system

Abstract

Provide a system. A user interface means for inputting symptoms of a pet; a communication means for transmitting the input symptom data to a server; data analysis means for analyzing the received symptom data and generating an appropriate first aid procedure; visualization means for displaying the generated first aid procedures in visual or video format; A hospital search tool to search for and provide information on veterinary hospitals that specialize in specific symptoms, A preventive information provider that regularly provides information on pet disease prevention and early detection; A system including:

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Pet owners often find themselves unsure of what to do when their pets suddenly become injured or unwell. Not knowing the appropriate first aid procedures in an emergency can put their pet's condition at risk of worsening. It's also difficult to quickly find a veterinary clinic that can provide specialized care. Lack of knowledge about early detection and prevention of disease is also a problem. There's a need to provide a system that can solve these issues and allow pet owners to respond quickly with reliable knowledge and information. [Means for solving the problem]

[0005] The present invention provides a system including a user interface means for inputting symptoms of a pet, a communication means for transmitting the input symptom data to a server, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a visualization means for displaying the generated first aid method in a visual or video format, a hospital search means for searching for and providing information on veterinary hospitals specializing in the symptoms, and a prevention information provision means for periodically providing information on the prevention and early detection of pet diseases, thereby realizing a system that enables pet owners to provide prompt and accurate first aid and, if necessary, obtain information to seek professional treatment.

[0006] "Symptoms of a pet" refers to the specific state of illness or injury that a pet exhibits.

[0007] "User interface means" refers to means having an interactive function for a user to input or obtain information.

[0008] "Communication means" refers to means having the function of transmitting and receiving data between a terminal and a server.

[0009] A "server" refers to a computer system that analyzes and stores data and provides specific services.

[0010] "Data analysis means" refers to means having an algorithm for predicting an appropriate treatment method or disease name based on input information.

[0011] "First aid measures" refer to temporary measures that should be taken to improve or stabilize your pet's condition.

[0012] "Visualization means" refers to a means for displaying information in a form that is easy for the user to understand.

[0013] "Hospital search means" refers to a means having a function for searching for specialized medical facilities corresponding to specific symptoms or disease names.

[0014] "Preventive information providing means" refers to a means that has the function of providing information to maintain the health of pets and prevent the occurrence of diseases.

[0015] "Location information" refers to data for identifying the current location of the user.

[0016] "Visual or animated format" refers to the use of graphics or animation to present information.

[0017] "Veterinary hospital" refers to a medical facility that provides medical services for small animals.

[0018] "User" refers to a pet owner who uses this system.

[0019] "Periodic provision" refers to notifying or delivering information to a user at regular intervals. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0025] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0026] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 1, a 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.

[0031] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0033] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0034] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0038] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] overview

[0042] This invention is an AI system that allows pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. The system includes a user interface for inputting the pet's symptoms, a communication means for transmitting symptom data to a server, a data analysis means, a visualization means, a hospital search means, and a preventive information provision means. Based on the symptoms input by the user, the server provides appropriate first aid procedures and specialized treatment information.

[0043] Program processing

[0044] The program of this system processes as follows:

[0045] 1. User Interface Methods

[0046] The user accesses a terminal and is provided with text boxes and options to input their pet's specific symptoms. The user enters the symptoms in detail and clicks the "Submit" button.

[0047] 2. Means of communication

[0048] The data sent by the user is converted to JSON format by the terminal and sent to the server, which improves data consistency and transmission efficiency.

[0049] 3. Data Analysis Methods

[0050] The server analyzes the received data and uses natural language processing (NLP) to extract keywords from the input text and compare them with a training database to predict the most relevant first aid method and disease name.

[0051] 4. Visualization tools

[0052] The resulting first aid procedures are then converted into visual or video formats. For example, a video can be created demonstrating how to apply a cold towel to an affected area. The video is then displayed on the device for easy user access.

[0053] 5. Hospital search tools

[0054] The server obtains the user's location information, searches for nearby veterinary clinics based on that location, and provides the user with a list of specialized medical facilities that can treat specific symptoms or illnesses.

[0055] 6. Preventive information provision measures

[0056] The server periodically provides information on pet health maintenance and early disease detection, including advice on how to prevent certain diseases and health management, which is displayed as notifications on the user's device.

[0057] Specific examples

[0058] Example 1: Skin rash

[0059] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes it and predicts that it is "allergic dermatitis." The server then instructs the user on how to treat the rash with a cold towel and recommends a nearby veterinary clinic that specializes in allergies. The system also provides visual instructions in a video and periodically notifies users of preventative care information.

[0060] Example 2: Difficulty breathing

[0061] The user enters, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It then provides a video of the appropriate first aid procedure. It also searches for the nearest veterinary hospital that can provide emergency care and directs the user to it.

[0062] In this way, this system can quickly provide appropriate first aid procedures and specialized medical information according to the pet's symptoms, allowing pet owners to care for their pets with peace of mind.In addition, by providing information on disease prevention and early detection, it can also contribute to maintaining pet health.

[0063] The processing flow will be explained below.

[0064] Step 1:

[0065] The user opens the application on the device and accesses the "Symptom Input" screen.

[0066] Step 2:

[0067] The user enters the pet's specific symptoms into a text box.

[0068] For example, enter "My pet has a red rash on its skin."

[0069] Step 3:

[0070] The user clicks the "Submit" button to submit the symptom data.

[0071] Step 4:

[0072] The terminal converts the user input data into JSON format.

[0073] For example, it converts to {"symptom": "My pet has a red rash on its skin"}.

[0074] Step 5:

[0075] The terminal transmits the converted data to the server.

[0076] Step 6:

[0077] The server begins the process of parsing the received data.

[0078] Step 7:

[0079] The server uses natural language processing (NLP) to extract keywords from the input text.

[0080] For example, extract keywords such as "skin," "red," and "rash."

[0081] Step 8:

[0082] The server compares the extracted keywords with the learning database and predicts the most relevant disease name.

[0083] As an example, "allergic dermatitis" is predicted.

[0084] Step 9:

[0085] The server retrieves first aid procedures associated with the predicted illness from a database.

[0086] For example, methods such as "cool the affected area with a cold towel" and "consider over-the-counter antihistamines" are obtained.

[0087] Step 10:

[0088] The server converts the first aid procedures into a visual or video format.

[0089] For example, we will generate a video showing the steps to cool an affected area using a cold towel.

[0090] Step 11:

[0091] The server obtains the user's location information and searches for nearby veterinary clinics based on that location.

[0092] Step 12:

[0093] The server generates a list of specialized veterinary clinics and best doctors and constructs the information to be provided to the user.

[0094] Step 13:

[0095] The server generates a packet that summarizes first aid procedures, disease predictions, and veterinary clinic information and sends it to the terminal.

[0096] Step 14:

[0097] The device analyzes the data received and displays the "First Aid Procedures" screen.

[0098] Step 15:

[0099] The device displays first aid procedures to the user in visual or video format.

[0100] For example, a video might show "steps to cool the affected area using a cold towel."

[0101] Step 16:

[0102] The device displays a predicted disease name and a list of recommended veterinary clinics.

[0103] For example, it could display something like, "There is a possibility of allergic dermatitis. Nearby veterinary clinics are listed below."

[0104] Step 17:

[0105] The server regularly updates information on maintaining pet health and early detection of illness and sends it to the device.

[0106] Step 18:

[0107] The device will send a notification to the user informing them that new preventative information is available.

[0108] Step 19:

[0109] The user checks the notification and views the new prevention information.

[0110] For example, information such as "Regular cleaning and avoiding certain foods are important for preventing pet allergies" may be displayed.

[0111] Example 1

[0112] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0113] Pet owners have limited means to respond quickly and accurately to sudden injuries or illnesses in their pets. It is also often difficult to immediately obtain appropriate first aid and specialized medical information. To solve this problem, a system is needed that allows users to easily input their pet's symptoms and quickly obtain appropriate first aid and specialized medical information.

[0114] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0115] In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for converting the input symptom data into a consistent format and transmitting the data to the server, a data analysis means for analyzing the received symptom data using a machine learning model and predicting an associated disease name and first aid method, a visualization means for displaying the generated first aid method in a visual or video format, a hospital search means for searching for nearby specialized medical facilities based on the user's location information and providing the information, and a prevention information provision means for periodically providing information on the prevention and early detection of pet diseases. This allows appropriate first aid methods and specialized medical information to be quickly provided according to the pet's symptoms, enabling pet owners to care for their pets with peace of mind.

[0116] The "user interface means" refers to an interface that provides text boxes and options for inputting symptoms of a pet, allowing the user to easily input symptoms.

[0117] The "communication method" refers to the method for converting the symptom data entered by the user into a consistent format and sending it to the server. Specifically, the data is converted into JSON format and a communication protocol such as an HTTP POST request is used.

[0118] The "data analysis means" is a means for analyzing the symptom data received by the server using machine learning models and natural language processing, extracting keywords from the input text, and comparing them with a learning database to predict the optimal first aid method and disease name.

[0119] The "visualization means" refers to a means for converting the first aid procedures and methods generated based on the data analysis into a visual or video format and displaying them in a way that is easily understandable to the user, for example, by using a video generation library or a graphics library.

[0120] "Hospital search means" refers to a means of searching for nearby specialized medical facilities and veterinary clinics using the user's location information and providing that information to the user. Specifically, search results are obtained using a local search API.

[0121] The "prevention information provision means" is a means by which a server periodically generates information on pet disease prevention and early detection and sends it to the user's device as a news feed or push notification. For example, it uses a notification system such as Firebase Cloud Messaging.

[0122] A "machine learning model" is an algorithm or framework that learns patterns from data to make predictions and classifications, and is used to analyze pet symptom data.

[0123] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, and is a data format that expresses data in a text format and enables consistent data exchange.

[0124] The present invention relates to an AI system that enables pet owners to provide quick and accurate first aid to their pets when they suddenly become injured or become ill. This system is realized using the following means.

[0125] First, the user accesses the terminal and is provided with text boxes and options to input the specific symptoms of their pet. The user enters the symptoms in detail and clicks the "Submit" button. For example, the user may enter "My pet has developed a red rash on its skin."

[0126] The terminal then converts the data entered by the user into JSON format and sends it to the server using a data communication protocol, which ensures data consistency and improves transfer efficiency.

[0127] The server analyzes the received data using a natural language processing (NLP) engine. At this stage, keywords are extracted from the input text and compared with a built-in learning database. This allows the most appropriate first aid method and diagnosis to be predicted. Specific software used is the machine learning framework PyTorch and TENSORFLOW (registered trademark).

[0128] Furthermore, the server creates first aid procedures based on the results of the data analysis. These procedures are converted into videos and diagrams for easy visual understanding. For example, a video showing the procedure for cooling the affected area with a cold towel can be created. Video generation libraries (e.g., FFmpeg) and graphics libraries (e.g., p5.js) are used to generate these videos.

[0129] The device receives the video and illustrations of first aid procedures sent from the server and displays them to the user, who can then take appropriate first aid. A user interface framework (e.g., React.js or Vue.js) is used for displaying the information.

[0130] The server also obtains the user's location information and searches for nearby veterinary clinics based on that location. Using a local search API (e.g., Google® Places API), it generates a list of clinics that can accommodate specific symptoms or illnesses and provides it to the user. For example, if the user enters "my pet is having difficulty breathing," it determines that oxygen supply is required and searches for the nearest veterinary clinic that can provide emergency care, providing the information.

[0131] The server then periodically provides information about pet health maintenance and early disease detection. This information is sent to the user's device as a news feed or push notification, and includes advice on disease prevention and health management. This is done using a periodic query and notification system (e.g., Firebase Cloud Messaging).

[0132] As a specific example, if a user inputs "My pet has a red rash on its skin," the device sends this data to the server. The server analyzes the data, predicts it is allergic dermatitis, generates a video showing first aid using a cold towel, and provides instructions to the user. It also searches for and lists nearby veterinary clinics specializing in allergies, and provides this to the user. On the other hand, if the user inputs "My pet is having difficulty breathing," it determines that oxygen supply is necessary, generates a video showing appropriate first aid, and searches for the nearest veterinary clinic that can provide emergency care.

[0133] In this way, this system quickly provides appropriate first aid methods and specialized medical information according to the pet's symptoms, allowing pet owners to care for their pets with peace of mind. In addition, the regular provision of information also contributes to maintaining the health of pets.

[0134] An example of a prompt is as follows:

[0135] "My pet has a red rash on its skin"

[0136] "My pet is having difficulty breathing"

[0137] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0138] Step 1:

[0139] The user accesses the terminal and inputs the specific symptoms of their pet. The user interface provides text boxes and options for entering the symptoms in detail. When the "Submit" button is clicked, the terminal retrieves the input data. The input is symptom data in text format, and the output is the symptom data itself.

[0140] Step 2:

[0141] The device converts the symptom data entered by the user into JSON format. The converted data is consistent and suitable for communication. Here, the input is symptom data in text format, and the output is data in JSON format. Specifically, the data conversion is performed using a JavaScript library.

[0142] Step 3:

[0143] The terminal sends data to the server using a communication protocol (for example, an HTTP POST request). At this stage, the input is JSON-formatted data, and the output is status information indicating that transmission to the server has been completed. HTTPS communication is used for data transfer, ensuring security.

[0144] Step 4:

[0145] The server receives the JSON-formatted data sent from the device. It then analyzes the data using a natural language processing (NLP) engine. The input is JSON-formatted data, and the output is symptom data with extracted keywords. Here, analysis is performed using a machine learning model (e.g., PyTorch or TensorFlow).

[0146] Step 5:

[0147] After extracting keywords, the server compares them with the learning database to predict the most relevant first aid method and disease name. The input is symptom data from which keywords have been extracted, and the output is first aid methods and predicted disease names. Past data and specialized knowledge are incorporated into the predictions.

[0148] Step 6:

[0149] The server creates first aid procedures based on the analysis results. These procedures are converted into videos and diagrams for easy visual understanding. The input is the first aid method and the name of the disease, and the output is the procedure in video or diagram format. Specifically, a video generation library (e.g., FFmpeg) and a graphics library (e.g., p5.js) are used.

[0150] Step 7:

[0151] The device receives the video or diagram of the first aid procedure sent from the server and displays it to the user. The user can then view it and take appropriate first aid. Here, the input is the video or diagram format of the procedure, and the output is the displayed information. A user interface framework (e.g., React.js or Vue.js) is used for display.

[0152] Step 8:

[0153] The server obtains the user's location information and searches for nearby veterinary clinics based on that location. The input is the user's location information and the output is the search results. A local search API (e.g., Google Places API) is used to provide the user with the most suitable clinic information.

[0154] Step 9:

[0155] The server periodically generates information on maintaining pet health and early disease detection, and sends it to the user's device as a news feed or push notification. The input is disease prevention information and health management advice, and the output is the notified information. Notifications are sent using Firebase Cloud Messaging and other technologies to ensure that information reaches the user reliably.

[0156] (Application example 1)

[0157] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0158] When a pet suddenly becomes injured or becomes unwell, it is difficult for pet owners to provide first aid quickly and accurately. It is also difficult to quickly find an appropriate medical institution that responds to the pet's symptoms. Furthermore, first aid methods are not presented visually in an easy-to-understand manner, which can make it difficult to actually carry them out. The present invention aims to solve these problems and enable pet owners to easily access the information they need.

[0159] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0160] In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for transmitting the input symptom data to the server, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a visualization means for displaying the generated first aid method visually or in video format in an augmented reality format, a hospital search means for searching for and providing information on veterinary clinics specializing in the symptoms, a means for providing information on nearby veterinary clinics based on the analysis results, and a prevention information provision means for periodically providing information on the prevention and early detection of diseases in pets. This makes it possible to provide appropriate first aid instructions according to the pet's symptoms visually through augmented reality, and also allows instant access to information on nearby veterinary clinics, enabling rapid response.

[0161] The "user interface means" is a function that provides text boxes and options for the user to input symptoms of their pet.

[0162] "Communication means" refers to a technique for transmitting input symptom data to a server.

[0163] The "data analysis means" is a function that analyzes the received symptom data and generates an appropriate first aid method and disease name.

[0164] The "visualization means" refers to a technology for visually displaying the generated first aid method in an augmented reality format or a video format.

[0165] The "hospital search tool" is a function that searches for veterinary hospitals that specialize in symptoms and provides information about them.

[0166] The "location information means" is a technology for acquiring the user's location information and searching for nearby veterinary clinics based on that information.

[0167] The "prevention information provision means" is a function that periodically provides information on the prevention and early detection of pet diseases.

[0168] "Augmented reality" is a technology that displays digital information overlaid on real-world information.

[0169] The present invention provides a system that enables pet owners to quickly and accurately provide first aid to their pets when they are injured or in poor health. An embodiment of the system will be described in detail below.

[0170] First, the user puts on the smart glasses and voice-inputs the specific symptoms of their pet. The smart glasses have a built-in voice recognition function that can convert the voice-input symptoms into text, allowing the user to easily communicate the symptoms to the system.

[0171] Next, the communication means installed in the smart glasses converts the input symptom data into JSON format and sends it to the server. The communication means requires a high-speed and stable internet connection.

[0172] The server uses a natural language processing (NLP) model to analyze the received symptom data. It extracts keywords from the input text data and compares them with a past learning database based on these keywords to generate the most relevant first aid method and predicted disease name. This data analysis method makes it possible to provide appropriate first aid methods.

[0173] The generated first aid instructions are visualized in augmented reality (AR) and displayed on the user's smart glasses, allowing the user to see specific treatment procedures for their pet superimposed on the real world. For example, a first aid instruction such as "cool the affected area with a cold towel" is visually displayed in AR.

[0174] The server also obtains the user's location information and searches for nearby veterinary clinics based on that location. The search results are displayed on the smart glasses, allowing the user to quickly access the nearest veterinary clinic. At the same time, the preventive information provider also regularly provides information on maintaining pet health and early detection of illnesses.

[0175] For example, if a user says, "My pet is having difficulty breathing," the server quickly analyzes the data and determines that oxygen is needed. As a result, the necessary first aid instructions are displayed in AR format on the smart glasses, along with information about the nearest veterinary clinic.

[0176] An example of a prompt for a generative AI model is as follows:

[0177] "My pet suddenly started having difficulty breathing. Please tell me first aid procedures and the nearest veterinary clinic."

[0178] As described above, the present invention enables quick and accurate responses to pet ailments, allowing owners to care for their pets with peace of mind. In addition, the function of providing preventive information contributes to maintaining the health of pets.

[0179] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0180] Step 1:

[0181] The user wears the smart glasses and inputs their pet's symptoms by voice. The input voice is converted into text data by the voice recognition system in the smart glasses. Input data: User's voice information, Output data: Symptom data in text format

[0182] Step 2:

[0183] The symptom information converted into text data is converted into JSON format by the smart glasses' communication means and sent to a server via the Internet. Input data: symptom data in text format, Output data: symptom data in JSON format

[0184] Step 3:

[0185] The server analyzes the received JSON-formatted symptom data. Using a natural language processing (NLP) model, it extracts keywords from the text data and compares them with a training database. This results in the most relevant first aid method and predicted disease name. Input data: JSON-formatted symptom data, Output data: first aid method, predicted disease name

[0186] Step 4:

[0187] The server converts the generated first aid method based on the analysis results into an augmented reality (AR) format. The augmented reality format data is sent to the smart glasses and visually displayed to the user. Input data: First aid method, Output data: First aid method in augmented reality format

[0188] Step 5:

[0189] The server acquires the user's location information and searches for nearby veterinary clinics based on the location information. The search results for veterinary clinic information are sent to the smart glasses and notified to the user. Input data: User's location information, Output data: Nearby veterinary clinic information

[0190] Step 6:

[0191] The server periodically generates preventive information related to maintaining pet health and early detection of diseases, and notifies the smart glasses. This allows users to periodically receive information useful for managing their pet's health. Input data: Preventive information stored in the server's database. Output data: Preventive information in notification format.

