system

Abstract

We provide the system. [Solution] Means for receiving images or video data of livestock, An artificial intelligence means for analyzing the health status of livestock from the aforementioned data, A means of selecting a medical institution recommended based on the aforementioned health condition, A means for generating reservation information for the aforementioned medical institution, A means for providing evaluation information regarding the feed of the aforementioned livestock, 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 chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] <00​​​​​​​​

[0006] "Livestock" refers to animals that live together with and are kept as pets.

[0007] "Image or video data" refers to digital media data that visually records an object or scene.

[0008] "Means of receiving" refers to technical means that have the function of acquiring data from other devices or systems.

[0009] "Artificial intelligence tools" refer to algorithms and systems used to perform analysis and inference based on given data.

[0010] "Analyzing a health condition" refers to the act of evaluating data that indicates an animal's state and gaining insights into its health.

[0011] "Recommended medical institutions" refers to a situation where facilities that provide necessary medical care are proposed based on specific criteria.

[0012] "Means for generating reservation information" refers to technical means for creating information to secure the use of a specific event or facility in advance.

[0013] "Feed evaluation information" refers to information based on analysis results and reviews regarding the quality and suitability of pet food. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4]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 a plurality of emotions are mapped. [[ID=十七]] [Figure 10] It shows an emotion map to which a plurality of 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 an 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 an emotion engine is combined.

Embodiments for Carrying Out the Invention

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

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

[0017] It should be noted that in the original text, there is an inconsistent "十七" in item 17 which is likely an error. I have translated it as "It shows an emotion map to which a plurality of emotions are mapped." as a normal continuation of the relevant content. If there are specific requirements for handling this incorrect item, please let me know for further adjustment.In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0018] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0019] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is a system for accurately managing the health status of livestock raised by users and promptly providing necessary care. This system collects data by taking and uploading images or videos of livestock using a communication terminal, and a server analyzes this data.

[0036] The user first launches the application using a mobile device and takes pictures or videos of livestock. The device receives the captured data and sends it to the server. This collects data that visualizes the current state of the livestock.

[0037] The server uses artificial intelligence to analyze received image and video data and assess the health of livestock. For example, if a dog is unwell, the server detects the condition of its eyes and movement patterns to determine if it may be showing signs of indigestion. Based on the analysis results, the server recommends the most suitable medical facility for the user's location and condition and generates information for making an appointment.

[0038] This system also centralizes information on veterinary clinics accessible to users and provides evaluation information on pet food and related products. This evaluation information is generated based on reviews from other users and expert opinions, and the server suggests the most suitable options.

[0039] For example, if a user notices their cat is lethargic, they can record a video of the cat's condition that same day and upload it to the server. The server immediately analyzes the video and sends a notification to the user's device stating, "Your cat may be dehydrated. We recommend checking its water supply, as temperatures have been high recently." In this way, the system analyzes pet health information in real time and helps provide optimal care.

[0040] This invention allows users to monitor the health of their livestock in a timely manner and take prompt action as needed. It also significantly reduces the effort involved in selecting appropriate pet food and caring for pets while traveling. The system comprehensively supports pet health management, providing peace of mind and convenience to livestock owners.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user launches the application on their mobile device and takes pictures or videos of livestock. Once the user has finished preparing the data, they perform an upload operation to send it to the server through the application.

[0044] Step 2:

[0045] The terminal receives image or video data from the user and performs preprocessing. Preprocessing includes compressing the data size and converting the format to prepare the data for efficient transfer.

[0046] Step 3:

[0047] The terminal sends the pre-processed data to the server. The transmitted data is transferred using a communication protocol that ensures it reaches the server securely and efficiently.

[0048] Step 4:

[0049] The server feeds the received image or video data into an artificial intelligence system for analysis. The AI ​​uses its configured algorithms to extract key features related to the health of livestock and detect abnormalities or signs that require attention.

[0050] Step 5:

[0051] Based on the analysis results, the server sends a notification to the user. The notification includes a health status assessment and, if necessary, an option to make an appointment at the nearest veterinary clinic. The server also generates information on recommended pet food and related products.

[0052] Step 6:

[0053] The device receives notifications and suggestions from the server and displays them to the user in a visually easy-to-understand format. Notifications include health advice, booking links, and product reviews.

[0054] Step 7:

[0055] The user selects the appropriate action based on the information displayed on the device. For example, if they want to make an appointment at a medical facility or purchase recommended pet food, they perform these actions on the device.

[0056] (Example 1)

[0057] 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."

[0058] When raising livestock, it is essential to quickly and accurately assess their health and provide necessary medical care and support. However, ordinary pet owners lack specialized knowledge and may overlook changes in their livestock's condition, and selecting appropriate medical facilities can also be difficult. Therefore, there is a growing demand for systems that automatically assess the health of livestock and suggest appropriate measures.

[0059] 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.

[0060] In this invention, the server includes a device for acquiring visual information data of livestock, a device for transmitting the visual information data to a central memory device, and a device for analyzing the visual information data using a generative intelligence model in the central memory device and evaluating the health status of the livestock. This enables pet owners to accurately understand the health status of their livestock, allowing for prompt action and selection of appropriate medical facilities.

[0061] "Livestock" refers to animals that are raised and managed by humans for agricultural or other purposes.

[0062] "Visual information data" refers to data expressed in image or video format, and includes information with visual elements.

[0063] "Device" refers to a machine or electronic device configured to achieve a specific function or purpose.

[0064] A "central memory device" refers to a memory device connected to a central control computer that is involved in the storage and processing of data.

[0065] A "generative intelligence model" refers to a model created using an artificial intelligence learning algorithm and trained to solve a specific problem.

[0066] "Analysis" refers to a series of processes for examining data in detail and understanding its structure and meaning.

[0067] A "veterinary clinic" refers to a medical facility established for the purpose of conducting health checkups and providing treatment for animals.

[0068] A "visit plan" refers to the process of planning the necessary steps and timing for visiting a specific facility or location.

[0069] "Related products" refer to goods and services related to the product in question.

[0070] "Opinion information" refers to information that includes evaluations and opinions about products and services.

[0071] This invention is implemented as a system for accurately assessing the health status of livestock and taking appropriate measures. The user begins by using a mobile device to capture images or videos of the livestock. The device securely transmits this visual information data to a server, which acts as a central storage device. Data transmission takes place over the internet and is protected by encryption technology.

[0072] The server uses generative AI models developed with machine learning frameworks such as TENSORFLOW® to analyze the received data in detail. For example, it implements an image recognition algorithm to detect eye redness and abnormal movements in images of dogs. This allows the health status of livestock to be evaluated, and if an abnormality is detected, the server suggests the most suitable facility to the user based on information about veterinary clinics.

[0073] Users are notified of the analysis results and recommended actions via their mobile devices. For example, specific instructions such as, "Mild dehydration is observed. Please give water and let your pet rest in a cool place," are included. Information on the nearest veterinary clinic and reviews of pet food are also provided.

[0074] For example, a user can enter a prompt such as, "My dog's behavior is a little strange. Please use AI to analyze if there are any signs of indigestion," which will quickly perform a health check on the livestock and provide the user with necessary countermeasures. In this way, users can manage the health of their livestock in a timely and effective manner.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] User behavior

[0078] The user launches a dedicated application on their mobile device and takes pictures of their livestock. The input is visual information data in the form of images or videos of the livestock. Specifically, when the user notices something unusual about their pet, they use the device to record what is happening at that time. The output is the storage of the visual information data on the device.

[0079] Step 2:

[0080] Device functions

[0081] The terminal receives captured visual information data and transfers it to a server via the internet. The input is the visual information data received from the user. Specifically, the terminal encrypts this data according to a security protocol and sends it to the server. The output is the encrypted visual information data sent to the server.

[0082] Step 3:

[0083] Server Processing

[0084] The server analyzes the received visual information data using a generating AI model. The input is visual information data sent from the terminal. Specifically, the server utilizes an AI model built using TensorFlow and applies an image recognition algorithm to evaluate the health status of livestock from the data. The output is the analysis result regarding the health status of the livestock.

[0085] Step 4:

[0086] Server's judgment and proposal

[0087] Based on the analysis results, the server selects an appropriate veterinary clinic based on the health status of the livestock and generates information to notify the user. The input is the analysis results. Specifically, the server retrieves the most suitable veterinary clinic from the database based on the location and urgency of the situation, and creates recommendation information including a visit plan. The output is notification information of the recommended veterinary clinic and specific countermeasures.

[0088] Step 5:

[0089] Notification to the user

[0090] The server sends the generated notification information to the user's mobile device. The input is the notification information sent from the server. Specifically, the user receives the analysis results and recommendations through their device and can check specific countermeasures and visit plans. The output is the analysis results and recommendations that the user receives and checks.

[0091] (Application Example 1)

[0092] 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."

[0093] Managing and monitoring the health of livestock and pets is an important, yet sometimes burdensome, task for pet owners. However, in the midst of busy lives, it is difficult to perform health checks at the appropriate time and to detect abnormalities early, and by the time an abnormality is noticed, the condition may already be serious. Therefore, there is a need for a system that can efficiently manage the health of livestock and pets on a daily basis and respond quickly when abnormalities occur.

[0094] 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.

[0095] In this invention, the server includes means for monitoring the behavior of livestock in real time and detecting abnormalities, means for notifying the user when such abnormalities are detected, and means for receiving the image or video data. This allows the user to monitor the health of livestock on a daily basis and to quickly obtain information and take countermeasures when abnormalities are detected.

[0096] "Means for receiving images or video data of livestock" refers to technology that allows users to acquire images or videos of their livestock or pets through a communication device.

[0097] "An artificial intelligence tool for analyzing the health status of livestock" refers to a function that uses AI technology to analyze and determine the health status of livestock and pets based on acquired image and video data.

[0098] "Methods for selecting recommended medical institutions" refers to the process of extracting and selecting appropriate medical facilities related to the health condition of livestock and pets.

[0099] "Means for generating reservation information" refers to a function that constructs the date, time, and other information for a visit to a selected medical institution, and confirms the reservation as needed.

[0100] "Means of providing evaluation information regarding livestock feed" refers to a function that provides users with reviews and recommendations regarding pet food and related products.

[0101] "Means for monitoring livestock behavior in real time and detecting abnormalities" refers to technology that tracks the daily behavior of livestock and pets in real time and immediately identifies any unusual behavior.

[0102] "Means of notifying users when an abnormality is detected" refers to a system that sends information to the user's communication terminal to warn them when abnormal behavior or changes in the health of livestock or pets are detected.

[0103] To implement this invention, the system is constructed by combining a household robot, a communication terminal, a cloud server, and other components. The household robot is equipped with a camera and monitors the behavior of livestock or pets in real time. The robot periodically takes pictures and videos of pets and uploads the data to the cloud server via the communication terminal.

[0104] The server is equipped with the ability to analyze collected data using artificial intelligence (AI). Specifically, it uses cloud services (e.g., AWS® Rekognition) to analyze the health status and abnormal behavior of animals in images and videos. If an abnormality is detected, the server sends a push notification to a communication device (e.g., a smartphone) to promptly warn the user.

[0105] Furthermore, the server collects and provides user reviews and expert opinions on pet food and related products. This information is generated based on collected user reviews and expert opinions. Users can then use this information to make the best choices.

[0106] For example, if a user leaves their pet at home while on a long business trip, the robot will automatically patrol and monitor the pet's health. If the pet exhibits unusual behavior, such as refusing to eat, the server will immediately notify the user. This allows the user to take appropriate action even remotely.

[0107] Examples of prompts to input into the generating AI model include, "Design a system that monitors a pet's condition in real time and immediately notifies the user if an abnormality is detected." Through these prompts, the AI ​​can generate specific discussions and proposals aimed at system design.

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The household robot captures images and videos of livestock and pets using its camera. The captured results are then transmitted as data to a communication terminal. The input is real-time footage of the pet, and the output is image and video data.

[0111] Step 2:

[0112] The communication terminal uploads received image and video data to a cloud server. The input is data transferred from the home robot, and the output is data sent to the cloud server.

[0113] Step 3:

[0114] The server analyzes data received on the cloud using artificial intelligence. This analysis uses, for example, AWS Rekognition to detect the health status and abnormal behavior of animals in images and videos. The input is image and video data on the cloud server, and the output is the analysis results regarding the pet's health status.

