system

Abstract

We provide the system. [Solution] A means of acquiring data from a vital sign monitoring device attached to an animal, A means of analyzing acquired data in real time and detecting anomalies, A means of issuing an alert in response to detected anomalies, Means for generating a diet and exercise plan based on the health status of an animal, A means of managing medical appointments and medical history, Means of providing first aid and contact information in emergencies, 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, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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] Properly managing a pet's health on a daily basis is a burdensome task for the owner. In particular, it has been difficult with conventional means to constantly monitor a pet's vital signs and detect abnormalities early. Furthermore, it is not easy to create a diet and exercise plan according to a pet's individual health condition and to perform appropriate medical management. The present invention addresses these problems and aims to efficiently and effectively manage a pet's health.

Means for Solving the Problems

[0005] This invention provides a means for acquiring data using a vital sign monitoring device attached to an animal and analyzing that data in real time. This enables early detection of abnormalities and provides a function to issue an alert when an abnormality is detected. It also provides a means for generating diet and exercise plans based on the animal's health condition, and further has a function for managing veterinary appointments and medical history. In addition, by combining this with means for providing first aid and contact information in emergencies, it is possible to comprehensively manage the health of pets.

[0006] A "vital sign monitoring device attached to an animal" is a device that is attached to an animal's body to continuously detect vital signs such as heart rate, body temperature, and activity level.

[0007] "Means for acquiring data" refers to an apparatus or method for collecting life sign information collected from the monitoring device and recording it in digital format.

[0008] "Means for analyzing data in real time" refers to a device or method for immediately processing collected vital sign information and determining whether it falls within the normal range by comparing it with reference values.

[0009] "Means for detecting abnormalities" refers to a device or method that has the function of identifying and reporting a condition when the analyzed data deviates from a set normal range.

[0010] "Means for issuing alerts" refers to a device or method for sending a warning message to a user based on a detected anomaly.

[0011] "Means for generating diet and exercise plans" refers to an apparatus or method for creating individual nutrition and activity recommendations based on animal health data.

[0012] "Means for managing medical appointments and medical history" refers to devices or methods for planning an animal's medical schedule and tracking past medical records.

[0013] "Means of providing first aid and contact information in emergencies" refers to a device or method that provides instructions and contact information to animal owners in order to enable them to take prompt action in the event of an emergency. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the 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.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the 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.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention provides a series of interconnected functions as a system for pet owners to effectively manage the health of their pets.

[0036] This system has the ability to collect data from a vital signs monitoring device attached to a pet. First, the terminal communicates with this device to obtain the pet's heart rate, body temperature, and activity level. The acquired data is then transmitted to the server in real time.

[0037] Upon receiving the transmitted data, the server immediately stores it in an analysis module and detects anomalies based on health standards. If this analysis process identifies a deviation from the standard values, the server generates an alert and sends a warning to the user's smartphone.

[0038] Furthermore, the server generates customized diet and exercise plans tailored to the pet's health condition. This allows users to incorporate specific care plans into their daily lives. These plans include recommendations for maintaining normal health and are adjusted to the pet's individual needs.

[0039] The terminal also includes features to support veterinarian appointment management, allowing users to plan appointments smoothly. Treatment history is managed digitally, and users can easily access past treatment records.

[0040] In addition, in the event of an emergency, the device has an interface that quickly provides the user with first aid procedures and nearby emergency contact information. This enables the user to take appropriate action.

[0041] For example, if the device detects a sudden rise in a pet's body temperature during normal health monitoring, the server will generate an anomaly detection alert and send the user instructions such as, "Your pet's body temperature is rising. Please let them rest in a cool place and visit a veterinarian if necessary." The emergency contact information included in this notification will provide contact details for a nearby animal hospital.

[0042] In this way, the system of the present invention highly automates pet health management, reducing the burden on pet owners while contributing to the well-being of pets.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The device connects to a vital signs monitoring device and acquires the pet's heart rate, body temperature, and activity level at regular intervals.

[0046] Step 2:

[0047] The device temporarily stores the data it acquires locally and sends it to the server at regular intervals.

[0048] Step 3:

[0049] The server saves the received data to the database, and the analysis module begins analyzing the data.

[0050] Step 4:

[0051] The server compares the data to a baseline value and sets an anomaly flag if it detects an anomaly.

[0052] Step 5:

[0053] If the server detects an anomaly, it generates an alert and calls an API to send a warning message to the user's smartphone.

[0054] Step 6:

[0055] The user checks the alert notification received on their smartphone and takes appropriate action according to the instructions.

[0056] Step 7:

[0057] The server generates a customized diet and exercise plan based on the pet's health condition, using the analysis results.

[0058] Step 8:

[0059] The server generates a plan, which is then provided to the user, and they are encouraged to use it for their daily care.

[0060] Step 9:

[0061] The terminal automatically makes appointments with veterinarians through the reservation system based on user instructions.

[0062] Step 10:

[0063] The server updates the medical history, allowing users to review past medical data as needed.

[0064] (Example 1)

[0065] 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."

[0066] In recent years, pet owners' interest in pet health management has increased, and there is a demand for technological solutions to provide appropriate care. However, while devices for monitoring pet vital signs exist on the market, systems that comprehensively provide data analysis, detection of health anomalies, and the provision of customized health care plans are not yet widespread. Furthermore, there is a lack of real-time information to support rapid response in the event of an emergency, and a lack of secure data management methods. As a result, the effective means by which pet owners can provide the best possible care for their pets are limited.

[0067] 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.

[0068] In this invention, the server includes means for analyzing biometric information in real time and identifying abnormalities, means for transmitting warnings, and means for generating customized health care plans. This allows pet owners to understand their pet's health status in detail and apply individualized care plans.

[0069] A "biological monitoring device" is a device used to measure biological information such as heart rate, body temperature, and activity level of living organisms.

[0070] "Means for acquiring information" refers to methods or techniques for collecting biological information from a device.

[0071] "Means of real-time analysis" refers to methods or technologies for processing and analyzing acquired information immediately.

[0072] "Means for identifying abnormalities" refers to methods or techniques for recognizing a condition that deviates from health standards based on analyzed information.

[0073] "Means for sending warnings" refers to methods or technologies for notifying users when an anomaly is detected.

[0074] "Means for generating nutrition and exercise plans" refers to methods or techniques for creating dietary and exercise plans tailored to the health condition of an animal.

[0075] "Means for managing medical appointments and medical history" refers to methods or technologies for making appointments for medical consultations and for storing and referencing past medical information.

[0076] "Means of providing first aid and contact information" refers to methods or technologies for providing users with information on how to respond and contact information in an emergency.

[0077] "Means for securely transferring and storing information" refers to methods or technologies for transferring acquired information while protecting it from third parties and for long-term storage.

[0078] A "generative AI model" is an artificial intelligence-powered model that generates customized care plans based on a large amount of data.

[0079] This invention relates to a system that provides advanced support for animal health management. This system acquires and analyzes animal health data through various means and provides useful information to the user.

[0080] The terminal acquires information from a biometric monitoring device attached to the animal. This includes hardware and programs for periodically collecting biometric data such as heart rate, body temperature, and activity level via Bluetooth. The terminal temporarily stores the collected data and transmits it to a server via Wi-Fi or a cellular network.

[0081] The server stores the received data in a database and analyzes it in real time using an analysis program written in Python. This analysis process determines whether there are abnormalities based on the acquired biometric information and generates warnings if the data deviates from the set health standards. A health management plan, utilizing a generated AI model, is customized based on this data to create specific plans regarding the animal's diet and exercise.

[0082] Users can receive alerts and health management plans through a smartphone app. The app also has additional features to help manage medical appointments and view past medical history. In the event of an emergency, first aid procedures and contact information for nearby medical facilities will be displayed on the device, allowing users to respond quickly.

[0083] For example, if a pet's body temperature rises rapidly, the device detects this and sends data to the server. The server analyzes the anomaly and notifies the user via the smartphone app with instructions such as, "Your pet's body temperature is rising. Let them rest in a cool place and visit a veterinarian if necessary," along with contact information for nearby animal hospitals.

[0084] An example of a prompt message is, "Collect vital data from your pet and explain the specific processing steps for detecting anomalies and generating a care plan based on that data." This allows users to understand their pet's health status in a timely manner and take necessary actions flexibly.

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The terminal connects to a biometric monitoring device attached to an animal via Bluetooth to acquire biometric data. During this process, biometric information such as heart rate, body temperature, and activity level is received as input. Based on this information, the terminal temporarily stores the data in its memory. The acquired data is then prepared for real-time transmission to a server.

[0088] Step 2:

[0089] The device transmits acquired biometric data to the server via Wi-Fi or a mobile communication network. Temporarily stored data is used as input, and encrypted data is sent to the server as output. Security measures are implemented to ensure the confidentiality of the information during this process.

[0090] Step 3:

[0091] The server collects received biometric data and stores it in a database. The input to this database is the biometric information received from the terminal, and the output is the information securely stored in storage. The server then prepares this data to provide to the analysis program.

[0092] Step 4:

[0093] The server uses an analysis program written in Python to analyze the stored data in real time. It receives biometric information read from a database as input and outputs anomaly detection results. The analysis uses an anomaly detection algorithm to identify data that deviates from the set health standards.

[0094] Step 5:

[0095] If an anomaly is detected, the server generates a warning and sends a push notification to the user's smartphone app. The input is the anomaly detection result from the analysis, and the output is the content of the notification to the user. This notification includes specific advice and emergency response procedures.

[0096] Step 6:

[0097] The server utilizes a generative AI model to generate individualized health care plans based on animal health data. The input is collected biometric data, and the output is a individually customized diet and exercise plan.

[0098] Step 7:

[0099] Users receive notifications of anomalies and health care plans through a smartphone app. Based on this information, users can care for their animals and flexibly adjust necessary actions. The input is notifications from the server, and the output is the user's action plan.

[0100] (Application Example 1)

[0101] 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."

[0102] In modern times, pet health management is a crucial issue for many pet owners. However, constantly monitoring a pet's health, quickly detecting abnormalities, and taking appropriate action is not easy. Furthermore, providing individualized health management plans and responding quickly in emergencies requires specialized knowledge and continuous effort. This increases the burden on pet owners and increases the risk of pets' health being poorly managed. Therefore, there is a need for automated systems that reduce the burden on pet owners and effectively manage pets' health.

[0103] 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.

[0104] In this invention, the server includes communication means for receiving animal biometric information and transmitting the information to a cloud server, means for providing data analysis and notification services on the cloud, and means for automatically generating individually tailored health management plans. This makes it possible to monitor the health status of pets in real time and to respond quickly and accurately when abnormalities occur.

[0105] A "biological signal monitoring device" is a device used to continuously acquire biological information such as the heart rate, body temperature, and activity level of animals.

[0106] "Real-time analysis" is an analytical method that processes acquired data almost instantly to quickly detect anomalies and patterns.

[0107] "Issuing a warning" is the process of sending a notification to the user to alert them when an anomaly is detected.

[0108] "Nutritional and activity plan development" refers to the act of creating individually tailored dietary and exercise plans to maintain or improve the health of animals.

[0109] A "cloud server" is a remote server that stores, processes, and manages data via the internet.

[0110] "Data transmission and protection measures" refer to technologies and protocols that securely transfer acquired information and protect it from unauthorized external access.

[0111] A "notification service" is a communication function that automates the delivery of information and warnings to users.

[0112] An "individually tailored health management plan" is a plan for maintaining the health of each animal that takes into account its individual characteristics and condition and is optimized for each animal.

[0113] To realize this invention, a biosignal monitoring device to be attached to a pet is first required. This device continuously acquires data such as heart rate, body temperature, and activity level, and transmits the data to the user's smartphone or robot terminal via wireless communication such as Bluetooth. The terminal uploads this data to a cloud server in real time.

[0114] Upon receiving this data, the cloud server performs real-time analysis using advanced data analysis technologies. Specifically, it monitors the health status using machine learning algorithms and detects anomalies. This analysis utilizes cloud platforms such as Amazon Web Services (AWS®). If an anomaly is detected, the cloud server promptly sends a notification to pre-registered users to issue a warning. Firebase Cloud Messaging is used for this notification function.

[0115] Furthermore, the cloud server automatically generates individually tailored nutrition and activity plans based on the acquired data. These plans are sent to the user's smartphone, robot, or other device, allowing the user to manage their pet's health daily based on them. The server also has an interface that can instantly provide emergency first-aid information and contact information for nearby veterinary hospitals.

[0116] For example, if a pet's body temperature is detected to be higher than normal, the server will send a message to the user saying, "Your pet's body temperature is elevated. Please have them rest in a cool place and visit a veterinarian if necessary." An example of a prompt message would be, "Your pet's heart rate is elevated. Please generate a guide on how to respond." This allows pet owners to take appropriate action quickly.

