system

Abstract

We provide the system. [Solution] A means for receiving data from an animal, from a wearable device equipped with sensors for acquiring animal behavior and health data, A means for analyzing the received data and evaluating the health status and behavioral patterns of the animals, A means for generating a notification to propose adjustment measures for animals based on the results of the aforementioned evaluation, Means for transmitting the aforementioned notification to an electronic terminal, A means of sharing the aforementioned animal's health data with medical professionals, 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, and includes 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] Changes in the health status and behavior of animals are often not immediately noticed by the owner, making it difficult to implement appropriate care in a timely manner. As a result, there is a possibility that the health problems of animals may worsen or problem behaviors may become established. In addition, since it is difficult for veterinarians to make early diagnoses and responses, it is often too late when health problems are discovered. Due to these problems, the quality of life of animals is reduced, and it is difficult to build a good relationship with the owner, which is an issue.

Means for Solving the Problems

[0005] This invention provides a system for continuously acquiring behavioral and health data from a wearable device equipped with sensors that can be attached to an animal. By analyzing the acquired data, the system evaluates the animal's health status and behavioral patterns, and generates notifications for the owner based on the results. This allows for the estimation of the animal's emotions and needs, and the suggestion of specific adjustment measures. Furthermore, by sharing the data with medical professionals, it supports early diagnosis and appropriate response. This enables appropriate care for the animal's health and behavior, and facilitates smooth communication with the owner.

[0006] "Animals" refer to living organisms, including pets and livestock kept by humans.

[0007] "Behavioral data" refers to information about the movements and activities of animals, specifically numerical data and patterns acquired by wearable devices.

[0008] "Health data" refers to information about an animal's biological or physiological state, including indicators such as activity level, sleep, and diet.

[0009] A "wearable device" is a device equipped with sensors that can be attached to animals, thereby enabling the acquisition of data.

[0010] A "sensor" is a device that detects physical phenomena and quantifies that information.

[0011] "Analysis" is the process of extracting specific insights or patterns using acquired data.

[0012] "Evaluation" refers to making objective judgments about an animal's health and behavior based on analyzed data.

[0013] "Notifications" are messages and information generated to inform pet owners of evaluation results and suggestions.

[0014] "Medical professional" refers to a veterinarian or medical staff member who has specialized knowledge and qualifications regarding the health of animals.

[0015] "Feedback" refers to the evaluation and advice provided by medical professionals based on data.

Brief Description of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] 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.

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

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, 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.

[0021] 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.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system for supporting animal health management and behavioral analysis, and consists of a wearable device equipped with sensors, a server for processing data, and a terminal for providing information. Specific embodiments are described below.

[0038] First, the wearable devices attached to the animals contain various sensors to acquire data on activity levels, sleep, and diet. These devices transmit the data acquired in real time from the sensors to a server via wireless communication. The server then uses this data to analyze the animals' health and behavior.

[0039] In the analysis, the server first compares each data point to a baseline value to assess the user's health status and detects any data that deviates from normal. If activity levels are significantly lower than normal, the server calculates the risk associated with that health status and determines it to be abnormal.

[0040] Regarding behavioral data, the server uses advanced algorithms to analyze the animals' behavioral patterns. For example, based on the frequency and pattern of barking, it can identify if an animal is experiencing stress. This behavioral analysis is also used to estimate the emotions and needs of pets.

[0041] Based on the analysis results, the server generates a notification tailored to the animal's condition and sends it to the device. This notification includes monitoring results of the animal's health status and specific instructions for behavioral improvement. The user receives the notification on their device and can take appropriate action for the animal.

[0042] For example, if the device receives a notification that "your pet's activity level has decreased," the user might consider increasing the amount of time spent walking their pet or providing indoor playtime. If a notification about barking is received, actionable advice such as "playing certain music may calm your pet" will be provided.

[0043] Furthermore, the server has the functionality to share animal health data with medical professionals such as veterinarians. This allows veterinarians to accurately understand the situation and provide appropriate treatment and feedback. This feedback is notified to the user via the terminal, helping them to take necessary actions.

[0044] As described above, this system comprehensively supports animal health management and behavioral improvement, while also enhancing convenience for pet owners.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The server receives data on animal activity levels, sleep, and diet from wearable devices. This includes raw data acquired by various sensors.

[0048] Step 2:

[0049] The server preprocesses the received data. This preprocessing includes data cleansing, such as imputing missing values ​​and removing noise. This process prepares the dataset for analysis.

[0050] Step 3:

[0051] The server assesses the health status of animals based on pre-processed data. Specifically, it compares the data to historical baseline data to determine whether it is within the normal range or abnormal. This assessment identifies risks if abnormal values ​​are present.

[0052] Step 4:

[0053] The server applies behavioral analysis algorithms to analyze the animals' behavioral patterns. Based on the data, it estimates the presence or absence of problematic behaviors and the animals' emotional states. For example, it identifies the frequency and patterns of abnormal barking and investigates their causes.

[0054] Step 5:

[0055] The server uses a natural language generation engine to create notifications based on the analysis of the animals' health status and behavior. These notifications include specific actions to take and advice for pet owners.

[0056] Step 6:

[0057] The server sends the generated notification to the device. The notification is immediately conveyed to the owner via the application and becomes available for viewing on the dashboard.

[0058] Step 7:

[0059] The user checks notifications received on their device and decides what action is needed for the animal. Based on the notification, they select actions to improve the animal's behavior and health.

[0060] Step 8:

[0061] The server shares health data with medical professionals such as veterinarians as needed. This sharing takes place via the cloud and provides the professionals with the basic information they need to conduct detailed analysis.

[0062] Step 9:

[0063] The device receives feedback from veterinarians and presents it to the user. Based on this feedback, the user considers further medical interventions.

[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] Modern households are required to accurately understand and properly manage their pets' health and behavioral patterns. However, achieving this requires a system that accurately analyzes the diverse data obtained from animals and provides owners with the necessary information. Conventional systems have the challenge of not being able to accurately estimate animals' emotions and desires and propose appropriate adjustment measures.

[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 receiving information from a wearable device equipped with a detection device for acquiring animal behavior and health information, means for analyzing the received information and evaluating the animal's health status and behavioral patterns, and means for generating notifications to propose adjustment measures for the animal based on the evaluation results. This makes it possible to understand the animal's health status and behavioral patterns in detail and to achieve effective management and improvement.

[0069] "Animals" refers to living creatures such as mammals, birds, and reptiles that are kept as pets or livestock.

[0070] "Movement" is a concept used to observe and analyze the bodily movements and actions that animals perform on a daily basis.

[0071] "Health information" refers to data that indicates an animal's physical condition, specifically including body temperature, heart rate, and activity level.

[0072] A "detection device" refers to equipment consisting of sensors attached to animals, used to acquire information about the animals' movements and health.

[0073] A "wearable device" is a device that is directly attached to an animal, equipped with sensors and communication functions, and used to collect and transmit data in real time.

[0074] "Information" is a broad concept referring to data acquired by detection devices and the results of their analysis.

[0075] "Analysis" refers to data processing performed to evaluate health status and behavioral patterns based on acquired data.

[0076] "Health status" refers to indicators that show the physical and mental well-being and presence or absence of abnormalities in an animal.

[0077] "Behavioral patterns" refer to certain patterns or tendencies in an animal's behavior.

[0078] "Adjustment measures" refer to specific actions and suggestions taken to improve the health and behavior of animals based on the evaluation results.

[0079] "Notifications" refer to messages and alerts used to inform users about analysis results and corrective actions.

[0080] "Electronic devices" refer to digital devices used by users to check the condition of animals and take appropriate action as needed.

[0081] "Medical professional" refers to a veterinarian or other healthcare worker who possesses knowledge and skills related to animal health.

[0082] "Generation" refers to the process of creating new information or notifications, and is particularly used when employing AI models.

[0083] This invention is a system for supporting animal health management and behavioral analysis. The system mainly consists of wearable devices, a server, and terminals. The following describes each component and how they work together in detail.

[0084] First, the wearable device is attached to the animal and is equipped with an accelerometer, heart rate sensor, environmental sensor, etc. This device acquires the animal's movements and health information in real time. The acquired data is transmitted to a server using wireless communication technologies such as Bluetooth or Wi-Fi.

[0085] The server uses an AI model to analyze the received data. During the analysis, the data is compared to baseline values ​​to evaluate the animal's health status and behavior. If a health abnormality is detected, the server generates a notification to suggest specific adjustment measures. For example, if activity levels decrease, it might generate a notification such as, "We recommend increasing your pet's exercise."

[0086] The generated notifications are sent from the server to the electronic terminal. The terminal is equipped with a user interface, allowing the user to check the notifications and take necessary actions. One example of a specific action is to alleviate the animal's stress by playing certain music. The terminal also has a function to share data with medical professionals such as veterinarians, and can receive feedback from professionals via the server.

[0087] In implementing this system, it is possible to precisely analyze animal behavior patterns using a generative AI model and achieve highly accurate estimations. Furthermore, a possible use case for prompts is, "Based on my pet's recent behavioral data, please suggest the optimal amount of exercise."

[0088] In summary, this invention comprehensively supports animal health management and behavioral monitoring, providing a useful means for pet owners to properly manage their pets.

[0089] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0090] Step 1:

[0091] The wearable device is attached to the animal and uses sensors to acquire real-time information about the animal's movements and health. The input data includes acceleration, heart rate, and information about the surrounding environment, and this information is recorded as digital signals. Specifically, while the animal is walking, the acceleration sensor measures the body's movement, and this is output digitally as an activity level.

[0092] Step 2:

[0093] Data obtained from wearable devices is transmitted to a server using wireless communication technology. The input data is sent in a compressed format, and the server receives and decompresses it. The data is processed in JSON format and formatted for parsing. Specifically, after receiving the data, the server stores it in a database.

[0094] Step 3:

[0095] The server uses an AI model to analyze the received data. The input data consists of behavioral and health information, which is evaluated as health status and behavioral patterns. The analysis includes comparison with baseline values ​​and pattern recognition. For example, if the activity level falls below the baseline value, the server detects an anomaly and assesses the health risk.

[0096] Step 4:

[0097] The server generates notifications based on the analysis results. The input is data on the evaluated health status and behavior patterns, and the output is a notification that proposes specific adjustment measures. Specifically, it creates a message such as, "Your pet's activity level has decreased. Please increase its exercise."

[0098] Step 5:

[0099] The server sends the generated notification to the electronic device. The input is the notification message, and the output is an alert to the user's electronic device. Specifically, the device immediately displays the notification through its user interface.

[0100] Step 6:

[0101] The user checks the notification received on their device and takes appropriate action. The input is the notification message, and the output is the user's action. Specifically, the user adjusts their actions based on the suggestion, such as taking their pet for a walk.

[0102] Step 7:

[0103] The device shares information with medical professionals such as veterinarians via a server, allowing for feedback. Specifically, it displays advice from veterinarians on the device to help users take more appropriate action.

[0104] (Application Example 1)

[0105] 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."

[0106] Real-time data acquisition, rapid detection of abnormal behavior, and proposal of countermeasures are required for animal health management and behavioral analysis. However, many current systems suffer from the problem of time-consuming data analysis, preventing pet owners from taking immediate action. Furthermore, it is difficult to accurately estimate the animal's emotions and needs and to immediately determine effective responses. Therefore, there is a need to develop a system that monitors the health status and behavior of animals in real time and immediately proposes appropriate countermeasures.

[0107] 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.

[0108] In this invention, the server includes a device for receiving animal data from a wearable device equipped with a sensing device for acquiring animal behavior and health data; a device for analyzing the received data and evaluating the animal's health status and behavioral patterns; and a device for generating notifications to propose corrective measures for the animal based on the results of the evaluation. This makes it possible to monitor the animal's health status in real time, quickly propose necessary countermeasures, and reduce reaction time.

[0109] "Animal behavior" refers to the various actions and patterns that animals exhibit in their daily lives, and is an important indicator of their health and emotions.

[0110] "Health data" refers to a collection of information that shows biomedical indicators such as an animal's body temperature, heart rate, and respiratory rate, and forms the basis for evaluating the health status of an animal.

[0111] A "sensing device" is a device that includes sensors used to acquire physical activity and physiological data of animals, and is often incorporated into wearable devices.

[0112] A "wearable device" is a device attached to an animal, which includes a sensing device and is responsible for acquiring health and behavioral data of the animal.

[0113] "Abnormal behavior" refers to actions that deviate from normal behavioral patterns and may indicate stress or health problems in animals.

[0114] An "information terminal" is an electronic device used to provide users with notifications and suggested adjustment measures, and includes smartphones and smart glasses.

[0115] A "medical professional" is a healthcare worker with specialized knowledge, such as a veterinarian, who is involved in the assessment and treatment of an animal's health.

[0116] A "visualization application" is software that visually displays data and presents users with analysis results of abnormal behavior and countermeasures.

[0117] The system for realizing this invention consists of a wearable device attached to an animal, a server for processing data, and a terminal for displaying information. The wearable device includes a sensing device for acquiring animal behavior and health data, and transmits this data to the server using wireless communication. The server analyzes the received data and uses an algorithm to evaluate the animal's health status and behavioral patterns. This algorithm detects abnormal behavior and estimates the animal's emotions and desires.

