's emotions by analyzing voice data and text data.

[0183] "Means of optimizing information" refers to a function that adjusts the information provided to reduce user stress and anxiety based on the analyzed emotions of the user.

[0184] A "user communication device" is an electronic device used by the user to receive and display health information and alerts about their pet.

[0185] This invention aims to ensure the safety of pets by measuring their biological information in real time through a pet health management system and sending appropriate alerts to the user when abnormalities are detected.

[0186] The core of the system lies in biometric information acquired by pet robots and wearable devices, emotion analysis means for analyzing the user's emotions, and optimization means for providing information based on these.

[0187] The system is configured as follows: Sensors attached to the pet collect biometric information such as heart rate, body temperature, and activity level. This data is transferred to the user's smartphone via Bluetooth or other means, and then sent to a server in the cloud. The server analyzes the collected data, and if an anomaly is detected, it immediately sends an alert to the user's communication device.

[0188] Furthermore, the server uses a speech recognition platform and text analysis software that utilizes smartphone voice input to understand the user's emotional state as a means of sentiment analysis. Specifically, it analyzes voice data using APIs such as OpenAI® to estimate whether the user is experiencing stress. Based on the results, it appropriately modifies the alert content and provides information that takes the user's emotions into consideration.

[0189] For example, if a pet becomes active at an unexpected time and the user is feeling anxious, the server will send reassuring information and supplementary messages in addition to the usual alerts. Conversely, if the user is deemed relaxed, less urgent information may take priority.

[0190] For example, by using prompts such as, "Generate an alert when the pet's activity level increases," or "Create a reassuring message when the user is feeling stressed," it is possible to request the AI ​​model to optimize its responses. In this way, the system reduces not only the pet's psychological burden but also that of the user, achieving comprehensive care.

[0191] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0192] Step 1:

[0193] The device measures biometric information such as heart rate, body temperature, and activity level through sensors attached to the pet. This biometric information is temporarily stored within the device. The collected data is transmitted to the user's smartphone using Bluetooth. The input is the pet's biometric information, and the output is a data packet containing this information.

[0194] Step 2:

[0195] The smartphone forwards the received biometric data packets to a server in the cloud. The smartphone transmits the information received via Bluetooth over the internet. The input is data packets from the device, and the output is a data stream sent to the server.

[0196] Step 3:

[0197] The server analyzes biometric data received on the cloud and checks for abnormalities. Specifically, it compares the data with pre-defined normal ranges and historical data to detect statistical anomalies. The input is biometric data sent to the cloud, and the output is the analysis result indicating whether or not an abnormality is present.

[0198] Step 4:

[0199] When an anomaly is detected, the server uses a generation AI model to generate an alert message to send to the user. A prompt is used to request the generation AI to create the most appropriate alert content. The input is the anomaly detection information, and the output is the alert message.

[0200] Step 5:

[0201] The terminal notifies the user's communication device of alert messages sent from the server. Smartphones and other communication devices function as receiving devices and display alerts in real time. The input is the alert message sent from the server, and the output is the warning display notified to the user.

[0202] Step 6:

[0203] The user's smartphone collects voice data using its microphone and estimates their current emotional state using emotion analysis tools. The voice data is sent to a server where voice analysis is performed using the OpenAI API. The input is the voice data obtained from the user, and the output is the estimated emotional state.

[0204] Step 7:

[0205] The server generates and provides optimized information to the user based on the estimated user's emotional state. Using a generative AI model, it generates information that takes emotional data into account through prompt messages. The input is the estimated emotional state, and the output is the optimized information.

[0206] 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.

[0207] Data generation model 58 is a type of 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.

[0208] 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.

[0209] [Second Embodiment]

[0210] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0211] 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.

[0212] 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).

[0213] 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.

[0214] 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.

[0215] 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).

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] 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.

[0221] 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".

[0222] As an embodiment of this invention, the pet health management system is configured as follows: The system is mainly operated using a server, a terminal attached to the pet, and a user's communication terminal.

[0223] The device is equipped with sensors that continuously measure multiple biometric data points, such as the pet's heart rate, body temperature, and activity level. The device periodically transmits the measurement data to a server via a protocol. Data transmission is essentially real-time, and the device incorporates a filtering function to minimize errors during data transmission.

[0224] The server compares the received biometric information with a statistical model and performs analysis using an algorithm that detects anomalies. If an anomaly is detected, the server generates an alert. For example, if a pet's heart rate significantly exceeds a certain threshold, the server sends a notification to the user's communication device, indicating potential stress or health problems.

[0225] Furthermore, the server uses an AI engine to automatically generate a nutrition plan optimized for each pet's health condition. This nutrition plan is created based on past health and activity data and is proposed to the user via a communication terminal. For example, the nutrition plan is presented in the form of a specific meal menu, offering choices of ingredients containing specific nutrients.

[0226] Users can receive alerts, nutritional plans, and exercise suggestions from the server via their own communication devices and implement them into their pet's life. The system also supports emergency response for pets by providing users with a function to check medical history and instructions for first aid in case of abnormalities.

[0227] In this way, the system comprehensively manages pet health information, allowing users to constantly monitor their pet's current health status and providing peace of mind. As an example of specific measures, for pets with reduced activity levels, the server suggests an appropriate exercise plan and supports users in implementing it. Through these functions, the system significantly reduces the burden on pet owners in managing their pets' health.

[0228] The following describes the processing flow.

[0229] Step 1:

[0230] The device measures the pet's heart rate, body temperature, and activity level in real time and stores this data in a buffer. At regular intervals, it prepares to upload the stored data to the server.

[0231] Step 2:

[0232] Data sent from the terminal is received by the server. The server checks the data's integrity and stores it in the database. This ensures the data quality necessary for the next analysis process.

[0233] Step 3:

[0234] The server analyzes the accumulated biometric data by comparing it with a statistical model. In this process, it identifies outliers that deviate from the normal range and evaluates the type and degree of the anomaly.

[0235] Step 4:

[0236] When the server detects an anomaly, it generates an alert related to that anomaly. The alert includes details of the biometric information in which the anomaly was detected and recommended countermeasures.

[0237] Step 5:

[0238] The generated alerts are sent from the server to the user's communication device. The user receives the alerts through the application and can immediately check the health status of their pet.

[0239] Step 6:

[0240] The server automatically generates a nutrition plan using the pet's biometric information and activity data. This nutrition plan is optimized for the pet's current health condition and also utilizes past data.

[0241] Step 7:

[0242] Users can check the nutrition plan provided on their communication terminal and manage their pet's diet based on specific meal menus and nutrient suggestions.

[0243] Step 8:

[0244] The server continuously optimizes the health management process based on user feedback and new data. This adaptive feedback loop ensures the system is always up-to-date and optimal.

[0245] (Example 1)

[0246] 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."

[0247] There is a challenge in continuously and efficiently monitoring a pet's health, quickly detecting abnormalities, and notifying the user. Furthermore, there is a need to automatically create and provide users with nutritional plans and activity suggestions tailored to each individual pet. In conventional systems, these processes are often complex and burdensome for users.

[0248] 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.

[0249] In this invention, the server includes means for collecting biometric data and transmitting it to a central processing unit via a communication protocol, means for analyzing the biometric data using a statistical model and detecting anomalies, means for immediately distributing the generated warnings to a user communication device, and an artificial intelligence engine that generates personalized nutrition and activity programs based on past biometric data. This enables real-time monitoring of the pet's health status, early detection of anomalies, and the suggestion of countermeasures.

[0250] A "pet device" is a device attached to a pet to collect biometric data, and its role is to measure data such as heart rate, body temperature, and activity level in real time.

[0251] A "communication protocol" is a set of communication rules used by pet devices to transmit data to a central processing unit. It is a system that uses technologies such as Bluetooth and Wi-Fi to transmit data safely and efficiently.

[0252] The "Central Processing Unit" is a device that collects and analyzes biometric data transmitted from pet devices, and is the main component that detects abnormalities and generates warnings based on the analysis results.

[0253] A "statistical model" is a mathematical model used by a central processing unit when analyzing biological data, providing a standard for detecting anomalies by comparing them with past data.

[0254] An "artificial intelligence engine" is a computing system used to learn from past biological data and automatically generate personalized nutrition plans and activity programs.

[0255] A "user communication device" refers to a device that notifies the user of generated warnings and nutrition plans, and includes communication-enabled mobile terminals such as smartphones and tablets.

[0256] In an embodiment for carrying out this invention, the pet health management system consists of a pet device, a central processing unit (server), and a user communication device.

[0257] The pet device is equipped with various sensors to continuously collect biometric data such as heart rate, body temperature, and activity level. These sensors can record the pet's biometric information in real time, and for example, they can measure changes in heart rate when the pet is exercising.

[0258] The server receives biometric data collected from pet devices and analyzes this data using statistical models. Data analysis tools such as Python and R can be used for the analysis. If an anomaly is detected, the server immediately generates a warning and sends a notification to the user's communication device. Furthermore, the server uses a generative AI model to create personalized nutrition and activity plans based on past biometric data. These plans provide specific guidance for maintaining the pet's health.

[0259] Users can receive notifications and suggestions from the server via their communication devices. For example, if a pet's heart rate is abnormal, the user will receive a warning such as, "Your pet's heart rate is high. It may be experiencing stress." This allows the user to take prompt action. Furthermore, specific nutritional plans are provided, such as, "A diet including chicken is recommended to increase protein intake."

[0260] For example, if a pet's activity level decreases, the server will immediately generate an exercise plan such as, "Your pet's activity level has decreased. Let's add a 30-minute walk today," and notify the user.

[0261] Examples of prompt messages include the following:

[0262] "Please describe an AI system that monitors a pet's health and issues warnings when abnormalities are detected. Also, please explain how it suggests optimal nutrition and exercise plans for pets."

[0263] In this way, the system can comprehensively support the daily health of pets.