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The device receives real-time data such as heart rate, body temperature, and activity level from a biosignal monitoring device attached to the pet. This data is acquired via Bluetooth communication. The input is biosignal data from the monitoring device, and the output is biosignal data aggregated in the device.

[0120] Step 2:

[0121] The device sends the received biometric data to a cloud server. This process utilizes cloud services such as AWS Lambda to ensure the data is securely uploaded. The input is the biometric data on the device, and the output is the biometric data stored in the cloud.

[0122] Step 3:

[0123] The server analyzes the received biometric data and detects anomalies. Machine learning algorithms are applied to this analysis to detect outliers. The input is biometric data stored in the cloud, and the output is a determination of whether or not an anomaly is present.

[0124] Step 4:

[0125] The server sends a warning message to the user's device if an anomaly is detected. Firebase Cloud Messaging is used to quickly notify the user. The input is the anomaly detection result, and the output is the warning notification sent to the user.

[0126] Step 5:

[0127] The server generates an individualized nutrition and activity plan for the pet based on biometric data. The generated plan is sent to the user's terminal, where the user can view it on the interface. The input is biometric data, and the output is the generated plan.

[0128] Step 6:

[0129] In the event of an emergency, the device provides the user with first-aid instructions and contact information for nearby veterinary hospitals. This allows the user to take necessary actions quickly. Input is an emergency alert from the server, and output is first-aid information and contact information.

[0130] 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.

[0131] This invention incorporates a function that takes user emotions into a system for managing pet health. The system aims to improve pet health management while simultaneously optimizing pet care according to the user's emotional state.

[0132] This system begins by acquiring data from a vital signs monitoring device attached to the pet, which is then received by a terminal. The acquired data is sent to a server, where data such as heart rate and body temperature are analyzed in real time. If an abnormality is detected, an alert is immediately sent to the user, allowing them to check the pet's current condition.

[0133] A distinctive feature of this system is the incorporation of an emotion engine that detects the user's emotions. The emotion engine uses the user's smart device's camera and microphone to analyze their emotional state from their facial expressions and tone of voice. The server has the function to adjust the pet's care plan based on these analysis results. For example, if the user is feeling stressed, it will suggest relaxing exercises and games for the pet.

[0134] For example, if the device detects an increase in the pet's body temperature and the emotion engine simultaneously detects that the user is feeling fatigued, the server will send an integrated alert to the user stating, "Your pet's body temperature is a little high. Please let it rest in a cool environment and observe its condition. Also, please take a break and relax." In this way, the system can provide information that takes the user's emotional state into account.

[0135] Furthermore, the appointment scheduling and medical history management functions are also adjusted based on the results of the emotion engine. For example, when the user is detected as busy or stressed, appointment reminders are sent earlier than usual, allowing for a more relaxed response to the pet's health.

[0136] Thus, the present invention provides an interactive care system that manages pets according to their health condition while also taking into account the user's emotions.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] The device acquires data from a vital signs monitoring device attached to the pet, periodically collecting information such as heart rate, body temperature, and activity level.

[0140] Step 2:

[0141] The device collects data, which is then sent to the server in real time and securely stored in a database.

[0142] Step 3:

[0143] The server analyzes the received vital sign data of the pet and detects abnormalities by comparing them to the normal range.

[0144] Step 4:

[0145] If the server detects an anomaly, it will generate an alert and send a notification to the user's smartphone. The notification will include specific instructions on how to address the issue.

[0146] Step 5:

[0147] The user's smart device uses its camera and microphone to collect emotions from facial expressions and voice data.

[0148] Step 6:

[0149] The server uses an emotion engine to analyze collected facial and voice data to determine the user's emotional state (e.g., stress, fatigue, calmness, etc.).

[0150] Step 7:

[0151] The server takes the user's emotional state into account and automatically adjusts the pet's care plan, for example, providing simple exercises or games that can be played with the pet if relaxation is needed.

[0152] Step 8:

[0153] The server sends a customized care plan to the user's device and suggests using it for daily pet care.

[0154] Step 9:

[0155] The device automatically schedules appointments based on the user's instructions, taking their emotional state into consideration. If necessary, it will send appointment reminders in advance.

[0156] Step 10:

[0157] Users receive alerts and reminders that take their emotional state into consideration, allowing for more effective pet health management.

[0158] (Example 2)

[0159] 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".

[0160] In modern society, animal health management is becoming increasingly important, but simply monitoring an animal's vital signs is insufficient. To optimally manage an animal's health, it is necessary to consider both the animal's physical information and the owner's psychological state. Furthermore, a system is needed to facilitate a rapid and appropriate response when an abnormality is detected. Therefore, this invention proposes a system that monitors both the animal's vital signs and the owner's emotional state to provide comprehensive health management.

[0161] 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.

[0162] In this invention, the server includes means for acquiring information from a biosignal monitoring device attached to an animal, means for immediately analyzing the acquired information and detecting abnormalities, and means for using an emotion analysis device for analyzing the user's emotions. This makes it possible to comprehensively evaluate the animal's health status and the user's emotional state and provide an individualized care plan.

[0163] A "biometric signal monitoring device" is a device that uses sensor technology to collect bodily information such as heart rate and body temperature when attached to an animal.

[0164] "Means of acquiring information" refers to the function of transmitting data obtained from sensors to a terminal, thereby enabling data collection.

[0165] "Means for immediate analysis and anomaly detection" refers to a function that analyzes acquired data in real time, identifies values ​​that deviate from the standard, and issues a warning.

[0166] "Methods using emotion analysis devices" refer to functions that use the camera and microphone of a smart device to analyze the user's facial expressions and voice and identify their emotional state.

[0167] "Providing individualized care plans" means providing specific and customized health management guidance and suggestions based on the animal's health condition and the user's emotional state.

[0168] "Information transfer and storage means" refers to technology for securely transmitting acquired information to other devices and storing it in a format that can be accessed later.

[0169] To implement this invention, the terminal first acquires vital data such as heart rate and body temperature from a biosignal monitoring device attached to an animal. This biosignal monitoring device is equipped with communication technologies such as Bluetooth or Wi-Fi and has the function of wirelessly transmitting data to the terminal. The terminal receives this data and transmits it to a server via a secure protocol (e.g., HTTPS).

[0170] The server analyzes acquired vital data in real time and detects abnormalities by comparing them to baseline values. This analysis uses data mining and machine learning algorithms, and has the function to immediately send a warning to the user when an abnormality is detected.

[0171] Furthermore, to take into account the user's emotional state, the device uses its camera and microphone as a smart device to capture the user's facial expressions and voice tone. This data is sent to a server, which uses an emotion analysis engine to analyze the user's emotional state and incorporate it into the pet care plan.

[0172] For example, if a pet's body temperature rises and the emotional engine simultaneously detects a high stress level in the user, the server will send an alert stating, "Your pet's body temperature is a little high. We recommend taking steps to cool it down and for you to relax." In this way, the system integrates animal health data with the user's emotional state to provide a more effective care plan.

[0173] The following prompt statements can be used as example inputs to a generative AI model.

[0174] "Please suggest solutions for when a pet's body temperature is high and the user is experiencing stress."

[0175] This allows the generated AI model to provide appropriate suggestions based on the situation. The system comprehensively supports pet health management, including the user's psychological factors. As a result, users can receive appropriate care tailored to their individual circumstances.

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] The device acquires vital data from a biosignal monitoring device attached to the animal. Specifically, the device receives data such as heart rate and body temperature via Bluetooth or Wi-Fi. In this process, vital data is received as input and prepared for the next step.

[0179] Step 2:

[0180] The terminal sends the acquired vital data to the server. The input is vital data, which is sent to the server using a secure protocol (e.g., HTTPS). The output here is the server receiving the data. This operation enables the next step of real-time analysis.

[0181] Step 3:

[0182] The server analyzes the vital data it receives. The input data includes heart rate and body temperature transmitted from the terminal, and the server compares this to standard health indicators to detect abnormalities. The server generates the analysis results as output and prepares subsequent actions if an abnormality is detected.

[0183] Step 4:

[0184] The device uses the smart device's camera and microphone to acquire user emotion data. The input includes user facial expressions and voice data, which the device collects and prepares to send to a server. The output of this step is a dataset containing emotion data.

[0185] Step 5:

[0186] The server analyzes the user's emotional data. The server receives facial expressions and voice tone as input data and analyzes them using an emotion analysis engine. This process identifies the user's emotional state and generates an emotional state report.

[0187] Step 6:

[0188] The server integrates vital data and emotional data to generate an appropriate care plan. The input is the analysis results obtained in the previous step, which are used to create the pet care plan and alert messages for the user. The output of this step is the adjusted care plan and alerts.

[0189] Step 7:

[0190] The device sends optimized care plans and alerts to the user via push notifications. The output is a notification message that the user can review, enabling them to take appropriate action. This functionality realizes the information-providing capabilities of the entire system.

[0191] (Application Example 2)

[0192] 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".

[0193] While conventional animal health management systems could monitor the health of animals, they had the challenge of not being able to optimize animal care while considering the user's emotional state. Furthermore, if the user was experiencing stress, it was not possible to suggest appropriate animal care, and thus it was not possible to provide a comfortable environment for both the user and the pet.

[0194] 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.

[0195] In this invention, the server includes means for acquiring vital information attached to the animal, means for detecting and analyzing the user's emotions, and means for adjusting the animal's care plan according to the user's emotional state. This makes it possible to realize animal care that takes into account not only the animal's health but also the user's emotional state.

[0196] "Vital information attached to animals" refers to information such as heart rate and body temperature obtained from devices attached to animals to indicate their health status.

[0197] "Means for detecting and analyzing user emotions" refers to methods for identifying a user's emotional state by analyzing their facial expressions and voice.

[0198] A "nutrition and exercise plan based on the animal's health condition" is a plan that proposes the optimal diet and exercise level according to the animal's current health condition and activity level.

[0199] "Means for adjusting animal care plans according to the user's emotional state" refers to a mechanism for appropriately changing the content and methods of care for animals based on the emotions expressed by the user.

[0200] "Data transmission and storage means" refers to a method for securely transmitting animal and user information and recording it so that it can be referenced later as needed.

[0201] To implement this invention, a vital signs acquisition device attached to an animal is first required. A terminal acquires information such as heart rate and body temperature from this device and transmits it to a server. The server has the function to analyze this data in real time and issue an alert if an abnormality is detected.

[0202] In addition, to detect the user's emotions, the terminal is equipped with a camera and microphone, and features an emotion recognition AI that can analyze facial expressions and voice. Machine learning libraries such as TENSORFLOW® are used for this analysis. Based on the analysis results, the server adjusts the animal care plan according to the user's emotional state and proposes it through the terminal.

[0203] Specific hardware options include a Raspberry Pi camera module and a standard heart rate monitor. For software, Azure® or AWS analytics servers and TensorFlow would be used for data analysis and emotion recognition.

[0204] For example, if a pet has a high body temperature, the device will suggest that the user take steps to cool it down. At the same time, if the server determines that the user is stressed, it can also recommend playing relaxing music.

[0205] For example, the following prompt can be input into the AI ​​model to generate alerts and suggestions: "Generate an appropriate care plan based on the pet's vital data and the user's emotional data. Provide a list of ways to generate advice that takes into account the pet's health condition and the user's stress level."

[0206] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0207] Step 1:

[0208] The terminal acquires data such as heart rate and body temperature from a vital signs acquisition device attached to the animal. The input is the data acquired by the vital signs acquisition device, and this data is stored internally as output. Specifically, it runs a program that periodically accesses the device to acquire the latest vital signs information.

[0209] Step 2:

[0210] The terminal sends the acquired vital data to the server. The input is the vital information acquired and saved in step 1, and the output is a response returned to the terminal indicating that the transmission is complete. Specifically, the process involves sending data to the server using a secure protocol.

[0211] Step 3:

[0212] The server analyzes the transmitted vital data in real time and detects abnormalities. The input is vital information received from the terminal, and the output is information on whether or not an abnormality was found. Specifically, it executes an algorithm that determines abnormalities by comparing them with a pre-set normal range.

[0213] Step 4:

[0214] The server sends an alert to the terminal if an anomaly is detected. The anomaly detection result from step 3 is taken as input, and an alert message is generated as output. Specifically, the server refers to a message template corresponding to the anomaly type and sends the most appropriate alert message to the terminal.

[0215] Step 5:

[0216] The device uses a camera and microphone to capture facial expressions and voice to detect the user's emotions. The input is the user's real-time facial and voice data, and the output is this raw data. Specifically, the camera and microphone are activated at regular intervals to collect data.

[0217] Step 6:

[0218] The server analyzes emotional data to determine the user's emotional state. The input is the facial expression and voice data obtained in step 5, and the output is the type of emotion analyzed. Specifically, it uses TensorFlow to execute an emotion recognition AI and classify the emotion.