[0115] Step 4:

[0116] If the analysis results indicate an anomaly, the server sends a notification to the user's communication terminal. The input is the analysis result, and the output is the warning message sent to the user's communication terminal.

[0117] Step 5:

[0118] The user checks notifications received on their device and, if necessary, directly checks on their pet's condition or contacts a medical institution. The input is the notification displayed on the device, and the output is the action taken by the user to improve the situation.

[0119] Step 6:

[0120] The server collects review information on pet food and related products and presents the user with the best options. Based on this information, the user can select the appropriate product. The input is the review information stored on the server, and the output is a list of products available for the user to choose from.

[0121] 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.

[0122] This invention combines an emotion engine with a system that supports the health management of livestock raised by users, comprehensively understanding the condition of both the livestock and the user, and providing optimized care and information. This system is composed of multiple means and realizes functions that enhance user convenience.

[0123] First, the user launches the application using their device and takes pictures or videos of livestock. This is used as basic data for assessing their health. The device receives this data, processes it, and then sends it to the server in the most suitable format.

[0124] The server uses artificial intelligence (AI) to analyze the received image or video data. This AI analyzes features in the data to determine the health status of livestock and decide on necessary medical treatment. Based on the analysis results, it selects a medical facility recommended to the user and generates information for making an appointment. This information is optimized taking into account the user's location and the condition of the livestock.

[0125] Furthermore, the server is equipped with an emotion engine that can recognize the user's emotions. This engine analyzes the user's voice and text input sent from the terminal to identify their emotional state. By adjusting the content and interface of the information provided according to the emotional state, the server ensures that users receive information in a way that is easiest to understand and reduces stress.

[0126] For example, when a user is worried about their pet's health, this emotion engine senses the user's tension and anxiety and prioritizes providing reassuring information in simple language. Similarly, when it comes to things like vet appointments or food recommendations, it adapts to the user's needs, providing quick instructions if they're in a hurry, and offering detailed explanations if they have more time.

[0127] Thus, the present invention is a system that not only analyzes the health status of livestock with high accuracy and efficiently selects appropriate medical measures, but also provides information that is sensitive to the user's emotional state, thereby realizing a safe and comfortable experience for users who raise livestock.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] The user launches the application on their mobile device and takes pictures or videos of their livestock. The captured data is saved in the application as initial data for evaluating the health status of the animals.

[0131] Step 2:

[0132] The device receives the stored image or video data and adjusts its size and format. This includes data compression and format conversion. The processed data is then sent to the server.

[0133] Step 3:

[0134] The server receives data sent from the terminal and passes it to the artificial intelligence engine. The AI ​​engine analyzes the characteristics of livestock in images and videos and determines their health status. If an abnormality is detected as a result of the analysis, it makes predictions about specific diseases and symptoms.

[0135] Step 4:

[0136] Based on the analysis results, the server recommends the most suitable medical facility to the user. This includes selecting an appropriate facility based on the user's location and the condition of their livestock. If necessary, it generates appointment information for the medical facility and sends it to the user's device.

[0137] Step 5:

[0138] The terminal displays analysis results received from the server and information on medical institutions. Based on the presented information, the user selects appropriate measures for the livestock. Evaluation information on feed related to health status is also displayed simultaneously, allowing the user to consider their options.

[0139] Step 6:

[0140] An emotion engine is used by the server to analyze user input (voice and text). It recognizes the user's emotional state and adjusts the information accordingly. For example, if the user is feeling anxious, the information will be presented in a way that provides reassurance.

[0141] Step 7:

[0142] Users manage and care for their pets through content that is flexibly adjusted to their emotions. This reduces the psychological burden of taking the next steps, such as making appointments with veterinarians or purchasing products, and supports smooth decision-making.

[0143] (Example 2)

[0144] 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".

[0145] Traditional systems for managing animal health have struggled to accurately assess health conditions and have lacked the ability to provide information tailored to the user's emotional needs. As a result, users sometimes experienced difficulties in selecting and booking appropriate medical facilities, and may have felt unnecessary stress. There was a need to solve these problems and realize appropriate and reassuring health management for both animals and users.

[0146] 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.

[0147] In this invention, the server includes means for receiving images or video information of animals, intelligent processing means for evaluating the health status of animals from the information, and means for recognizing the user's emotional state and adjusting the content and format of the information provided. This makes it possible to accurately evaluate the health status of animals and provide optimal information that is sensitive to the user's emotions.

[0148] "Animals" refers to living creatures kept as livestock or pets, and these are the subjects whose health status is managed by this system.

[0149] "Image or video information" refers to photographic or video data used to visually record the condition of an animal.

[0150] "Intelligent processing means" refers to a system that uses artificial intelligence technology to analyze received image or video information and evaluate the health status of animals.

[0151] A "medical facility" refers to an organization such as a hospital or clinic that can provide medical treatment according to the health condition of an animal.

[0152] "Means for creating reservation information" refers to the function of generating information to ensure that animals receive medical treatment at selected medical facilities.

[0153] "Feed evaluation information" refers to information related to animal nutrition management, specifically data on recommended types and amounts of feed based on the animal's health condition.

[0154] "Means of recognizing emotional states" refers to a function that can analyze information entered by the user and identify that emotion.

[0155] "Means of adjusting the content and format of information" refers to a function that dynamically changes the type and presentation method of information provided based on the user's emotional state.

[0156] This invention is a system for evaluating the health status of animals and providing users with appropriate medical information and support. The user first uses a terminal to launch a dedicated application and capture images or video information of the animal. For this purpose, an electronic device with a camera function, such as a smartphone or tablet, is used.

[0157] The device processes the captured images and video information, converts them to the optimal format, and sends them to the server. This process includes software that performs data compression and format conversion.

[0158] The server receives the transmitted information and uses intelligent processing to evaluate the animal's health status. This evaluation utilizes a generative AI model powered by deep learning technology, which analyzes the animal's behavior and physical characteristics to determine its health status. It also recognizes the user's emotional state using voice and text input and provides information accordingly. An analysis program equipped with an emotion engine executes this process.

[0159] For example, if a user enters a prompt such as, "My dog ​​seems lethargic lately, so please check its health," the server will assess its health condition and provide information to reassure the user. It will also select the nearest appropriate medical facility and create an appointment if necessary.

[0160] This system allows users to continuously and accurately manage their animals' health, resulting in a less stressful pet-rearing experience.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The user uses a device to launch a dedicated application and capture images or videos of the animals they are keeping. During this process, the user must select the appropriate moment for the shot and focus the camera. The input is high-resolution image or video data acquired by the camera. The output is the captured image or video file.

[0164] Step 2:

[0165] The device receives the acquired image or video data and converts it to an appropriate format. This process involves image format conversion and data compression. The input is raw image data, and the output is a compressed data format (e.g., JPEG or MP4). Specifically, image processing software is used to reduce the size of the data.

[0166] Step 3:

[0167] The terminal sends the converted data to the server. The data is securely transferred over the internet. The input for this step is compressed image or video data, and the output is the data transferred to the server via a communication protocol. In particular, encryption protocols such as SSL are used to ensure the security of the data.

[0168] Step 4:

[0169] The server uses intelligent processing tools to analyze the received data. The input is image or video data that arrives at the server. The server analyzes this data using a generative AI model to determine the health status of the animals. The output is evaluation data indicating the health status. Specifically, a deep learning algorithm extracts features from the video and compares them with an existing health database.

[0170] Step 5:

[0171] The server uses an emotion engine to recognize the user's emotional state. Input is voice input or text data from the user. The server analyzes this data to identify the user's emotions. Output is the user's emotional status information. Emotion analysis software performs operations such as analyzing voice tone and keywords.

[0172] Step 6:

[0173] The server generates optimal information tailored to the animal's current condition based on analysis results and emotional information, and sends it to the user. This information includes the selection and booking of medical facilities. The input is the animal's health assessment and the user's emotional information, and the output is an informational message presented to the user. The server uses an information generation program to adaptively customize the information and provide it in the most easily understandable format for the user.

[0174] (Application Example 2)

[0175] 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".

[0176] The objective of this invention is to support livestock owners in providing effective care with peace of mind by analyzing the health status of livestock with high accuracy and providing information tailored to the user's emotions. Furthermore, it aims to provide support to pet shops and related facilities, enabling pet owners to easily manage their pets' health status and select appropriate products and services.

[0177] 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.

[0178] In this invention, the server includes means for receiving visual data of livestock, means for calculating the health status of the livestock from the data, and means for recognizing the emotional state of the user and adapting information accordingly. This enables accurate analysis of the health status of livestock and the provision of optimal information tailored to the user's emotions.

[0179] "Visual data of livestock" refers to digital information obtained as images or videos of livestock.

[0180] "Analytical computational means" refers to computational techniques used to evaluate the health status of livestock from acquired visual data.

[0181] A "recommended medical facility" is a place that provides medical services appropriate to the health of livestock based on the analysis results.

[0182] "Means for generating reservation information" refers to technology that has the function of determining the date and time of visit to the selected medical facility and preparing the necessary information.

[0183] "Means of providing nutritional information" refers to technologies that have the function of generating advice and recommendations useful for the nutritional management of livestock.

[0184] "Means for recognizing a user's emotional state" refers to technologies that analyze user voice and text data to identify their emotions.

[0185] "Means of adjusting the priority and content of information" refers to technologies that change the importance and content of the information provided based on the perceived emotional state.

[0186] A "user computing device" is a terminal that includes computer technology for users to receive information and interact with it.

[0187] The system for implementing this invention consists of a user's computing device, a communication network, and a server. First, the user's terminal is used to acquire image or video data of livestock. The user captures the data through a dedicated application and sends the data from the terminal to the server. This application is built using a platform such as "React Native".

[0188] The server analyzes the received visual data using AI frameworks such as TensorFlow or PyTorch. This analysis is a process that uses features derived from the visual data to determine the health status of livestock. The server also uses IBM Watson® and Google Cloud Natural Language API to recognize the user's emotional state through voice and text input. This makes it possible to adjust the priority and content of information according to the user's emotions and provide optimal information.

[0189] The main value this system provides is the ability to accurately assess the health status of livestock and automate the selection and booking of recommended medical facilities based on that assessment. Furthermore, it provides information and advice in a stress-reducing manner based on the user's emotional state, creating an environment where pet owners can manage their livestock's health with peace of mind.

[0190] As a concrete example, there was a case where a customer visiting a pet shop checked their dog's health status using an app and noticed weight gain. In this situation, the emotional engine displayed advice to alleviate the owner's anxiety and recommended products suitable for weight management, thereby improving customer satisfaction.

[0191] An example of a prompt using a generative AI model is: "Consider how you can provide reassuring advice based on the feelings of a pet owner who is concerned about their dog's health."

[0192] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0193] Step 1:

[0194] The user launches a smartphone application and takes an image or video of livestock. This data is input to the device as visual information and prepared to be sent directly to the server. Data processing involves format conversion and compression of the visual data.

[0195] Step 2:

[0196] The server receives visual data sent from the terminal. The server uses TensorFlow or PyTorch to extract features from the visual data and perform data calculations to determine the health status of livestock. The output is the health check results.

[0197] Step 3:

[0198] The server identifies recommended medical facilities based on the diagnostic results. In this process, data processing is performed on the input information (diagnosis results), taking into account geographical information and the expertise of the facilities, and a list of medical facilities is output.

[0199] Step 4:

[0200] Based on the selection of a medical facility, the server generates reservation information. Using input data such as the user's current location, the server automatically sets the optimal reservation date and time, and outputs the reservation information.

[0201] Step 5:

[0202] Voice and text data entered by the user through the application are sent to the server for sentiment analysis. The server uses "IBM Watson" or "Google Cloud Natural Language API" to analyze the emotional state and prepare to provide information tailored to the user's situation.

[0203] Step 6:

[0204] The server adjusts the priority and content of information provided based on the sentiment analysis results, and the final information is output and displayed on the user's terminal. This adjustment includes information optimization operations that correspond to the input of the user's emotional state.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] [Second Embodiment]

[0209] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0210] 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.

[0211] 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).

[0212] 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.

[0213] 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.

[0214] 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).

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] 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".

[0221] This invention is a system for accurately managing the health status of livestock raised by users and promptly providing necessary care. This system collects data by taking and uploading images or videos of livestock using a communication terminal, and a server analyzes this data.