[0264] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0265] Step 1:

[0266] The device collects biometric data such as heart rate, body temperature, and activity level using sensors attached to the pet. This data is recorded in real time and stored in internal memory at regular intervals. The input is biometric data, and the output is filtered data. Through filtering, noise and errors are removed.

[0267] Step 2:

[0268] The device transmits collected biometric data to a server via a communication protocol (e.g., Bluetooth, Wi-Fi). Data transmission occurs in real time; the input is filtered data, and the output is the data sent to the server. To ensure the stability of data transmission, signal strength and connection status are monitored.

[0269] Step 3:

[0270] The server analyzes biometric data received from the terminal. The input is biometric data transmitted from the terminal, and anomalies are detected using a statistical model; the output is the analysis result. For example, if the heart rate exceeds the normal range, it is flagged as an anomaly.

[0271] Step 4:

[0272] The server generates a warning if an anomaly is detected based on the analysis results. The input is the analysis results of the anomaly data, and the output is the generated warning message. This message may include content such as, "Your pet's heart rate is high. Stress is a possible cause."

[0273] Step 5:

[0274] The server utilizes a generative AI model to automatically generate pet nutrition and activity plans based on historical data. Input is historical biometric and activity data, and output is an individually optimized plan. The nutrition plan includes specific advice such as, "A diet with increased protein is recommended."

[0275] Step 6:

[0276] Users receive warnings and nutritional plans from the server via a communication terminal. The input consists of warning messages and plans sent from the server, and the output is used by the user to manage their pet's health. This allows users to take appropriate action immediately.

[0277] (Application Example 1)

[0278] 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."

[0279] One challenge in pet health management is the difficulty for owners to monitor their pet's health in real time and take appropriate action quickly based on that information. Conventional systems lacked sufficient integration of biometric data measurement and analysis, leading to delays in detecting abnormalities and suggesting preventative measures, which could cause anxiety regarding pet health management. Furthermore, busy owners may find it difficult to frequently check their communication devices, increasing the risk of overlooking their pet's condition.

[0280] 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.

[0281] In this invention, the server includes means for aggregating data in real time and analyzing anomalies using automated machinery available in the home, means for automatically generating a nutrition plan based on biometric information, and means for notifying the user using voice output or visual display. This makes it possible for pet owners to receive important notifications and suggestions regarding their pet's health without having to directly check a communication terminal.

[0282] "Biometric information" refers to various data indicating a pet's health status, such as heart rate, body temperature, and activity level.

[0283] "Abnormality" refers to a state or pattern in which biological information deviates from the set normal range.

[0284] "Alert" is a notification that occurs when an abnormality is detected and is a means to inform the user of the pet's situation.

[0285] "Nutrition plan" is a plan consisting of a diet menu and nutrient proposals optimized for the pet based on biological information.

[0286] "Automated machine" is a device that operates within the home and collects, analyzes, and notifies biological information to assist in the health management of the pet.

[0287] "Voice output or visual display" is a means to convey information to the user and is a method to present alerts and proposals visually or aurally.

[0288] In this invention, a system is constructed using an automated machine within the home to monitor the health status of the pet in real time. The server continuously collects data such as heart rate, body temperature, and activity level from the biological information sensors attached to the pet. This information is transmitted to the server through the Robot Operating System (ROS). The server receives these data and performs analysis for detecting abnormalities in real time. When an abnormality is detected, the AI engine automatically generates a customized nutrition plan and notifies the user of the alert through voice output or visual display.

[0289] Specifically, the server utilizes a data analysis module implemented using Python and a nutrition plan generation model by AI using TensorFlow. This enables the real-time provision of advice according to the health status of the pet simultaneously with the detection of abnormalities. For example, when the activity level of the pet decreases, a proposal such as "Since the activity level is low, let's add ingredients that increase energy" is made based on the nutrition plan generated by the AI.

[0290] By receiving notifications from the system, users can understand their pet's health status and provide more appropriate care. Leveraging the features of the generative AI model, a more specific and practical plan can be provided by using a prompt such as, "Generate a nutrition plan for when the dog's activity level decreases."

[0291] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0292] Step 1:

[0293] The device collects biometric information (heart rate, body temperature, activity level) from the pet using sensors. The input is the pet's biometric data. The device filters this data and formats it to minimize errors. The output is the formatted biometric data.

[0294] Step 2:

[0295] The terminal sends the formatted biometric data to the server via a communication protocol. The input is the formatted biometric data. The terminal packets the data and performs the transmission process. The output is the packets forwarded to the server.

[0296] Step 3:

[0297] The server analyzes biometric data received from the terminal. The input is the biometric data received from the terminal. The server analyzes the data in real time and uses a statistical model to detect anomalies. The output is a determination of whether or not an anomaly was detected.

[0298] Step 4:

[0299] If an anomaly is detected, the server uses an AI engine to generate a customized nutrition plan. The input is the biometric data in which the anomaly was detected. The AI ​​engine references past health data to generate the optimal nutrition plan. The output is the generated nutrition plan.

[0300] Step 5:

[0301] The server notifies the user of the generated nutrition plan and provides audio or visual alerts. Inputs include the nutrition plan and information about any abnormalities. The server parses the data according to the notification format, performs speech synthesis or text generation, and sends it to the user's terminal. Output is a specific notification message to the user.

[0302] 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.

[0303] This invention relates to a system that, in addition to managing the health of pets, includes an engine that recognizes user emotions and optimizes the system's response. This system consists of a server, a terminal attached to the pet, and a user's communication terminal.

[0304] The device measures the pet's heart rate, body temperature, and activity level in real time and transmits this biometric information to a server. The server analyzes the transmitted biometric information, detects abnormalities, and generates alerts as needed. The server also takes the pet's past health data into consideration and automatically generates an optimal nutrition plan.

[0305] In addition, this system incorporates an emotion engine, which has the function of recognizing the user's emotions. This emotion engine analyzes voice and text data acquired from the user's communication terminal to estimate the user's current emotional state. For example, when a user receives an alert message, the emotion engine monitors the user's response to the message and, if it is estimated that the user is feeling stressed or anxious, can provide additional information and support to alleviate these feelings.

[0306] Specifically, when the emotion engine detects uneasiness when the user receives an emergency alert, the server can preferentially transmit supplementary information for reassuring the user and response procedures in case of emergency. Also, when the user is judged to be relaxed, the user experience can be improved by providing plain expressions and light advice accordingly.

[0307] The user can use the communication terminal to check a nutrition plan and alerts optimized by the emotion engine. Also, based on feedback using emotion information, the server can continuously improve the proposed content and support the health management of the pet and the reduction of the user's mental burden. For this reason, as a whole system, comprehensive care that takes into account not only the health of the pet but also the user's feelings is realized.

[0308] The processing flow will be described below.

[0309] Step 1:

[0310] The terminal measures the pet's heart rate, body temperature, and activity level with sensors and accumulates this data in a buffer. At regular intervals, this data is prepared to be sent to the server via the network.

[0311] Step 2:

[0312] The server receives the biometric information data sent from the terminal. The received data is stored in a database and a consistency check is performed to confirm that there are no missing values or outliers.

[0313] Step 3:

[0314] The server compares the stored biometric information with a statistical model to detect anomalies. If the heart rate, body temperature, etc. deviate from the normal range, an alert is generated and notified to the user.

[0315] Step 4:

[0316] The server uses an AI engine to automatically generate a nutrition plan, taking into account the pet's health status and past data. The generated plan is then provided to the user as specific meal suggestions and nutrient management.

[0317] Step 5:

[0318] The server retrieves emotion data from the user's communication device. By analyzing voice, text, or other user interactions, the emotion engine estimates the user's emotional state.

[0319] Step 6:

[0320] The emotion engine recognizes the user's emotions, and the server adjusts the tone of alerts and notifications based on that. For example, if the user is feeling stressed, an alert can be sent that is reassuring.

[0321] Step 7:

[0322] Users receive and review alerts, nutritional plans, and emotionally-tailored information via a communication device. Based on the received information, they manage their pet's health and adjust their lifestyle accordingly.

[0323] Step 8:

[0324] User feedback and new sentiment data are sent to the server. The server reflects this data and performs analysis to continuously improve the accuracy and usefulness of the entire system.

[0325] (Example 2)

[0326] 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".

[0327] Traditional pet management systems, while capable of monitoring the health of animals, lacked the ability to optimize responses based on the user's emotional state, resulting in insufficient reassurance and support for users. Furthermore, there was a need to simultaneously achieve pet health management and reduce the emotional burden on users.

[0328] 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.

[0329] In this invention, the server includes means for measuring the animal's biological information and detecting abnormalities, means for notifying the user of a warning based on the abnormality, and means for analyzing the user's emotional state using an emotion engine and optimizing the response. This enables monitoring of the animal's health status and providing accurate information in accordance with the user's emotions.

[0330] "Animals" refers to mammals, birds, and other living creatures kept as pets.

[0331] "Biometric information" refers to data about an animal's internal organs and behavior, such as heart rate, body temperature, and activity level.

[0332] An "abnormality" refers to a fluctuation in biological information that deviates from the normal range, indicating a possible health problem.

[0333] "Warning" refers to an alert message that notifies the user when an abnormality is detected in the animal's health condition.

[0334] A "nutritional plan" refers to a management plan that includes the type and amount of food an animal eats in order to maintain or improve its health.

[0335] "Users" refer to individuals who use this system to manage the health of animals and receive information.

[0336] "Communication devices" refer to electronic devices capable of sending and receiving information, such as smartphones and tablets.

[0337] An "emotion engine" refers to an algorithm or processing system that analyzes a user's voice or text to estimate their emotional state.

[0338] "Response optimization" refers to the process of taking into account the user's emotional state and providing appropriate responses and information.

[0339] This invention is a system that uses animal biological information to detect abnormalities and enables the provision of optimal information tailored to the user's emotional state. The system consists of a terminal, a server, and a user communication device.

[0340] The device is attached to the animal's body and is equipped with sensors to measure biometric information such as heart rate, body temperature, and activity level in real time. The device formats the measured data and transmits it to a server in an encrypted form using wireless communication.

