System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to capture an image of a tooth using an image acquisition device; means for the image acquisition device to pre-process the captured image of the tooth and transmit the pre-processed image to a server; means for the server to receive the pre-processed image, perform analysis using an artificial intelligence model, and generate an analysis result in a text format; and means for the image acquisition device to visually display the received analysis result to the user and provide a specific solution or suggestion.SELECTED DRAWING: Figure 1

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] Many people suffer from dental health problems such as cavities and periodontal disease, but tend to avoid regular dental checkups because they lack the time, it's a hassle, or they don't want to go to the dentist. This can lead to a deterioration in dental health and even have a negative impact on overall health. The present invention aims to solve this problem by providing a system that supports regular dental visits by allowing users to easily check their dental health at home and take necessary measures. [Means for solving the problem]

[0005] The system includes a means for a user to take an image of their teeth using an image acquisition device, a means for the image acquisition device to preprocess the captured image of the teeth and send the preprocessed image to a server, a means for the server to receive the preprocessed image, analyze it using an artificial intelligence model, and generate an analysis result in text format, a means for sending the analysis result generated by the server to the image acquisition device, and a means for visually displaying the analysis result received by the image acquisition device to the user and providing specific countermeasures and suggestions. This system allows users to easily check the health of their teeth at home, enabling early detection and prevention of cavities and periodontal disease, thereby maintaining the health of their teeth.

[0006] "User" refers to the individual who takes the dental images and receives the dental health analysis results.

[0007] "Image capture device" refers to a device, such as a smartphone or digital camera, that a user uses to capture images of their teeth.

[0008] "Preprocessing" refers to the processing required for processing photographed tooth images before analysis, such as noise removal, resolution adjustment, and tooth region extraction.

[0009] "Server" refers to a computer system for receiving pre-processed images, analyzing them using artificial intelligence models, and generating analysis results.

[0010] An "artificial intelligence model" refers to a mathematical model that uses technologies such as machine learning and deep learning to analyze dental images and evaluate health conditions such as cavities and periodontal disease.

[0011] "Analysis results" refers to information that indicates risk assessments of cavities, periodontal disease, missed spots, dirt, discoloration, wear, etc., generated by the artificial intelligence model based on preprocessed images.

[0012] "Visual display" refers to displaying the analysis results on the screen of the image acquisition device in a format that is easy for the user to understand.

[0013] "Specific countermeasures and suggestions" refers to information including recommended tooth brushing methods and dental products for users based on the analysis results, as well as links to make dentist appointments. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

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

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

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

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0029] 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.

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

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention relates to a system that allows a user to easily check the state of dental health at home and take appropriate measures. Specific embodiments for implementing this system are described below.

[0036] First, the user takes an image of their teeth using an image capture device such as a smartphone or digital camera. The user then launches the application and follows the instructions on the screen to capture the image.

[0037] Next, the device (such as a smartphone) receives the captured image and pre-processes it, including noise reduction, resolution adjustment, and tooth region extraction to obtain the clearest and most appropriate image.

[0038] After the preprocessing is complete, the device sends the preprocessed image data to a server. The server receives the image data and analyzes it using an artificial intelligence model (AI model). Specifically, the AI ​​model evaluates the risk of cavities, periodontal disease, missed spots, dirt, stains, and wear.

[0039] Once the server completes the analysis, it generates a textual result that includes a detailed assessment of the condition of the teeth and highlights any specific risks, such as a specific diagnosis like "Your upper right molar is suspected of having cavities."

[0040] The generated analysis results are sent from the server to the device. The device receives the analysis results and visually displays them to the user. The display format is designed to be intuitive and easy for users to understand. For example, it includes a function to highlight problem areas.

[0041] The device also offers specific strategies and suggestions based on the analysis, including recommendations for specific brushing techniques and dental products, and even links to schedule dentist appointments if needed. For example, a notification might say, "You suspect a cavity in your upper right molar. Use specific toothpaste products to prevent it. Click the link for more information."

[0042] In this way, users can effectively manage their dental health from the comfort of their own home, and maintain dental health through early detection and prevention.

[0043] The processing flow will be explained below.

[0044] Step 1:

[0045] The user launches the application and takes an image of the teeth using an image capture device (such as a smartphone or digital camera). The user follows the on-screen instructions to take an image in the appropriate position and under the appropriate lighting conditions.

[0046] Step 2:

[0047] The device receives the captured tooth images and stores them in local storage.

[0048] Step 3:

[0049] The device denoises the stored images by using a filtering algorithm to reduce unavoidable image noise.

[0050] Step 4:

[0051] The device extracts the tooth region from the image and uses segmentation technology to separate the tooth from the background, extracting only the tooth portion.

[0052] Step 5:

[0053] The device adjusts the image resolution, scaling the image to the appropriate resolution for optimal analysis by the AI ​​model.

[0054] Step 6:

[0055] The terminal transmits the preprocessed image data to the server.

[0056] Step 7:

[0057] A server receives the preprocessed image data.

[0058] Step 8:

[0059] The server inputs the received image data into an AI model, which is trained using machine learning and deep learning, and analyzes the dental health status.

[0060] Step 9:

[0061] The server uses AI models to analyze the risk of cavities, periodontal disease, missed spots, stains, discoloration, wear, etc. For example, the AI ​​model analyzes specific pixel patterns in the image to identify areas that may be prone to cavities.

[0062] Step 10:

[0063] The server generates the analysis results in text format, such as a specific diagnosis such as "You may have a cavity in your upper right molar."

[0064] Step 11:

[0065] The server transmits the generated analysis results to the terminal.

[0066] Step 12:

[0067] The device visually displays the analysis results received from the server to the user, for example highlighting risk areas based on the analysis results.

[0068] Step 13:

[0069] The device will then provide specific solutions and suggestions based on the analysis, such as recommendations for specific toothpaste products and links to make dentist appointments. For example, it might say, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[0070] Example 1

[0071] 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."

[0072] Conventional dental health management systems have the drawback of making it difficult for users to easily evaluate the condition of their teeth at home and take appropriate measures. Furthermore, they require users to visit a dentist in person, which is a significant time and financial burden. For this reason, there is a demand for a method to easily check the health of teeth and detect abnormalities early.

[0073] 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.

[0074] In this invention, the server includes means for receiving the preprocessed images, performing an analysis using a deep learning model to evaluate the risk of cavities, periodontal disease, missed brushing areas, stains, discoloration, and wear, and generating the analysis results in text format, means for transmitting the analysis results generated by the server to the image acquisition device, and means for visually displaying the analysis results received by the image acquisition device to the user and providing specific countermeasures and suggestions based on the analysis results. This enables the user to easily evaluate the health of their teeth from the comfort of their own home and take appropriate measures.

[0075] "User" refers to an individual who uses an image capture device to take images of their teeth and have their health assessed.

[0076] "Image capture device" refers to a device for taking and pre-processing dental images, such as a smartphone or digital camera.

[0077] "Preprocessing" refers to the process of removing noise from the captured image, adjusting resolution, and extracting tooth areas to obtain optimal analysis results.

[0078] "Server" refers to a computing device responsible for receiving pre-processed image data, performing image analysis using deep learning models, and generating and transmitting the results.

[0079] A "deep learning model" is a mathematical model that uses artificial intelligence technology to analyze images and assess the risk of cavities, periodontal disease, missed spots, dirt, discoloration, and wear.

[0080] The "analysis results" are textual representations of the image evaluation results obtained using the deep learning model, providing users with a detailed assessment of their health status and highlighting specific risks.

[0081] "Measures and suggestions" include specific methods and product recommendations for users to improve their health based on the analysis results, as well as links to make dentist appointments if necessary.

[0082] A "notification" is a message that the image acquisition device visually displays to the user the analysis results and countermeasures or suggestions.

[0083] "Dentist appointment link" refers to a link on the Internet that allows a user to schedule a dentist appointment if necessary.

[0084] This invention provides a system that allows users to easily check the state of their dental health at home and take appropriate measures. Specific embodiments for implementing this system are described below.

[0085] Users take pictures of their teeth using an image capture device such as a smartphone or digital camera. They launch a dedicated application and follow the instructions on the screen to capture images of their teeth. When taking a photo, it is recommended to adjust the lighting so that the inside of the mouth can be seen clearly.

[0086] Next, the device (such as a smartphone) receives the captured image and performs preprocessing such as noise removal, resolution adjustment, and tooth region extraction. This preprocessing is performed using the OpenCV image processing library. For noise removal, OpenCV functions (e.g., cv2.fastNlMeansDenoisingColored) are used, and for resolution adjustment, cv2.resize is executed to adjust the number of pixels in the image to a certain standard.

[0087] After preprocessing, the image data is sent from the device to the server. An encryption protocol (e.g., SSL / TLS) is used to transmit the data, protecting the privacy of the data. The server then runs an artificial intelligence model (AI model) using deep learning libraries such as TensorFlow and PyTorch to analyze the received image data. The analysis evaluates the risk of cavities, periodontal disease, missed spots, dirt, stains, and wear. This analysis takes anywhere from a few seconds to a few minutes.

[0088] Once the server completes the analysis, it generates a textual result that includes a detailed assessment of the condition of the teeth and highlights any specific risks, such as a diagnosis that reads, "Your upper right molar is suspected of having cavities."

[0089] The generated analysis results are then sent from the server to the device using an encryption protocol. The device receives the analysis results and displays them visually to the user. The design is intuitive and easy for users to understand, including a function that highlights problem areas.

[0090] Additionally, the device will notify the user of specific measures and suggestions based on the analysis, including recommendations for specific brushing techniques and dental products, and links to make dentist appointments if necessary. For example, a message might read, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[0091] For example, a user takes a picture of their teeth with their smartphone and uploads it to an application. The image is then denoised and its resolution adjusted on the device. This pre-processed image is then sent to a server where it is analyzed using an AI model. A text result, such as "suspected cavity in upper right molar," is generated and returned to the device. The user can review the result in the application, which then recommends a specific toothbrush or toothpaste as a solution.

[0092] Example prompts to input to a generative AI model:

[0093] "Analyze images of your teeth taken with your smartphone to assess your risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear."

[0094] In this way, users can efficiently manage their dental health from the comfort of their own home, and maintain dental health through early detection and prevention.

[0095] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0096] Step 1:

[0097] The user takes an image of the teeth

[0098] Input: A user uses a smartphone or digital camera.

[0099] How it works: The user launches the app and follows the instructions to take a picture of their teeth, adjusting the lighting to get a clear view of the inside of their mouth.

[0100] Output: The captured tooth images are saved on your smartphone.

[0101] Step 2:

[0102] The device preprocesses the image

[0103] Input: User-taken tooth images.

[0104] Operation: The device receives the captured image and uses OpenCV to remove noise (e.g., cv2.fastNlMeansDenoisingColored), adjust the resolution (e.g., cv2.resize), and extract the tooth region.

[0105] Output: Pre-processed, sharp image data is generated.

[0106] Step 3:

[0107] The device sends the preprocessed image data to the server.

[0108] Input: Preprocessed image data.

[0109] How it works: The device sends preprocessed image data to a server over the internet, using encryption protocols such as SSL / TLS.

[0110] Output: The server receives the preprocessed image data.

[0111] Step 4:

[0112] The server analyzes the image data

[0113] Input: Preprocessed image data.

[0114] How it works: The server analyzes the received image data and runs AI models built using deep learning libraries such as TensorFlow and PyTorch. The models assess the risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear.

[0115] Output: An analysis result is generated that assesses dental health risks.

[0116] Step 5:

[0117] The server generates the analysis results

[0118] Input: The results analyzed using the AI ​​model.

[0119] How it works: The server generates a textual analysis result, which includes a detailed assessment and highlights specific risks, such as a diagnosis like "You have suspected cavities in your upper right molar."

[0120] Output: Analysis results in text format are generated.

[0121] Step 6:

[0122] The server sends the analysis results to the device.

[0123] Input: Analysis results in text format.

[0124] How it works: The server generates and sends the analysis results to the device, again using encryption protocols such as SSL / TLS to protect the privacy of the data.

[0125] Output: The device receives the analysis results.

[0126] Step 7:

[0127] The device displays the analysis results to the user.

[0128] Input: Analysis results in text format.

[0129] How it works: The device visually displays the analysis results it receives, including highlighting problem areas, designed to be intuitive for the user.

[0130] Output: The analysis results are displayed visually to the user.

[0131] Step 8:

[0132] The device notifies the user of countermeasures and suggestions

[0133] Input: Specific countermeasures and proposals based on the analysis results.

[0134] What it does: The device uses the analysis to notify the user of potential solutions and suggestions, including recommendations for specific brushing techniques and dental products, as well as links to schedule dentist appointments. For example, it might say, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[0135] Output: The user is notified of specific countermeasures and suggestions.

[0136] The above are the specific processing steps of the program of this system and their detailed operations.

[0137] (Application example 1)

[0138] 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."

[0139] In conventional dental diagnostic systems, the process in which users acquire and transmit images and AI performs analysis often raises security concerns. Furthermore, there were cases in which data security was not ensured even when the analysis results were visually displayed to the user. This posed a challenge, increasing the risk of unauthorized access to users' dental data by third parties. Another problem was the lack of encryption for analysis results and security breach detection capabilities.

[0140] 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.

[0141] In the present invention, the server includes a data encryption means and a security intrusion detection means, which allows data security and privacy to be enhanced in the process of transferring and displaying the analysis results.

[0142] An "image capture device" is a device that a user uses to capture an image of their teeth, and includes a smartphone, digital camera, etc.

[0143] "Preprocessing" refers to image processing operations such as noise removal, resolution adjustment, and tooth region extraction that are performed on the captured image.

[0144] "Server" means a computer system for receiving pre-processed image data, analyzing it using an artificial intelligence model, and generating analytical results.

[0145] An "artificial intelligence model" is a model trained based on machine learning and deep learning algorithms and used to analyze dental images and assess risks.

[0146] "Analysis Results" means a textual representation of dental health information analyzed using an artificial intelligence model.

[0147] "Data encryption means" refers to a method or device for encrypting images and analysis results, ensuring the security of information during data transfer and storage.

[0148] "Security intrusion detection means" refers to methods and devices for detecting unauthorized access to or tampering with data, and is necessary to maintain the security of the entire system.

[0149] "Visual display" refers to displaying the analysis results in a format that can be intuitively understood by the user, and includes a function to highlight problem areas.

[0150] To implement this invention, a user must first take an image of their teeth using an image capture device. A smartphone or digital camera is suitable as the image capture device. The user then launches a dedicated application and follows the application's instructions to capture an image of their teeth.

[0151] Next, the device (such as a smartphone) receives the captured image and performs preprocessing. This preprocessing includes using image processing libraries such as OpenCV to remove noise, adjust resolution, and extract tooth regions. For example, removing noise from the image and adjusting it to a certain resolution results in an image that is easier for the AI ​​model to analyze.

[0152] After preprocessing is complete, the device sends the preprocessed image data to a server, which then analyzes it using an artificial intelligence (AI) model. The AI ​​model, trained using a framework such as TensorFlow, evaluates the image for cavities, periodontal disease, missed spots, dirt, stains, and wear.

[0153] The server generates the analysis results in text format and encrypts them using a cryptography library to ensure the privacy and security of the user's data. The encrypted analysis results are then sent back to the device from the server.

[0154] The device receives the analysis results and visually displays them to the user, highlighting problem areas for intuitive understanding. It also provides specific solutions and suggestions based on the analysis results, such as recommending specific toothpaste products and displaying links to schedule appointments with a dentist, if necessary.

[0155] Additionally, the system incorporates a security breach detection function that uses the requests library to obtain security information from external services and detect unauthorized access, further enhancing the safety of analysis results and user data.

[0156] For example, use the following prompt:

[0157] "Analyze the image below and assess the health of your teeth."

[0158] This invention allows users to easily check their dental health at home and take appropriate measures.In addition, data security and privacy are fully ensured, making it a system that can be used with peace of mind.

[0159] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0160] Step 1:

[0161] A user takes an image of the teeth using an image capture device.

[0162] Input: A smartphone or digital camera to photograph the user's teeth

[0163] How it works: The user launches the dedicated application and follows the on-screen instructions to take pictures of their teeth from the desired angles.

[0164] Output: Image data of photographed teeth

[0165] Step 2:

[0166] The device (e.g., a smartphone) preprocesses the tooth images taken.

[0167] Input: Image data of photographed teeth

[0168] How it works: The image is denoised, the resolution is adjusted, and the tooth regions are extracted using OpenCV.

[0169] Output: Preprocessed image data

[0170] Step 3:

[0171] The terminal transmits the preprocessed image data to the server.

[0172] Input: Preprocessed image data

[0173] What it does: The device sends image data to a server via an internet connection.

[0174] Output: Preprocessed image data sent to the server

[0175] Step 4:

[0176] The server receives the pre-processed image data and analyzes it using an artificial intelligence model.

[0177] Input: Preprocessed image data sent from the terminal

[0178] How it works: The server uses an AI model trained with TensorFlow to analyze image data and assess the risk of cavities, periodontal disease, etc.

[0179] Output: Analysis result data

[0180] Step 5:

[0181] The server generates the analysis results in text format and encrypts the data.

[0182] Input: Analysis result data

[0183] How it works: The server uses a cryptography library to convert the parsed results into text and then encrypts the text.