[0192] Step 7:

[0193] The user performs first aid on the pet based on the augmented reality first aid method displayed on the smart glasses. The user also refers to the veterinary clinic information displayed on the smart glasses to quickly access the veterinary clinic. Input data: augmented reality first aid method, veterinary clinic information. Output data: first aid to be performed, location information of the veterinary clinic.

[0194] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0195] overview

[0196] This invention is an AI system that enables pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. It aims to improve the method of presenting first aid procedures and the quality of user support by incorporating an emotion engine that recognizes the user's emotions. This system includes a user interface for inputting the pet's symptoms, a communication means for transmitting symptom data to a server, a data analysis means, a visualization means, a hospital search means, a preventive information provision means, and an emotion engine. Based on the symptoms and emotion information entered by the user, the server provides appropriate first aid procedures and specialized treatment information.

[0197] Program processing

[0198] The program of this system processes as follows:

[0199] 1. User Interface Methods

[0200] The user accesses a terminal and is provided with text boxes and options to input their pet's specific symptoms. The user enters the symptoms in detail and clicks the "Submit" button.

[0201] 2. Means of communication

[0202] The data sent by the user is converted to JSON format by the terminal and sent to the server, which improves data consistency and transmission efficiency.

[0203] 3. Data Analysis Methods

[0204] The server analyzes the received data and uses natural language processing (NLP) to extract keywords from the input text and compare them with a training database to predict the most relevant first aid method and disease name.

[0205] 4. Visualization tools

[0206] The resulting first aid procedures are then converted into visual or video formats. For example, a video can be created demonstrating how to apply a cold towel to an affected area. The video is then displayed on the device for easy user access.

[0207] 5. Hospital search tools

[0208] The server obtains the user's location information, searches for nearby veterinary clinics based on that location, and provides the user with a list of specialized medical facilities that can treat specific symptoms or illnesses.

[0209] 6. Emotion Engine

[0210] The emotion engine analyzes the user's voice input and facial expression data to recognize their emotions. For example, if the user shows signs of anxiety or impatience, it will suggest first aid measures and provide advice on how to calm the user.

[0211] 7. Preventive information provision measures

[0212] The server periodically provides information on pet health maintenance and early disease detection, including advice on how to prevent certain diseases and health management, which is displayed as notifications on the user's device.

[0213] Specific examples

[0214] Example 1: Skin rash

[0215] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes the data and predicts that it is "allergic dermatitis." It also instructs the user on how to provide first aid using a cold towel and recommends a nearby veterinary clinic that specializes in allergies. It also provides visual instructions in the form of a video and periodically notifies users of preventative care information. Furthermore, if the device senses anxiety in the user's voice, it displays reassuring advice.

[0216] Example 2: Difficulty breathing

[0217] The user types, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It provides a video of the appropriate first aid procedure. It also searches for the nearest veterinary hospital that can provide emergency care and instructs the user. The emotion engine recognizes the user's impatience and provides instructions and advice on how to respond calmly.

[0218] In this way, by combining this system with an emotion engine, it is possible to quickly provide appropriate first aid procedures and specialized medical information according to the pet's symptoms, as well as provide appropriate support according to the user's emotional state. This allows pet owners to care for their pets with peace of mind. In addition, by providing information on disease prevention and early detection, it can also contribute to maintaining pet health.

[0219] The processing flow will be explained below.

[0220] Step 1:

[0221] The user opens the application on the device and accesses the "Symptom Input" screen.

[0222] Step 2:

[0223] The user enters the pet's specific symptoms into a text box.

[0224] For example, enter "My pet has a red rash on its skin."

[0225] Step 3:

[0226] The user clicks the "Submit" button to submit the symptom data.

[0227] Step 4:

[0228] The terminal converts the user input data into JSON format.

[0229] For example, it converts to {"symptom": "My pet has a red rash on its skin"}.

[0230] Step 5:

[0231] The terminal transmits the converted data to the server.

[0232] Step 6:

[0233] The server begins the process of parsing the received data.

[0234] Step 7:

[0235] The server uses natural language processing (NLP) to extract keywords from the input text.

[0236] For example, extract keywords such as "skin," "red," and "rash."

[0237] Step 8:

[0238] The server compares the extracted keywords with the learning database and predicts the most relevant disease name.

[0239] As an example, "allergic dermatitis" is predicted.

[0240] Step 9:

[0241] The server retrieves first aid procedures associated with the predicted illness from a database.

[0242] For example, methods such as "cool the affected area with a cold towel" and "consider over-the-counter antihistamines" are obtained.

[0243] Step 10:

[0244] The server converts the first aid procedures into a visual or video format.

[0245] For example, we will generate a video showing the steps to cool an affected area using a cold towel.

[0246] Step 11:

[0247] The server obtains the user's location information and searches for nearby veterinary clinics based on that location.

[0248] Step 12:

[0249] The server generates a list of specialized veterinary clinics and best doctors and constructs the information to be provided to the user.

[0250] Step 13:

[0251] The emotion engine analyzes the user's voice input and facial expression data to recognize emotions.

[0252] For example, if the user is feeling anxious, the emotion of "anxiety" is recognized from the tone of voice and facial expression.

[0253] Step 14:

[0254] Based on the emotion engine's analysis, the server adjusts how first aid procedures are presented.

[0255] For example, for a user who is feeling anxious, gentle words or audio guidance are provided to give a sense of security.

[0256] Step 15:

[0257] The server generates advice based on the emotion recognition results.

[0258] For example, if the user is feeling anxious, the system generates advice such as "Please stay calm. First, calm down and take a deep breath."

[0259] Step 16:

[0260] The server generates a packet containing first aid procedures, disease predictions, veterinary clinic information, and advice based on the patient's emotions, and sends it to the terminal.

[0261] Step 17:

[0262] The device analyzes the data received and displays the "First Aid Procedures" screen.

[0263] Step 18:

[0264] The device displays first aid procedures to the user in visual or video format.

[0265] For example, a video might show "steps to cool the affected area using a cold towel."

[0266] Step 19:

[0267] The device displays a predicted disease name and a list of recommended veterinary clinics.

[0268] For example, it could display something like, "There is a possibility of allergic dermatitis. Nearby veterinary clinics are listed below."

[0269] Step 20:

[0270] The terminal displays advice based on emotion recognition to the user.

[0271] For example, it displays the message, "Please stay calm. First, calm down and take a deep breath."

[0272] Step 21:

[0273] The server regularly updates information on maintaining pet health and early detection of illness and sends it to the device.

[0274] Step 22:

[0275] The device will send a notification to the user informing them that new preventative information is available.

[0276] Step 23:

[0277] The user checks the notification and views the new prevention information.

[0278] For example, information such as "Regular cleaning and avoiding certain foods are important for preventing pet allergies" may be displayed.

[0279] Example 2

[0280] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0281] Providing prompt and accurate first aid for pets suffering from sudden injuries or illness is an important issue for pet owners. Furthermore, there is a need for a means to provide appropriate support and reassurance in situations where pet owners feel anxious or impatient. To address these issues, the present invention aims to provide a system that allows pet owners to input their pet's symptoms and quickly analyzes and responds to them.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0283] In this invention, the server includes an information input means for inputting the symptoms of the pet, a communication means for transmitting the input symptom data to the central device, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a display means for displaying the generated first aid method in a visual or video format, a medical facility search means for searching for and providing information on medical facilities specializing in the symptoms, a preventive information provision means for periodically providing information on the prevention and early detection of diseases in pets, and an emotion recognition means for recognizing the user's emotions and providing appropriate first aid methods and advice to reassure the user, thereby enabling quick and accurate first aid for the pet's symptoms and providing a sense of security.

[0284] The "information input means" is a device that provides an interface for the user to input specific symptoms of the pet.

[0285] The "communication means" is a device having a function for transmitting input symptom data to the central device.

[0286] The "data analysis means" is a device for analyzing the received symptom data and generating an appropriate first aid method.

[0287] The "display means" is a device that displays the generated first aid method in a visual or animated format.

[0288] The "medical facility search means" is a device that searches for medical facilities that specialize in symptoms and provides information.

[0289] The "prevention information providing means" is a device that periodically provides information on the prevention and early detection of pet diseases.

[0290] The "emotion recognition means" is a device that recognizes the user's emotions and provides appropriate first aid or advice to reassure the user.

[0291] The "Central Unit" is the main component that analyzes the received data, generates appropriate first aid procedures, and provides information to the user.

[0292] This invention is a system for providing quick and accurate first aid to pets when they suddenly become injured or ill, and also aims to provide appropriate support and peace of mind to pet owners in situations where they feel anxious or impatient.

[0293] A web browser or mobile application can be used as an information input method for users to enter their pet's symptoms. For example, users can open the application and enter their pet's specific symptoms into the text box. Alternatively, they can select options based on the symptoms. Once they have completed the input, they click the "Submit" button.

[0294] The terminal converts the user's input data into JSON format and sends it to a central device (server) via the Internet, which improves data consistency and transfer efficiency.

[0295] The server analyzes the received JSON data. The analysis method used here is natural language processing (NLP) technology. For example, Python and a natural language processing library are used to extract important keywords from the text data. This results in keywords such as "red rash" and "skin." These keywords are compared with a pre-trained database to predict the most relevant disease name and first aid method.

[0296] The server generates first aid procedures based on the analysis results and converts them into a visual or video format. For example, a video showing the procedure of "cooling the affected area with a cold towel" can be shown. Video editing software is used to generate the video. The generated video is sent to the user's device and displayed on the device.

[0297] The server obtains location information from the user's device and searches for nearby medical facilities based on that location. The search results provide a list of medical facilities that can accommodate specific symptoms or illnesses. This list is displayed on the user's device, allowing them to quickly head to the nearest medical facility.

[0298] The server performs voice analysis and facial expression analysis as emotion recognition means. Voice input is converted into text using a voice recognition API, and facial expression data is analyzed using facial recognition technology. For example, Google's Cloud Speech-to-Text API can be used for voice analysis, and Microsoft's facial recognition API can be used for facial expression recognition. This allows the server to recognize when a user is anxious or impatient and display advice to reassure the user.

[0299] The server also periodically provides information on pet disease prevention and early detection, including advice on how to prevent specific illnesses and health management, such as "seasonal allergy prevention measures," to the user's device.

[0300] Specific examples

[0301] Example 1: Skin rash

[0302] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes the data and predicts "allergic dermatitis." It then instructs the user on how to provide first aid using a cold towel and recommends a nearby medical facility specializing in allergies. It also provides visual instructions in the form of a video and periodically notifies users of preventive measures. Furthermore, if the device senses anxiety in the user's voice, it displays reassuring advice.

[0303] Example 2: Difficulty breathing

[0304] The user types, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It provides a video of the appropriate first aid procedure. It also searches for the nearest emergency medical facility and instructs the user on the procedure. The emotion engine recognizes the user's impatience and provides instructions and advice on how to respond calmly.

[0305] In this way, by combining an emotion engine, the present invention is a system that provides quick and accurate first aid for pet symptoms and a sense of security. It also contributes to maintaining pet health by providing preventive information.

[0306] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0307] Step 1:

[0308] The user opens the application and enters the specific symptoms of their pet. They use the text boxes and options to enter details about the symptoms and click the "Submit" button.

[0309] Input: Pet's specific symptoms (text format)

[0310] Output: Symptom data sent to the device (text format)

[0311] Specific behavior: The user enters "My pet has a red rash on its skin" into the application and presses the send button.

[0312] Step 2:

[0313] The terminal converts the user's input data into JSON format and sends it to a central device (server) via the Internet.

[0314] Input: Submitted symptom data (text format)

[0315] Output: JSON format data sent to the server

[0316] Specific behavior: The application on the device converts the text "My pet has a red rash on its skin" into JSON format and sends it to the server.

[0317] Step 3:

[0318] The server parses the received JSON data and uses natural language processing (NLP) techniques to extract important keywords from the text data and match them with existing databases to predict the most relevant disease names and first aid methods.

[0319] Input: Symptom data in JSON format

[0320] Output: Prediction results of disease name and first aid method

[0321] Specific operation: The server uses Python and NLP libraries to extract keywords such as "red rash" and "skin" and predicts "allergic dermatitis."

[0322] Step 4:

[0323] The server generates first aid procedures based on the analysis results and converts them into a visual or video format. Editing software is used to convert the first aid procedures into a video and send it to the user's device.

[0324] Input: Disease name and first aid method prediction results

[0325] Output: Visual or video first aid instructions

[0326] Specific operation: The server generates a video showing the steps of "cooling the affected area with a cold towel" and sends it to the user's device.

[0327] Step 5:

[0328] The server obtains location information from the user's terminal and searches for nearby medical facilities based on that location.

[0329] Input: User's location

[0330] Output: A list of symptom-specific medical facilities

[0331] Specific operation: The server acquires the user's location information, generates a list of "allergy specialty medical facilities," and provides it to the user.

[0332] Step 6:

[0333] The emotion recognition means analyzes the user's voice input and facial expression data to recognize the user's emotions. For example, it analyzes the user's voice to recognize anxiety and provide advice accordingly.

[0334] Input: Voice input and facial expression data

[0335] Output: Emotion recognition results and corresponding advice

[0336] Specific operation: The server converts speech into text using Google's Cloud Speech-to-Text API, analyzes facial expressions using Azure (registered trademark) Face API, recognizes anxiety, and displays advice such as "stay calm."

[0337] Step 7:

[0338] The server periodically provides information on maintaining pet health and early detection of illness.

[0339] Input: Pet health data and related information

[0340] Output: Preventive and health care advice

[0341] Specific operation: The server displays notifications such as "Seasonal allergy prevention measures" on the user's device.

[0342] Through the above processing steps, the system can provide users with fast and accurate first aid information and provide a sense of security through emotion recognition.

[0343] (Application example 2)

[0344] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0345] Conventional pet first aid systems have the problem of being unable to quickly provide appropriate treatment methods for pet symptoms and are unable to take into account the feelings of pet owners, which means they are unable to alleviate the anxiety and impatience of pet owners. Furthermore, searching for and providing information on veterinary medical facilities specializing in symptoms is not intuitive, and support is lacking in situations where a quick response is required.

[0346] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for transmitting the input symptom data to the server, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a visualization means for displaying the generated first aid method in a visual or video format, a medical facility search means for searching for and providing information on veterinary medical facilities specializing in the symptoms, a preventive information provision means for periodically providing information on the prevention and early detection of pet diseases, and an emotion recognition means for recognizing the user's emotions and suggesting appropriate first aid methods and providing psychological support. This allows pet owners to quickly and accurately provide appropriate first aid, and by providing psychological support in accordance with the user's emotions, the pet owner's anxiety and impatience can be alleviated, making it possible to more effectively manage the pet's health.

[0347] The "user interface means" is an interface device that the user uses to input the symptoms of the pet.

[0348] "Communication means" refers to the technical means for transmitting the input symptom data to the server.

[0349] The "data analysis means" is a technical means for analyzing the symptom data received by the server and generating an appropriate first aid method.

[0350] A "visualization tool" is a device or technique for displaying the generated first aid instructions in a visual or animated format.

[0351] A "medical facility search tool" is a device or technology for searching for and providing information on veterinary medical facilities that specialize in certain symptoms.

[0352] A "preventive information providing means" is a device or technology that periodically provides information on the prevention and early detection of pet diseases.

[0353] An "emotion recognition means" is a device or technology for recognizing a user's emotions and suggesting appropriate first aid methods or providing psychological support.

[0354] overview

[0355] This invention is an AI system that allows pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. The system analyzes symptom and emotional data entered by the user and provides appropriate first aid. It also searches for nearby veterinary medical facilities and provides information, thereby reducing user anxiety and supporting pet health management.

[0356] User Interface Means

[0357] The user accesses the terminal and inputs the specific symptoms of their pet. To do this, an interface such as text boxes and check boxes is provided. The system also has voice input and facial recognition functions to recognize the user's emotions.

[0358] communication means

[0359] The entered data is converted to JSON format and sent to the server over the Internet, which improves data consistency and transfer efficiency.

[0360] Data Analysis Methods

[0361] The server uses natural language processing (NLP) technology to analyze the received symptom data. Specifically, it extracts keywords from the input text and compares them with a training database to predict the most relevant first aid method and disease name. For emotional data, it uses an emotion recognition engine to analyze the user's feelings, such as anxiety or impatience.

[0362] Visualization tools

[0363] The generated first aid instructions can be displayed on the device in visual or video format. For example, an animation can show the steps for applying a cold towel to an affected area. This video is provided in a user-friendly format.

[0364] Medical facility search tools

[0365] The server searches for nearby veterinary medical facilities based on the user's location information. It then lists medical facilities that can treat specific symptoms or illnesses and provides them to the user. This information is obtained in real time, allowing it to provide the most up-to-date data.

[0366] Preventive information provision methods

[0367] The server periodically provides information on maintaining pet health and early detection of diseases, including advice on how to prevent certain diseases and health management, and provides the information to the user in a timely manner using a notification function.

[0368] emotion recognition means

[0369] The emotion recognition means analyzes the user's voice input and facial expression data to recognize their emotions. For example, if the user shows signs of anxiety or impatience, it will suggest first aid measures to address the situation and provide advice on how to calm down. This function allows the user to respond calmly.

[0370] Examples and prompts

[0371] For example, if a user types "my pet has a red rash on its skin," the system will predict "allergic dermatitis" and provide a video showing first aid using a cold towel. It will also recommend nearby veterinary clinics that specialize in allergies, and its emotion recognition capabilities will sense the user's anxiety and provide reassuring advice.

[0372] Example prompt sentence:

[0373] Input: "My pet has a skin rash."

[0374] output:

[0375] First aid: "Cool the area with a cold towel."

[0376] Veterinary Clinic: "We can connect you to a nearby specialized medical facility."

[0377] Emotional care: "Remain calm. Seek medical attention to determine the cause of the rash."

[0378] This system allows pet owners to provide prompt and appropriate first aid and receive comprehensive support that also takes into consideration the user's emotions.

[0379] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0380] Step 1:

[0381] The user uses the device to input their pet's symptoms. Specifically, they type "My pet has a red rash on its skin" into the text box and click the send button. Based on this input, the system begins initial processing. The user's emotions are also collected through voice input and the camera.

[0382] Input: Pet's specific symptoms (text), user's emotions (voice, facial recognition)

[0383] Output: Input data in JSON format

[0384] Step 2:

[0385] The device converts the input data into JSON format and sends it to the server using a communication method. The internet is used to maintain data consistency and transmit data efficiently.

[0386] Input: User-entered symptoms and emotional information

[0387] Output: JSON data sent to the server

[0388] Step 3:

[0389] The server analyzes the received JSON data, using natural language processing (NLP) technology to analyze symptoms and generate appropriate first aid methods and a predicted illness name based on extracted keywords. An emotion recognition engine analyzes the user's emotions and compares them with a database to determine the appropriate psychological support.

[0390] Input: JSON data (symptoms, emotions)

[0391] Output: First aid methods, predicted illness names, mental support information

[0392] Step 4:

[0393] The server generates the generated first aid method in the form of a video or image through a visualization means. This visualized data is sent to the terminal in a format that is easy for the user to understand. Specifically, a video of "the procedure for cooling the affected area with a cold towel" is generated.

[0394] Input: First Aid Methods

[0395] Output: Video or image data

[0396] Step 5:

[0397] The server uses the user's location information to search for nearby veterinary clinics, compiles a list of clinics that can treat specific symptoms or illnesses, and sends that information to the device. This is done using location services such as Google Maps API.

[0398] Input: User's location information, predicted disease name

[0399] Output: List of veterinary facilities with details

[0400] Step 6:

[0401] The device displays information received from the server, including first aid videos, a list of nearby veterinary clinics, and emotional support information, allowing users to take prompt and appropriate action.