[0341] The server immediately stores biometric data in a database upon receiving it. Simultaneously, it uses a real-time analysis engine to detect anomalies. This engine executes algorithms to identify data fluctuations that exceed a pre-defined normal range. If an anomaly is detected, it generates an alert and immediately notifies the user's communication device.

[0342] An emotion engine is also integrated into the server, analyzing voice and text data received from the user's communication device. This engine uses natural language processing technology to estimate the user's emotional state. Based on the results, it provides appropriate information and responses that are sensitive to the user's emotions. It also uses a generative AI model to generate prompts tailored to the user, customizing the system's responses.

[0343] As a concrete example of its operation, if the server determines that an animal is showing signs of inactivity, the AI ​​model will generate a message such as, "Your pet hasn't been moving around much lately. Would you like to take them for a walk?" and send it to the user. An example of a prompt message would be, "Your pet's body temperature is slightly elevated. How would you like to notify the user?"

[0344] In this way, the system can manage the health of the animals while providing comprehensive support that takes into account the user's feelings.

[0345] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0346] Step 1:

[0347] The device measures the animal's biological information in real time. Sensors capture heart rate, body temperature, and activity levels as input, and this data is formatted and output at regular intervals. Specifically, these sensors are attached to the animal's body, and the data is read and converted into digital signals.

[0348] Step 2:

[0349] The terminal encrypts the measured biometric information and transmits it to the server using a secure protocol. It uses formatted biometric information as input, protects the data with an encryption algorithm, and transmits the data to the server as output. Specifically, the terminal uses wireless communication to transfer data packets to the server.

[0350] Step 3:

[0351] The server stores the received biometric information in a database and detects anomalies using a real-time analysis engine. The input is biometric information transmitted from the terminal, and the anomaly detection algorithm is applied to obtain an anomaly determination result as output. The specific operations are recording to the database and executing the data analysis process.

[0352] Step 4:

[0353] When an anomaly is detected, the server generates an alert and immediately notifies the user's communication device. The input is the anomaly detection result, and based on the nature of the anomaly, it constructs an alert message and sends the alert to the communication device as output. Specifically, it uses automated email sending or push notifications.

[0354] Step 5:

[0355] The user's communication device records the user's response to received alerts. Inputs are voice and text data, which the emotion engine analyzes to estimate the user's emotional state. The system utilizes speech recognition and natural language processing for emotion analysis.

[0356] Step 6:

[0357] The server uses a generative AI model to generate prompt messages based on the estimated user's emotional state, providing the user with optimal information. The input is the user's emotional state, which the generative AI model analyzes and outputs as prompt messages. Specifically, its function is to provide supportive messages and advice aimed at reducing user stress.

[0358] (Application Example 2)

[0359] 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."

[0360] Pet health management is a crucial issue in modern times. However, it's necessary to go beyond simply measuring a pet's biological information and instead use that data to detect abnormalities early and automatically create nutritional plans for pets, thereby reducing the burden on owners. Furthermore, there is a lack of information provided that takes into account the emotional state of owners, so a comprehensive system is needed to alleviate owner stress and anxiety and to foster a smoother relationship with their pets.

[0361] 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.

[0362] In this invention, the server includes means for measuring the pet's biological information and detecting abnormalities based on said biological information; means for notifying the user of an alert based on said abnormality; means for automatically generating a pet's nutrition plan based on said biological information; and means for estimating the user's emotions using emotion analysis means and optimizing information based on said emotions. This makes it possible to provide optimal health management and psychological support for both the owner and the pet.

[0363] "Pet biometric information" refers to data measured to indicate the animal's health status, such as heart rate, body temperature, and activity level.

[0364] An "abnormality" refers to a state of health that is different from the normal state, as detected based on the pet's biological information.

[0365] An "alert" is a warning or cautionary message that is sent to the user when an abnormality is detected in the pet's health condition.

[0366] A "nutritional plan" is a recommended diet and nutrient plan automatically generated based on biological information, with the aim of maintaining the health of pets.

[0367] "Emotion analysis means" refers to a function that estimates a user's emotions by analyzing voice data and text data.

[0368] "Means of optimizing information" refers to a function that adjusts the information provided to reduce user stress and anxiety based on the analyzed emotions of the user.

[0369] A "user communication device" is an electronic device used by the user to receive and display health information and alerts about their pet.

[0370] This invention aims to ensure the safety of pets by measuring their biological information in real time through a pet health management system and sending appropriate alerts to the user when abnormalities are detected.

[0371] The core of the system lies in biometric information acquired by pet robots and wearable devices, emotion analysis means for analyzing the user's emotions, and optimization means for providing information based on these.

[0372] The system is configured as follows: Sensors attached to the pet collect biometric information such as heart rate, body temperature, and activity level. This data is transferred to the user's smartphone via Bluetooth or other means, and then sent to a server in the cloud. The server analyzes the collected data, and if an anomaly is detected, it immediately sends an alert to the user's communication device.

[0373] Furthermore, the server uses a speech recognition platform and text analysis software that utilizes smartphone voice input to understand the user's emotional state as a means of sentiment analysis. Specifically, it analyzes voice data using the OpenAI API and other tools to estimate whether the user is experiencing stress. Based on the results, it appropriately modifies the alert content and provides information that takes the user's emotions into consideration.

[0374] For example, if a pet becomes active at an unexpected time and the user is feeling anxious, the server will send reassuring information and supplementary messages in addition to the usual alerts. Conversely, if the user is deemed relaxed, less urgent information may take priority.

[0375] For example, by using prompts such as, "Generate an alert when the pet's activity level increases," or "Create a reassuring message when the user is feeling stressed," it is possible to request the AI ​​model to optimize its responses. In this way, the system reduces not only the pet's psychological burden but also that of the user, achieving comprehensive care.

[0376] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0377] Step 1:

[0378] The device measures biometric information such as heart rate, body temperature, and activity level through sensors attached to the pet. This biometric information is temporarily stored within the device. The collected data is transmitted to the user's smartphone using Bluetooth. The input is the pet's biometric information, and the output is a data packet containing this information.

[0379] Step 2:

[0380] The smartphone forwards the received biometric data packets to a server in the cloud. The smartphone transmits the information received via Bluetooth over the internet. The input is data packets from the device, and the output is a data stream sent to the server.

[0381] Step 3:

[0382] The server analyzes biometric data received on the cloud and checks for abnormalities. Specifically, it compares the data with pre-defined normal ranges and historical data to detect statistical anomalies. The input is biometric data sent to the cloud, and the output is the analysis result indicating whether or not an abnormality is present.

[0383] Step 4:

[0384] When an anomaly is detected, the server uses a generation AI model to generate an alert message to send to the user. A prompt is used to request the generation AI to create the most appropriate alert content. The input is the anomaly detection information, and the output is the alert message.

[0385] Step 5:

[0386] The terminal notifies the user's communication device of alert messages sent from the server. Smartphones and other communication devices function as receiving devices and display alerts in real time. The input is the alert message sent from the server, and the output is the warning display notified to the user.

[0387] Step 6:

[0388] The user's smartphone collects voice data using its microphone and estimates their current emotional state using emotion analysis tools. The voice data is sent to a server where voice analysis is performed using the OpenAI API. The input is the voice data obtained from the user, and the output is the estimated emotional state.

[0389] Step 7:

[0390] The server generates and provides optimized information to the user based on the estimated user's emotional state. Using a generative AI model, it generates information that takes emotional data into account through prompt messages. The input is the estimated emotional state, and the output is the optimized information.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] [Third Embodiment]

[0395] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0396] 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.

[0397] 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).

[0398] 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.

[0399] 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.

[0400] 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).

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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".

[0407] As an embodiment of this invention, the pet health management system is configured as follows: The system is mainly operated using a server, a terminal attached to the pet, and a user's communication terminal.

[0408] The device is equipped with sensors that continuously measure multiple biometric data points, such as the pet's heart rate, body temperature, and activity level. The device periodically transmits the measurement data to a server via a protocol. Data transmission is essentially real-time, and the device incorporates a filtering function to minimize errors during data transmission.

[0409] The server compares the received biometric information with a statistical model and performs analysis using an algorithm that detects anomalies. If an anomaly is detected, the server generates an alert. For example, if a pet's heart rate significantly exceeds a certain threshold, the server sends a notification to the user's communication device, indicating potential stress or health problems.

[0410] Furthermore, the server uses an AI engine to automatically generate a nutrition plan optimized for each pet's health condition. This nutrition plan is created based on past health and activity data and is proposed to the user via a communication terminal. For example, the nutrition plan is presented in the form of a specific meal menu, offering choices of ingredients containing specific nutrients.

[0411] Users can receive alerts, nutritional plans, and exercise suggestions from the server via their own communication devices and implement them into their pet's life. The system also supports emergency response for pets by providing users with a function to check medical history and instructions for first aid in case of abnormalities.

[0412] In this way, the system comprehensively manages pet health information, allowing users to constantly monitor their pet's current health status and providing peace of mind. As an example of specific measures, for pets with reduced activity levels, the server suggests an appropriate exercise plan and supports users in implementing it. Through these functions, the system significantly reduces the burden on pet owners in managing their pets' health.

[0413] The following describes the processing flow.

[0414] Step 1:

[0415] The device measures the pet's heart rate, body temperature, and activity level in real time and stores this data in a buffer. At regular intervals, it prepares to upload the stored data to the server.

[0416] Step 2:

[0417] Data sent from the terminal is received by the server. The server checks the data's integrity and stores it in the database. This ensures the data quality necessary for the next analysis process.

[0418] Step 3:

[0419] The server analyzes the accumulated biometric data by comparing it with a statistical model. In this process, it identifies outliers that deviate from the normal range and evaluates the type and degree of the anomaly.

[0420] Step 4:

[0421] When the server detects an anomaly, it generates an alert related to that anomaly. The alert includes details of the biometric information in which the anomaly was detected and recommended countermeasures.