[0222] The user first launches the application using a mobile device and takes pictures or videos of livestock. The device receives the captured data and sends it to the server. This collects data that visualizes the current state of the livestock.

[0223] The server uses artificial intelligence to analyze received image and video data and assess the health of livestock. For example, if a dog is unwell, the server detects the condition of its eyes and movement patterns to determine if it may be showing signs of indigestion. Based on the analysis results, the server recommends the most suitable medical facility for the user's location and condition and generates information for making an appointment.

[0224] This system also centralizes information on veterinary clinics accessible to users and provides evaluation information on pet food and related products. This evaluation information is generated based on reviews from other users and expert opinions, and the server suggests the most suitable options.

[0225] For example, if a user notices their cat is lethargic, they can record a video of the cat's condition that same day and upload it to the server. The server immediately analyzes the video and sends a notification to the user's device stating, "Your cat may be dehydrated. We recommend checking its water supply, as temperatures have been high recently." In this way, the system analyzes pet health information in real time and helps provide optimal care.

[0226] This invention allows users to monitor the health of their livestock in a timely manner and take prompt action as needed. It also significantly reduces the effort involved in selecting appropriate pet food and caring for pets while traveling. The system comprehensively supports pet health management, providing peace of mind and convenience to livestock owners.

[0227] The following describes the processing flow.

[0228] Step 1:

[0229] The user launches the application on their mobile device and takes pictures or videos of livestock. Once the user has finished preparing the data, they perform an upload operation to send it to the server through the application.

[0230] Step 2:

[0231] The terminal receives image or video data from the user and performs preprocessing. Preprocessing includes compressing the data size and converting the format to prepare the data for efficient transfer.

[0232] Step 3:

[0233] The terminal sends the pre-processed data to the server. The transmitted data is transferred using a communication protocol that ensures it reaches the server securely and efficiently.

[0234] Step 4:

[0235] The server feeds the received image or video data into an artificial intelligence system for analysis. The AI ​​uses its configured algorithms to extract key features related to the health of livestock and detect abnormalities or signs that require attention.

[0236] Step 5:

[0237] Based on the analysis results, the server sends a notification to the user. The notification includes a health status assessment and, if necessary, an option to make an appointment at the nearest veterinary clinic. The server also generates information on recommended pet food and related products.

[0238] Step 6:

[0239] The device receives notifications and suggestions from the server and displays them to the user in a visually easy-to-understand format. Notifications include health advice, booking links, and product reviews.

[0240] Step 7:

[0241] The user selects the appropriate action based on the information displayed on the device. For example, if they want to make an appointment at a medical facility or purchase recommended pet food, they perform these actions on the device.

[0242] (Example 1)

[0243] 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."

[0244] When raising livestock, it is essential to quickly and accurately assess their health and provide necessary medical care and support. However, ordinary pet owners lack specialized knowledge and may overlook changes in their livestock's condition, and selecting appropriate medical facilities can also be difficult. Therefore, there is a growing demand for systems that automatically assess the health of livestock and suggest appropriate measures.

[0245] 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.

[0246] In this invention, the server includes a device for acquiring visual information data of livestock, a device for transmitting the visual information data to a central memory device, and a device for analyzing the visual information data using a generative intelligence model in the central memory device and evaluating the health status of the livestock. This enables pet owners to accurately understand the health status of their livestock, allowing for prompt action and selection of appropriate medical facilities.

[0247] "Livestock" refers to animals that are raised and managed by humans for agricultural or other purposes.

[0248] "Visual information data" refers to data expressed in image or video format, and includes information with visual elements.

[0249] "Device" refers to a machine or electronic device configured to achieve a specific function or purpose.

[0250] A "central memory device" refers to a memory device connected to a central control computer that is involved in the storage and processing of data.

[0251] A "generative intelligence model" refers to a model created using an artificial intelligence learning algorithm and trained to solve a specific problem.

[0252] "Analysis" refers to a series of processes for examining data in detail and understanding its structure and meaning.

[0253] A "veterinary clinic" refers to a medical facility established for the purpose of conducting health checkups and providing treatment for animals.

[0254] A "visit plan" refers to the process of planning the necessary steps and timing for visiting a specific facility or location.

[0255] "Related products" refer to goods and services related to the product in question.

[0256] "Opinion information" refers to information that includes evaluations and opinions about products and services.

[0257] This invention is implemented as a system for accurately assessing the health status of livestock and taking appropriate measures. The user begins by using a mobile device to capture images or videos of the livestock. The device securely transmits this visual information data to a server, which acts as a central storage device. Data transmission takes place over the internet and is protected by encryption technology.

[0258] The server uses generative AI models developed with machine learning frameworks such as TensorFlow to analyze the received data in detail. For example, it has implemented an image recognition algorithm to detect eye redness and abnormal movements in images of dogs. This allows the health status of livestock to be evaluated, and if an abnormality is detected, the server suggests the most suitable facility to the user based on information about veterinary clinics.

[0259] Users are notified of the analysis results and recommended actions via their mobile devices. For example, specific instructions such as, "Mild dehydration is observed. Please give water and let your pet rest in a cool place," are included. Information on the nearest veterinary clinic and reviews of pet food are also provided.

[0260] For example, a user can enter a prompt such as, "My dog's behavior is a little strange. Please use AI to analyze if there are any signs of indigestion," which will quickly perform a health check on the livestock and provide the user with necessary countermeasures. In this way, users can manage the health of their livestock in a timely and effective manner.

[0261] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0262] Step 1:

[0263] User behavior

[0264] The user launches a dedicated application on their mobile device and takes pictures of their livestock. The input is visual information data in the form of images or videos of the livestock. Specifically, when the user notices something unusual about their pet, they use the device to record what is happening at that time. The output is the storage of the visual information data on the device.

[0265] Step 2:

[0266] Device functions

[0267] The terminal receives captured visual information data and transfers it to a server via the internet. The input is the visual information data received from the user. Specifically, the terminal encrypts this data according to a security protocol and sends it to the server. The output is the encrypted visual information data sent to the server.

[0268] Step 3:

[0269] Server Processing

[0270] The server analyzes the received visual information data using a generating AI model. The input is visual information data sent from the terminal. Specifically, the server utilizes an AI model built using TensorFlow and applies an image recognition algorithm to evaluate the health status of livestock from the data. The output is the analysis result regarding the health status of the livestock.

[0271] Step 4:

[0272] Server's judgment and proposal

[0273] Based on the analysis results, the server selects an appropriate veterinary clinic based on the health status of the livestock and generates information to notify the user. The input is the analysis results. Specifically, the server retrieves the most suitable veterinary clinic from the database based on the location and urgency of the situation, and creates recommendation information including a visit plan. The output is notification information of the recommended veterinary clinic and specific countermeasures.

[0274] Step 5:

[0275] Notification to the user

[0276] The server sends the generated notification information to the user's mobile device. The input is the notification information sent from the server. Specifically, the user receives the analysis results and recommendations through their device and can check specific countermeasures and visit plans. The output is the analysis results and recommendations that the user receives and checks.

[0277] (Application Example 1)

[0278] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0279] Managing and monitoring the health status of livestock and pets is an important and sometimes burdensome task for their owners. However, it is difficult to manage their health at appropriate times and detect abnormalities early in a busy life, and when an abnormality is noticed, the situation may already be serious. Therefore, there is a need for a system that can efficiently manage the health status of livestock and pets on a daily basis and respond quickly when an abnormality occurs.

[0280] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following respective means.

[0281] In this invention, the server includes means for monitoring the behavior of livestock in real time and detecting abnormalities, means for notifying the user when the abnormality is detected, and means for receiving the image or video data. Thereby, the user can monitor the health of livestock on a daily basis and obtain information quickly and take measures when an abnormality is detected.

[0282] The "means for receiving image or video data of livestock" refers to a technology for acquiring images and videos that can capture the appearance of livestock and pets raised by the user through a communication device.

[0283] The "artificial intelligence means for analyzing the health status of livestock" refers to a function for analyzing and judging the health status of livestock and pets using AI technology based on the acquired image and video data.

[0284] The "means for selecting a recommended medical institution" refers to a process of extracting and selecting an appropriate medical facility related to the health status of livestock and pets.

[0285] The "means for generating reservation information" refers to a function for constructing the date and time and information for visiting the selected medical institution and finalizing the reservation if necessary.

[0286] The "means for providing evaluation information regarding livestock feed" refers to a function for providing the user with reviews and recommendations regarding pet food and related products.

[0287] The means for "monitoring livestock behavior in real time and detecting abnormalities" refers to a technology that tracks the daily behavior of livestock and pets in real time and immediately identifies behaviors that are different from normal.

[0288] The means for "notifying the user when an abnormality is detected" refers to a system that transmits such information to the user's communication terminal and issues a warning when abnormal behaviors or changes in the health status of livestock and pets are confirmed.

[0289] To implement this invention, the system is constructed by combining a household robot, a communication terminal, a cloud server, etc. The household robot is equipped with a camera and monitors the behavior of livestock and pets in real time. The robot periodically takes pictures and videos of the pet and uploads the data to the cloud server via the communication terminal.

[0290] The server has a function of analyzing the collected data using artificial intelligence (AI). Specifically, it uses cloud services (such as AWS Rekognition) to analyze the health status and abnormal behaviors of animals in images and videos. When an abnormality is detected, the server sends a push notification to the communication terminal (such as a smartphone) to quickly warn the user.

[0291] Furthermore, the server collects evaluation information on pet food and related products and provides it to the user. This information is generated based on the collected user reviews and expert opinions. The user can make an optimal choice based on this information.

[0292] As a specific example, when the user leaves the pet at home during a long business trip, the robot automatically makes rounds to monitor the pet's health. If the pet shows abnormal behavior, for example, stops eating, the server immediately notifies the user. This enables the user to take appropriate measures even from a remote location.

[0293] Examples of prompts to input into the generating AI model include, "Design a system that monitors a pet's condition in real time and immediately notifies the user if an abnormality is detected." Through these prompts, the AI ​​can generate specific discussions and proposals aimed at system design.

[0294] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0295] Step 1:

[0296] The household robot captures images and videos of livestock and pets using its camera. The captured results are then transmitted as data to a communication terminal. The input is real-time footage of the pet, and the output is image and video data.

[0297] Step 2:

[0298] The communication terminal uploads received image and video data to a cloud server. The input is data transferred from the home robot, and the output is data sent to the cloud server.

[0299] Step 3:

[0300] The server analyzes data received on the cloud using artificial intelligence. This analysis uses, for example, AWS Rekognition to detect the health status and abnormal behavior of animals in images and videos. The input is image and video data on the cloud server, and the output is the analysis results regarding the pet's health status.

[0301] Step 4:

[0302] If the analysis results indicate an anomaly, the server sends a notification to the user's communication terminal. The input is the analysis result, and the output is the warning message sent to the user's communication terminal.

[0303] Step 5:

[0304] The user checks the notifications received on the terminal and, if necessary, directly checks the status of the pet or contacts a medical institution. The input is the notifications displayed on the terminal, and the output is the measures for improving the situation based on the user's actions.

[0305] Step 6:

[0306] The server collects evaluation information on pet food and related products and shows the optimal options to the user. Based on this information, the user can select appropriate products. The input is the review information stored in the server, and the output is a list of products that the user can select.

[0307] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions.

[0308] The present invention combines an emotion engine with a system for supporting the health management of livestock raised by a user, comprehensively grasps the states of the livestock and the user, and provides optimized care and information. This system is configured by combining a plurality of means and realizes a function of enhancing the convenience of the user.

[0309] First, the user uses the terminal to start an application and takes a picture or video of the livestock. This is used as basic data for evaluating the health status. The terminal receives this data, processes it, and then transmits it to the server in an optimal format.

[0310] The server uses artificial intelligence means to analyze the received image or video data. This artificial intelligence analyzes the features in the data to determine the health status of the livestock and judge the necessary medical measures. Based on the analysis results, a medical institution recommended to the user is selected, and information for reservation is generated. This information is optimized considering the user's location information and the status of the livestock.

[0311] Furthermore, the server is equipped with an emotion engine that can recognize the user's emotions. This engine analyzes the user's voice and text input sent from the terminal to identify their emotional state. By adjusting the content and interface of the information provided according to the emotional state, the server ensures that users receive information in a way that is easiest to understand and reduces stress.