[0402] Input: First aid methods, medical facility information, and mental support information from the server

[0403] Output: A user-accessible visual representation

[0404] Step 7:

[0405] The server periodically sends information about pet disease prevention and early detection to the terminal using the preventive information providing means. This allows the user to obtain a specific action plan for disease prevention and early detection. For example, information such as "methods for preventing allergic dermatitis" is provided.

[0406] Input: Preventive Information

[0407] Output: Providing periodic notifications and preventative information

[0408] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0409] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0410] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0411] [Second embodiment]

[0412] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0413] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0414] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0415] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0416] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0417] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0418] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0419] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0420] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0421] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0422] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0423] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0424] overview

[0425] This invention is an AI system that allows pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. The system includes a user interface for inputting the pet's symptoms, a communication means for transmitting symptom data to a server, a data analysis means, a visualization means, a hospital search means, and a preventive information provision means. Based on the symptoms input by the user, the server provides appropriate first aid procedures and specialized treatment information.

[0426] Program processing

[0427] The program of this system processes as follows:

[0428] 1. User Interface Methods

[0429] The user accesses a terminal and is provided with text boxes and options to input their pet's specific symptoms. The user enters the symptoms in detail and clicks the "Submit" button.

[0430] 2. Means of communication

[0431] The data sent by the user is converted to JSON format by the terminal and sent to the server, which improves data consistency and transmission efficiency.

[0432] 3. Data Analysis Methods

[0433] The server analyzes the received data and uses natural language processing (NLP) to extract keywords from the input text and compare them with a training database to predict the most relevant first aid method and disease name.

[0434] 4. Visualization tools

[0435] The resulting first aid procedures are then converted into visual or video formats. For example, a video can be created demonstrating how to apply a cold towel to an affected area. The video is then displayed on the device for easy user access.

[0436] 5. Hospital search tools

[0437] The server obtains the user's location information, searches for nearby veterinary clinics based on that location, and provides the user with a list of specialized medical facilities that can treat specific symptoms or illnesses.

[0438] 6. Preventive information provision measures

[0439] The server periodically provides information on pet health maintenance and early disease detection, including advice on how to prevent certain diseases and health management, which is displayed as notifications on the user's device.

[0440] Specific examples

[0441] Example 1: Skin rash

[0442] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes it and predicts that it is "allergic dermatitis." The server then instructs the user on how to treat the rash with a cold towel and recommends a nearby veterinary clinic that specializes in allergies. The system also provides visual instructions in a video and periodically notifies users of preventative care information.

[0443] Example 2: Difficulty breathing

[0444] The user enters, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It then provides a video of the appropriate first aid procedure. It also searches for the nearest veterinary hospital that can provide emergency care and directs the user to it.

[0445] In this way, this system can quickly provide appropriate first aid procedures and specialized medical information according to the pet's symptoms, allowing pet owners to care for their pets with peace of mind.In addition, by providing information on disease prevention and early detection, it can also contribute to maintaining pet health.

[0446] The processing flow will be explained below.

[0447] Step 1:

[0448] The user opens the application on the device and accesses the "Symptom Input" screen.

[0449] Step 2:

[0450] The user enters the pet's specific symptoms into a text box.

[0451] For example, enter "My pet has a red rash on its skin."

[0452] Step 3:

[0453] The user clicks the "Submit" button to submit the symptom data.

[0454] Step 4:

[0455] The terminal converts the user input data into JSON format.

[0456] For example, it converts to {"symptom": "My pet has a red rash on its skin"}.

[0457] Step 5:

[0458] The terminal transmits the converted data to the server.

[0459] Step 6:

[0460] The server begins the process of parsing the received data.

[0461] Step 7:

[0462] The server uses natural language processing (NLP) to extract keywords from the input text.

[0463] For example, extract keywords such as "skin," "red," and "rash."

[0464] Step 8:

[0465] The server compares the extracted keywords with the learning database and predicts the most relevant disease name.

[0466] As an example, "allergic dermatitis" is predicted.

[0467] Step 9:

[0468] The server retrieves first aid procedures associated with the predicted illness from a database.

[0469] For example, methods such as "cool the affected area with a cold towel" and "consider over-the-counter antihistamines" are obtained.

[0470] Step 10:

[0471] The server converts the first aid procedures into a visual or video format.

[0472] For example, we will generate a video showing the steps to cool an affected area using a cold towel.

[0473] Step 11:

[0474] The server obtains the user's location information and searches for nearby veterinary clinics based on that location.

[0475] Step 12:

[0476] The server generates a list of specialized veterinary clinics and best doctors and constructs the information to be provided to the user.

[0477] Step 13:

[0478] The server generates a packet that summarizes first aid procedures, disease predictions, and veterinary clinic information and sends it to the terminal.

[0479] Step 14:

[0480] The device analyzes the data received and displays the "First Aid Procedures" screen.

[0481] Step 15:

[0482] The device displays first aid procedures to the user in visual or video format.

[0483] For example, a video might show "steps to cool the affected area using a cold towel."

[0484] Step 16:

[0485] The device displays a predicted disease name and a list of recommended veterinary clinics.

[0486] For example, it could display something like, "There is a possibility of allergic dermatitis. Nearby veterinary clinics are listed below."

[0487] Step 17:

[0488] The server regularly updates information on maintaining pet health and early detection of illness and sends it to the device.

[0489] Step 18:

[0490] The device will send a notification to the user informing them that new preventative information is available.

[0491] Step 19:

[0492] The user checks the notification and views the new prevention information.

[0493] For example, information such as "Regular cleaning and avoiding certain foods are important for preventing pet allergies" may be displayed.

[0494] Example 1

[0495] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0496] Pet owners have limited means to respond quickly and accurately to sudden injuries or illnesses in their pets. It is also often difficult to immediately obtain appropriate first aid and specialized medical information. To solve this problem, a system is needed that allows users to easily input their pet's symptoms and quickly obtain appropriate first aid and specialized medical information.

[0497] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0498] In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for converting the input symptom data into a consistent format and transmitting the data to the server, a data analysis means for analyzing the received symptom data using a machine learning model and predicting an associated disease name and first aid method, a visualization means for displaying the generated first aid method in a visual or video format, a hospital search means for searching for nearby specialized medical facilities based on the user's location information and providing the information, and a prevention information provision means for periodically providing information on the prevention and early detection of pet diseases. This allows appropriate first aid methods and specialized medical information to be quickly provided according to the pet's symptoms, enabling pet owners to care for their pets with peace of mind.

[0499] The "user interface means" refers to an interface that provides text boxes and options for inputting symptoms of a pet, allowing the user to easily input symptoms.

[0500] The "communication method" refers to the method for converting the symptom data entered by the user into a consistent format and sending it to the server. Specifically, the data is converted into JSON format and a communication protocol such as an HTTP POST request is used.

[0501] The "data analysis means" is a means for analyzing the symptom data received by the server using machine learning models and natural language processing, extracting keywords from the input text, and comparing them with a learning database to predict the optimal first aid method and disease name.

[0502] The "visualization means" refers to a means for converting the first aid procedures and methods generated based on the data analysis into a visual or video format and displaying them in a way that is easily understandable to the user, for example, by using a video generation library or a graphics library.

[0503] "Hospital search means" refers to a means of searching for nearby specialized medical facilities and veterinary clinics using the user's location information and providing that information to the user. Specifically, search results are obtained using a local search API.

[0504] The "prevention information provision means" is a means by which a server periodically generates information on pet disease prevention and early detection and sends it to the user's device as a news feed or push notification. For example, it uses a notification system such as Firebase Cloud Messaging.

[0505] A "machine learning model" is an algorithm or framework that learns patterns from data to make predictions and classifications, and is used to analyze pet symptom data.

[0506] "JSON format" is an abbreviation for JavaScript Object Notation, and is a data format that represents data in text format and enables consistent data exchange.

[0507] The present invention relates to an AI system that enables pet owners to provide quick and accurate first aid to their pets when they suddenly become injured or become ill. This system is realized using the following means.

[0508] First, the user accesses the terminal and is provided with text boxes and options to input the specific symptoms of their pet. The user enters the symptoms in detail and clicks the "Submit" button. For example, the user may enter "My pet has developed a red rash on its skin."

[0509] The terminal then converts the data entered by the user into JSON format and sends it to the server using a data communication protocol, which ensures data consistency and improves transfer efficiency.

[0510] The server analyzes the received data using a natural language processing (NLP) engine. At this stage, keywords are extracted from the input text and compared with a built-in learning database. This allows the system to predict the most appropriate first aid method and diagnosis. Specific software used is the machine learning frameworks PyTorch and TensorFlow.

[0511] Furthermore, the server creates first aid procedures based on the results of the data analysis. These procedures are converted into videos and diagrams for easy visual understanding. For example, a video showing the procedure for cooling the affected area with a cold towel can be created. Video generation libraries (e.g., FFmpeg) and graphics libraries (e.g., p5.js) are used to generate these videos.

[0512] The device receives the video and illustrations of first aid procedures sent from the server and displays them to the user, who can then take appropriate first aid. A user interface framework (e.g., React.js or Vue.js) is used for displaying the information.

[0513] The server also obtains the user's location information and searches for nearby veterinary clinics based on that location. Using a local search API (e.g., Google Places API), it generates a list of clinics that can handle specific symptoms or illnesses and provides it to the user. For example, if the user enters "my pet is having difficulty breathing," it determines that oxygen supply is required and searches for the nearest veterinary clinic that can provide emergency care, providing the information.

[0514] The server then periodically provides information about pet health maintenance and early disease detection. This information is sent to the user's device as a news feed or push notification, and includes advice on disease prevention and health management. This is done using a periodic query and notification system (e.g., Firebase Cloud Messaging).

[0515] As a specific example, if a user inputs "My pet has a red rash on its skin," the device sends this data to the server. The server analyzes the data, predicts it is allergic dermatitis, generates a video showing first aid using a cold towel, and provides instructions to the user. It also searches for and lists nearby veterinary clinics specializing in allergies, and provides this to the user. On the other hand, if the user inputs "My pet is having difficulty breathing," it determines that oxygen supply is necessary, generates a video showing appropriate first aid, and searches for the nearest veterinary clinic that can provide emergency care.

[0516] In this way, this system quickly provides appropriate first aid methods and specialized medical information according to the pet's symptoms, allowing pet owners to care for their pets with peace of mind. In addition, the regular provision of information also contributes to maintaining the health of pets.

[0517] An example of a prompt is as follows:

[0518] "My pet has a red rash on its skin"

[0519] "My pet is having difficulty breathing"

[0520] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0521] Step 1:

[0522] The user accesses the terminal and inputs the specific symptoms of their pet. The user interface provides text boxes and options for entering the symptoms in detail. When the "Submit" button is clicked, the terminal retrieves the input data. The input is symptom data in text format, and the output is the symptom data itself.

[0523] Step 2:

[0524] The device converts the symptom data entered by the user into JSON format. The converted data is consistent and suitable for communication. Here, the input is symptom data in text format, and the output is data in JSON format. Specifically, the data conversion is performed using a JavaScript library.

[0525] Step 3:

[0526] The terminal sends data to the server using a communication protocol (for example, an HTTP POST request). At this stage, the input is JSON-formatted data, and the output is status information indicating that transmission to the server has been completed. HTTPS communication is used for data transfer, ensuring security.

[0527] Step 4:

[0528] The server receives the JSON-formatted data sent from the device. It then analyzes the data using a natural language processing (NLP) engine. The input is JSON-formatted data, and the output is symptom data with extracted keywords. Here, analysis is performed using a machine learning model (e.g., PyTorch or TensorFlow).

[0529] Step 5:

[0530] After extracting keywords, the server compares them with the learning database to predict the most relevant first aid method and disease name. The input is symptom data from which keywords have been extracted, and the output is first aid methods and predicted disease names. Past data and specialized knowledge are incorporated into the predictions.

[0531] Step 6:

[0532] The server creates first aid procedures based on the analysis results. These procedures are converted into videos and diagrams for easy visual understanding. The input is the first aid method and the name of the disease, and the output is the procedure in video or diagram format. Specifically, a video generation library (e.g., FFmpeg) and a graphics library (e.g., p5.js) are used.

[0533] Step 7:

[0534] The device receives the video or diagram of the first aid procedure sent from the server and displays it to the user. The user can then view it and take appropriate first aid. Here, the input is the video or diagram format of the procedure, and the output is the displayed information. A user interface framework (e.g., React.js or Vue.js) is used for display.

[0535] Step 8:

[0536] The server obtains the user's location information and searches for nearby veterinary clinics based on that location. The input is the user's location information and the output is the search results. A local search API (e.g., Google Places API) is used to provide the user with the most suitable clinic information.

[0537] Step 9:

[0538] The server periodically generates information on maintaining pet health and early disease detection, and sends it to the user's device as a news feed or push notification. The input is disease prevention information and health management advice, and the output is the notified information. Notifications are sent using Firebase Cloud Messaging and other technologies to ensure that information reaches the user reliably.

[0539] (Application example 1)

[0540] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0541] When a pet suddenly becomes injured or becomes unwell, it is difficult for pet owners to provide first aid quickly and accurately. It is also difficult to quickly find an appropriate medical institution that responds to the pet's symptoms. Furthermore, first aid methods are not presented visually in an easy-to-understand manner, which can make it difficult to actually carry them out. The present invention aims to solve these problems and enable pet owners to easily access the information they need.

[0542] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0543] In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for transmitting the input symptom data to the server, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a visualization means for displaying the generated first aid method visually or in video format in an augmented reality format, a hospital search means for searching for and providing information on veterinary clinics specializing in the symptoms, a means for providing information on nearby veterinary clinics based on the analysis results, and a prevention information provision means for periodically providing information on the prevention and early detection of diseases in pets. This makes it possible to provide appropriate first aid instructions according to the pet's symptoms visually through augmented reality, and also allows instant access to information on nearby veterinary clinics, enabling rapid response.

[0544] The "user interface means" is a function that provides text boxes and options for the user to input symptoms of their pet.

[0545] "Communication means" refers to a technique for transmitting input symptom data to a server.

[0546] The "data analysis means" is a function that analyzes the received symptom data and generates an appropriate first aid method and disease name.

[0547] The "visualization means" refers to a technology for visually displaying the generated first aid method in an augmented reality format or a video format.

[0548] The "hospital search tool" is a function that searches for veterinary hospitals that specialize in symptoms and provides information about them.

[0549] The "location information means" is a technology for acquiring the user's location information and searching for nearby veterinary clinics based on that information.

[0550] The "prevention information provision means" is a function that periodically provides information on the prevention and early detection of pet diseases.

[0551] "Augmented reality" is a technology that displays digital information overlaid on real-world information.

[0552] The present invention provides a system that enables pet owners to quickly and accurately provide first aid to their pets when they are injured or in poor health. An embodiment of the system will be described in detail below.

[0553] First, the user puts on the smart glasses and voice-inputs the specific symptoms of their pet. The smart glasses have a built-in voice recognition function that can convert the voice-input symptoms into text, allowing the user to easily communicate the symptoms to the system.

[0554] Next, the communication means installed in the smart glasses converts the input symptom data into JSON format and sends it to the server. The communication means requires a high-speed and stable internet connection.

[0555] The server uses a natural language processing (NLP) model to analyze the received symptom data. It extracts keywords from the input text data and compares them with a past learning database based on these keywords to generate the most relevant first aid method and predicted disease name. This data analysis method makes it possible to provide appropriate first aid methods.

[0556] The generated first aid instructions are visualized in augmented reality (AR) and displayed on the user's smart glasses, allowing the user to see specific treatment procedures for their pet superimposed on the real world. For example, a first aid instruction such as "cool the affected area with a cold towel" is visually displayed in AR.

[0557] The server also obtains the user's location information and searches for nearby veterinary clinics based on that location. The search results are displayed on the smart glasses, allowing the user to quickly access the nearest veterinary clinic. At the same time, the preventive information provider also regularly provides information on maintaining pet health and early detection of illnesses.

[0558] For example, if a user says, "My pet is having difficulty breathing," the server quickly analyzes the data and determines that oxygen is needed. As a result, the necessary first aid instructions are displayed in AR format on the smart glasses, along with information about the nearest veterinary clinic.

[0559] An example of a prompt for a generative AI model is as follows:

[0560] "My pet suddenly started having difficulty breathing. Please tell me first aid procedures and the nearest veterinary clinic."

[0561] As described above, the present invention enables quick and accurate responses to pet ailments, allowing owners to care for their pets with peace of mind. In addition, the function of providing preventive information contributes to maintaining the health of pets.

[0562] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0563] Step 1:

[0564] The user wears the smart glasses and inputs their pet's symptoms by voice. The input voice is converted into text data by the voice recognition system in the smart glasses. Input data: User's voice information, Output data: Symptom data in text format

[0565] Step 2:

[0566] The symptom information converted into text data is converted into JSON format by the smart glasses' communication means and sent to a server via the Internet. Input data: symptom data in text format, Output data: symptom data in JSON format

[0567] Step 3:

[0568] The server analyzes the received JSON-formatted symptom data. Using a natural language processing (NLP) model, it extracts keywords from the text data and compares them with a training database. This results in the most relevant first aid method and predicted disease name. Input data: JSON-formatted symptom data, Output data: first aid method, predicted disease name

[0569] Step 4:

[0570] The server converts the generated first aid method based on the analysis results into an augmented reality (AR) format. The augmented reality format data is sent to the smart glasses and visually displayed to the user. Input data: First aid method, Output data: First aid method in augmented reality format

[0571] Step 5:

[0572] The server acquires the user's location information and searches for nearby veterinary clinics based on the location information. The search results for veterinary clinic information are sent to the smart glasses and notified to the user. Input data: User's location information, Output data: Nearby veterinary clinic information

[0573] Step 6:

[0574] The server periodically generates preventive information related to maintaining pet health and early detection of diseases, and notifies the smart glasses. This allows users to periodically receive information useful for managing their pet's health. Input data: Preventive information stored in the server's database. Output data: Preventive information in notification format.

[0575] Step 7:

[0576] The user performs first aid on the pet based on the augmented reality first aid method displayed on the smart glasses. The user also refers to the veterinary clinic information displayed on the smart glasses to quickly access the veterinary clinic. Input data: augmented reality first aid method, veterinary clinic information. Output data: first aid to be performed, location information of the veterinary clinic.

[0577] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0578] overview

[0579] This invention is an AI system that enables pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. It aims to improve the method of presenting first aid procedures and the quality of user support by incorporating an emotion engine that recognizes the user's emotions. This system includes a user interface for inputting the pet's symptoms, a communication means for transmitting symptom data to a server, a data analysis means, a visualization means, a hospital search means, a preventive information provision means, and an emotion engine. Based on the symptoms and emotion information entered by the user, the server provides appropriate first aid procedures and specialized treatment information.

[0580] Program processing

[0581] The program of this system processes as follows:

[0582] 1. User Interface Methods

[0583] The user accesses a terminal and is provided with text boxes and options to input their pet's specific symptoms. The user enters the symptoms in detail and clicks the "Submit" button.

[0584] 2. Means of communication

[0585] The data sent by the user is converted to JSON format by the terminal and sent to the server, which improves data consistency and transmission efficiency.

[0586] 3. Data Analysis Methods

[0587] The server analyzes the received data and uses natural language processing (NLP) to extract keywords from the input text and compare them with a training database to predict the most relevant first aid method and disease name.

[0588] 4. Visualization tools

[0589] The resulting first aid procedures are then converted into visual or video formats. For example, a video can be created demonstrating how to apply a cold towel to an affected area. The video is then displayed on the device for easy user access.

[0590] 5. Hospital search tools

[0591] The server obtains the user's location information, searches for nearby veterinary clinics based on that location, and provides the user with a list of specialized medical facilities that can treat specific symptoms or illnesses.

[0592] 6. Emotion Engine

[0593] The emotion engine analyzes the user's voice input and facial expression data to recognize their emotions. For example, if the user shows signs of anxiety or impatience, it will suggest first aid measures and provide advice on how to calm the user.