[0422] Step 5:

[0423] The generated alerts are sent from the server to the user's communication device. The user receives the alerts through the application and can immediately check the health status of their pet.

[0424] Step 6:

[0425] The server automatically generates a nutrition plan using the pet's biometric information and activity data. This nutrition plan is optimized for the pet's current health condition and also utilizes past data.

[0426] Step 7:

[0427] Users can check the nutrition plan provided on their communication terminal and manage their pet's diet based on specific meal menus and nutrient suggestions.

[0428] Step 8:

[0429] The server continuously optimizes the health management process based on user feedback and new data. This adaptive feedback loop ensures the system is always up-to-date and optimal.

[0430] (Example 1)

[0431] 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."

[0432] There is a challenge in continuously and efficiently monitoring a pet's health, quickly detecting abnormalities, and notifying the user. Furthermore, there is a need to automatically create and provide users with nutritional plans and activity suggestions tailored to each individual pet. In conventional systems, these processes are often complex and burdensome for users.

[0433] 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.

[0434] In this invention, the server includes means for collecting biometric data and transmitting it to a central processing unit via a communication protocol, means for analyzing the biometric data using a statistical model and detecting anomalies, means for immediately distributing the generated warnings to a user communication device, and an artificial intelligence engine that generates personalized nutrition and activity programs based on past biometric data. This enables real-time monitoring of the pet's health status, early detection of anomalies, and the suggestion of countermeasures.

[0435] A "pet device" is a device attached to a pet to collect biometric data, and its role is to measure data such as heart rate, body temperature, and activity level in real time.

[0436] A "communication protocol" is a set of communication rules used by pet devices to transmit data to a central processing unit. It is a system that uses technologies such as Bluetooth and Wi-Fi to transmit data safely and efficiently.

[0437] The "Central Processing Unit" is a device that collects and analyzes biometric data transmitted from pet devices, and is the main component that detects abnormalities and generates warnings based on the analysis results.

[0438] A "statistical model" is a mathematical model used by a central processing unit when analyzing biological data, providing a standard for detecting anomalies by comparing them with past data.

[0439] An "artificial intelligence engine" is a computing system used to learn from past biological data and automatically generate personalized nutrition plans and activity programs.

[0440] A "user communication device" refers to a device that notifies the user of generated warnings and nutrition plans, and includes communication-enabled mobile terminals such as smartphones and tablets.

[0441] In an embodiment for carrying out this invention, the pet health management system consists of a pet device, a central processing unit (server), and a user communication device.

[0442] The pet device is equipped with various sensors to continuously collect biometric data such as heart rate, body temperature, and activity level. These sensors can record the pet's biometric information in real time, and for example, they can measure changes in heart rate when the pet is exercising.

[0443] The server receives biometric data collected from pet devices and analyzes this data using statistical models. Data analysis tools such as Python and R can be used for the analysis. If an anomaly is detected, the server immediately generates a warning and sends a notification to the user's communication device. Furthermore, the server uses a generative AI model to create personalized nutrition and activity plans based on past biometric data. These plans provide specific guidance for maintaining the pet's health.

[0444] Users can receive notifications and suggestions from the server via their communication devices. For example, if a pet's heart rate is abnormal, the user will receive a warning such as, "Your pet's heart rate is high. It may be experiencing stress." This allows the user to take prompt action. Furthermore, specific nutritional plans are provided, such as, "A diet including chicken is recommended to increase protein intake."

[0445] For example, if a pet's activity level decreases, the server will immediately generate an exercise plan such as, "Your pet's activity level has decreased. Let's add a 30-minute walk today," and notify the user.

[0446] Examples of prompt messages include the following:

[0447] "Please describe an AI system that monitors a pet's health and issues warnings when abnormalities are detected. Also, please explain how it suggests optimal nutrition and exercise plans for pets."

[0448] In this way, the system can comprehensively support the daily health of pets.

[0449] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0450] Step 1:

[0451] The device collects biometric data such as heart rate, body temperature, and activity level using sensors attached to the pet. This data is recorded in real time and stored in internal memory at regular intervals. The input is biometric data, and the output is filtered data. Through filtering, noise and errors are removed.

[0452] Step 2:

[0453] The device transmits collected biometric data to a server via a communication protocol (e.g., Bluetooth, Wi-Fi). Data transmission occurs in real time; the input is filtered data, and the output is the data sent to the server. To ensure the stability of data transmission, signal strength and connection status are monitored.

[0454] Step 3:

[0455] The server analyzes biometric data received from the terminal. The input is biometric data transmitted from the terminal, and anomalies are detected using a statistical model; the output is the analysis result. For example, if the heart rate exceeds the normal range, it is flagged as an anomaly.

[0456] Step 4:

[0457] The server generates a warning if an anomaly is detected based on the analysis results. The input is the analysis results of the anomaly data, and the output is the generated warning message. This message may include content such as, "Your pet's heart rate is high. Stress is a possible cause."

[0458] Step 5:

[0459] The server utilizes a generative AI model to automatically generate pet nutrition and activity plans based on historical data. Input is historical biometric and activity data, and output is an individually optimized plan. The nutrition plan includes specific advice such as, "A diet with increased protein is recommended."

[0460] Step 6:

[0461] Users receive warnings and nutritional plans from the server via a communication terminal. The input consists of warning messages and plans sent from the server, and the output is used by the user to manage their pet's health. This allows users to take appropriate action immediately.

[0462] (Application Example 1)

[0463] 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."

[0464] One challenge in pet health management is the difficulty for owners to monitor their pet's health in real time and take appropriate action quickly based on that information. Conventional systems lacked sufficient integration of biometric data measurement and analysis, leading to delays in detecting abnormalities and suggesting preventative measures, which could cause anxiety regarding pet health management. Furthermore, busy owners may find it difficult to frequently check their communication devices, increasing the risk of overlooking their pet's condition.

[0465] 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.

[0466] In this invention, the server includes means for aggregating data in real time and analyzing anomalies using automated machinery available in the home, means for automatically generating a nutrition plan based on biometric information, and means for notifying the user using voice output or visual display. This makes it possible for pet owners to receive important notifications and suggestions regarding their pet's health without having to directly check a communication terminal.

[0467] "Biometric information" refers to various data indicating a pet's health status, such as heart rate, body temperature, and activity level.

[0468] "Abnormal" refers to a state or pattern in which biological information deviates from the set normal range.

[0469] An "alert" is a notification that is triggered when an anomaly is detected, and it is a means of informing the user about the status of their pet.

[0470] A "nutritional plan" is a plan that consists of a meal menu and nutrient recommendations optimized for a pet based on its biological information.

[0471] An "automated machine" is a device that operates in the home and collects, analyzes, and notifies users of biometric information to support pet health management.

[0472] "Audio output or visual display" refers to a means of communicating information to a user, and is a method of presenting alerts or suggestions visually or audibly.

[0473] This invention constructs a system that uses automated household machinery to monitor a pet's health in real time. The server continuously collects data such as heart rate, body temperature, and activity level from biometric sensors attached to the pet. This information is transmitted to the server via a robotic operating system (ROS). The server receives this data and performs analysis to detect anomalies in real time. If an anomaly is detected, the AI ​​engine automatically generates a personalized nutrition plan and notifies the user of the alert through voice output and visual display.

[0474] Specifically, the server utilizes a data analysis module implemented using Python and an AI-powered nutrition plan generation model using TensorFlow. This enables real-time advice tailored to the pet's health condition, along with anomaly detection. For example, if a pet's activity level decreases, the AI-generated nutrition plan will suggest, "Since your pet is less active, let's add some foods to increase its energy."

[0475] By receiving notifications from the system, users can understand their pet's health status and provide more appropriate care. Leveraging the features of the generative AI model, a more specific and practical plan can be provided by using a prompt such as, "Generate a nutrition plan for when the dog's activity level decreases."

[0476] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0477] Step 1:

[0478] The device collects biometric information (heart rate, body temperature, activity level) from the pet using sensors. The input is the pet's biometric data. The device filters this data and formats it to minimize errors. The output is the formatted biometric data.

[0479] Step 2:

[0480] The terminal sends the formatted biometric data to the server via a communication protocol. The input is the formatted biometric data. The terminal packets the data and performs the transmission process. The output is the packets forwarded to the server.

[0481] Step 3:

[0482] The server analyzes biometric data received from the terminal. The input is the biometric data received from the terminal. The server analyzes the data in real time and uses a statistical model to detect anomalies. The output is a determination of whether or not an anomaly was detected.

[0483] Step 4:

[0484] If an anomaly is detected, the server uses an AI engine to generate a customized nutrition plan. The input is the biometric data in which the anomaly was detected. The AI ​​engine references past health data to generate the optimal nutrition plan. The output is the generated nutrition plan.

[0485] Step 5:

[0486] The server notifies the user of the generated nutrition plan and provides audio or visual alerts. Inputs include the nutrition plan and information about any abnormalities. The server parses the data according to the notification format, performs speech synthesis or text generation, and sends it to the user's terminal. Output is a specific notification message to the user.

[0487] 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.

[0488] This invention relates to a system that, in addition to managing the health of pets, includes an engine that recognizes user emotions and optimizes the system's response. This system consists of a server, a terminal attached to the pet, and a user's communication terminal.

[0489] The device measures the pet's heart rate, body temperature, and activity level in real time and transmits this biometric information to a server. The server analyzes the transmitted biometric information, detects abnormalities, and generates alerts as needed. The server also takes the pet's past health data into consideration and automatically generates an optimal nutrition plan.

[0490] In addition, this system incorporates an emotion engine, which has the function of recognizing the user's emotions. This emotion engine analyzes voice and text data acquired from the user's communication terminal to estimate the user's current emotional state. For example, when a user receives an alert message, the emotion engine monitors the user's response to the message and, if it is estimated that the user is feeling stressed or anxious, can provide additional information and support to alleviate these feelings.