[0118] As a concrete example, the server monitors the animal's heart rate and activity level in real time and compares them to normal levels. If an abnormal pattern is detected, it sends a notification to the user and suggests appropriate countermeasures. For example, if the animal's heart rate suddenly increases, the device will receive a notification stating, "The animal may be excited. Please provide a calm environment to help it settle down." In this case, a generative AI model is used to generate prompts that recommend actions that take the animal's condition into consideration. An example of a specific prompt might be, "Analyze the pet's behavioral data and suggest appropriate relaxation methods."

[0119] The terminal displays information received from the server in an easy-to-understand manner for the user and supports communication with experts as needed. This system also includes a function to share collected data with medical professionals, enabling veterinarians to gain a more accurate understanding of the situation and utilize it in treatment.

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] Wearable devices acquire animal behavior and health data using sensing devices. Inputs are real-time data such as animal activity levels and heart rate, which are transmitted wirelessly to a server. Outputs are the animal's biometric data used by the server for analysis.

[0123] Step 2:

[0124] The server analyzes the data received from the wearable device. The input is the transmitted biometric data. In this step, the data is processed using an algorithm to detect anomalies. The output is the result of anomaly detection in the animal's health status and behavioral patterns. The server uses a generative AI model to generate prompts that estimate the animal's emotions and desires from this analysis result.

[0125] Step 3:

[0126] The server generates a notification based on the results of anomaly detection. The input is the anomaly data obtained through analysis and the estimated state of the animal. Based on this information, the server creates a notification message suggesting specific corrective actions for the user and sends it to the terminal. The output is the notification message that the user receives in real time.

[0127] Step 4:

[0128] The terminal displays notifications received from the server to the user. The input is the notification message sent from the server. The terminal displays this notification on the screen, providing the user with information to take appropriate action regarding the animal. The output is the animal's current condition and recommended actions as perceived by the user.

[0129] Step 5:

[0130] The user modifies their actions towards the animal based on notifications and shares data with medical professionals as needed. The input is the content of the notification displayed on the device. The user takes appropriate action to improve the animal's condition and configures the system to send data from the server to the veterinarian as needed. The output is the specific behavioral changes made towards the animal and the situational data collected by the professional.

[0131] 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.

[0132] This invention is a system that considers not only the animal's condition but also the user's emotional state in order to improve the interaction between the animal and its owner. The system comprises a wearable device attached to the animal, a server for analyzing data, a terminal for displaying notifications, and an emotion engine for analyzing the user's emotions.

[0133] First, wearable devices are attached to the animal's body to collect data on activity levels, sleep, vocalizations, and movements in real time. This data is transmitted wirelessly to a server. The server uses this received data to analyze the animal's health status and behavioral patterns.

[0134] The server then passes the user's facial expressions and voice data entered from the terminal to the emotion engine. This engine uses advanced machine learning algorithms to identify the user's emotional state and provides the results to the server. For example, it can identify whether the user is stressed or relaxed.

[0135] The server determines corrective actions based on data that includes both the animal's condition and the user's emotional state. It not only generates general notifications about the animal's behavior and health, but also provides more personalized advice by suggesting coping strategies adapted to the user's emotions.

[0136] For example, if the server analyzes the user's emotions and determines that they are highly stressed, it will suggest an immediate task to perform with the animal and notify the user's device of how to do it. Conversely, if the server determines that the user is relaxed, it can also suggest training methods that take more time but are effective, or games aimed at relaxation.

[0137] The device displays generated notifications to the user, providing guidance for selecting specific actions to take regarding the animal. It also shares data with veterinarians as needed, receiving feedback from medical professionals. This feedback is displayed to the user through the device, allowing them to consider further actions.

[0138] This system provides comprehensive support based on the condition of both the animal and the user, enriching daily life with pets and enabling pet owners to better understand and respond to their animals' needs.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] The server receives data on animal activity levels, sleep, vocalizations, and behavior from wearable devices. This data is collected regularly in real time and made available directly on the server.

[0142] Step 2:

[0143] The server transfers the user's facial expressions and voice data collected via the terminal to the emotion engine. The emotion engine analyzes this data to identify the user's emotional state. The results include stress levels and relaxation levels.

[0144] Step 3:

[0145] The server comprehensively analyzes animal behavioral data and user emotional data. While evaluating the animals' health status and behavioral anomalies, it optimizes adjustment measures based on the user's emotional state.

[0146] Step 4:

[0147] The server generates notifications based on the analysis results. These notifications include not only standard advice about the animal's condition, but also specific instructions tailored to the user's emotions. This may include stress-relieving play or training methods.

[0148] Step 5:

[0149] The server sends the generated notification to the device. The notification is displayed to the user on the device, and the user can check its contents.

[0150] Step 6:

[0151] The user reviews the notification received on their device and decides on specific adjustments to be taken for the animal. Based on the notification, they are shown what actions to take immediately and what to consider in the future.

[0152] Step 7:

[0153] The server offers the option of sharing animal health data with veterinarians, which is expected to provide expert feedback on the animals' condition.

[0154] Step 8:

[0155] The device receives feedback from veterinarians and presents it to the user. Based on this feedback, the user can then consider further actions.

[0156] (Example 2)

[0157] 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".

[0158] There is a need to deepen the relationship between animals and their owners, and to provide comprehensive support that simultaneously considers the animal's health status, behavioral patterns, and the user's emotional state. However, current technology is limited to analyzing animal data and individual health indicators, and has limitations in proposing interactions and adjustment measures that take the user's emotional state into account. Therefore, a new system is needed to deepen mutual understanding between animals and their owners and improve the quality of their daily lives.

[0159] 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.

[0160] In this invention, the server includes means for receiving animal activity data, means for analyzing the received data to evaluate health status and behavioral tendencies, and means for analyzing facial and voice data to identify the user's emotional state. This enables improved mutual understanding and relationships by proposing adjustment measures adapted to both the animal and the user.

[0161] "Animals" refers to living organisms other than humans, and in this invention, it refers to organisms kept as pets.

[0162] "Activity data" refers to information about an animal's exercise level, sleep, vocalizations, and movements, and is used to assess the animal's health and behavioral tendencies.

[0163] A "device" refers to an instrument attached to an animal's body that collects activity data and transmits it wirelessly.

[0164] A "server" refers to an information processing device that receives data and performs processing such as analysis, evaluation, and notification generation.

[0165] "Analysis means" refers to a process or tool for evaluating and identifying the health status and behavioral patterns of animals, or the emotional state of users, using acquired data.

[0166] "Means of receiving" refers to the process or tools used to import data from external sources into a server or other device.

[0167] "User" refers to the owner of an animal that uses the system of the present invention, and is also the subject of analysis of their emotional state.

[0168] "Notifications" refer to information or instructions generated based on analysis results and sent to the user.

[0169] A "healthcare professional" refers to a person who possesses expertise in animal medicine and provides feedback on animal health.

[0170] This invention provides a system that offers comprehensive support by evaluating the health status and behavioral patterns of animals while also considering the emotional state of the user. The system mainly consists of an activity data collection device attached to the animal, a server that analyzes the data, a terminal that notifies the user, and an emotion analysis engine that analyzes the user's emotions.

[0171] The server receives real-time data wirelessly from devices that collect animal activity data. It then uses libraries such as Python's Pandas and NumPy to analyze this data and evaluate the animals' health and behavioral tendencies. This allows pet owners to detect abnormalities early.

[0172] Furthermore, the device collects the user's facial expressions and voice data and sends it to an emotion analysis engine. The emotion analysis engine uses a generative AI model to identify the user's emotional state. For example, if the user is smiling, it determines that they are relaxed.

[0173] The server integrates these analysis results and devises adjustment measures adapted to both the animal and the user. The resulting notifications are then delivered to the user via the terminal. For example, if the animal is unstable and the user is stressed, the server can suggest a short refreshing activity.

[0174] As a concrete example, here is an example of a prompt message:

[0175] "What activities would you suggest to a user who is saddened because their dog has been lethargic lately?"

[0176] In this way, the system provides optimal support for both animals and users, improving the quality of life for both.

[0177] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0178] Step 1:

[0179] The server receives data wirelessly from activity data collection devices attached to animals. It acquires data on activity levels, sleep patterns, vocalizations, and movements as input. The server uses analysis software to organize this data and generate foundational data for understanding the animals' health status and behavioral tendencies in real time. This output includes indicators of health status and abnormal behavioral patterns.

[0180] Step 2:

[0181] The device collects the user's facial expressions and voice data. It uses the smartphone's camera and microphone as input to record changes in the user's facial expressions and voice tone. This data is sent to a server and fed into an emotion analysis engine. The server uses a generative AI model to identify the user's emotional state. The output provides an emotional state, such as whether the user is stressed or relaxed.

[0182] Step 3:

[0183] The server integrates the analyzed animal's health status, behavioral tendencies, and the user's emotional state. The input is the analysis results from Step 1 and Step 2. Based on these results, the server devises adjustment measures and considers using a generative AI model, including the use of prompts. The output is specific suggestions and notifications for the animal and the user.

[0184] Step 4:

[0185] The terminal displays suggestions and notifications provided by the server to the user. It receives notification data from the server as input. The terminal displays this data on the screen as user information, suggesting activities and measures to be taken with the animals. The output consists of specific action guidelines and suggestions provided to the user.

[0186] Step 5:

[0187] Users adjust their interactions with animals and provide feedback based on the measures and activities suggested by the device. Input includes reporting user behavior and impressions to the system via the device. This feedback is accumulated by the system and used for future analysis and improvement of the accuracy of suggestions. Output consists of user practice results and opinions necessary for system improvement.

[0188] (Application Example 2)

[0189] 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".

[0190] Lack of communication and misunderstandings between animals and their owners can lead to stress and frustration, negatively impacting the animal's health and behavior. Furthermore, if owners cannot accurately understand their animal's condition, appropriate responses and care become difficult. Additionally, insufficient consideration of the user's emotional state results in inadequately optimized interactions with animals.

[0191] 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.

[0192] In this invention, the server includes means for receiving information from a device for acquiring biological information of animals, means for analyzing the received information and evaluating the animal's health status and behavioral characteristics, and means for acquiring and analyzing the user's emotional state. This enables comprehensive judgment based on the interaction between the animal and the user, and improves personalized care and communication.

[0193] "Animal biometric information" refers to various data related to the health status and activity levels of animals.

[0194] An "information terminal" refers to an electronic device that can receive and display notifications.

[0195] "User emotional state" refers to data used to analyze the user's psychological and emotional state.

[0196] "Analysis" is the process of examining received data in detail to extract meaningful information.

[0197] A "notification" is an informational message generated by a system that serves to draw the user's attention or suggest an action.

[0198] A "specialist" refers to a medical professional who possesses expertise related to animal health and behavior.

[0199] The system for implementing this invention consists of multiple components. First, a wearable device attached to an animal collects its biometric information in real time and transmits it to a server via wireless communication. The server operates on a cloud platform and performs detailed analysis of the animal's biometric information. The analysis includes the animal's activity level, sleep patterns, vocalizations, and movement information. This makes it possible to evaluate the animal's health status and behavioral characteristics.

[0200] Furthermore, the server receives facial and voice data transmitted from the user's information terminal and uses an emotion analysis engine to identify the user's emotional state. This can utilize advanced machine learning algorithms. The analysis results are integrated with the assessment results regarding the animal's condition, and based on the processing results on the server, a notification is generated to suggest corrective actions.

[0201] Notifications are sent to information terminals. These terminals include smartphones and tablets and function as user interfaces. The terminals provide users with specific suggestions for actions and care tailored to the animal's condition. For example, if the user is stressed, suggestions for short, playful activities with the animal will be provided. Such suggestions are displayed to the user using prompt messages generated by the system.

[0202] As a concrete example, the following prompt statements are possible:

[0203] "Your stress level is high today. How about spending about 20 minutes playing with your dog in the park?"

[0204] "A short walk is also recommended. Let's take it easy today."

[0205] This invention provides support for both animals and users to live better lives.

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

[0207] Step 1:

[0208] Wearable devices acquire biometric information from animals. Inputs include animal activity levels, sleep patterns, vocalizations, and movement data. This data is transmitted wirelessly to a server. The output is the data stream received by the server.

[0209] Step 2:

[0210] The server analyzes the received data. The input is the data stream obtained in step 1. Machine learning algorithms are used to process the data in order to evaluate the health status and behavioral characteristics of the animals. The output is the health assessment result of the animals obtained through the analysis.

[0211] Step 3:

[0212] The server receives user facial expressions and voice data from the information terminal. The input is emotion data transmitted from the terminal. The emotion analysis engine is used to identify the user's emotional state. The output is the result of the user's emotion analysis.

[0213] Step 4:

[0214] The server integrates the animal evaluation results and the user's sentiment analysis results. The input is the results from steps 2 and 3. Based on this integrated data, data processing is performed to determine adjustment measures for the animals and users. The output is a plan of the adjustment measures to be proposed.

[0215] Step 5:

[0216] The server generates a notification based on the adjustment measures. The input is the adjustment plan from step 4. A generation AI model is used to create a prompt message, which is presented clearly to the user. The output is a notification sent to the information terminal.

[0217] Step 6:

[0218] The terminal receives notifications sent from the server and displays them to the user. The input is the notification from step 5. The user selects specific actions or care for the animal through suggested prompts. The output is the user's action selection.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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".