[0594] 7. Preventive information provision measures

[0595] The server periodically provides information on pet health maintenance and early disease detection, including advice on how to prevent certain diseases and health management, which is displayed as notifications on the user's device.

[0596] Specific examples

[0597] Example 1: Skin rash

[0598] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes the data and predicts that it is "allergic dermatitis." It also instructs the user on how to provide first aid using a cold towel and recommends a nearby veterinary clinic that specializes in allergies. It also provides visual instructions in the form of a video and periodically notifies users of preventative care information. Furthermore, if the device senses anxiety in the user's voice, it displays reassuring advice.

[0599] Example 2: Difficulty breathing

[0600] The user types, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It provides a video of the appropriate first aid procedure. It also searches for the nearest veterinary hospital that can provide emergency care and instructs the user. The emotion engine recognizes the user's impatience and provides instructions and advice on how to respond calmly.

[0601] In this way, by combining this system with an emotion engine, it is possible to quickly provide appropriate first aid procedures and specialized medical information according to the pet's symptoms, as well as provide appropriate support according to the user's emotional state. This allows pet owners to care for their pets with peace of mind. In addition, by providing information on disease prevention and early detection, it can also contribute to maintaining pet health.

[0602] The processing flow will be explained below.

[0603] Step 1:

[0604] The user opens the application on the device and accesses the "Symptom Input" screen.

[0605] Step 2:

[0606] The user enters the pet's specific symptoms into a text box.

[0607] For example, enter "My pet has a red rash on its skin."

[0608] Step 3:

[0609] The user clicks the "Submit" button to submit the symptom data.

[0610] Step 4:

[0611] The terminal converts the user input data into JSON format.

[0612] For example, it converts to {"symptom": "My pet has a red rash on its skin"}.

[0613] Step 5:

[0614] The terminal transmits the converted data to the server.

[0615] Step 6:

[0616] The server begins the process of parsing the received data.

[0617] Step 7:

[0618] The server uses natural language processing (NLP) to extract keywords from the input text.

[0619] For example, extract keywords such as "skin," "red," and "rash."

[0620] Step 8:

[0621] The server compares the extracted keywords with the learning database and predicts the most relevant disease name.

[0622] As an example, "allergic dermatitis" is predicted.

[0623] Step 9:

[0624] The server retrieves first aid procedures associated with the predicted illness from a database.

[0625] For example, methods such as "cool the affected area with a cold towel" and "consider over-the-counter antihistamines" are obtained.

[0626] Step 10:

[0627] The server converts the first aid procedures into a visual or video format.

[0628] For example, we will generate a video showing the steps to cool an affected area using a cold towel.

[0629] Step 11:

[0630] The server obtains the user's location information and searches for nearby veterinary clinics based on that location.

[0631] Step 12:

[0632] The server generates a list of specialized veterinary clinics and best doctors and constructs the information to be provided to the user.

[0633] Step 13:

[0634] The emotion engine analyzes the user's voice input and facial expression data to recognize emotions.

[0635] For example, if the user is feeling anxious, the emotion of "anxiety" is recognized from the tone of voice and facial expression.

[0636] Step 14:

[0637] Based on the emotion engine's analysis, the server adjusts how first aid procedures are presented.

[0638] For example, for a user who is feeling anxious, gentle words or audio guidance are provided to give a sense of security.

[0639] Step 15:

[0640] The server generates advice based on the emotion recognition results.

[0641] For example, if the user is feeling anxious, the system generates advice such as "Please stay calm. First, calm down and take a deep breath."

[0642] Step 16:

[0643] The server generates a packet containing first aid procedures, disease predictions, veterinary clinic information, and advice based on the patient's emotions, and sends it to the terminal.

[0644] Step 17:

[0645] The device analyzes the data received and displays the "First Aid Procedures" screen.

[0646] Step 18:

[0647] The device displays first aid procedures to the user in visual or video format.

[0648] For example, a video might show "steps to cool the affected area using a cold towel."

[0649] Step 19:

[0650] The device displays a predicted disease name and a list of recommended veterinary clinics.

[0651] For example, it could display something like, "There is a possibility of allergic dermatitis. Nearby veterinary clinics are listed below."

[0652] Step 20:

[0653] The terminal displays advice based on emotion recognition to the user.

[0654] For example, it displays the message, "Please stay calm. First, calm down and take a deep breath."

[0655] Step 21:

[0656] The server regularly updates information on maintaining pet health and early detection of illness and sends it to the device.

[0657] Step 22:

[0658] The device will send a notification to the user informing them that new preventative information is available.

[0659] Step 23:

[0660] The user checks the notification and views the new prevention information.

[0661] For example, information such as "Regular cleaning and avoiding certain foods are important for preventing pet allergies" may be displayed.

[0662] Example 2

[0663] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0664] Providing prompt and accurate first aid for pets suffering from sudden injuries or illness is an important issue for pet owners. Furthermore, there is a need for a means to provide appropriate support and reassurance in situations where pet owners feel anxious or impatient. To address these issues, the present invention aims to provide a system that allows pet owners to input their pet's symptoms and quickly analyzes and responds to them.

[0665] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0666] In this invention, the server includes an information input means for inputting the symptoms of the pet, a communication means for transmitting the input symptom data to the central device, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a display means for displaying the generated first aid method in a visual or video format, a medical facility search means for searching for and providing information on medical facilities specializing in the symptoms, a preventive information provision means for periodically providing information on the prevention and early detection of diseases in pets, and an emotion recognition means for recognizing the user's emotions and providing appropriate first aid methods and advice to reassure the user, thereby enabling quick and accurate first aid for the pet's symptoms and providing a sense of security.

[0667] The "information input means" is a device that provides an interface for the user to input specific symptoms of the pet.

[0668] The "communication means" is a device having a function for transmitting input symptom data to the central device.

[0669] The "data analysis means" is a device for analyzing the received symptom data and generating an appropriate first aid method.

[0670] The "display means" is a device that displays the generated first aid method in a visual or animated format.

[0671] The "medical facility search means" is a device that searches for medical facilities that specialize in symptoms and provides information.

[0672] The "prevention information providing means" is a device that periodically provides information on the prevention and early detection of pet diseases.

[0673] The "emotion recognition means" is a device that recognizes the user's emotions and provides appropriate first aid or advice to reassure the user.

[0674] The "Central Unit" is the main component that analyzes the received data, generates appropriate first aid procedures, and provides information to the user.

[0675] This invention is a system for providing quick and accurate first aid to pets when they suddenly become injured or ill, and also aims to provide appropriate support and peace of mind to pet owners in situations where they feel anxious or impatient.

[0676] A web browser or mobile application can be used as an information input method for users to enter their pet's symptoms. For example, users can open the application and enter their pet's specific symptoms into the text box. Alternatively, they can select options based on the symptoms. Once they have completed the input, they click the "Submit" button.

[0677] The terminal converts the user's input data into JSON format and sends it to a central device (server) via the Internet, which improves data consistency and transfer efficiency.

[0678] The server analyzes the received JSON data. The analysis method used here is natural language processing (NLP) technology. For example, Python and a natural language processing library are used to extract important keywords from the text data. This results in keywords such as "red rash" and "skin." These keywords are compared with a pre-trained database to predict the most relevant disease name and first aid method.

[0679] The server generates first aid procedures based on the analysis results and converts them into a visual or video format. For example, a video showing the procedure of "cooling the affected area with a cold towel" can be shown. Video editing software is used to generate the video. The generated video is sent to the user's device and displayed on the device.

[0680] The server obtains location information from the user's device and searches for nearby medical facilities based on that location. The search results provide a list of medical facilities that can accommodate specific symptoms or illnesses. This list is displayed on the user's device, allowing them to quickly head to the nearest medical facility.

[0681] The server performs voice and facial expression analysis to recognize emotions. Voice input is converted into text using a voice recognition API, and facial expression data is analyzed using facial recognition technology. For example, Google's Cloud Speech-to-Text API can be used for voice analysis, and Microsoft's facial recognition API can be used for facial expression recognition. This allows the server to recognize when a user is anxious or impatient and display advice to reassure the user.

[0682] The server also periodically provides information on pet disease prevention and early detection, including advice on how to prevent specific illnesses and health management, such as "seasonal allergy prevention measures," to the user's device.

[0683] Specific examples

[0684] Example 1: Skin rash

[0685] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes the data and predicts "allergic dermatitis." It then instructs the user on how to provide first aid using a cold towel and recommends a nearby medical facility specializing in allergies. It also provides visual instructions in the form of a video and periodically notifies users of preventive measures. Furthermore, if the device senses anxiety in the user's voice, it displays reassuring advice.

[0686] Example 2: Difficulty breathing

[0687] The user types, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It provides a video of the appropriate first aid procedure. It also searches for the nearest emergency medical facility and instructs the user on the procedure. The emotion engine recognizes the user's impatience and provides instructions and advice on how to respond calmly.

[0688] In this way, by combining an emotion engine, the present invention is a system that provides quick and accurate first aid for pet symptoms and a sense of security. It also contributes to maintaining pet health by providing preventive information.

[0689] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0690] Step 1:

[0691] The user opens the application and enters the specific symptoms of their pet. They use the text boxes and options to enter details about the symptoms and click the "Submit" button.

[0692] Input: Pet's specific symptoms (text format)

[0693] Output: Symptom data sent to the device (text format)

[0694] Specific behavior: The user enters "My pet has a red rash on its skin" into the application and presses the send button.

[0695] Step 2:

[0696] The terminal converts the user's input data into JSON format and sends it to a central device (server) via the Internet.

[0697] Input: Submitted symptom data (text format)

[0698] Output: JSON format data sent to the server

[0699] Specific behavior: The application on the device converts the text "My pet has a red rash on its skin" into JSON format and sends it to the server.

[0700] Step 3:

[0701] The server parses the received JSON data and uses natural language processing (NLP) techniques to extract important keywords from the text data and match them with existing databases to predict the most relevant disease names and first aid methods.

[0702] Input: Symptom data in JSON format

[0703] Output: Prediction results of disease name and first aid method

[0704] Specific operation: The server uses Python and NLP libraries to extract keywords such as "red rash" and "skin" and predicts "allergic dermatitis."

[0705] Step 4:

[0706] The server generates first aid procedures based on the analysis results and converts them into a visual or video format. Editing software is used to convert the first aid procedures into a video and send it to the user's device.

[0707] Input: Disease name and first aid method prediction results

[0708] Output: Visual or video first aid instructions

[0709] Specific operation: The server generates a video showing the steps of "cooling the affected area with a cold towel" and sends it to the user's device.

[0710] Step 5:

[0711] The server obtains location information from the user's terminal and searches for nearby medical facilities based on that location.

[0712] Input: User's location

[0713] Output: A list of symptom-specific medical facilities

[0714] Specific operation: The server acquires the user's location information, generates a list of "allergy specialty medical facilities," and provides it to the user.

[0715] Step 6:

[0716] The emotion recognition means analyzes the user's voice input and facial expression data to recognize the user's emotions. For example, it analyzes the user's voice to recognize anxiety and provide advice accordingly.

[0717] Input: Voice input and facial expression data

[0718] Output: Emotion recognition results and corresponding advice

[0719] How it works: The server converts speech into text using Google's Cloud Speech-to-Text API, analyzes facial expressions using Azure Face API, recognizes anxiety, and displays advice such as "stay calm."

[0720] Step 7:

[0721] The server periodically provides information on maintaining pet health and early detection of illness.

[0722] Input: Pet health data and related information

[0723] Output: Preventive and health care advice

[0724] Specific operation: The server displays notifications such as "Seasonal allergy prevention measures" on the user's device.

[0725] Through the above processing steps, the system can provide users with fast and accurate first aid information and provide a sense of security through emotion recognition.

[0726] (Application example 2)

[0727] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0728] Conventional pet first aid systems have the problem of being unable to quickly provide appropriate treatment methods for pet symptoms and are unable to take into account the feelings of pet owners, which means they are unable to alleviate the anxiety and impatience of pet owners. Furthermore, searching for and providing information on veterinary medical facilities specializing in symptoms is not intuitive, and support is lacking in situations where a quick response is required.

[0729] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for transmitting the input symptom data to the server, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a visualization means for displaying the generated first aid method in a visual or video format, a medical facility search means for searching for and providing information on veterinary medical facilities specializing in the symptoms, a preventive information provision means for periodically providing information on the prevention and early detection of pet diseases, and an emotion recognition means for recognizing the user's emotions and suggesting appropriate first aid methods and providing psychological support. This allows pet owners to quickly and accurately provide appropriate first aid, and by providing psychological support in accordance with the user's emotions, the pet owner's anxiety and impatience can be alleviated, making it possible to more effectively manage the pet's health.

[0730] The "user interface means" is an interface device that the user uses to input the symptoms of the pet.

[0731] "Communication means" refers to the technical means for transmitting the input symptom data to the server.

[0732] The "data analysis means" is a technical means for analyzing the symptom data received by the server and generating an appropriate first aid method.

[0733] A "visualization tool" is a device or technique for displaying the generated first aid instructions in a visual or animated format.

[0734] A "medical facility search tool" is a device or technology for searching for and providing information on veterinary medical facilities that specialize in certain symptoms.

[0735] A "preventive information providing means" is a device or technology that periodically provides information on the prevention and early detection of pet diseases.

[0736] An "emotion recognition means" is a device or technology for recognizing a user's emotions and suggesting appropriate first aid methods or providing psychological support.

[0737] overview

[0738] This invention is an AI system that allows pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. The system analyzes symptom and emotional data entered by the user and provides appropriate first aid. It also searches for nearby veterinary medical facilities and provides information, thereby reducing user anxiety and supporting pet health management.

[0739] User Interface Means

[0740] The user accesses the terminal and inputs the specific symptoms of their pet. To do this, an interface such as text boxes and check boxes is provided. The system also has voice input and facial recognition functions to recognize the user's emotions.

[0741] communication means

[0742] The entered data is converted to JSON format and sent to the server over the Internet, which improves data consistency and transfer efficiency.

[0743] Data Analysis Methods

[0744] The server uses natural language processing (NLP) technology to analyze the received symptom data. Specifically, it extracts keywords from the input text and compares them with a training database to predict the most relevant first aid method and disease name. For emotional data, it uses an emotion recognition engine to analyze the user's feelings, such as anxiety or impatience.

[0745] Visualization tools

[0746] The generated first aid instructions can be displayed on the device in visual or video format. For example, an animation can show the steps for applying a cold towel to an affected area. This video is provided in a user-friendly format.

[0747] Medical facility search tools

[0748] The server searches for nearby veterinary medical facilities based on the user's location information. It then lists medical facilities that can treat specific symptoms or illnesses and provides them to the user. This information is obtained in real time, allowing it to provide the most up-to-date data.

[0749] Preventive information provision methods

[0750] The server periodically provides information on maintaining pet health and early detection of diseases, including advice on how to prevent certain diseases and health management, and provides the information to the user in a timely manner using a notification function.

[0751] emotion recognition means

[0752] The emotion recognition means analyzes the user's voice input and facial expression data to recognize their emotions. For example, if the user shows signs of anxiety or impatience, it will suggest first aid measures to address the situation and provide advice on how to calm down. This function allows the user to respond calmly.

[0753] Examples and prompts

[0754] For example, if a user types "my pet has a red rash on its skin," the system will predict "allergic dermatitis" and provide a video showing first aid using a cold towel. It will also recommend nearby veterinary clinics that specialize in allergies, and its emotion recognition capabilities will sense the user's anxiety and provide reassuring advice.

[0755] Example prompt sentence:

[0756] Input: "My pet has a skin rash."

[0757] output:

[0758] First aid: "Cool the area with a cold towel."

[0759] Veterinary Clinic: "We can connect you to a nearby specialized medical facility."

[0760] Emotional care: "Remain calm. Seek medical attention to determine the cause of the rash."

[0761] This system allows pet owners to provide prompt and appropriate first aid and receive comprehensive support that also takes into consideration the user's emotions.

[0762] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0763] Step 1:

[0764] The user uses the device to input their pet's symptoms. Specifically, they type "My pet has a red rash on its skin" into the text box and click the send button. Based on this input, the system begins initial processing. The user's emotions are also collected through voice input and the camera.

[0765] Input: Pet's specific symptoms (text), user's emotions (voice, facial recognition)

[0766] Output: Input data in JSON format

[0767] Step 2:

[0768] The device converts the input data into JSON format and sends it to the server using a communication method. The internet is used to maintain data consistency and transmit data efficiently.

[0769] Input: User-entered symptoms and emotional information

[0770] Output: JSON data sent to the server

[0771] Step 3:

[0772] The server analyzes the received JSON data, using natural language processing (NLP) technology to analyze symptoms and generate appropriate first aid methods and a predicted illness name based on extracted keywords. An emotion recognition engine analyzes the user's emotions and compares them with a database to determine the appropriate psychological support.

[0773] Input: JSON data (symptoms, emotions)

[0774] Output: First aid methods, predicted illness names, mental support information

[0775] Step 4:

[0776] The server generates the generated first aid method in the form of a video or image through a visualization means. This visualized data is sent to the terminal in a format that is easy for the user to understand. Specifically, a video of "the procedure for cooling the affected area with a cold towel" is generated.

[0777] Input: First Aid Methods

[0778] Output: Video or image data

[0779] Step 5:

[0780] The server uses the user's location information to search for nearby veterinary clinics, compiles a list of clinics that can treat specific symptoms or illnesses, and sends that information to the device. This is done using location services such as Google Maps API.

[0781] Input: User's location information, predicted disease name

[0782] Output: List of veterinary facilities with details

[0783] Step 6:

[0784] The device displays information received from the server, including first aid videos, a list of nearby veterinary clinics, and emotional support information, allowing users to take prompt and appropriate action.

[0785] Input: First aid methods, medical facility information, and mental support information from the server

[0786] Output: A user-accessible visual representation

[0787] Step 7:

[0788] The server periodically sends information about pet disease prevention and early detection to the terminal using the preventive information providing means. This allows the user to obtain a specific action plan for disease prevention and early detection. For example, information such as "methods for preventing allergic dermatitis" is provided.

[0789] Input: Preventive Information

[0790] Output: Providing periodic notifications and preventative information

[0791] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0792] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0793] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0794] [Third embodiment]

[0795] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0796] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0797] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0798] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0799] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0800] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0801] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0802] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0803] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0804] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0805] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0806] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0807] overview

[0808] This invention is an AI system that allows pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. The system includes a user interface for inputting the pet's symptoms, a communication means for transmitting symptom data to a server, a data analysis means, a visualization means, a hospital search means, and a preventive information provision means. Based on the symptoms input by the user, the server provides appropriate first aid procedures and specialized treatment information.

[0809] Program processing

[0810] The program of this system processes as follows:

[0811] 1. User Interface Methods

[0812] The user accesses a terminal and is provided with text boxes and options to input their pet's specific symptoms. The user enters the symptoms in detail and clicks the "Submit" button.

[0813] 2. Means of communication

[0814] The data sent by the user is converted to JSON format by the terminal and sent to the server, which improves data consistency and transmission efficiency.

[0815] 3. Data Analysis Methods

[0816] The server analyzes the received data and uses natural language processing (NLP) to extract keywords from the input text and compare them with a training database to predict the most relevant first aid method and disease name.

[0817] 4. Visualization tools

[0818] The resulting first aid procedures are then converted into visual or video formats. For example, a video can be created demonstrating how to apply a cold towel to an affected area. The video is then displayed on the device for easy user access.

[0819] 5. Hospital search tools

[0820] The server obtains the user's location information, searches for nearby veterinary clinics based on that location, and provides the user with a list of specialized medical facilities that can treat specific symptoms or illnesses.

[0821] 6. Preventive information provision measures

[0822] The server periodically provides information on pet health maintenance and early disease detection, including advice on how to prevent certain diseases and health management, which is displayed as notifications on the user's device.