[0219] Step 7:

[0220] The server generates an animal care plan tailored to the user's emotional state and provides it to the user via the terminal. The inputs are the emotional analysis results from step 6 and the vital signs analysis results from step 3, while the output is a care plan proposal to the user. Specifically, it utilizes a generation AI model to execute care suggestions based on prompts and displays the results on the terminal.

[0221] 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.

[0222] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0223] 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.

[0224] [Second Embodiment]

[0225] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0226] 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.

[0227] 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).

[0228] 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.

[0229] 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.

[0230] 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).

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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".

[0237] This invention provides a series of interconnected functions as a system for pet owners to effectively manage the health of their pets.

[0238] This system has the ability to collect data from a vital signs monitoring device attached to a pet. First, the terminal communicates with this device to obtain the pet's heart rate, body temperature, and activity level. The acquired data is then transmitted to the server in real time.

[0239] Upon receiving the transmitted data, the server immediately stores it in an analysis module and detects anomalies based on health standards. If this analysis process identifies a deviation from the standard values, the server generates an alert and sends a warning to the user's smartphone.

[0240] Furthermore, the server generates customized diet and exercise plans tailored to the pet's health condition. This allows users to incorporate specific care plans into their daily lives. These plans include recommendations for maintaining normal health and are adjusted to the pet's individual needs.

[0241] The terminal also includes features to support veterinarian appointment management, allowing users to plan appointments smoothly. Treatment history is managed digitally, and users can easily access past treatment records.

[0242] In addition, in the event of an emergency, the device has an interface that quickly provides the user with first aid procedures and nearby emergency contact information. This enables the user to take appropriate action.

[0243] For example, if the device detects a sudden rise in a pet's body temperature during normal health monitoring, the server will generate an anomaly detection alert and send the user instructions such as, "Your pet's body temperature is rising. Please let them rest in a cool place and visit a veterinarian if necessary." The emergency contact information included in this notification will provide contact details for a nearby animal hospital.

[0244] In this way, the system of the present invention highly automates pet health management, reducing the burden on pet owners while contributing to the well-being of pets.

[0245] The following describes the processing flow.

[0246] Step 1:

[0247] The device connects to a vital signs monitoring device and acquires the pet's heart rate, body temperature, and activity level at regular intervals.

[0248] Step 2:

[0249] The device temporarily stores the data it acquires locally and sends it to the server at regular intervals.

[0250] Step 3:

[0251] The server saves the received data to the database, and the analysis module begins analyzing the data.

[0252] Step 4:

[0253] The server compares the data to a baseline value and sets an anomaly flag if it detects an anomaly.

[0254] Step 5:

[0255] If the server detects an anomaly, it generates an alert and calls an API to send a warning message to the user's smartphone.

[0256] Step 6:

[0257] The user checks the alert notification received on their smartphone and takes appropriate action according to the instructions.

[0258] Step 7:

[0259] The server generates a customized diet and exercise plan based on the pet's health condition, using the analysis results.

[0260] Step 8:

[0261] The server generates a plan, which is then provided to the user, and they are encouraged to use it for their daily care.

[0262] Step 9:

[0263] The terminal automatically makes appointments with veterinarians through the reservation system based on user instructions.

[0264] Step 10:

[0265] The server updates the medical history, allowing users to review past medical data as needed.

[0266] (Example 1)

[0267] 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."

[0268] In recent years, pet owners' interest in pet health management has increased, and there is a demand for technological solutions to provide appropriate care. However, while devices for monitoring pet vital signs exist on the market, systems that comprehensively provide data analysis, detection of health anomalies, and the provision of customized health care plans are not yet widespread. Furthermore, there is a lack of real-time information to support rapid response in the event of an emergency, and a lack of secure data management methods. As a result, the effective means by which pet owners can provide the best possible care for their pets are limited.

[0269] 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.

[0270] In this invention, the server includes means for analyzing biometric information in real time and identifying abnormalities, means for transmitting warnings, and means for generating customized health care plans. This allows pet owners to understand their pet's health status in detail and apply individualized care plans.

[0271] A "biological monitoring device" is a device used to measure biological information such as heart rate, body temperature, and activity level of living organisms.

[0272] "Means for acquiring information" refers to methods or techniques for collecting biological information from a device.

[0273] "Means of real-time analysis" refers to methods or technologies for processing and analyzing acquired information immediately.

[0274] "Means for identifying abnormalities" refers to methods or techniques for recognizing a condition that deviates from health standards based on analyzed information.

[0275] "Means for sending warnings" refers to methods or technologies for notifying users when an anomaly is detected.

[0276] "Means for generating nutrition and exercise plans" refers to methods or techniques for creating dietary and exercise plans tailored to the health condition of an animal.

[0277] "Means for managing medical appointments and medical history" refers to methods or technologies for making appointments for medical consultations and for storing and referencing past medical information.

[0278] "Means of providing first aid and contact information" refers to methods or technologies for providing users with information on how to respond and contact information in an emergency.

[0279] "Means for securely transferring and storing information" refers to methods or technologies for transferring acquired information while protecting it from third parties and for long-term storage.

[0280] A "generative AI model" is an artificial intelligence-powered model that generates customized care plans based on a large amount of data.

[0281] This invention relates to a system that provides advanced support for animal health management. This system acquires and analyzes animal health data through various means and provides useful information to the user.

[0282] The terminal acquires information from a biometric monitoring device worn on an animal. This includes hardware and programs for periodically collecting biometric data such as heart rate, body temperature, and activity level via Bluetooth. The terminal has the role of temporarily storing the collected data and transmitting the data to a server via Wi-Fi or a mobile communication network.

[0283] The server stores the received data in a database and analyzes the data in real time using an analysis program written in Python. In this analysis process, it determines the presence or absence of abnormalities based on the acquired biometric information, and generates a warning when the set health criteria are deviated from. A health management plan utilizing a generated AI model is customized based on this data and creates specific plans regarding the animal's diet and exercise.

[0284] The user can receive abnormality warnings and health management plans through a smartphone app. This app also has additional functions to assist in managing medical appointments and viewing past medical histories. Also, in case of an emergency, the procedures for first aid and contact information of nearby medical institutions are displayed through the terminal, enabling the user to respond promptly.

[0285] As a specific example, when the body temperature of a pet rises rapidly, the terminal detects it and transmits the data to the server. The server analyzes the abnormality and notifies the smartphone app with instructions such as "The body temperature of your pet is rising. Let it rest in a cool place and visit a veterinarian if necessary." along with the contact information of nearby animal hospitals.

[0286] An example of a prompt sentence is "Please explain the specific processing steps for collecting the pet's vital data and detecting abnormalities and generating a care plan based on it." Thus, the user can timely grasp the health status of the pet and flexibly take necessary actions.

[0287] The flow of the specific processing in Example 1 will be described using FIG. 11.

[0288] Step 1:

[0289] The terminal connects to a biometric monitoring device attached to an animal via Bluetooth to acquire biometric data. During this process, biometric information such as heart rate, body temperature, and activity level is received as input. Based on this information, the terminal temporarily stores the data in its memory. The acquired data is then prepared for real-time transmission to a server.

[0290] Step 2:

[0291] The device transmits acquired biometric data to the server via Wi-Fi or a mobile communication network. Temporarily stored data is used as input, and encrypted data is sent to the server as output. Security measures are implemented to ensure the confidentiality of the information during this process.

[0292] Step 3:

[0293] The server collects received biometric data and stores it in a database. The input to this database is the biometric information received from the terminal, and the output is the information securely stored in storage. The server then prepares this data to provide to the analysis program.

[0294] Step 4:

[0295] The server uses an analysis program written in Python to analyze the stored data in real time. It receives biometric information read from a database as input and outputs anomaly detection results. The analysis uses an anomaly detection algorithm to identify data that deviates from the set health standards.

[0296] Step 5:

[0297] If an anomaly is detected, the server generates a warning and sends a push notification to the user's smartphone app. The input is the anomaly detection result from the analysis, and the output is the content of the notification to the user. This notification includes specific advice and emergency response procedures.

[0298] Step 6:

[0299] The server utilizes a generative AI model to generate individualized health care plans based on animal health data. The input is collected biometric data, and the output is a individually customized diet and exercise plan.

[0300] Step 7:

[0301] Users receive notifications of anomalies and health care plans through a smartphone app. Based on this information, users can care for their animals and flexibly adjust necessary actions. The input is notifications from the server, and the output is the user's action plan.

[0302] (Application Example 1)

[0303] 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."

[0304] In modern times, pet health management is a crucial issue for many pet owners. However, constantly monitoring a pet's health, quickly detecting abnormalities, and taking appropriate action is not easy. Furthermore, providing individualized health management plans and responding quickly in emergencies requires specialized knowledge and continuous effort. This increases the burden on pet owners and increases the risk of pets' health being poorly managed. Therefore, there is a need for automated systems that reduce the burden on pet owners and effectively manage pets' health.

[0305] 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.

[0306] In this invention, the server includes communication means for receiving biometric information of an animal and transmitting the information to a cloud server, means for providing data analysis and notification services on the cloud, and means for automatically generating an individually adjusted health management plan. As a result, it becomes possible to monitor the health status of a pet in real time and respond quickly and accurately when an abnormality occurs.

[0307] The "biological signal monitoring device" is a device for continuously acquiring biological information such as the heart rate, body temperature, and activity level of an animal.

[0308] "Real-time analysis" is an analysis method that processes the acquired data almost immediately and quickly detects abnormalities and patterns.

[0309] "Sending a warning" is a process of sending a notification to prompt the user's attention when an abnormality is detected.

[0310] "Generation of a nutrition and activity plan" is an act of creating an individually adjusted diet and exercise plan to maintain or improve the health status of an animal.

[0311] A "cloud server" is a remote server for storing, processing, and managing data through the Internet.

[0312] "Data transmission and protection means" are technologies and protocols for safely moving the acquired information and protecting it from unauthorized access from the outside.

[0313] A "notification service" is a communication function for automating the provision of information to the user and the delivery of warnings.

[0314] An "individually adjusted health management plan" is a plan for maintaining health optimized for each animal, taking into account the characteristics and conditions of each animal.

[0315] To realize this invention, a biosignal monitoring device to be attached to a pet is first required. This device continuously acquires data such as heart rate, body temperature, and activity level, and transmits the data to the user's smartphone or robot terminal via wireless communication such as Bluetooth. The terminal uploads this data to a cloud server in real time.

[0316] Upon receiving this data, the cloud server performs real-time analysis using advanced data analysis technologies. Specifically, it monitors the health status using machine learning algorithms and detects anomalies. This analysis utilizes cloud platforms such as Amazon Web Services (AWS). If an anomaly is detected, the cloud server promptly sends a notification to pre-registered users to issue a warning. Firebase Cloud Messaging is used for this notification function.

[0317] Furthermore, the cloud server automatically generates individually tailored nutrition and activity plans based on the acquired data. These plans are sent to the user's smartphone, robot, or other device, allowing the user to manage their pet's health daily based on them. The server also has an interface that can instantly provide emergency first-aid information and contact information for nearby veterinary hospitals.

[0318] For example, if a pet's body temperature is detected to be higher than normal, the server will send a message to the user saying, "Your pet's body temperature is elevated. Please have them rest in a cool place and visit a veterinarian if necessary." An example of a prompt message would be, "Your pet's heart rate is elevated. Please generate a guide on how to respond." This allows pet owners to take appropriate action quickly.

[0319] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0320] Step 1:

[0321] The device receives real-time data such as heart rate, body temperature, and activity level from a biosignal monitoring device attached to the pet. This data is acquired via Bluetooth communication. The input is biosignal data from the monitoring device, and the output is biosignal data aggregated in the device.

[0322] Step 2:

[0323] The device sends the received biometric data to a cloud server. This process utilizes cloud services such as AWS Lambda to ensure the data is securely uploaded. The input is the biometric data on the device, and the output is the biometric data stored in the cloud.

[0324] Step 3:

[0325] The server analyzes the received biometric data and detects anomalies. Machine learning algorithms are applied to this analysis to detect outliers. The input is biometric data stored in the cloud, and the output is a determination of whether or not an anomaly is present.

[0326] Step 4:

[0327] The server sends a warning message to the user's device if an anomaly is detected. Firebase Cloud Messaging is used to quickly notify the user. The input is the anomaly detection result, and the output is the warning notification sent to the user.

[0328] Step 5:

[0329] The server generates an individualized nutrition and activity plan for the pet based on biometric data. The generated plan is sent to the user's terminal, where the user can view it on the interface. The input is biometric data, and the output is the generated plan.

[0330] Step 6:

[0331] In the event of an emergency, the device provides the user with first-aid instructions and contact information for nearby veterinary hospitals. This allows the user to take necessary actions quickly. Input is an emergency alert from the server, and output is first-aid information and contact information.

[0332] 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.

[0333] This invention incorporates a function that takes user emotions into a system for managing pet health. The system aims to improve pet health management while simultaneously optimizing pet care according to the user's emotional state.