[0235] This invention is a system for supporting animal health management and behavioral analysis, and consists of a wearable device equipped with sensors, a server for processing data, and a terminal for providing information. Specific embodiments are described below.

[0236] First, the wearable devices attached to the animals contain various sensors to acquire data on activity levels, sleep, and diet. These devices transmit the data acquired in real time from the sensors to a server via wireless communication. The server then uses this data to analyze the animals' health and behavior.

[0237] In the analysis, the server first compares each data point to a baseline value to assess the user's health status and detects any data that deviates from normal. If activity levels are significantly lower than normal, the server calculates the risk associated with that health status and determines it to be abnormal.

[0238] Regarding behavioral data, the server uses advanced algorithms to analyze the animals' behavioral patterns. For example, based on the frequency and pattern of barking, it can identify if an animal is experiencing stress. This behavioral analysis is also used to estimate the emotions and needs of pets.

[0239] Based on the analysis results, the server generates a notification tailored to the animal's condition and sends it to the device. This notification includes monitoring results of the animal's health status and specific instructions for behavioral improvement. The user receives the notification on their device and can take appropriate action for the animal.

[0240] For example, if the device receives a notification that "your pet's activity level has decreased," the user might consider increasing the amount of time spent walking their pet or providing indoor playtime. If a notification about barking is received, actionable advice such as "playing certain music may calm your pet" will be provided.

[0241] Furthermore, the server has the functionality to share animal health data with medical professionals such as veterinarians. This allows veterinarians to accurately understand the situation and provide appropriate treatment and feedback. This feedback is notified to the user via the terminal, helping them to take necessary actions.

[0242] As described above, this system comprehensively supports animal health management and behavioral improvement, while also enhancing convenience for pet owners.

[0243] The following describes the processing flow.

[0244] Step 1:

[0245] The server receives data on animal activity levels, sleep, and diet from wearable devices. This includes raw data acquired by various sensors.

[0246] Step 2:

[0247] The server preprocesses the received data. This preprocessing includes data cleansing, such as imputing missing values ​​and removing noise. This process prepares the dataset for analysis.

[0248] Step 3:

[0249] The server assesses the health status of animals based on pre-processed data. Specifically, it compares the data to historical baseline data to determine whether it is within the normal range or abnormal. This assessment identifies risks if abnormal values ​​are present.

[0250] Step 4:

[0251] The server applies behavioral analysis algorithms to analyze the animals' behavioral patterns. Based on the data, it estimates the presence or absence of problematic behaviors and the animals' emotional states. For example, it identifies the frequency and patterns of abnormal barking and investigates their causes.

[0252] Step 5:

[0253] The server uses a natural language generation engine to create notifications based on the analysis of the animals' health status and behavior. These notifications include specific actions to take and advice for pet owners.

[0254] Step 6:

[0255] The server sends the generated notification to the device. The notification is immediately conveyed to the owner via the application and becomes available for viewing on the dashboard.

[0256] Step 7:

[0257] The user checks notifications received on their device and decides what action is needed for the animal. Based on the notification, they select actions to improve the animal's behavior and health.

[0258] Step 8:

[0259] The server shares health data with medical professionals such as veterinarians as needed. This sharing takes place via the cloud and provides the professionals with the basic information they need to conduct detailed analysis.

[0260] Step 9:

[0261] The device receives feedback from veterinarians and presents it to the user. Based on this feedback, the user considers further medical interventions.

[0262] (Example 1)

[0263] 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."

[0264] Modern households are required to accurately understand and properly manage their pets' health and behavioral patterns. However, achieving this requires a system that accurately analyzes the diverse data obtained from animals and provides owners with the necessary information. Conventional systems have the challenge of not being able to accurately estimate animals' emotions and desires and propose appropriate adjustment measures.

[0265] 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.

[0266] In this invention, the server includes means for receiving information from a wearable device equipped with a detection device for acquiring animal behavior and health information, means for analyzing the received information and evaluating the animal's health status and behavioral patterns, and means for generating notifications to propose adjustment measures for the animal based on the evaluation results. This makes it possible to understand the animal's health status and behavioral patterns in detail and to achieve effective management and improvement.

[0267] "Animals" refers to living creatures such as mammals, birds, and reptiles that are kept as pets or livestock.

[0268] "Movement" is a concept used to observe and analyze the bodily movements and actions that animals perform on a daily basis.

[0269] "Health information" refers to data that indicates an animal's physical condition, specifically including body temperature, heart rate, and activity level.

[0270] A "detection device" refers to equipment consisting of sensors attached to animals, used to acquire information about the animals' movements and health.

[0271] A "wearable device" is a device that is directly attached to an animal, equipped with sensors and communication functions, and used to collect and transmit data in real time.

[0272] "Information" is a broad concept referring to data acquired by detection devices and the results of their analysis.

[0273] "Analysis" refers to data processing performed to evaluate health status and behavioral patterns based on acquired data.

[0274] "Health status" refers to indicators that show the physical and mental well-being and presence or absence of abnormalities in an animal.

[0275] "Behavioral patterns" refer to certain patterns or tendencies in an animal's behavior.

[0276] "Adjustment measures" refer to specific actions and suggestions taken to improve the health and behavior of animals based on the evaluation results.

[0277] "Notifications" refer to messages and alerts used to inform users about analysis results and corrective actions.

[0278] "Electronic devices" refer to digital devices used by users to check the condition of animals and take appropriate action as needed.

[0279] "Medical professional" refers to a veterinarian or other healthcare worker who possesses knowledge and skills related to animal health.

[0280] "Generation" refers to the process of creating new information or notifications, and is particularly used when employing AI models.

[0281] This invention is a system for supporting animal health management and behavioral analysis. The system mainly consists of wearable devices, a server, and terminals. The following describes each component and how they work together in detail.

[0282] First, the wearable device is attached to the animal and is equipped with an accelerometer, heart rate sensor, environmental sensor, etc. This device acquires the animal's movements and health information in real time. The acquired data is transmitted to a server using wireless communication technologies such as Bluetooth or Wi-Fi.

[0283] The server uses an AI model to analyze the received data. During the analysis, the data is compared to baseline values ​​to evaluate the animal's health status and behavior. If a health abnormality is detected, the server generates a notification to suggest specific adjustment measures. For example, if activity levels decrease, it might generate a notification such as, "We recommend increasing your pet's exercise."

[0284] The generated notification is sent from the server to the electronic terminal. The terminal is equipped with a user interface, and the user can check the notification and take necessary actions. As an example of a specific action method, there is a method of relieving animal stress by playing specific music. In addition, the terminal also has a function of sharing data with medical experts such as veterinarians, and can receive feedback from experts via the server.

[0285] In implementing this system, it is possible to precisely analyze the behavior patterns of animals using a generative AI model and achieve highly accurate estimation. Also, as an example of a prompt sentence, usage scenarios in the form of "Please propose an optimal amount of exercise based on the recent behavior data of the pet." are assumed.

[0286] As described above, this invention comprehensively supports the health management and behavior monitoring of animals, and provides a useful means for the owner to appropriately manage the pet.

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

[0288] Step 1:

[0289] The wearable device is worn on the animal, and sensors are used to acquire the animal's motion and health information in real time. The input data includes acceleration, heart rate, ambient environmental information, etc., and these information are recorded as digital signals. As a specific motion, during the animal's walking, the acceleration sensor measures the body's sway, which is digitally output as the amount of activity.

[0290] Step 2:

[0291] Data obtained from wearable devices is transmitted to a server using wireless communication technology. The input data is sent in a compressed format, and the server receives and decompresses it. The data is processed in JSON format and formatted for parsing. Specifically, after receiving the data, the server stores it in a database.

[0292] Step 3:

[0293] The server uses an AI model to analyze the received data. The input data consists of behavioral and health information, which is evaluated as health status and behavioral patterns. The analysis includes comparison with baseline values ​​and pattern recognition. For example, if the activity level falls below the baseline value, the server detects an anomaly and assesses the health risk.

[0294] Step 4:

[0295] The server generates notifications based on the analysis results. The input is data on the evaluated health status and behavior patterns, and the output is a notification that proposes specific adjustment measures. Specifically, it creates a message such as, "Your pet's activity level has decreased. Please increase its exercise."

[0296] Step 5:

[0297] The server sends the generated notification to the electronic device. The input is the notification message, and the output is an alert to the user's electronic device. Specifically, the device immediately displays the notification through its user interface.

[0298] Step 6:

[0299] The user checks the notification received on their device and takes appropriate action. The input is the notification message, and the output is the user's action. Specifically, the user adjusts their actions based on the suggestion, such as taking their pet for a walk.

[0300] Step 7:

[0301] The terminal shares information with medical experts such as veterinarians via a server, enabling feedback to be received. Specifically, advice from the veterinarian is displayed on the terminal to provide support for the user to take more appropriate actions.

[0302] (Application Example 1)

[0303] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0304] For the health management and behavior analysis of animals, real-time data acquisition, rapid detection of abnormal behaviors, and proposal of countermeasures are required. However, many current systems have problems such as taking a long time for data analysis and preventing the owner from taking immediate countermeasures. It is also difficult to appropriately estimate the emotions and desires of animals and immediately determine effective countermeasures. Therefore, there is a need to develop a system that monitors the health status and behavior of animals in real time and immediately proposes appropriate countermeasures.

[0305] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0306] In this invention, the server includes a device that receives data of the animal from a wearable device equipped with a sensing device for acquiring behavior and health data of the animal, a device that analyzes the received data and evaluates the health status and behavior pattern of the animal, and a device that generates a notification for proposing adjustment measures for the animal based on the result of the evaluation. Thereby, it becomes possible to monitor the health status of the animal in real time, quickly propose necessary countermeasures, and shorten the response time.

[0307] "Animal behavior" refers to various actions and patterns that an animal takes in daily life and is an important indicator indicating the health status and emotions.

[0308] "Health data" refers to a collection of information that shows biomedical indicators such as an animal's body temperature, heart rate, and respiratory rate, and forms the basis for evaluating the health status of an animal.

[0309] A "sensing device" is a device that includes sensors used to acquire physical activity and physiological data of animals, and is often incorporated into wearable devices.

[0310] A "wearable device" is a device attached to an animal, which includes a sensing device and is responsible for acquiring health and behavioral data of the animal.

[0311] "Abnormal behavior" refers to actions that deviate from normal behavioral patterns and may indicate stress or health problems in animals.

[0312] An "information terminal" is an electronic device used to provide users with notifications and suggested adjustment measures, and includes smartphones and smart glasses.

[0313] A "medical professional" is a healthcare worker with specialized knowledge, such as a veterinarian, who is involved in the assessment and treatment of an animal's health.

[0314] A "visualization application" is software that visually displays data and presents users with analysis results of abnormal behavior and countermeasures.

[0315] The system for realizing this invention consists of a wearable device attached to an animal, a server for processing data, and a terminal for displaying information. The wearable device includes a sensing device for acquiring animal behavior and health data, and transmits this data to the server using wireless communication. The server analyzes the received data and uses an algorithm to evaluate the animal's health status and behavioral patterns. This algorithm detects abnormal behavior and estimates the animal's emotions and desires.

[0316] As a concrete example, the server monitors the animal's heart rate and activity level in real time and compares them to normal levels. If an abnormal pattern is detected, it sends a notification to the user and suggests appropriate countermeasures. For example, if the animal's heart rate suddenly increases, the device will receive a notification stating, "The animal may be excited. Please provide a calm environment to help it settle down." In this case, a generative AI model is used to generate prompts that recommend actions that take the animal's condition into consideration. An example of a specific prompt might be, "Analyze the pet's behavioral data and suggest appropriate relaxation methods."

[0317] The terminal displays information received from the server in an easy-to-understand manner for the user and supports communication with experts as needed. This system also includes a function to share collected data with medical professionals, enabling veterinarians to gain a more accurate understanding of the situation and utilize it in treatment.

[0318] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0319] Step 1:

[0320] Wearable devices acquire animal behavior and health data using sensing devices. Inputs are real-time data such as animal activity levels and heart rate, which are transmitted wirelessly to a server. Outputs are the animal's biometric data used by the server for analysis.

[0321] Step 2:

[0322] The server analyzes the data received from the wearable device. The input is the transmitted biometric data. In this step, the data is processed using an algorithm to detect anomalies. The output is the result of anomaly detection in the animal's health status and behavioral patterns. The server uses a generative AI model to generate prompts that estimate the animal's emotions and desires from this analysis result.

[0323] Step 3:

[0324] The server generates a notification based on the results of anomaly detection. The input is the anomaly data obtained through analysis and the estimated state of the animal. Based on this information, the server creates a notification message suggesting specific corrective actions for the user and sends it to the terminal. The output is the notification message that the user receives in real time.

[0325] Step 4:

[0326] The terminal displays notifications received from the server to the user. The input is the notification message sent from the server. The terminal displays this notification on the screen, providing the user with information to take appropriate action regarding the animal. The output is the animal's current condition and recommended actions as perceived by the user.

[0327] Step 5:

[0328] The user modifies their actions towards the animal based on notifications and shares data with medical professionals as needed. The input is the content of the notification displayed on the device. The user takes appropriate action to improve the animal's condition and configures the system to send data from the server to the veterinarian as needed. The output is the specific behavioral changes made towards the animal and the situational data collected by the professional.