[0823] Specific examples

[0824] Example 1: Skin rash

[0825] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes it and predicts that it is "allergic dermatitis." The server then instructs the user on how to treat the rash with a cold towel and recommends a nearby veterinary clinic that specializes in allergies. The system also provides visual instructions in a video and periodically notifies users of preventative care information.

[0826] Example 2: Difficulty breathing

[0827] The user enters, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It then provides a video of the appropriate first aid procedure. It also searches for the nearest veterinary hospital that can provide emergency care and directs the user to it.

[0828] In this way, this system can quickly provide appropriate first aid procedures and specialized medical information according to the pet's symptoms, allowing pet owners to care for their pets with peace of mind.In addition, by providing information on disease prevention and early detection, it can also contribute to maintaining pet health.

[0829] The processing flow will be explained below.

[0830] Step 1:

[0831] The user opens the application on the device and accesses the "Symptom Input" screen.

[0832] Step 2:

[0833] The user enters the pet's specific symptoms into a text box.

[0834] For example, enter "My pet has a red rash on its skin."

[0835] Step 3:

[0836] The user clicks the "Submit" button to submit the symptom data.

[0837] Step 4:

[0838] The terminal converts the user input data into JSON format.

[0839] For example, it converts to {"symptom": "My pet has a red rash on its skin"}.

[0840] Step 5:

[0841] The terminal transmits the converted data to the server.

[0842] Step 6:

[0843] The server begins the process of parsing the received data.

[0844] Step 7:

[0845] The server uses natural language processing (NLP) to extract keywords from the input text.

[0846] For example, extract keywords such as "skin," "red," and "rash."

[0847] Step 8:

[0848] The server compares the extracted keywords with the learning database and predicts the most relevant disease name.

[0849] As an example, "allergic dermatitis" is predicted.

[0850] Step 9:

[0851] The server retrieves first aid procedures associated with the predicted illness from a database.

[0852] For example, methods such as "cool the affected area with a cold towel" and "consider over-the-counter antihistamines" are obtained.

[0853] Step 10:

[0854] The server converts the first aid procedures into a visual or video format.

[0855] For example, we will generate a video showing the steps to cool an affected area using a cold towel.

[0856] Step 11:

[0857] The server obtains the user's location information and searches for nearby veterinary clinics based on that location.

[0858] Step 12:

[0859] The server generates a list of specialized veterinary clinics and best doctors and constructs the information to be provided to the user.

[0860] Step 13:

[0861] The server generates a packet that summarizes first aid procedures, disease predictions, and veterinary clinic information and sends it to the terminal.

[0862] Step 14:

[0863] The device analyzes the data received and displays the "First Aid Procedures" screen.

[0864] Step 15:

[0865] The device displays first aid procedures to the user in visual or video format.

[0866] For example, a video might show "steps to cool the affected area using a cold towel."

[0867] Step 16:

[0868] The device displays a predicted disease name and a list of recommended veterinary clinics.

[0869] For example, it could display something like, "There is a possibility of allergic dermatitis. Nearby veterinary clinics are listed below."

[0870] Step 17:

[0871] The server regularly updates information on maintaining pet health and early detection of illness and sends it to the device.

[0872] Step 18:

[0873] The device will send a notification to the user informing them that new preventative information is available.

[0874] Step 19:

[0875] The user checks the notification and views the new prevention information.

[0876] For example, information such as "Regular cleaning and avoiding certain foods are important for preventing pet allergies" may be displayed.

[0877] Example 1

[0878] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0879] Pet owners have limited means to respond quickly and accurately to sudden injuries or illnesses in their pets. It is also often difficult to immediately obtain appropriate first aid and specialized medical information. To solve this problem, a system is needed that allows users to easily input their pet's symptoms and quickly obtain appropriate first aid and specialized medical information.

[0880] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0881] In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for converting the input symptom data into a consistent format and transmitting the data to the server, a data analysis means for analyzing the received symptom data using a machine learning model and predicting an associated disease name and first aid method, a visualization means for displaying the generated first aid method in a visual or video format, a hospital search means for searching for nearby specialized medical facilities based on the user's location information and providing the information, and a prevention information provision means for periodically providing information on the prevention and early detection of pet diseases. This allows appropriate first aid methods and specialized medical information to be quickly provided according to the pet's symptoms, enabling pet owners to care for their pets with peace of mind.

[0882] The "user interface means" refers to an interface that provides text boxes and options for inputting symptoms of a pet, allowing the user to easily input symptoms.

[0883] The "communication method" refers to the method for converting the symptom data entered by the user into a consistent format and sending it to the server. Specifically, the data is converted into JSON format and a communication protocol such as an HTTP POST request is used.

[0884] The "data analysis means" is a means for analyzing the symptom data received by the server using machine learning models and natural language processing, extracting keywords from the input text, and comparing them with a learning database to predict the optimal first aid method and disease name.

[0885] The "visualization means" refers to a means for converting the first aid procedures and methods generated based on the data analysis into a visual or video format and displaying them in a way that is easily understandable to the user, for example, by using a video generation library or a graphics library.

[0886] "Hospital search means" refers to a means of searching for nearby specialized medical facilities and veterinary clinics using the user's location information and providing that information to the user. Specifically, search results are obtained using a local search API.

[0887] The "prevention information provision means" is a means by which a server periodically generates information on pet disease prevention and early detection and sends it to the user's device as a news feed or push notification. For example, it uses a notification system such as Firebase Cloud Messaging.

[0888] A "machine learning model" is an algorithm or framework that learns patterns from data to make predictions and classifications, and is used to analyze pet symptom data.

[0889] "JSON format" is an abbreviation for JavaScript Object Notation, and is a data format that represents data in text format and enables consistent data exchange.

[0890] The present invention relates to an AI system that enables pet owners to provide quick and accurate first aid to their pets when they suddenly become injured or become ill. This system is realized using the following means.

[0891] First, the user accesses the terminal and is provided with text boxes and options to input the specific symptoms of their pet. The user enters the symptoms in detail and clicks the "Submit" button. For example, the user may enter "My pet has developed a red rash on its skin."

[0892] The terminal then converts the data entered by the user into JSON format and sends it to the server using a data communication protocol, which ensures data consistency and improves transfer efficiency.

[0893] The server analyzes the received data using a natural language processing (NLP) engine. At this stage, keywords are extracted from the input text and compared with a built-in learning database. This allows the system to predict the most appropriate first aid method and diagnosis. Specific software used is the machine learning frameworks PyTorch and TensorFlow.

[0894] Furthermore, the server creates first aid procedures based on the results of the data analysis. These procedures are converted into videos and diagrams for easy visual understanding. For example, a video showing the procedure for cooling the affected area with a cold towel can be created. Video generation libraries (e.g., FFmpeg) and graphics libraries (e.g., p5.js) are used to generate these videos.

[0895] The device receives the video and illustrations of first aid procedures sent from the server and displays them to the user, who can then take appropriate first aid. A user interface framework (e.g., React.js or Vue.js) is used for displaying the information.

[0896] The server also obtains the user's location information and searches for nearby veterinary clinics based on that location. Using a local search API (e.g., Google Places API), it generates a list of clinics that can handle specific symptoms or illnesses and provides it to the user. For example, if the user enters "my pet is having difficulty breathing," it determines that oxygen supply is required and searches for the nearest veterinary clinic that can provide emergency care, providing the information.

[0897] The server then periodically provides information about pet health maintenance and early disease detection. This information is sent to the user's device as a news feed or push notification, and includes advice on disease prevention and health management. This is done using a periodic query and notification system (e.g., Firebase Cloud Messaging).

[0898] As a specific example, if a user inputs "My pet has a red rash on its skin," the device sends this data to the server. The server analyzes the data, predicts it is allergic dermatitis, generates a video showing first aid using a cold towel, and provides instructions to the user. It also searches for and lists nearby veterinary clinics specializing in allergies, and provides this to the user. On the other hand, if the user inputs "My pet is having difficulty breathing," it determines that oxygen supply is necessary, generates a video showing appropriate first aid, and searches for the nearest veterinary clinic that can provide emergency care.

[0899] In this way, this system quickly provides appropriate first aid methods and specialized medical information according to the pet's symptoms, allowing pet owners to care for their pets with peace of mind. In addition, the regular provision of information also contributes to maintaining the health of pets.

[0900] An example of a prompt is as follows:

[0901] "My pet has a red rash on its skin"

[0902] "My pet is having difficulty breathing"

[0903] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0904] Step 1:

[0905] The user accesses the terminal and inputs the specific symptoms of their pet. The user interface provides text boxes and options for entering the symptoms in detail. When the "Submit" button is clicked, the terminal retrieves the input data. The input is symptom data in text format, and the output is the symptom data itself.

[0906] Step 2:

[0907] The device converts the symptom data entered by the user into JSON format. The converted data is consistent and suitable for communication. Here, the input is symptom data in text format, and the output is data in JSON format. Specifically, the data conversion is performed using a JavaScript library.

[0908] Step 3:

[0909] The terminal sends data to the server using a communication protocol (for example, an HTTP POST request). At this stage, the input is JSON-formatted data, and the output is status information indicating that transmission to the server has been completed. HTTPS communication is used for data transfer, ensuring security.

[0910] Step 4:

[0911] The server receives the JSON-formatted data sent from the device. It then analyzes the data using a natural language processing (NLP) engine. The input is JSON-formatted data, and the output is symptom data with extracted keywords. Here, analysis is performed using a machine learning model (e.g., PyTorch or TensorFlow).

[0912] Step 5:

[0913] After extracting keywords, the server compares them with the learning database to predict the most relevant first aid method and disease name. The input is symptom data from which keywords have been extracted, and the output is first aid methods and predicted disease names. Past data and specialized knowledge are incorporated into the predictions.

[0914] Step 6:

[0915] The server creates first aid procedures based on the analysis results. These procedures are converted into videos and diagrams for easy visual understanding. The input is the first aid method and the name of the disease, and the output is the procedure in video or diagram format. Specifically, a video generation library (e.g., FFmpeg) and a graphics library (e.g., p5.js) are used.

[0916] Step 7:

[0917] The device receives the video or diagram of the first aid procedure sent from the server and displays it to the user. The user can then view it and take appropriate first aid. Here, the input is the video or diagram format of the procedure, and the output is the displayed information. A user interface framework (e.g., React.js or Vue.js) is used for display.

[0918] Step 8:

[0919] The server obtains the user's location information and searches for nearby veterinary clinics based on that location. The input is the user's location information and the output is the search results. A local search API (e.g., Google Places API) is used to provide the user with the most suitable clinic information.

[0920] Step 9:

[0921] The server periodically generates information on maintaining pet health and early disease detection, and sends it to the user's device as a news feed or push notification. The input is disease prevention information and health management advice, and the output is the notified information. Notifications are sent using Firebase Cloud Messaging and other technologies to ensure that information reaches the user reliably.

[0922] (Application example 1)

[0923] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0924] When a pet suddenly becomes injured or becomes unwell, it is difficult for pet owners to provide first aid quickly and accurately. It is also difficult to quickly find an appropriate medical institution that responds to the pet's symptoms. Furthermore, first aid methods are not presented visually in an easy-to-understand manner, which can make it difficult to actually carry them out. The present invention aims to solve these problems and enable pet owners to easily access the information they need.

[0925] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0926] In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for transmitting the input symptom data to the server, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a visualization means for displaying the generated first aid method visually or in video format in an augmented reality format, a hospital search means for searching for and providing information on veterinary clinics specializing in the symptoms, a means for providing information on nearby veterinary clinics based on the analysis results, and a prevention information provision means for periodically providing information on the prevention and early detection of diseases in pets. This makes it possible to provide appropriate first aid instructions according to the pet's symptoms visually through augmented reality, and also allows instant access to information on nearby veterinary clinics, enabling rapid response.

[0927] The "user interface means" is a function that provides text boxes and options for the user to input symptoms of their pet.

[0928] "Communication means" refers to a technique for transmitting input symptom data to a server.

[0929] The "data analysis means" is a function that analyzes the received symptom data and generates an appropriate first aid method and disease name.

[0930] The "visualization means" refers to a technology for visually displaying the generated first aid method in an augmented reality format or a video format.

[0931] The "hospital search tool" is a function that searches for veterinary hospitals that specialize in symptoms and provides information about them.

[0932] The "location information means" is a technology for acquiring the user's location information and searching for nearby veterinary clinics based on that information.

[0933] The "prevention information provision means" is a function that periodically provides information on the prevention and early detection of pet diseases.

[0934] "Augmented reality" is a technology that displays digital information overlaid on real-world information.

[0935] The present invention provides a system that enables pet owners to quickly and accurately provide first aid to their pets when they are injured or in poor health. An embodiment of the system will be described in detail below.

[0936] First, the user puts on the smart glasses and voice-inputs the specific symptoms of their pet. The smart glasses have a built-in voice recognition function that can convert the voice-input symptoms into text, allowing the user to easily communicate the symptoms to the system.

[0937] Next, the communication means installed in the smart glasses converts the input symptom data into JSON format and sends it to the server. The communication means requires a high-speed and stable internet connection.

[0938] The server uses a natural language processing (NLP) model to analyze the received symptom data. It extracts keywords from the input text data and compares them with a past learning database based on these keywords to generate the most relevant first aid method and predicted disease name. This data analysis method makes it possible to provide appropriate first aid methods.

[0939] The generated first aid instructions are visualized in augmented reality (AR) and displayed on the user's smart glasses, allowing the user to see specific treatment procedures for their pet superimposed on the real world. For example, a first aid instruction such as "cool the affected area with a cold towel" is visually displayed in AR.

[0940] The server also obtains the user's location information and searches for nearby veterinary clinics based on that location. The search results are displayed on the smart glasses, allowing the user to quickly access the nearest veterinary clinic. At the same time, the preventive information provider also regularly provides information on maintaining pet health and early detection of illnesses.

[0941] For example, if a user says, "My pet is having difficulty breathing," the server quickly analyzes the data and determines that oxygen is needed. As a result, the necessary first aid instructions are displayed in AR format on the smart glasses, along with information about the nearest veterinary clinic.

[0942] An example of a prompt for a generative AI model is as follows:

[0943] "My pet suddenly started having difficulty breathing. Please tell me first aid procedures and the nearest veterinary clinic."

[0944] As described above, the present invention enables quick and accurate responses to pet ailments, allowing owners to care for their pets with peace of mind. In addition, the function of providing preventive information contributes to maintaining the health of pets.

[0945] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0946] Step 1:

[0947] The user wears the smart glasses and inputs their pet's symptoms by voice. The input voice is converted into text data by the voice recognition system in the smart glasses. Input data: User's voice information, Output data: Symptom data in text format

[0948] Step 2:

[0949] The symptom information converted into text data is converted into JSON format by the smart glasses' communication means and sent to a server via the Internet. Input data: symptom data in text format, Output data: symptom data in JSON format

[0950] Step 3:

[0951] The server analyzes the received JSON-formatted symptom data. Using a natural language processing (NLP) model, it extracts keywords from the text data and compares them with a training database. This results in the most relevant first aid method and predicted disease name. Input data: JSON-formatted symptom data, Output data: first aid method, predicted disease name

[0952] Step 4:

[0953] The server converts the generated first aid method based on the analysis results into an augmented reality (AR) format. The augmented reality format data is sent to the smart glasses and visually displayed to the user. Input data: First aid method, Output data: First aid method in augmented reality format

[0954] Step 5:

[0955] The server acquires the user's location information and searches for nearby veterinary clinics based on the location information. The search results for veterinary clinic information are sent to the smart glasses and notified to the user. Input data: User's location information, Output data: Nearby veterinary clinic information

[0956] Step 6:

[0957] The server periodically generates preventive information related to maintaining pet health and early detection of diseases, and notifies the smart glasses. This allows users to periodically receive information useful for managing their pet's health. Input data: Preventive information stored in the server's database. Output data: Preventive information in notification format.

[0958] Step 7:

[0959] The user performs first aid on the pet based on the augmented reality first aid method displayed on the smart glasses. The user also refers to the veterinary clinic information displayed on the smart glasses to quickly access the veterinary clinic. Input data: augmented reality first aid method, veterinary clinic information. Output data: first aid to be performed, location information of the veterinary clinic.

[0960] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0961] overview

[0962] This invention is an AI system that enables pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. It aims to improve the method of presenting first aid procedures and the quality of user support by incorporating an emotion engine that recognizes the user's emotions. This system includes a user interface for inputting the pet's symptoms, a communication means for transmitting symptom data to a server, a data analysis means, a visualization means, a hospital search means, a preventive information provision means, and an emotion engine. Based on the symptoms and emotion information entered by the user, the server provides appropriate first aid procedures and specialized treatment information.

[0963] Program processing

[0964] The program of this system processes as follows:

[0965] 1. User Interface Methods

[0966] The user accesses a terminal and is provided with text boxes and options to input their pet's specific symptoms. The user enters the symptoms in detail and clicks the "Submit" button.

[0967] 2. Means of communication

[0968] The data sent by the user is converted to JSON format by the terminal and sent to the server, which improves data consistency and transmission efficiency.

[0969] 3. Data Analysis Methods

[0970] The server analyzes the received data and uses natural language processing (NLP) to extract keywords from the input text and compare them with a training database to predict the most relevant first aid method and disease name.

[0971] 4. Visualization tools

[0972] The resulting first aid procedures are then converted into visual or video formats. For example, a video can be created demonstrating how to apply a cold towel to an affected area. The video is then displayed on the device for easy user access.

[0973] 5. Hospital search tools

[0974] The server obtains the user's location information, searches for nearby veterinary clinics based on that location, and provides the user with a list of specialized medical facilities that can treat specific symptoms or illnesses.

[0975] 6. Emotion Engine

[0976] The emotion engine analyzes the user's voice input and facial expression data to recognize their emotions. For example, if the user shows signs of anxiety or impatience, it will suggest first aid measures and provide advice on how to calm the user.

[0977] 7. Preventive information provision measures

[0978] The server periodically provides information on pet health maintenance and early disease detection, including advice on how to prevent certain diseases and health management, which is displayed as notifications on the user's device.

[0979] Specific examples

[0980] Example 1: Skin rash

[0981] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes the data and predicts that it is "allergic dermatitis." It also instructs the user on how to provide first aid using a cold towel and recommends a nearby veterinary clinic that specializes in allergies. It also provides visual instructions in the form of a video and periodically notifies users of preventative care information. Furthermore, if the device senses anxiety in the user's voice, it displays reassuring advice.

[0982] Example 2: Difficulty breathing

[0983] The user types, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It provides a video of the appropriate first aid procedure. It also searches for the nearest veterinary hospital that can provide emergency care and instructs the user. The emotion engine recognizes the user's impatience and provides instructions and advice on how to respond calmly.

[0984] In this way, by combining this system with an emotion engine, it is possible to quickly provide appropriate first aid procedures and specialized medical information according to the pet's symptoms, as well as provide appropriate support according to the user's emotional state. This allows pet owners to care for their pets with peace of mind. In addition, by providing information on disease prevention and early detection, it can also contribute to maintaining pet health.

[0985] The processing flow will be explained below.

[0986] Step 1:

[0987] The user opens the application on the device and accesses the "Symptom Input" screen.

[0988] Step 2:

[0989] The user enters the pet's specific symptoms into a text box.

[0990] For example, enter "My pet has a red rash on its skin."

[0991] Step 3:

[0992] The user clicks the "Submit" button to submit the symptom data.

[0993] Step 4:

[0994] The terminal converts the user input data into JSON format.

[0995] For example, it converts to {"symptom": "My pet has a red rash on its skin"}.

[0996] Step 5:

[0997] The terminal transmits the converted data to the server.

[0998] Step 6:

[0999] The server begins the process of parsing the received data.

[1000] Step 7:

[1001] The server uses natural language processing (NLP) to extract keywords from the input text.

[1002] For example, extract keywords such as "skin," "red," and "rash."

[1003] Step 8:

[1004] The server compares the extracted keywords with the learning database and predicts the most relevant disease name.

[1005] As an example, "allergic dermatitis" is predicted.