[0491] Specifically, when the emotion engine detects anxiety in a user who has received an urgent alert, the server can prioritize sending supplemental information and emergency response procedures to the user to provide reassurance. Furthermore, if the system determines that the user is relaxed, it can improve the user experience by providing simpler language and lighter advice.

[0492] Users can use a communication terminal to view nutrition plans and alerts optimized by the emotion engine. Furthermore, feedback based on emotional information allows the server to continuously improve its recommendations, supporting pet health management and reducing user stress. Therefore, the entire system provides comprehensive care that considers not only the pet's health but also the user's emotional well-being.

[0493] The following describes the processing flow.

[0494] Step 1:

[0495] The device uses sensors to measure the pet's heart rate, body temperature, and activity level, and stores this data in a buffer. At regular intervals, this data is prepared to be sent to a server over the network.

[0496] Step 2:

[0497] The server receives biometric data transmitted from the terminal. The received data is stored in a database, and an integrity check is performed to confirm that there are no missing or abnormal values.

[0498] Step 3:

[0499] The server uses stored biometric data to compare with statistical models and detect anomalies. If heart rate, body temperature, or other parameters deviate from the normal range, it generates an alert and notifies the user.

[0500] Step 4:

[0501] The server uses an AI engine to automatically generate a nutrition plan, taking into account the pet's health status and past data. The generated plan is then provided to the user as specific meal suggestions and nutrient management.

[0502] Step 5:

[0503] The server retrieves emotion data from the user's communication device. By analyzing voice, text, or other user interactions, the emotion engine estimates the user's emotional state.

[0504] Step 6:

[0505] The emotion engine recognizes the user's emotions, and the server adjusts the tone of alerts and notifications based on that. For example, if the user is feeling stressed, an alert can be sent that is reassuring.

[0506] Step 7:

[0507] Users receive and review alerts, nutritional plans, and emotionally-tailored information via a communication device. Based on the received information, they manage their pet's health and adjust their lifestyle accordingly.

[0508] Step 8:

[0509] User feedback and new sentiment data are sent to the server. The server reflects this data and performs analysis to continuously improve the accuracy and usefulness of the entire system.

[0510] (Example 2)

[0511] 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."

[0512] Traditional pet management systems, while capable of monitoring the health of animals, lacked the ability to optimize responses based on the user's emotional state, resulting in insufficient reassurance and support for users. Furthermore, there was a need to simultaneously achieve pet health management and reduce the emotional burden on users.

[0513] 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.

[0514] In this invention, the server includes means for measuring the animal's biological information and detecting abnormalities, means for notifying the user of a warning based on the abnormality, and means for analyzing the user's emotional state using an emotion engine and optimizing the response. This enables monitoring of the animal's health status and providing accurate information in accordance with the user's emotions.

[0515] "Animals" refers to mammals, birds, and other living creatures kept as pets.

[0516] "Biometric information" refers to data about an animal's internal organs and behavior, such as heart rate, body temperature, and activity level.

[0517] An "abnormality" refers to a fluctuation in biological information that deviates from the normal range, indicating a possible health problem.

[0518] "Warning" refers to an alert message that notifies the user when an abnormality is detected in the animal's health condition.

[0519] A "nutritional plan" refers to a management plan that includes the type and amount of food an animal eats in order to maintain or improve its health.

[0520] "Users" refer to individuals who use this system to manage the health of animals and receive information.

[0521] "Communication devices" refer to electronic devices capable of sending and receiving information, such as smartphones and tablets.

[0522] An "emotion engine" refers to an algorithm or processing system that analyzes a user's voice or text to estimate their emotional state.

[0523] "Response optimization" refers to the process of taking into account the user's emotional state and providing appropriate responses and information.

[0524] This invention is a system that uses animal biological information to detect abnormalities and enables the provision of optimal information tailored to the user's emotional state. The system consists of a terminal, a server, and a user communication device.

[0525] The device is attached to the animal's body and is equipped with sensors to measure biometric information such as heart rate, body temperature, and activity level in real time. The device formats the measured data and transmits it to a server in an encrypted form using wireless communication.

[0526] The server immediately stores biometric data in a database upon receiving it. Simultaneously, it uses a real-time analysis engine to detect anomalies. This engine executes algorithms to identify data fluctuations that exceed a pre-defined normal range. If an anomaly is detected, it generates an alert and immediately notifies the user's communication device.

[0527] An emotion engine is also integrated into the server, analyzing voice and text data received from the user's communication device. This engine uses natural language processing technology to estimate the user's emotional state. Based on the results, it provides appropriate information and responses that are sensitive to the user's emotions. It also uses a generative AI model to generate prompts tailored to the user, customizing the system's responses.

[0528] As a concrete example of its operation, if the server determines that an animal is showing signs of inactivity, the AI ​​model will generate a message such as, "Your pet hasn't been moving around much lately. Would you like to take them for a walk?" and send it to the user. An example of a prompt message would be, "Your pet's body temperature is slightly elevated. How would you like to notify the user?"

[0529] In this way, the system can manage the health of the animals while providing comprehensive support that takes into account the user's feelings.

[0530] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0531] Step 1:

[0532] The device measures the animal's biological information in real time. Sensors capture heart rate, body temperature, and activity levels as input, and this data is formatted and output at regular intervals. Specifically, these sensors are attached to the animal's body, and the data is read and converted into digital signals.

[0533] Step 2:

[0534] The terminal encrypts the measured biometric information and transmits it to the server using a secure protocol. It uses formatted biometric information as input, protects the data with an encryption algorithm, and transmits the data to the server as output. Specifically, the terminal uses wireless communication to transfer data packets to the server.

[0535] Step 3:

[0536] The server stores the received biometric information in a database and detects anomalies using a real-time analysis engine. The input is biometric information transmitted from the terminal, and the anomaly detection algorithm is applied to obtain an anomaly determination result as output. The specific operations are recording to the database and executing the data analysis process.

[0537] Step 4:

[0538] When an anomaly is detected, the server generates an alert and immediately notifies the user's communication device. The input is the anomaly detection result, and based on the nature of the anomaly, it constructs an alert message and sends the alert to the communication device as output. Specifically, it uses automated email sending or push notifications.

[0539] Step 5:

[0540] The user's communication device records the user's response to received alerts. Inputs are voice and text data, which the emotion engine analyzes to estimate the user's emotional state. The system utilizes speech recognition and natural language processing for emotion analysis.

[0541] Step 6:

[0542] The server uses a generative AI model to generate prompt messages based on the estimated user's emotional state, providing the user with optimal information. The input is the user's emotional state, which the generative AI model analyzes and outputs as prompt messages. Specifically, its function is to provide supportive messages and advice aimed at reducing user stress.

[0543] (Application Example 2)

[0544] 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."

[0545] Pet health management is a crucial issue in modern times. However, it's necessary to go beyond simply measuring a pet's biological information and instead use that data to detect abnormalities early and automatically create nutritional plans for pets, thereby reducing the burden on owners. Furthermore, there is a lack of information provided that takes into account the emotional state of owners, so a comprehensive system is needed to alleviate owner stress and anxiety and to foster a smoother relationship with their pets.

[0546] 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.

[0547] In this invention, the server includes means for measuring the pet's biological information and detecting abnormalities based on said biological information; means for notifying the user of an alert based on said abnormality; means for automatically generating a pet's nutrition plan based on said biological information; and means for estimating the user's emotions using emotion analysis means and optimizing information based on said emotions. This makes it possible to provide optimal health management and psychological support for both the owner and the pet.

[0548] "Pet biometric information" refers to data measured to indicate the animal's health status, such as heart rate, body temperature, and activity level.

[0549] An "abnormality" refers to a state of health that is different from the normal state, as detected based on the pet's biological information.

[0550] An "alert" is a warning or cautionary message that is sent to the user when an abnormality is detected in the pet's health condition.

[0551] A "nutritional plan" is a recommended diet and nutrient plan automatically generated based on biological information, with the aim of maintaining the health of pets.

[0552] "Emotion analysis means" refers to a function that estimates a user's emotions by analyzing voice data and text data.

[0553] "Means of optimizing information" refers to a function that adjusts the information provided to reduce user stress and anxiety based on the analyzed emotions of the user.

[0554] A "user communication device" is an electronic device used by the user to receive and display health information and alerts about their pet.

[0555] This invention aims to ensure the safety of pets by measuring their biological information in real time through a pet health management system and sending appropriate alerts to the user when abnormalities are detected.

[0556] The core of the system lies in biometric information acquired by pet robots and wearable devices, emotion analysis means for analyzing the user's emotions, and optimization means for providing information based on these.

[0557] The system is configured as follows: Sensors attached to the pet collect biometric information such as heart rate, body temperature, and activity level. This data is transferred to the user's smartphone via Bluetooth or other means, and then sent to a server in the cloud. The server analyzes the collected data, and if an anomaly is detected, it immediately sends an alert to the user's communication device.

[0558] Furthermore, the server uses a speech recognition platform and text analysis software that utilizes smartphone voice input to understand the user's emotional state as a means of sentiment analysis. Specifically, it analyzes voice data using the OpenAI API and other tools to estimate whether the user is experiencing stress. Based on the results, it appropriately modifies the alert content and provides information that takes the user's emotions into consideration.

[0559] For example, if a pet becomes active at an unexpected time and the user is feeling anxious, the server will send reassuring information and supplementary messages in addition to the usual alerts. Conversely, if the user is deemed relaxed, less urgent information may take priority.

[0560] For example, by using prompts such as, "Generate an alert when the pet's activity level increases," or "Create a reassuring message when the user is feeling stressed," it is possible to request the AI ​​model to optimize its responses. In this way, the system reduces not only the pet's psychological burden but also that of the user, achieving comprehensive care.

[0561] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0562] Step 1:

[0563] The device measures biometric information such as heart rate, body temperature, and activity level through sensors attached to the pet. This biometric information is temporarily stored within the device. The collected data is transmitted to the user's smartphone using Bluetooth. The input is the pet's biometric information, and the output is a data packet containing this information.