[0329] 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.

[0330] This invention is a system that considers not only the animal's condition but also the user's emotional state in order to improve the interaction between the animal and its owner. The system comprises a wearable device attached to the animal, a server for analyzing data, a terminal for displaying notifications, and an emotion engine for analyzing the user's emotions.

[0331] First, wearable devices are attached to the animal's body to collect data on activity levels, sleep, vocalizations, and movements in real time. This data is transmitted wirelessly to a server. The server uses this received data to analyze the animal's health status and behavioral patterns.

[0332] The server then passes the user's facial expressions and voice data entered from the terminal to the emotion engine. This engine uses advanced machine learning algorithms to identify the user's emotional state and provides the results to the server. For example, it can identify whether the user is stressed or relaxed.

[0333] The server determines corrective actions based on data that includes both the animal's condition and the user's emotional state. It not only generates general notifications about the animal's behavior and health, but also provides more personalized advice by suggesting coping strategies adapted to the user's emotions.

[0334] For example, if the server analyzes the user's emotions and determines that they are highly stressed, it will suggest an immediate task to perform with the animal and notify the user's device of how to do it. Conversely, if the server determines that the user is relaxed, it can also suggest training methods that take more time but are effective, or games aimed at relaxation.

[0335] The device displays generated notifications to the user, providing guidance for selecting specific actions to take regarding the animal. It also shares data with veterinarians as needed, receiving feedback from medical professionals. This feedback is displayed to the user through the device, allowing them to consider further actions.

[0336] This system provides comprehensive support based on the condition of both the animal and the user, enriching daily life with pets and enabling pet owners to better understand and respond to their animals' needs.

[0337] The following describes the processing flow.

[0338] Step 1:

[0339] The server receives data on animal activity levels, sleep, vocalizations, and behavior from wearable devices. This data is collected regularly in real time and made available directly on the server.

[0340] Step 2:

[0341] The server transfers the user's facial expressions and voice data collected via the terminal to the emotion engine. The emotion engine analyzes this data to identify the user's emotional state. The results include stress levels and relaxation levels.

[0342] Step 3:

[0343] The server comprehensively analyzes animal behavioral data and user emotional data. While evaluating the animals' health status and behavioral anomalies, it optimizes adjustment measures based on the user's emotional state.

[0344] Step 4:

[0345] The server generates notifications based on the analysis results. These notifications include not only standard advice about the animal's condition, but also specific instructions tailored to the user's emotions. This may include stress-relieving play or training methods.

[0346] Step 5:

[0347] The server sends the generated notification to the device. The notification is displayed to the user on the device, and the user can check its contents.

[0348] Step 6:

[0349] The user reviews the notification received on their device and decides on specific adjustments to be taken for the animal. Based on the notification, they are shown what actions to take immediately and what to consider in the future.

[0350] Step 7:

[0351] The server offers the option of sharing animal health data with veterinarians, which is expected to provide expert feedback on the animals' condition.

[0352] Step 8:

[0353] The device receives feedback from veterinarians and presents it to the user. Based on this feedback, the user can then consider further actions.

[0354] (Example 2)

[0355] 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".

[0356] There is a need to deepen the relationship between animals and their owners, and to provide comprehensive support that simultaneously considers the animal's health status, behavioral patterns, and the user's emotional state. However, current technology is limited to analyzing animal data and individual health indicators, and has limitations in proposing interactions and adjustment measures that take the user's emotional state into account. Therefore, a new system is needed to deepen mutual understanding between animals and their owners and improve the quality of their daily lives.

[0357] 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.

[0358] In this invention, the server includes means for receiving animal activity data, means for analyzing the received data to evaluate health status and behavioral tendencies, and means for analyzing facial and voice data to identify the user's emotional state. This enables improved mutual understanding and relationships by proposing adjustment measures adapted to both the animal and the user.

[0359] "Animals" refers to living organisms other than humans, and in this invention, it refers to organisms kept as pets.

[0360] "Activity data" refers to information about an animal's exercise level, sleep, vocalizations, and movements, and is used to assess the animal's health and behavioral tendencies.

[0361] A "device" refers to an instrument attached to an animal's body that collects activity data and transmits it wirelessly.

[0362] A "server" refers to an information processing device that receives data and performs processing such as analysis, evaluation, and notification generation.

[0363] "Analysis means" refers to a process or tool for evaluating and identifying the health status and behavioral patterns of animals, or the emotional state of users, using acquired data.

[0364] "Means of receiving" refers to the process or tools used to import data from external sources into a server or other device.

[0365] "User" refers to the owner of an animal that uses the system of the present invention, and is also the subject of analysis of their emotional state.

[0366] "Notifications" refer to information or instructions generated based on analysis results and sent to the user.

[0367] A "healthcare professional" refers to a person who possesses expertise in animal medicine and provides feedback on animal health.

[0368] This invention provides a system that offers comprehensive support by evaluating the health status and behavioral patterns of animals while also considering the emotional state of the user. The system mainly consists of an activity data collection device attached to the animal, a server that analyzes the data, a terminal that notifies the user, and an emotion analysis engine that analyzes the user's emotions.

[0369] The server receives real-time data wirelessly from devices that collect animal activity data. It then uses libraries such as Python's Pandas and NumPy to analyze this data and evaluate the animals' health and behavioral tendencies. This allows pet owners to detect abnormalities early.

[0370] Furthermore, the device collects the user's facial expressions and voice data and sends it to an emotion analysis engine. The emotion analysis engine uses a generative AI model to identify the user's emotional state. For example, if the user is smiling, it determines that they are relaxed.

[0371] The server integrates these analysis results and devises adjustment measures adapted to both the animal and the user. The resulting notifications are then delivered to the user via the terminal. For example, if the animal is unstable and the user is stressed, the server can suggest a short refreshing activity.

[0372] As a concrete example, here is an example of a prompt message:

[0373] "What activities would you suggest to a user who is saddened because their dog has been lethargic lately?"

[0374] In this way, the system provides optimal support for both animals and users, improving the quality of life for both.

[0375] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0376] Step 1:

[0377] The server receives data wirelessly from activity data collection devices attached to animals. It acquires data on activity levels, sleep patterns, vocalizations, and movements as input. The server uses analysis software to organize this data and generate foundational data for understanding the animals' health status and behavioral tendencies in real time. This output includes indicators of health status and abnormal behavioral patterns.

[0378] Step 2:

[0379] The device collects the user's facial expressions and voice data. It uses the smartphone's camera and microphone as input to record changes in the user's facial expressions and voice tone. This data is sent to a server and fed into an emotion analysis engine. The server uses a generative AI model to identify the user's emotional state. The output provides an emotional state, such as whether the user is stressed or relaxed.

[0380] Step 3:

[0381] The server integrates the analyzed animal's health status, behavioral tendencies, and the user's emotional state. The input is the analysis results from Step 1 and Step 2. Based on these results, the server devises adjustment measures and considers using a generative AI model, including the use of prompts. The output is specific suggestions and notifications for the animal and the user.

[0382] Step 4:

[0383] The terminal displays suggestions and notifications provided by the server to the user. It receives notification data from the server as input. The terminal displays this data on the screen as user information, suggesting activities and measures to be taken with the animals. The output consists of specific action guidelines and suggestions provided to the user.

[0384] Step 5:

[0385] Users adjust their interactions with animals and provide feedback based on the measures and activities suggested by the device. Input includes reporting user behavior and impressions to the system via the device. This feedback is accumulated by the system and used for future analysis and improvement of the accuracy of suggestions. Output consists of user practice results and opinions necessary for system improvement.

[0386] (Application Example 2)

[0387] 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."

[0388] Lack of communication and misunderstandings between animals and their owners can lead to stress and frustration, negatively impacting the animal's health and behavior. Furthermore, if owners cannot accurately understand their animal's condition, appropriate responses and care become difficult. Additionally, insufficient consideration of the user's emotional state results in inadequately optimized interactions with animals.

[0389] 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.

[0390] In this invention, the server includes means for receiving information from a device for acquiring biological information of animals, means for analyzing the received information and evaluating the animal's health status and behavioral characteristics, and means for acquiring and analyzing the user's emotional state. This enables comprehensive judgment based on the interaction between the animal and the user, and improves personalized care and communication.

[0391] "Animal biometric information" refers to various data related to the health status and activity levels of animals.

[0392] An "information terminal" refers to an electronic device that can receive and display notifications.

[0393] "User emotional state" refers to data used to analyze the user's psychological and emotional state.

[0394] "Analysis" is the process of examining received data in detail to extract meaningful information.

[0395] A "notification" is an informational message generated by a system that serves to draw the user's attention or suggest an action.

[0396] A "specialist" refers to a medical professional who possesses expertise related to animal health and behavior.

[0397] The system for implementing this invention consists of multiple components. First, a wearable device attached to an animal collects its biometric information in real time and transmits it to a server via wireless communication. The server operates on a cloud platform and performs detailed analysis of the animal's biometric information. The analysis includes the animal's activity level, sleep patterns, vocalizations, and movement information. This makes it possible to evaluate the animal's health status and behavioral characteristics.

[0398] Furthermore, the server receives facial and voice data transmitted from the user's information terminal and uses an emotion analysis engine to identify the user's emotional state. This can utilize advanced machine learning algorithms. The analysis results are integrated with the assessment results regarding the animal's condition, and based on the processing results on the server, a notification is generated to suggest corrective actions.

[0399] Notifications are sent to information terminals. These terminals include smartphones and tablets and function as user interfaces. The terminals provide users with specific suggestions for actions and care tailored to the animal's condition. For example, if the user is stressed, suggestions for short, playful activities with the animal will be provided. Such suggestions are displayed to the user using prompt messages generated by the system.

[0400] As a concrete example, the following prompt statements are possible:

[0401] "Your stress level is high today. How about spending about 20 minutes playing with your dog in the park?"

[0402] "A short walk is also recommended. Let's take it easy today."

[0403] This invention provides support for both animals and users to live better lives.

[0404] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0405] Step 1:

[0406] Wearable devices acquire biometric information from animals. Inputs include animal activity levels, sleep patterns, vocalizations, and movement data. This data is transmitted wirelessly to a server. The output is the data stream received by the server.

[0407] Step 2:

[0408] The server analyzes the received data. The input is the data stream obtained in step 1. Machine learning algorithms are used to process the data in order to evaluate the health status and behavioral characteristics of the animals. The output is the health assessment result of the animals obtained through the analysis.

[0409] Step 3:

[0410] The server receives user facial expressions and voice data from the information terminal. The input is emotion data transmitted from the terminal. The emotion analysis engine is used to identify the user's emotional state. The output is the result of the user's emotion analysis.

[0411] Step 4:

[0412] The server integrates the animal evaluation results and the user's sentiment analysis results. The input is the results from steps 2 and 3. Based on this integrated data, data processing is performed to determine adjustment measures for the animals and users. The output is a plan of the adjustment measures to be proposed.

[0413] Step 5:

[0414] The server generates a notification based on the adjustment measures. The input is the adjustment plan from step 4. A generation AI model is used to create a prompt message, which is presented clearly to the user. The output is a notification sent to the information terminal.

[0415] Step 6:

[0416] The terminal receives notifications sent from the server and displays them to the user. The input is the notification from step 5. The user selects specific actions or care for the animal through suggested prompts. The output is the user's action selection.

[0417] 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.

[0418] 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.

[0419] 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.

[0420] [Third Embodiment]

[0421] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0422] 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.

[0423] 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).

[0424] 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.

[0425] 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.

[0426] 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).

[0427] 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.

[0428] 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.

[0429] 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.

[0430] 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.

[0431] 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.

[0432] 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".

[0433] This invention is a system for supporting animal health management and behavioral analysis, and consists of a wearable device equipped with sensors, a server for processing data, and a terminal for providing information. Specific embodiments are described below.

[0434] First, the wearable devices attached to the animals contain various sensors to acquire data on activity levels, sleep, and diet. These devices transmit the data acquired in real time from the sensors to a server via wireless communication. The server then uses this data to analyze the animals' health and behavior.

[0435] In the analysis, the server first compares each data point to a baseline value to assess the user's health status and detects any data that deviates from normal. If activity levels are significantly lower than normal, the server calculates the risk associated with that health status and determines it to be abnormal.

[0436] Regarding behavioral data, the server uses advanced algorithms to analyze the animals' behavioral patterns. For example, based on the frequency and pattern of barking, it can identify if an animal is experiencing stress. This behavioral analysis is also used to estimate the emotions and needs of pets.

[0437] Based on the analysis results, the server generates a notification tailored to the animal's condition and sends it to the device. This notification includes monitoring results of the animal's health status and specific instructions for behavioral improvement. The user receives the notification on their device and can take appropriate action for the animal.

[0438] For example, if the device receives a notification that "your pet's activity level has decreased," the user might consider increasing the amount of time spent walking their pet or providing indoor playtime. If a notification about barking is received, actionable advice such as "playing certain music may calm your pet" will be provided.

[0439] Furthermore, the server has the functionality to share animal health data with medical professionals such as veterinarians. This allows veterinarians to accurately understand the situation and provide appropriate treatment and feedback. This feedback is notified to the user via the terminal, helping them to take necessary actions.