[0312] For example, when a user is worried about their pet's health, this emotion engine senses the user's tension and anxiety and prioritizes providing reassuring information in simple language. Similarly, when it comes to things like vet appointments or food recommendations, it adapts to the user's needs, providing quick instructions if they're in a hurry, and offering detailed explanations if they have more time.

[0313] Thus, the present invention is a system that not only analyzes the health status of livestock with high accuracy and efficiently selects appropriate medical measures, but also provides information that is sensitive to the user's emotional state, thereby realizing a safe and comfortable experience for users who raise livestock.

[0314] The following describes the processing flow.

[0315] Step 1:

[0316] The user launches the application on their mobile device and takes pictures or videos of their livestock. The captured data is saved in the application as initial data for evaluating the health status of the animals.

[0317] Step 2:

[0318] The device receives the stored image or video data and adjusts its size and format. This includes data compression and format conversion. The processed data is then sent to the server.

[0319] Step 3:

[0320] The server receives data sent from the terminal and passes it to the artificial intelligence engine. The AI ​​engine analyzes the characteristics of livestock in images and videos and determines their health status. If an abnormality is detected as a result of the analysis, it makes predictions about specific diseases and symptoms.

[0321] Step 4:

[0322] Based on the analysis results, the server recommends the most suitable medical facility to the user. This includes selecting an appropriate facility based on the user's location and the condition of their livestock. If necessary, it generates appointment information for the medical facility and sends it to the user's device.

[0323] Step 5:

[0324] The terminal displays analysis results received from the server and information on medical institutions. Based on the presented information, the user selects appropriate measures for the livestock. Evaluation information on feed related to health status is also displayed simultaneously, allowing the user to consider their options.

[0325] Step 6:

[0326] An emotion engine is used by the server to analyze user input (voice and text). It recognizes the user's emotional state and adjusts the information accordingly. For example, if the user is feeling anxious, the information will be presented in a way that provides reassurance.

[0327] Step 7:

[0328] Users manage and care for their pets through content that is flexibly adjusted to their emotions. This reduces the psychological burden of taking the next steps, such as making appointments with veterinarians or purchasing products, and supports smooth decision-making.

[0329] (Example 2)

[0330] 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".

[0331] Traditional systems for managing animal health have struggled to accurately assess health conditions and have lacked the ability to provide information tailored to the user's emotional needs. As a result, users sometimes experienced difficulties in selecting and booking appropriate medical facilities, and may have felt unnecessary stress. There was a need to solve these problems and realize appropriate and reassuring health management for both animals and users.

[0332] 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.

[0333] In this invention, the server includes means for receiving images or video information of animals, intelligent processing means for evaluating the health status of animals from the information, and means for recognizing the user's emotional state and adjusting the content and format of the information provided. This makes it possible to accurately evaluate the health status of animals and provide optimal information that is sensitive to the user's emotions.

[0334] "Animals" refers to living creatures kept as livestock or pets, and these are the subjects whose health status is managed by this system.

[0335] "Image or video information" refers to photographic or video data used to visually record the condition of an animal.

[0336] "Intelligent processing means" refers to a system that uses artificial intelligence technology to analyze received image or video information and evaluate the health status of animals.

[0337] A "medical facility" refers to an organization such as a hospital or clinic that can provide medical treatment according to the health condition of an animal.

[0338] "Means for creating reservation information" refers to the function of generating information to ensure that animals receive medical treatment at selected medical facilities.

[0339] "Feed evaluation information" refers to information related to animal nutrition management, specifically data on recommended types and amounts of feed based on the animal's health condition.

[0340] "Means of recognizing emotional states" refers to a function that can analyze information entered by the user and identify that emotion.

[0341] "Means of adjusting the content and format of information" refers to a function that dynamically changes the type and presentation method of information provided based on the user's emotional state.

[0342] This invention is a system for evaluating the health status of animals and providing users with appropriate medical information and support. The user first uses a terminal to launch a dedicated application and capture images or video information of the animal. For this purpose, an electronic device with a camera function, such as a smartphone or tablet, is used.

[0343] The device processes the captured images and video information, converts them to the optimal format, and sends them to the server. This process includes software that performs data compression and format conversion.

[0344] The server receives the transmitted information and uses intelligent processing to evaluate the animal's health status. This evaluation utilizes a generative AI model powered by deep learning technology, which analyzes the animal's behavior and physical characteristics to determine its health status. It also recognizes the user's emotional state using voice and text input and provides information accordingly. An analysis program equipped with an emotion engine executes this process.

[0345] For example, if a user enters a prompt such as, "My dog ​​seems lethargic lately, so please check its health," the server will assess its health condition and provide information to reassure the user. It will also select the nearest appropriate medical facility and create an appointment if necessary.

[0346] This system allows users to continuously and accurately manage their animals' health, resulting in a less stressful pet-rearing experience.

[0347] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0348] Step 1:

[0349] The user uses a device to launch a dedicated application and capture images or videos of the animals they are keeping. During this process, the user must select the appropriate moment for the shot and focus the camera. The input is high-resolution image or video data acquired by the camera. The output is the captured image or video file.

[0350] Step 2:

[0351] The device receives the acquired image or video data and converts it to an appropriate format. This process involves image format conversion and data compression. The input is raw image data, and the output is a compressed data format (e.g., JPEG or MP4). Specifically, image processing software is used to reduce the size of the data.

[0352] Step 3:

[0353] The terminal sends the converted data to the server. The data is securely transferred over the internet. The input for this step is compressed image or video data, and the output is the data transferred to the server via a communication protocol. In particular, encryption protocols such as SSL are used to ensure the security of the data.

[0354] Step 4:

[0355] The server uses intelligent processing tools to analyze the received data. The input is image or video data that arrives at the server. The server analyzes this data using a generative AI model to determine the health status of the animals. The output is evaluation data indicating the health status. Specifically, a deep learning algorithm extracts features from the video and compares them with an existing health database.

[0356] Step 5:

[0357] The server uses an emotion engine to recognize the user's emotional state. Input is voice input or text data from the user. The server analyzes this data to identify the user's emotions. Output is the user's emotional status information. Emotion analysis software performs operations such as analyzing voice tone and keywords.

[0358] Step 6:

[0359] The server generates optimal information tailored to the animal's current condition based on analysis results and emotional information, and sends it to the user. This information includes the selection and booking of medical facilities. The input is the animal's health assessment and the user's emotional information, and the output is an informational message presented to the user. The server uses an information generation program to adaptively customize the information and provide it in the most easily understandable format for the user.

[0360] (Application Example 2)

[0361] 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."

[0362] The objective of this invention is to support livestock owners in providing effective care with peace of mind by analyzing the health status of livestock with high accuracy and providing information tailored to the user's emotions. Furthermore, it aims to provide support to pet shops and related facilities, enabling pet owners to easily manage their pets' health status and select appropriate products and services.

[0363] 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.

[0364] In this invention, the server includes means for receiving visual data of livestock, means for calculating the health status of the livestock from the data, and means for recognizing the emotional state of the user and adapting information accordingly. This enables accurate analysis of the health status of livestock and the provision of optimal information tailored to the user's emotions.

[0365] "Visual data of livestock" refers to digital information obtained as images or videos of livestock.

[0366] "Analytical computational means" refers to computational techniques used to evaluate the health status of livestock from acquired visual data.

[0367] A "recommended medical facility" is a place that provides medical services appropriate to the health of livestock based on the analysis results.

[0368] "Means for generating reservation information" refers to technology that has the function of determining the date and time of visit to the selected medical facility and preparing the necessary information.

[0369] "Means of providing nutritional information" refers to technologies that have the function of generating advice and recommendations useful for the nutritional management of livestock.

[0370] "Means for recognizing a user's emotional state" refers to technologies that analyze user voice and text data to identify their emotions.

[0371] "Means of adjusting the priority and content of information" refers to technologies that change the importance and content of the information provided based on the perceived emotional state.

[0372] A "user computing device" is a terminal that includes computer technology for users to receive information and interact with it.

[0373] The system for implementing this invention consists of a user's computing device, a communication network, and a server. First, the user's terminal is used to acquire image or video data of livestock. The user captures the data through a dedicated application and sends the data from the terminal to the server. This application is built using a platform such as "React Native".

[0374] The server analyzes the received visual data using AI frameworks such as TensorFlow or PyTorch. This analysis is a process that uses features derived from the visual data to determine the health status of livestock. The server also uses IBM Watson and Google Cloud Natural Language API to recognize the user's emotional state through voice and text input. This makes it possible to adjust the priority and content of information according to the user's emotions and provide the most relevant information.

[0375] The main value this system provides is the ability to accurately assess the health status of livestock and automate the selection and booking of recommended medical facilities based on that assessment. Furthermore, it provides information and advice in a stress-reducing manner based on the user's emotional state, creating an environment where pet owners can manage their livestock's health with peace of mind.

[0376] As a concrete example, there was a case where a customer visiting a pet shop checked their dog's health status using an app and noticed weight gain. In this situation, the emotional engine displayed advice to alleviate the owner's anxiety and recommended products suitable for weight management, thereby improving customer satisfaction.

[0377] An example of a prompt using a generative AI model is: "Consider how you can provide reassuring advice based on the feelings of a pet owner who is concerned about their dog's health."

[0378] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0379] Step 1:

[0380] The user launches a smartphone application and takes an image or video of livestock. This data is input to the device as visual information and prepared to be sent directly to the server. Data processing involves format conversion and compression of the visual data.

[0381] Step 2:

[0382] The server receives visual data sent from the terminal. The server uses TensorFlow or PyTorch to extract features from the visual data and perform data calculations to determine the health status of livestock. The output is the health check results.

[0383] Step 3:

[0384] The server identifies recommended medical facilities based on the diagnostic results. In this process, data processing is performed on the input information (diagnosis results), taking into account geographical information and the expertise of the facilities, and a list of medical facilities is output.

[0385] Step 4:

[0386] Based on the selection of a medical facility, the server generates reservation information. Using input data such as the user's current location, the server automatically sets the optimal reservation date and time, and outputs the reservation information.

[0387] Step 5:

[0388] Voice and text data entered by the user through the application are sent to the server for sentiment analysis. The server uses "IBM Watson" or "Google Cloud Natural Language API" to analyze the emotional state and prepare to provide information tailored to the user's situation.

[0389] Step 6:

[0390] The server adjusts the priority and content of information provided based on the sentiment analysis results, and the final information is output and displayed on the user's terminal. This adjustment includes information optimization operations that correspond to the input of the user's emotional state.

[0391] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0392] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0393] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0394] [Third Embodiment]

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

[0396] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0397] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0398] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0399] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0400] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0401] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0402] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0403] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0404] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0405] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0406] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0407] This invention is a system for accurately managing the health status of livestock raised by users and promptly providing necessary care. This system collects data by taking and uploading images or videos of livestock using a communication terminal, and a server analyzes this data.

[0408] The user first launches the application using a mobile device and takes pictures or videos of livestock. The device receives the captured data and sends it to the server. This collects data that visualizes the current state of the livestock.

[0409] The server uses artificial intelligence to analyze received image and video data and assess the health of livestock. For example, if a dog is unwell, the server detects the condition of its eyes and movement patterns to determine if it may be showing signs of indigestion. Based on the analysis results, the server recommends the most suitable medical facility for the user's location and condition and generates information for making an appointment.

[0410] This system also centralizes information on veterinary clinics accessible to users and provides evaluation information on pet food and related products. This evaluation information is generated based on reviews from other users and expert opinions, and the server suggests the most suitable options.

[0411] For example, if a user notices their cat is lethargic, they can record a video of the cat's condition that same day and upload it to the server. The server immediately analyzes the video and sends a notification to the user's device stating, "Your cat may be dehydrated. We recommend checking its water supply, as temperatures have been high recently." In this way, the system analyzes pet health information in real time and helps provide optimal care.

[0412] This invention allows users to monitor the health of their livestock in a timely manner and take prompt action as needed. It also significantly reduces the effort involved in selecting appropriate pet food and caring for pets while traveling. The system comprehensively supports pet health management, providing peace of mind and convenience to livestock owners.

[0413] The following describes the processing flow.