[0564] Step 2:

[0565] The smartphone forwards the received biometric data packets to a server in the cloud. The smartphone transmits the information received via Bluetooth over the internet. The input is data packets from the device, and the output is a data stream sent to the server.

[0566] Step 3:

[0567] The server analyzes biometric data received on the cloud and checks for abnormalities. Specifically, it compares the data with pre-defined normal ranges and historical data to detect statistical anomalies. The input is biometric data sent to the cloud, and the output is the analysis result indicating whether or not an abnormality is present.

[0568] Step 4:

[0569] When an anomaly is detected, the server uses a generation AI model to generate an alert message to send to the user. A prompt is used to request the generation AI to create the most appropriate alert content. The input is the anomaly detection information, and the output is the alert message.

[0570] Step 5:

[0571] The terminal notifies the user's communication device of alert messages sent from the server. Smartphones and other communication devices function as receiving devices and display alerts in real time. The input is the alert message sent from the server, and the output is the warning display notified to the user.

[0572] Step 6:

[0573] The user's smartphone collects voice data using its microphone and estimates their current emotional state using emotion analysis tools. The voice data is sent to a server where voice analysis is performed using the OpenAI API. The input is the voice data obtained from the user, and the output is the estimated emotional state.

[0574] Step 7:

[0575] The server generates and provides optimized information to the user based on the estimated user's emotional state. Using a generative AI model, it generates information that takes emotional data into account through prompt messages. The input is the estimated emotional state, and the output is the optimized information.

[0576] 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.

[0577] 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.

[0578] 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.

[0579] [Fourth Embodiment]

[0580] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0581] 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.

[0582] 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).

[0583] 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.

[0584] 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.

[0585] 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).

[0586] 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.

[0587] 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.

[0588] 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.

[0589] 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.

[0590] 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.

[0591] 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.

[0592] 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".

[0593] As an embodiment of this invention, the pet health management system is configured as follows: The system is mainly operated using a server, a terminal attached to the pet, and a user's communication terminal.

[0594] The device is equipped with sensors that continuously measure multiple biometric data points, such as the pet's heart rate, body temperature, and activity level. The device periodically transmits the measurement data to a server via a protocol. Data transmission is essentially real-time, and the device incorporates a filtering function to minimize errors during data transmission.

[0595] The server compares the received biometric information with a statistical model and performs analysis using an algorithm that detects anomalies. If an anomaly is detected, the server generates an alert. For example, if a pet's heart rate significantly exceeds a certain threshold, the server sends a notification to the user's communication device, indicating potential stress or health problems.

[0596] Furthermore, the server uses an AI engine to automatically generate a nutrition plan optimized for each pet's health condition. This nutrition plan is created based on past health and activity data and is proposed to the user via a communication terminal. For example, the nutrition plan is presented in the form of a specific meal menu, offering choices of ingredients containing specific nutrients.

[0597] Users can receive alerts, nutritional plans, and exercise suggestions from the server via their own communication devices and implement them into their pet's life. The system also supports emergency response for pets by providing users with a function to check medical history and instructions for first aid in case of abnormalities.

[0598] In this way, the system comprehensively manages pet health information, allowing users to constantly monitor their pet's current health status and providing peace of mind. As an example of specific measures, for pets with reduced activity levels, the server suggests an appropriate exercise plan and supports users in implementing it. Through these functions, the system significantly reduces the burden on pet owners in managing their pets' health.

[0599] The following describes the processing flow.

[0600] Step 1:

[0601] The device measures the pet's heart rate, body temperature, and activity level in real time and stores this data in a buffer. At regular intervals, it prepares to upload the stored data to the server.

[0602] Step 2:

[0603] Data sent from the terminal is received by the server. The server checks the data's integrity and stores it in the database. This ensures the data quality necessary for the next analysis process.

[0604] Step 3:

[0605] The server analyzes the accumulated biometric data by comparing it with a statistical model. In this process, it identifies outliers that deviate from the normal range and evaluates the type and degree of the anomaly.

[0606] Step 4:

[0607] When the server detects an anomaly, it generates an alert related to that anomaly. The alert includes details of the biometric information in which the anomaly was detected and recommended countermeasures.

[0608] Step 5:

[0609] The generated alerts are sent from the server to the user's communication device. The user receives the alerts through the application and can immediately check the health status of their pet.

[0610] Step 6:

[0611] The server automatically generates a nutrition plan using the pet's biometric information and activity data. This nutrition plan is optimized for the pet's current health condition and also utilizes past data.

[0612] Step 7:

[0613] Users can check the nutrition plan provided on their communication terminal and manage their pet's diet based on specific meal menus and nutrient suggestions.

[0614] Step 8:

[0615] The server continuously optimizes the health management process based on user feedback and new data. This adaptive feedback loop ensures the system is always up-to-date and optimal.

[0616] (Example 1)

[0617] 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".

[0618] There is a challenge in continuously and efficiently monitoring a pet's health, quickly detecting abnormalities, and notifying the user. Furthermore, there is a need to automatically create and provide users with nutritional plans and activity suggestions tailored to each individual pet. In conventional systems, these processes are often complex and burdensome for users.

[0619] 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.

[0620] In this invention, the server includes means for collecting biometric data and transmitting it to a central processing unit via a communication protocol, means for analyzing the biometric data using a statistical model and detecting anomalies, means for immediately distributing the generated warnings to a user communication device, and an artificial intelligence engine that generates personalized nutrition and activity programs based on past biometric data. This enables real-time monitoring of the pet's health status, early detection of anomalies, and the suggestion of countermeasures.

[0621] A "pet device" is a device attached to a pet to collect biometric data, and its role is to measure data such as heart rate, body temperature, and activity level in real time.

[0622] A "communication protocol" is a set of communication rules used by pet devices to transmit data to a central processing unit. It is a system that uses technologies such as Bluetooth and Wi-Fi to transmit data safely and efficiently.

[0623] The "Central Processing Unit" is a device that collects and analyzes biometric data transmitted from pet devices, and is the main component that detects abnormalities and generates warnings based on the analysis results.

[0624] A "statistical model" is a mathematical model used by a central processing unit when analyzing biological data, providing a standard for detecting anomalies by comparing them with past data.

[0625] An "artificial intelligence engine" is a computing system used to learn from past biological data and automatically generate personalized nutrition plans and activity programs.

[0626] A "user communication device" refers to a device that notifies the user of generated warnings and nutrition plans, and includes communication-enabled mobile terminals such as smartphones and tablets.

[0627] In an embodiment for carrying out this invention, the pet health management system consists of a pet device, a central processing unit (server), and a user communication device.

[0628] The pet device is equipped with various sensors to continuously collect biometric data such as heart rate, body temperature, and activity level. These sensors can record the pet's biometric information in real time, and for example, they can measure changes in heart rate when the pet is exercising.

[0629] The server receives biometric data collected from pet devices and analyzes this data using statistical models. Data analysis tools such as Python and R can be used for the analysis. If an anomaly is detected, the server immediately generates a warning and sends a notification to the user's communication device. Furthermore, the server uses a generative AI model to create personalized nutrition and activity plans based on past biometric data. These plans provide specific guidance for maintaining the pet's health.

[0630] Users can receive notifications and suggestions from the server via their communication devices. For example, if a pet's heart rate is abnormal, the user will receive a warning such as, "Your pet's heart rate is high. It may be experiencing stress." This allows the user to take prompt action. Furthermore, specific nutritional plans are provided, such as, "A diet including chicken is recommended to increase protein intake."

[0631] For example, if a pet's activity level decreases, the server will immediately generate an exercise plan such as, "Your pet's activity level has decreased. Let's add a 30-minute walk today," and notify the user.

[0632] Examples of prompt messages include the following:

[0633] "Please describe an AI system that monitors a pet's health and issues warnings when abnormalities are detected. Also, please explain how it suggests optimal nutrition and exercise plans for pets."

[0634] In this way, the system can comprehensively support the daily health of pets.

[0635] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0636] Step 1:

[0637] The device collects biometric data such as heart rate, body temperature, and activity level using sensors attached to the pet. This data is recorded in real time and stored in internal memory at regular intervals. The input is biometric data, and the output is filtered data. Through filtering, noise and errors are removed.

[0638] Step 2:

[0639] The device transmits collected biometric data to a server via a communication protocol (e.g., Bluetooth, Wi-Fi). Data transmission occurs in real time; the input is filtered data, and the output is the data sent to the server. To ensure the stability of data transmission, signal strength and connection status are monitored.

[0640] Step 3:

[0641] The server analyzes biometric data received from the terminal. The input is biometric data transmitted from the terminal, and anomalies are detected using a statistical model; the output is the analysis result. For example, if the heart rate exceeds the normal range, it is flagged as an anomaly.

[0642] Step 4:

[0643] The server generates a warning if an anomaly is detected based on the analysis results. The input is the analysis results of the anomaly data, and the output is the generated warning message. This message may include content such as, "Your pet's heart rate is high. Stress is a possible cause."

[0644] Step 5:

[0645] The server utilizes a generative AI model to automatically generate pet nutrition and activity plans based on historical data. Input is historical biometric and activity data, and output is an individually optimized plan. The nutrition plan includes specific advice such as, "A diet with increased protein is recommended."

[0646] Step 6:

[0647] Users receive warnings and nutritional plans from the server via a communication terminal. The input consists of warning messages and plans sent from the server, and the output is used by the user to manage their pet's health. This allows users to take appropriate action immediately.

[0648] (Application Example 1)

[0649] 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".

[0650] One challenge in pet health management is the difficulty for owners to monitor their pet's health in real time and take appropriate action quickly based on that information. Conventional systems lacked sufficient integration of biometric data measurement and analysis, leading to delays in detecting abnormalities and suggesting preventative measures, which could cause anxiety regarding pet health management. Furthermore, busy owners may find it difficult to frequently check their communication devices, increasing the risk of overlooking their pet's condition.

[0651] 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.