[0184] Output: Encrypted analysis result text data

[0185] Step 6:

[0186] The server sends the encrypted analysis results to the terminal.

[0187] Input: Encrypted analysis result text data

[0188] What it does: Sends encrypted data over the internet to your device

[0189] Output: Encrypted analysis result text data sent to the terminal

[0190] Step 7:

[0191] The terminal decrypts the encrypted analysis results and visually displays them to the user.

[0192] Input: Encrypted analysis result text data sent from the server

[0193] How it works: The device decrypts the data using a cryptography library, highlights problem areas, and presents the analysis results to the user in an intuitive manner.

[0194] Output: Analysis results visually displayed to the user

[0195] Step 8:

[0196] The device will provide specific countermeasures and suggestions based on the analysis results.

[0197] Input: Decrypted analysis result text data

[0198] What it does: Based on the analysis, it recommends specific brushing techniques and dental products, and provides a link to book a dentist appointment if needed.

[0199] Output: Specific countermeasures and proposal information provided

[0200] Step 9:

[0201] A security breach detection function is in operation to monitor the security status of the entire system.

[0202] Input: Data handled throughout the system and system operation information

[0203] Operation: Uses the requests library to obtain security information from external services and detect unauthorized access.

[0204] Output: Alerts or log information about the security status

[0205] 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.

[0206] This invention relates to a system that allows users to easily check their dental health at home and take appropriate measures. In addition to conventional image analysis, this invention combines an emotion engine that recognizes and analyzes the user's emotional state to provide more effective feedback.

[0207] First, the user takes a picture of their teeth using an image capture device such as a smartphone or digital camera. The user then launches the application and follows the on-screen instructions to capture the tooth image. At this time, the emotion engine is also activated, analyzing the user's facial expressions and recognizing their emotional state.

[0208] Next, the device (such as a smartphone) receives the captured tooth image and the user's emotional state data. The tooth image is stored in local storage, as is the emotional data obtained by the emotion engine.

[0209] The device performs pre-processing on the stored tooth images, including noise reduction, resolution adjustment, and tooth region extraction, to obtain the clearest and most appropriate images, and prepares the emotion data to be sent to the server.

[0210] After preprocessing is complete, the device sends the preprocessed image data and emotion data to a server. The server receives the data and analyzes it using an artificial intelligence model (AI model). Specifically, the AI ​​model evaluates the risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear. The analysis results include a detailed assessment of the condition of the teeth and highlights specific risks.

[0211] Once the server completes the analysis, it generates the analysis results in text format. The system then adjusts the feedback based on the user's emotional state. For example, if the user is feeling anxious, the system may include an encouraging message.

[0212] The generated analysis results and emotion-based feedback are sent from the server to the device. The device receives these results and visually displays them to the user. The display format is designed to be intuitive and easy for the user to understand. For example, it includes a function to highlight problem areas.

[0213] The device also offers specific strategies and suggestions based on the analysis and emotional state, including specific brushing techniques, recommendations for appropriate dental products, and even links to make dentist appointments if needed. For example, a notification might say, "You suspect you have a cavity in your upper right molar. Don't worry. Use specific dental products to prevent it. Click the link for more information."

[0214] In this way, users can feel more secure in managing their dental health by receiving feedback based on their emotional state. The combination of the emotion engine improves the user experience and increases motivation to maintain dental health.

[0215] The processing flow will be explained below.

[0216] Step 1:

[0217] The user launches the application and takes an image of their teeth using an image capture device (such as a smartphone or digital camera). At this time, the application captures the user's facial expressions in real time and recognizes the user's emotional state using an emotion engine.

[0218] Step 2:

[0219] The device receives the captured tooth images and the user's emotion data, which are then stored in local storage. The captured emotion data includes emotions inferred from the user's facial expressions (e.g., anxiety, relief, doubt, etc.).

[0220] Step 3:

[0221] The device removes noise from the tooth images stored in the device. Specific methods for noise removal include Gaussian filters and median filters.

[0222] Step 4:

[0223] The device extracts the tooth region from the image and uses segmentation techniques to separate the tooth from the background and extract only the tooth portion. Specifically, it uses an edge detection algorithm and a region growing algorithm.

[0224] Step 5:

[0225] The device adjusts the image resolution, scaling the image to the appropriate resolution for optimal analysis by the AI ​​model. Specifically, resolution conversion techniques such as bicubic interpolation are used.

[0226] Step 6:

[0227] The terminal transmits the preprocessed image data and emotion data to the server.

[0228] Step 7:

[0229] The server receives the preprocessed image data and emotion data.

[0230] Step 8:

[0231] The server inputs the received image data into an AI model, which is trained using machine learning and deep learning techniques to analyze the dental health status. Specifically, deep learning algorithms such as convolutional neural networks (CNNs) are used.

[0232] Step 9:

[0233] The server uses AI models to analyze the risk of cavities, periodontal disease, missed spots, stains, discoloration, wear, etc. For example, the AI ​​model analyzes specific pixel patterns in the image to identify areas that may be prone to cavities.

[0234] Step 10:

[0235] The server generates the analysis results in text format, such as a specific diagnosis such as "You may have a cavity in your upper right molar."

[0236] Step 11:

[0237] The server tailors the feedback based on the user's emotional state, for example, including encouraging messages if the user is feeling anxious.

[0238] Step 12:

[0239] The server sends the generated analysis results and feedback based on the emotions to the device.

[0240] Step 13:

[0241] The terminal visually displays the analysis results and feedback received from the server to the user. For example, the display format may highlight risky areas to visually draw attention.

[0242] Step 14:

[0243] The device will then provide specific solutions and suggestions based on the analysis and emotional state. This could include recommendations for specific brushing techniques or dental products, or even a link to make a dentist appointment. For example, a notification might say, "You suspect you have a cavity in your upper right molar. Don't worry. Use specific toothpaste products to prevent this. Click the link for more information."

[0244] Example 2

[0245] 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."

[0246] Current dental health monitoring systems often leave users feeling anxious because they do not provide feedback that takes into account the user's emotional state. Furthermore, conventional systems do not comprehensively pre-process images or recognize emotional states, so analysis results may not be accurate enough.

[0247] 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.

[0248] In this invention, the server includes means for receiving the preprocessed image and emotional state data, analyzing the data using a generative AI model, and generating analysis results in text format, means for generating feedback based on the generated analysis results and the user's emotional state, and means for transmitting the analysis results and feedback generated by the server to the image capture device, thereby enabling the provision of accurate analysis results and feedback that take the user's emotional state into consideration.

[0249] An "image capture device" is a device that a user uses to take an image of their teeth, including, for example, a smartphone or digital camera.

[0250] "Preprocessing" refers to the process of preparing the acquired image for analysis by removing noise, adjusting resolution, extracting tooth regions, etc.

[0251] "Emotional state" is data indicating the psychological state recognized from the user's facial expression, and includes emotions such as anxiety, relief, and surprise.

[0252] "Server" refers to a central processing unit for receiving pre-processed image data and emotion data for analysis and feedback generation.

[0253] A "generative AI model" is an artificial intelligence model used to analyze image data and emotional data, including models that use deep learning.

[0254] "Analysis results" refers to the assessment and diagnostic information regarding dental health obtained by the generative AI model.

[0255] "Feedback" refers to messages and advice generated based on the analysis results and emotional state, and includes specific countermeasures and suggestions for the user.

[0256] "Specific countermeasures and suggestions" refers to instructions that show users specific actions to take or products to use based on the analysis results, as well as links to make dentist appointments if necessary.

[0257] This invention relates to a system that allows users to easily check their dental health at home and take appropriate measures. The invention is implemented using an image acquisition device, a terminal, a server, and a generative AI model. The specific configuration and operation are described below.

[0258] First, the user takes an image of their teeth using an image capture device such as a smartphone or digital camera. For example, the user launches a camera app on their smartphone and takes a photo of their teeth following the instruction to "hold the smartphone close to your mouth and show your teeth." This allows the image capture device to capture an image of the user's teeth.

[0259] The device then receives the captured image and uses an emotion engine to analyze the user's emotional state. The emotion engine analyzes the user's facial expressions in real time and recognizes emotions such as anxiety, relief, and surprise. After the emotional state is recognized, the device stores the captured tooth image and emotion data.

[0260] The device then performs preprocessing on the saved tooth images, such as noise reduction, resolution adjustment, and tooth region extraction. Once preprocessing is complete, the preprocessed image data and emotion data are sent to the server. For security reasons, the HTTPS protocol is used for data transmission.

[0261] The server receives the preprocessed image data and emotion data and analyzes the data using a generative AI model. Specifically, the AI ​​model (e.g., TensorFlow or PyTorch) evaluates the risk of cavities, periodontal disease, and incomplete brushing. As a result of the risk assessment, detailed analysis information about the condition of the teeth is generated.

[0262] The server then generates feedback based on the analysis and the user's emotional state. For example, if the user is feeling anxious, it generates a gentle message such as, "Your teeth are generally healthy, but there are some areas that need cleaning. Don't worry. We'll try to take a little more time next time."

[0263] The generated analysis results and feedback are sent from the server to the device. The device visually displays the received analysis results and feedback to the user. Specifically, it has a function to highlight problem areas and visually explain them using animations. In addition, it provides the user with specific countermeasures and suggestions based on the analysis results. For example, a notification may be displayed saying, "You may have a cavity in your upper right molar. Use a specific toothpaste gel to prevent this. Click here for details."

[0264] This allows users to easily check their dental health at home and take appropriate measures while receiving feedback that takes into account their emotional state. Below are examples of prompts for the generative AI model.

[0265] Example prompt sentence:

[0266] "Analyze this image to assess the risk of cavities and periodontal disease. Generate feedback with detailed results."

[0267] "Because the user's emotional state is anxious, provide gentle feedback. For example, include a message like, 'Don't worry. Let's take a little more time next time.'"

[0268] The above is a specific embodiment for carrying out the present invention. The present invention enables users to manage their dental health with peace of mind and to take appropriate measures.

[0269] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0270] System processing flow and specific explanation

[0271] Step 1:

[0272] The user takes an image of their teeth using a smartphone or digital camera.

[0273] Input: The user holds an image capture device (such as a smartphone or digital camera) and takes an image of the teeth.

[0274] Specific operation: The user launches the smartphone camera app and takes a photo of their teeth by following the instructions to "hold the smartphone close to your mouth and show your teeth." A "Take a photo" button appears on the screen, and the user presses it to capture the image.

[0275] Output: Image data of the photographed teeth.

[0276] Step 2:

[0277] The device analyzes the captured images of the teeth and the user's facial expressions to recognize their emotional state and store that data.

[0278] Input: Dental image data and user facial expression data.

[0279] Specific operation: The emotion engine analyzes the user's facial expressions in real time and recognizes emotions such as anxiety, relief, surprise, etc. In parallel, it acquires dental image data.

[0280] Output: The tooth image data and the recognized emotion data are saved in local storage.

[0281] Step 3:

[0282] The device performs preprocessing on the stored tooth images, such as noise removal, resolution adjustment, and tooth region extraction.

[0283] Input: Stored tooth image data.

[0284] Specific operation: Using OpenCV library, apply noise reduction filter to improve image quality, unify resolution and apply tooth region extraction algorithm to identify teeth.

[0285] Output: Preprocessed tooth image data.

[0286] Step 4:

[0287] The terminal transmits the preprocessed image data and emotion data to the server.

[0288] Input: Preprocessed dental image data and emotion data.

[0289] What it does: Securely uploads data to the server using the HTTPS protocol. Sends a POST request to an API endpoint to transfer the data.

[0290] Output: Preprocessed image data and emotion data sent to the server.

[0291] Step 5:

[0292] The server receives the preprocessed image data and emotion data, analyzes them using a generative AI model, and generates the analysis results in text format.

[0293] Input: Preprocessed dental image data and emotion data.

[0294] Specific operation: The server runs a generative AI model using TensorFlow and PyTorch to assess the risk of cavities, periodontal disease, and missed brushing spots. The results of the AI ​​model are formatted in text format.

[0295] Output: Text data of the analysis results.

[0296] Step 6:

[0297] The server generates feedback based on the analysis results and the user's emotional state.

[0298] Input: Text data and sentiment data from the analysis results.

[0299] Specific behavior: Based on the analysis results, a feedback message is generated that takes into account the user's emotional state. For example, for a user who is feeling anxious, a gentle message is created saying, "Your teeth are generally healthy, but there are some areas that need brushing. Don't worry. We'll try to take a little more time next time."

[0300] Output: The generated feedback message.

[0301] Step 7:

[0302] The server sends the generated analysis results and feedback to the terminal.

[0303] Input: Text data of generated feedback messages and analysis results.

[0304] Specific operation: The generated data is uploaded to the terminal via the HTTPS protocol, and a POST request is sent to the API endpoint to transfer the data.

[0305] Output: Analysis results and feedback messages sent to the terminal.

[0306] Step 8:

[0307] The analysis results and feedback received by the device are visually displayed to the user, and specific countermeasures and suggestions are provided.

[0308] Input: Received analysis result data and feedback messages.

[0309] Specific operation: A UI (user interface) is constructed to visually display the analysis results in an easy-to-understand manner. Problem areas are highlighted and explained using animation. Furthermore, specific countermeasures and suggestions are displayed as necessary, such as a notification that reads, "You may have cavities in your upper right molar. Use a specific toothpaste gel to prevent this. Click here for details."

[0310] Output: Visual display and suggested actions to the user.

[0311] This series of processes allows users to easily check the health of their teeth at home and receive appropriate feedback, allowing them to take care of their teeth with peace of mind.

[0312] (Application example 2)

[0313] 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."

[0314] Conventional dental image analysis systems have the problem that they do not provide feedback that takes into account the user's emotional state, making it difficult to completely alleviate the user's anxiety. In particular, there is a demand for systems that allow customers to manage their health on the spot with peace of mind in brick-and-mortar stores such as dental clinics and beauty salons.

[0315] 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: means for a user to capture an image of their teeth using an image capture device; means for the image capture device to preprocess the captured tooth image and the user's facial expression data and transmit the preprocessed image and facial expression data to the server; means for the server to receive the preprocessed image and facial expression data, analyze them using an artificial intelligence model, and generate analysis results in text format; means for transmitting the analysis results generated by the server to the image capture device; and means for visually displaying the analysis results received by the image capture device to the user and providing specific countermeasures and suggestions based on the analysis results and the user's emotional state. This provides feedback that takes into account the user's emotional state, allowing customers to have their teeth checked at a physical store with peace of mind.

[0316] Understood. Below are definitions of important words.

[0317] A "user" is a person who uses an image capture device to check the health of their teeth.

[0318] An "image acquisition device" is a device that captures dental images and facial expression data, such as a smartphone, digital camera, smart glasses, or head-mounted display.

[0319] "Preprocessing" refers to performing processes such as noise removal, resolution adjustment, and tooth area extraction on captured images and data to make them suitable for analysis.

[0320] "Server" refers to a central computing device that receives pre-processed images and data and performs analysis using artificial intelligence models.

[0321] An "artificial intelligence model" is a computational program that uses machine learning algorithms to analyze images of teeth and evaluate cavities, periodontal disease, areas that have not been brushed properly, dirt, discoloration, wear, etc.

[0322] "Analysis Results" means the dental health assessment generated by the AI ​​model, provided in text format.

[0323] "Facial expression data" is data that indicates the emotional state of the user, and is information obtained from the user's facial expression using image recognition technology.

[0324] "Feedback" refers to information and suggested actions provided based on the analysis results and the user's emotional state. Step 1:

[0325] The user puts on smart glasses or a head-mounted display installed in a physical store and launches the application. At this time, the image capture device takes an image of the user's teeth, and the emotion engine analyzes the user's facial expressions to obtain emotion data.

[0326] Input: Images of the user's teeth, facial expression data

[0327] Output: Raw image data and raw emotion data for preprocessing

[0328] Step 2:

[0329] The device preprocesses the captured tooth images and emotion data, which includes noise removal, resolution adjustment, and tooth region extraction.

[0330] Input: Raw image data, raw emotion data

[0331] Output: Preprocessed image data, preprocessed emotion data

[0332] Step 3:

[0333] The device sends the preprocessed image data and emotion data to the cloud server, which receives the data.

[0334] Input: Preprocessed image data, preprocessed emotion data

[0335] Output: Image data and emotion data stored on a cloud server

[0336] Step 4:

[0337] The server analyzes the received data using an artificial intelligence model to assess dental health (cavities, periodontal disease, missed spots, stains, discoloration, wear, etc.) and adjusts the feedback based on emotional data.

[0338] Input: Image data and emotion data stored on a cloud server

[0339] Output: Detailed analysis results and feedback on dental health status

[0340] Step 5:

[0341] The server generates analysis results and sends feedback based on emotions to the device, which receives these results and visually displays them to the user.

[0342] Input: Analysis results, feedback content

[0343] Output: Analysis results and feedback displayed on your device

[0344] Step 6:

[0345] The device visually displays the analysis, highlights problem areas for the user, and provides specific solutions and suggestions based on the analysis and emotional state, such as specific brushing techniques, recommendations for appropriate dental products, and links to book dentist appointments if needed.

[0346] Input: Analysis results and feedback displayed on the device

[0347] Output: Visual analysis results, actionable recommendations, and a link to book an appointment with the dentist.

[0348] 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.

[0349] 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.

[0350] 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.

[0351] [Second embodiment]

[0352] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0353] 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.

[0354] 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).