[0414] Step 1:

[0415] The user launches the application on their mobile device and takes pictures or videos of livestock. Once the user has finished preparing the data, they perform an upload operation to send it to the server through the application.

[0416] Step 2:

[0417] The terminal receives image or video data from the user and performs preprocessing. Preprocessing includes compressing the data size and converting the format to prepare the data for efficient transfer.

[0418] Step 3:

[0419] The terminal sends the pre-processed data to the server. The transmitted data is transferred using a communication protocol that ensures it reaches the server securely and efficiently.

[0420] Step 4:

[0421] The server feeds the received image or video data into an artificial intelligence system for analysis. The AI ​​uses its configured algorithms to extract key features related to the health of livestock and detect abnormalities or signs that require attention.

[0422] Step 5:

[0423] Based on the analysis results, the server sends a notification to the user. The notification includes a health status assessment and, if necessary, an option to make an appointment at the nearest veterinary clinic. The server also generates information on recommended pet food and related products.

[0424] Step 6:

[0425] The device receives notifications and suggestions from the server and displays them to the user in a visually easy-to-understand format. Notifications include health advice, booking links, and product reviews.

[0426] Step 7:

[0427] The user selects the appropriate action based on the information displayed on the device. For example, if they want to make an appointment at a medical facility or purchase recommended pet food, they perform these actions on the device.

[0428] (Example 1)

[0429] 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."

[0430] When raising livestock, it is essential to quickly and accurately assess their health and provide necessary medical care and support. However, ordinary pet owners lack specialized knowledge and may overlook changes in their livestock's condition, and selecting appropriate medical facilities can also be difficult. Therefore, there is a growing demand for systems that automatically assess the health of livestock and suggest appropriate measures.

[0431] 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.

[0432] In this invention, the server includes a device for acquiring visual information data of livestock, a device for transmitting the visual information data to a central memory device, and a device for analyzing the visual information data using a generative intelligence model in the central memory device and evaluating the health status of the livestock. This enables pet owners to accurately understand the health status of their livestock, allowing for prompt action and selection of appropriate medical facilities.

[0433] "Livestock" refers to animals that are raised and managed by humans for agricultural or other purposes.

[0434] "Visual information data" refers to data expressed in image or video format, and includes information with visual elements.

[0435] "Device" refers to a machine or electronic device configured to achieve a specific function or purpose.

[0436] A "central memory device" refers to a memory device connected to a central control computer that is involved in the storage and processing of data.

[0437] A "generative intelligence model" refers to a model created using an artificial intelligence learning algorithm and trained to solve a specific problem.

[0438] "Analysis" refers to a series of processes for examining data in detail and understanding its structure and meaning.

[0439] A "veterinary clinic" refers to a medical facility established for the purpose of conducting health checkups and providing treatment for animals.

[0440] A "visit plan" refers to the process of planning the necessary steps and timing for visiting a specific facility or location.

[0441] "Related products" refer to goods and services related to the product in question.

[0442] "Opinion information" refers to information that includes evaluations and opinions about products and services.

[0443] This invention is implemented as a system for accurately assessing the health status of livestock and taking appropriate measures. The user begins by using a mobile device to capture images or videos of the livestock. The device securely transmits this visual information data to a server, which acts as a central storage device. Data transmission takes place over the internet and is protected by encryption technology.

[0444] The server uses generative AI models developed with machine learning frameworks such as TensorFlow to analyze the received data in detail. For example, it has implemented an image recognition algorithm to detect eye redness and abnormal movements in images of dogs. This allows the health status of livestock to be evaluated, and if an abnormality is detected, the server suggests the most suitable facility to the user based on information about veterinary clinics.

[0445] Users are notified of the analysis results and recommended actions via their mobile devices. For example, specific instructions such as, "Mild dehydration is observed. Please give water and let your pet rest in a cool place," are included. Information on the nearest veterinary clinic and reviews of pet food are also provided.

[0446] For example, a user can enter a prompt such as, "My dog's behavior is a little strange. Please use AI to analyze if there are any signs of indigestion," which will quickly perform a health check on the livestock and provide the user with necessary countermeasures. In this way, users can manage the health of their livestock in a timely and effective manner.

[0447] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0448] Step 1:

[0449] User behavior

[0450] The user launches a dedicated application on their mobile device and takes pictures of their livestock. The input is visual information data in the form of images or videos of the livestock. Specifically, when the user notices something unusual about their pet, they use the device to record what is happening at that time. The output is the storage of the visual information data on the device.

[0451] Step 2:

[0452] Device functions

[0453] The terminal receives captured visual information data and transfers it to a server via the internet. The input is the visual information data received from the user. Specifically, the terminal encrypts this data according to a security protocol and sends it to the server. The output is the encrypted visual information data sent to the server.

[0454] Step 3:

[0455] Server Processing

[0456] The server analyzes the received visual information data using a generating AI model. The input is visual information data sent from the terminal. Specifically, the server utilizes an AI model built using TensorFlow and applies an image recognition algorithm to evaluate the health status of livestock from the data. The output is the analysis result regarding the health status of the livestock.

[0457] Step 4:

[0458] Server's judgment and proposal

[0459] Based on the analysis results, the server selects an appropriate veterinary clinic based on the health status of the livestock and generates information to notify the user. The input is the analysis results. Specifically, the server retrieves the most suitable veterinary clinic from the database based on the location and urgency of the situation, and creates recommendation information including a visit plan. The output is notification information of the recommended veterinary clinic and specific countermeasures.

[0460] Step 5:

[0461] Notification to the user

[0462] The server sends the generated notification information to the user's mobile device. The input is the notification information sent from the server. Specifically, the user receives the analysis results and recommendations through their device and can check specific countermeasures and visit plans. The output is the analysis results and recommendations that the user receives and checks.

[0463] (Application Example 1)

[0464] 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."

[0465] Managing and monitoring the health of livestock and pets is an important, yet sometimes burdensome, task for pet owners. However, in the midst of busy lives, it is difficult to perform health checks at the appropriate time and to detect abnormalities early, and by the time an abnormality is noticed, the condition may already be serious. Therefore, there is a need for a system that can efficiently manage the health of livestock and pets on a daily basis and respond quickly when abnormalities occur.

[0466] 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.

[0467] In this invention, the server includes means for monitoring the behavior of livestock in real time and detecting abnormalities, means for notifying the user when such abnormalities are detected, and means for receiving the image or video data. This allows the user to monitor the health of livestock on a daily basis and to quickly obtain information and take countermeasures when abnormalities are detected.

[0468] "Means for receiving images or video data of livestock" refers to technology that allows users to acquire images or videos of their livestock or pets through a communication device.

[0469] "An artificial intelligence tool for analyzing the health status of livestock" refers to a function that uses AI technology to analyze and determine the health status of livestock and pets based on acquired image and video data.

[0470] "Methods for selecting recommended medical institutions" refers to the process of extracting and selecting appropriate medical facilities related to the health condition of livestock and pets.

[0471] "Means for generating reservation information" refers to a function that constructs the date, time, and other information for a visit to a selected medical institution, and confirms the reservation as needed.

[0472] "Means of providing evaluation information regarding livestock feed" refers to a function that provides users with reviews and recommendations regarding pet food and related products.

[0473] "Means for monitoring livestock behavior in real time and detecting abnormalities" refers to technology that tracks the daily behavior of livestock and pets in real time and immediately identifies any unusual behavior.

[0474] "Means of notifying users when an abnormality is detected" refers to a system that sends information to the user's communication terminal to warn them when abnormal behavior or changes in the health of livestock or pets are detected.

[0475] To implement this invention, the system is constructed by combining a household robot, a communication terminal, a cloud server, and other components. The household robot is equipped with a camera and monitors the behavior of livestock or pets in real time. The robot periodically takes pictures and videos of pets and uploads the data to the cloud server via the communication terminal.

[0476] The server is equipped with the ability to analyze collected data using artificial intelligence (AI). Specifically, it uses cloud services (e.g., AWS Rekognition) to analyze the health status and abnormal behavior of animals in images and videos. If an abnormality is detected, the server sends a push notification to a communication device (e.g., a smartphone) to promptly warn the user.

[0477] Furthermore, the server collects and provides user reviews and expert opinions on pet food and related products. This information is generated based on collected user reviews and expert opinions. Users can then use this information to make the best choices.

[0478] For example, if a user leaves their pet at home while on a long business trip, the robot will automatically patrol and monitor the pet's health. If the pet exhibits unusual behavior, such as refusing to eat, the server will immediately notify the user. This allows the user to take appropriate action even remotely.

[0479] Examples of prompts to input into the generating AI model include, "Design a system that monitors a pet's condition in real time and immediately notifies the user if an abnormality is detected." Through these prompts, the AI ​​can generate specific discussions and proposals aimed at system design.

[0480] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0481] Step 1:

[0482] The household robot captures images and videos of livestock and pets using its camera. The captured results are then transmitted as data to a communication terminal. The input is real-time footage of the pet, and the output is image and video data.

[0483] Step 2:

[0484] The communication terminal uploads received image and video data to a cloud server. The input is data transferred from the home robot, and the output is data sent to the cloud server.

[0485] Step 3:

[0486] The server analyzes data received on the cloud using artificial intelligence. This analysis uses, for example, AWS Rekognition to detect the health status and abnormal behavior of animals in images and videos. The input is image and video data on the cloud server, and the output is the analysis results regarding the pet's health status.

[0487] Step 4:

[0488] If the analysis results indicate an anomaly, the server sends a notification to the user's communication terminal. The input is the analysis result, and the output is the warning message sent to the user's communication terminal.

[0489] Step 5:

[0490] The user checks notifications received on their device and, if necessary, directly checks on their pet's condition or contacts a medical institution. The input is the notification displayed on the device, and the output is the action taken by the user to improve the situation.

[0491] Step 6:

[0492] The server collects review information on pet food and related products and presents the user with the best options. Based on this information, the user can select the appropriate product. The input is the review information stored on the server, and the output is a list of products available for the user to choose from.

[0493] 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.

[0494] This invention combines an emotion engine with a system that supports the health management of livestock raised by users, comprehensively understanding the condition of both the livestock and the user, and providing optimized care and information. This system is composed of multiple means and realizes functions that enhance user convenience.

[0495] First, the user launches the application using their device and takes pictures or videos of livestock. This is used as basic data for assessing their health. The device receives this data, processes it, and then sends it to the server in the most suitable format.

[0496] The server uses artificial intelligence (AI) to analyze the received image or video data. This AI analyzes features in the data to determine the health status of livestock and decide on necessary medical treatment. Based on the analysis results, it selects a medical facility recommended to the user and generates information for making an appointment. This information is optimized taking into account the user's location and the condition of the livestock.

[0497] Furthermore, the server is equipped with an emotion engine that can recognize the user's emotions. This engine analyzes the user's voice and text input sent from the terminal to identify their emotional state. By adjusting the content and interface of the information provided according to the emotional state, the server ensures that users receive information in a way that is easiest to understand and reduces stress.

[0498] For example, when a user is worried about their pet's health, this emotion engine senses the user's tension and anxiety and prioritizes providing reassuring information in simple language. Similarly, when it comes to things like vet appointments or food recommendations, it adapts to the user's needs, providing quick instructions if they're in a hurry, and offering detailed explanations if they have more time.

[0499] Thus, the present invention is a system that not only analyzes the health status of livestock with high accuracy and efficiently selects appropriate medical measures, but also provides information that is sensitive to the user's emotional state, thereby realizing a safe and comfortable experience for users who raise livestock.

[0500] The following describes the processing flow.

[0501] Step 1:

[0502] The user launches the application on their mobile device and takes pictures or videos of their livestock. The captured data is saved in the application as initial data for evaluating the health status of the animals.

[0503] Step 2:

[0504] The device receives the stored image or video data and adjusts its size and format. This includes data compression and format conversion. The processed data is then sent to the server.

[0505] Step 3:

[0506] The server receives data sent from the terminal and passes it to the artificial intelligence engine. The AI ​​engine analyzes the characteristics of livestock in images and videos and determines their health status. If an abnormality is detected as a result of the analysis, it makes predictions about specific diseases and symptoms.

[0507] Step 4:

[0508] Based on the analysis results, the server recommends the most suitable medical facility to the user. This includes selecting an appropriate facility based on the user's location and the condition of their livestock. If necessary, it generates appointment information for the medical facility and sends it to the user's device.