[0652] In this invention, the server includes means for aggregating data in real time and analyzing anomalies using automated machinery available in the home, means for automatically generating a nutrition plan based on biometric information, and means for notifying the user using voice output or visual display. This makes it possible for pet owners to receive important notifications and suggestions regarding their pet's health without having to directly check a communication terminal.

[0653] "Biometric information" refers to various data indicating a pet's health status, such as heart rate, body temperature, and activity level.

[0654] "Abnormal" refers to a state or pattern in which biological information deviates from the set normal range.

[0655] An "alert" is a notification that is triggered when an anomaly is detected, and it is a means of informing the user about the status of their pet.

[0656] A "nutritional plan" is a plan that consists of a meal menu and nutrient recommendations optimized for a pet based on its biological information.

[0657] An "automated machine" is a device that operates in the home and collects, analyzes, and notifies users of biometric information to support pet health management.

[0658] "Audio output or visual display" refers to a means of communicating information to a user, and is a method of presenting alerts or suggestions visually or audibly.

[0659] This invention constructs a system that uses automated household machinery to monitor a pet's health in real time. The server continuously collects data such as heart rate, body temperature, and activity level from biometric sensors attached to the pet. This information is transmitted to the server via a robotic operating system (ROS). The server receives this data and performs analysis to detect anomalies in real time. If an anomaly is detected, the AI ​​engine automatically generates a personalized nutrition plan and notifies the user of the alert through voice output and visual display.

[0660] Specifically, the server utilizes a data analysis module implemented using Python and an AI-powered nutrition plan generation model using TensorFlow. This enables real-time advice tailored to the pet's health condition, along with anomaly detection. For example, if a pet's activity level decreases, the AI-generated nutrition plan will suggest, "Since your pet is less active, let's add some foods to increase its energy."

[0661] By receiving notifications from the system, users can understand their pet's health status and provide more appropriate care. Leveraging the features of the generative AI model, a more specific and practical plan can be provided by using a prompt such as, "Generate a nutrition plan for when the dog's activity level decreases."

[0662] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0663] Step 1:

[0664] The device collects biometric information (heart rate, body temperature, activity level) from the pet using sensors. The input is the pet's biometric data. The device filters this data and formats it to minimize errors. The output is the formatted biometric data.

[0665] Step 2:

[0666] The terminal sends the formatted biometric data to the server via a communication protocol. The input is the formatted biometric data. The terminal packets the data and performs the transmission process. The output is the packets forwarded to the server.

[0667] Step 3:

[0668] The server analyzes biometric data received from the terminal. The input is the biometric data received from the terminal. The server analyzes the data in real time and uses a statistical model to detect anomalies. The output is a determination of whether or not an anomaly was detected.

[0669] Step 4:

[0670] If an anomaly is detected, the server uses an AI engine to generate a customized nutrition plan. The input is the biometric data in which the anomaly was detected. The AI ​​engine references past health data to generate the optimal nutrition plan. The output is the generated nutrition plan.

[0671] Step 5:

[0672] The server notifies the user of the generated nutrition plan and provides audio or visual alerts. Inputs include the nutrition plan and information about any abnormalities. The server parses the data according to the notification format, performs speech synthesis or text generation, and sends it to the user's terminal. Output is a specific notification message to the user.

[0673] 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.

[0674] This invention relates to a system that, in addition to managing the health of pets, includes an engine that recognizes user emotions and optimizes the system's response. This system consists of a server, a terminal attached to the pet, and a user's communication terminal.

[0675] The device measures the pet's heart rate, body temperature, and activity level in real time and transmits this biometric information to a server. The server analyzes the transmitted biometric information, detects abnormalities, and generates alerts as needed. The server also takes the pet's past health data into consideration and automatically generates an optimal nutrition plan.

[0676] In addition, this system incorporates an emotion engine, which has the function of recognizing the user's emotions. This emotion engine analyzes voice and text data acquired from the user's communication terminal to estimate the user's current emotional state. For example, when a user receives an alert message, the emotion engine monitors the user's response to the message and, if it is estimated that the user is feeling stressed or anxious, can provide additional information and support to alleviate these feelings.

[0677] Specifically, when the emotion engine detects anxiety in a user who has received an urgent alert, the server can prioritize sending supplemental information and emergency response procedures to the user to provide reassurance. Furthermore, if the system determines that the user is relaxed, it can improve the user experience by providing simpler language and lighter advice.

[0678] Users can use a communication terminal to view nutrition plans and alerts optimized by the emotion engine. Furthermore, feedback based on emotional information allows the server to continuously improve its recommendations, supporting pet health management and reducing user stress. Therefore, the entire system provides comprehensive care that considers not only the pet's health but also the user's emotional well-being.

[0679] The following describes the processing flow.

[0680] Step 1:

[0681] The device uses sensors to measure the pet's heart rate, body temperature, and activity level, and stores this data in a buffer. At regular intervals, this data is prepared to be sent to a server over the network.

[0682] Step 2:

[0683] The server receives biometric data transmitted from the terminal. The received data is stored in a database, and an integrity check is performed to confirm that there are no missing or abnormal values.

[0684] Step 3:

[0685] The server uses stored biometric data to compare with statistical models and detect anomalies. If heart rate, body temperature, or other parameters deviate from the normal range, it generates an alert and notifies the user.

[0686] Step 4:

[0687] The server uses an AI engine to automatically generate a nutrition plan, taking into account the pet's health status and past data. The generated plan is then provided to the user as specific meal suggestions and nutrient management.

[0688] Step 5:

[0689] The server retrieves emotion data from the user's communication device. By analyzing voice, text, or other user interactions, the emotion engine estimates the user's emotional state.

[0690] Step 6:

[0691] The emotion engine recognizes the user's emotions, and the server adjusts the tone of alerts and notifications based on that. For example, if the user is feeling stressed, an alert can be sent that is reassuring.

[0692] Step 7:

[0693] Users receive and review alerts, nutritional plans, and emotionally-tailored information via a communication device. Based on the received information, they manage their pet's health and adjust their lifestyle accordingly.

[0694] Step 8:

[0695] User feedback and new sentiment data are sent to the server. The server reflects this data and performs analysis to continuously improve the accuracy and usefulness of the entire system.

[0696] (Example 2)

[0697] 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".

[0698] Traditional pet management systems, while capable of monitoring the health of animals, lacked the ability to optimize responses based on the user's emotional state, resulting in insufficient reassurance and support for users. Furthermore, there was a need to simultaneously achieve pet health management and reduce the emotional burden on users.

[0699] 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.

[0700] In this invention, the server includes means for measuring the animal's biological information and detecting abnormalities, means for notifying the user of a warning based on the abnormality, and means for analyzing the user's emotional state using an emotion engine and optimizing the response. This enables monitoring of the animal's health status and providing accurate information in accordance with the user's emotions.

[0701] "Animals" refers to mammals, birds, and other living creatures kept as pets.

[0702] "Biometric information" refers to data about an animal's internal organs and behavior, such as heart rate, body temperature, and activity level.

[0703] An "abnormality" refers to a fluctuation in biological information that deviates from the normal range, indicating a possible health problem.

[0704] "Warning" refers to an alert message that notifies the user when an abnormality is detected in the animal's health condition.

[0705] A "nutritional plan" refers to a management plan that includes the type and amount of food an animal eats in order to maintain or improve its health.

[0706] "Users" refer to individuals who use this system to manage the health of animals and receive information.

[0707] "Communication devices" refer to electronic devices capable of sending and receiving information, such as smartphones and tablets.

[0708] An "emotion engine" refers to an algorithm or processing system that analyzes a user's voice or text to estimate their emotional state.

[0709] "Response optimization" refers to the process of taking into account the user's emotional state and providing appropriate responses and information.

[0710] This invention is a system that uses animal biological information to detect abnormalities and enables the provision of optimal information tailored to the user's emotional state. The system consists of a terminal, a server, and a user communication device.

[0711] The device is attached to the animal's body and is equipped with sensors to measure biometric information such as heart rate, body temperature, and activity level in real time. The device formats the measured data and transmits it to a server in an encrypted form using wireless communication.

[0712] The server immediately stores biometric data in a database upon receiving it. Simultaneously, it uses a real-time analysis engine to detect anomalies. This engine executes algorithms to identify data fluctuations that exceed a pre-defined normal range. If an anomaly is detected, it generates an alert and immediately notifies the user's communication device.

[0713] An emotion engine is also integrated into the server, analyzing voice and text data received from the user's communication device. This engine uses natural language processing technology to estimate the user's emotional state. Based on the results, it provides appropriate information and responses that are sensitive to the user's emotions. It also uses a generative AI model to generate prompts tailored to the user, customizing the system's responses.

[0714] As a concrete example of its operation, if the server determines that an animal is showing signs of inactivity, the AI ​​model will generate a message such as, "Your pet hasn't been moving around much lately. Would you like to take them for a walk?" and send it to the user. An example of a prompt message would be, "Your pet's body temperature is slightly elevated. How would you like to notify the user?"

[0715] In this way, the system can manage the health of the animals while providing comprehensive support that takes into account the user's feelings.

[0716] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0717] Step 1:

[0718] The device measures the animal's biological information in real time. Sensors capture heart rate, body temperature, and activity levels as input, and this data is formatted and output at regular intervals. Specifically, these sensors are attached to the animal's body, and the data is read and converted into digital signals.

[0719] Step 2:

[0720] The terminal encrypts the measured biometric information and transmits it to the server using a secure protocol. It uses formatted biometric information as input, protects the data with an encryption algorithm, and transmits the data to the server as output. Specifically, the terminal uses wireless communication to transfer data packets to the server.

[0721] Step 3:

[0722] The server stores the received biometric information in a database and detects anomalies using a real-time analysis engine. The input is biometric information transmitted from the terminal, and the anomaly detection algorithm is applied to obtain an anomaly determination result as output. The specific operations are recording to the database and executing the data analysis process.