[0355] 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.

[0356] 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.

[0357] 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).

[0358] 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.

[0359] 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.

[0360] 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.

[0361] 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.

[0362] 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.

[0363] 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."

[0364] The present invention relates to a system that allows a user to easily check the state of dental health at home and take appropriate measures. Specific embodiments for implementing this system are described below.

[0365] First, the user takes an image of their teeth using an image capture device such as a smartphone or digital camera. The user then launches the application and follows the instructions on the screen to capture the image.

[0366] Next, the device (such as a smartphone) receives the captured image and pre-processes it, including noise reduction, resolution adjustment, and tooth region extraction to obtain the clearest and most appropriate image.

[0367] After the preprocessing is complete, the device sends the preprocessed image data to a server. The server receives the image data and analyzes it using an artificial intelligence model (AI model). Specifically, the AI ​​model evaluates the risk of cavities, periodontal disease, missed spots, dirt, stains, and wear.

[0368] Once the server completes the analysis, it generates a textual result that includes a detailed assessment of the condition of the teeth and highlights any specific risks, such as a specific diagnosis like "Your upper right molar is suspected of having cavities."

[0369] The generated analysis results are sent from the server to the device. The device receives the analysis results and visually displays them to the user. The display format is designed to be intuitive and easy for users to understand. For example, it includes a function to highlight problem areas.

[0370] The device also offers specific strategies and suggestions based on the analysis, including recommendations for specific brushing techniques and dental products, and even links to schedule dentist appointments if needed. For example, a notification might say, "You suspect a cavity in your upper right molar. Use specific toothpaste products to prevent it. Click the link for more information."

[0371] In this way, users can effectively manage their dental health from the comfort of their own home, and maintain dental health through early detection and prevention.

[0372] The processing flow will be explained below.

[0373] Step 1:

[0374] The user launches the application and takes an image of the teeth using an image capture device (such as a smartphone or digital camera). The user follows the on-screen instructions to take an image in the appropriate position and under the appropriate lighting conditions.

[0375] Step 2:

[0376] The device receives the captured tooth images and stores them in local storage.

[0377] Step 3:

[0378] The device denoises the stored images by using a filtering algorithm to reduce unavoidable image noise.

[0379] Step 4:

[0380] The device extracts the tooth region from the image and uses segmentation technology to separate the tooth from the background, extracting only the tooth portion.

[0381] Step 5:

[0382] The device adjusts the image resolution, scaling the image to the appropriate resolution for optimal analysis by the AI ​​model.

[0383] Step 6:

[0384] The terminal transmits the preprocessed image data to the server.

[0385] Step 7:

[0386] A server receives the preprocessed image data.

[0387] Step 8:

[0388] The server inputs the received image data into an AI model, which is trained using machine learning and deep learning, and analyzes the dental health status.

[0389] Step 9:

[0390] The server uses AI models to analyze the risk of cavities, periodontal disease, missed spots, stains, discoloration, wear, etc. For example, the AI ​​model analyzes specific pixel patterns in the image to identify areas that may be prone to cavities.

[0391] Step 10:

[0392] The server generates the analysis results in text format, such as a specific diagnosis such as "You may have a cavity in your upper right molar."

[0393] Step 11:

[0394] The server transmits the generated analysis results to the terminal.

[0395] Step 12:

[0396] The device visually displays the analysis results received from the server to the user, for example highlighting risk areas based on the analysis results.

[0397] Step 13:

[0398] The device will then provide specific solutions and suggestions based on the analysis, such as recommendations for specific toothpaste products and links to make dentist appointments. For example, it might say, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[0399] Example 1

[0400] 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."

[0401] Conventional dental health management systems have the drawback of making it difficult for users to easily evaluate the condition of their teeth at home and take appropriate measures. Furthermore, they require users to visit a dentist in person, which is a significant time and financial burden. For this reason, there is a demand for a method to easily check the health of teeth and detect abnormalities early.

[0402] 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.

[0403] In this invention, the server includes means for receiving the preprocessed images, performing an analysis using a deep learning model to evaluate the risk of cavities, periodontal disease, missed brushing areas, stains, discoloration, and wear, and generating the analysis results in text format, means for transmitting the analysis results generated by the server to the image acquisition device, and means for visually displaying the analysis results received by the image acquisition device to the user and providing specific countermeasures and suggestions based on the analysis results. This enables the user to easily evaluate the health of their teeth from the comfort of their own home and take appropriate measures.

[0404] "User" refers to an individual who uses an image capture device to take images of their teeth and have their health assessed.

[0405] "Image capture device" refers to a device for taking and pre-processing dental images, such as a smartphone or digital camera.

[0406] "Preprocessing" refers to the process of removing noise from the captured image, adjusting resolution, and extracting tooth areas to obtain optimal analysis results.

[0407] "Server" refers to a computing device responsible for receiving pre-processed image data, performing image analysis using deep learning models, and generating and transmitting the results.

[0408] A "deep learning model" is a mathematical model that uses artificial intelligence technology to analyze images and assess the risk of cavities, periodontal disease, missed spots, dirt, discoloration, and wear.

[0409] The "analysis results" are textual representations of the image evaluation results obtained using the deep learning model, providing users with a detailed assessment of their health status and highlighting specific risks.

[0410] "Measures and suggestions" include specific methods and product recommendations for users to improve their health based on the analysis results, as well as links to make dentist appointments if necessary.

[0411] A "notification" is a message that the image acquisition device visually displays to the user the analysis results and countermeasures or suggestions.

[0412] "Dentist appointment link" refers to a link on the Internet that allows a user to schedule a dentist appointment if necessary.

[0413] This invention provides a system that allows users to easily check the state of their dental health at home and take appropriate measures. Specific embodiments for implementing this system are described below.

[0414] Users take pictures of their teeth using an image capture device such as a smartphone or digital camera. They launch a dedicated application and follow the instructions on the screen to capture images of their teeth. When taking a photo, it is recommended to adjust the lighting so that the inside of the mouth can be seen clearly.

[0415] Next, the device (such as a smartphone) receives the captured image and performs preprocessing such as noise removal, resolution adjustment, and tooth region extraction. This preprocessing is performed using the OpenCV image processing library. For noise removal, OpenCV functions (e.g., cv2.fastNlMeansDenoisingColored) are used, and for resolution adjustment, cv2.resize is executed to adjust the number of pixels in the image to a certain standard.

[0416] After preprocessing, the image data is sent from the device to the server. An encryption protocol (e.g., SSL / TLS) is used to transmit the data, protecting the privacy of the data. The server then runs an artificial intelligence model (AI model) using deep learning libraries such as TensorFlow and PyTorch to analyze the received image data. The analysis evaluates the risk of cavities, periodontal disease, missed spots, dirt, stains, and wear. This analysis takes anywhere from a few seconds to a few minutes.

[0417] Once the server completes the analysis, it generates a textual result that includes a detailed assessment of the condition of the teeth and highlights any specific risks, such as a diagnosis that reads, "Your upper right molar is suspected of having cavities."

[0418] The generated analysis results are then sent from the server to the device using an encryption protocol. The device receives the analysis results and displays them visually to the user. The design is intuitive and easy for users to understand, including a function that highlights problem areas.

[0419] Additionally, the device will notify the user of specific measures and suggestions based on the analysis, including recommendations for specific brushing techniques and dental products, and links to make dentist appointments if necessary. For example, a message might read, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[0420] For example, a user takes a picture of their teeth with their smartphone and uploads it to an application. The image is then denoised and its resolution adjusted on the device. This pre-processed image is then sent to a server where it is analyzed using an AI model. A text result, such as "suspected cavity in upper right molar," is generated and returned to the device. The user can review the result in the application, which then recommends a specific toothbrush or toothpaste as a solution.

[0421] Example prompts to input to a generative AI model:

[0422] "Analyze images of your teeth taken with your smartphone to assess your risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear."

[0423] In this way, users can efficiently manage their dental health from the comfort of their own home, and maintain dental health through early detection and prevention.

[0424] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0425] Step 1:

[0426] The user takes an image of the teeth

[0427] Input: A user uses a smartphone or digital camera.

[0428] How it works: The user launches the app and follows the instructions to take a picture of their teeth, adjusting the lighting to get a clear view of the inside of their mouth.

[0429] Output: The captured tooth images are saved on your smartphone.

[0430] Step 2:

[0431] The device preprocesses the image

[0432] Input: User-taken tooth images.

[0433] Operation: The device receives the captured image and uses OpenCV to remove noise (e.g., cv2.fastNlMeansDenoisingColored), adjust the resolution (e.g., cv2.resize), and extract the tooth region.

[0434] Output: Pre-processed, sharp image data is generated.

[0435] Step 3:

[0436] The device sends the preprocessed image data to the server.

[0437] Input: Preprocessed image data.

[0438] How it works: The device sends preprocessed image data to a server over the internet, using encryption protocols such as SSL / TLS.

[0439] Output: The server receives the preprocessed image data.

[0440] Step 4:

[0441] The server analyzes the image data

[0442] Input: Preprocessed image data.

[0443] How it works: The server analyzes the received image data and runs AI models built using deep learning libraries such as TensorFlow and PyTorch. The models assess the risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear.

[0444] Output: An analysis result is generated that assesses dental health risks.

[0445] Step 5:

[0446] The server generates the analysis results

[0447] Input: The results analyzed using the AI ​​model.

[0448] How it works: The server generates a textual analysis result, which includes a detailed assessment and highlights specific risks, such as a diagnosis like "You have suspected cavities in your upper right molar."

[0449] Output: Analysis results in text format are generated.

[0450] Step 6:

[0451] The server sends the analysis results to the device.

[0452] Input: Analysis results in text format.

[0453] How it works: The server generates and sends the analysis results to the device, again using encryption protocols such as SSL / TLS to protect the privacy of the data.

[0454] Output: The device receives the analysis results.

[0455] Step 7:

[0456] The device displays the analysis results to the user.

[0457] Input: Analysis results in text format.

[0458] How it works: The device visually displays the analysis results it receives, including highlighting problem areas, designed to be intuitive for the user.

[0459] Output: The analysis results are displayed visually to the user.

[0460] Step 8:

[0461] The device notifies the user of countermeasures and suggestions

[0462] Input: Specific countermeasures and proposals based on the analysis results.

[0463] What it does: The device uses the analysis to notify the user of potential solutions and suggestions, including recommendations for specific brushing techniques and dental products, as well as links to schedule dentist appointments. For example, it might say, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[0464] Output: The user is notified of specific countermeasures and suggestions.

[0465] The above are the specific processing steps of the program of this system and their detailed operations.

[0466] (Application example 1)

[0467] 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."

[0468] In conventional dental diagnostic systems, the process in which users acquire and transmit images and AI performs analysis often raises security concerns. Furthermore, there were cases in which data security was not ensured even when the analysis results were visually displayed to the user. This posed a challenge, increasing the risk of unauthorized access to users' dental data by third parties. Another problem was the lack of encryption for analysis results and security breach detection capabilities.

[0469] 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.

[0470] In the present invention, the server includes a data encryption means and a security intrusion detection means, which allows data security and privacy to be enhanced in the process of transferring and displaying the analysis results.

[0471] An "image capture device" is a device that a user uses to capture an image of their teeth, and includes a smartphone, digital camera, etc.

[0472] "Preprocessing" refers to image processing operations such as noise removal, resolution adjustment, and tooth region extraction that are performed on the captured image.

[0473] "Server" means a computer system for receiving pre-processed image data, analyzing it using an artificial intelligence model, and generating analytical results.

[0474] An "artificial intelligence model" is a model trained based on machine learning and deep learning algorithms and used to analyze dental images and assess risks.

[0475] "Analysis Results" means a textual representation of dental health information analyzed using an artificial intelligence model.

[0476] "Data encryption means" refers to a method or device for encrypting images and analysis results, ensuring the security of information during data transfer and storage.

[0477] "Security intrusion detection means" refers to methods and devices for detecting unauthorized access to or tampering with data, and is necessary to maintain the security of the entire system.

[0478] "Visual display" refers to displaying the analysis results in a format that can be intuitively understood by the user, and includes a function to highlight problem areas.

[0479] To implement this invention, a user must first take an image of their teeth using an image capture device. A smartphone or digital camera is suitable as the image capture device. The user then launches a dedicated application and follows the application's instructions to capture an image of their teeth.

[0480] Next, the device (such as a smartphone) receives the captured image and performs preprocessing. This preprocessing includes using image processing libraries such as OpenCV to remove noise, adjust resolution, and extract tooth regions. For example, removing noise from the image and adjusting it to a certain resolution results in an image that is easier for the AI ​​model to analyze.

[0481] After preprocessing is complete, the device sends the preprocessed image data to a server, which then analyzes it using an artificial intelligence (AI) model. The AI ​​model, trained using a framework such as TensorFlow, evaluates the image for cavities, periodontal disease, missed spots, dirt, stains, and wear.

[0482] The server generates the analysis results in text format and encrypts them using a cryptography library to ensure the privacy and security of the user's data. The encrypted analysis results are then sent back to the device from the server.

[0483] The device receives the analysis results and visually displays them to the user, highlighting problem areas for intuitive understanding. It also provides specific solutions and suggestions based on the analysis results, such as recommending specific toothpaste products and displaying links to schedule appointments with a dentist, if necessary.

[0484] Additionally, the system incorporates a security breach detection function that uses the requests library to obtain security information from external services and detect unauthorized access, further enhancing the safety of analysis results and user data.

[0485] For example, use the following prompt:

[0486] "Analyze the image below and assess the health of your teeth."

[0487] This invention allows users to easily check their dental health at home and take appropriate measures.In addition, data security and privacy are fully ensured, making it a system that can be used with peace of mind.

[0488] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0489] Step 1:

[0490] A user takes an image of the teeth using an image capture device.

[0491] Input: A smartphone or digital camera to photograph the user's teeth

[0492] How it works: The user launches the dedicated application and follows the on-screen instructions to take pictures of their teeth from the desired angles.

[0493] Output: Image data of photographed teeth

[0494] Step 2:

[0495] The device (e.g., a smartphone) preprocesses the tooth images taken.

[0496] Input: Image data of photographed teeth

[0497] How it works: The image is denoised, the resolution is adjusted, and the tooth regions are extracted using OpenCV.

[0498] Output: Preprocessed image data

[0499] Step 3:

[0500] The terminal transmits the preprocessed image data to the server.

[0501] Input: Preprocessed image data

[0502] What it does: The device sends image data to a server via an internet connection.

[0503] Output: Preprocessed image data sent to the server

[0504] Step 4:

[0505] The server receives the pre-processed image data and analyzes it using an artificial intelligence model.

[0506] Input: Preprocessed image data sent from the terminal

[0507] How it works: The server uses an AI model trained with TensorFlow to analyze image data and assess the risk of cavities, periodontal disease, etc.

[0508] Output: Analysis result data

[0509] Step 5:

[0510] The server generates the analysis results in text format and encrypts the data.

[0511] Input: Analysis result data

[0512] How it works: The server uses a cryptography library to convert the parsed results into text and then encrypts the text.

[0513] Output: Encrypted analysis result text data

[0514] Step 6:

[0515] The server sends the encrypted analysis results to the terminal.

[0516] Input: Encrypted analysis result text data

[0517] What it does: Sends encrypted data over the internet to your device

[0518] Output: Encrypted analysis result text data sent to the terminal

[0519] Step 7:

[0520] The terminal decrypts the encrypted analysis results and visually displays them to the user.

[0521] Input: Encrypted analysis result text data sent from the server

[0522] How it works: The device decrypts the data using a cryptography library, highlights problem areas, and presents the analysis results to the user in an intuitive manner.

[0523] Output: Analysis results visually displayed to the user

[0524] Step 8:

[0525] The device will provide specific countermeasures and suggestions based on the analysis results.

[0526] Input: Decrypted analysis result text data

[0527] What it does: Based on the analysis, it recommends specific brushing techniques and dental products, and provides a link to book a dentist appointment if needed.

[0528] Output: Specific countermeasures and proposal information provided

[0529] Step 9:

[0530] A security breach detection function is in operation to monitor the security status of the entire system.

[0531] Input: Data handled throughout the system and system operation information

[0532] Operation: Uses the requests library to obtain security information from external services and detect unauthorized access.

[0533] Output: Alerts or log information about the security status

[0534] 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.

[0535] This invention relates to a system that allows users to easily check their dental health at home and take appropriate measures. In addition to conventional image analysis, this invention combines an emotion engine that recognizes and analyzes the user's emotional state to provide more effective feedback.

[0536] First, the user takes a picture of their teeth using an image capture device such as a smartphone or digital camera. The user then launches the application and follows the on-screen instructions to capture the tooth image. At this time, the emotion engine is also activated, analyzing the user's facial expressions and recognizing their emotional state.

[0537] Next, the device (such as a smartphone) receives the captured tooth image and the user's emotional state data. The tooth image is stored in local storage, as is the emotional data obtained by the emotion engine.

[0538] The device performs pre-processing on the stored tooth images, including noise reduction, resolution adjustment, and tooth region extraction, to obtain the clearest and most appropriate images, and prepares the emotion data to be sent to the server.

[0539] After preprocessing is complete, the device sends the preprocessed image data and emotion data to a server. The server receives the data and analyzes it using an artificial intelligence model (AI model). Specifically, the AI ​​model evaluates the risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear. The analysis results include a detailed assessment of the condition of the teeth and highlights specific risks.