[1006] Step 9:

[1007] The server retrieves first aid procedures associated with the predicted illness from a database.

[1008] For example, methods such as "cool the affected area with a cold towel" and "consider over-the-counter antihistamines" are obtained.

[1009] Step 10:

[1010] The server converts the first aid procedures into a visual or video format.

[1011] For example, we will generate a video showing the steps to cool an affected area using a cold towel.

[1012] Step 11:

[1013] The server obtains the user's location information and searches for nearby veterinary clinics based on that location.

[1014] Step 12:

[1015] The server generates a list of specialized veterinary clinics and best doctors and constructs the information to be provided to the user.

[1016] Step 13:

[1017] The emotion engine analyzes the user's voice input and facial expression data to recognize emotions.

[1018] For example, if the user is feeling anxious, the emotion of "anxiety" is recognized from the tone of voice and facial expression.

[1019] Step 14:

[1020] Based on the emotion engine's analysis, the server adjusts how first aid procedures are presented.

[1021] For example, for a user who is feeling anxious, gentle words or audio guidance are provided to give a sense of security.

[1022] Step 15:

[1023] The server generates advice based on the emotion recognition results.

[1024] For example, if the user is feeling anxious, the system generates advice such as "Please stay calm. First, calm down and take a deep breath."

[1025] Step 16:

[1026] The server generates a packet containing first aid procedures, disease predictions, veterinary clinic information, and advice based on the patient's emotions, and sends it to the terminal.

[1027] Step 17:

[1028] The device analyzes the data received and displays the "First Aid Procedures" screen.

[1029] Step 18:

[1030] The device displays first aid procedures to the user in visual or video format.

[1031] For example, a video might show "steps to cool the affected area using a cold towel."

[1032] Step 19:

[1033] The device displays a predicted disease name and a list of recommended veterinary clinics.

[1034] For example, it could display something like, "There is a possibility of allergic dermatitis. Nearby veterinary clinics are listed below."

[1035] Step 20:

[1036] The terminal displays advice based on emotion recognition to the user.

[1037] For example, it displays the message, "Please stay calm. First, calm down and take a deep breath."

[1038] Step 21:

[1039] The server regularly updates information on maintaining pet health and early detection of illness and sends it to the device.

[1040] Step 22:

[1041] The device will send a notification to the user informing them that new preventative information is available.

[1042] Step 23:

[1043] The user checks the notification and views the new prevention information.

[1044] For example, information such as "Regular cleaning and avoiding certain foods are important for preventing pet allergies" may be displayed.

[1045] Example 2

[1046] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1047] Providing prompt and accurate first aid for pets suffering from sudden injuries or illness is an important issue for pet owners. Furthermore, there is a need for a means to provide appropriate support and reassurance in situations where pet owners feel anxious or impatient. To address these issues, the present invention aims to provide a system that allows pet owners to input their pet's symptoms and quickly analyzes and responds to them.

[1048] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1049] In this invention, the server includes an information input means for inputting the symptoms of the pet, a communication means for transmitting the input symptom data to the central device, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a display means for displaying the generated first aid method in a visual or video format, a medical facility search means for searching for and providing information on medical facilities specializing in the symptoms, a preventive information provision means for periodically providing information on the prevention and early detection of diseases in pets, and an emotion recognition means for recognizing the user's emotions and providing appropriate first aid methods and advice to reassure the user, thereby enabling quick and accurate first aid for the pet's symptoms and providing a sense of security.

[1050] The "information input means" is a device that provides an interface for the user to input specific symptoms of the pet.

[1051] The "communication means" is a device having a function for transmitting input symptom data to the central device.

[1052] The "data analysis means" is a device for analyzing the received symptom data and generating an appropriate first aid method.

[1053] The "display means" is a device that displays the generated first aid method in a visual or animated format.

[1054] The "medical facility search means" is a device that searches for medical facilities that specialize in symptoms and provides information.

[1055] The "prevention information providing means" is a device that periodically provides information on the prevention and early detection of pet diseases.

[1056] The "emotion recognition means" is a device that recognizes the user's emotions and provides appropriate first aid or advice to reassure the user.

[1057] The "Central Unit" is the main component that analyzes the received data, generates appropriate first aid procedures, and provides information to the user.

[1058] This invention is a system for providing quick and accurate first aid to pets when they suddenly become injured or ill, and also aims to provide appropriate support and peace of mind to pet owners in situations where they feel anxious or impatient.

[1059] A web browser or mobile application can be used as an information input method for users to enter their pet's symptoms. For example, users can open the application and enter their pet's specific symptoms into the text box. Alternatively, they can select options based on the symptoms. Once they have completed the input, they click the "Submit" button.

[1060] The terminal converts the user's input data into JSON format and sends it to a central device (server) via the Internet, which improves data consistency and transfer efficiency.

[1061] The server analyzes the received JSON data. The analysis method used here is natural language processing (NLP) technology. For example, Python and a natural language processing library are used to extract important keywords from the text data. This results in keywords such as "red rash" and "skin." These keywords are compared with a pre-trained database to predict the most relevant disease name and first aid method.

[1062] The server generates first aid procedures based on the analysis results and converts them into a visual or video format. For example, a video showing the procedure of "cooling the affected area with a cold towel" can be shown. Video editing software is used to generate the video. The generated video is sent to the user's device and displayed on the device.

[1063] The server obtains location information from the user's device and searches for nearby medical facilities based on that location. The search results provide a list of medical facilities that can accommodate specific symptoms or illnesses. This list is displayed on the user's device, allowing them to quickly head to the nearest medical facility.

[1064] The server performs voice and facial expression analysis to recognize emotions. Voice input is converted into text using a voice recognition API, and facial expression data is analyzed using facial recognition technology. For example, Google's Cloud Speech-to-Text API can be used for voice analysis, and Microsoft's facial recognition API can be used for facial expression recognition. This allows the server to recognize when a user is anxious or impatient and display advice to reassure the user.

[1065] The server also periodically provides information on pet disease prevention and early detection, including advice on how to prevent specific illnesses and health management, such as "seasonal allergy prevention measures," to the user's device.

[1066] Specific examples

[1067] Example 1: Skin rash

[1068] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes the data and predicts "allergic dermatitis." It then instructs the user on how to provide first aid using a cold towel and recommends a nearby medical facility specializing in allergies. It also provides visual instructions in the form of a video and periodically notifies users of preventive measures. Furthermore, if the device senses anxiety in the user's voice, it displays reassuring advice.

[1069] Example 2: Difficulty breathing

[1070] The user types, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It provides a video of the appropriate first aid procedure. It also searches for the nearest emergency medical facility and instructs the user on the procedure. The emotion engine recognizes the user's impatience and provides instructions and advice on how to respond calmly.

[1071] In this way, by combining an emotion engine, the present invention is a system that provides quick and accurate first aid for pet symptoms and a sense of security. It also contributes to maintaining pet health by providing preventive information.

[1072] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1073] Step 1:

[1074] The user opens the application and enters the specific symptoms of their pet. They use the text boxes and options to enter details about the symptoms and click the "Submit" button.

[1075] Input: Pet's specific symptoms (text format)

[1076] Output: Symptom data sent to the device (text format)

[1077] Specific behavior: The user enters "My pet has a red rash on its skin" into the application and presses the send button.

[1078] Step 2:

[1079] The terminal converts the user's input data into JSON format and sends it to a central device (server) via the Internet.

[1080] Input: Submitted symptom data (text format)

[1081] Output: JSON format data sent to the server

[1082] Specific behavior: The application on the device converts the text "My pet has a red rash on its skin" into JSON format and sends it to the server.

[1083] Step 3:

[1084] The server parses the received JSON data and uses natural language processing (NLP) techniques to extract important keywords from the text data and match them with existing databases to predict the most relevant disease names and first aid methods.

[1085] Input: Symptom data in JSON format

[1086] Output: Prediction results of disease name and first aid method

[1087] Specific operation: The server uses Python and NLP libraries to extract keywords such as "red rash" and "skin" and predicts "allergic dermatitis."

[1088] Step 4:

[1089] The server generates first aid procedures based on the analysis results and converts them into a visual or video format. Editing software is used to convert the first aid procedures into a video and send it to the user's device.

[1090] Input: Disease name and first aid method prediction results

[1091] Output: Visual or video first aid instructions

[1092] Specific operation: The server generates a video showing the steps of "cooling the affected area with a cold towel" and sends it to the user's device.

[1093] Step 5:

[1094] The server obtains location information from the user's terminal and searches for nearby medical facilities based on that location.

[1095] Input: User's location

[1096] Output: A list of symptom-specific medical facilities

[1097] Specific operation: The server acquires the user's location information, generates a list of "allergy specialty medical facilities," and provides it to the user.

[1098] Step 6:

[1099] The emotion recognition means analyzes the user's voice input and facial expression data to recognize the user's emotions. For example, it analyzes the user's voice to recognize anxiety and provide advice accordingly.

[1100] Input: Voice input and facial expression data

[1101] Output: Emotion recognition results and corresponding advice

[1102] How it works: The server converts speech into text using Google's Cloud Speech-to-Text API, analyzes facial expressions using Azure Face API, recognizes anxiety, and displays advice such as "stay calm."

[1103] Step 7:

[1104] The server periodically provides information on maintaining pet health and early detection of illness.

[1105] Input: Pet health data and related information

[1106] Output: Preventive and health care advice

[1107] Specific operation: The server displays notifications such as "Seasonal allergy prevention measures" on the user's device.

[1108] Through the above processing steps, the system can provide users with fast and accurate first aid information and provide a sense of security through emotion recognition.

[1109] (Application example 2)

[1110] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1111] Conventional pet first aid systems have the problem of being unable to quickly provide appropriate treatment methods for pet symptoms and are unable to take into account the feelings of pet owners, which means they are unable to alleviate the anxiety and impatience of pet owners. Furthermore, searching for and providing information on veterinary medical facilities specializing in symptoms is not intuitive, and support is lacking in situations where a quick response is required.

[1112] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for transmitting the input symptom data to the server, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a visualization means for displaying the generated first aid method in a visual or video format, a medical facility search means for searching for and providing information on veterinary medical facilities specializing in the symptoms, a preventive information provision means for periodically providing information on the prevention and early detection of pet diseases, and an emotion recognition means for recognizing the user's emotions and suggesting appropriate first aid methods and providing psychological support. This allows pet owners to quickly and accurately provide appropriate first aid, and by providing psychological support in accordance with the user's emotions, the pet owner's anxiety and impatience can be alleviated, making it possible to more effectively manage the pet's health.

[1113] The "user interface means" is an interface device that the user uses to input the symptoms of the pet.

[1114] "Communication means" refers to the technical means for transmitting the input symptom data to the server.

[1115] The "data analysis means" is a technical means for analyzing the symptom data received by the server and generating an appropriate first aid method.

[1116] A "visualization tool" is a device or technique for displaying the generated first aid instructions in a visual or animated format.

[1117] A "medical facility search tool" is a device or technology for searching for and providing information on veterinary medical facilities that specialize in certain symptoms.

[1118] A "preventive information providing means" is a device or technology that periodically provides information on the prevention and early detection of pet diseases.

[1119] An "emotion recognition means" is a device or technology for recognizing a user's emotions and suggesting appropriate first aid methods or providing psychological support.

[1120] overview

[1121] This invention is an AI system that allows pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. The system analyzes symptom and emotional data entered by the user and provides appropriate first aid. It also searches for nearby veterinary medical facilities and provides information, thereby reducing user anxiety and supporting pet health management.

[1122] User Interface Means

[1123] The user accesses the terminal and inputs the specific symptoms of their pet. To do this, an interface such as text boxes and check boxes is provided. The system also has voice input and facial recognition functions to recognize the user's emotions.

[1124] communication means

[1125] The entered data is converted to JSON format and sent to the server over the Internet, which improves data consistency and transfer efficiency.

[1126] Data Analysis Methods

[1127] The server uses natural language processing (NLP) technology to analyze the received symptom data. Specifically, it extracts keywords from the input text and compares them with a training database to predict the most relevant first aid method and disease name. For emotional data, it uses an emotion recognition engine to analyze the user's feelings, such as anxiety or impatience.

[1128] Visualization tools

[1129] The generated first aid instructions can be displayed on the device in visual or video format. For example, an animation can show the steps for applying a cold towel to an affected area. This video is provided in a user-friendly format.

[1130] Medical facility search tools

[1131] The server searches for nearby veterinary medical facilities based on the user's location information. It then lists medical facilities that can treat specific symptoms or illnesses and provides them to the user. This information is obtained in real time, allowing it to provide the most up-to-date data.

[1132] Preventive information provision methods

[1133] The server periodically provides information on maintaining pet health and early detection of diseases, including advice on how to prevent certain diseases and health management, and provides the information to the user in a timely manner using a notification function.

[1134] emotion recognition means

[1135] The emotion recognition means analyzes the user's voice input and facial expression data to recognize their emotions. For example, if the user shows signs of anxiety or impatience, it will suggest first aid measures to address the situation and provide advice on how to calm down. This function allows the user to respond calmly.

[1136] Examples and prompts

[1137] For example, if a user types "my pet has a red rash on its skin," the system will predict "allergic dermatitis" and provide a video showing first aid using a cold towel. It will also recommend nearby veterinary clinics that specialize in allergies, and its emotion recognition capabilities will sense the user's anxiety and provide reassuring advice.

[1138] Example prompt sentence:

[1139] Input: "My pet has a skin rash."

[1140] output:

[1141] First aid: "Cool the area with a cold towel."

[1142] Veterinary Clinic: "We can connect you to a nearby specialized medical facility."

[1143] Emotional care: "Remain calm. Seek medical attention to determine the cause of the rash."

[1144] This system allows pet owners to provide prompt and appropriate first aid and receive comprehensive support that also takes into consideration the user's emotions.

[1145] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1146] Step 1:

[1147] The user uses the device to input their pet's symptoms. Specifically, they type "My pet has a red rash on its skin" into the text box and click the send button. Based on this input, the system begins initial processing. The user's emotions are also collected through voice input and the camera.

[1148] Input: Pet's specific symptoms (text), user's emotions (voice, facial recognition)

[1149] Output: Input data in JSON format

[1150] Step 2:

[1151] The device converts the input data into JSON format and sends it to the server using a communication method. The internet is used to maintain data consistency and transmit data efficiently.

[1152] Input: User-entered symptoms and emotional information

[1153] Output: JSON data sent to the server

[1154] Step 3:

[1155] The server analyzes the received JSON data, using natural language processing (NLP) technology to analyze symptoms and generate appropriate first aid methods and a predicted illness name based on extracted keywords. An emotion recognition engine analyzes the user's emotions and compares them with a database to determine the appropriate psychological support.

[1156] Input: JSON data (symptoms, emotions)

[1157] Output: First aid methods, predicted illness names, mental support information

[1158] Step 4:

[1159] The server generates the generated first aid method in the form of a video or image through a visualization means. This visualized data is sent to the terminal in a format that is easy for the user to understand. Specifically, a video of "the procedure for cooling the affected area with a cold towel" is generated.

[1160] Input: First Aid Methods

[1161] Output: Video or image data

[1162] Step 5:

[1163] The server uses the user's location information to search for nearby veterinary clinics, compiles a list of clinics that can treat specific symptoms or illnesses, and sends that information to the device. This is done using location services such as Google Maps API.

[1164] Input: User's location information, predicted disease name

[1165] Output: List of veterinary facilities with details

[1166] Step 6:

[1167] The device displays information received from the server, including first aid videos, a list of nearby veterinary clinics, and emotional support information, allowing users to take prompt and appropriate action.

[1168] Input: First aid methods, medical facility information, and mental support information from the server

[1169] Output: A user-accessible visual representation

[1170] Step 7:

[1171] The server periodically sends information about pet disease prevention and early detection to the terminal using the preventive information providing means. This allows the user to obtain a specific action plan for disease prevention and early detection. For example, information such as "methods for preventing allergic dermatitis" is provided.

[1172] Input: Preventive Information

[1173] Output: Providing periodic notifications and preventative information

[1174] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1175] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1176] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1177] [Fourth embodiment]

[1178] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1179] 7, a 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.

[1180] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1181] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1182] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1183] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1184] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1185] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1186] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1187] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1188] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1189] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1190] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1191] overview

[1192] This invention is an AI system that allows pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. The system includes a user interface for inputting the pet's symptoms, a communication means for transmitting symptom data to a server, a data analysis means, a visualization means, a hospital search means, and a preventive information provision means. Based on the symptoms input by the user, the server provides appropriate first aid procedures and specialized treatment information.

[1193] Program processing

[1194] The program of this system processes as follows:

[1195] 1. User Interface Methods

[1196] The user accesses a terminal and is provided with text boxes and options to input their pet's specific symptoms. The user enters the symptoms in detail and clicks the "Submit" button.

[1197] 2. Means of communication

[1198] The data sent by the user is converted to JSON format by the terminal and sent to the server, which improves data consistency and transmission efficiency.

[1199] 3. Data Analysis Methods

[1200] The server analyzes the received data and uses natural language processing (NLP) to extract keywords from the input text and compare them with a training database to predict the most relevant first aid method and disease name.

[1201] 4. Visualization tools

[1202] The resulting first aid procedures are then converted into visual or video formats. For example, a video can be created demonstrating how to apply a cold towel to an affected area. The video is then displayed on the device for easy user access.

[1203] 5. Hospital search tools

[1204] The server obtains the user's location information, searches for nearby veterinary clinics based on that location, and provides the user with a list of specialized medical facilities that can treat specific symptoms or illnesses.

[1205] 6. Preventive information provision measures

[1206] The server periodically provides information on pet health maintenance and early disease detection, including advice on how to prevent certain diseases and health management, which is displayed as notifications on the user's device.

[1207] Specific examples

[1208] Example 1: Skin rash

[1209] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes it and predicts that it is "allergic dermatitis." The server then instructs the user on how to treat the rash with a cold towel and recommends a nearby veterinary clinic that specializes in allergies. The system also provides visual instructions in a video and periodically notifies users of preventative care information.

[1210] Example 2: Difficulty breathing

[1211] The user enters, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It then provides a video of the appropriate first aid procedure. It also searches for the nearest veterinary hospital that can provide emergency care and directs the user to it.

[1212] In this way, this system can quickly provide appropriate first aid procedures and specialized medical information according to the pet's symptoms, allowing pet owners to care for their pets with peace of mind.In addition, by providing information on disease prevention and early detection, it can also contribute to maintaining pet health.

[1213] The processing flow will be explained below.

[1214] Step 1:

[1215] The user opens the application on the device and accesses the "Symptom Input" screen.

[1216] Step 2:

[1217] The user enters the pet's specific symptoms into a text box.

[1218] For example, enter "My pet has a red rash on its skin."

[1219] Step 3:

[1220] The user clicks the "Submit" button to submit the symptom data.

[1221] Step 4:

[1222] The terminal converts the user input data into JSON format.

[1223] For example, it converts to {"symptom": "My pet has a red rash on its skin"}.

[1224] Step 5:

[1225] The terminal transmits the converted data to the server.

[1226] Step 6:

[1227] The server begins the process of parsing the received data.

[1228] Step 7:

[1229] The server uses natural language processing (NLP) to extract keywords from the input text.

[1230] For example, extract keywords such as "skin," "red," and "rash."

[1231] Step 8:

[1232] The server compares the extracted keywords with the learning database and predicts the most relevant disease name.

[1233] As an example, "allergic dermatitis" is predicted.

[1234] Step 9:

[1235] The server retrieves first aid procedures associated with the predicted illness from a database.

[1236] For example, methods such as "cool the affected area with a cold towel" and "consider over-the-counter antihistamines" are obtained.

[1237] Step 10:

[1238] The server converts the first aid procedures into a visual or video format.

[1239] For example, we will generate a video showing the steps to cool an affected area using a cold towel.

[1240] Step 11:

[1241] The server obtains the user's location information and searches for nearby veterinary clinics based on that location.