[0509] Step 5:

[0510] The terminal displays analysis results received from the server and information on medical institutions. Based on the presented information, the user selects appropriate measures for the livestock. Evaluation information on feed related to health status is also displayed simultaneously, allowing the user to consider their options.

[0511] Step 6:

[0512] An emotion engine is used by the server to analyze user input (voice and text). It recognizes the user's emotional state and adjusts the information accordingly. For example, if the user is feeling anxious, the information will be presented in a way that provides reassurance.

[0513] Step 7:

[0514] Users manage and care for their pets through content that is flexibly adjusted to their emotions. This reduces the psychological burden of taking the next steps, such as making appointments with veterinarians or purchasing products, and supports smooth decision-making.

[0515] (Example 2)

[0516] 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."

[0517] Traditional systems for managing animal health have struggled to accurately assess health conditions and have lacked the ability to provide information tailored to the user's emotional needs. As a result, users sometimes experienced difficulties in selecting and booking appropriate medical facilities, and may have felt unnecessary stress. There was a need to solve these problems and realize appropriate and reassuring health management for both animals and users.

[0518] 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.

[0519] In this invention, the server includes means for receiving images or video information of animals, intelligent processing means for evaluating the health status of animals from the information, and means for recognizing the user's emotional state and adjusting the content and format of the information provided. This makes it possible to accurately evaluate the health status of animals and provide optimal information that is sensitive to the user's emotions.

[0520] "Animals" refers to living creatures kept as livestock or pets, and these are the subjects whose health status is managed by this system.

[0521] "Image or video information" refers to photographic or video data used to visually record the condition of an animal.

[0522] "Intelligent processing means" refers to a system that uses artificial intelligence technology to analyze received image or video information and evaluate the health status of animals.

[0523] A "medical facility" refers to an organization such as a hospital or clinic that can provide medical treatment according to the health condition of an animal.

[0524] "Means for creating reservation information" refers to the function of generating information to ensure that animals receive medical treatment at selected medical facilities.

[0525] "Feed evaluation information" refers to information related to animal nutrition management, specifically data on recommended types and amounts of feed based on the animal's health condition.

[0526] "Means of recognizing emotional states" refers to a function that can analyze information entered by the user and identify that emotion.

[0527] "Means of adjusting the content and format of information" refers to a function that dynamically changes the type and presentation method of information provided based on the user's emotional state.

[0528] This invention is a system for evaluating the health status of animals and providing users with appropriate medical information and support. The user first uses a terminal to launch a dedicated application and capture images or video information of the animal. For this purpose, an electronic device with a camera function, such as a smartphone or tablet, is used.

[0529] The device processes the captured images and video information, converts them to the optimal format, and sends them to the server. This process includes software that performs data compression and format conversion.

[0530] The server receives the transmitted information and uses intelligent processing to evaluate the animal's health status. This evaluation utilizes a generative AI model powered by deep learning technology, which analyzes the animal's behavior and physical characteristics to determine its health status. It also recognizes the user's emotional state using voice and text input and provides information accordingly. An analysis program equipped with an emotion engine executes this process.

[0531] For example, if a user enters a prompt such as, "My dog ​​seems lethargic lately, so please check its health," the server will assess its health condition and provide information to reassure the user. It will also select the nearest appropriate medical facility and create an appointment if necessary.

[0532] This system allows users to continuously and accurately manage their animals' health, resulting in a less stressful pet-rearing experience.

[0533] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0534] Step 1:

[0535] The user uses a device to launch a dedicated application and capture images or videos of the animals they are keeping. During this process, the user must select the appropriate moment for the shot and focus the camera. The input is high-resolution image or video data acquired by the camera. The output is the captured image or video file.

[0536] Step 2:

[0537] The device receives the acquired image or video data and converts it to an appropriate format. This process involves image format conversion and data compression. The input is raw image data, and the output is a compressed data format (e.g., JPEG or MP4). Specifically, image processing software is used to reduce the size of the data.

[0538] Step 3:

[0539] The terminal sends the converted data to the server. The data is securely transferred over the internet. The input for this step is compressed image or video data, and the output is the data transferred to the server via a communication protocol. In particular, encryption protocols such as SSL are used to ensure the security of the data.

[0540] Step 4:

[0541] The server uses intelligent processing tools to analyze the received data. The input is image or video data that arrives at the server. The server analyzes this data using a generative AI model to determine the health status of the animals. The output is evaluation data indicating the health status. Specifically, a deep learning algorithm extracts features from the video and compares them with an existing health database.

[0542] Step 5:

[0543] The server uses an emotion engine to recognize the user's emotional state. Input is voice input or text data from the user. The server analyzes this data to identify the user's emotions. Output is the user's emotional status information. Emotion analysis software performs operations such as analyzing voice tone and keywords.

[0544] Step 6:

[0545] The server generates optimal information tailored to the animal's current condition based on analysis results and emotional information, and sends it to the user. This information includes the selection and booking of medical facilities. The input is the animal's health assessment and the user's emotional information, and the output is an informational message presented to the user. The server uses an information generation program to adaptively customize the information and provide it in the most easily understandable format for the user.

[0546] (Application Example 2)

[0547] 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."

[0548] The objective of this invention is to support livestock owners in providing effective care with peace of mind by analyzing the health status of livestock with high accuracy and providing information tailored to the user's emotions. Furthermore, it aims to provide support to pet shops and related facilities, enabling pet owners to easily manage their pets' health status and select appropriate products and services.

[0549] 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.

[0550] In this invention, the server includes means for receiving visual data of livestock, means for calculating the health status of the livestock from the data, and means for recognizing the emotional state of the user and adapting information accordingly. This enables accurate analysis of the health status of livestock and the provision of optimal information tailored to the user's emotions.

[0551] "Visual data of livestock" refers to digital information obtained as images or videos of livestock.

[0552] "Analytical computational means" refers to computational techniques used to evaluate the health status of livestock from acquired visual data.

[0553] A "recommended medical facility" is a place that provides medical services appropriate to the health of livestock based on the analysis results.

[0554] "Means for generating reservation information" refers to technology that has the function of determining the date and time of visit to the selected medical facility and preparing the necessary information.

[0555] "Means of providing nutritional information" refers to technologies that have the function of generating advice and recommendations useful for the nutritional management of livestock.

[0556] "Means for recognizing a user's emotional state" refers to technologies that analyze user voice and text data to identify their emotions.

[0557] "Means of adjusting the priority and content of information" refers to technologies that change the importance and content of the information provided based on the perceived emotional state.

[0558] A "user computing device" is a terminal that includes computer technology for users to receive information and interact with it.

[0559] The system for implementing this invention consists of a user's computing device, a communication network, and a server. First, the user's terminal is used to acquire image or video data of livestock. The user captures the data through a dedicated application and sends the data from the terminal to the server. This application is built using a platform such as "React Native".

[0560] The server analyzes the received visual data using AI frameworks such as TensorFlow or PyTorch. This analysis is a process that uses features derived from the visual data to determine the health status of livestock. The server also uses IBM Watson and Google Cloud Natural Language API to recognize the user's emotional state through voice and text input. This makes it possible to adjust the priority and content of information according to the user's emotions and provide the most relevant information.

[0561] The main value this system provides is the ability to accurately assess the health status of livestock and automate the selection and booking of recommended medical facilities based on that assessment. Furthermore, it provides information and advice in a stress-reducing manner based on the user's emotional state, creating an environment where pet owners can manage their livestock's health with peace of mind.

[0562] As a concrete example, there was a case where a customer visiting a pet shop checked their dog's health status using an app and noticed weight gain. In this situation, the emotional engine displayed advice to alleviate the owner's anxiety and recommended products suitable for weight management, thereby improving customer satisfaction.

[0563] An example of a prompt using a generative AI model is: "Consider how you can provide reassuring advice based on the feelings of a pet owner who is concerned about their dog's health."

[0564] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0565] Step 1:

[0566] The user launches a smartphone application and takes an image or video of livestock. This data is input to the device as visual information and prepared to be sent directly to the server. Data processing involves format conversion and compression of the visual data.

[0567] Step 2:

[0568] The server receives visual data sent from the terminal. The server uses TensorFlow or PyTorch to extract features from the visual data and perform data calculations to determine the health status of livestock. The output is the health check results.

[0569] Step 3:

[0570] The server identifies recommended medical facilities based on the diagnostic results. In this process, data processing is performed on the input information (diagnosis results), taking into account geographical information and the expertise of the facilities, and a list of medical facilities is output.

[0571] Step 4:

[0572] Based on the selection of a medical facility, the server generates reservation information. Using input data such as the user's current location, the server automatically sets the optimal reservation date and time, and outputs the reservation information.

[0573] Step 5:

[0574] Voice and text data entered by the user through the application are sent to the server for sentiment analysis. The server uses "IBM Watson" or "Google Cloud Natural Language API" to analyze the emotional state and prepare to provide information tailored to the user's situation.

[0575] Step 6:

[0576] The server adjusts the priority and content of information provided based on the sentiment analysis results, and the final information is output and displayed on the user's terminal. This adjustment includes information optimization operations that correspond to the input of the user's emotional state.

[0577] 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.

[0578] 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.

[0579] 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.

[0580] [Fourth Embodiment]

[0581] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0582] 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.

[0583] 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).

[0584] 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.

[0585] 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.

[0586] 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).

[0587] 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.

[0588] 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.

[0589] 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.

[0590] 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.

[0591] 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.

[0592] 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.

[0593] 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".

[0594] This invention is a system for accurately managing the health status of livestock raised by users and promptly providing necessary care. This system collects data by taking and uploading images or videos of livestock using a communication terminal, and a server analyzes this data.

[0595] The user first launches the application using a mobile device and takes pictures or videos of livestock. The device receives the captured data and sends it to the server. This collects data that visualizes the current state of the livestock.

[0596] The server uses artificial intelligence to analyze received image and video data and assess the health of livestock. For example, if a dog is unwell, the server detects the condition of its eyes and movement patterns to determine if it may be showing signs of indigestion. Based on the analysis results, the server recommends the most suitable medical facility for the user's location and condition and generates information for making an appointment.

[0597] This system also centralizes information on veterinary clinics accessible to users and provides evaluation information on pet food and related products. This evaluation information is generated based on reviews from other users and expert opinions, and the server suggests the most suitable options.

[0598] For example, if a user notices their cat is lethargic, they can record a video of the cat's condition that same day and upload it to the server. The server immediately analyzes the video and sends a notification to the user's device stating, "Your cat may be dehydrated. We recommend checking its water supply, as temperatures have been high recently." In this way, the system analyzes pet health information in real time and helps provide optimal care.

[0599] This invention allows users to monitor the health of their livestock in a timely manner and take prompt action as needed. It also significantly reduces the effort involved in selecting appropriate pet food and caring for pets while traveling. The system comprehensively supports pet health management, providing peace of mind and convenience to livestock owners.

[0600] The following describes the processing flow.

[0601] Step 1:

[0602] The user launches the application on their mobile device and takes pictures or videos of livestock. Once the user has finished preparing the data, they perform an upload operation to send it to the server through the application.

[0603] Step 2:

[0604] The terminal receives image or video data from the user and performs preprocessing. Preprocessing includes compressing the data size and converting the format to prepare the data for efficient transfer.

[0605] Step 3:

[0606] The terminal sends the pre-processed data to the server. The transmitted data is transferred using a communication protocol that ensures it reaches the server securely and efficiently.

[0607] Step 4:

[0608] The server feeds the received image or video data into an artificial intelligence system for analysis. The AI ​​uses its configured algorithms to extract key features related to the health of livestock and detect abnormalities or signs that require attention.

[0609] Step 5:

[0610] Based on the analysis results, the server sends a notification to the user. The notification includes a health status assessment and, if necessary, an option to make an appointment at the nearest veterinary clinic. The server also generates information on recommended pet food and related products.

[0611] Step 6:

[0612] The device receives notifications and suggestions from the server and displays them to the user in a visually easy-to-understand format. Notifications include health advice, booking links, and product reviews.

[0613] Step 7:

[0614] The user selects the appropriate action based on the information displayed on the device. For example, if they want to make an appointment at a medical facility or purchase recommended pet food, they perform these actions on the device.