[0540] Once the server completes the analysis, it generates the analysis results in text format. The system then adjusts the feedback based on the user's emotional state. For example, if the user is feeling anxious, the system may include an encouraging message.

[0541] The generated analysis results and emotion-based feedback are sent from the server to the device. The device receives these results and visually displays them to the user. The display format is designed to be intuitive and easy for the user to understand. For example, it includes a function to highlight problem areas.

[0542] The device also offers specific strategies and suggestions based on the analysis and emotional state, including specific brushing techniques, recommendations for appropriate dental products, and even links to make dentist appointments if needed. For example, a notification might say, "You suspect you have a cavity in your upper right molar. Don't worry. Use specific dental products to prevent it. Click the link for more information."

[0543] In this way, users can feel more secure in managing their dental health by receiving feedback based on their emotional state. The combination of the emotion engine improves the user experience and increases motivation to maintain dental health.

[0544] The processing flow will be explained below.

[0545] Step 1:

[0546] The user launches the application and takes an image of their teeth using an image capture device (such as a smartphone or digital camera). At this time, the application captures the user's facial expressions in real time and recognizes the user's emotional state using an emotion engine.

[0547] Step 2:

[0548] The device receives the captured tooth images and the user's emotion data, which are then stored in local storage. The captured emotion data includes emotions inferred from the user's facial expressions (e.g., anxiety, relief, doubt, etc.).

[0549] Step 3:

[0550] The device removes noise from the tooth images stored in the device. Specific methods for noise removal include Gaussian filters and median filters.

[0551] Step 4:

[0552] The device extracts the tooth region from the image and uses segmentation techniques to separate the tooth from the background and extract only the tooth portion. Specifically, it uses an edge detection algorithm and a region growing algorithm.

[0553] Step 5:

[0554] The device adjusts the image resolution, scaling the image to the appropriate resolution for optimal analysis by the AI ​​model. Specifically, resolution conversion techniques such as bicubic interpolation are used.

[0555] Step 6:

[0556] The terminal transmits the preprocessed image data and emotion data to the server.

[0557] Step 7:

[0558] The server receives the preprocessed image data and emotion data.

[0559] Step 8:

[0560] The server inputs the received image data into an AI model, which is trained using machine learning and deep learning techniques to analyze the dental health status. Specifically, deep learning algorithms such as convolutional neural networks (CNNs) are used.

[0561] Step 9:

[0562] The server uses AI models to analyze the risk of cavities, periodontal disease, missed spots, stains, discoloration, wear, etc. For example, the AI ​​model analyzes specific pixel patterns in the image to identify areas that may be prone to cavities.

[0563] Step 10:

[0564] The server generates the analysis results in text format, such as a specific diagnosis such as "You may have a cavity in your upper right molar."

[0565] Step 11:

[0566] The server tailors the feedback based on the user's emotional state, for example, including encouraging messages if the user is feeling anxious.

[0567] Step 12:

[0568] The server sends the generated analysis results and feedback based on the emotions to the device.

[0569] Step 13:

[0570] The terminal visually displays the analysis results and feedback received from the server to the user. For example, the display format may highlight risky areas to visually draw attention.

[0571] Step 14:

[0572] The device will then provide specific solutions and suggestions based on the analysis and emotional state. This could include recommendations for specific brushing techniques or dental products, or even a link to make a dentist appointment. For example, a notification might say, "You suspect you have a cavity in your upper right molar. Don't worry. Use specific toothpaste products to prevent this. Click the link for more information."

[0573] Example 2

[0574] 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."

[0575] Current dental health monitoring systems often leave users feeling anxious because they do not provide feedback that takes into account the user's emotional state. Furthermore, conventional systems do not comprehensively pre-process images or recognize emotional states, so analysis results may not be accurate enough.

[0576] 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.

[0577] In this invention, the server includes means for receiving the preprocessed image and emotional state data, analyzing the data using a generative AI model, and generating analysis results in text format, means for generating feedback based on the generated analysis results and the user's emotional state, and means for transmitting the analysis results and feedback generated by the server to the image capture device, thereby enabling the provision of accurate analysis results and feedback that take the user's emotional state into consideration.

[0578] An "image capture device" is a device that a user uses to take an image of their teeth, including, for example, a smartphone or digital camera.

[0579] "Preprocessing" refers to the process of preparing the acquired image for analysis by removing noise, adjusting resolution, extracting tooth regions, etc.

[0580] "Emotional state" is data indicating the psychological state recognized from the user's facial expression, and includes emotions such as anxiety, relief, and surprise.

[0581] "Server" refers to a central processing unit for receiving pre-processed image data and emotion data for analysis and feedback generation.

[0582] A "generative AI model" is an artificial intelligence model used to analyze image data and emotional data, including models that use deep learning.

[0583] "Analysis results" refers to the assessment and diagnostic information regarding dental health obtained by the generative AI model.

[0584] "Feedback" refers to messages and advice generated based on the analysis results and emotional state, and includes specific countermeasures and suggestions for the user.

[0585] "Specific countermeasures and suggestions" refers to instructions that show users specific actions to take or products to use based on the analysis results, as well as links to make dentist appointments if necessary.

[0586] This invention relates to a system that allows users to easily check their dental health at home and take appropriate measures. The invention is implemented using an image acquisition device, a terminal, a server, and a generative AI model. The specific configuration and operation are described below.

[0587] First, the user takes an image of their teeth using an image capture device such as a smartphone or digital camera. For example, the user launches a camera app on their smartphone and takes a photo of their teeth following the instruction to "hold the smartphone close to your mouth and show your teeth." This allows the image capture device to capture an image of the user's teeth.

[0588] The device then receives the captured image and uses an emotion engine to analyze the user's emotional state. The emotion engine analyzes the user's facial expressions in real time and recognizes emotions such as anxiety, relief, and surprise. After the emotional state is recognized, the device stores the captured tooth image and emotion data.

[0589] The device then performs preprocessing on the saved tooth images, such as noise reduction, resolution adjustment, and tooth region extraction. Once preprocessing is complete, the preprocessed image data and emotion data are sent to the server. For security reasons, the HTTPS protocol is used for data transmission.

[0590] The server receives the preprocessed image data and emotion data and analyzes the data using a generative AI model. Specifically, the AI ​​model (e.g., TensorFlow or PyTorch) evaluates the risk of cavities, periodontal disease, and incomplete brushing. As a result of the risk assessment, detailed analysis information about the condition of the teeth is generated.

[0591] The server then generates feedback based on the analysis and the user's emotional state. For example, if the user is feeling anxious, it generates a gentle message such as, "Your teeth are generally healthy, but there are some areas that need cleaning. Don't worry. We'll try to take a little more time next time."

[0592] The generated analysis results and feedback are sent from the server to the device. The device visually displays the received analysis results and feedback to the user. Specifically, it has a function to highlight problem areas and visually explain them using animations. In addition, it provides the user with specific countermeasures and suggestions based on the analysis results. For example, a notification may be displayed saying, "You may have a cavity in your upper right molar. Use a specific toothpaste gel to prevent this. Click here for details."

[0593] This allows users to easily check their dental health at home and take appropriate measures while receiving feedback that takes into account their emotional state. Below are examples of prompts for the generative AI model.

[0594] Example prompt sentence:

[0595] "Analyze this image to assess the risk of cavities and periodontal disease. Generate feedback with detailed results."

[0596] "Because the user's emotional state is anxious, provide gentle feedback. For example, include a message like, 'Don't worry. Let's take a little more time next time.'"

[0597] The above is a specific embodiment for carrying out the present invention. The present invention enables users to manage their dental health with peace of mind and to take appropriate measures.

[0598] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0599] System processing flow and specific explanation

[0600] Step 1:

[0601] The user takes an image of their teeth using a smartphone or digital camera.

[0602] Input: The user holds an image capture device (such as a smartphone or digital camera) and takes an image of the teeth.

[0603] Specific operation: The user launches the smartphone camera app and takes a photo of their teeth by following the instructions to "hold the smartphone close to your mouth and show your teeth." A "Take a photo" button appears on the screen, and the user presses it to capture the image.

[0604] Output: Image data of the photographed teeth.

[0605] Step 2:

[0606] The device analyzes the captured images of the teeth and the user's facial expressions to recognize their emotional state and store that data.

[0607] Input: Dental image data and user facial expression data.

[0608] Specific operation: The emotion engine analyzes the user's facial expressions in real time and recognizes emotions such as anxiety, relief, surprise, etc. In parallel, it acquires dental image data.

[0609] Output: The tooth image data and the recognized emotion data are saved in local storage.

[0610] Step 3:

[0611] The device performs preprocessing on the stored tooth images, such as noise removal, resolution adjustment, and tooth region extraction.

[0612] Input: Stored tooth image data.

[0613] Specific operation: Using OpenCV library, apply noise reduction filter to improve image quality, unify resolution and apply tooth region extraction algorithm to identify teeth.

[0614] Output: Preprocessed tooth image data.

[0615] Step 4:

[0616] The terminal transmits the preprocessed image data and emotion data to the server.

[0617] Input: Preprocessed dental image data and emotion data.

[0618] What it does: Securely uploads data to the server using the HTTPS protocol. Sends a POST request to an API endpoint to transfer the data.

[0619] Output: Preprocessed image data and emotion data sent to the server.

[0620] Step 5:

[0621] The server receives the preprocessed image data and emotion data, analyzes them using a generative AI model, and generates the analysis results in text format.

[0622] Input: Preprocessed dental image data and emotion data.

[0623] Specific operation: The server runs a generative AI model using TensorFlow and PyTorch to assess the risk of cavities, periodontal disease, and missed brushing spots. The results of the AI ​​model are formatted in text format.

[0624] Output: Text data of the analysis results.

[0625] Step 6:

[0626] The server generates feedback based on the analysis results and the user's emotional state.

[0627] Input: Text data and sentiment data from the analysis results.

[0628] Specific behavior: Based on the analysis results, a feedback message is generated that takes into account the user's emotional state. For example, for a user who is feeling anxious, a gentle message is created saying, "Your teeth are generally healthy, but there are some areas that need brushing. Don't worry. We'll try to take a little more time next time."

[0629] Output: The generated feedback message.

[0630] Step 7:

[0631] The server sends the generated analysis results and feedback to the terminal.

[0632] Input: Text data of generated feedback messages and analysis results.

[0633] Specific operation: The generated data is uploaded to the terminal via the HTTPS protocol, and a POST request is sent to the API endpoint to transfer the data.

[0634] Output: Analysis results and feedback messages sent to the terminal.

[0635] Step 8:

[0636] The analysis results and feedback received by the device are visually displayed to the user, and specific countermeasures and suggestions are provided.

[0637] Input: Received analysis result data and feedback messages.

[0638] Specific operation: A UI (user interface) is constructed to visually display the analysis results in an easy-to-understand manner. Problem areas are highlighted and explained using animation. Furthermore, specific countermeasures and suggestions are displayed as necessary, such as a notification that reads, "You may have cavities in your upper right molar. Use a specific toothpaste gel to prevent this. Click here for details."

[0639] Output: Visual display and suggested actions to the user.

[0640] This series of processes allows users to easily check the health of their teeth at home and receive appropriate feedback, allowing them to take care of their teeth with peace of mind.

[0641] (Application example 2)

[0642] 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."

[0643] Conventional dental image analysis systems have the problem that they do not provide feedback that takes into account the user's emotional state, making it difficult to completely alleviate the user's anxiety. In particular, there is a demand for systems that allow customers to manage their health on the spot with peace of mind in brick-and-mortar stores such as dental clinics and beauty salons.

[0644] 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: means for a user to capture an image of their teeth using an image capture device; means for the image capture device to preprocess the captured tooth image and the user's facial expression data and transmit the preprocessed image and facial expression data to the server; means for the server to receive the preprocessed image and facial expression data, analyze them using an artificial intelligence model, and generate analysis results in text format; means for transmitting the analysis results generated by the server to the image capture device; and means for visually displaying the analysis results received by the image capture device to the user and providing specific countermeasures and suggestions based on the analysis results and the user's emotional state. This provides feedback that takes into account the user's emotional state, allowing customers to have their teeth checked at a physical store with peace of mind.

[0645] Understood. Below are definitions of important words.

[0646] A "user" is a person who uses an image capture device to check the health of their teeth.

[0647] An "image acquisition device" is a device that captures dental images and facial expression data, such as a smartphone, digital camera, smart glasses, or head-mounted display.

[0648] "Preprocessing" refers to performing processes such as noise removal, resolution adjustment, and tooth area extraction on captured images and data to make them suitable for analysis.

[0649] "Server" refers to a central computing device that receives pre-processed images and data and performs analysis using artificial intelligence models.

[0650] An "artificial intelligence model" is a computational program that uses machine learning algorithms to analyze images of teeth and evaluate cavities, periodontal disease, areas that have not been brushed properly, dirt, discoloration, wear, etc.

[0651] "Analysis Results" means the dental health assessment generated by the AI ​​model, provided in text format.

[0652] "Facial expression data" is data that indicates the emotional state of the user, and is information obtained from the user's facial expression using image recognition technology.

[0653] "Feedback" refers to information and suggested actions provided based on the analysis results and the user's emotional state. Step 1:

[0654] The user puts on smart glasses or a head-mounted display installed in a physical store and launches the application. At this time, the image capture device takes an image of the user's teeth, and the emotion engine analyzes the user's facial expressions to obtain emotion data.

[0655] Input: Images of the user's teeth, facial expression data

[0656] Output: Raw image data and raw emotion data for preprocessing

[0657] Step 2:

[0658] The device preprocesses the captured tooth images and emotion data, which includes noise removal, resolution adjustment, and tooth region extraction.

[0659] Input: Raw image data, raw emotion data

[0660] Output: Preprocessed image data, preprocessed emotion data

[0661] Step 3:

[0662] The device sends the preprocessed image data and emotion data to the cloud server, which receives the data.

[0663] Input: Preprocessed image data, preprocessed emotion data

[0664] Output: Image data and emotion data stored on a cloud server

[0665] Step 4:

[0666] The server analyzes the received data using an artificial intelligence model to assess dental health (cavities, periodontal disease, missed spots, stains, discoloration, wear, etc.) and adjusts the feedback based on emotional data.

[0667] Input: Image data and emotion data stored on a cloud server

[0668] Output: Detailed analysis results and feedback on dental health status

[0669] Step 5:

[0670] The server generates analysis results and sends feedback based on emotions to the device, which receives these results and visually displays them to the user.

[0671] Input: Analysis results, feedback content

[0672] Output: Analysis results and feedback displayed on your device

[0673] Step 6:

[0674] The device visually displays the analysis, highlights problem areas for the user, and provides specific solutions and suggestions based on the analysis and emotional state, such as specific brushing techniques, recommendations for appropriate dental products, and links to book dentist appointments if needed.

[0675] Input: Analysis results and feedback displayed on the device

[0676] Output: Visual analysis results, actionable recommendations, and a link to book an appointment with the dentist.

[0677] 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.

[0678] 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.

[0679] 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.

[0680] [Third embodiment]

[0681] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0682] 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.

[0683] 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).

[0684] 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.

[0685] 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.

[0686] 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).

[0687] 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.

[0688] 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.

[0689] 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.

[0690] 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.

[0691] 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.

[0692] 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."

[0693] The present invention relates to a system that allows a user to easily check the state of dental health at home and take appropriate measures. Specific embodiments for implementing this system are described below.

[0694] First, the user takes an image of their teeth using an image capture device such as a smartphone or digital camera. The user then launches the application and follows the instructions on the screen to capture the image.

[0695] Next, the device (such as a smartphone) receives the captured image and pre-processes it, including noise reduction, resolution adjustment, and tooth region extraction to obtain the clearest and most appropriate image.

[0696] After the preprocessing is complete, the device sends the preprocessed image data to a server. The server receives the image data and analyzes it using an artificial intelligence model (AI model). Specifically, the AI ​​model evaluates the risk of cavities, periodontal disease, missed spots, dirt, stains, and wear.

[0697] Once the server completes the analysis, it generates a textual result that includes a detailed assessment of the condition of the teeth and highlights any specific risks, such as a specific diagnosis like "Your upper right molar is suspected of having cavities."

[0698] The generated analysis results are sent from the server to the device. The device receives the analysis results and visually displays them to the user. The display format is designed to be intuitive and easy for users to understand. For example, it includes a function to highlight problem areas.

[0699] The device also offers specific strategies and suggestions based on the analysis, including recommendations for specific brushing techniques and dental products, and even links to schedule dentist appointments if needed. For example, a notification might say, "You suspect a cavity in your upper right molar. Use specific toothpaste products to prevent it. Click the link for more information."

[0700] In this way, users can effectively manage their dental health from the comfort of their own home, and maintain dental health through early detection and prevention.

[0701] The processing flow will be explained below.

[0702] Step 1:

[0703] The user launches the application and takes an image of the teeth using an image capture device (such as a smartphone or digital camera). The user follows the on-screen instructions to take an image in the appropriate position and under the appropriate lighting conditions.

[0704] Step 2:

[0705] The device receives the captured tooth images and stores them in local storage.

[0706] Step 3:

[0707] The device denoises the stored images by using a filtering algorithm to reduce unavoidable image noise.

[0708] Step 4:

[0709] The device extracts the tooth region from the image and uses segmentation technology to separate the tooth from the background, extracting only the tooth portion.