[1242] Step 12:

[1243] The server generates a list of specialized veterinary clinics and best doctors and constructs the information to be provided to the user.

[1244] Step 13:

[1245] The server generates a packet that summarizes first aid procedures, disease predictions, and veterinary clinic information and sends it to the terminal.

[1246] Step 14:

[1247] The device analyzes the data received and displays the "First Aid Procedures" screen.

[1248] Step 15:

[1249] The device displays first aid procedures to the user in visual or video format.

[1250] For example, a video might show "steps to cool the affected area using a cold towel."

[1251] Step 16:

[1252] The device displays a predicted disease name and a list of recommended veterinary clinics.

[1253] For example, it could display something like, "There is a possibility of allergic dermatitis. Nearby veterinary clinics are listed below."

[1254] Step 17:

[1255] The server regularly updates information on maintaining pet health and early detection of illness and sends it to the device.

[1256] Step 18:

[1257] The device will send a notification to the user informing them that new preventative information is available.

[1258] Step 19:

[1259] The user checks the notification and views the new prevention information.

[1260] For example, information such as "Regular cleaning and avoiding certain foods are important for preventing pet allergies" may be displayed.

[1261] Example 1

[1262] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1263] Pet owners have limited means to respond quickly and accurately to sudden injuries or illnesses in their pets. It is also often difficult to immediately obtain appropriate first aid and specialized medical information. To solve this problem, a system is needed that allows users to easily input their pet's symptoms and quickly obtain appropriate first aid and specialized medical information.

[1264] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1265] In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for converting the input symptom data into a consistent format and transmitting the data to the server, a data analysis means for analyzing the received symptom data using a machine learning model and predicting an associated disease name and first aid method, a visualization means for displaying the generated first aid method in a visual or video format, a hospital search means for searching for nearby specialized medical facilities based on the user's location information and providing the information, and a prevention information provision means for periodically providing information on the prevention and early detection of pet diseases. This allows appropriate first aid methods and specialized medical information to be quickly provided according to the pet's symptoms, enabling pet owners to care for their pets with peace of mind.

[1266] The "user interface means" refers to an interface that provides text boxes and options for inputting symptoms of a pet, allowing the user to easily input symptoms.

[1267] The "communication method" refers to the method for converting the symptom data entered by the user into a consistent format and sending it to the server. Specifically, the data is converted into JSON format and a communication protocol such as an HTTP POST request is used.

[1268] The "data analysis means" is a means for analyzing the symptom data received by the server using machine learning models and natural language processing, extracting keywords from the input text, and comparing them with a learning database to predict the optimal first aid method and disease name.

[1269] The "visualization means" refers to a means for converting the first aid procedures and methods generated based on the data analysis into a visual or video format and displaying them in a way that is easily understandable to the user, for example, by using a video generation library or a graphics library.

[1270] "Hospital search means" refers to a means of searching for nearby specialized medical facilities and veterinary clinics using the user's location information and providing that information to the user. Specifically, search results are obtained using a local search API.

[1271] The "prevention information provision means" is a means by which a server periodically generates information on pet disease prevention and early detection and sends it to the user's device as a news feed or push notification. For example, it uses a notification system such as Firebase Cloud Messaging.

[1272] A "machine learning model" is an algorithm or framework that learns patterns from data to make predictions and classifications, and is used to analyze pet symptom data.

[1273] "JSON format" is an abbreviation for JavaScript Object Notation, and is a data format that represents data in text format and enables consistent data exchange.

[1274] The present invention relates to an AI system that enables pet owners to provide quick and accurate first aid to their pets when they suddenly become injured or become ill. This system is realized using the following means.

[1275] First, the user accesses the terminal and is provided with text boxes and options to input the specific symptoms of their pet. The user enters the symptoms in detail and clicks the "Submit" button. For example, the user may enter "My pet has developed a red rash on its skin."

[1276] The terminal then converts the data entered by the user into JSON format and sends it to the server using a data communication protocol, which ensures data consistency and improves transfer efficiency.

[1277] The server analyzes the received data using a natural language processing (NLP) engine. At this stage, keywords are extracted from the input text and compared with a built-in learning database. This allows the system to predict the most appropriate first aid method and diagnosis. Specific software used is the machine learning frameworks PyTorch and TensorFlow.

[1278] Furthermore, the server creates first aid procedures based on the results of the data analysis. These procedures are converted into videos and diagrams for easy visual understanding. For example, a video showing the procedure for cooling the affected area with a cold towel can be created. Video generation libraries (e.g., FFmpeg) and graphics libraries (e.g., p5.js) are used to generate these videos.

[1279] The device receives the video and illustrations of first aid procedures sent from the server and displays them to the user, who can then take appropriate first aid. A user interface framework (e.g., React.js or Vue.js) is used for displaying the information.

[1280] The server also obtains the user's location information and searches for nearby veterinary clinics based on that location. Using a local search API (e.g., Google Places API), it generates a list of clinics that can handle specific symptoms or illnesses and provides it to the user. For example, if the user enters "my pet is having difficulty breathing," it determines that oxygen supply is required and searches for the nearest veterinary clinic that can provide emergency care, providing the information.

[1281] The server then periodically provides information about pet health maintenance and early disease detection. This information is sent to the user's device as a news feed or push notification, and includes advice on disease prevention and health management. This is done using a periodic query and notification system (e.g., Firebase Cloud Messaging).

[1282] As a specific example, if a user inputs "My pet has a red rash on its skin," the device sends this data to the server. The server analyzes the data, predicts it is allergic dermatitis, generates a video showing first aid using a cold towel, and provides instructions to the user. It also searches for and lists nearby veterinary clinics specializing in allergies, and provides this to the user. On the other hand, if the user inputs "My pet is having difficulty breathing," it determines that oxygen supply is necessary, generates a video showing appropriate first aid, and searches for the nearest veterinary clinic that can provide emergency care.

[1283] In this way, this system quickly provides appropriate first aid methods and specialized medical information according to the pet's symptoms, allowing pet owners to care for their pets with peace of mind. In addition, the regular provision of information also contributes to maintaining the health of pets.

[1284] An example of a prompt is as follows:

[1285] "My pet has a red rash on its skin"

[1286] "My pet is having difficulty breathing"

[1287] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1288] Step 1:

[1289] The user accesses the terminal and inputs the specific symptoms of their pet. The user interface provides text boxes and options for entering the symptoms in detail. When the "Submit" button is clicked, the terminal retrieves the input data. The input is symptom data in text format, and the output is the symptom data itself.

[1290] Step 2:

[1291] The device converts the symptom data entered by the user into JSON format. The converted data is consistent and suitable for communication. Here, the input is symptom data in text format, and the output is data in JSON format. Specifically, the data conversion is performed using a JavaScript library.

[1292] Step 3:

[1293] The terminal sends data to the server using a communication protocol (for example, an HTTP POST request). At this stage, the input is JSON-formatted data, and the output is status information indicating that transmission to the server has been completed. HTTPS communication is used for data transfer, ensuring security.

[1294] Step 4:

[1295] The server receives the JSON-formatted data sent from the device. It then analyzes the data using a natural language processing (NLP) engine. The input is JSON-formatted data, and the output is symptom data with extracted keywords. Here, analysis is performed using a machine learning model (e.g., PyTorch or TensorFlow).

[1296] Step 5:

[1297] After extracting keywords, the server compares them with the learning database to predict the most relevant first aid method and disease name. The input is symptom data from which keywords have been extracted, and the output is first aid methods and predicted disease names. Past data and specialized knowledge are incorporated into the predictions.

[1298] Step 6:

[1299] The server creates first aid procedures based on the analysis results. These procedures are converted into videos and diagrams for easy visual understanding. The input is the first aid method and the name of the disease, and the output is the procedure in video or diagram format. Specifically, a video generation library (e.g., FFmpeg) and a graphics library (e.g., p5.js) are used.

[1300] Step 7:

[1301] The device receives the video or diagram of the first aid procedure sent from the server and displays it to the user. The user can then view it and take appropriate first aid. Here, the input is the video or diagram format of the procedure, and the output is the displayed information. A user interface framework (e.g., React.js or Vue.js) is used for display.

[1302] Step 8:

[1303] The server obtains the user's location information and searches for nearby veterinary clinics based on that location. The input is the user's location information and the output is the search results. A local search API (e.g., Google Places API) is used to provide the user with the most suitable clinic information.

[1304] Step 9:

[1305] The server periodically generates information on maintaining pet health and early disease detection, and sends it to the user's device as a news feed or push notification. The input is disease prevention information and health management advice, and the output is the notified information. Notifications are sent using Firebase Cloud Messaging and other technologies to ensure that information reaches the user reliably.

[1306] (Application example 1)

[1307] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1308] When a pet suddenly becomes injured or becomes unwell, it is difficult for pet owners to provide first aid quickly and accurately. It is also difficult to quickly find an appropriate medical institution that responds to the pet's symptoms. Furthermore, first aid methods are not presented visually in an easy-to-understand manner, which can make it difficult to actually carry them out. The present invention aims to solve these problems and enable pet owners to easily access the information they need.

[1309] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1310] In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for transmitting the input symptom data to the server, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a visualization means for displaying the generated first aid method visually or in video format in an augmented reality format, a hospital search means for searching for and providing information on veterinary clinics specializing in the symptoms, a means for providing information on nearby veterinary clinics based on the analysis results, and a prevention information provision means for periodically providing information on the prevention and early detection of diseases in pets. This makes it possible to provide appropriate first aid instructions according to the pet's symptoms visually through augmented reality, and also allows instant access to information on nearby veterinary clinics, enabling rapid response.

[1311] The "user interface means" is a function that provides text boxes and options for the user to input symptoms of their pet.

[1312] "Communication means" refers to a technique for transmitting input symptom data to a server.

[1313] The "data analysis means" is a function that analyzes the received symptom data and generates an appropriate first aid method and disease name.

[1314] The "visualization means" refers to a technology for visually displaying the generated first aid method in an augmented reality format or a video format.

[1315] The "hospital search tool" is a function that searches for veterinary hospitals that specialize in symptoms and provides information about them.

[1316] The "location information means" is a technology for acquiring the user's location information and searching for nearby veterinary clinics based on that information.

[1317] The "prevention information provision means" is a function that periodically provides information on the prevention and early detection of pet diseases.

[1318] "Augmented reality" is a technology that displays digital information overlaid on real-world information.

[1319] The present invention provides a system that enables pet owners to quickly and accurately provide first aid to their pets when they are injured or in poor health. An embodiment of the system will be described in detail below.

[1320] First, the user puts on the smart glasses and voice-inputs the specific symptoms of their pet. The smart glasses have a built-in voice recognition function that can convert the voice-input symptoms into text, allowing the user to easily communicate the symptoms to the system.

[1321] Next, the communication means installed in the smart glasses converts the input symptom data into JSON format and sends it to the server. The communication means requires a high-speed and stable internet connection.

[1322] The server uses a natural language processing (NLP) model to analyze the received symptom data. It extracts keywords from the input text data and compares them with a past learning database based on these keywords to generate the most relevant first aid method and predicted disease name. This data analysis method makes it possible to provide appropriate first aid methods.

[1323] The generated first aid instructions are visualized in augmented reality (AR) and displayed on the user's smart glasses, allowing the user to see specific treatment procedures for their pet superimposed on the real world. For example, a first aid instruction such as "cool the affected area with a cold towel" is visually displayed in AR.

[1324] The server also obtains the user's location information and searches for nearby veterinary clinics based on that location. The search results are displayed on the smart glasses, allowing the user to quickly access the nearest veterinary clinic. At the same time, the preventive information provider also regularly provides information on maintaining pet health and early detection of illnesses.

[1325] For example, if a user says, "My pet is having difficulty breathing," the server quickly analyzes the data and determines that oxygen is needed. As a result, the necessary first aid instructions are displayed in AR format on the smart glasses, along with information about the nearest veterinary clinic.

[1326] An example of a prompt for a generative AI model is as follows:

[1327] "My pet suddenly started having difficulty breathing. Please tell me first aid procedures and the nearest veterinary clinic."

[1328] As described above, the present invention enables quick and accurate responses to pet ailments, allowing owners to care for their pets with peace of mind. In addition, the function of providing preventive information contributes to maintaining the health of pets.

[1329] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1330] Step 1:

[1331] The user wears the smart glasses and inputs their pet's symptoms by voice. The input voice is converted into text data by the voice recognition system in the smart glasses. Input data: User's voice information, Output data: Symptom data in text format

[1332] Step 2:

[1333] The symptom information converted into text data is converted into JSON format by the smart glasses' communication means and sent to a server via the Internet. Input data: symptom data in text format, Output data: symptom data in JSON format

[1334] Step 3:

[1335] The server analyzes the received JSON-formatted symptom data. Using a natural language processing (NLP) model, it extracts keywords from the text data and compares them with a training database. This results in the most relevant first aid method and predicted disease name. Input data: JSON-formatted symptom data, Output data: first aid method, predicted disease name

[1336] Step 4:

[1337] The server converts the generated first aid method based on the analysis results into an augmented reality (AR) format. The augmented reality format data is sent to the smart glasses and visually displayed to the user. Input data: First aid method, Output data: First aid method in augmented reality format

[1338] Step 5:

[1339] The server acquires the user's location information and searches for nearby veterinary clinics based on the location information. The search results for veterinary clinic information are sent to the smart glasses and notified to the user. Input data: User's location information, Output data: Nearby veterinary clinic information

[1340] Step 6:

[1341] The server periodically generates preventive information related to maintaining pet health and early detection of diseases, and notifies the smart glasses. This allows users to periodically receive information useful for managing their pet's health. Input data: Preventive information stored in the server's database. Output data: Preventive information in notification format.

[1342] Step 7:

[1343] The user performs first aid on the pet based on the augmented reality first aid method displayed on the smart glasses. The user also refers to the veterinary clinic information displayed on the smart glasses to quickly access the veterinary clinic. Input data: augmented reality first aid method, veterinary clinic information. Output data: first aid to be performed, location information of the veterinary clinic.

[1344] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1345] overview

[1346] This invention is an AI system that enables pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. It aims to improve the method of presenting first aid procedures and the quality of user support by incorporating an emotion engine that recognizes the user's emotions. This system includes a user interface for inputting the pet's symptoms, a communication means for transmitting symptom data to a server, a data analysis means, a visualization means, a hospital search means, a preventive information provision means, and an emotion engine. Based on the symptoms and emotion information entered by the user, the server provides appropriate first aid procedures and specialized treatment information.

[1347] Program processing

[1348] The program of this system processes as follows:

[1349] 1. User Interface Methods

[1350] The user accesses a terminal and is provided with text boxes and options to input their pet's specific symptoms. The user enters the symptoms in detail and clicks the "Submit" button.

[1351] 2. Means of communication

[1352] The data sent by the user is converted to JSON format by the terminal and sent to the server, which improves data consistency and transmission efficiency.

[1353] 3. Data Analysis Methods

[1354] The server analyzes the received data and uses natural language processing (NLP) to extract keywords from the input text and compare them with a training database to predict the most relevant first aid method and disease name.

[1355] 4. Visualization tools

[1356] The resulting first aid procedures are then converted into visual or video formats. For example, a video can be created demonstrating how to apply a cold towel to an affected area. The video is then displayed on the device for easy user access.

[1357] 5. Hospital search tools

[1358] The server obtains the user's location information, searches for nearby veterinary clinics based on that location, and provides the user with a list of specialized medical facilities that can treat specific symptoms or illnesses.

[1359] 6. Emotion Engine

[1360] The emotion engine analyzes the user's voice input and facial expression data to recognize their emotions. For example, if the user shows signs of anxiety or impatience, it will suggest first aid measures and provide advice on how to calm the user.

[1361] 7. Preventive information provision measures

[1362] The server periodically provides information on pet health maintenance and early disease detection, including advice on how to prevent certain diseases and health management, which is displayed as notifications on the user's device.

[1363] Specific examples

[1364] Example 1: Skin rash

[1365] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes the data and predicts that it is "allergic dermatitis." It also instructs the user on how to provide first aid using a cold towel and recommends a nearby veterinary clinic that specializes in allergies. It also provides visual instructions in the form of a video and periodically notifies users of preventative care information. Furthermore, if the device senses anxiety in the user's voice, it displays reassuring advice.

[1366] Example 2: Difficulty breathing

[1367] The user types, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It provides a video of the appropriate first aid procedure. It also searches for the nearest veterinary hospital that can provide emergency care and instructs the user. The emotion engine recognizes the user's impatience and provides instructions and advice on how to respond calmly.

[1368] In this way, by combining this system with an emotion engine, it is possible to quickly provide appropriate first aid procedures and specialized medical information according to the pet's symptoms, as well as provide appropriate support according to the user's emotional state. This allows pet owners to care for their pets with peace of mind. In addition, by providing information on disease prevention and early detection, it can also contribute to maintaining pet health.

[1369] The processing flow will be explained below.

[1370] Step 1:

[1371] The user opens the application on the device and accesses the "Symptom Input" screen.

[1372] Step 2:

[1373] The user enters the pet's specific symptoms into a text box.

[1374] For example, enter "My pet has a red rash on its skin."

[1375] Step 3:

[1376] The user clicks the "Submit" button to submit the symptom data.

[1377] Step 4:

[1378] The terminal converts the user input data into JSON format.

[1379] For example, it converts to {"symptom": "My pet has a red rash on its skin"}.

[1380] Step 5:

[1381] The terminal transmits the converted data to the server.

[1382] Step 6:

[1383] The server begins the process of parsing the received data.

[1384] Step 7:

[1385] The server uses natural language processing (NLP) to extract keywords from the input text.

[1386] For example, extract keywords such as "skin," "red," and "rash."

[1387] Step 8:

[1388] The server compares the extracted keywords with the learning database and predicts the most relevant disease name.

[1389] As an example, "allergic dermatitis" is predicted.

[1390] Step 9:

[1391] The server retrieves first aid procedures associated with the predicted illness from a database.

[1392] For example, methods such as "cool the affected area with a cold towel" and "consider over-the-counter antihistamines" are obtained.

[1393] Step 10:

[1394] The server converts the first aid procedures into a visual or video format.

[1395] For example, we will generate a video showing the steps to cool an affected area using a cold towel.

[1396] Step 11:

[1397] The server obtains the user's location information and searches for nearby veterinary clinics based on that location.

[1398] Step 12:

[1399] The server generates a list of specialized veterinary clinics and best doctors and constructs the information to be provided to the user.

[1400] Step 13:

[1401] The emotion engine analyzes the user's voice input and facial expression data to recognize emotions.

[1402] For example, if the user is feeling anxious, the emotion of "anxiety" is recognized from the tone of voice and facial expression.

[1403] Step 14:

[1404] Based on the emotion engine's analysis, the server adjusts how first aid procedures are presented.

[1405] For example, for a user who is feeling anxious, gentle words or audio guidance are provided to give a sense of security.

[1406] Step 15:

[1407] The server generates advice based on the emotion recognition results.

[1408] For example, if the user is feeling anxious, the system generates advice such as "Please stay calm. First, calm down and take a deep breath."

[1409] Step 16:

[1410] The server generates a packet containing first aid procedures, disease predictions, veterinary clinic information, and advice based on the patient's emotions, and sends it to the terminal.

[1411] Step 17:

[1412] The device analyzes the data received and displays the "First Aid Procedures" screen.

[1413] Step 18:

[1414] The device displays first aid procedures to the user in visual or video format.

[1415] For example, a video might show "steps to cool the affected area using a cold towel."

[1416] Step 19:

[1417] The device displays a predicted disease name and a list of recommended veterinary clinics.

[1418] For example, it could display something like, "There is a possibility of allergic dermatitis. Nearby veterinary clinics are listed below."

[1419] Step 20:

[1420] The terminal displays advice based on emotion recognition to the user.

[1421] For example, it displays the message, "Please stay calm. First, calm down and take a deep breath."