[0334] This system begins by acquiring data from a vital signs monitoring device attached to the pet, which is then received by a terminal. The acquired data is sent to a server, where data such as heart rate and body temperature are analyzed in real time. If an abnormality is detected, an alert is immediately sent to the user, allowing them to check the pet's current condition.

[0335] A distinctive feature of this system is the incorporation of an emotion engine that detects the user's emotions. The emotion engine uses the user's smart device's camera and microphone to analyze their emotional state from their facial expressions and tone of voice. The server has the function to adjust the pet's care plan based on these analysis results. For example, if the user is feeling stressed, it will suggest relaxing exercises and games for the pet.

[0336] For example, if the device detects an increase in the pet's body temperature and the emotion engine simultaneously detects that the user is feeling fatigued, the server will send an integrated alert to the user stating, "Your pet's body temperature is a little high. Please let it rest in a cool environment and observe its condition. Also, please take a break and relax." In this way, the system can provide information that takes the user's emotional state into account.

[0337] Furthermore, the appointment scheduling and medical history management functions are also adjusted based on the results of the emotion engine. For example, when the user is detected as busy or stressed, appointment reminders are sent earlier than usual, allowing for a more relaxed response to the pet's health.

[0338] Thus, the present invention provides an interactive care system that manages pets according to their health condition while also taking into account the user's emotions.

[0339] The following describes the processing flow.

[0340] Step 1:

[0341] The device acquires data from a vital signs monitoring device attached to the pet, periodically collecting information such as heart rate, body temperature, and activity level.

[0342] Step 2:

[0343] The device collects data, which is then sent to the server in real time and securely stored in a database.

[0344] Step 3:

[0345] The server analyzes the received vital sign data of the pet and detects abnormalities by comparing them to the normal range.

[0346] Step 4:

[0347] If the server detects an anomaly, it will generate an alert and send a notification to the user's smartphone. The notification will include specific instructions on how to address the issue.

[0348] Step 5:

[0349] The user's smart device uses its camera and microphone to collect emotions from facial expressions and voice data.

[0350] Step 6:

[0351] The server uses an emotion engine to analyze collected facial and voice data to determine the user's emotional state (e.g., stress, fatigue, calmness, etc.).

[0352] Step 7:

[0353] The server takes the user's emotional state into account and automatically adjusts the pet's care plan, for example, providing simple exercises or games that can be played with the pet if relaxation is needed.

[0354] Step 8:

[0355] The server sends a customized care plan to the user's device and suggests using it for daily pet care.

[0356] Step 9:

[0357] The device automatically schedules appointments based on the user's instructions, taking their emotional state into consideration. If necessary, it will send appointment reminders in advance.

[0358] Step 10:

[0359] Users receive alerts and reminders that take their emotional state into consideration, allowing for more effective pet health management.

[0360] (Example 2)

[0361] 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".

[0362] In modern society, animal health management is becoming increasingly important, but simply monitoring an animal's vital signs is insufficient. To optimally manage an animal's health, it is necessary to consider both the animal's physical information and the owner's psychological state. Furthermore, a system is needed to facilitate a rapid and appropriate response when an abnormality is detected. Therefore, this invention proposes a system that monitors both the animal's vital signs and the owner's emotional state to provide comprehensive health management.

[0363] 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.

[0364] In this invention, the server includes means for acquiring information from a biosignal monitoring device attached to an animal, means for immediately analyzing the acquired information and detecting abnormalities, and means for using an emotion analysis device for analyzing the user's emotions. This makes it possible to comprehensively evaluate the animal's health status and the user's emotional state and provide an individualized care plan.

[0365] A "biometric signal monitoring device" is a device that uses sensor technology to collect bodily information such as heart rate and body temperature when attached to an animal.

[0366] "Means of acquiring information" refers to the function of transmitting data obtained from sensors to a terminal, thereby enabling data collection.

[0367] "Means for immediate analysis and anomaly detection" refers to a function that analyzes acquired data in real time, identifies values ​​that deviate from the standard, and issues a warning.

[0368] "Methods using emotion analysis devices" refer to functions that use the camera and microphone of a smart device to analyze the user's facial expressions and voice and identify their emotional state.

[0369] "Providing individualized care plans" means providing specific and customized health management guidance and suggestions based on the animal's health condition and the user's emotional state.

[0370] "Information transfer and storage means" refers to technology for securely transmitting acquired information to other devices and storing it in a format that can be accessed later.

[0371] To implement this invention, the terminal first acquires vital data such as heart rate and body temperature from a biosignal monitoring device attached to an animal. This biosignal monitoring device is equipped with communication technologies such as Bluetooth or Wi-Fi and has the function of wirelessly transmitting data to the terminal. The terminal receives this data and transmits it to a server via a secure protocol (e.g., HTTPS).

[0372] The server analyzes acquired vital data in real time and detects abnormalities by comparing them to baseline values. This analysis uses data mining and machine learning algorithms, and has the function to immediately send a warning to the user when an abnormality is detected.

[0373] Furthermore, to take into account the user's emotional state, the device uses its camera and microphone as a smart device to capture the user's facial expressions and voice tone. This data is sent to a server, which uses an emotion analysis engine to analyze the user's emotional state and incorporate it into the pet care plan.

[0374] For example, if a pet's body temperature rises and the emotional engine simultaneously detects a high stress level in the user, the server will send an alert stating, "Your pet's body temperature is a little high. We recommend taking steps to cool it down and for you to relax." In this way, the system integrates animal health data with the user's emotional state to provide a more effective care plan.

[0375] The following prompt statements can be used as example inputs to a generative AI model.

[0376] "Please suggest solutions for when a pet's body temperature is high and the user is experiencing stress."

[0377] This allows the generated AI model to provide appropriate suggestions based on the situation. The system comprehensively supports pet health management, including the user's psychological factors. As a result, users can receive appropriate care tailored to their individual circumstances.

[0378] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0379] Step 1:

[0380] The device acquires vital data from a biosignal monitoring device attached to the animal. Specifically, the device receives data such as heart rate and body temperature via Bluetooth or Wi-Fi. In this process, vital data is received as input and prepared for the next step.

[0381] Step 2:

[0382] The terminal sends the acquired vital data to the server. The input is vital data, which is sent to the server using a secure protocol (e.g., HTTPS). The output here is the server receiving the data. This operation enables the next step of real-time analysis.

[0383] Step 3:

[0384] The server analyzes the vital data it receives. The input data includes heart rate and body temperature transmitted from the terminal, and the server compares this to standard health indicators to detect abnormalities. The server generates the analysis results as output and prepares subsequent actions if an abnormality is detected.

[0385] Step 4:

[0386] The device uses the smart device's camera and microphone to acquire user emotion data. The input includes user facial expressions and voice data, which the device collects and prepares to send to a server. The output of this step is a dataset containing emotion data.

[0387] Step 5:

[0388] The server analyzes the user's emotional data. The server receives facial expressions and voice tone as input data and analyzes them using an emotion analysis engine. This process identifies the user's emotional state and generates an emotional state report.

[0389] Step 6:

[0390] The server integrates vital data and emotional data to generate an appropriate care plan. The input is the analysis results obtained in the previous step, which are used to create the pet care plan and alert messages for the user. The output of this step is the adjusted care plan and alerts.

[0391] Step 7:

[0392] The device sends optimized care plans and alerts to the user via push notifications. The output is a notification message that the user can review, enabling them to take appropriate action. This functionality realizes the information-providing capabilities of the entire system.

[0393] (Application Example 2)

[0394] 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."

[0395] While conventional animal health management systems could monitor the health of animals, they had the challenge of not being able to optimize animal care while considering the user's emotional state. Furthermore, if the user was experiencing stress, it was not possible to suggest appropriate animal care, and thus it was not possible to provide a comfortable environment for both the user and the pet.

[0396] 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.

[0397] In this invention, the server includes means for acquiring vital information attached to the animal, means for detecting and analyzing the user's emotions, and means for adjusting the animal's care plan according to the user's emotional state. This makes it possible to realize animal care that takes into account not only the animal's health but also the user's emotional state.

[0398] "Vital information attached to animals" refers to information such as heart rate and body temperature obtained from devices attached to animals to indicate their health status.

[0399] "Means for detecting and analyzing user emotions" refers to methods for identifying a user's emotional state by analyzing their facial expressions and voice.

[0400] A "nutrition and exercise plan based on the animal's health condition" is a plan that proposes the optimal diet and exercise level according to the animal's current health condition and activity level.

[0401] "Means for adjusting animal care plans according to the user's emotional state" refers to a mechanism for appropriately changing the content and methods of care for animals based on the emotions expressed by the user.

[0402] "Data transmission and storage means" refers to a method for securely transmitting animal and user information and recording it so that it can be referenced later as needed.

[0403] To implement this invention, a vital signs acquisition device attached to an animal is first required. A terminal acquires information such as heart rate and body temperature from this device and transmits it to a server. The server has the function to analyze this data in real time and issue an alert if an abnormality is detected.

[0404] In addition, to detect the user's emotions, the device is equipped with a camera and microphone, and features an emotion recognition AI that can analyze facial expressions and voice. Machine learning libraries such as TensorFlow are used for this analysis. Based on the analysis results, the server adjusts the animal care plan according to the user's emotional state and proposes it through the device.

[0405] Specific hardware options include a Raspberry Pi camera module and a standard heart rate monitor. For software, Azure or AWS analytics servers and TensorFlow would be used for data analysis and emotion recognition.

[0406] For example, if a pet has a high body temperature, the device will suggest that the user take steps to cool it down. At the same time, if the server determines that the user is stressed, it can also recommend playing relaxing music.

[0407] For example, the following prompt can be input into the AI ​​model to generate alerts and suggestions: "Generate an appropriate care plan based on the pet's vital data and the user's emotional data. Provide a list of ways to generate advice that takes into account the pet's health condition and the user's stress level."

[0408] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0409] Step 1:

[0410] The terminal acquires data such as heart rate and body temperature from a vital signs acquisition device attached to the animal. The input is the data acquired by the vital signs acquisition device, and this data is stored internally as output. Specifically, it runs a program that periodically accesses the device to acquire the latest vital signs information.

[0411] Step 2:

[0412] The terminal sends the acquired vital data to the server. The input is the vital information acquired and saved in step 1, and the output is a response returned to the terminal indicating that the transmission is complete. Specifically, the process involves sending data to the server using a secure protocol.

[0413] Step 3:

[0414] The server analyzes the transmitted vital data in real time and detects abnormalities. The input is vital information received from the terminal, and the output is information on whether or not an abnormality was found. Specifically, it executes an algorithm that determines abnormalities by comparing them with a pre-set normal range.

[0415] Step 4:

[0416] The server sends an alert to the terminal if an anomaly is detected. The anomaly detection result from step 3 is taken as input, and an alert message is generated as output. Specifically, the server refers to a message template corresponding to the anomaly type and sends the most appropriate alert message to the terminal.

[0417] Step 5:

[0418] The device uses a camera and microphone to capture facial expressions and voice to detect the user's emotions. The input is the user's real-time facial and voice data, and the output is this raw data. Specifically, the camera and microphone are activated at regular intervals to collect data.

[0419] Step 6:

[0420] The server analyzes emotional data to determine the user's emotional state. The input is the facial expression and voice data obtained in step 5, and the output is the type of emotion analyzed. Specifically, it uses TensorFlow to execute an emotion recognition AI and classify the emotion.

[0421] Step 7:

[0422] The server generates an animal care plan tailored to the user's emotional state and provides it to the user via the terminal. The inputs are the emotional analysis results from step 6 and the vital signs analysis results from step 3, while the output is a care plan proposal to the user. Specifically, it utilizes a generation AI model to execute care suggestions based on prompts and displays the results on the terminal.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] [Third Embodiment]

[0427] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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".

[0439] This invention provides a series of interconnected functions as a system for pet owners to effectively manage the health of their pets.

[0440] This system has the ability to collect data from a vital signs monitoring device attached to a pet. First, the terminal communicates with this device to obtain the pet's heart rate, body temperature, and activity level. The acquired data is then transmitted to the server in real time.

[0441] Upon receiving the transmitted data, the server immediately stores it in an analysis module and detects anomalies based on health standards. If this analysis process identifies a deviation from the standard values, the server generates an alert and sends a warning to the user's smartphone.

[0442] Furthermore, the server generates customized diet and exercise plans tailored to the pet's health condition. This allows users to incorporate specific care plans into their daily lives. These plans include recommendations for maintaining normal health and are adjusted to the pet's individual needs.

[0443] The terminal also includes features to support veterinarian appointment management, allowing users to plan appointments smoothly. Treatment history is managed digitally, and users can easily access past treatment records.

[0444] In addition, in the event of an emergency, the device has an interface that quickly provides the user with first aid procedures and nearby emergency contact information. This enables the user to take appropriate action.