[0710] Step 5:

[0711] The device adjusts the image resolution, scaling the image to the appropriate resolution for optimal analysis by the AI ​​model.

[0712] Step 6:

[0713] The terminal transmits the preprocessed image data to the server.

[0714] Step 7:

[0715] A server receives the preprocessed image data.

[0716] Step 8:

[0717] The server inputs the received image data into an AI model, which is trained using machine learning and deep learning, and analyzes the dental health status.

[0718] Step 9:

[0719] The server uses AI models to analyze the risk of cavities, periodontal disease, missed spots, stains, discoloration, wear, etc. For example, the AI ​​model analyzes specific pixel patterns in the image to identify areas that may be prone to cavities.

[0720] Step 10:

[0721] The server generates the analysis results in text format, such as a specific diagnosis such as "You may have a cavity in your upper right molar."

[0722] Step 11:

[0723] The server transmits the generated analysis results to the terminal.

[0724] Step 12:

[0725] The device visually displays the analysis results received from the server to the user, for example highlighting risk areas based on the analysis results.

[0726] Step 13:

[0727] The device will then provide specific solutions and suggestions based on the analysis, such as recommendations for specific toothpaste products and links to make dentist appointments. For example, it might say, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[0728] Example 1

[0729] 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."

[0730] Conventional dental health management systems have the drawback of making it difficult for users to easily evaluate the condition of their teeth at home and take appropriate measures. Furthermore, they require users to visit a dentist in person, which is a significant time and financial burden. For this reason, there is a demand for a method to easily check the health of teeth and detect abnormalities early.

[0731] 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.

[0732] In this invention, the server includes means for receiving the preprocessed images, performing an analysis using a deep learning model to evaluate the risk of cavities, periodontal disease, missed brushing areas, stains, discoloration, and wear, and generating the analysis results in text format, means for transmitting the analysis results generated by the server to the image acquisition device, and means for visually displaying the analysis results received by the image acquisition device to the user and providing specific countermeasures and suggestions based on the analysis results. This enables the user to easily evaluate the health of their teeth from the comfort of their own home and take appropriate measures.

[0733] "User" refers to an individual who uses an image capture device to take images of their teeth and have their health assessed.

[0734] "Image capture device" refers to a device for taking and pre-processing dental images, such as a smartphone or digital camera.

[0735] "Preprocessing" refers to the process of removing noise from the captured image, adjusting resolution, and extracting tooth areas to obtain optimal analysis results.

[0736] "Server" refers to a computing device responsible for receiving pre-processed image data, performing image analysis using deep learning models, and generating and transmitting the results.

[0737] A "deep learning model" is a mathematical model that uses artificial intelligence technology to analyze images and assess the risk of cavities, periodontal disease, missed spots, dirt, discoloration, and wear.

[0738] The "analysis results" are textual representations of the image evaluation results obtained using the deep learning model, providing users with a detailed assessment of their health status and highlighting specific risks.

[0739] "Measures and suggestions" include specific methods and product recommendations for users to improve their health based on the analysis results, as well as links to make dentist appointments if necessary.

[0740] A "notification" is a message that the image acquisition device visually displays to the user the analysis results and countermeasures or suggestions.

[0741] "Dentist appointment link" refers to a link on the Internet that allows a user to schedule a dentist appointment if necessary.

[0742] This invention provides a system that allows users to easily check the state of their dental health at home and take appropriate measures. Specific embodiments for implementing this system are described below.

[0743] Users take pictures of their teeth using an image capture device such as a smartphone or digital camera. They launch a dedicated application and follow the instructions on the screen to capture images of their teeth. When taking a photo, it is recommended to adjust the lighting so that the inside of the mouth can be seen clearly.

[0744] Next, the device (such as a smartphone) receives the captured image and performs preprocessing such as noise removal, resolution adjustment, and tooth region extraction. This preprocessing is performed using the OpenCV image processing library. For noise removal, OpenCV functions (e.g., cv2.fastNlMeansDenoisingColored) are used, and for resolution adjustment, cv2.resize is executed to adjust the number of pixels in the image to a certain standard.

[0745] After preprocessing, the image data is sent from the device to the server. An encryption protocol (e.g., SSL / TLS) is used to transmit the data, protecting the privacy of the data. The server then runs an artificial intelligence model (AI model) using deep learning libraries such as TensorFlow and PyTorch to analyze the received image data. The analysis evaluates the risk of cavities, periodontal disease, missed spots, dirt, stains, and wear. This analysis takes anywhere from a few seconds to a few minutes.

[0746] Once the server completes the analysis, it generates a textual result that includes a detailed assessment of the condition of the teeth and highlights any specific risks, such as a diagnosis that reads, "Your upper right molar is suspected of having cavities."

[0747] The generated analysis results are then sent from the server to the device using an encryption protocol. The device receives the analysis results and displays them visually to the user. The design is intuitive and easy for users to understand, including a function that highlights problem areas.

[0748] Additionally, the device will notify the user of specific measures and suggestions based on the analysis, including recommendations for specific brushing techniques and dental products, and links to make dentist appointments if necessary. For example, a message might read, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[0749] For example, a user takes a picture of their teeth with their smartphone and uploads it to an application. The image is then denoised and its resolution adjusted on the device. This pre-processed image is then sent to a server where it is analyzed using an AI model. A text result, such as "suspected cavity in upper right molar," is generated and returned to the device. The user can review the result in the application, which then recommends a specific toothbrush or toothpaste as a solution.

[0750] Example prompts to input to a generative AI model:

[0751] "Analyze images of your teeth taken with your smartphone to assess your risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear."

[0752] In this way, users can efficiently manage their dental health from the comfort of their own home, and maintain dental health through early detection and prevention.

[0753] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0754] Step 1:

[0755] The user takes an image of the teeth

[0756] Input: A user uses a smartphone or digital camera.

[0757] How it works: The user launches the app and follows the instructions to take a picture of their teeth, adjusting the lighting to get a clear view of the inside of their mouth.

[0758] Output: The captured tooth images are saved on your smartphone.

[0759] Step 2:

[0760] The device preprocesses the image

[0761] Input: User-taken tooth images.

[0762] Operation: The device receives the captured image and uses OpenCV to remove noise (e.g., cv2.fastNlMeansDenoisingColored), adjust the resolution (e.g., cv2.resize), and extract the tooth region.

[0763] Output: Pre-processed, sharp image data is generated.

[0764] Step 3:

[0765] The device sends the preprocessed image data to the server.

[0766] Input: Preprocessed image data.

[0767] How it works: The device sends preprocessed image data to a server over the internet, using encryption protocols such as SSL / TLS.

[0768] Output: The server receives the preprocessed image data.

[0769] Step 4:

[0770] The server analyzes the image data

[0771] Input: Preprocessed image data.

[0772] How it works: The server analyzes the received image data and runs AI models built using deep learning libraries such as TensorFlow and PyTorch. The models assess the risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear.

[0773] Output: An analysis result is generated that assesses dental health risks.

[0774] Step 5:

[0775] The server generates the analysis results

[0776] Input: The results analyzed using the AI ​​model.

[0777] How it works: The server generates a textual analysis result, which includes a detailed assessment and highlights specific risks, such as a diagnosis like "You have suspected cavities in your upper right molar."

[0778] Output: Analysis results in text format are generated.

[0779] Step 6:

[0780] The server sends the analysis results to the device.

[0781] Input: Analysis results in text format.

[0782] How it works: The server generates and sends the analysis results to the device, again using encryption protocols such as SSL / TLS to protect the privacy of the data.

[0783] Output: The device receives the analysis results.

[0784] Step 7:

[0785] The device displays the analysis results to the user.

[0786] Input: Analysis results in text format.

[0787] How it works: The device visually displays the analysis results it receives, including highlighting problem areas, designed to be intuitive for the user.

[0788] Output: The analysis results are displayed visually to the user.

[0789] Step 8:

[0790] The device notifies the user of countermeasures and suggestions

[0791] Input: Specific countermeasures and proposals based on the analysis results.

[0792] What it does: The device uses the analysis to notify the user of potential solutions and suggestions, including recommendations for specific brushing techniques and dental products, as well as links to schedule dentist appointments. For example, it might say, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[0793] Output: The user is notified of specific countermeasures and suggestions.

[0794] The above are the specific processing steps of the program of this system and their detailed operations.

[0795] (Application example 1)

[0796] 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."

[0797] In conventional dental diagnostic systems, the process in which users acquire and transmit images and AI performs analysis often raises security concerns. Furthermore, there were cases in which data security was not ensured even when the analysis results were visually displayed to the user. This posed a challenge, increasing the risk of unauthorized access to users' dental data by third parties. Another problem was the lack of encryption for analysis results and security breach detection capabilities.

[0798] 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.

[0799] In the present invention, the server includes a data encryption means and a security intrusion detection means, which allows data security and privacy to be enhanced in the process of transferring and displaying the analysis results.

[0800] An "image capture device" is a device that a user uses to capture an image of their teeth, and includes a smartphone, digital camera, etc.

[0801] "Preprocessing" refers to image processing operations such as noise removal, resolution adjustment, and tooth region extraction that are performed on the captured image.

[0802] "Server" means a computer system for receiving pre-processed image data, analyzing it using an artificial intelligence model, and generating analytical results.

[0803] An "artificial intelligence model" is a model trained based on machine learning and deep learning algorithms and used to analyze dental images and assess risks.

[0804] "Analysis Results" means a textual representation of dental health information analyzed using an artificial intelligence model.

[0805] "Data encryption means" refers to a method or device for encrypting images and analysis results, ensuring the security of information during data transfer and storage.

[0806] "Security intrusion detection means" refers to methods and devices for detecting unauthorized access to or tampering with data, and is necessary to maintain the security of the entire system.

[0807] "Visual display" refers to displaying the analysis results in a format that can be intuitively understood by the user, and includes a function to highlight problem areas.

[0808] To implement this invention, a user must first take an image of their teeth using an image capture device. A smartphone or digital camera is suitable as the image capture device. The user then launches a dedicated application and follows the application's instructions to capture an image of their teeth.

[0809] Next, the device (such as a smartphone) receives the captured image and performs preprocessing. This preprocessing includes using image processing libraries such as OpenCV to remove noise, adjust resolution, and extract tooth regions. For example, removing noise from the image and adjusting it to a certain resolution results in an image that is easier for the AI ​​model to analyze.

[0810] After preprocessing is complete, the device sends the preprocessed image data to a server, which then analyzes it using an artificial intelligence (AI) model. The AI ​​model, trained using a framework such as TensorFlow, evaluates the image for cavities, periodontal disease, missed spots, dirt, stains, and wear.

[0811] The server generates the analysis results in text format and encrypts them using a cryptography library to ensure the privacy and security of the user's data. The encrypted analysis results are then sent back to the device from the server.

[0812] The device receives the analysis results and visually displays them to the user, highlighting problem areas for intuitive understanding. It also provides specific solutions and suggestions based on the analysis results, such as recommending specific toothpaste products and displaying links to schedule appointments with a dentist, if necessary.

[0813] Additionally, the system incorporates a security breach detection function that uses the requests library to obtain security information from external services and detect unauthorized access, further enhancing the safety of analysis results and user data.

[0814] For example, use the following prompt:

[0815] "Analyze the image below and assess the health of your teeth."

[0816] This invention allows users to easily check their dental health at home and take appropriate measures.In addition, data security and privacy are fully ensured, making it a system that can be used with peace of mind.

[0817] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0818] Step 1:

[0819] A user takes an image of the teeth using an image capture device.

[0820] Input: A smartphone or digital camera to photograph the user's teeth

[0821] How it works: The user launches the dedicated application and follows the on-screen instructions to take pictures of their teeth from the desired angles.

[0822] Output: Image data of photographed teeth

[0823] Step 2:

[0824] The device (e.g., a smartphone) preprocesses the tooth images taken.

[0825] Input: Image data of photographed teeth

[0826] How it works: The image is denoised, the resolution is adjusted, and the tooth regions are extracted using OpenCV.

[0827] Output: Preprocessed image data

[0828] Step 3:

[0829] The terminal transmits the preprocessed image data to the server.

[0830] Input: Preprocessed image data

[0831] What it does: The device sends image data to a server via an internet connection.

[0832] Output: Preprocessed image data sent to the server

[0833] Step 4:

[0834] The server receives the pre-processed image data and analyzes it using an artificial intelligence model.

[0835] Input: Preprocessed image data sent from the terminal

[0836] How it works: The server uses an AI model trained with TensorFlow to analyze image data and assess the risk of cavities, periodontal disease, etc.

[0837] Output: Analysis result data

[0838] Step 5:

[0839] The server generates the analysis results in text format and encrypts the data.

[0840] Input: Analysis result data

[0841] How it works: The server uses a cryptography library to convert the parsed results into text and then encrypts the text.

[0842] Output: Encrypted analysis result text data

[0843] Step 6:

[0844] The server sends the encrypted analysis results to the terminal.

[0845] Input: Encrypted analysis result text data

[0846] What it does: Sends encrypted data over the internet to your device

[0847] Output: Encrypted analysis result text data sent to the terminal

[0848] Step 7:

[0849] The terminal decrypts the encrypted analysis results and visually displays them to the user.

[0850] Input: Encrypted analysis result text data sent from the server

[0851] How it works: The device decrypts the data using a cryptography library, highlights problem areas, and presents the analysis results to the user in an intuitive manner.

[0852] Output: Analysis results visually displayed to the user

[0853] Step 8:

[0854] The device will provide specific countermeasures and suggestions based on the analysis results.

[0855] Input: Decrypted analysis result text data

[0856] What it does: Based on the analysis, it recommends specific brushing techniques and dental products, and provides a link to book a dentist appointment if needed.

[0857] Output: Specific countermeasures and proposal information provided

[0858] Step 9:

[0859] A security breach detection function is in operation to monitor the security status of the entire system.

[0860] Input: Data handled throughout the system and system operation information

[0861] Operation: Uses the requests library to obtain security information from external services and detect unauthorized access.

[0862] Output: Alerts or log information about the security status

[0863] 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.

[0864] This invention relates to a system that allows users to easily check their dental health at home and take appropriate measures. In addition to conventional image analysis, this invention combines an emotion engine that recognizes and analyzes the user's emotional state to provide more effective feedback.

[0865] First, the user takes a picture of their teeth using an image capture device such as a smartphone or digital camera. The user then launches the application and follows the on-screen instructions to capture the tooth image. At this time, the emotion engine is also activated, analyzing the user's facial expressions and recognizing their emotional state.

[0866] Next, the device (such as a smartphone) receives the captured tooth image and the user's emotional state data. The tooth image is stored in local storage, as is the emotional data obtained by the emotion engine.

[0867] The device performs pre-processing on the stored tooth images, including noise reduction, resolution adjustment, and tooth region extraction, to obtain the clearest and most appropriate images, and prepares the emotion data to be sent to the server.

[0868] After preprocessing is complete, the device sends the preprocessed image data and emotion data to a server. The server receives the data and analyzes it using an artificial intelligence model (AI model). Specifically, the AI ​​model evaluates the risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear. The analysis results include a detailed assessment of the condition of the teeth and highlights specific risks.

[0869] Once the server completes the analysis, it generates the analysis results in text format. The system then adjusts the feedback based on the user's emotional state. For example, if the user is feeling anxious, the system may include an encouraging message.

[0870] The generated analysis results and emotion-based feedback are sent from the server to the device. The device receives these results and visually displays them to the user. The display format is designed to be intuitive and easy for the user to understand. For example, it includes a function to highlight problem areas.

[0871] The device also offers specific strategies and suggestions based on the analysis and emotional state, including specific brushing techniques, recommendations for appropriate dental products, and even links to make dentist appointments if needed. For example, a notification might say, "You suspect you have a cavity in your upper right molar. Don't worry. Use specific dental products to prevent it. Click the link for more information."

[0872] In this way, users can feel more secure in managing their dental health by receiving feedback based on their emotional state. The combination of the emotion engine improves the user experience and increases motivation to maintain dental health.

[0873] The processing flow will be explained below.

[0874] Step 1:

[0875] The user launches the application and takes an image of their teeth using an image capture device (such as a smartphone or digital camera). At this time, the application captures the user's facial expressions in real time and recognizes the user's emotional state using an emotion engine.

[0876] Step 2:

[0877] The device receives the captured tooth images and the user's emotion data, which are then stored in local storage. The captured emotion data includes emotions inferred from the user's facial expressions (e.g., anxiety, relief, doubt, etc.).

[0878] Step 3:

[0879] The device removes noise from the tooth images stored in the device. Specific methods for noise removal include Gaussian filters and median filters.

[0880] Step 4:

[0881] The device extracts the tooth region from the image and uses segmentation techniques to separate the tooth from the background and extract only the tooth portion. Specifically, it uses an edge detection algorithm and a region growing algorithm.

[0882] Step 5:

[0883] The device adjusts the image resolution, scaling the image to the appropriate resolution for optimal analysis by the AI ​​model. Specifically, resolution conversion techniques such as bicubic interpolation are used.

[0884] Step 6:

[0885] The terminal transmits the preprocessed image data and emotion data to the server.

[0886] Step 7:

[0887] The server receives the preprocessed image data and emotion data.

[0888] Step 8:

[0889] The server inputs the received image data into an AI model, which is trained using machine learning and deep learning techniques to analyze the dental health status. Specifically, deep learning algorithms such as convolutional neural networks (CNNs) are used.