[0615] (Example 1)

[0616] 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".

[0617] When raising livestock, it is essential to quickly and accurately assess their health and provide necessary medical care and support. However, ordinary pet owners lack specialized knowledge and may overlook changes in their livestock's condition, and selecting appropriate medical facilities can also be difficult. Therefore, there is a growing demand for systems that automatically assess the health of livestock and suggest appropriate measures.

[0618] 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.

[0619] In this invention, the server includes a device for acquiring visual information data of livestock, a device for transmitting the visual information data to a central memory device, and a device for analyzing the visual information data using a generative intelligence model in the central memory device and evaluating the health status of the livestock. This enables pet owners to accurately understand the health status of their livestock, allowing for prompt action and selection of appropriate medical facilities.

[0620] "Livestock" refers to animals that are raised and managed by humans for agricultural or other purposes.

[0621] "Visual information data" refers to data expressed in image or video format, and includes information with visual elements.

[0622] "Device" refers to a machine or electronic device configured to achieve a specific function or purpose.

[0623] A "central memory device" refers to a memory device connected to a central control computer that is involved in the storage and processing of data.

[0624] A "generative intelligence model" refers to a model created using an artificial intelligence learning algorithm and trained to solve a specific problem.

[0625] "Analysis" refers to a series of processes for examining data in detail and understanding its structure and meaning.

[0626] A "veterinary clinic" refers to a medical facility established for the purpose of conducting health checkups and providing treatment for animals.

[0627] A "visit plan" refers to the process of planning the necessary steps and timing for visiting a specific facility or location.

[0628] "Related products" refer to goods and services related to the product in question.

[0629] "Opinion information" refers to information that includes evaluations and opinions about products and services.

[0630] This invention is implemented as a system for accurately assessing the health status of livestock and taking appropriate measures. The user begins by using a mobile device to capture images or videos of the livestock. The device securely transmits this visual information data to a server, which acts as a central storage device. Data transmission takes place over the internet and is protected by encryption technology.

[0631] The server uses generative AI models developed with machine learning frameworks such as TensorFlow to analyze the received data in detail. For example, it has implemented an image recognition algorithm to detect eye redness and abnormal movements in images of dogs. This allows the health status of livestock to be evaluated, and if an abnormality is detected, the server suggests the most suitable facility to the user based on information about veterinary clinics.

[0632] Users are notified of the analysis results and recommended actions via their mobile devices. For example, specific instructions such as, "Mild dehydration is observed. Please give water and let your pet rest in a cool place," are included. Information on the nearest veterinary clinic and reviews of pet food are also provided.

[0633] For example, a user can enter a prompt such as, "My dog's behavior is a little strange. Please use AI to analyze if there are any signs of indigestion," which will quickly perform a health check on the livestock and provide the user with necessary countermeasures. In this way, users can manage the health of their livestock in a timely and effective manner.

[0634] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0635] Step 1:

[0636] User behavior

[0637] The user launches a dedicated application on their mobile device and takes pictures of their livestock. The input is visual information data in the form of images or videos of the livestock. Specifically, when the user notices something unusual about their pet, they use the device to record what is happening at that time. The output is the storage of the visual information data on the device.

[0638] Step 2:

[0639] Device functions

[0640] The terminal receives captured visual information data and transfers it to a server via the internet. The input is the visual information data received from the user. Specifically, the terminal encrypts this data according to a security protocol and sends it to the server. The output is the encrypted visual information data sent to the server.

[0641] Step 3:

[0642] Server Processing

[0643] The server analyzes the received visual information data using a generating AI model. The input is visual information data sent from the terminal. Specifically, the server utilizes an AI model built using TensorFlow and applies an image recognition algorithm to evaluate the health status of livestock from the data. The output is the analysis result regarding the health status of the livestock.

[0644] Step 4:

[0645] Server's judgment and proposal

[0646] Based on the analysis results, the server selects an appropriate veterinary clinic based on the health status of the livestock and generates information to notify the user. The input is the analysis results. Specifically, the server retrieves the most suitable veterinary clinic from the database based on the location and urgency of the situation, and creates recommendation information including a visit plan. The output is notification information of the recommended veterinary clinic and specific countermeasures.

[0647] Step 5:

[0648] Notification to the user

[0649] The server sends the generated notification information to the user's mobile device. The input is the notification information sent from the server. Specifically, the user receives the analysis results and recommendations through their device and can check specific countermeasures and visit plans. The output is the analysis results and recommendations that the user receives and checks.

[0650] (Application Example 1)

[0651] 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".

[0652] Managing and monitoring the health of livestock and pets is an important, yet sometimes burdensome, task for pet owners. However, in the midst of busy lives, it is difficult to perform health checks at the appropriate time and to detect abnormalities early, and by the time an abnormality is noticed, the condition may already be serious. Therefore, there is a need for a system that can efficiently manage the health of livestock and pets on a daily basis and respond quickly when abnormalities occur.

[0653] 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.

[0654] In this invention, the server includes means for monitoring the behavior of livestock in real time and detecting abnormalities, means for notifying the user when such abnormalities are detected, and means for receiving the image or video data. This allows the user to monitor the health of livestock on a daily basis and to quickly obtain information and take countermeasures when abnormalities are detected.

[0655] "Means for receiving images or video data of livestock" refers to technology that allows users to acquire images or videos of their livestock or pets through a communication device.

[0656] "An artificial intelligence tool for analyzing the health status of livestock" refers to a function that uses AI technology to analyze and determine the health status of livestock and pets based on acquired image and video data.

[0657] "Methods for selecting recommended medical institutions" refers to the process of extracting and selecting appropriate medical facilities related to the health condition of livestock and pets.

[0658] "Means for generating reservation information" refers to a function that constructs the date, time, and other information for a visit to a selected medical institution, and confirms the reservation as needed.

[0659] "Means of providing evaluation information regarding livestock feed" refers to a function that provides users with reviews and recommendations regarding pet food and related products.

[0660] "Means for monitoring livestock behavior in real time and detecting abnormalities" refers to technology that tracks the daily behavior of livestock and pets in real time and immediately identifies any unusual behavior.

[0661] "Means of notifying users when an abnormality is detected" refers to a system that sends information to the user's communication terminal to warn them when abnormal behavior or changes in the health of livestock or pets are detected.

[0662] To implement this invention, the system is constructed by combining a household robot, a communication terminal, a cloud server, and other components. The household robot is equipped with a camera and monitors the behavior of livestock or pets in real time. The robot periodically takes pictures and videos of pets and uploads the data to the cloud server via the communication terminal.

[0663] The server is equipped with the ability to analyze collected data using artificial intelligence (AI). Specifically, it uses cloud services (e.g., AWS Rekognition) to analyze the health status and abnormal behavior of animals in images and videos. If an abnormality is detected, the server sends a push notification to a communication device (e.g., a smartphone) to promptly warn the user.

[0664] Furthermore, the server collects and provides user reviews and expert opinions on pet food and related products. This information is generated based on collected user reviews and expert opinions. Users can then use this information to make the best choices.

[0665] For example, if a user leaves their pet at home while on a long business trip, the robot will automatically patrol and monitor the pet's health. If the pet exhibits unusual behavior, such as refusing to eat, the server will immediately notify the user. This allows the user to take appropriate action even remotely.

[0666] Examples of prompts to input into the generating AI model include, "Design a system that monitors a pet's condition in real time and immediately notifies the user if an abnormality is detected." Through these prompts, the AI ​​can generate specific discussions and proposals aimed at system design.

[0667] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0668] Step 1:

[0669] The household robot captures images and videos of livestock and pets using its camera. The captured results are then transmitted as data to a communication terminal. The input is real-time footage of the pet, and the output is image and video data.

[0670] Step 2:

[0671] The communication terminal uploads received image and video data to a cloud server. The input is data transferred from the home robot, and the output is data sent to the cloud server.

[0672] Step 3:

[0673] The server analyzes data received on the cloud using artificial intelligence. This analysis uses, for example, AWS Rekognition to detect the health status and abnormal behavior of animals in images and videos. The input is image and video data on the cloud server, and the output is the analysis results regarding the pet's health status.

[0674] Step 4:

[0675] If the analysis results indicate an anomaly, the server sends a notification to the user's communication terminal. The input is the analysis result, and the output is the warning message sent to the user's communication terminal.

[0676] Step 5:

[0677] The user checks notifications received on their device and, if necessary, directly checks on their pet's condition or contacts a medical institution. The input is the notification displayed on the device, and the output is the action taken by the user to improve the situation.

[0678] Step 6:

[0679] The server collects review information on pet food and related products and presents the user with the best options. Based on this information, the user can select the appropriate product. The input is the review information stored on the server, and the output is a list of products available for the user to choose from.

[0680] 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.

[0681] This invention combines an emotion engine with a system that supports the health management of livestock raised by users, comprehensively understanding the condition of both the livestock and the user, and providing optimized care and information. This system is composed of multiple means and realizes functions that enhance user convenience.

[0682] First, the user launches the application using their device and takes pictures or videos of livestock. This is used as basic data for assessing their health. The device receives this data, processes it, and then sends it to the server in the most suitable format.

[0683] The server uses artificial intelligence (AI) to analyze the received image or video data. This AI analyzes features in the data to determine the health status of livestock and decide on necessary medical treatment. Based on the analysis results, it selects a medical facility recommended to the user and generates information for making an appointment. This information is optimized taking into account the user's location and the condition of the livestock.

[0684] Furthermore, the server is equipped with an emotion engine that can recognize the user's emotions. This engine analyzes the user's voice and text input sent from the terminal to identify their emotional state. By adjusting the content and interface of the information provided according to the emotional state, the server ensures that users receive information in a way that is easiest to understand and reduces stress.

[0685] For example, when a user is worried about their pet's health, this emotion engine senses the user's tension and anxiety and prioritizes providing reassuring information in simple language. Similarly, when it comes to things like vet appointments or food recommendations, it adapts to the user's needs, providing quick instructions if they're in a hurry, and offering detailed explanations if they have more time.

[0686] Thus, the present invention is a system that not only analyzes the health status of livestock with high accuracy and efficiently selects appropriate medical measures, but also provides information that is sensitive to the user's emotional state, thereby realizing a safe and comfortable experience for users who raise livestock.

[0687] The following describes the processing flow.

[0688] Step 1:

[0689] The user launches the application on their mobile device and takes pictures or videos of their livestock. The captured data is saved in the application as initial data for evaluating the health status of the animals.

[0690] Step 2:

[0691] The device receives the stored image or video data and adjusts its size and format. This includes data compression and format conversion. The processed data is then sent to the server.

[0692] Step 3:

[0693] The server receives data sent from the terminal and passes it to the artificial intelligence engine. The AI ​​engine analyzes the characteristics of livestock in images and videos and determines their health status. If an abnormality is detected as a result of the analysis, it makes predictions about specific diseases and symptoms.

[0694] Step 4:

[0695] Based on the analysis results, the server recommends the most suitable medical facility to the user. This includes selecting an appropriate facility based on the user's location and the condition of their livestock. If necessary, it generates appointment information for the medical facility and sends it to the user's device.

[0696] Step 5:

[0697] The terminal displays analysis results received from the server and information on medical institutions. Based on the presented information, the user selects appropriate measures for the livestock. Evaluation information on feed related to health status is also displayed simultaneously, allowing the user to consider their options.

[0698] Step 6:

[0699] An emotion engine is used by the server to analyze user input (voice and text). It recognizes the user's emotional state and adjusts the information accordingly. For example, if the user is feeling anxious, the information will be presented in a way that provides reassurance.

[0700] Step 7:

[0701] Users manage and care for their pets through content that is flexibly adjusted to their emotions. This reduces the psychological burden of taking the next steps, such as making appointments with veterinarians or purchasing products, and supports smooth decision-making.

[0702] (Example 2)

[0703] 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".

[0704] Traditional systems for managing animal health have struggled to accurately assess health conditions and have lacked the ability to provide information tailored to the user's emotional needs. As a result, users sometimes experienced difficulties in selecting and booking appropriate medical facilities, and may have felt unnecessary stress. There was a need to solve these problems and realize appropriate and reassuring health management for both animals and users.

[0705] 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.