[0445] For example, if the device detects a sudden rise in a pet's body temperature during normal health monitoring, the server will generate an anomaly detection alert and send the user instructions such as, "Your pet's body temperature is rising. Please let them rest in a cool place and visit a veterinarian if necessary." The emergency contact information included in this notification will provide contact details for a nearby animal hospital.

[0446] In this way, the system of the present invention highly automates pet health management, reducing the burden on pet owners while contributing to the well-being of pets.

[0447] The following describes the processing flow.

[0448] Step 1:

[0449] The device connects to a vital signs monitoring device and acquires the pet's heart rate, body temperature, and activity level at regular intervals.

[0450] Step 2:

[0451] The device temporarily stores the data it acquires locally and sends it to the server at regular intervals.

[0452] Step 3:

[0453] The server saves the received data to the database, and the analysis module begins analyzing the data.

[0454] Step 4:

[0455] The server compares the data to a baseline value and sets an anomaly flag if it detects an anomaly.

[0456] Step 5:

[0457] If the server detects an anomaly, it generates an alert and calls an API to send a warning message to the user's smartphone.

[0458] Step 6:

[0459] The user checks the alert notification received on their smartphone and takes appropriate action according to the instructions.

[0460] Step 7:

[0461] The server generates a customized diet and exercise plan based on the pet's health condition, using the analysis results.

[0462] Step 8:

[0463] The server generates a plan, which is then provided to the user, and they are encouraged to use it for their daily care.

[0464] Step 9:

[0465] The terminal automatically makes appointments with veterinarians through the reservation system based on user instructions.

[0466] Step 10:

[0467] The server updates the medical history, allowing users to review past medical data as needed.

[0468] (Example 1)

[0469] 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."

[0470] In recent years, pet owners' interest in pet health management has increased, and there is a demand for technological solutions to provide appropriate care. However, while devices for monitoring pet vital signs exist on the market, systems that comprehensively provide data analysis, detection of health anomalies, and the provision of customized health care plans are not yet widespread. Furthermore, there is a lack of real-time information to support rapid response in the event of an emergency, and a lack of secure data management methods. As a result, the effective means by which pet owners can provide the best possible care for their pets are limited.

[0471] 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.

[0472] In this invention, the server includes means for analyzing biometric information in real time and identifying abnormalities, means for transmitting warnings, and means for generating customized health care plans. This allows pet owners to understand their pet's health status in detail and apply individualized care plans.

[0473] A "biological monitoring device" is a device used to measure biological information such as heart rate, body temperature, and activity level of living organisms.

[0474] "Means for acquiring information" refers to methods or techniques for collecting biological information from a device.

[0475] "Means of real-time analysis" refers to methods or technologies for processing and analyzing acquired information immediately.

[0476] "Means for identifying abnormalities" refers to methods or techniques for recognizing a condition that deviates from health standards based on analyzed information.

[0477] "Means for sending warnings" refers to methods or technologies for notifying users when an anomaly is detected.

[0478] "Means for generating nutrition and exercise plans" refers to methods or techniques for creating dietary and exercise plans tailored to the health condition of an animal.

[0479] "Means for managing medical appointments and medical history" refers to methods or technologies for making appointments for medical consultations and for storing and referencing past medical information.

[0480] "Means of providing first aid and contact information" refers to methods or technologies for providing users with information on how to respond and contact information in an emergency.

[0481] "Means for securely transferring and storing information" refers to methods or technologies for transferring acquired information while protecting it from third parties and for long-term storage.

[0482] A "generative AI model" is an artificial intelligence-powered model that generates customized care plans based on a large amount of data.

[0483] This invention relates to a system that provides advanced support for animal health management. This system acquires and analyzes animal health data through various means and provides useful information to the user.

[0484] The terminal acquires information from a biometric monitoring device attached to the animal. This includes hardware and programs for periodically collecting biometric data such as heart rate, body temperature, and activity level via Bluetooth. The terminal temporarily stores the collected data and transmits it to a server via Wi-Fi or a cellular network.

[0485] The server stores the received data in a database and analyzes it in real time using an analysis program written in Python. This analysis process determines whether there are abnormalities based on the acquired biometric information and generates warnings if the data deviates from the set health standards. A health management plan, utilizing a generated AI model, is customized based on this data to create specific plans regarding the animal's diet and exercise.

[0486] Users can receive alerts and health management plans through a smartphone app. The app also has additional features to help manage medical appointments and view past medical history. In the event of an emergency, first aid procedures and contact information for nearby medical facilities will be displayed on the device, allowing users to respond quickly.

[0487] For example, if a pet's body temperature rises rapidly, the device detects this and sends data to the server. The server analyzes the anomaly and notifies the user via the smartphone app with instructions such as, "Your pet's body temperature is rising. Let them rest in a cool place and visit a veterinarian if necessary," along with contact information for nearby animal hospitals.

[0488] An example of a prompt message is, "Collect vital data from your pet and explain the specific processing steps for detecting anomalies and generating a care plan based on that data." This allows users to understand their pet's health status in a timely manner and take necessary actions flexibly.

[0489] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0490] Step 1:

[0491] The terminal connects to a biometric monitoring device attached to an animal via Bluetooth to acquire biometric data. During this process, biometric information such as heart rate, body temperature, and activity level is received as input. Based on this information, the terminal temporarily stores the data in its memory. The acquired data is then prepared for real-time transmission to a server.

[0492] Step 2:

[0493] The device transmits acquired biometric data to the server via Wi-Fi or a mobile communication network. Temporarily stored data is used as input, and encrypted data is sent to the server as output. Security measures are implemented to ensure the confidentiality of the information during this process.

[0494] Step 3:

[0495] The server collects received biometric data and stores it in a database. The input to this database is the biometric information received from the terminal, and the output is the information securely stored in storage. The server then prepares this data to provide to the analysis program.

[0496] Step 4:

[0497] The server uses an analysis program written in Python to analyze the stored data in real time. It receives biometric information read from a database as input and outputs anomaly detection results. The analysis uses an anomaly detection algorithm to identify data that deviates from the set health standards.

[0498] Step 5:

[0499] If an anomaly is detected, the server generates a warning and sends a push notification to the user's smartphone app. The input is the anomaly detection result from the analysis, and the output is the content of the notification to the user. This notification includes specific advice and emergency response procedures.

[0500] Step 6:

[0501] The server utilizes a generative AI model to generate individualized health care plans based on animal health data. The input is collected biometric data, and the output is a individually customized diet and exercise plan.

[0502] Step 7:

[0503] Users receive notifications of anomalies and health care plans through a smartphone app. Based on this information, users can care for their animals and flexibly adjust necessary actions. The input is notifications from the server, and the output is the user's action plan.

[0504] (Application Example 1)

[0505] 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."

[0506] In modern times, pet health management is a crucial issue for many pet owners. However, constantly monitoring a pet's health, quickly detecting abnormalities, and taking appropriate action is not easy. Furthermore, providing individualized health management plans and responding quickly in emergencies requires specialized knowledge and continuous effort. This increases the burden on pet owners and increases the risk of pets' health being poorly managed. Therefore, there is a need for automated systems that reduce the burden on pet owners and effectively manage pets' health.

[0507] 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.

[0508] In this invention, the server includes communication means for receiving animal biometric information and transmitting the information to a cloud server, means for providing data analysis and notification services on the cloud, and means for automatically generating individually tailored health management plans. This makes it possible to monitor the health status of pets in real time and to respond quickly and accurately when abnormalities occur.

[0509] A "biological signal monitoring device" is a device used to continuously acquire biological information such as the heart rate, body temperature, and activity level of animals.

[0510] "Real-time analysis" is an analytical method that processes acquired data almost instantly to quickly detect anomalies and patterns.

[0511] "Issuing a warning" is the process of sending a notification to the user to alert them when an anomaly is detected.

[0512] "Nutritional and activity plan development" refers to the act of creating individually tailored dietary and exercise plans to maintain or improve the health of animals.

[0513] A "cloud server" is a remote server that stores, processes, and manages data via the internet.

[0514] "Data transmission and protection measures" refer to technologies and protocols that securely transfer acquired information and protect it from unauthorized external access.

[0515] A "notification service" is a communication function that automates the delivery of information and warnings to users.

[0516] An "individually tailored health management plan" is a plan for maintaining the health of each animal that takes into account its individual characteristics and condition and is optimized for each animal.

[0517] To realize this invention, a biosignal monitoring device to be attached to a pet is first required. This device continuously acquires data such as heart rate, body temperature, and activity level, and transmits the data to the user's smartphone or robot terminal via wireless communication such as Bluetooth. The terminal uploads this data to a cloud server in real time.

[0518] Upon receiving this data, the cloud server performs real-time analysis using advanced data analysis technologies. Specifically, it monitors the health status using machine learning algorithms and detects anomalies. This analysis utilizes cloud platforms such as Amazon Web Services (AWS). If an anomaly is detected, the cloud server promptly sends a notification to pre-registered users to issue a warning. Firebase Cloud Messaging is used for this notification function.

[0519] Furthermore, the cloud server automatically generates individually tailored nutrition and activity plans based on the acquired data. These plans are sent to the user's smartphone, robot, or other device, allowing the user to manage their pet's health daily based on them. The server also has an interface that can instantly provide emergency first-aid information and contact information for nearby veterinary hospitals.

[0520] For example, if a pet's body temperature is detected to be higher than normal, the server will send a message to the user saying, "Your pet's body temperature is elevated. Please have them rest in a cool place and visit a veterinarian if necessary." An example of a prompt message would be, "Your pet's heart rate is elevated. Please generate a guide on how to respond." This allows pet owners to take appropriate action quickly.

[0521] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0522] Step 1:

[0523] The device receives real-time data such as heart rate, body temperature, and activity level from a biosignal monitoring device attached to the pet. This data is acquired via Bluetooth communication. The input is biosignal data from the monitoring device, and the output is biosignal data aggregated in the device.

[0524] Step 2:

[0525] The device sends the received biometric data to a cloud server. This process utilizes cloud services such as AWS Lambda to ensure the data is securely uploaded. The input is the biometric data on the device, and the output is the biometric data stored in the cloud.

[0526] Step 3:

[0527] The server analyzes the received biometric data and detects anomalies. Machine learning algorithms are applied to this analysis to detect outliers. The input is biometric data stored in the cloud, and the output is a determination of whether or not an anomaly is present.

[0528] Step 4:

[0529] The server sends a warning message to the user's device if an anomaly is detected. Firebase Cloud Messaging is used to quickly notify the user. The input is the anomaly detection result, and the output is the warning notification sent to the user.

[0530] Step 5:

[0531] The server generates an individualized nutrition and activity plan for the pet based on biometric data. The generated plan is sent to the user's terminal, where the user can view it on the interface. The input is biometric data, and the output is the generated plan.

[0532] Step 6:

[0533] In the event of an emergency, the device provides the user with first-aid instructions and contact information for nearby veterinary hospitals. This allows the user to take necessary actions quickly. Input is an emergency alert from the server, and output is first-aid information and contact information.

[0534] 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.

[0535] This invention incorporates a function that takes user emotions into a system for managing pet health. The system aims to improve pet health management while simultaneously optimizing pet care according to the user's emotional state.

[0536] This system begins by acquiring data from a vital signs monitoring device attached to the pet, which is then received by a terminal. The acquired data is sent to a server, where data such as heart rate and body temperature are analyzed in real time. If an abnormality is detected, an alert is immediately sent to the user, allowing them to check the pet's current condition.

[0537] A distinctive feature of this system is the incorporation of an emotion engine that detects the user's emotions. The emotion engine uses the user's smart device's camera and microphone to analyze their emotional state from their facial expressions and tone of voice. The server has the function to adjust the pet's care plan based on these analysis results. For example, if the user is feeling stressed, it will suggest relaxing exercises and games for the pet.

[0538] For example, if the device detects an increase in the pet's body temperature and the emotion engine simultaneously detects that the user is feeling fatigued, the server will send an integrated alert to the user stating, "Your pet's body temperature is a little high. Please let it rest in a cool environment and observe its condition. Also, please take a break and relax." In this way, the system can provide information that takes the user's emotional state into account.

[0539] Furthermore, the appointment scheduling and medical history management functions are also adjusted based on the results of the emotion engine. For example, when the user is detected as busy or stressed, appointment reminders are sent earlier than usual, allowing for a more relaxed response to the pet's health.

[0540] Thus, the present invention provides an interactive care system that manages pets according to their health condition while also taking into account the user's emotions.

[0541] The following describes the processing flow.

[0542] Step 1:

[0543] The device acquires data from a vital signs monitoring device attached to the pet, periodically collecting information such as heart rate, body temperature, and activity level.

[0544] Step 2:

[0545] The device collects data, which is then sent to the server in real time and securely stored in a database.

[0546] Step 3:

[0547] The server analyzes the received vital sign data of the pet and detects abnormalities by comparing them to the normal range.

[0548] Step 4:

[0549] If the server detects an anomaly, it will generate an alert and send a notification to the user's smartphone. The notification will include specific instructions on how to address the issue.