[1422] Step 21:

[1423] The server regularly updates information on maintaining pet health and early detection of illness and sends it to the device.

[1424] Step 22:

[1425] The device will send a notification to the user informing them that new preventative information is available.

[1426] Step 23:

[1427] The user checks the notification and views the new prevention information.

[1428] For example, information such as "Regular cleaning and avoiding certain foods are important for preventing pet allergies" may be displayed.

[1429] Example 2

[1430] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1431] Providing prompt and accurate first aid for pets suffering from sudden injuries or illness is an important issue for pet owners. Furthermore, there is a need for a means to provide appropriate support and reassurance in situations where pet owners feel anxious or impatient. To address these issues, the present invention aims to provide a system that allows pet owners to input their pet's symptoms and quickly analyzes and responds to them.

[1432] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1433] In this invention, the server includes an information input means for inputting the symptoms of the pet, a communication means for transmitting the input symptom data to the central device, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a display means for displaying the generated first aid method in a visual or video format, a medical facility search means for searching for and providing information on medical facilities specializing in the symptoms, a preventive information provision means for periodically providing information on the prevention and early detection of diseases in pets, and an emotion recognition means for recognizing the user's emotions and providing appropriate first aid methods and advice to reassure the user, thereby enabling quick and accurate first aid for the pet's symptoms and providing a sense of security.

[1434] The "information input means" is a device that provides an interface for the user to input specific symptoms of the pet.

[1435] The "communication means" is a device having a function for transmitting input symptom data to the central device.

[1436] The "data analysis means" is a device for analyzing the received symptom data and generating an appropriate first aid method.

[1437] The "display means" is a device that displays the generated first aid method in a visual or animated format.

[1438] The "medical facility search means" is a device that searches for medical facilities that specialize in symptoms and provides information.

[1439] The "prevention information providing means" is a device that periodically provides information on the prevention and early detection of pet diseases.

[1440] The "emotion recognition means" is a device that recognizes the user's emotions and provides appropriate first aid or advice to reassure the user.

[1441] The "Central Unit" is the main component that analyzes the received data, generates appropriate first aid procedures, and provides information to the user.

[1442] This invention is a system for providing quick and accurate first aid to pets when they suddenly become injured or ill, and also aims to provide appropriate support and peace of mind to pet owners in situations where they feel anxious or impatient.

[1443] A web browser or mobile application can be used as an information input method for users to enter their pet's symptoms. For example, users can open the application and enter their pet's specific symptoms into the text box. Alternatively, they can select options based on the symptoms. Once they have completed the input, they click the "Submit" button.

[1444] The terminal converts the user's input data into JSON format and sends it to a central device (server) via the Internet, which improves data consistency and transfer efficiency.

[1445] The server analyzes the received JSON data. The analysis method used here is natural language processing (NLP) technology. For example, Python and a natural language processing library are used to extract important keywords from the text data. This results in keywords such as "red rash" and "skin." These keywords are compared with a pre-trained database to predict the most relevant disease name and first aid method.

[1446] The server generates first aid procedures based on the analysis results and converts them into a visual or video format. For example, a video showing the procedure of "cooling the affected area with a cold towel" can be shown. Video editing software is used to generate the video. The generated video is sent to the user's device and displayed on the device.

[1447] The server obtains location information from the user's device and searches for nearby medical facilities based on that location. The search results provide a list of medical facilities that can accommodate specific symptoms or illnesses. This list is displayed on the user's device, allowing them to quickly head to the nearest medical facility.

[1448] The server performs voice and facial expression analysis to recognize emotions. Voice input is converted into text using a voice recognition API, and facial expression data is analyzed using facial recognition technology. For example, Google's Cloud Speech-to-Text API can be used for voice analysis, and Microsoft's facial recognition API can be used for facial expression recognition. This allows the server to recognize when a user is anxious or impatient and display advice to reassure the user.

[1449] The server also periodically provides information on pet disease prevention and early detection, including advice on how to prevent specific illnesses and health management, such as "seasonal allergy prevention measures," to the user's device.

[1450] Specific examples

[1451] Example 1: Skin rash

[1452] The user types, "My pet has a red rash on its skin." The device sends this data to the server, which analyzes the data and predicts "allergic dermatitis." It then instructs the user on how to provide first aid using a cold towel and recommends a nearby medical facility specializing in allergies. It also provides visual instructions in the form of a video and periodically notifies users of preventive measures. Furthermore, if the device senses anxiety in the user's voice, it displays reassuring advice.

[1453] Example 2: Difficulty breathing

[1454] The user types, "My pet is having difficulty breathing." The server immediately analyzes the data and determines that oxygen is needed. It provides a video of the appropriate first aid procedure. It also searches for the nearest emergency medical facility and instructs the user on the procedure. The emotion engine recognizes the user's impatience and provides instructions and advice on how to respond calmly.

[1455] In this way, by combining an emotion engine, the present invention is a system that provides quick and accurate first aid for pet symptoms and a sense of security. It also contributes to maintaining pet health by providing preventive information.

[1456] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1457] Step 1:

[1458] The user opens the application and enters the specific symptoms of their pet. They use the text boxes and options to enter details about the symptoms and click the "Submit" button.

[1459] Input: Pet's specific symptoms (text format)

[1460] Output: Symptom data sent to the device (text format)

[1461] Specific behavior: The user enters "My pet has a red rash on its skin" into the application and presses the send button.

[1462] Step 2:

[1463] The terminal converts the user's input data into JSON format and sends it to a central device (server) via the Internet.

[1464] Input: Submitted symptom data (text format)

[1465] Output: JSON format data sent to the server

[1466] Specific behavior: The application on the device converts the text "My pet has a red rash on its skin" into JSON format and sends it to the server.

[1467] Step 3:

[1468] The server parses the received JSON data and uses natural language processing (NLP) techniques to extract important keywords from the text data and match them with existing databases to predict the most relevant disease names and first aid methods.

[1469] Input: Symptom data in JSON format

[1470] Output: Prediction results of disease name and first aid method

[1471] Specific operation: The server uses Python and NLP libraries to extract keywords such as "red rash" and "skin" and predicts "allergic dermatitis."

[1472] Step 4:

[1473] The server generates first aid procedures based on the analysis results and converts them into a visual or video format. Editing software is used to convert the first aid procedures into a video and send it to the user's device.

[1474] Input: Disease name and first aid method prediction results

[1475] Output: Visual or video first aid instructions

[1476] Specific operation: The server generates a video showing the steps of "cooling the affected area with a cold towel" and sends it to the user's device.

[1477] Step 5:

[1478] The server obtains location information from the user's terminal and searches for nearby medical facilities based on that location.

[1479] Input: User's location

[1480] Output: A list of symptom-specific medical facilities

[1481] Specific operation: The server acquires the user's location information, generates a list of "allergy specialty medical facilities," and provides it to the user.

[1482] Step 6:

[1483] The emotion recognition means analyzes the user's voice input and facial expression data to recognize the user's emotions. For example, it analyzes the user's voice to recognize anxiety and provide advice accordingly.

[1484] Input: Voice input and facial expression data

[1485] Output: Emotion recognition results and corresponding advice

[1486] How it works: The server converts speech into text using Google's Cloud Speech-to-Text API, analyzes facial expressions using Azure Face API, recognizes anxiety, and displays advice such as "stay calm."

[1487] Step 7:

[1488] The server periodically provides information on maintaining pet health and early detection of illness.

[1489] Input: Pet health data and related information

[1490] Output: Preventive and health care advice

[1491] Specific operation: The server displays notifications such as "Seasonal allergy prevention measures" on the user's device.

[1492] Through the above processing steps, the system can provide users with fast and accurate first aid information and provide a sense of security through emotion recognition.

[1493] (Application example 2)

[1494] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1495] Conventional pet first aid systems have the problem of being unable to quickly provide appropriate treatment methods for pet symptoms and are unable to take into account the feelings of pet owners, which means they are unable to alleviate the anxiety and impatience of pet owners. Furthermore, searching for and providing information on veterinary medical facilities specializing in symptoms is not intuitive, and support is lacking in situations where a quick response is required.

[1496] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user interface means for inputting the pet's symptoms, a communication means for transmitting the input symptom data to the server, a data analysis means for analyzing the received symptom data and generating an appropriate first aid method, a visualization means for displaying the generated first aid method in a visual or video format, a medical facility search means for searching for and providing information on veterinary medical facilities specializing in the symptoms, a preventive information provision means for periodically providing information on the prevention and early detection of pet diseases, and an emotion recognition means for recognizing the user's emotions and suggesting appropriate first aid methods and providing psychological support. This allows pet owners to quickly and accurately provide appropriate first aid, and by providing psychological support in accordance with the user's emotions, the pet owner's anxiety and impatience can be alleviated, making it possible to more effectively manage the pet's health.

[1497] The "user interface means" is an interface device that the user uses to input the symptoms of the pet.

[1498] "Communication means" refers to the technical means for transmitting the input symptom data to the server.

[1499] The "data analysis means" is a technical means for analyzing the symptom data received by the server and generating an appropriate first aid method.

[1500] A "visualization tool" is a device or technique for displaying the generated first aid instructions in a visual or animated format.

[1501] A "medical facility search tool" is a device or technology for searching for and providing information on veterinary medical facilities that specialize in certain symptoms.

[1502] A "preventive information providing means" is a device or technology that periodically provides information on the prevention and early detection of pet diseases.

[1503] An "emotion recognition means" is a device or technology for recognizing a user's emotions and suggesting appropriate first aid methods or providing psychological support.

[1504] overview

[1505] This invention is an AI system that allows pet owners to provide fast and accurate first aid for sudden injuries or illnesses to their pets. The system analyzes symptom and emotional data entered by the user and provides appropriate first aid. It also searches for nearby veterinary medical facilities and provides information, thereby reducing user anxiety and supporting pet health management.

[1506] User Interface Means

[1507] The user accesses the terminal and inputs the specific symptoms of their pet. To do this, an interface such as text boxes and check boxes is provided. The system also has voice input and facial recognition functions to recognize the user's emotions.

[1508] communication means

[1509] The entered data is converted to JSON format and sent to the server over the Internet, which improves data consistency and transfer efficiency.

[1510] Data Analysis Methods

[1511] The server uses natural language processing (NLP) technology to analyze the received symptom data. Specifically, it extracts keywords from the input text and compares them with a training database to predict the most relevant first aid method and disease name. For emotional data, it uses an emotion recognition engine to analyze the user's feelings, such as anxiety or impatience.

[1512] Visualization tools

[1513] The generated first aid instructions can be displayed on the device in visual or video format. For example, an animation can show the steps for applying a cold towel to an affected area. This video is provided in a user-friendly format.

[1514] Medical facility search tools

[1515] The server searches for nearby veterinary medical facilities based on the user's location information. It then lists medical facilities that can treat specific symptoms or illnesses and provides them to the user. This information is obtained in real time, allowing it to provide the most up-to-date data.

[1516] Preventive information provision methods

[1517] The server periodically provides information on maintaining pet health and early detection of diseases, including advice on how to prevent certain diseases and health management, and provides the information to the user in a timely manner using a notification function.

[1518] emotion recognition means

[1519] The emotion recognition means analyzes the user's voice input and facial expression data to recognize their emotions. For example, if the user shows signs of anxiety or impatience, it will suggest first aid measures to address the situation and provide advice on how to calm down. This function allows the user to respond calmly.

[1520] Examples and prompts

[1521] For example, if a user types "my pet has a red rash on its skin," the system will predict "allergic dermatitis" and provide a video showing first aid using a cold towel. It will also recommend nearby veterinary clinics that specialize in allergies, and its emotion recognition capabilities will sense the user's anxiety and provide reassuring advice.

[1522] Example prompt sentence:

[1523] Input: "My pet has a skin rash."

[1524] output:

[1525] First aid: "Cool the area with a cold towel."

[1526] Veterinary Clinic: "We can connect you to a nearby specialized medical facility."

[1527] Emotional care: "Remain calm. Seek medical attention to determine the cause of the rash."

[1528] This system allows pet owners to provide prompt and appropriate first aid and receive comprehensive support that also takes into consideration the user's emotions.

[1529] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1530] Step 1:

[1531] The user uses the device to input their pet's symptoms. Specifically, they type "My pet has a red rash on its skin" into the text box and click the send button. Based on this input, the system begins initial processing. The user's emotions are also collected through voice input and the camera.

[1532] Input: Pet's specific symptoms (text), user's emotions (voice, facial recognition)

[1533] Output: Input data in JSON format

[1534] Step 2:

[1535] The device converts the input data into JSON format and sends it to the server using a communication method. The internet is used to maintain data consistency and transmit data efficiently.

[1536] Input: User-entered symptoms and emotional information

[1537] Output: JSON data sent to the server

[1538] Step 3:

[1539] The server analyzes the received JSON data, using natural language processing (NLP) technology to analyze symptoms and generate appropriate first aid methods and a predicted illness name based on extracted keywords. An emotion recognition engine analyzes the user's emotions and compares them with a database to determine the appropriate psychological support.

[1540] Input: JSON data (symptoms, emotions)

[1541] Output: First aid methods, predicted illness names, mental support information

[1542] Step 4:

[1543] The server generates the generated first aid method in the form of a video or image through a visualization means. This visualized data is sent to the terminal in a format that is easy for the user to understand. Specifically, a video of "the procedure for cooling the affected area with a cold towel" is generated.

[1544] Input: First Aid Methods

[1545] Output: Video or image data

[1546] Step 5:

[1547] The server uses the user's location information to search for nearby veterinary clinics, compiles a list of clinics that can treat specific symptoms or illnesses, and sends that information to the device. This is done using location services such as Google Maps API.

[1548] Input: User's location information, predicted disease name

[1549] Output: List of veterinary facilities with details

[1550] Step 6:

[1551] The device displays information received from the server, including first aid videos, a list of nearby veterinary clinics, and emotional support information, allowing users to take prompt and appropriate action.

[1552] Input: First aid methods, medical facility information, and mental support information from the server

[1553] Output: A user-accessible visual representation

[1554] Step 7:

[1555] The server periodically sends information about pet disease prevention and early detection to the terminal using the preventive information providing means. This allows the user to obtain a specific action plan for disease prevention and early detection. For example, information such as "methods for preventing allergic dermatitis" is provided.

[1556] Input: Preventive Information

[1557] Output: Providing periodic notifications and preventative information

[1558] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1559] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1560] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1561] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1562] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1563] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1564] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1565] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1566] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1567] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1568] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1569] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1570] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1571] 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.

[1572] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1573] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1574] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1575] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1576] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1577] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1578] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1579] The following is further disclosed regarding the above embodiment.

[1580] (Claim 1)

[1581] a user interface means for inputting symptoms of the pet;

[1582] a communication means for transmitting the input symptom data to a server;

[1583] data analysis means for analyzing the received symptom data and generating an appropriate first aid procedure;

[1584] visualization means for displaying the generated first aid procedures in visual or video format;

[1585] A hospital search tool to search for and provide information on veterinary hospitals that specialize in specific symptoms,

[1586] A preventive information provider that regularly provides information on pet disease prevention and early detection;

[1587] A system including:

[1588] (Claim 2)

[1589] 10. The system of claim 1, further comprising means for predicting a disease name based on the analyzed symptom data and generating a first aid method associated with the disease name.

[1590] (Claim 3)

[1591] 10. The system of claim 1, further comprising means for searching for and providing information about nearby veterinary clinics using location information of the user.

[1592] "Example 1"

[1593] (Claim 1)

[1594] a user interface means for inputting symptoms of the pet;

[1595] a communication means for converting the input symptom data into a consistent format and transmitting the same to a server;

[1596] a data analysis means for analyzing the received symptom data using a machine learning model and predicting an associated disease name and first aid method;

[1597] visualization means for displaying the generated first aid procedures in visual or video format;

[1598] a hospital search means for searching for nearby specialized medical facilities based on the user's location information and providing information about them;

[1599] A preventive information provider that regularly provides information on pet disease prevention and early detection;

[1600] A system including:

[1601] (Claim 2)

[1602] The system of claim 1, further comprising means for predicting a disease name based on the analyzed symptom data, generating first aid methods associated with the disease name, and providing the methods in the form of videos and illustrations.

[1603] (Claim 3)

[1604] 10. The system according to claim 1, further comprising means for searching for nearby veterinary clinics using the user's location information and providing information on veterinary clinics that can treat specific symptoms or disease names.

[1605] "Application Example 1"

[1606] (Claim 1)

[1607] a user interface means for inputting symptoms of the pet;

[1608] a communication means for transmitting the input symptom data to a server;

[1609] data analysis means for analyzing the received symptom data and generating an appropriate first aid procedure;

[1610] visualization means for displaying the generated first aid procedure in augmented reality visual or video format;

[1611] A hospital search tool to search for and provide information on veterinary hospitals that specialize in specific symptoms,

[1612] A means to provide information on nearby veterinary clinics based on the analysis results, and

[1613] A preventive information provider that regularly provides information on pet disease prevention and early detection;

[1614] A system including:

[1615] (Claim 2)

[1616] 10. The system of claim 1, further comprising means for predicting a disease name based on the analyzed symptom data, and generating first aid methods and nearby specialized medical facility information associated with the disease name.

[1617] (Claim 3)

[1618] 10. The system of claim 1, further comprising means for using a user's location information to search for nearby veterinary clinics and displaying the information in an augmented reality format.

[1619] "Example 2: Combining Emotion Engines"

[1620] (Claim 1)

[1621] an information input means for inputting symptoms of a pet;

[1622] a communication means for transmitting the input symptom data to a central device;

[1623] data analysis means for analyzing the received symptom data and generating an appropriate first aid procedure;

[1624] display means for displaying the generated first aid instructions in visual or video format;

[1625] A medical facility search tool for searching for medical facilities specialized in symptoms and providing information;

[1626] A preventive information provider that regularly provides information on pet disease prevention and early detection;

[1627] an emotion recognition means for recognizing the emotion of the user and providing appropriate first aid or reassuring advice;

[1628] A system including:

[1629] (Claim 2)

[1630] 10. The system of claim 1, further comprising means for predicting a disease name based on the analyzed symptom data and generating a first aid method associated with the disease name.

[1631] (Claim 3)

[1632] 10. The system of claim 1, further comprising means for using location information of the user to search for and provide information about nearby medical facilities.

[1633] "Application example 2 when combining emotion engines"

[1634] (Claim 1)

[1635] a user interface means for inputting symptoms of the pet;

[1636] a communication means for transmitting the input symptom data to a server;

[1637] data analysis means for analyzing the received symptom data and generating an appropriate first aid procedure;

[1638] visualization means for displaying the generated first aid procedures in visual or video format;

[1639] A medical facility search tool for searching for and providing information on veterinary medical facilities specializing in symptoms;

[1640] A preventive information provider that regularly provides information on pet disease prevention and early detection;

[1641] an emotion recognition means for recognizing the emotion of the user and providing appropriate first aid and psychological support;

[1642] A system including:

[1643] (Claim 2)

[1644] 10. The system of claim 1, further comprising means for predicting a disease name based on the analyzed symptom data and generating a first aid method associated with the disease name.

[1645] (Claim 3)

[1646] 10. The system of claim 1, further comprising means for using the user's location information to search for and provide information about nearby veterinary medical facilities. [Explanation of symbols]

[1647] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a user interface means for inputting symptoms of the pet; a communication means for transmitting the input symptom data to a server; data analysis means for analyzing the received symptom data and generating an appropriate first aid procedure; visualization means for displaying the generated first aid procedures in visual or video format; A hospital search tool to search for and provide information on veterinary hospitals that specialize in specific symptoms, A preventive information provider that regularly provides information on pet disease prevention and early detection; A system including:

2. The system of claim 1 further comprising means for predicting a disease name based on the analyzed symptom data and generating a first aid method associated with the disease name.

3. The system according to claim 1 , further comprising means for searching for nearby veterinary clinics and providing information about them using the user's location information.

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