[0706] In this invention, the server includes means for receiving images or video information of animals, intelligent processing means for evaluating the health status of animals from the information, and means for recognizing the user's emotional state and adjusting the content and format of the information provided. This makes it possible to accurately evaluate the health status of animals and provide optimal information that is sensitive to the user's emotions.

[0707] "Animals" refers to living creatures kept as livestock or pets, and these are the subjects whose health status is managed by this system.

[0708] "Image or video information" refers to photographic or video data used to visually record the condition of an animal.

[0709] "Intelligent processing means" refers to a system that uses artificial intelligence technology to analyze received image or video information and evaluate the health status of animals.

[0710] A "medical facility" refers to an organization such as a hospital or clinic that can provide medical treatment according to the health condition of an animal.

[0711] "Means for creating reservation information" refers to the function of generating information to ensure that animals receive medical treatment at selected medical facilities.

[0712] "Feed evaluation information" refers to information related to animal nutrition management, specifically data on recommended types and amounts of feed based on the animal's health condition.

[0713] "Means of recognizing emotional states" refers to a function that can analyze information entered by the user and identify that emotion.

[0714] "Means of adjusting the content and format of information" refers to a function that dynamically changes the type and presentation method of information provided based on the user's emotional state.

[0715] This invention is a system for evaluating the health status of animals and providing users with appropriate medical information and support. The user first uses a terminal to launch a dedicated application and capture images or video information of the animal. For this purpose, an electronic device with a camera function, such as a smartphone or tablet, is used.

[0716] The device processes the captured images and video information, converts them to the optimal format, and sends them to the server. This process includes software that performs data compression and format conversion.

[0717] The server receives the transmitted information and uses intelligent processing to evaluate the animal's health status. This evaluation utilizes a generative AI model powered by deep learning technology, which analyzes the animal's behavior and physical characteristics to determine its health status. It also recognizes the user's emotional state using voice and text input and provides information accordingly. An analysis program equipped with an emotion engine executes this process.

[0718] For example, if a user enters a prompt such as, "My dog ​​seems lethargic lately, so please check its health," the server will assess its health condition and provide information to reassure the user. It will also select the nearest appropriate medical facility and create an appointment if necessary.

[0719] This system allows users to continuously and accurately manage their animals' health, resulting in a less stressful pet-rearing experience.

[0720] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0721] Step 1:

[0722] The user uses a device to launch a dedicated application and capture images or videos of the animals they are keeping. During this process, the user must select the appropriate moment for the shot and focus the camera. The input is high-resolution image or video data acquired by the camera. The output is the captured image or video file.

[0723] Step 2:

[0724] The device receives the acquired image or video data and converts it to an appropriate format. This process involves image format conversion and data compression. The input is raw image data, and the output is a compressed data format (e.g., JPEG or MP4). Specifically, image processing software is used to reduce the size of the data.

[0725] Step 3:

[0726] The terminal sends the converted data to the server. The data is securely transferred over the internet. The input for this step is compressed image or video data, and the output is the data transferred to the server via a communication protocol. In particular, encryption protocols such as SSL are used to ensure the security of the data.

[0727] Step 4:

[0728] The server uses intelligent processing tools to analyze the received data. The input is image or video data that arrives at the server. The server analyzes this data using a generative AI model to determine the health status of the animals. The output is evaluation data indicating the health status. Specifically, a deep learning algorithm extracts features from the video and compares them with an existing health database.

[0729] Step 5:

[0730] The server uses an emotion engine to recognize the user's emotional state. Input is voice input or text data from the user. The server analyzes this data to identify the user's emotions. Output is the user's emotional status information. Emotion analysis software performs operations such as analyzing voice tone and keywords.

[0731] Step 6:

[0732] The server generates optimal information tailored to the animal's current condition based on analysis results and emotional information, and sends it to the user. This information includes the selection and booking of medical facilities. The input is the animal's health assessment and the user's emotional information, and the output is an informational message presented to the user. The server uses an information generation program to adaptively customize the information and provide it in the most easily understandable format for the user.

[0733] (Application Example 2)

[0734] 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".

[0735] The objective of this invention is to support livestock owners in providing effective care with peace of mind by analyzing the health status of livestock with high accuracy and providing information tailored to the user's emotions. Furthermore, it aims to provide support to pet shops and related facilities, enabling pet owners to easily manage their pets' health status and select appropriate products and services.

[0736] 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.

[0737] In this invention, the server includes means for receiving visual data of livestock, means for calculating the health status of the livestock from the data, and means for recognizing the emotional state of the user and adapting information accordingly. This enables accurate analysis of the health status of livestock and the provision of optimal information tailored to the user's emotions.

[0738] "Visual data of livestock" refers to digital information obtained as images or videos of livestock.

[0739] "Analytical computational means" refers to computational techniques used to evaluate the health status of livestock from acquired visual data.

[0740] A "recommended medical facility" is a place that provides medical services appropriate to the health of livestock based on the analysis results.

[0741] "Means for generating reservation information" refers to technology that has the function of determining the date and time of visit to the selected medical facility and preparing the necessary information.

[0742] "Means of providing nutritional information" refers to technologies that have the function of generating advice and recommendations useful for the nutritional management of livestock.

[0743] "Means for recognizing a user's emotional state" refers to technologies that analyze user voice and text data to identify their emotions.

[0744] "Means of adjusting the priority and content of information" refers to technologies that change the importance and content of the information provided based on the perceived emotional state.

[0745] A "user computing device" is a terminal that includes computer technology for users to receive information and interact with it.

[0746] The system for implementing this invention consists of a user's computing device, a communication network, and a server. First, the user's terminal is used to acquire image or video data of livestock. The user captures the data through a dedicated application and sends the data from the terminal to the server. This application is built using a platform such as "React Native".

[0747] The server analyzes the received visual data using AI frameworks such as TensorFlow or PyTorch. This analysis is a process that uses features derived from the visual data to determine the health status of livestock. The server also uses IBM Watson and Google Cloud Natural Language API to recognize the user's emotional state through voice and text input. This makes it possible to adjust the priority and content of information according to the user's emotions and provide the most relevant information.

[0748] The main value this system provides is the ability to accurately assess the health status of livestock and automate the selection and booking of recommended medical facilities based on that assessment. Furthermore, it provides information and advice in a stress-reducing manner based on the user's emotional state, creating an environment where pet owners can manage their livestock's health with peace of mind.

[0749] As a concrete example, there was a case where a customer visiting a pet shop checked their dog's health status using an app and noticed weight gain. In this situation, the emotional engine displayed advice to alleviate the owner's anxiety and recommended products suitable for weight management, thereby improving customer satisfaction.

[0750] An example of a prompt using a generative AI model is: "Consider how you can provide reassuring advice based on the feelings of a pet owner who is concerned about their dog's health."

[0751] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0752] Step 1:

[0753] The user launches a smartphone application and takes an image or video of livestock. This data is input to the device as visual information and prepared to be sent directly to the server. Data processing involves format conversion and compression of the visual data.

[0754] Step 2:

[0755] The server receives visual data sent from the terminal. The server uses TensorFlow or PyTorch to extract features from the visual data and perform data calculations to determine the health status of livestock. The output is the health check results.

[0756] Step 3:

[0757] The server identifies recommended medical facilities based on the diagnostic results. In this process, data processing is performed on the input information (diagnosis results), taking into account geographical information and the expertise of the facilities, and a list of medical facilities is output.

[0758] Step 4:

[0759] Based on the selection of a medical facility, the server generates reservation information. Using input data such as the user's current location, the server automatically sets the optimal reservation date and time, and outputs the reservation information.

[0760] Step 5:

[0761] Voice and text data entered by the user through the application are sent to the server for sentiment analysis. The server uses "IBM Watson" or "Google Cloud Natural Language API" to analyze the emotional state and prepare to provide information tailored to the user's situation.

[0762] Step 6:

[0763] The server adjusts the priority and content of information provided based on the sentiment analysis results, and the final information is output and displayed on the user's terminal. This adjustment includes information optimization operations that correspond to the input of the user's emotional state.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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."

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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.

[0783] 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.

[0784] 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.

[0785] The following is further disclosed regarding the embodiments described above.

[0786] (Claim 1)

[0787] Means for receiving images or video data of livestock,

[0788] An artificial intelligence means for analyzing the health status of livestock from the aforementioned data,

[0789] A means of selecting a medical institution recommended based on the aforementioned health condition,

[0790] A means for generating reservation information for the aforementioned medical institution,

[0791] A means for providing evaluation information regarding the feed of the aforementioned livestock,

[0792] A system that includes this.

[0793] (Claim 2)

[0794] The system according to claim 1, further comprising means for converting the aforementioned image or video data into an optimal format.

[0795] (Claim 3)

[0796] The system according to claim 1, further comprising means for transmitting the analysis results to a user terminal.

[0797] "Example 1"

[0798] (Claim 1)

[0799] A device for acquiring visual information data of livestock,

[0800] A device for transmitting the aforementioned visual information data to a central memory device,

[0801] A device that analyzes the visual information data using a generative intelligence model in the central memory device and evaluates the health status of livestock,

[0802] A device that identifies and notifies appropriate medical facilities based on analysis results,

[0803] A device for planning visits to the aforementioned medical facilities,

[0804] A device for supplying opinion information on other related products,

[0805] A system that includes this.

[0806] (Claim 2)

[0807] The system according to claim 1, further comprising a device for converting the aforementioned visual information data into a standardized format.

[0808] (Claim 3)

[0809] The system according to claim 1, further comprising a device for transmitting the evaluation results to a user information device.

[0810] "Application Example 1"

[0811] (Claim 1)

[0812] Means for receiving images or video data of livestock,

[0813] An artificial intelligence means for analyzing the health status of livestock from the aforementioned data,

[0814] A means of selecting a medical institution recommended based on the aforementioned health condition,

[0815] A means for generating reservation information for the aforementioned medical institution,

[0816] A means for providing evaluation information regarding the feed of the aforementioned livestock,

[0817] A means for monitoring the behavior of the aforementioned livestock in real time and detecting abnormalities,

[0818] A means for notifying the user when the aforementioned abnormality is detected,

[0819] A system that includes this.

[0820] (Claim 2)

[0821] The system according to claim 1, further comprising means for converting the aforementioned image or video data into an optimal format.

[0822] (Claim 3)

[0823] The system according to claim 1, further comprising means for transmitting the analysis results and information regarding anomaly detection to a user terminal.

[0824] "Example 2 of combining an emotion engine"

[0825] (Claim 1)

[0826] Means for receiving images or video information of animals,

[0827] An intelligent processing means for evaluating the health status of an animal from the aforementioned information,

[0828] A means for selecting an appropriate medical facility based on the aforementioned health condition,

[0829] A means for creating reservation information for the aforementioned medical facility,

[0830] Means for providing evaluation information regarding the feed for the aforementioned animals,

[0831] A means of recognizing the user's emotional state and adjusting the content and format of the information provided,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, further comprising means for converting the aforementioned image or video information into an optimal format.

[0835] (Claim 3)

[0836] The system according to claim 1, further comprising means for transmitting the evaluation results to a user device.

[0837] "Application example 2 when combining with an emotional engine"

[0838] (Claim 1)

[0839] A means for receiving visual data of livestock,

[0840] A calculation means for analyzing the health status of livestock from the aforementioned data,

[0841] A means of selecting a medical facility recommended based on the aforementioned health condition,

[0842] Means for generating reservation information for the aforementioned medical facility,

[0843] A means for providing information regarding the nutrition of the aforementioned livestock,

[0844] A means of recognizing the user's emotional state and adapting information accordingly,

[0845] A means of adjusting the priority and content of information based on the aforementioned emotional state,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, further comprising means for converting the aforementioned visual data into an optimal format.

[0849] (Claim 3)

[0850] The system according to claim 1, further comprising means for transmitting the analysis results and adjusted information to a user computing device. [Explanation of Symbols]

[0851] 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. Means for receiving images or video data of livestock, An artificial intelligence means for analyzing the health status of livestock from the aforementioned data, A means of selecting a medical institution recommended based on the aforementioned health condition, A means for generating reservation information for the aforementioned medical institution, A means for providing evaluation information regarding the feed of the aforementioned livestock, A system that includes this.

2. The system according to claim 1, further comprising means for converting the aforementioned image or video data into an optimal format.

3. The system according to claim 1, further comprising means for transmitting the analysis results to a user terminal.

Images