[0550] Step 5:

[0551] The user's smart device uses its camera and microphone to collect emotions from facial expressions and voice data.

[0552] Step 6:

[0553] The server uses an emotion engine to analyze collected facial and voice data to determine the user's emotional state (e.g., stress, fatigue, calmness, etc.).

[0554] Step 7:

[0555] The server takes the user's emotional state into account and automatically adjusts the pet's care plan, for example, providing simple exercises or games that can be played with the pet if relaxation is needed.

[0556] Step 8:

[0557] The server sends a customized care plan to the user's device and suggests using it for daily pet care.

[0558] Step 9:

[0559] The device automatically schedules appointments based on the user's instructions, taking their emotional state into consideration. If necessary, it will send appointment reminders in advance.

[0560] Step 10:

[0561] Users receive alerts and reminders that take their emotional state into consideration, allowing for more effective pet health management.

[0562] (Example 2)

[0563] 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."

[0564] In modern society, animal health management is becoming increasingly important, but simply monitoring an animal's vital signs is insufficient. To optimally manage an animal's health, it is necessary to consider both the animal's physical information and the owner's psychological state. Furthermore, a system is needed to facilitate a rapid and appropriate response when an abnormality is detected. Therefore, this invention proposes a system that monitors both the animal's vital signs and the owner's emotional state to provide comprehensive health management.

[0565] 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.

[0566] In this invention, the server includes means for acquiring information from a biosignal monitoring device attached to an animal, means for immediately analyzing the acquired information and detecting abnormalities, and means for using an emotion analysis device for analyzing the user's emotions. This makes it possible to comprehensively evaluate the animal's health status and the user's emotional state and provide an individualized care plan.

[0567] A "biometric signal monitoring device" is a device that uses sensor technology to collect bodily information such as heart rate and body temperature when attached to an animal.

[0568] "Means of acquiring information" refers to the function of transmitting data obtained from sensors to a terminal, thereby enabling data collection.

[0569] "Means for immediate analysis and anomaly detection" refers to a function that analyzes acquired data in real time, identifies values ​​that deviate from the standard, and issues a warning.

[0570] "Methods using emotion analysis devices" refer to functions that use the camera and microphone of a smart device to analyze the user's facial expressions and voice and identify their emotional state.

[0571] "Providing individualized care plans" means providing specific and customized health management guidance and suggestions based on the animal's health condition and the user's emotional state.

[0572] "Information transfer and storage means" refers to technology for securely transmitting acquired information to other devices and storing it in a format that can be accessed later.

[0573] To implement this invention, the terminal first acquires vital data such as heart rate and body temperature from a biosignal monitoring device attached to an animal. This biosignal monitoring device is equipped with communication technologies such as Bluetooth or Wi-Fi and has the function of wirelessly transmitting data to the terminal. The terminal receives this data and transmits it to a server via a secure protocol (e.g., HTTPS).

[0574] The server analyzes acquired vital data in real time and detects abnormalities by comparing them to baseline values. This analysis uses data mining and machine learning algorithms, and has the function to immediately send a warning to the user when an abnormality is detected.

[0575] Furthermore, to take into account the user's emotional state, the device uses its camera and microphone as a smart device to capture the user's facial expressions and voice tone. This data is sent to a server, which uses an emotion analysis engine to analyze the user's emotional state and incorporate it into the pet care plan.

[0576] For example, if a pet's body temperature rises and the emotional engine simultaneously detects a high stress level in the user, the server will send an alert stating, "Your pet's body temperature is a little high. We recommend taking steps to cool it down and for you to relax." In this way, the system integrates animal health data with the user's emotional state to provide a more effective care plan.

[0577] The following prompt statements can be used as example inputs to a generative AI model.

[0578] "Please suggest solutions for when a pet's body temperature is high and the user is experiencing stress."

[0579] This allows the generated AI model to provide appropriate suggestions based on the situation. The system comprehensively supports pet health management, including the user's psychological factors. As a result, users can receive appropriate care tailored to their individual circumstances.

[0580] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0581] Step 1:

[0582] The device acquires vital data from a biosignal monitoring device attached to the animal. Specifically, the device receives data such as heart rate and body temperature via Bluetooth or Wi-Fi. In this process, vital data is received as input and prepared for the next step.

[0583] Step 2:

[0584] The terminal sends the acquired vital data to the server. The input is vital data, which is sent to the server using a secure protocol (e.g., HTTPS). The output here is the server receiving the data. This operation enables the next step of real-time analysis.

[0585] Step 3:

[0586] The server analyzes the vital data it receives. The input data includes heart rate and body temperature transmitted from the terminal, and the server compares this to standard health indicators to detect abnormalities. The server generates the analysis results as output and prepares subsequent actions if an abnormality is detected.

[0587] Step 4:

[0588] The device uses the smart device's camera and microphone to acquire user emotion data. The input includes user facial expressions and voice data, which the device collects and prepares to send to a server. The output of this step is a dataset containing emotion data.

[0589] Step 5:

[0590] The server analyzes the user's emotional data. The server receives facial expressions and voice tone as input data and analyzes them using an emotion analysis engine. This process identifies the user's emotional state and generates an emotional state report.

[0591] Step 6:

[0592] The server integrates vital data and emotional data to generate an appropriate care plan. The input is the analysis results obtained in the previous step, which are used to create the pet care plan and alert messages for the user. The output of this step is the adjusted care plan and alerts.

[0593] Step 7:

[0594] The device sends optimized care plans and alerts to the user via push notifications. The output is a notification message that the user can review, enabling them to take appropriate action. This functionality realizes the information-providing capabilities of the entire system.

[0595] (Application Example 2)

[0596] 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."

[0597] While conventional animal health management systems could monitor the health of animals, they had the challenge of not being able to optimize animal care while considering the user's emotional state. Furthermore, if the user was experiencing stress, it was not possible to suggest appropriate animal care, and thus it was not possible to provide a comfortable environment for both the user and the pet.

[0598] 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.

[0599] In this invention, the server includes means for acquiring vital information attached to the animal, means for detecting and analyzing the user's emotions, and means for adjusting the animal's care plan according to the user's emotional state. This makes it possible to realize animal care that takes into account not only the animal's health but also the user's emotional state.

[0600] "Vital information attached to animals" refers to information such as heart rate and body temperature obtained from devices attached to animals to indicate their health status.

[0601] "Means for detecting and analyzing user emotions" refers to methods for identifying a user's emotional state by analyzing their facial expressions and voice.

[0602] A "nutrition and exercise plan based on the animal's health condition" is a plan that proposes the optimal diet and exercise level according to the animal's current health condition and activity level.

[0603] "Means for adjusting animal care plans according to the user's emotional state" refers to a mechanism for appropriately changing the content and methods of care for animals based on the emotions expressed by the user.

[0604] "Data transmission and storage means" refers to a method for securely transmitting animal and user information and recording it so that it can be referenced later as needed.

[0605] To implement this invention, a vital signs acquisition device attached to an animal is first required. A terminal acquires information such as heart rate and body temperature from this device and transmits it to a server. The server has the function to analyze this data in real time and issue an alert if an abnormality is detected.

[0606] In addition, to detect the user's emotions, the device is equipped with a camera and microphone, and features an emotion recognition AI that can analyze facial expressions and voice. Machine learning libraries such as TensorFlow are used for this analysis. Based on the analysis results, the server adjusts the animal care plan according to the user's emotional state and proposes it through the device.

[0607] Specific hardware options include a Raspberry Pi camera module and a standard heart rate monitor. For software, Azure or AWS analytics servers and TensorFlow would be used for data analysis and emotion recognition.

[0608] For example, if a pet has a high body temperature, the device will suggest that the user take steps to cool it down. At the same time, if the server determines that the user is stressed, it can also recommend playing relaxing music.

[0609] For example, the following prompt can be input into the AI ​​model to generate alerts and suggestions: "Generate an appropriate care plan based on the pet's vital data and the user's emotional data. Provide a list of ways to generate advice that takes into account the pet's health condition and the user's stress level."

[0610] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0611] Step 1:

[0612] The terminal acquires data such as heart rate and body temperature from a vital signs acquisition device attached to the animal. The input is the data acquired by the vital signs acquisition device, and this data is stored internally as output. Specifically, it runs a program that periodically accesses the device to acquire the latest vital signs information.

[0613] Step 2:

[0614] The terminal sends the acquired vital data to the server. The input is the vital information acquired and saved in step 1, and the output is a response returned to the terminal indicating that the transmission is complete. Specifically, the process involves sending data to the server using a secure protocol.

[0615] Step 3:

[0616] The server analyzes the transmitted vital data in real time and detects abnormalities. The input is vital information received from the terminal, and the output is information on whether or not an abnormality was found. Specifically, it executes an algorithm that determines abnormalities by comparing them with a pre-set normal range.

[0617] Step 4:

[0618] The server sends an alert to the terminal if an anomaly is detected. The anomaly detection result from step 3 is taken as input, and an alert message is generated as output. Specifically, the server refers to a message template corresponding to the anomaly type and sends the most appropriate alert message to the terminal.

[0619] Step 5:

[0620] The device uses a camera and microphone to capture facial expressions and voice to detect the user's emotions. The input is the user's real-time facial and voice data, and the output is this raw data. Specifically, the camera and microphone are activated at regular intervals to collect data.

[0621] Step 6:

[0622] The server analyzes emotional data to determine the user's emotional state. The input is the facial expression and voice data obtained in step 5, and the output is the type of emotion analyzed. Specifically, it uses TensorFlow to execute an emotion recognition AI and classify the emotion.

[0623] Step 7:

[0624] The server generates an animal care plan tailored to the user's emotional state and provides it to the user via the terminal. The inputs are the emotional analysis results from step 6 and the vital signs analysis results from step 3, while the output is a care plan proposal to the user. Specifically, it utilizes a generation AI model to execute care suggestions based on prompts and displays the results on the terminal.

[0625] 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.

[0626] 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.

[0627] 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.

[0628] [Fourth Embodiment]

[0629] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0630] 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.

[0631] 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).

[0632] 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.

[0633] 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.

[0634] 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).

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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.

[0641] 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".

[0642] This invention provides a series of interconnected functions as a system for pet owners to effectively manage the health of their pets.

[0643] This system has the ability to collect data from a vital signs monitoring device attached to a pet. First, the terminal communicates with this device to obtain the pet's heart rate, body temperature, and activity level. The acquired data is then transmitted to the server in real time.

[0644] Upon receiving the transmitted data, the server immediately stores it in an analysis module and detects anomalies based on health standards. If this analysis process identifies a deviation from the standard values, the server generates an alert and sends a warning to the user's smartphone.

[0645] Furthermore, the server generates customized diet and exercise plans tailored to the pet's health condition. This allows users to incorporate specific care plans into their daily lives. These plans include recommendations for maintaining normal health and are adjusted to the pet's individual needs.

[0646] The terminal also includes features to support veterinarian appointment management, allowing users to plan appointments smoothly. Treatment history is managed digitally, and users can easily access past treatment records.

[0647] In addition, in the event of an emergency, the device has an interface that quickly provides the user with first aid procedures and nearby emergency contact information. This enables the user to take appropriate action.

[0648] For example, if the device detects a sudden rise in a pet's body temperature during normal health monitoring, the server will generate an anomaly detection alert and send the user instructions such as, "Your pet's body temperature is rising. Please let them rest in a cool place and visit a veterinarian if necessary." The emergency contact information included in this notification will provide contact details for a nearby animal hospital.

[0649] In this way, the system of the present invention highly automates pet health management, reducing the burden on pet owners while contributing to the well-being of pets.

[0650] The following describes the processing flow.

[0651] Step 1:

[0652] The device connects to a vital signs monitoring device and acquires the pet's heart rate, body temperature, and activity level at regular intervals.

[0653] Step 2:

[0654] The device temporarily stores the data it acquires locally and sends it to the server at regular intervals.

[0655] Step 3:

[0656] The server saves the received data to the database, and the analysis module begins analyzing the data.

[0657] Step 4:

[0658] The server compares the data to a baseline value and sets an anomaly flag if it detects an anomaly.

[0659] Step 5:

[0660] If the server detects an anomaly, it generates an alert and calls an API to send a warning message to the user's smartphone.

[0661] Step 6:

[0662] The user checks the alert notification received on their smartphone and takes appropriate action according to the instructions.

[0663] Step 7:

[0664] The server generates a customized diet and exercise plan based on the pet's health condition, using the analysis results.

[0665] Step 8:

[0666] The server generates a plan, which is then provided to the user, and they are encouraged to use it for their daily care.

[0667] Step 9:

[0668] The terminal automatically makes appointments with veterinarians through the reservation system based on user instructions.

[0669] Step 10:

[0670] The server updates the medical history, allowing users to review past medical data as needed.

[0671] (Example 1)

[0672] 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".