[0440] As described above, this system comprehensively supports animal health management and behavioral improvement, while also enhancing convenience for pet owners.

[0441] The following describes the processing flow.

[0442] Step 1:

[0443] The server receives data on animal activity levels, sleep, and diet from wearable devices. This includes raw data acquired by various sensors.

[0444] Step 2:

[0445] The server preprocesses the received data. This preprocessing includes data cleansing, such as imputing missing values ​​and removing noise. This process prepares the dataset for analysis.

[0446] Step 3:

[0447] The server assesses the health status of animals based on pre-processed data. Specifically, it compares the data to historical baseline data to determine whether it is within the normal range or abnormal. This assessment identifies risks if abnormal values ​​are present.

[0448] Step 4:

[0449] The server applies behavioral analysis algorithms to analyze the animals' behavioral patterns. Based on the data, it estimates the presence or absence of problematic behaviors and the animals' emotional states. For example, it identifies the frequency and patterns of abnormal barking and investigates their causes.

[0450] Step 5:

[0451] The server uses a natural language generation engine to create notifications based on the analysis of the animals' health status and behavior. These notifications include specific actions to take and advice for pet owners.

[0452] Step 6:

[0453] The server sends the generated notification to the device. The notification is immediately conveyed to the owner via the application and becomes available for viewing on the dashboard.

[0454] Step 7:

[0455] The user checks notifications received on their device and decides what action is needed for the animal. Based on the notification, they select actions to improve the animal's behavior and health.

[0456] Step 8:

[0457] The server shares health data with medical professionals such as veterinarians as needed. This sharing takes place via the cloud and provides the professionals with the basic information they need to conduct detailed analysis.

[0458] Step 9:

[0459] The device receives feedback from veterinarians and presents it to the user. Based on this feedback, the user considers further medical interventions.

[0460] (Example 1)

[0461] 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."

[0462] Modern households are required to accurately understand and properly manage their pets' health and behavioral patterns. However, achieving this requires a system that accurately analyzes the diverse data obtained from animals and provides owners with the necessary information. Conventional systems have the challenge of not being able to accurately estimate animals' emotions and desires and propose appropriate adjustment measures.

[0463] 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.

[0464] In this invention, the server includes means for receiving information from a wearable device equipped with a detection device for acquiring animal behavior and health information, means for analyzing the received information and evaluating the animal's health status and behavioral patterns, and means for generating notifications to propose adjustment measures for the animal based on the evaluation results. This makes it possible to understand the animal's health status and behavioral patterns in detail and to achieve effective management and improvement.

[0465] "Animals" refers to living creatures such as mammals, birds, and reptiles that are kept as pets or livestock.

[0466] "Movement" is a concept used to observe and analyze the bodily movements and actions that animals perform on a daily basis.

[0467] "Health information" refers to data that indicates an animal's physical condition, specifically including body temperature, heart rate, and activity level.

[0468] A "detection device" refers to equipment consisting of sensors attached to animals, used to acquire information about the animals' movements and health.

[0469] A "wearable device" is a device that is directly attached to an animal, equipped with sensors and communication functions, and used to collect and transmit data in real time.

[0470] "Information" is a broad concept referring to data acquired by detection devices and the results of their analysis.

[0471] "Analysis" refers to data processing performed to evaluate health status and behavioral patterns based on acquired data.

[0472] "Health status" refers to indicators that show the physical and mental well-being and presence or absence of abnormalities in an animal.

[0473] "Behavioral patterns" refer to certain patterns or tendencies in an animal's behavior.

[0474] "Adjustment measures" refer to specific actions and suggestions taken to improve the health and behavior of animals based on the evaluation results.

[0475] "Notifications" refer to messages and alerts used to inform users about analysis results and corrective actions.

[0476] "Electronic devices" refer to digital devices used by users to check the condition of animals and take appropriate action as needed.

[0477] "Medical professional" refers to a veterinarian or other healthcare worker who possesses knowledge and skills related to animal health.

[0478] "Generation" refers to the process of creating new information or notifications, and is particularly used when employing AI models.

[0479] This invention is a system for supporting animal health management and behavioral analysis. The system mainly consists of wearable devices, a server, and terminals. The following describes each component and how they work together in detail.

[0480] First, the wearable device is attached to the animal and is equipped with an accelerometer, heart rate sensor, environmental sensor, etc. This device acquires the animal's movements and health information in real time. The acquired data is transmitted to a server using wireless communication technologies such as Bluetooth or Wi-Fi.

[0481] The server uses an AI model to analyze the received data. During the analysis, the data is compared to baseline values ​​to evaluate the animal's health status and behavior. If a health abnormality is detected, the server generates a notification to suggest specific adjustment measures. For example, if activity levels decrease, it might generate a notification such as, "We recommend increasing your pet's exercise."

[0482] The generated notifications are sent from the server to the electronic terminal. The terminal is equipped with a user interface, allowing the user to check the notifications and take necessary actions. One example of a specific action is to alleviate the animal's stress by playing certain music. The terminal also has a function to share data with medical professionals such as veterinarians, and can receive feedback from professionals via the server.

[0483] In implementing this system, it is possible to precisely analyze animal behavior patterns using a generative AI model and achieve highly accurate estimations. Furthermore, a possible use case for prompts is, "Based on my pet's recent behavioral data, please suggest the optimal amount of exercise."

[0484] In summary, this invention comprehensively supports animal health management and behavioral monitoring, providing a useful means for pet owners to properly manage their pets.

[0485] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0486] Step 1:

[0487] The wearable device is attached to the animal and uses sensors to acquire real-time information about the animal's movements and health. The input data includes acceleration, heart rate, and information about the surrounding environment, and this information is recorded as digital signals. Specifically, while the animal is walking, the acceleration sensor measures the body's movement, and this is output digitally as an activity level.

[0488] Step 2:

[0489] Data obtained from wearable devices is transmitted to a server using wireless communication technology. The input data is sent in a compressed format, and the server receives and decompresses it. The data is processed in JSON format and formatted for parsing. Specifically, after receiving the data, the server stores it in a database.

[0490] Step 3:

[0491] The server uses an AI model to analyze the received data. The input data consists of behavioral and health information, which is evaluated as health status and behavioral patterns. The analysis includes comparison with baseline values ​​and pattern recognition. For example, if the activity level falls below the baseline value, the server detects an anomaly and assesses the health risk.

[0492] Step 4:

[0493] The server generates notifications based on the analysis results. The input is data on the evaluated health status and behavior patterns, and the output is a notification that proposes specific adjustment measures. Specifically, it creates a message such as, "Your pet's activity level has decreased. Please increase its exercise."

[0494] Step 5:

[0495] The server sends the generated notification to the electronic device. The input is the notification message, and the output is an alert to the user's electronic device. Specifically, the device immediately displays the notification through its user interface.

[0496] Step 6:

[0497] The user checks the notification received on their device and takes appropriate action. The input is the notification message, and the output is the user's action. Specifically, the user adjusts their actions based on the suggestion, such as taking their pet for a walk.

[0498] Step 7:

[0499] The device shares information with medical professionals such as veterinarians via a server, allowing for feedback. Specifically, it displays advice from veterinarians on the device to help users take more appropriate action.

[0500] (Application Example 1)

[0501] 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."

[0502] Real-time data acquisition, rapid detection of abnormal behavior, and proposal of countermeasures are required for animal health management and behavioral analysis. However, many current systems suffer from the problem of time-consuming data analysis, preventing pet owners from taking immediate action. Furthermore, it is difficult to accurately estimate the animal's emotions and needs and to immediately determine effective responses. Therefore, there is a need to develop a system that monitors the health status and behavior of animals in real time and immediately proposes appropriate countermeasures.

[0503] 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.

[0504] In this invention, the server includes a device for receiving animal data from a wearable device equipped with a sensing device for acquiring animal behavior and health data; a device for analyzing the received data and evaluating the animal's health status and behavioral patterns; and a device for generating notifications to propose corrective measures for the animal based on the results of the evaluation. This makes it possible to monitor the animal's health status in real time, quickly propose necessary countermeasures, and reduce reaction time.

[0505] "Animal behavior" refers to the various actions and patterns that animals exhibit in their daily lives, and is an important indicator of their health and emotions.

[0506] "Health data" refers to a collection of information that shows biomedical indicators such as an animal's body temperature, heart rate, and respiratory rate, and forms the basis for evaluating the health status of an animal.

[0507] A "sensing device" is a device that includes sensors used to acquire physical activity and physiological data of animals, and is often incorporated into wearable devices.

[0508] A "wearable device" is a device attached to an animal, which includes a sensing device and is responsible for acquiring health and behavioral data of the animal.

[0509] "Abnormal behavior" refers to actions that deviate from normal behavioral patterns and may indicate stress or health problems in animals.

[0510] An "information terminal" is an electronic device used to provide users with notifications and suggested adjustment measures, and includes smartphones and smart glasses.

[0511] A "medical professional" is a healthcare worker with specialized knowledge, such as a veterinarian, who is involved in the assessment and treatment of an animal's health.

[0512] A "visualization application" is software that visually displays data and presents users with analysis results of abnormal behavior and countermeasures.

[0513] The system for realizing this invention consists of a wearable device attached to an animal, a server for processing data, and a terminal for displaying information. The wearable device includes a sensing device for acquiring animal behavior and health data, and transmits this data to the server using wireless communication. The server analyzes the received data and uses an algorithm to evaluate the animal's health status and behavioral patterns. This algorithm detects abnormal behavior and estimates the animal's emotions and desires.

[0514] As a concrete example, the server monitors the animal's heart rate and activity level in real time and compares them to normal levels. If an abnormal pattern is detected, it sends a notification to the user and suggests appropriate countermeasures. For example, if the animal's heart rate suddenly increases, the device will receive a notification stating, "The animal may be excited. Please provide a calm environment to help it settle down." In this case, a generative AI model is used to generate prompts that recommend actions that take the animal's condition into consideration. An example of a specific prompt might be, "Analyze the pet's behavioral data and suggest appropriate relaxation methods."

[0515] The terminal displays information received from the server in an easy-to-understand manner for the user and supports communication with experts as needed. This system also includes a function to share collected data with medical professionals, enabling veterinarians to gain a more accurate understanding of the situation and utilize it in treatment.

[0516] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0517] Step 1:

[0518] Wearable devices acquire animal behavior and health data using sensing devices. Inputs are real-time data such as animal activity levels and heart rate, which are transmitted wirelessly to a server. Outputs are the animal's biometric data used by the server for analysis.

[0519] Step 2:

[0520] The server analyzes the data received from the wearable device. The input is the transmitted biometric data. In this step, the data is processed using an algorithm to detect anomalies. The output is the result of anomaly detection in the animal's health status and behavioral patterns. The server uses a generative AI model to generate prompts that estimate the animal's emotions and desires from this analysis result.

[0521] Step 3:

[0522] The server generates a notification based on the results of anomaly detection. The input is the anomaly data obtained through analysis and the estimated state of the animal. Based on this information, the server creates a notification message suggesting specific corrective actions for the user and sends it to the terminal. The output is the notification message that the user receives in real time.

[0523] Step 4:

[0524] The terminal displays notifications received from the server to the user. The input is the notification message sent from the server. The terminal displays this notification on the screen, providing the user with information to take appropriate action regarding the animal. The output is the animal's current condition and recommended actions as perceived by the user.

[0525] Step 5:

[0526] The user modifies their actions towards the animal based on notifications and shares data with medical professionals as needed. The input is the content of the notification displayed on the device. The user takes appropriate action to improve the animal's condition and configures the system to send data from the server to the veterinarian as needed. The output is the specific behavioral changes made towards the animal and the situational data collected by the professional.

[0527] 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.

[0528] This invention is a system that considers not only the animal's condition but also the user's emotional state in order to improve the interaction between the animal and its owner. The system comprises a wearable device attached to the animal, a server for analyzing data, a terminal for displaying notifications, and an emotion engine for analyzing the user's emotions.

[0529] First, wearable devices are attached to the animal's body to collect data on activity levels, sleep, vocalizations, and movements in real time. This data is transmitted wirelessly to a server. The server uses this received data to analyze the animal's health status and behavioral patterns.

[0530] The server then passes the user's facial expressions and voice data entered from the terminal to the emotion engine. This engine uses advanced machine learning algorithms to identify the user's emotional state and provides the results to the server. For example, it can identify whether the user is stressed or relaxed.

[0531] The server determines corrective actions based on data that includes both the animal's condition and the user's emotional state. It not only generates general notifications about the animal's behavior and health, but also provides more personalized advice by suggesting coping strategies adapted to the user's emotions.

[0532] For example, if the server analyzes the user's emotions and determines that they are highly stressed, it will suggest an immediate task to perform with the animal and notify the user's device of how to do it. Conversely, if the server determines that the user is relaxed, it can also suggest training methods that take more time but are effective, or games aimed at relaxation.

[0533] The device displays generated notifications to the user, providing guidance for selecting specific actions to take regarding the animal. It also shares data with veterinarians as needed, receiving feedback from medical professionals. This feedback is displayed to the user through the device, allowing them to consider further actions.

[0534] This system provides comprehensive support based on the condition of both the animal and the user, enriching daily life with pets and enabling pet owners to better understand and respond to their animals' needs.