[0890] Step 9:

[0891] The server uses AI models to analyze the risk of cavities, periodontal disease, missed spots, stains, discoloration, wear, etc. For example, the AI ​​model analyzes specific pixel patterns in the image to identify areas that may be prone to cavities.

[0892] Step 10:

[0893] The server generates the analysis results in text format, such as a specific diagnosis such as "You may have a cavity in your upper right molar."

[0894] Step 11:

[0895] The server tailors the feedback based on the user's emotional state, for example, including encouraging messages if the user is feeling anxious.

[0896] Step 12:

[0897] The server sends the generated analysis results and feedback based on the emotions to the device.

[0898] Step 13:

[0899] The terminal visually displays the analysis results and feedback received from the server to the user. For example, the display format may highlight risky areas to visually draw attention.

[0900] Step 14:

[0901] The device will then provide specific solutions and suggestions based on the analysis and emotional state. This could include recommendations for specific brushing techniques or dental products, or even a link to make a dentist appointment. For example, a notification might say, "You suspect you have a cavity in your upper right molar. Don't worry. Use specific toothpaste products to prevent this. Click the link for more information."

[0902] Example 2

[0903] 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."

[0904] Current dental health monitoring systems often leave users feeling anxious because they do not provide feedback that takes into account the user's emotional state. Furthermore, conventional systems do not comprehensively pre-process images or recognize emotional states, so analysis results may not be accurate enough.

[0905] 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.

[0906] In this invention, the server includes means for receiving the preprocessed image and emotional state data, analyzing the data using a generative AI model, and generating analysis results in text format, means for generating feedback based on the generated analysis results and the user's emotional state, and means for transmitting the analysis results and feedback generated by the server to the image capture device, thereby enabling the provision of accurate analysis results and feedback that take the user's emotional state into consideration.

[0907] An "image capture device" is a device that a user uses to take an image of their teeth, including, for example, a smartphone or digital camera.

[0908] "Preprocessing" refers to the process of preparing the acquired image for analysis by removing noise, adjusting resolution, extracting tooth regions, etc.

[0909] "Emotional state" is data indicating the psychological state recognized from the user's facial expression, and includes emotions such as anxiety, relief, and surprise.

[0910] "Server" refers to a central processing unit for receiving pre-processed image data and emotion data for analysis and feedback generation.

[0911] A "generative AI model" is an artificial intelligence model used to analyze image data and emotional data, including models that use deep learning.

[0912] "Analysis results" refers to the assessment and diagnostic information regarding dental health obtained by the generative AI model.

[0913] "Feedback" refers to messages and advice generated based on the analysis results and emotional state, and includes specific countermeasures and suggestions for the user.

[0914] "Specific countermeasures and suggestions" refers to instructions that show users specific actions to take or products to use based on the analysis results, as well as links to make dentist appointments if necessary.

[0915] This invention relates to a system that allows users to easily check their dental health at home and take appropriate measures. The invention is implemented using an image acquisition device, a terminal, a server, and a generative AI model. The specific configuration and operation are described below.

[0916] First, the user takes an image of their teeth using an image capture device such as a smartphone or digital camera. For example, the user launches a camera app on their smartphone and takes a photo of their teeth following the instruction to "hold the smartphone close to your mouth and show your teeth." This allows the image capture device to capture an image of the user's teeth.

[0917] The device then receives the captured image and uses an emotion engine to analyze the user's emotional state. The emotion engine analyzes the user's facial expressions in real time and recognizes emotions such as anxiety, relief, and surprise. After the emotional state is recognized, the device stores the captured tooth image and emotion data.

[0918] The device then performs preprocessing on the saved tooth images, such as noise reduction, resolution adjustment, and tooth region extraction. Once preprocessing is complete, the preprocessed image data and emotion data are sent to the server. For security reasons, the HTTPS protocol is used for data transmission.

[0919] The server receives the preprocessed image data and emotion data and analyzes the data using a generative AI model. Specifically, the AI ​​model (e.g., TensorFlow or PyTorch) evaluates the risk of cavities, periodontal disease, and incomplete brushing. As a result of the risk assessment, detailed analysis information about the condition of the teeth is generated.

[0920] The server then generates feedback based on the analysis and the user's emotional state. For example, if the user is feeling anxious, it generates a gentle message such as, "Your teeth are generally healthy, but there are some areas that need cleaning. Don't worry. We'll try to take a little more time next time."

[0921] The generated analysis results and feedback are sent from the server to the device. The device visually displays the received analysis results and feedback to the user. Specifically, it has a function to highlight problem areas and visually explain them using animations. In addition, it provides the user with specific countermeasures and suggestions based on the analysis results. For example, a notification may be displayed saying, "You may have a cavity in your upper right molar. Use a specific toothpaste gel to prevent this. Click here for details."

[0922] This allows users to easily check their dental health at home and take appropriate measures while receiving feedback that takes into account their emotional state. Below are examples of prompts for the generative AI model.

[0923] Example prompt sentence:

[0924] "Analyze this image to assess the risk of cavities and periodontal disease. Generate feedback with detailed results."

[0925] "Because the user's emotional state is anxious, provide gentle feedback. For example, include a message like, 'Don't worry. Let's take a little more time next time.'"

[0926] The above is a specific embodiment for carrying out the present invention. The present invention enables users to manage their dental health with peace of mind and to take appropriate measures.

[0927] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0928] System processing flow and specific explanation

[0929] Step 1:

[0930] The user takes an image of their teeth using a smartphone or digital camera.

[0931] Input: The user holds an image capture device (such as a smartphone or digital camera) and takes an image of the teeth.

[0932] Specific operation: The user launches the smartphone camera app and takes a photo of their teeth by following the instructions to "hold the smartphone close to your mouth and show your teeth." A "Take a photo" button appears on the screen, and the user presses it to capture the image.

[0933] Output: Image data of the photographed teeth.

[0934] Step 2:

[0935] The device analyzes the captured images of the teeth and the user's facial expressions to recognize their emotional state and store that data.

[0936] Input: Dental image data and user facial expression data.

[0937] Specific operation: The emotion engine analyzes the user's facial expressions in real time and recognizes emotions such as anxiety, relief, surprise, etc. In parallel, it acquires dental image data.

[0938] Output: The tooth image data and the recognized emotion data are saved in local storage.

[0939] Step 3:

[0940] The device performs preprocessing on the stored tooth images, such as noise removal, resolution adjustment, and tooth region extraction.

[0941] Input: Stored tooth image data.

[0942] Specific operation: Using OpenCV library, apply noise reduction filter to improve image quality, unify resolution and apply tooth region extraction algorithm to identify teeth.

[0943] Output: Preprocessed tooth image data.

[0944] Step 4:

[0945] The terminal transmits the preprocessed image data and emotion data to the server.

[0946] Input: Preprocessed dental image data and emotion data.

[0947] What it does: Securely uploads data to the server using the HTTPS protocol. Sends a POST request to an API endpoint to transfer the data.

[0948] Output: Preprocessed image data and emotion data sent to the server.

[0949] Step 5:

[0950] The server receives the preprocessed image data and emotion data, analyzes them using a generative AI model, and generates the analysis results in text format.

[0951] Input: Preprocessed dental image data and emotion data.

[0952] Specific operation: The server runs a generative AI model using TensorFlow and PyTorch to assess the risk of cavities, periodontal disease, and missed brushing spots. The results of the AI ​​model are formatted in text format.

[0953] Output: Text data of the analysis results.

[0954] Step 6:

[0955] The server generates feedback based on the analysis results and the user's emotional state.

[0956] Input: Text data and sentiment data from the analysis results.

[0957] Specific behavior: Based on the analysis results, a feedback message is generated that takes into account the user's emotional state. For example, for a user who is feeling anxious, a gentle message is created saying, "Your teeth are generally healthy, but there are some areas that need brushing. Don't worry. We'll try to take a little more time next time."

[0958] Output: The generated feedback message.

[0959] Step 7:

[0960] The server sends the generated analysis results and feedback to the terminal.

[0961] Input: Text data of generated feedback messages and analysis results.

[0962] Specific operation: The generated data is uploaded to the terminal via the HTTPS protocol, and a POST request is sent to the API endpoint to transfer the data.

[0963] Output: Analysis results and feedback messages sent to the terminal.

[0964] Step 8:

[0965] The analysis results and feedback received by the device are visually displayed to the user, and specific countermeasures and suggestions are provided.

[0966] Input: Received analysis result data and feedback messages.

[0967] Specific operation: A UI (user interface) is constructed to visually display the analysis results in an easy-to-understand manner. Problem areas are highlighted and explained using animation. Furthermore, specific countermeasures and suggestions are displayed as necessary, such as a notification that reads, "You may have cavities in your upper right molar. Use a specific toothpaste gel to prevent this. Click here for details."

[0968] Output: Visual display and suggested actions to the user.

[0969] This series of processes allows users to easily check the health of their teeth at home and receive appropriate feedback, allowing them to take care of their teeth with peace of mind.

[0970] (Application example 2)

[0971] 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."

[0972] Conventional dental image analysis systems have the problem that they do not provide feedback that takes into account the user's emotional state, making it difficult to completely alleviate the user's anxiety. In particular, there is a demand for systems that allow customers to manage their health on the spot with peace of mind in brick-and-mortar stores such as dental clinics and beauty salons.

[0973] 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: means for a user to capture an image of their teeth using an image capture device; means for the image capture device to preprocess the captured tooth image and the user's facial expression data and transmit the preprocessed image and facial expression data to the server; means for the server to receive the preprocessed image and facial expression data, analyze them using an artificial intelligence model, and generate analysis results in text format; means for transmitting the analysis results generated by the server to the image capture device; and means for visually displaying the analysis results received by the image capture device to the user and providing specific countermeasures and suggestions based on the analysis results and the user's emotional state. This provides feedback that takes into account the user's emotional state, allowing customers to have their teeth checked at a physical store with peace of mind.

[0974] Understood. Below are definitions of important words.

[0975] A "user" is a person who uses an image capture device to check the health of their teeth.

[0976] An "image acquisition device" is a device that captures dental images and facial expression data, such as a smartphone, digital camera, smart glasses, or head-mounted display.

[0977] "Preprocessing" refers to performing processes such as noise removal, resolution adjustment, and tooth area extraction on captured images and data to make them suitable for analysis.

[0978] "Server" refers to a central computing device that receives pre-processed images and data and performs analysis using artificial intelligence models.

[0979] An "artificial intelligence model" is a computational program that uses machine learning algorithms to analyze images of teeth and evaluate cavities, periodontal disease, areas that have not been brushed properly, dirt, discoloration, wear, etc.

[0980] "Analysis Results" means the dental health assessment generated by the AI ​​model, provided in text format.

[0981] "Facial expression data" is data that indicates the emotional state of the user, and is information obtained from the user's facial expression using image recognition technology.

[0982] "Feedback" refers to information and suggested actions provided based on the analysis results and the user's emotional state. Step 1:

[0983] The user puts on smart glasses or a head-mounted display installed in a physical store and launches the application. At this time, the image capture device takes an image of the user's teeth, and the emotion engine analyzes the user's facial expressions to obtain emotion data.

[0984] Input: Images of the user's teeth, facial expression data

[0985] Output: Raw image data and raw emotion data for preprocessing

[0986] Step 2:

[0987] The device preprocesses the captured tooth images and emotion data, which includes noise removal, resolution adjustment, and tooth region extraction.

[0988] Input: Raw image data, raw emotion data

[0989] Output: Preprocessed image data, preprocessed emotion data

[0990] Step 3:

[0991] The device sends the preprocessed image data and emotion data to the cloud server, which receives the data.

[0992] Input: Preprocessed image data, preprocessed emotion data

[0993] Output: Image data and emotion data stored on a cloud server

[0994] Step 4:

[0995] The server analyzes the received data using an artificial intelligence model to assess dental health (cavities, periodontal disease, missed spots, stains, discoloration, wear, etc.) and adjusts the feedback based on emotional data.

[0996] Input: Image data and emotion data stored on a cloud server

[0997] Output: Detailed analysis results and feedback on dental health status

[0998] Step 5:

[0999] The server generates analysis results and sends feedback based on emotions to the device, which receives these results and visually displays them to the user.

[1000] Input: Analysis results, feedback content

[1001] Output: Analysis results and feedback displayed on your device

[1002] Step 6:

[1003] The device visually displays the analysis, highlights problem areas for the user, and provides specific solutions and suggestions based on the analysis and emotional state, such as specific brushing techniques, recommendations for appropriate dental products, and links to book dentist appointments if needed.

[1004] Input: Analysis results and feedback displayed on the device

[1005] Output: Visual analysis results, actionable recommendations, and a link to book an appointment with the dentist.

[1006] 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.

[1007] 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.

[1008] 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.

[1009] [Fourth embodiment]

[1010] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1011] 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.

[1012] 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).

[1013] 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.

[1014] 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.

[1015] 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).

[1016] 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.

[1017] 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.

[1018] 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.

[1019] 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.

[1020] 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.

[1021] 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.

[1022] 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."

[1023] The present invention relates to a system that allows a user to easily check the state of dental health at home and take appropriate measures. Specific embodiments for implementing this system are described below.

[1024] First, the user takes an image of their teeth using an image capture device such as a smartphone or digital camera. The user then launches the application and follows the instructions on the screen to capture the image.

[1025] Next, the device (such as a smartphone) receives the captured image and pre-processes it, including noise reduction, resolution adjustment, and tooth region extraction to obtain the clearest and most appropriate image.

[1026] After the preprocessing is complete, the device sends the preprocessed image data to a server. The server receives the image data and analyzes it using an artificial intelligence model (AI model). Specifically, the AI ​​model evaluates the risk of cavities, periodontal disease, missed spots, dirt, stains, and wear.

[1027] Once the server completes the analysis, it generates a textual result that includes a detailed assessment of the condition of the teeth and highlights any specific risks, such as a specific diagnosis like "Your upper right molar is suspected of having cavities."

[1028] The generated analysis results are sent from the server to the device. The device receives the analysis results and visually displays them to the user. The display format is designed to be intuitive and easy for users to understand. For example, it includes a function to highlight problem areas.

[1029] The device also offers specific solutions and suggestions based on the analysis, including recommendations for specific brushing techniques and dental products, and even links to make dentist appointments if needed. For example, a notification might say, "You suspect a cavity in your upper right molar. Use specific toothpaste products to prevent it. Click the link for more information."

[1030] In this way, users can effectively manage their dental health from the comfort of their own home, and maintain dental health through early detection and prevention.

[1031] The processing flow will be explained below.

[1032] Step 1:

[1033] The user launches the application and takes an image of the teeth using an image capture device (such as a smartphone or digital camera). The user follows the on-screen instructions to take an image in the appropriate position and under the appropriate lighting conditions.

[1034] Step 2:

[1035] The device receives the captured tooth images and stores them in local storage.

[1036] Step 3:

[1037] The device denoises the stored images by using a filtering algorithm to reduce unavoidable image noise.

[1038] Step 4:

[1039] The device extracts the tooth region from the image and uses segmentation technology to separate the tooth from the background, extracting only the tooth portion.

[1040] Step 5:

[1041] The device adjusts the image resolution, scaling the image to the appropriate resolution for optimal analysis by the AI ​​model.

[1042] Step 6:

[1043] The terminal transmits the preprocessed image data to the server.

[1044] Step 7:

[1045] A server receives the preprocessed image data.

[1046] Step 8:

[1047] The server inputs the received image data into an AI model, which is trained using machine learning and deep learning, and analyzes the dental health status.

[1048] Step 9:

[1049] The server uses AI models to analyze the risk of cavities, periodontal disease, missed spots, stains, discoloration, wear, etc. For example, the AI ​​model analyzes specific pixel patterns in the image to identify areas that may be prone to cavities.

[1050] Step 10:

[1051] The server generates the analysis results in text format, such as a specific diagnosis such as "You may have a cavity in your upper right molar."

[1052] Step 11:

[1053] The server transmits the generated analysis results to the terminal.

[1054] Step 12:

[1055] The device visually displays the analysis results received from the server to the user, for example highlighting risk areas based on the analysis results.

[1056] Step 13:

[1057] The device will then provide specific solutions and suggestions based on the analysis, such as recommendations for specific toothpaste products and links to make dentist appointments. For example, it might say, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[1058] Example 1

[1059] 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."

[1060] Conventional dental health management systems have the drawback of making it difficult for users to easily evaluate the condition of their teeth at home and take appropriate measures. Furthermore, they require users to visit a dentist in person, which is a significant time and financial burden. For this reason, there is a demand for a method to easily check the health of teeth and detect abnormalities early.

[1061] 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.

[1062] In this invention, the server includes means for receiving the preprocessed images, performing an analysis using a deep learning model to evaluate the risk of cavities, periodontal disease, missed brushing areas, stains, discoloration, and wear, and generating the analysis results in text format, means for transmitting the analysis results generated by the server to the image acquisition device, and means for visually displaying the analysis results received by the image acquisition device to the user and providing specific countermeasures and suggestions based on the analysis results. This enables the user to easily evaluate the health of their teeth from the comfort of their own home and take appropriate measures.

[1063] "User" refers to an individual who uses an image capture device to take images of their teeth and have their health assessed.

[1064] "Image capture device" refers to a device for taking and pre-processing dental images, such as a smartphone or digital camera.