[0673] In recent years, pet owners' interest in pet health management has increased, and there is a demand for technological solutions to provide appropriate care. However, while devices for monitoring pet vital signs exist on the market, systems that comprehensively provide data analysis, detection of health anomalies, and the provision of customized health care plans are not yet widespread. Furthermore, there is a lack of real-time information to support rapid response in the event of an emergency, and a lack of secure data management methods. As a result, the effective means by which pet owners can provide the best possible care for their pets are limited.

[0674] 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.

[0675] In this invention, the server includes means for analyzing biometric information in real time and identifying abnormalities, means for transmitting warnings, and means for generating customized health care plans. This allows pet owners to understand their pet's health status in detail and apply individualized care plans.

[0676] A "biological monitoring device" is a device used to measure biological information such as heart rate, body temperature, and activity level of living organisms.

[0677] "Means for acquiring information" refers to methods or techniques for collecting biological information from a device.

[0678] "Means of real-time analysis" refers to methods or technologies for processing and analyzing acquired information immediately.

[0679] "Means for identifying abnormalities" refers to methods or techniques for recognizing a condition that deviates from health standards based on analyzed information.

[0680] "Means for sending warnings" refers to methods or technologies for notifying users when an anomaly is detected.

[0681] "Means for generating nutrition and exercise plans" refers to methods or techniques for creating dietary and exercise plans tailored to the health condition of an animal.

[0682] "Means for managing medical appointments and medical history" refers to methods or technologies for making appointments for medical consultations and for storing and referencing past medical information.

[0683] "Means of providing first aid and contact information" refers to methods or technologies for providing users with information on how to respond and contact information in an emergency.

[0684] "Means for securely transferring and storing information" refers to methods or technologies for transferring acquired information while protecting it from third parties and for long-term storage.

[0685] A "generative AI model" is an artificial intelligence-powered model that generates customized care plans based on a large amount of data.

[0686] This invention relates to a system that provides advanced support for animal health management. This system acquires and analyzes animal health data through various means and provides useful information to the user.

[0687] The terminal acquires information from a biometric monitoring device attached to the animal. This includes hardware and programs for periodically collecting biometric data such as heart rate, body temperature, and activity level via Bluetooth. The terminal temporarily stores the collected data and transmits it to a server via Wi-Fi or a cellular network.

[0688] The server stores the received data in a database and analyzes it in real time using an analysis program written in Python. This analysis process determines whether there are abnormalities based on the acquired biometric information and generates warnings if the data deviates from the set health standards. A health management plan, utilizing a generated AI model, is customized based on this data to create specific plans regarding the animal's diet and exercise.

[0689] Users can receive alerts and health management plans through a smartphone app. The app also has additional features to help manage medical appointments and view past medical history. In the event of an emergency, first aid procedures and contact information for nearby medical facilities will be displayed on the device, allowing users to respond quickly.

[0690] For example, if a pet's body temperature rises rapidly, the device detects this and sends data to the server. The server analyzes the anomaly and notifies the user via the smartphone app with instructions such as, "Your pet's body temperature is rising. Let them rest in a cool place and visit a veterinarian if necessary," along with contact information for nearby animal hospitals.

[0691] An example of a prompt message is, "Collect vital data from your pet and explain the specific processing steps for detecting anomalies and generating a care plan based on that data." This allows users to understand their pet's health status in a timely manner and take necessary actions flexibly.

[0692] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0693] Step 1:

[0694] The terminal connects to a biometric monitoring device attached to an animal via Bluetooth to acquire biometric data. During this process, biometric information such as heart rate, body temperature, and activity level is received as input. Based on this information, the terminal temporarily stores the data in its memory. The acquired data is then prepared for real-time transmission to a server.

[0695] Step 2:

[0696] The device transmits acquired biometric data to the server via Wi-Fi or a mobile communication network. Temporarily stored data is used as input, and encrypted data is sent to the server as output. Security measures are implemented to ensure the confidentiality of the information during this process.

[0697] Step 3:

[0698] The server collects received biometric data and stores it in a database. The input to this database is the biometric information received from the terminal, and the output is the information securely stored in storage. The server then prepares this data to provide to the analysis program.

[0699] Step 4:

[0700] The server uses an analysis program written in Python to analyze the stored data in real time. It receives biometric information read from a database as input and outputs anomaly detection results. The analysis uses an anomaly detection algorithm to identify data that deviates from the set health standards.

[0701] Step 5:

[0702] If an anomaly is detected, the server generates a warning and sends a push notification to the user's smartphone app. The input is the anomaly detection result from the analysis, and the output is the content of the notification to the user. This notification includes specific advice and emergency response procedures.

[0703] Step 6:

[0704] The server utilizes a generative AI model to generate individualized health care plans based on animal health data. The input is collected biometric data, and the output is a individually customized diet and exercise plan.

[0705] Step 7:

[0706] Users receive notifications of anomalies and health care plans through a smartphone app. Based on this information, users can care for their animals and flexibly adjust necessary actions. The input is notifications from the server, and the output is the user's action plan.

[0707] (Application Example 1)

[0708] 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".

[0709] In modern times, pet health management is a crucial issue for many pet owners. However, constantly monitoring a pet's health, quickly detecting abnormalities, and taking appropriate action is not easy. Furthermore, providing individualized health management plans and responding quickly in emergencies requires specialized knowledge and continuous effort. This increases the burden on pet owners and increases the risk of pets' health being poorly managed. Therefore, there is a need for automated systems that reduce the burden on pet owners and effectively manage pets' health.

[0710] 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.

[0711] In this invention, the server includes communication means for receiving animal biometric information and transmitting the information to a cloud server, means for providing data analysis and notification services on the cloud, and means for automatically generating individually tailored health management plans. This makes it possible to monitor the health status of pets in real time and to respond quickly and accurately when abnormalities occur.

[0712] A "biological signal monitoring device" is a device used to continuously acquire biological information such as the heart rate, body temperature, and activity level of animals.

[0713] "Real-time analysis" is an analytical method that processes acquired data almost instantly to quickly detect anomalies and patterns.

[0714] "Issuing a warning" is the process of sending a notification to the user to alert them when an anomaly is detected.

[0715] "Nutritional and activity plan development" refers to the act of creating individually tailored dietary and exercise plans to maintain or improve the health of animals.

[0716] A "cloud server" is a remote server that stores, processes, and manages data via the internet.

[0717] "Data transmission and protection measures" refer to technologies and protocols that securely transfer acquired information and protect it from unauthorized external access.

[0718] A "notification service" is a communication function that automates the delivery of information and warnings to users.

[0719] An "individually tailored health management plan" is a plan for maintaining the health of each animal that takes into account its individual characteristics and condition and is optimized for each animal.

[0720] To realize this invention, a biosignal monitoring device to be attached to a pet is first required. This device continuously acquires data such as heart rate, body temperature, and activity level, and transmits the data to the user's smartphone or robot terminal via wireless communication such as Bluetooth. The terminal uploads this data to a cloud server in real time.

[0721] Upon receiving this data, the cloud server performs real-time analysis using advanced data analysis technologies. Specifically, it monitors the health status using machine learning algorithms and detects anomalies. This analysis utilizes cloud platforms such as Amazon Web Services (AWS). If an anomaly is detected, the cloud server promptly sends a notification to pre-registered users to issue a warning. Firebase Cloud Messaging is used for this notification function.

[0722] Furthermore, the cloud server automatically generates individually tailored nutrition and activity plans based on the acquired data. These plans are sent to the user's smartphone, robot, or other device, allowing the user to manage their pet's health daily based on them. The server also has an interface that can instantly provide emergency first-aid information and contact information for nearby veterinary hospitals.

[0723] For example, if a pet's body temperature is detected to be higher than normal, the server will send a message to the user saying, "Your pet's body temperature is elevated. Please have them rest in a cool place and visit a veterinarian if necessary." An example of a prompt message would be, "Your pet's heart rate is elevated. Please generate a guide on how to respond." This allows pet owners to take appropriate action quickly.

[0724] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0725] Step 1:

[0726] The device receives real-time data such as heart rate, body temperature, and activity level from a biosignal monitoring device attached to the pet. This data is acquired via Bluetooth communication. The input is biosignal data from the monitoring device, and the output is biosignal data aggregated in the device.

[0727] Step 2:

[0728] The device sends the received biometric data to a cloud server. This process utilizes cloud services such as AWS Lambda to ensure the data is securely uploaded. The input is the biometric data on the device, and the output is the biometric data stored in the cloud.

[0729] Step 3:

[0730] The server analyzes the received biometric data and detects anomalies. Machine learning algorithms are applied to this analysis to detect outliers. The input is biometric data stored in the cloud, and the output is a determination of whether or not an anomaly is present.

[0731] Step 4:

[0732] The server sends a warning message to the user's device if an anomaly is detected. Firebase Cloud Messaging is used to quickly notify the user. The input is the anomaly detection result, and the output is the warning notification sent to the user.

[0733] Step 5:

[0734] The server generates an individualized nutrition and activity plan for the pet based on biometric data. The generated plan is sent to the user's terminal, where the user can view it on the interface. The input is biometric data, and the output is the generated plan.

[0735] Step 6:

[0736] In the event of an emergency, the device provides the user with first-aid instructions and contact information for nearby veterinary hospitals. This allows the user to take necessary actions quickly. Input is an emergency alert from the server, and output is first-aid information and contact information.

[0737] 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.

[0738] This invention incorporates a function that takes user emotions into a system for managing pet health. The system aims to improve pet health management while simultaneously optimizing pet care according to the user's emotional state.

[0739] This system begins by acquiring data from a vital signs monitoring device attached to the pet, which is then received by a terminal. The acquired data is sent to a server, where data such as heart rate and body temperature are analyzed in real time. If an abnormality is detected, an alert is immediately sent to the user, allowing them to check the pet's current condition.

[0740] A distinctive feature of this system is the incorporation of an emotion engine that detects the user's emotions. The emotion engine uses the user's smart device's camera and microphone to analyze their emotional state from their facial expressions and tone of voice. The server has the function to adjust the pet's care plan based on these analysis results. For example, if the user is feeling stressed, it will suggest relaxing exercises and games for the pet.

[0741] For example, if the device detects an increase in the pet's body temperature and the emotion engine simultaneously detects that the user is feeling fatigued, the server will send an integrated alert to the user stating, "Your pet's body temperature is a little high. Please let it rest in a cool environment and observe its condition. Also, please take a break and relax." In this way, the system can provide information that takes the user's emotional state into account.

[0742] Furthermore, the appointment scheduling and medical history management functions are also adjusted based on the results of the emotion engine. For example, when the user is detected as busy or stressed, appointment reminders are sent earlier than usual, allowing for a more relaxed response to the pet's health.

[0743] Thus, the present invention provides an interactive care system that manages pets according to their health condition while also taking into account the user's emotions.

[0744] The following describes the processing flow.

[0745] Step 1:

[0746] The device acquires data from a vital signs monitoring device attached to the pet, periodically collecting information such as heart rate, body temperature, and activity level.

[0747] Step 2:

[0748] The device collects data, which is then sent to the server in real time and securely stored in a database.

[0749] Step 3:

[0750] The server analyzes the received vital sign data of the pet and detects abnormalities by comparing them to the normal range.

[0751] Step 4:

[0752] If the server detects an anomaly, it will generate an alert and send a notification to the user's smartphone. The notification will include specific instructions on how to address the issue.

[0753] Step 5:

[0754] The user's smart device uses its camera and microphone to collect emotions from facial expressions and voice data.

[0755] Step 6:

[0756] The server uses an emotion engine to analyze collected facial and voice data to determine the user's emotional state (e.g., stress, fatigue, calmness, etc.).

[0757] Step 7:

[0758] The server takes the user's emotional state into account and automatically adjusts the pet's care plan, for example, providing simple exercises or games that can be played with the pet if relaxation is needed.

[0759] Step 8:

[0760] The server sends a customized care plan to the user's device and suggests using it for daily pet care.

[0761] Step 9:

[0762] The device automatically schedules appointments based on the user's instructions, taking their emotional state into consideration. If necessary, it will send appointment reminders in advance.

[0763] Step 10:

[0764] Users receive alerts and reminders that take their emotional state into consideration, allowing for more effective pet health management.

[0765] (Example 2)

[0766] 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".

[0767] In modern society, animal health management is becoming increasingly important, but simply monitoring an animal's vital signs is insufficient. To optimally manage an animal's health, it is necessary to consider both the animal's physical information and the owner's psychological state. Furthermore, a system is needed to facilitate a rapid and appropriate response when an abnormality is detected. Therefore, this invention proposes a system that monitors both the animal's vital signs and the owner's emotional state to provide comprehensive health management.

[0768] 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.

[0769] In this invention, the server includes means for acquiring information from a biosignal monitoring device attached to an animal, means for immediately analyzing the acquired information and detecting abnormalities, and means for using an emotion analysis device for analyzing the user's emotions. This makes it possible to comprehensively evaluate the animal's health status and the user's emotional state and provide an individualized care plan.