[0535] The following describes the processing flow.

[0536] Step 1:

[0537] The server receives data on animal activity levels, sleep, vocalizations, and behavior from wearable devices. This data is collected regularly in real time and made available directly on the server.

[0538] Step 2:

[0539] The server transfers the user's facial expressions and voice data collected via the terminal to the emotion engine. The emotion engine analyzes this data to identify the user's emotional state. The results include stress levels and relaxation levels.

[0540] Step 3:

[0541] The server comprehensively analyzes animal behavioral data and user emotional data. While evaluating the animals' health status and behavioral anomalies, it optimizes adjustment measures based on the user's emotional state.

[0542] Step 4:

[0543] The server generates notifications based on the analysis results. These notifications include not only standard advice about the animal's condition, but also specific instructions tailored to the user's emotions. This may include stress-relieving play or training methods.

[0544] Step 5:

[0545] The server sends the generated notification to the device. The notification is displayed to the user on the device, and the user can check its contents.

[0546] Step 6:

[0547] The user reviews the notification received on their device and decides on specific adjustments to be taken for the animal. Based on the notification, they are shown what actions to take immediately and what to consider in the future.

[0548] Step 7:

[0549] The server offers the option of sharing animal health data with veterinarians, which is expected to provide expert feedback on the animals' condition.

[0550] Step 8:

[0551] The device receives feedback from veterinarians and presents it to the user. Based on this feedback, the user can then consider further actions.

[0552] (Example 2)

[0553] 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."

[0554] There is a need to deepen the relationship between animals and their owners, and to provide comprehensive support that simultaneously considers the animal's health status, behavioral patterns, and the user's emotional state. However, current technology is limited to analyzing animal data and individual health indicators, and has limitations in proposing interactions and adjustment measures that take the user's emotional state into account. Therefore, a new system is needed to deepen mutual understanding between animals and their owners and improve the quality of their daily lives.

[0555] 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.

[0556] In this invention, the server includes means for receiving animal activity data, means for analyzing the received data to evaluate health status and behavioral tendencies, and means for analyzing facial and voice data to identify the user's emotional state. This enables improved mutual understanding and relationships by proposing adjustment measures adapted to both the animal and the user.

[0557] "Animals" refers to living organisms other than humans, and in this invention, it refers to organisms kept as pets.

[0558] "Activity data" refers to information about an animal's exercise level, sleep, vocalizations, and movements, and is used to assess the animal's health and behavioral tendencies.

[0559] A "device" refers to an instrument attached to an animal's body that collects activity data and transmits it wirelessly.

[0560] A "server" refers to an information processing device that receives data and performs processing such as analysis, evaluation, and notification generation.

[0561] "Analysis means" refers to a process or tool for evaluating and identifying the health status and behavioral patterns of animals, or the emotional state of users, using acquired data.

[0562] "Means of receiving" refers to the process or tools used to import data from external sources into a server or other device.

[0563] "User" refers to the owner of an animal that uses the system of the present invention, and is also the subject of analysis of their emotional state.

[0564] "Notifications" refer to information or instructions generated based on analysis results and sent to the user.

[0565] A "healthcare professional" refers to a person who possesses expertise in animal medicine and provides feedback on animal health.

[0566] This invention provides a system that offers comprehensive support by evaluating the health status and behavioral patterns of animals while also considering the emotional state of the user. The system mainly consists of an activity data collection device attached to the animal, a server that analyzes the data, a terminal that notifies the user, and an emotion analysis engine that analyzes the user's emotions.

[0567] The server receives real-time data wirelessly from devices that collect animal activity data. It then uses libraries such as Python's Pandas and NumPy to analyze this data and evaluate the animals' health and behavioral tendencies. This allows pet owners to detect abnormalities early.

[0568] Furthermore, the device collects the user's facial expressions and voice data and sends it to an emotion analysis engine. The emotion analysis engine uses a generative AI model to identify the user's emotional state. For example, if the user is smiling, it determines that they are relaxed.

[0569] The server integrates these analysis results and devises adjustment measures adapted to both the animal and the user. The resulting notifications are then delivered to the user via the terminal. For example, if the animal is unstable and the user is stressed, the server can suggest a short refreshing activity.

[0570] As a concrete example, here is an example of a prompt message:

[0571] "What activities would you suggest to a user who is saddened because their dog has been lethargic lately?"

[0572] In this way, the system provides optimal support for both animals and users, improving the quality of life for both.

[0573] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0574] Step 1:

[0575] The server receives data wirelessly from activity data collection devices attached to animals. It acquires data on activity levels, sleep patterns, vocalizations, and movements as input. The server uses analysis software to organize this data and generate foundational data for understanding the animals' health status and behavioral tendencies in real time. This output includes indicators of health status and abnormal behavioral patterns.

[0576] Step 2:

[0577] The device collects the user's facial expressions and voice data. It uses the smartphone's camera and microphone as input to record changes in the user's facial expressions and voice tone. This data is sent to a server and fed into an emotion analysis engine. The server uses a generative AI model to identify the user's emotional state. The output provides an emotional state, such as whether the user is stressed or relaxed.

[0578] Step 3:

[0579] The server integrates the analyzed animal's health status, behavioral tendencies, and the user's emotional state. The input is the analysis results from Step 1 and Step 2. Based on these results, the server devises adjustment measures and considers using a generative AI model, including the use of prompts. The output is specific suggestions and notifications for the animal and the user.

[0580] Step 4:

[0581] The terminal displays suggestions and notifications provided by the server to the user. It receives notification data from the server as input. The terminal displays this data on the screen as user information, suggesting activities and measures to be taken with the animals. The output consists of specific action guidelines and suggestions provided to the user.

[0582] Step 5:

[0583] Users adjust their interactions with animals and provide feedback based on the measures and activities suggested by the device. Input includes reporting user behavior and impressions to the system via the device. This feedback is accumulated by the system and used for future analysis and improvement of the accuracy of suggestions. Output consists of user practice results and opinions necessary for system improvement.

[0584] (Application Example 2)

[0585] 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."

[0586] Lack of communication and misunderstandings between animals and their owners can lead to stress and frustration, negatively impacting the animal's health and behavior. Furthermore, if owners cannot accurately understand their animal's condition, appropriate responses and care become difficult. Additionally, insufficient consideration of the user's emotional state results in inadequately optimized interactions with animals.

[0587] 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.

[0588] In this invention, the server includes means for receiving information from a device for acquiring biological information of animals, means for analyzing the received information and evaluating the animal's health status and behavioral characteristics, and means for acquiring and analyzing the user's emotional state. This enables comprehensive judgment based on the interaction between the animal and the user, and improves personalized care and communication.

[0589] "Animal biometric information" refers to various data related to the health status and activity levels of animals.

[0590] An "information terminal" refers to an electronic device that can receive and display notifications.

[0591] "User emotional state" refers to data used to analyze the user's psychological and emotional state.

[0592] "Analysis" is the process of examining received data in detail to extract meaningful information.

[0593] A "notification" is an informational message generated by a system that serves to draw the user's attention or suggest an action.

[0594] A "specialist" refers to a medical professional who possesses expertise related to animal health and behavior.

[0595] The system for implementing this invention consists of multiple components. First, a wearable device attached to an animal collects its biometric information in real time and transmits it to a server via wireless communication. The server operates on a cloud platform and performs detailed analysis of the animal's biometric information. The analysis includes the animal's activity level, sleep patterns, vocalizations, and movement information. This makes it possible to evaluate the animal's health status and behavioral characteristics.

[0596] Furthermore, the server receives facial and voice data transmitted from the user's information terminal and uses an emotion analysis engine to identify the user's emotional state. This can utilize advanced machine learning algorithms. The analysis results are integrated with the assessment results regarding the animal's condition, and based on the processing results on the server, a notification is generated to suggest corrective actions.

[0597] Notifications are sent to information terminals. These terminals include smartphones and tablets and function as user interfaces. The terminals provide users with specific suggestions for actions and care tailored to the animal's condition. For example, if the user is stressed, suggestions for short, playful activities with the animal will be provided. Such suggestions are displayed to the user using prompt messages generated by the system.

[0598] As a concrete example, the following prompt statements are possible:

[0599] "Your stress level is high today. How about spending about 20 minutes playing with your dog in the park?"

[0600] "A short walk is also recommended. Let's take it easy today."

[0601] This invention provides support for both animals and users to live better lives.

[0602] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0603] Step 1:

[0604] Wearable devices acquire biometric information from animals. Inputs include animal activity levels, sleep patterns, vocalizations, and movement data. This data is transmitted wirelessly to a server. The output is the data stream received by the server.

[0605] Step 2:

[0606] The server analyzes the received data. The input is the data stream obtained in step 1. Machine learning algorithms are used to process the data in order to evaluate the health status and behavioral characteristics of the animals. The output is the health assessment result of the animals obtained through the analysis.

[0607] Step 3:

[0608] The server receives user facial expressions and voice data from the information terminal. The input is emotion data transmitted from the terminal. The emotion analysis engine is used to identify the user's emotional state. The output is the result of the user's emotion analysis.

[0609] Step 4:

[0610] The server integrates the animal evaluation results and the user's sentiment analysis results. The input is the results from steps 2 and 3. Based on this integrated data, data processing is performed to determine adjustment measures for the animals and users. The output is a plan of the adjustment measures to be proposed.

[0611] Step 5:

[0612] The server generates a notification based on the adjustment measures. The input is the adjustment plan from step 4. A generation AI model is used to create a prompt message, which is presented clearly to the user. The output is a notification sent to the information terminal.

[0613] Step 6:

[0614] The terminal receives notifications sent from the server and displays them to the user. The input is the notification from step 5. The user selects specific actions or care for the animal through suggested prompts. The output is the user's action selection.

[0615] 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.

[0616] 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.

[0617] 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.

[0618] [Fourth Embodiment]

[0619] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0620] 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.

[0621] 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).

[0622] 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.

[0623] 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.

[0624] 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).

[0625] 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.

[0626] 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.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] 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.

[0631] 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".

[0632] This invention is a system for supporting animal health management and behavioral analysis, and consists of a wearable device equipped with sensors, a server for processing data, and a terminal for providing information. Specific embodiments are described below.

[0633] First, the wearable devices attached to the animals contain various sensors to acquire data on activity levels, sleep, and diet. These devices transmit the data acquired in real time from the sensors to a server via wireless communication. The server then uses this data to analyze the animals' health and behavior.

[0634] In the analysis, the server first compares each data point to a baseline value to assess the user's health status and detects any data that deviates from normal. If activity levels are significantly lower than normal, the server calculates the risk associated with that health status and determines it to be abnormal.

[0635] Regarding behavioral data, the server uses advanced algorithms to analyze the animals' behavioral patterns. For example, based on the frequency and pattern of barking, it can identify if an animal is experiencing stress. This behavioral analysis is also used to estimate the emotions and needs of pets.

[0636] Based on the analysis results, the server generates a notification tailored to the animal's condition and sends it to the device. This notification includes monitoring results of the animal's health status and specific instructions for behavioral improvement. The user receives the notification on their device and can take appropriate action for the animal.

[0637] For example, if the device receives a notification that "your pet's activity level has decreased," the user might consider increasing the amount of time spent walking their pet or providing indoor playtime. If a notification about barking is received, actionable advice such as "playing certain music may calm your pet" will be provided.

[0638] Furthermore, the server has the functionality to share animal health data with medical professionals such as veterinarians. This allows veterinarians to accurately understand the situation and provide appropriate treatment and feedback. This feedback is notified to the user via the terminal, helping them to take necessary actions.

[0639] As described above, this system comprehensively supports animal health management and behavioral improvement, while also enhancing convenience for pet owners.

[0640] The following describes the processing flow.

[0641] Step 1:

[0642] The server receives data on animal activity levels, sleep, and diet from wearable devices. This includes raw data acquired by various sensors.

[0643] Step 2:

[0644] The server preprocesses the received data. This preprocessing includes data cleansing, such as imputing missing values ​​and removing noise. This process prepares the dataset for analysis.

[0645] Step 3:

[0646] The server assesses the health status of animals based on pre-processed data. Specifically, it compares the data to historical baseline data to determine whether it is within the normal range or abnormal. This assessment identifies risks if abnormal values ​​are present.

[0647] Step 4:

[0648] The server applies behavioral analysis algorithms to analyze the animals' behavioral patterns. Based on the data, it estimates the presence or absence of problematic behaviors and the animals' emotional states. For example, it identifies the frequency and patterns of abnormal barking and investigates their causes.

[0649] Step 5:

[0650] The server uses a natural language generation engine to create notifications based on the analysis of the animals' health status and behavior. These notifications include specific actions to take and advice for pet owners.

[0651] Step 6:

[0652] The server sends the generated notification to the device. The notification is immediately conveyed to the owner via the application and becomes available for viewing on the dashboard.

[0653] Step 7:

[0654] The user checks notifications received on their device and decides what action is needed for the animal. Based on the notification, they select actions to improve the animal's behavior and health.

[0655] Step 8:

[0656] The server shares health data with medical professionals such as veterinarians as needed. This sharing takes place via the cloud and provides the professionals with the basic information they need to conduct detailed analysis.

[0657] Step 9:

[0658] The device receives feedback from veterinarians and presents it to the user. Based on this feedback, the user considers further medical interventions.