[0723] Step 4:

[0724] When an anomaly is detected, the server generates an alert and immediately notifies the user's communication device. The input is the anomaly detection result, and based on the nature of the anomaly, it constructs an alert message and sends the alert to the communication device as output. Specifically, it uses automated email sending or push notifications.

[0725] Step 5:

[0726] The user's communication device records the user's response to received alerts. Inputs are voice and text data, which the emotion engine analyzes to estimate the user's emotional state. The system utilizes speech recognition and natural language processing for emotion analysis.

[0727] Step 6:

[0728] The server uses a generative AI model to generate prompt messages based on the estimated user's emotional state, providing the user with optimal information. The input is the user's emotional state, which the generative AI model analyzes and outputs as prompt messages. Specifically, its function is to provide supportive messages and advice aimed at reducing user stress.

[0729] (Application Example 2)

[0730] 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".

[0731] Pet health management is a crucial issue in modern times. However, it's necessary to go beyond simply measuring a pet's biological information and instead use that data to detect abnormalities early and automatically create nutritional plans for pets, thereby reducing the burden on owners. Furthermore, there is a lack of information provided that takes into account the emotional state of owners, so a comprehensive system is needed to alleviate owner stress and anxiety and to foster a smoother relationship with their pets.

[0732] 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.

[0733] In this invention, the server includes means for measuring the pet's biological information and detecting abnormalities based on said biological information; means for notifying the user of an alert based on said abnormality; means for automatically generating a pet's nutrition plan based on said biological information; and means for estimating the user's emotions using emotion analysis means and optimizing information based on said emotions. This makes it possible to provide optimal health management and psychological support for both the owner and the pet.

[0734] "Pet biometric information" refers to data measured to indicate the animal's health status, such as heart rate, body temperature, and activity level.

[0735] An "abnormality" refers to a state of health that is different from the normal state, as detected based on the pet's biological information.

[0736] An "alert" is a warning or cautionary message that is sent to the user when an abnormality is detected in the pet's health condition.

[0737] A "nutritional plan" is a recommended diet and nutrient plan automatically generated based on biological information, with the aim of maintaining the health of pets.

[0738] "Emotion analysis means" refers to a function that estimates a user's emotions by analyzing voice data and text data.

[0739] "Means of optimizing information" refers to a function that adjusts the information provided to reduce user stress and anxiety based on the analyzed emotions of the user.

[0740] A "user communication device" is an electronic device used by the user to receive and display health information and alerts about their pet.

[0741] This invention aims to ensure the safety of pets by measuring their biological information in real time through a pet health management system and sending appropriate alerts to the user when abnormalities are detected.

[0742] The core of the system lies in biometric information acquired by pet robots and wearable devices, emotion analysis means for analyzing the user's emotions, and optimization means for providing information based on these.

[0743] The system is configured as follows: Sensors attached to the pet collect biometric information such as heart rate, body temperature, and activity level. This data is transferred to the user's smartphone via Bluetooth or other means, and then sent to a server in the cloud. The server analyzes the collected data, and if an anomaly is detected, it immediately sends an alert to the user's communication device.

[0744] Furthermore, the server uses a speech recognition platform and text analysis software that utilizes smartphone voice input to understand the user's emotional state as a means of sentiment analysis. Specifically, it analyzes voice data using the OpenAI API and other tools to estimate whether the user is experiencing stress. Based on the results, it appropriately modifies the alert content and provides information that takes the user's emotions into consideration.

[0745] For example, if a pet becomes active at an unexpected time and the user is feeling anxious, the server will send reassuring information and supplementary messages in addition to the usual alerts. Conversely, if the user is deemed relaxed, less urgent information may take priority.

[0746] For example, by using prompts such as, "Generate an alert when the pet's activity level increases," or "Create a reassuring message when the user is feeling stressed," it is possible to request the AI ​​model to optimize its responses. In this way, the system reduces not only the pet's psychological burden but also that of the user, achieving comprehensive care.

[0747] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0748] Step 1:

[0749] The device measures biometric information such as heart rate, body temperature, and activity level through sensors attached to the pet. This biometric information is temporarily stored within the device. The collected data is transmitted to the user's smartphone using Bluetooth. The input is the pet's biometric information, and the output is a data packet containing this information.

[0750] Step 2:

[0751] The smartphone forwards the received biometric data packets to a server in the cloud. The smartphone transmits the information received via Bluetooth over the internet. The input is data packets from the device, and the output is a data stream sent to the server.

[0752] Step 3:

[0753] The server analyzes biometric data received on the cloud and checks for abnormalities. Specifically, it compares the data with pre-defined normal ranges and historical data to detect statistical anomalies. The input is biometric data sent to the cloud, and the output is the analysis result indicating whether or not an abnormality is present.

[0754] Step 4:

[0755] When an anomaly is detected, the server uses a generation AI model to generate an alert message to send to the user. A prompt is used to request the generation AI to create the most appropriate alert content. The input is the anomaly detection information, and the output is the alert message.

[0756] Step 5:

[0757] The terminal notifies the user's communication device of alert messages sent from the server. Smartphones and other communication devices function as receiving devices and display alerts in real time. The input is the alert message sent from the server, and the output is the warning display notified to the user.

[0758] Step 6:

[0759] The user's smartphone collects voice data using its microphone and estimates their current emotional state using emotion analysis tools. The voice data is sent to a server where voice analysis is performed using the OpenAI API. The input is the voice data obtained from the user, and the output is the estimated emotional state.

[0760] Step 7:

[0761] The server generates and provides optimized information to the user based on the estimated user's emotional state. Using a generative AI model, it generates information that takes emotional data into account through prompt messages. The input is the estimated emotional state, and the output is the optimized information.

[0762] 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.

[0763] 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.

[0764] 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 robot 414.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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."

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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 to be incorporated by reference.

[0783] The following is further disclosed regarding the embodiments described above.

[0784] (Claim 1)

[0785] A means for measuring the biological information of a pet and detecting abnormalities based on said biological information,

[0786] A means for notifying the user of an alert based on the anomaly,

[0787] A means for automatically generating a pet's nutrition plan based on the said biological information,

[0788] Means for providing the nutrition plan to the user,

[0789] A system that includes this.

[0790] (Claim 2)

[0791] The system according to claim 1, wherein the aforementioned biological information includes the pet's heart rate, body temperature, and activity level.

[0792] (Claim 3)

[0793] The system according to claim 1, wherein the aforementioned alert is transmitted to the user's communication terminal in real time.

[0794] "Example 1"

[0795] (Claim 1)

[0796] A means for a pet device to collect biometric data and transmit said biometric data to a central processing unit via a communication protocol,

[0797] The central processing unit includes means for analyzing the biological data using a statistical model and detecting anomalies,

[0798] A means by which a warning is generated in response to the abnormality and the warning is immediately delivered to the user communication device,

[0799] Means for providing the generated warnings and nutritional plans to the user communication device,

[0800] Means including an artificial intelligence engine that generates personalized pet nutrition and activity programs based on past biometric data,

[0801] A system that includes this.

[0802] (Claim 2)

[0803] The system according to claim 1, wherein the biological data includes information on the pet's circulatory system, temperature, and movement activity.

[0804] (Claim 3)

[0805] The system according to claim 1, wherein the aforementioned warning is transmitted to a user communication device in real time.

[0806] "Application Example 1"

[0807] (Claim 1)

[0808] A means for measuring the biological information of a pet and detecting abnormalities based on said biological information,

[0809] A means for notifying the user of an alert based on the anomaly,

[0810] A means for automatically generating a pet's nutrition plan based on the said biological information,

[0811] Automated machines available for use in the home provide a means to collect data in real time and analyze anomalies,

[0812] Means for providing the nutrition plan to the user,

[0813] Means for notifying the user using audio output or visual display,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, wherein the aforementioned biological information includes the pet's heart rate, body temperature, and activity level.

[0817] (Claim 3)

[0818] The system according to claim 1, wherein the alert is not only transmitted in real time to the user's communication terminal, but is also notified via a physical automated machine.

[0819] "Example 2 of combining an emotion engine"

[0820] (Claim 1)

[0821] A means for measuring the biological information of an animal and detecting abnormalities based on said biological information,

[0822] A means for notifying the user of a warning based on the abnormality,

[0823] A means for automatically generating an animal nutrition plan based on the said biological information,

[0824] Means for providing the nutrition plan to the user,

[0825] A means for analyzing the user's emotional state and optimizing the response based on that emotional state,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, wherein the biological information includes the heart rate, body temperature, and activity level of an animal.

[0829] (Claim 3)

[0830] The system according to claim 1, wherein the aforementioned warning is immediately transmitted to the user's communication device.

[0831] "Application example 2 when combining with an emotional engine"

[0832] (Claim 1)

[0833] A means for measuring the biological information of a pet and detecting abnormalities based on said biological information,

[0834] A means for notifying the user of an alert based on the anomaly,

[0835] A means for automatically generating a pet's nutrition plan based on the said biological information,

[0836] Means for providing the nutrition plan to the user,

[0837] A means for estimating the user's emotions using emotion analysis means and optimizing information based on those emotions,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, wherein the biometric information includes the pet's heart rate, body temperature, and activity level, and the emotion analysis means uses voice data and text data.

[0841] (Claim 3)

[0842] The system according to claim 1, wherein the aforementioned alerts and optimized information are transmitted to the user's communication device in real time. [Explanation of Symbols]

[0843] 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 measuring the biological information of a pet and detecting abnormalities based on said biological information, A means for notifying the user of an alert based on the anomaly, A means for automatically generating a pet's nutrition plan based on the said biological information, Automated machines available for use in the home provide a means to collect data in real time and analyze anomalies, Means for providing the nutrition plan to the user, Means for notifying the user using audio output or visual display, A system that includes this.

2. The system according to claim 1, wherein the aforementioned biological information includes the pet's heart rate, body temperature, and activity level.

3. The system according to claim 1, wherein the alert is not only transmitted to the user's communication terminal in real time, but is also notified via a physical automated machine.

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