[0770] A "biometric signal monitoring device" is a device that uses sensor technology to collect bodily information such as heart rate and body temperature when attached to an animal.

[0771] "Means of acquiring information" refers to the function of transmitting data obtained from sensors to a terminal, thereby enabling data collection.

[0772] "Means for immediate analysis and anomaly detection" refers to a function that analyzes acquired data in real time, identifies values ​​that deviate from the standard, and issues a warning.

[0773] "Methods using emotion analysis devices" refer to functions that use the camera and microphone of a smart device to analyze the user's facial expressions and voice and identify their emotional state.

[0774] "Providing individualized care plans" means providing specific and customized health management guidance and suggestions based on the animal's health condition and the user's emotional state.

[0775] "Information transfer and storage means" refers to technology for securely transmitting acquired information to other devices and storing it in a format that can be accessed later.

[0776] To implement this invention, the terminal first acquires vital data such as heart rate and body temperature from a biosignal monitoring device attached to an animal. This biosignal monitoring device is equipped with communication technologies such as Bluetooth or Wi-Fi and has the function of wirelessly transmitting data to the terminal. The terminal receives this data and transmits it to a server via a secure protocol (e.g., HTTPS).

[0777] The server analyzes acquired vital data in real time and detects abnormalities by comparing them to baseline values. This analysis uses data mining and machine learning algorithms, and has the function to immediately send a warning to the user when an abnormality is detected.

[0778] Furthermore, to take into account the user's emotional state, the device uses its camera and microphone as a smart device to capture the user's facial expressions and voice tone. This data is sent to a server, which uses an emotion analysis engine to analyze the user's emotional state and incorporate it into the pet care plan.

[0779] For example, if a pet's body temperature rises and the emotional engine simultaneously detects a high stress level in the user, the server will send an alert stating, "Your pet's body temperature is a little high. We recommend taking steps to cool it down and for you to relax." In this way, the system integrates animal health data with the user's emotional state to provide a more effective care plan.

[0780] The following prompt statements can be used as example inputs to a generative AI model.

[0781] "Please suggest solutions for when a pet's body temperature is high and the user is experiencing stress."

[0782] This allows the generated AI model to provide appropriate suggestions based on the situation. The system comprehensively supports pet health management, including the user's psychological factors. As a result, users can receive appropriate care tailored to their individual circumstances.

[0783] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0784] Step 1:

[0785] The device acquires vital data from a biosignal monitoring device attached to the animal. Specifically, the device receives data such as heart rate and body temperature via Bluetooth or Wi-Fi. In this process, vital data is received as input and prepared for the next step.

[0786] Step 2:

[0787] The terminal sends the acquired vital data to the server. The input is vital data, which is sent to the server using a secure protocol (e.g., HTTPS). The output here is the server receiving the data. This operation enables the next step of real-time analysis.

[0788] Step 3:

[0789] The server analyzes the vital data it receives. The input data includes heart rate and body temperature transmitted from the terminal, and the server compares this to standard health indicators to detect abnormalities. The server generates the analysis results as output and prepares subsequent actions if an abnormality is detected.

[0790] Step 4:

[0791] The device uses the smart device's camera and microphone to acquire user emotion data. The input includes user facial expressions and voice data, which the device collects and prepares to send to a server. The output of this step is a dataset containing emotion data.

[0792] Step 5:

[0793] The server analyzes the user's emotional data. The server receives facial expressions and voice tone as input data and analyzes them using an emotion analysis engine. This process identifies the user's emotional state and generates an emotional state report.

[0794] Step 6:

[0795] The server integrates vital data and emotional data to generate an appropriate care plan. The input is the analysis results obtained in the previous step, which are used to create the pet care plan and alert messages for the user. The output of this step is the adjusted care plan and alerts.

[0796] Step 7:

[0797] The device sends optimized care plans and alerts to the user via push notifications. The output is a notification message that the user can review, enabling them to take appropriate action. This functionality realizes the information-providing capabilities of the entire system.

[0798] (Application Example 2)

[0799] 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".

[0800] While conventional animal health management systems could monitor the health of animals, they had the challenge of not being able to optimize animal care while considering the user's emotional state. Furthermore, if the user was experiencing stress, it was not possible to suggest appropriate animal care, and thus it was not possible to provide a comfortable environment for both the user and the pet.

[0801] 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.

[0802] In this invention, the server includes means for acquiring vital information attached to the animal, means for detecting and analyzing the user's emotions, and means for adjusting the animal's care plan according to the user's emotional state. This makes it possible to realize animal care that takes into account not only the animal's health but also the user's emotional state.

[0803] "Vital information attached to animals" refers to information such as heart rate and body temperature obtained from devices attached to animals to indicate their health status.

[0804] "Means for detecting and analyzing user emotions" refers to methods for identifying a user's emotional state by analyzing their facial expressions and voice.

[0805] A "nutrition and exercise plan based on the animal's health condition" is a plan that proposes the optimal diet and exercise level according to the animal's current health condition and activity level.

[0806] "Means for adjusting animal care plans according to the user's emotional state" refers to a mechanism for appropriately changing the content and methods of care for animals based on the emotions expressed by the user.

[0807] "Data transmission and storage means" refers to a method for securely transmitting animal and user information and recording it so that it can be referenced later as needed.

[0808] To implement this invention, a vital signs acquisition device attached to an animal is first required. A terminal acquires information such as heart rate and body temperature from this device and transmits it to a server. The server has the function to analyze this data in real time and issue an alert if an abnormality is detected.

[0809] In addition, to detect the user's emotions, the device is equipped with a camera and microphone, and features an emotion recognition AI that can analyze facial expressions and voice. Machine learning libraries such as TensorFlow are used for this analysis. Based on the analysis results, the server adjusts the animal care plan according to the user's emotional state and proposes it through the device.

[0810] Specific hardware options include a Raspberry Pi camera module and a standard heart rate monitor. For software, Azure or AWS analytics servers and TensorFlow would be used for data analysis and emotion recognition.

[0811] For example, if a pet has a high body temperature, the device will suggest that the user take steps to cool it down. At the same time, if the server determines that the user is stressed, it can also recommend playing relaxing music.

[0812] For example, the following prompt can be input into the AI ​​model to generate alerts and suggestions: "Generate an appropriate care plan based on the pet's vital data and the user's emotional data. Provide a list of ways to generate advice that takes into account the pet's health condition and the user's stress level."

[0813] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0814] Step 1:

[0815] The terminal acquires data such as heart rate and body temperature from a vital signs acquisition device attached to the animal. The input is the data acquired by the vital signs acquisition device, and this data is stored internally as output. Specifically, it runs a program that periodically accesses the device to acquire the latest vital signs information.

[0816] Step 2:

[0817] The terminal sends the acquired vital data to the server. The input is the vital information acquired and saved in step 1, and the output is a response returned to the terminal indicating that the transmission is complete. Specifically, the process involves sending data to the server using a secure protocol.

[0818] Step 3:

[0819] The server analyzes the transmitted vital data in real time and detects abnormalities. The input is vital information received from the terminal, and the output is information on whether or not an abnormality was found. Specifically, it executes an algorithm that determines abnormalities by comparing them with a pre-set normal range.

[0820] Step 4:

[0821] The server sends an alert to the terminal if an anomaly is detected. The anomaly detection result from step 3 is taken as input, and an alert message is generated as output. Specifically, the server refers to a message template corresponding to the anomaly type and sends the most appropriate alert message to the terminal.

[0822] Step 5:

[0823] The device uses a camera and microphone to capture facial expressions and voice to detect the user's emotions. The input is the user's real-time facial and voice data, and the output is this raw data. Specifically, the camera and microphone are activated at regular intervals to collect data.

[0824] Step 6:

[0825] The server analyzes emotional data to determine the user's emotional state. The input is the facial expression and voice data obtained in step 5, and the output is the type of emotion analyzed. Specifically, it uses TensorFlow to execute an emotion recognition AI and classify the emotion.

[0826] Step 7:

[0827] The server generates an animal care plan tailored to the user's emotional state and provides it to the user via the terminal. The inputs are the emotional analysis results from step 6 and the vital signs analysis results from step 3, while the output is a care plan proposal to the user. Specifically, it utilizes a generation AI model to execute care suggestions based on prompts and displays the results on the terminal.

[0828] 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.

[0829] 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.

[0830] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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."

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] The following is further disclosed regarding the embodiments described above.

[0850] (Claim 1)

[0851] A means of acquiring data from a vital sign monitoring device attached to an animal,

[0852] A means of analyzing acquired data in real time and detecting anomalies,

[0853] A means of issuing an alert in response to detected anomalies,

[0854] Means for generating a diet and exercise plan based on the health status of an animal,

[0855] A means of managing medical appointments and medical history,

[0856] Means of providing first aid and contact information in emergencies,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, which provides a customized health care plan based on the vital signs of an animal.

[0860] (Claim 3)

[0861] The system according to claim 1, comprising data transfer and storage means for securely storing and analyzing animal data.

[0862] "Example 1"

[0863] (Claim 1)

[0864] A means of acquiring information from a biological monitoring device attached to an animal,

[0865] A means of analyzing acquired information in real time and identifying anomalies,

[0866] A means for sending a warning in response to a detected anomaly,

[0867] Means for generating nutrition and exercise plans based on the health status of animals,

[0868] A means of managing medical appointments and medical history,

[0869] Means of providing first aid and contact information in emergencies,

[0870] Means for securely transferring and storing the collected information,

[0871] A means of providing a customized care plan based on health status using an AI model,

[0872] A system that includes this.

[0873] (Claim 2)

[0874] The system according to claim 1, which provides an individually tailored health care plan based on the biological information of an animal.

[0875] (Claim 3)

[0876] The system according to claim 1, comprising means for transferring and storing information for securely storing and analyzing animal information.

[0877] "Application Example 1"

[0878] (Claim 1)

[0879] A means of acquiring information from a biosignal monitoring device attached to an animal,

[0880] A means of analyzing acquired information in real time and detecting anomalies,

[0881] A means of issuing a warning in response to detected anomalies,

[0882] Means for generating nutrition and activity plans based on the health status of animals,

[0883] A means of managing medical appointments and treatment history,

[0884] Means of providing first aid and contact information in emergencies,

[0885] A communication method for receiving animal biometric information and transmitting that information to a cloud server,

[0886] A means of providing data analysis and notification services on the cloud,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, which provides an individually tailored health management plan based on the biological information of an animal.

[0890] (Claim 3)

[0891] The system according to claim 1, comprising data transmission and protection means for securely transferring and storing animal information.

[0892] "Example 2 of combining an emotion engine"

[0893] (Claim 1)

[0894] A means of acquiring information from a biosignal monitoring device attached to an animal,

[0895] A means for immediately analyzing acquired information and detecting anomalies,

[0896] A means for sending a warning in response to a detected anomaly,

[0897] A means of proposing nutrition and exercise plans based on the health status of animals,

[0898] A means of using an emotion analysis device to analyze the user's emotions,

[0899] A means to adjust the system so that the analyzed emotional state of the user is reflected in health management,

[0900] A means of managing medical appointments and medical history,

[0901] Means of providing emergency medical treatment and contact information in times of emergency,

[0902] A system that includes this.

[0903] (Claim 2)

[0904] The system according to claim 1, which provides a customized health care plan based on the animal's biosignals and the user's emotions.

[0905] (Claim 3)

[0906] The system according to claim 1, comprising information transfer and storage means for securely transferring, storing, and analyzing animal information.

[0907] "Application example 2 when combining with an emotional engine"

[0908] (Claim 1)

[0909] A means of acquiring vital information attached to an animal,

[0910] A means of analyzing acquired vital information in real time and identifying abnormalities,

[0911] A means of disseminating information when an anomaly is detected,

[0912] Means for generating nutrition and exercise plans based on the health status of animals,

[0913] A means of managing medical visit appointments and medical records,

[0914] Means of providing first aid and contact information in emergencies,

[0915] A means of detecting and analyzing the user's emotions,

[0916] A means of adjusting the animal care plan according to the user's emotional state,

[0917] A system that includes this.

[0918] (Claim 2)

[0919] The system according to claim 1, which provides a customized health management plan based on the vital information of an animal and the emotional information of a user.

[0920] (Claim 3)

[0921] The system according to claim 1, comprising data transmission and storage means for securely recording and analyzing animal information and user emotional information. [Explanation of symbols]

[0922] 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 of acquiring data from a vital sign monitoring device attached to an animal, A means of analyzing acquired data in real time and detecting anomalies, A means of issuing an alert for detected anomalies, Means for generating a diet and exercise plan based on the animal's health condition, A means of managing medical appointments and medical history, Means of providing first aid and contact information in emergencies, A system that includes this.

2. The system according to claim 1, which provides a customized health care plan based on the vital signs of an animal.

3. The system according to claim 1, comprising data transfer and storage means for securely storing and analyzing animal data.

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