[1065] "Preprocessing" refers to the process of removing noise from the captured image, adjusting resolution, and extracting tooth areas to obtain optimal analysis results.

[1066] "Server" refers to a computing device responsible for receiving pre-processed image data, performing image analysis using deep learning models, and generating and transmitting the results.

[1067] A "deep learning model" is a mathematical model that uses artificial intelligence technology to analyze images and assess the risk of cavities, periodontal disease, missed spots, dirt, discoloration, and wear.

[1068] The "analysis results" are textual representations of the image evaluation results obtained using the deep learning model, providing users with a detailed assessment of their health status and highlighting specific risks.

[1069] "Measures and suggestions" include specific methods and product recommendations for users to improve their health based on the analysis results, as well as links to make dentist appointments if necessary.

[1070] A "notification" is a message that the image acquisition device visually displays to the user the analysis results and countermeasures or suggestions.

[1071] "Dentist appointment link" refers to a link on the Internet that allows a user to schedule a dentist appointment if necessary.

[1072] This invention provides a system that allows users to easily check the state of their dental health at home and take appropriate measures. Specific embodiments for implementing this system are described below.

[1073] Users take pictures of their teeth using an image capture device such as a smartphone or digital camera. They launch a dedicated application and follow the instructions on the screen to capture images of their teeth. When taking a photo, it is recommended to adjust the lighting so that the inside of the mouth can be seen clearly.

[1074] Next, the device (such as a smartphone) receives the captured image and performs preprocessing such as noise removal, resolution adjustment, and tooth region extraction. This preprocessing is performed using the image processing library OpenCV. For noise removal, OpenCV functions (e.g., cv2.fastNlMeansDenoisingColored) are used, and for resolution adjustment, cv2.resize is executed to adjust the number of pixels in the image to a certain standard.

[1075] After preprocessing, the image data is sent from the device to the server. An encryption protocol (e.g., SSL / TLS) is used to transmit the data, protecting the privacy of the data. The server then runs an artificial intelligence model (AI model) using deep learning libraries such as TensorFlow and PyTorch to analyze the received image data. The analysis evaluates the risk of cavities, periodontal disease, missed spots, dirt, stains, and wear. This analysis takes anywhere from a few seconds to a few minutes.

[1076] Once the server completes the analysis, it generates a textual result that includes a detailed assessment of the condition of the teeth and highlights any specific risks, such as a diagnosis that reads, "Your upper right molar is suspected of having cavities."

[1077] The generated analysis results are then sent from the server to the device using an encryption protocol. The device receives the analysis results and displays them visually to the user. The design is intuitive and easy for users to understand, including a function that highlights problem areas.

[1078] Additionally, the device will notify the user of specific measures and suggestions based on the analysis, including recommendations for specific brushing techniques and dental products, and links to make dentist appointments if necessary. For example, a message might read, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[1079] For example, a user takes a picture of their teeth with their smartphone and uploads it to an application. The image is then denoised and its resolution adjusted on the device. This pre-processed image is then sent to a server where it is analyzed using an AI model. A text result, such as "suspected cavity in upper right molar," is generated and returned to the device. The user can review the result in the application, which then recommends a specific toothbrush or toothpaste as a solution.

[1080] Example prompts to input to a generative AI model:

[1081] "Analyze images of your teeth taken with your smartphone to assess your risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear."

[1082] In this way, users can efficiently manage their dental health from the comfort of their own home, and maintain dental health through early detection and prevention.

[1083] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1084] Step 1:

[1085] The user takes an image of the teeth

[1086] Input: A user uses a smartphone or digital camera.

[1087] How it works: The user launches the app and follows the instructions to take a picture of their teeth, adjusting the lighting to get a clear view of the inside of their mouth.

[1088] Output: The captured tooth images are saved on your smartphone.

[1089] Step 2:

[1090] The device preprocesses the image

[1091] Input: User-taken tooth images.

[1092] Operation: The device receives the captured image and uses OpenCV to remove noise (e.g., cv2.fastNlMeansDenoisingColored), adjust the resolution (e.g., cv2.resize), and extract the tooth region.

[1093] Output: Pre-processed, sharp image data is generated.

[1094] Step 3:

[1095] The device sends the preprocessed image data to the server.

[1096] Input: Preprocessed image data.

[1097] How it works: The device sends preprocessed image data to a server over the internet, using encryption protocols such as SSL / TLS.

[1098] Output: The server receives the preprocessed image data.

[1099] Step 4:

[1100] The server analyzes the image data

[1101] Input: Preprocessed image data.

[1102] How it works: The server analyzes the received image data and runs AI models built using deep learning libraries such as TensorFlow and PyTorch. The models assess the risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear.

[1103] Output: An analysis result is generated that assesses dental health risks.

[1104] Step 5:

[1105] The server generates the analysis results

[1106] Input: The results analyzed using the AI ​​model.

[1107] How it works: The server generates a textual analysis result, which includes a detailed assessment and highlights specific risks, such as a diagnosis like "You have suspected cavities in your upper right molar."

[1108] Output: Analysis results in text format are generated.

[1109] Step 6:

[1110] The server sends the analysis results to the device.

[1111] Input: Analysis results in text format.

[1112] How it works: The server generates and sends the analysis results to the device, again using encryption protocols such as SSL / TLS to protect the privacy of the data.

[1113] Output: The device receives the analysis results.

[1114] Step 7:

[1115] The device displays the analysis results to the user.

[1116] Input: Analysis results in text format.

[1117] How it works: The device visually displays the analysis results it receives, including highlighting problem areas, designed to be intuitive for the user.

[1118] Output: The analysis results are displayed visually to the user.

[1119] Step 8:

[1120] The device notifies the user of countermeasures and suggestions

[1121] Input: Specific countermeasures and proposals based on the analysis results.

[1122] What it does: The device uses the analysis to notify the user of potential solutions and suggestions, including recommendations for specific brushing techniques and dental products, as well as links to schedule dentist appointments. For example, it might say, "You suspect you have a cavity in your upper right molar. Use specific toothpaste products to prevent this. Click the link for more information."

[1123] Output: The user is notified of specific countermeasures and suggestions.

[1124] The above are the specific processing steps of the program of this system and their detailed operations.

[1125] (Application example 1)

[1126] 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."

[1127] In conventional dental diagnostic systems, the process in which users acquire and transmit images and AI performs analysis often raises security concerns. Furthermore, there were cases in which data security was not ensured even when the analysis results were visually displayed to the user. This posed a challenge, increasing the risk of unauthorized access to users' dental data by third parties. Another problem was the lack of encryption for analysis results and security breach detection capabilities.

[1128] 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.

[1129] In the present invention, the server includes a data encryption means and a security intrusion detection means, which allows data security and privacy to be enhanced in the process of transferring and displaying the analysis results.

[1130] An "image capture device" is a device that a user uses to capture an image of their teeth, and includes a smartphone, digital camera, etc.

[1131] "Preprocessing" refers to image processing operations such as noise removal, resolution adjustment, and tooth region extraction that are performed on the captured image.

[1132] "Server" means a computer system for receiving pre-processed image data, performing analysis using an artificial intelligence model, and generating analysis results.

[1133] An "artificial intelligence model" is a model trained based on machine learning and deep learning algorithms and used to analyze dental images and assess risks.

[1134] "Analysis Results" means a textual representation of dental health information analyzed using an artificial intelligence model.

[1135] "Data encryption means" refers to a method or device for encrypting images and analysis results, ensuring the security of information during data transfer and storage.

[1136] "Security intrusion detection means" refers to methods and devices for detecting unauthorized access to or tampering with data, and is necessary to maintain the security of the entire system.

[1137] "Visual display" refers to displaying the analysis results in a format that can be intuitively understood by the user, and includes a function to highlight problem areas.

[1138] To implement this invention, a user must first take an image of their teeth using an image capture device. A smartphone or digital camera is suitable as the image capture device. The user then launches a dedicated application and follows the application's instructions to take an image of their teeth.

[1139] Next, the device (such as a smartphone) receives the captured image and performs preprocessing. This preprocessing includes using image processing libraries such as OpenCV to remove noise, adjust resolution, and extract tooth regions. For example, removing noise from the image and adjusting it to a certain resolution results in an image that is easier for the AI ​​model to analyze.

[1140] After preprocessing is complete, the device sends the preprocessed image data to a server, which then analyzes it using an artificial intelligence (AI) model. The AI ​​model, trained using a framework such as TensorFlow, evaluates the image for cavities, periodontal disease, missed spots, dirt, stains, and wear.

[1141] The server generates the analysis results in text format and encrypts them using a cryptography library to ensure the privacy and security of the user's data. The encrypted analysis results are then sent back to the device from the server.

[1142] The device receives the analysis results and visually displays them to the user, highlighting problem areas for intuitive understanding. It also provides specific solutions and suggestions based on the analysis results, such as recommending specific toothpaste products and displaying links to schedule appointments with a dentist, if necessary.

[1143] Additionally, the system incorporates a security breach detection function that uses the requests library to obtain security information from external services and detect unauthorized access, further enhancing the safety of analysis results and user data.

[1144] For example, use the following prompt:

[1145] "Analyze the image below and assess the health of your teeth."

[1146] This invention allows users to easily check their dental health at home and take appropriate measures.In addition, data security and privacy are fully ensured, making it a system that can be used with peace of mind.

[1147] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1148] Step 1:

[1149] A user takes an image of the teeth using an image capture device.

[1150] Input: A smartphone or digital camera to photograph the user's teeth

[1151] How it works: The user launches the dedicated application and follows the on-screen instructions to take pictures of their teeth from the desired angles.

[1152] Output: Image data of photographed teeth

[1153] Step 2:

[1154] The device (e.g., a smartphone) preprocesses the tooth images taken.

[1155] Input: Image data of photographed teeth

[1156] How it works: The image is denoised, the resolution is adjusted, and the tooth regions are extracted using OpenCV.

[1157] Output: Preprocessed image data

[1158] Step 3:

[1159] The terminal transmits the preprocessed image data to the server.

[1160] Input: Preprocessed image data

[1161] What it does: The device sends image data to a server via an internet connection.

[1162] Output: Preprocessed image data sent to the server

[1163] Step 4:

[1164] The server receives the pre-processed image data and analyzes it using an artificial intelligence model.

[1165] Input: Preprocessed image data sent from the terminal

[1166] How it works: The server uses an AI model trained with TensorFlow to analyze image data and assess the risk of cavities, periodontal disease, etc.

[1167] Output: Analysis result data

[1168] Step 5:

[1169] The server generates the analysis results in text format and encrypts the data.

[1170] Input: Analysis result data

[1171] How it works: The server uses a cryptography library to convert the parsed results into text and then encrypts the text.

[1172] Output: Encrypted analysis result text data

[1173] Step 6:

[1174] The server sends the encrypted analysis results to the terminal.

[1175] Input: Encrypted analysis result text data

[1176] What it does: Sends encrypted data over the internet to your device

[1177] Output: Encrypted analysis result text data sent to the terminal

[1178] Step 7:

[1179] The terminal decrypts the encrypted analysis results and visually displays them to the user.

[1180] Input: Encrypted analysis result text data sent from the server

[1181] How it works: The device decrypts the data using a cryptography library, highlights problem areas, and presents the analysis results to the user in an intuitive manner.

[1182] Output: Analysis results visually displayed to the user

[1183] Step 8:

[1184] The device will provide specific countermeasures and suggestions based on the analysis results.

[1185] Input: Decrypted analysis result text data

[1186] What it does: Based on the analysis, it recommends specific brushing techniques and dental products, and provides a link to book a dentist appointment if needed.

[1187] Output: Specific countermeasures and proposal information provided

[1188] Step 9:

[1189] A security breach detection function is in operation to monitor the security status of the entire system.

[1190] Input: Data handled throughout the system and system operation information

[1191] Operation: Uses the requests library to obtain security information from external services and detect unauthorized access.

[1192] Output: Alerts or log information about the security status

[1193] 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.

[1194] This invention relates to a system that allows users to easily check their dental health at home and take appropriate measures. In addition to conventional image analysis, this invention combines an emotion engine that recognizes and analyzes the user's emotional state to provide more effective feedback.

[1195] First, the user takes a picture of their teeth using an image capture device such as a smartphone or digital camera. The user then launches the application and follows the on-screen instructions to capture the tooth image. At this time, the emotion engine is also activated, analyzing the user's facial expressions and recognizing their emotional state.

[1196] Next, the device (such as a smartphone) receives the captured tooth image and the user's emotional state data. The tooth image is stored in local storage, as is the emotional data obtained by the emotion engine.

[1197] The device performs pre-processing on the stored tooth images, including noise reduction, resolution adjustment, and tooth region extraction, to obtain the clearest and most appropriate images, and prepares the emotion data to be sent to the server.

[1198] After preprocessing is complete, the device sends the preprocessed image data and emotion data to a server. The server receives the data and analyzes it using an artificial intelligence model (AI model). Specifically, the AI ​​model evaluates the risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear. The analysis results include a detailed assessment of the condition of the teeth and highlights specific risks.

[1199] Once the server completes the analysis, it generates the analysis results in text format. The system then adjusts the feedback based on the user's emotional state. For example, if the user is feeling anxious, the system may include an encouraging message.

[1200] The generated analysis results and emotion-based feedback are sent from the server to the device. The device receives these results and visually displays them to the user. The display format is designed to be intuitive and easy for the user to understand. For example, it includes a function to highlight problem areas.

[1201] The device also offers specific strategies and suggestions based on the analysis and emotional state, including specific brushing techniques, recommendations for appropriate dental products, and even links to make dentist appointments if needed. For example, a notification might say, "You suspect you have a cavity in your upper right molar. Don't worry. Use specific dental products to prevent it. Click the link for more information."

[1202] In this way, users can feel more secure in managing their dental health by receiving feedback based on their emotional state. The combination of the emotion engine improves the user experience and increases motivation to maintain dental health.

[1203] The processing flow will be explained below.

[1204] Step 1:

[1205] The user launches the application and takes an image of their teeth using an image capture device (such as a smartphone or digital camera). At this time, the application captures the user's facial expressions in real time and recognizes the user's emotional state using an emotion engine.

[1206] Step 2:

[1207] The device receives the captured tooth images and the user's emotion data, which are then stored in local storage. The captured emotion data includes emotions inferred from the user's facial expressions (e.g., anxiety, relief, doubt, etc.).

[1208] Step 3:

[1209] The device removes noise from the tooth images stored in the device. Specific methods for noise removal include Gaussian filters and median filters.

[1210] Step 4:

[1211] The device extracts the tooth region from the image and uses segmentation techniques to separate the tooth from the background and extract only the tooth portion. Specifically, it uses an edge detection algorithm and a region growing algorithm.

[1212] Step 5:

[1213] The device adjusts the image resolution, scaling the image to the appropriate resolution for optimal analysis by the AI ​​model. Specifically, resolution conversion techniques such as bicubic interpolation are used.

[1214] Step 6:

[1215] The terminal transmits the preprocessed image data and emotion data to the server.

[1216] Step 7:

[1217] The server receives the preprocessed image data and emotion data.

[1218] Step 8:

[1219] The server inputs the received image data into an AI model, which is trained using machine learning and deep learning techniques to analyze the dental health status. Specifically, deep learning algorithms such as convolutional neural networks (CNNs) are used.

[1220] Step 9:

[1221] The server uses AI models to analyze the risk of cavities, periodontal disease, missed spots, stains, discoloration, wear, etc. For example, the AI ​​model analyzes specific pixel patterns in the image to identify areas that may be prone to cavities.

[1222] Step 10:

[1223] The server generates the analysis results in text format, such as a specific diagnosis such as "You may have a cavity in your upper right molar."

[1224] Step 11:

[1225] The server tailors the feedback based on the user's emotional state, for example, including encouraging messages if the user is feeling anxious.

[1226] Step 12:

[1227] The server sends the generated analysis results and feedback based on the emotions to the device.

[1228] Step 13:

[1229] The terminal visually displays the analysis results and feedback received from the server to the user. For example, the display format may highlight risky areas to visually draw attention.

[1230] Step 14:

[1231] The device will then provide specific solutions and suggestions based on the analysis and emotional state. This could include recommendations for specific brushing techniques or dental products, or even a link to make a dentist appointment. For example, a notification might say, "You suspect you have a cavity in your upper right molar. Don't worry. Use specific toothpaste products to prevent this. Click the link for more information."

[1232] Example 2

[1233] 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."

[1234] Current dental health monitoring systems often leave users feeling anxious because they do not provide feedback that takes into account the user's emotional state. Furthermore, conventional systems do not comprehensively pre-process images or recognize emotional states, so analysis results may not be accurate enough.

[1235] 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.

[1236] In this invention, the server includes means for receiving the preprocessed image and emotional state data, analyzing the data using a generative AI model, and generating analysis results in text format, means for generating feedback based on the generated analysis results and the user's emotional state, and means for transmitting the analysis results and feedback generated by the server to the image capture device, thereby enabling the provision of accurate analysis results and feedback that take the user's emotional state into consideration.

[1237] An "image capture device" is a device that a user uses to take an image of their teeth, including, for example, a smartphone or digital camera.

[1238] "Preprocessing" refers to the process of preparing the acquired image for analysis by removing noise, adjusting resolution, extracting tooth regions, etc.

[1239] "Emotional state" is data indicating the psychological state recognized from the user's facial expression, and includes emotions such as anxiety, relief, and surprise.