[0659] (Example 1)

[0660] 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".

[0661] Modern households are required to accurately understand and properly manage their pets' health and behavioral patterns. However, achieving this requires a system that accurately analyzes the diverse data obtained from animals and provides owners with the necessary information. Conventional systems have the challenge of not being able to accurately estimate animals' emotions and desires and propose appropriate adjustment measures.

[0662] 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.

[0663] In this invention, the server includes means for receiving information from a wearable device equipped with a detection device for acquiring animal behavior and health information, means for analyzing the received information and evaluating the animal's health status and behavioral patterns, and means for generating notifications to propose adjustment measures for the animal based on the evaluation results. This makes it possible to understand the animal's health status and behavioral patterns in detail and to achieve effective management and improvement.

[0664] "Animals" refers to living creatures such as mammals, birds, and reptiles that are kept as pets or livestock.

[0665] "Movement" is a concept used to observe and analyze the bodily movements and actions that animals perform on a daily basis.

[0666] "Health information" refers to data that indicates an animal's physical condition, specifically including body temperature, heart rate, and activity level.

[0667] A "detection device" refers to equipment consisting of sensors attached to animals, used to acquire information about the animals' movements and health.

[0668] A "wearable device" is a device that is directly attached to an animal, equipped with sensors and communication functions, and used to collect and transmit data in real time.

[0669] "Information" is a broad concept referring to data acquired by detection devices and the results of their analysis.

[0670] "Analysis" refers to data processing performed to evaluate health status and behavioral patterns based on acquired data.

[0671] "Health status" refers to indicators that show the physical and mental well-being and presence or absence of abnormalities in an animal.

[0672] "Behavioral patterns" refer to certain patterns or tendencies in an animal's behavior.

[0673] "Adjustment measures" refer to specific actions and suggestions taken to improve the health and behavior of animals based on the evaluation results.

[0674] "Notifications" refer to messages and alerts used to inform users about analysis results and corrective actions.

[0675] "Electronic devices" refer to digital devices used by users to check the condition of animals and take appropriate action as needed.

[0676] "Medical professional" refers to a veterinarian or other healthcare worker who possesses knowledge and skills related to animal health.

[0677] "Generation" refers to the process of creating new information or notifications, and is particularly used when employing AI models.

[0678] This invention is a system for supporting animal health management and behavioral analysis. The system mainly consists of wearable devices, a server, and terminals. The following describes each component and how they work together in detail.

[0679] First, the wearable device is attached to the animal and is equipped with an accelerometer, heart rate sensor, environmental sensor, etc. This device acquires the animal's movements and health information in real time. The acquired data is transmitted to a server using wireless communication technologies such as Bluetooth or Wi-Fi.

[0680] The server uses an AI model to analyze the received data. During the analysis, the data is compared to baseline values ​​to evaluate the animal's health status and behavior. If a health abnormality is detected, the server generates a notification to suggest specific adjustment measures. For example, if activity levels decrease, it might generate a notification such as, "We recommend increasing your pet's exercise."

[0681] The generated notifications are sent from the server to the electronic terminal. The terminal is equipped with a user interface, allowing the user to check the notifications and take necessary actions. One example of a specific action is to alleviate the animal's stress by playing certain music. The terminal also has a function to share data with medical professionals such as veterinarians, and can receive feedback from professionals via the server.

[0682] In implementing this system, it is possible to precisely analyze animal behavior patterns using a generative AI model and achieve highly accurate estimations. Furthermore, a possible use case for prompts is, "Based on my pet's recent behavioral data, please suggest the optimal amount of exercise."

[0683] In summary, this invention comprehensively supports animal health management and behavioral monitoring, providing a useful means for pet owners to properly manage their pets.

[0684] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0685] Step 1:

[0686] The wearable device is attached to the animal and uses sensors to acquire real-time information about the animal's movements and health. The input data includes acceleration, heart rate, and information about the surrounding environment, and this information is recorded as digital signals. Specifically, while the animal is walking, the acceleration sensor measures the body's movement, and this is output digitally as an activity level.

[0687] Step 2:

[0688] Data obtained from wearable devices is transmitted to a server using wireless communication technology. The input data is sent in a compressed format, and the server receives and decompresses it. The data is processed in JSON format and formatted for parsing. Specifically, after receiving the data, the server stores it in a database.

[0689] Step 3:

[0690] The server uses an AI model to analyze the received data. The input data consists of behavioral and health information, which is evaluated as health status and behavioral patterns. The analysis includes comparison with baseline values ​​and pattern recognition. For example, if the activity level falls below the baseline value, the server detects an anomaly and assesses the health risk.

[0691] Step 4:

[0692] The server generates notifications based on the analysis results. The input is data on the evaluated health status and behavior patterns, and the output is a notification that proposes specific adjustment measures. Specifically, it creates a message such as, "Your pet's activity level has decreased. Please increase its exercise."

[0693] Step 5:

[0694] The server sends the generated notification to the electronic device. The input is the notification message, and the output is an alert to the user's electronic device. Specifically, the device immediately displays the notification through its user interface.

[0695] Step 6:

[0696] The user checks the notification received on their device and takes appropriate action. The input is the notification message, and the output is the user's action. Specifically, the user adjusts their actions based on the suggestion, such as taking their pet for a walk.

[0697] Step 7:

[0698] The device shares information with medical professionals such as veterinarians via a server, allowing for feedback. Specifically, it displays advice from veterinarians on the device to help users take more appropriate action.

[0699] (Application Example 1)

[0700] 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".

[0701] Real-time data acquisition, rapid detection of abnormal behavior, and proposal of countermeasures are required for animal health management and behavioral analysis. However, many current systems suffer from the problem of time-consuming data analysis, preventing pet owners from taking immediate action. Furthermore, it is difficult to accurately estimate the animal's emotions and needs and to immediately determine effective responses. Therefore, there is a need to develop a system that monitors the health status and behavior of animals in real time and immediately proposes appropriate countermeasures.

[0702] 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.

[0703] In this invention, the server includes a device for receiving animal data from a wearable device equipped with a sensing device for acquiring animal behavior and health data; a device for analyzing the received data and evaluating the animal's health status and behavioral patterns; and a device for generating notifications to propose corrective measures for the animal based on the results of the evaluation. This makes it possible to monitor the animal's health status in real time, quickly propose necessary countermeasures, and reduce reaction time.

[0704] "Animal behavior" refers to the various actions and patterns that animals exhibit in their daily lives, and is an important indicator of their health and emotions.

[0705] "Health data" refers to a collection of information that shows biomedical indicators such as an animal's body temperature, heart rate, and respiratory rate, and forms the basis for evaluating the health status of an animal.

[0706] A "sensing device" is a device that includes sensors used to acquire physical activity and physiological data of animals, and is often incorporated into wearable devices.

[0707] A "wearable device" is a device attached to an animal, which includes a sensing device and is responsible for acquiring health and behavioral data of the animal.

[0708] "Abnormal behavior" refers to actions that deviate from normal behavioral patterns and may indicate stress or health problems in animals.

[0709] An "information terminal" is an electronic device used to provide users with notifications and suggested adjustment measures, and includes smartphones and smart glasses.

[0710] A "medical professional" is a healthcare worker with specialized knowledge, such as a veterinarian, who is involved in the assessment and treatment of an animal's health.

[0711] A "visualization application" is software that visually displays data and presents users with analysis results of abnormal behavior and countermeasures.

[0712] The system for realizing this invention consists of a wearable device attached to an animal, a server for processing data, and a terminal for displaying information. The wearable device includes a sensing device for acquiring animal behavior and health data, and transmits this data to the server using wireless communication. The server analyzes the received data and uses an algorithm to evaluate the animal's health status and behavioral patterns. This algorithm detects abnormal behavior and estimates the animal's emotions and desires.

[0713] As a concrete example, the server monitors the animal's heart rate and activity level in real time and compares them to normal levels. If an abnormal pattern is detected, it sends a notification to the user and suggests appropriate countermeasures. For example, if the animal's heart rate suddenly increases, the device will receive a notification stating, "The animal may be excited. Please provide a calm environment to help it settle down." In this case, a generative AI model is used to generate prompts that recommend actions that take the animal's condition into consideration. An example of a specific prompt might be, "Analyze the pet's behavioral data and suggest appropriate relaxation methods."

[0714] The terminal displays information received from the server in an easy-to-understand manner for the user and supports communication with experts as needed. This system also includes a function to share collected data with medical professionals, enabling veterinarians to gain a more accurate understanding of the situation and utilize it in treatment.

[0715] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0716] Step 1:

[0717] Wearable devices acquire animal behavior and health data using sensing devices. Inputs are real-time data such as animal activity levels and heart rate, which are transmitted wirelessly to a server. Outputs are the animal's biometric data used by the server for analysis.

[0718] Step 2:

[0719] The server analyzes the data received from the wearable device. The input is the transmitted biometric data. In this step, the data is processed using an algorithm to detect anomalies. The output is the result of anomaly detection in the animal's health status and behavioral patterns. The server uses a generative AI model to generate prompts that estimate the animal's emotions and desires from this analysis result.

[0720] Step 3:

[0721] The server generates a notification based on the results of anomaly detection. The input is the anomaly data obtained through analysis and the estimated state of the animal. Based on this information, the server creates a notification message suggesting specific corrective actions for the user and sends it to the terminal. The output is the notification message that the user receives in real time.

[0722] Step 4:

[0723] The terminal displays notifications received from the server to the user. The input is the notification message sent from the server. The terminal displays this notification on the screen, providing the user with information to take appropriate action regarding the animal. The output is the animal's current condition and recommended actions as perceived by the user.

[0724] Step 5:

[0725] The user modifies their actions towards the animal based on notifications and shares data with medical professionals as needed. The input is the content of the notification displayed on the device. The user takes appropriate action to improve the animal's condition and configures the system to send data from the server to the veterinarian as needed. The output is the specific behavioral changes made towards the animal and the situational data collected by the professional.

[0726] 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.

[0727] This invention is a system that considers not only the animal's condition but also the user's emotional state in order to improve the interaction between the animal and its owner. The system comprises a wearable device attached to the animal, a server for analyzing data, a terminal for displaying notifications, and an emotion engine for analyzing the user's emotions.

[0728] First, wearable devices are attached to the animal's body to collect data on activity levels, sleep, vocalizations, and movements in real time. This data is transmitted wirelessly to a server. The server uses this received data to analyze the animal's health status and behavioral patterns.

[0729] The server then passes the user's facial expressions and voice data entered from the terminal to the emotion engine. This engine uses advanced machine learning algorithms to identify the user's emotional state and provides the results to the server. For example, it can identify whether the user is stressed or relaxed.

[0730] The server determines corrective actions based on data that includes both the animal's condition and the user's emotional state. It not only generates general notifications about the animal's behavior and health, but also provides more personalized advice by suggesting coping strategies adapted to the user's emotions.

[0731] For example, if the server analyzes the user's emotions and determines that they are highly stressed, it will suggest an immediate task to perform with the animal and notify the user's device of how to do it. Conversely, if the server determines that the user is relaxed, it can also suggest training methods that take more time but are effective, or games aimed at relaxation.

[0732] The device displays generated notifications to the user, providing guidance for selecting specific actions to take regarding the animal. It also shares data with veterinarians as needed, receiving feedback from medical professionals. This feedback is displayed to the user through the device, allowing them to consider further actions.

[0733] This system provides comprehensive support based on the condition of both the animal and the user, enriching daily life with pets and enabling pet owners to better understand and respond to their animals' needs.

[0734] The following describes the processing flow.

[0735] Step 1:

[0736] The server receives data on animal activity levels, sleep, vocalizations, and behavior from wearable devices. This data is collected regularly in real time and made available directly on the server.

[0737] Step 2:

[0738] The server transfers the user's facial expressions and voice data collected via the terminal to the emotion engine. The emotion engine analyzes this data to identify the user's emotional state. The results include stress levels and relaxation levels.

[0739] Step 3:

[0740] The server comprehensively analyzes animal behavioral data and user emotional data. While evaluating the animals' health status and behavioral anomalies, it optimizes adjustment measures based on the user's emotional state.

[0741] Step 4:

[0742] The server generates notifications based on the analysis results. These notifications include not only standard advice about the animal's condition, but also specific instructions tailored to the user's emotions. This may include stress-relieving play or training methods.

[0743] Step 5:

[0744] The server sends the generated notification to the device. The notification is displayed to the user on the device, and the user can check its contents.

[0745] Step 6:

[0746] The user reviews the notification received on their device and decides on specific adjustments to be taken for the animal. Based on the notification, they are shown what actions to take immediately and what to consider in the future.

[0747] Step 7:

[0748] The server offers the option of sharing animal health data with veterinarians, which is expected to provide expert feedback on the animals' condition.

[0749] Step 8:

[0750] The device receives feedback from veterinarians and presents it to the user. Based on this feedback, the user can then consider further actions.

[0751] (Example 2)

[0752] 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".

[0753] There is a need to deepen the relationship between animals and their owners, and to provide comprehensive support that simultaneously considers the animal's health status, behavioral patterns, and the user's emotional state. However, current technology is limited to analyzing animal data and individual health indicators, and has limitations in proposing interactions and adjustment measures that take the user's emotional state into account. Therefore, a new system is needed to deepen mutual understanding between animals and their owners and improve the quality of their daily lives.