[1240] "Server" refers to a central processing unit for receiving pre-processed image data and emotion data for analysis and feedback generation.

[1241] A "generative AI model" is an artificial intelligence model used to analyze image data and emotional data, including models that use deep learning.

[1242] "Analysis results" refers to the assessment and diagnostic information regarding dental health obtained by the generative AI model.

[1243] "Feedback" refers to messages and advice generated based on the analysis results and emotional state, and includes specific countermeasures and suggestions for the user.

[1244] "Specific countermeasures and suggestions" refers to instructions that show users specific actions to take or products to use based on the analysis results, as well as links to make dentist appointments if necessary.

[1245] This invention relates to a system that allows users to easily check their dental health at home and take appropriate measures. The invention is implemented using an image acquisition device, a terminal, a server, and a generative AI model. The specific configuration and operation are described below.

[1246] First, the user takes an image of their teeth using an image capture device such as a smartphone or digital camera. For example, the user launches a camera app on their smartphone and takes a photo of their teeth following the instruction to "hold the smartphone close to your mouth and show your teeth." This allows the image capture device to capture an image of the user's teeth.

[1247] The device then receives the captured image and uses an emotion engine to analyze the user's emotional state. The emotion engine analyzes the user's facial expressions in real time and recognizes emotions such as anxiety, relief, and surprise. After the emotional state is recognized, the device stores the captured tooth image and emotion data.

[1248] The device then performs preprocessing on the saved tooth images, such as noise reduction, resolution adjustment, and tooth region extraction. Once preprocessing is complete, the preprocessed image data and emotion data are sent to the server. For security reasons, the HTTPS protocol is used for data transmission.

[1249] The server receives the preprocessed image data and emotion data and analyzes the data using a generative AI model. Specifically, the AI ​​model (e.g., TensorFlow or PyTorch) evaluates the risk of cavities, periodontal disease, and incomplete brushing. As a result of the risk assessment, detailed analysis information about the condition of the teeth is generated.

[1250] The server then generates feedback based on the analysis and the user's emotional state. For example, if the user is feeling anxious, it generates a gentle message such as, "Your teeth are generally healthy, but there are some areas that need cleaning. Don't worry. We'll try to take a little more time next time."

[1251] The generated analysis results and feedback are sent from the server to the device. The device visually displays the received analysis results and feedback to the user. Specifically, it has a function to highlight problem areas and visually explain them using animations. In addition, it provides the user with specific countermeasures and suggestions based on the analysis results. For example, a notification may be displayed saying, "You may have a cavity in your upper right molar. Use a specific toothpaste gel to prevent this. Click here for details."

[1252] This allows users to easily check their dental health at home and take appropriate measures while receiving feedback that takes into account their emotional state. Below are examples of prompts for the generative AI model.

[1253] Example prompt sentence:

[1254] "Analyze this image to assess the risk of cavities and periodontal disease. Generate feedback with detailed results."

[1255] "Because the user's emotional state is anxious, provide gentle feedback. For example, include a message like, 'Don't worry. Let's take a little more time next time.'"

[1256] The above is a specific embodiment for carrying out the present invention. The present invention enables users to manage their dental health with peace of mind and to take appropriate measures.

[1257] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1258] System processing flow and specific explanation

[1259] Step 1:

[1260] The user takes an image of their teeth using a smartphone or digital camera.

[1261] Input: The user holds an image capture device (such as a smartphone or digital camera) and takes an image of the teeth.

[1262] Specific operation: The user launches the smartphone camera app and takes a photo of their teeth by following the instructions to "hold the smartphone close to your mouth and show your teeth." A "Take a photo" button appears on the screen, and the user presses it to capture the image.

[1263] Output: Image data of the photographed teeth.

[1264] Step 2:

[1265] The device analyzes the captured images of the teeth and the user's facial expressions to recognize their emotional state and store that data.

[1266] Input: Dental image data and user facial expression data.

[1267] Specific operation: The emotion engine analyzes the user's facial expressions in real time and recognizes emotions such as anxiety, relief, surprise, etc. In parallel, it acquires dental image data.

[1268] Output: The tooth image data and the recognized emotion data are saved in local storage.

[1269] Step 3:

[1270] The device performs preprocessing on the stored tooth images, such as noise removal, resolution adjustment, and tooth region extraction.

[1271] Input: Stored tooth image data.

[1272] Specific operation: Using OpenCV library, apply noise reduction filter to improve image quality, unify resolution and apply tooth region extraction algorithm to identify teeth.

[1273] Output: Preprocessed tooth image data.

[1274] Step 4:

[1275] The terminal transmits the preprocessed image data and emotion data to the server.

[1276] Input: Preprocessed dental image data and emotion data.

[1277] What it does: Securely uploads data to the server using the HTTPS protocol. Sends a POST request to an API endpoint to transfer the data.

[1278] Output: Preprocessed image data and emotion data sent to the server.

[1279] Step 5:

[1280] The server receives the preprocessed image data and emotion data, analyzes them using a generative AI model, and generates the analysis results in text format.

[1281] Input: Preprocessed dental image data and emotion data.

[1282] Specific operation: The server runs a generative AI model using TensorFlow and PyTorch to assess the risk of cavities, periodontal disease, and missed brushing spots. The results of the AI ​​model are formatted in text format.

[1283] Output: Text data of the analysis results.

[1284] Step 6:

[1285] The server generates feedback based on the analysis results and the user's emotional state.

[1286] Input: Text data and sentiment data from the analysis results.

[1287] Specific behavior: Based on the analysis results, a feedback message is generated that takes into account the user's emotional state. For example, for a user who is feeling anxious, a gentle message is created saying, "Your teeth are generally healthy, but there are some areas that need brushing. Don't worry. We'll try to take a little more time next time."

[1288] Output: The generated feedback message.

[1289] Step 7:

[1290] The server sends the generated analysis results and feedback to the terminal.

[1291] Input: Text data of generated feedback messages and analysis results.

[1292] Specific operation: The generated data is uploaded to the terminal via the HTTPS protocol, and a POST request is sent to the API endpoint to transfer the data.

[1293] Output: Analysis results and feedback messages sent to the terminal.

[1294] Step 8:

[1295] The analysis results and feedback received by the device are visually displayed to the user, and specific countermeasures and suggestions are provided.

[1296] Input: Received analysis result data and feedback messages.

[1297] Specific operation: A UI (user interface) is constructed to visually display the analysis results in an easy-to-understand manner. Problem areas are highlighted and explained using animation. Furthermore, specific countermeasures and suggestions are displayed as necessary, such as a notification that reads, "You may have cavities in your upper right molar. Use a specific toothpaste gel to prevent this. Click here for details."

[1298] Output: Visual display and suggested actions to the user.

[1299] This series of processes allows users to easily check the health of their teeth at home and receive appropriate feedback, allowing them to take care of their teeth with peace of mind.

[1300] (Application example 2)

[1301] 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."

[1302] Conventional dental image analysis systems have the problem that they do not provide feedback that takes into account the user's emotional state, making it difficult to completely alleviate the user's anxiety. In particular, there is a demand for systems that allow customers to manage their health on the spot with peace of mind in brick-and-mortar stores such as dental clinics and beauty salons.

[1303] 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: means for a user to capture an image of their teeth using an image capture device; means for the image capture device to preprocess the captured tooth image and the user's facial expression data and transmit the preprocessed image and facial expression data to the server; means for the server to receive the preprocessed image and facial expression data, analyze them using an artificial intelligence model, and generate analysis results in text format; means for transmitting the analysis results generated by the server to the image capture device; and means for visually displaying the analysis results received by the image capture device to the user and providing specific countermeasures and suggestions based on the analysis results and the user's emotional state. This provides feedback that takes into account the user's emotional state, allowing customers to have their teeth checked at a physical store with peace of mind.

[1304] Understood. Below are definitions of important words.

[1305] A "user" is a person who uses an image capture device to check the health of their teeth.

[1306] An "image acquisition device" is a device that captures dental images and facial expression data, such as a smartphone, digital camera, smart glasses, or head-mounted display.

[1307] "Preprocessing" refers to performing processes such as noise removal, resolution adjustment, and tooth area extraction on captured images and data to make them suitable for analysis.

[1308] "Server" refers to a central computing device that receives pre-processed images and data and performs analysis using artificial intelligence models.

[1309] An "artificial intelligence model" is a computational program that uses machine learning algorithms to analyze images of teeth and evaluate cavities, periodontal disease, areas that have not been brushed properly, dirt, discoloration, wear, etc.

[1310] "Analysis Results" means the dental health assessment generated by the AI ​​model, provided in text format.

[1311] "Facial expression data" is data that indicates the emotional state of the user, and is information obtained from the user's facial expression using image recognition technology.

[1312] "Feedback" refers to information and suggested actions provided based on the analysis results and the user's emotional state. Step 1:

[1313] The user puts on smart glasses or a head-mounted display installed in a physical store and launches the application. At this time, the image capture device takes an image of the user's teeth, and the emotion engine analyzes the user's facial expressions to obtain emotion data.

[1314] Input: Images of the user's teeth, facial expression data

[1315] Output: Raw image data and raw emotion data for preprocessing

[1316] Step 2:

[1317] The device preprocesses the captured tooth images and emotion data, which includes noise removal, resolution adjustment, and tooth region extraction.

[1318] Input: Raw image data, raw emotion data

[1319] Output: Preprocessed image data, preprocessed emotion data

[1320] Step 3:

[1321] The device sends the preprocessed image data and emotion data to the cloud server, which receives the data.

[1322] Input: Preprocessed image data, preprocessed emotion data

[1323] Output: Image data and emotion data stored on a cloud server

[1324] Step 4:

[1325] The server analyzes the received data using an artificial intelligence model to assess dental health (cavities, periodontal disease, missed spots, stains, discoloration, wear, etc.) and adjusts the feedback based on emotional data.

[1326] Input: Image data and emotion data stored on a cloud server

[1327] Output: Detailed analysis results and feedback on dental health status

[1328] Step 5:

[1329] The server generates analysis results and sends feedback based on emotions to the device, which receives these results and visually displays them to the user.

[1330] Input: Analysis results, feedback content

[1331] Output: Analysis results and feedback displayed on your device

[1332] Step 6:

[1333] The device visually displays the analysis, highlights problem areas for the user, and provides specific solutions and suggestions based on the analysis and emotional state, such as specific brushing techniques, recommendations for appropriate dental products, and links to book dentist appointments if needed.

[1334] Input: Analysis results and feedback displayed on the device

[1335] Output: Visual analysis results, actionable recommendations, and a link to book an appointment with the dentist.

[1336] 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.

[1337] 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.

[1338] 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.

[1339] 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.

[1340] 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.

[1341] 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.

[1342] 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).

[1343] 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.

[1344] 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."

[1345] 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.

[1346] 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).

[1347] 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.

[1348] 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.

[1349] 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.

[1350] 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.

[1351] 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.

[1352] 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.

[1353] 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.

[1354] 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.

[1355] 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.

[1356] 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.

[1357] The following is further disclosed regarding the above embodiment.

[1358] (Claim 1)

[1359] means for a user to take an image of the teeth using an image capture device;

[1360] means for pre-processing the tooth images captured by the image capture device and transmitting the pre-processed images to a server;

[1361] a server receiving the preprocessed image, analyzing it using an artificial intelligence model, and generating an analysis result in text format;

[1362] means for transmitting the analysis results generated by the server to the image acquisition device;

[1363] A means for visually displaying the analysis results received by the image acquisition device to a user and providing specific countermeasures and suggestions;

[1364] …

[1365] A system including:

[1366] (Claim 2)

[1367] The system of claim 1, wherein the artificial intelligence model analyzes at least one of caries, periodontal disease, missed brushing areas, dirt, stains, and wear based on the preprocessed image.

[1368] (Claim 3)

[1369] 10. The system of claim 1, wherein the system provides the user with specific tooth brushing recommendations and dental products based on the generated analysis results, and optionally displays a link to make a dentist appointment.

[1370] "Example 1"

[1371] (Claim 1)

[1372] means for a user to take an image of the teeth using an image capture device;

[1373] A means for pre-processing the tooth images captured by the image capture device to remove noise, adjust resolution, and extract tooth regions;

[1374] means for transmitting the preprocessed image to a server;

[1375] The server receives the preprocessed images, analyzes them using a deep learning model to assess the risk of cavities, periodontal disease, missed spots, stains, discoloration, and wear, and generates the analysis results in text format.

[1376] means for transmitting the analysis results generated by the server to the image acquisition device;

[1377] a means for visually displaying the analysis results received by the image acquisition device to a user and providing specific countermeasures and proposals based on the analysis results;

[1378] A means of displaying notices containing recommendations for specific tooth brushing techniques or dental product use;

[1379] A means to provide a dentist appointment link if needed;

[1380] A system including:

[1381] (Claim 2)

[1382] The system of claim 1, wherein the deep learning model analyzes at least one of cavities, periodontal disease, missed brushing areas, dirt, stains, and wear based on the preprocessed image.

[1383] (Claim 3)

[1384] 10. The system of claim 1, wherein the system provides the user with specific tooth brushing recommendations and dental products based on the generated analysis results, and optionally displays a link to make a dentist appointment.

[1385] "Application Example 1"

[1386] (Claim 1)

[1387] means for a user to take an image of the teeth using an image capture device;

[1388] means for pre-processing the tooth images captured by the image capture device and transmitting the pre-processed images to a server;

[1389] a server receiving the preprocessed image, analyzing it using an artificial intelligence model, and generating an analysis result in text format;

[1390] means for transmitting the analysis results generated by the server to the image acquisition device;

[1391] A means for visually displaying the analysis results received by the image acquisition device to a user and providing specific countermeasures and suggestions;

[1392] data encryption means;

[1393] a security breach detection means;

[1394] A system including:

[1395] (Claim 2)

[1396] The system of claim 1, wherein the artificial intelligence model analyzes at least one of caries, periodontal disease, missed brushing areas, dirt, stains, and wear based on the preprocessed image.

[1397] (Claim 3)

[1398] 10. The system of claim 1, wherein the system provides the user with specific tooth brushing recommendations and dental products based on the generated analysis results, provides a link to make a dentist appointment if necessary, and encrypts the analysis results.

[1399] "Example 2: Combining Emotion Engines"

[1400] (Claim 1)

[1401] means for a user to take an image of the teeth using an image capture device;

[1402] means for recognizing and preprocessing the tooth images captured by the image capture device and the emotional state of the user;

[1403] means for transmitting the preprocessed image and emotional state data to a server;

[1404] A server receives the preprocessed image and emotional state data, analyzes the data using a generative AI model, and generates the analysis results in text format;

[1405] means for generating feedback based on the generated analysis results and the user's emotional state;

[1406] means for transmitting the analysis results and feedback generated by the server to the image capture device;

[1407] a means for visually displaying the analysis results and feedback received by the image acquisition device to a user and providing specific countermeasures and suggestions;

[1408] …

[1409] A system including:

[1410] (Claim 2)

[1411] The system of claim 1, wherein the generative AI model analyzes at least one of cavities, periodontal disease, missed brushing spots, dirt, stains, and wear based on the preprocessed image and emotional state data.

[1412] (Claim 3)

[1413] 10. The system of claim 1, wherein the system provides the user with specific tooth brushing recommendations and dental products based on the generated analysis and emotional state, and optionally displays a link to make a dentist appointment.

[1414] "Application example 2 when combining emotion engines"

[1415] Understood. Below are the claims rewritten to reflect the new invention.

[1416] (Claim 1)

[1417] means for a user to take an image of the teeth using an image capture device;

[1418] means for preprocessing the tooth images and facial expression data of the user captured by the image capture device and transmitting the preprocessed images and facial expression data to a server;

[1419] a server receiving the preprocessed image and facial expression data, analyzing the image and facial expression data using an artificial intelligence model, and generating an analysis result in a text format;

[1420] means for transmitting the analysis results generated by the server to the image acquisition device;

[1421] a means for visually displaying the analysis results received by the image capture device to the user and providing specific countermeasures and suggestions based on the analysis results and the user's emotional state;

[1422] …

[1423] A system including:

[1424] (Claim 2)

[1425] The system of claim 1, wherein the artificial intelligence model analyzes at least one of cavities, periodontal disease, missed spots, dirt, stains, and wear based on the preprocessed images, and adjusts the feedback content based on the user's facial expression data.

[1426] (Claim 3)

[1427] The system of claim 1, wherein, based on the generated analysis results, the system suggests specific tooth brushing methods and dental products to the user, displays links to make dentist appointments as needed, and provides messages that take into account the user's emotional state. [Explanation of symbols]

[1428] 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. means for a user to take an image of the teeth using an image capture device; means for pre-processing the tooth images captured by the image capture device and transmitting the pre-processed images to a server; a server receiving the preprocessed image, analyzing it using an artificial intelligence model, and generating an analysis result in text format; means for transmitting the analysis results generated by the server to the image acquisition device; A means for visually displaying the analysis results received by the image acquisition device to a user and providing specific countermeasures and suggestions; A system including:

2. The system of claim 1 , wherein the artificial intelligence model analyzes at least one of caries, periodontal disease, missed brushing areas, stains, discoloration, and wear based on the pre-processed image.

3. The system of claim 1 , wherein the system provides the user with specific tooth brushing recommendations and dental products based on the generated analysis results, and optionally displays a link to make a dentist appointment.

Images