[0754] 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.

[0755] In this invention, the server includes means for receiving animal activity data, means for analyzing the received data to evaluate health status and behavioral tendencies, and means for analyzing facial and voice data to identify the user's emotional state. This enables improved mutual understanding and relationships by proposing adjustment measures adapted to both the animal and the user.

[0756] "Animals" refers to living organisms other than humans, and in this invention, it refers to organisms kept as pets.

[0757] "Activity data" refers to information about an animal's exercise level, sleep, vocalizations, and movements, and is used to assess the animal's health and behavioral tendencies.

[0758] A "device" refers to an instrument attached to an animal's body that collects activity data and transmits it wirelessly.

[0759] A "server" refers to an information processing device that receives data and performs processing such as analysis, evaluation, and notification generation.

[0760] "Analysis means" refers to a process or tool for evaluating and identifying the health status and behavioral patterns of animals, or the emotional state of users, using acquired data.

[0761] "Means of receiving" refers to the process or tools used to import data from external sources into a server or other device.

[0762] "User" refers to the owner of an animal that uses the system of the present invention, and is also the subject of analysis of their emotional state.

[0763] "Notifications" refer to information or instructions generated based on analysis results and sent to the user.

[0764] A "healthcare professional" refers to a person who possesses expertise in animal medicine and provides feedback on animal health.

[0765] This invention provides a system that offers comprehensive support by evaluating the health status and behavioral patterns of animals while also considering the emotional state of the user. The system mainly consists of an activity data collection device attached to the animal, a server that analyzes the data, a terminal that notifies the user, and an emotion analysis engine that analyzes the user's emotions.

[0766] The server receives real-time data wirelessly from devices that collect animal activity data. It then uses libraries such as Python's Pandas and NumPy to analyze this data and evaluate the animals' health and behavioral tendencies. This allows pet owners to detect abnormalities early.

[0767] Furthermore, the device collects the user's facial expressions and voice data and sends it to an emotion analysis engine. The emotion analysis engine uses a generative AI model to identify the user's emotional state. For example, if the user is smiling, it determines that they are relaxed.

[0768] The server integrates these analysis results and devises adjustment measures adapted to both the animal and the user. The resulting notifications are then delivered to the user via the terminal. For example, if the animal is unstable and the user is stressed, the server can suggest a short refreshing activity.

[0769] As a concrete example, here is an example of a prompt message:

[0770] "What activities would you suggest to a user who is saddened because their dog has been lethargic lately?"

[0771] In this way, the system provides optimal support for both animals and users, improving the quality of life for both.

[0772] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0773] Step 1:

[0774] The server receives data wirelessly from activity data collection devices attached to animals. It acquires data on activity levels, sleep patterns, vocalizations, and movements as input. The server uses analysis software to organize this data and generate foundational data for understanding the animals' health status and behavioral tendencies in real time. This output includes indicators of health status and abnormal behavioral patterns.

[0775] Step 2:

[0776] The device collects the user's facial expressions and voice data. It uses the smartphone's camera and microphone as input to record changes in the user's facial expressions and voice tone. This data is sent to a server and fed into an emotion analysis engine. The server uses a generative AI model to identify the user's emotional state. The output provides an emotional state, such as whether the user is stressed or relaxed.

[0777] Step 3:

[0778] The server integrates the analyzed animal's health status, behavioral tendencies, and the user's emotional state. The input is the analysis results from Step 1 and Step 2. Based on these results, the server devises adjustment measures and considers using a generative AI model, including the use of prompts. The output is specific suggestions and notifications for the animal and the user.

[0779] Step 4:

[0780] The terminal displays suggestions and notifications provided by the server to the user. It receives notification data from the server as input. The terminal displays this data on the screen as user information, suggesting activities and measures to be taken with the animals. The output consists of specific action guidelines and suggestions provided to the user.

[0781] Step 5:

[0782] Users adjust their interactions with animals and provide feedback based on the measures and activities suggested by the device. Input includes reporting user behavior and impressions to the system via the device. This feedback is accumulated by the system and used for future analysis and improvement of the accuracy of suggestions. Output consists of user practice results and opinions necessary for system improvement.

[0783] (Application Example 2)

[0784] 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".

[0785] Lack of communication and misunderstandings between animals and their owners can lead to stress and frustration, negatively impacting the animal's health and behavior. Furthermore, if owners cannot accurately understand their animal's condition, appropriate responses and care become difficult. Additionally, insufficient consideration of the user's emotional state results in inadequately optimized interactions with animals.

[0786] 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.

[0787] In this invention, the server includes means for receiving information from a device for acquiring biological information of animals, means for analyzing the received information and evaluating the animal's health status and behavioral characteristics, and means for acquiring and analyzing the user's emotional state. This enables comprehensive judgment based on the interaction between the animal and the user, and improves personalized care and communication.

[0788] "Animal biometric information" refers to various data related to the health status and activity levels of animals.

[0789] An "information terminal" refers to an electronic device that can receive and display notifications.

[0790] "User emotional state" refers to data used to analyze the user's psychological and emotional state.

[0791] "Analysis" is the process of examining received data in detail to extract meaningful information.

[0792] A "notification" is an informational message generated by a system that serves to draw the user's attention or suggest an action.

[0793] A "specialist" refers to a medical professional who possesses expertise related to animal health and behavior.

[0794] The system for implementing this invention consists of multiple components. First, a wearable device attached to an animal collects its biometric information in real time and transmits it to a server via wireless communication. The server operates on a cloud platform and performs detailed analysis of the animal's biometric information. The analysis includes the animal's activity level, sleep patterns, vocalizations, and movement information. This makes it possible to evaluate the animal's health status and behavioral characteristics.

[0795] Furthermore, the server receives facial and voice data transmitted from the user's information terminal and uses an emotion analysis engine to identify the user's emotional state. This can utilize advanced machine learning algorithms. The analysis results are integrated with the assessment results regarding the animal's condition, and based on the processing results on the server, a notification is generated to suggest corrective actions.

[0796] Notifications are sent to information terminals. These terminals include smartphones and tablets and function as user interfaces. The terminals provide users with specific suggestions for actions and care tailored to the animal's condition. For example, if the user is stressed, suggestions for short, playful activities with the animal will be provided. Such suggestions are displayed to the user using prompt messages generated by the system.

[0797] As a concrete example, the following prompt statements are possible:

[0798] "Your stress level is high today. How about spending about 20 minutes playing with your dog in the park?"

[0799] "A short walk is also recommended. Let's take it easy today."

[0800] This invention provides support for both animals and users to live better lives.

[0801] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0802] Step 1:

[0803] Wearable devices acquire biometric information from animals. Inputs include animal activity levels, sleep patterns, vocalizations, and movement data. This data is transmitted wirelessly to a server. The output is the data stream received by the server.

[0804] Step 2:

[0805] The server analyzes the received data. The input is the data stream obtained in step 1. Machine learning algorithms are used to process the data in order to evaluate the health status and behavioral characteristics of the animals. The output is the health assessment result of the animals obtained through the analysis.

[0806] Step 3:

[0807] The server receives user facial expressions and voice data from the information terminal. The input is emotion data transmitted from the terminal. The emotion analysis engine is used to identify the user's emotional state. The output is the result of the user's emotion analysis.

[0808] Step 4:

[0809] The server integrates the animal evaluation results and the user's sentiment analysis results. The input is the results from steps 2 and 3. Based on this integrated data, data processing is performed to determine adjustment measures for the animals and users. The output is a plan of the adjustment measures to be proposed.

[0810] Step 5:

[0811] The server generates a notification based on the adjustment measures. The input is the adjustment plan from step 4. A generation AI model is used to create a prompt message, which is presented clearly to the user. The output is a notification sent to the information terminal.

[0812] Step 6:

[0813] The terminal receives notifications sent from the server and displays them to the user. The input is the notification from step 5. The user selects specific actions or care for the animal through suggested prompts. The output is the user's action selection.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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."

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] The following is further disclosed regarding the embodiments described above.

[0836] (Claim 1)

[0837] A means for receiving data from an animal, from a wearable device equipped with sensors for acquiring animal behavior and health data,

[0838] A means for analyzing the received data and evaluating the health status and behavioral patterns of the animals,

[0839] A means for generating a notification to propose adjustment measures for animals based on the results of the aforementioned evaluation,

[0840] Means for transmitting the aforementioned notification to an electronic terminal,

[0841] A means of sharing the aforementioned animal's health data with medical professionals,

[0842] A system that includes this.

[0843] (Claim 2)

[0844] The system according to claim 1, which analyzes vocalization and behavioral data in order to estimate the emotions and desires of the aforementioned animal.

[0845] (Claim 3)

[0846] The system according to claim 1, further comprising means for receiving feedback from veterinary medical professionals based on the results of the aforementioned evaluation.

[0847] "Example 1"

[0848] (Claim 1)

[0849] A means for receiving information from an animal, from a wearable device equipped with a detection device for acquiring animal behavior and health information,

[0850] A means for analyzing the received information and evaluating the health status and behavioral patterns of the animals,

[0851] A means for generating a notification to propose adjustment measures for animals based on the results of the aforementioned evaluation,

[0852] Means for transmitting the aforementioned notification to an electronic device,

[0853] A means of sharing the health information of the aforementioned animals with medical professionals,

[0854] A means of analyzing behavioral patterns using a generative artificial intelligence model in order to learn the behavioral patterns of animals,

[0855] A means for estimating the emotions and desires of an animal based on the analyzed behavioral patterns,

[0856] A means for detecting abnormalities in the aforementioned health information and presenting specific action plans to the user,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, which analyzes voice and behavioral data in order to estimate the emotions and desires of the aforementioned animal.

[0860] (Claim 3)

[0861] The system according to claim 1, further comprising means for receiving a response from a veterinary medical professional based on the results of the aforementioned evaluation.

[0862] "Application Example 1"

[0863] (Claim 1)

[0864] A device that receives data from an animal, from a wearable device equipped with a sensing device for acquiring animal behavior and health data,

[0865] A device that analyzes the received data and evaluates the health status and behavioral patterns of animals,

[0866] A device for generating a notification to propose adjustment measures for animals based on the results of the aforementioned evaluation,

[0867] A device that transmits the aforementioned notification to an information terminal,

[0868] A device for sharing the health data of the aforementioned animals with medical professionals,

[0869] A device including a visualization application for analyzing the abnormal behavior of the aforementioned animals in real time and proposing countermeasures,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, which analyzes voice and behavioral data in order to estimate the emotions and desires of the aforementioned animal.

[0873] (Claim 3)

[0874] The system according to claim 1, further comprising a device for receiving feedback from veterinary medical professionals based on the results of the aforementioned evaluation.

[0875] "Example 2 of combining an emotion engine"

[0876] (Claim 1)

[0877] A means for receiving animal data from a device for acquiring animal activity data,

[0878] A means for analyzing the received data and evaluating the health status and behavioral tendencies of the animals,

[0879] An analysis means for analyzing facial and voice data to identify the user's emotional state,

[0880] Means for generating notifications to propose adjustment measures for the animal and the user based on the results of the evaluation and the identified emotional state,

[0881] Means for transmitting the aforementioned notification to an information processing device,

[0882] A means of sharing the health data of the aforementioned animals with medical professionals,

[0883] A system that includes this.

[0884] (Claim 2)

[0885] The system according to claim 1, which uses behavioral and audio data to analyze the emotional state of the animal and the user.

[0886] (Claim 3)

[0887] The system according to claim 1, further comprising means for receiving feedback from healthcare professionals based on the results of the evaluation and the user's emotional state.

[0888] "Application example 2 when combining with an emotional engine"

[0889] (Claim 1)

[0890] A means for receiving information about an animal from a device for acquiring the animal's biological information,

[0891] A means for analyzing the received information and evaluating the health status and behavioral characteristics of the animal,

[0892] A means of acquiring and analyzing the user's emotional state,

[0893] A means for generating a notification to propose adjustment measures for animals and users based on the results of the aforementioned evaluation and analysis,

[0894] Means for transmitting the aforementioned notification to an information terminal,

[0895] A means of sharing the health information of the aforementioned animals with medical professionals,

[0896] A system that includes this.

[0897] (Claim 2)

[0898] The system according to claim 1, which analyzes animal vocalizations and movement information, as well as the user's facial expressions and voice information, in order to estimate the emotional state of the animal and the user.

[0899] (Claim 3)

[0900] The system according to claim 1, further comprising means for receiving feedback from experts based on the results of the evaluation and analysis. [Explanation of symbols]

[0901] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving data from an animal, from a wearable device equipped with sensors for acquiring animal behavior and health data, A means for analyzing the received data and evaluating the health status and behavioral patterns of the animals, A means for generating a notification to propose adjustment measures for animals based on the results of the aforementioned evaluation, Means for transmitting the aforementioned notification to an electronic terminal, A means of sharing the aforementioned animal's health data with medical professionals, A system that includes this.

2. The system according to claim 1, which analyzes vocalization and behavioral data in order to estimate the emotions and desires of the aforementioned animal.

3. The system according to claim 1, further comprising means for receiving feedback from veterinary medical professionals based on the results of the aforementioned evaluation.

Images