system

Abstract

We provide the system. [Solution] A means for receiving image data and attribute information from a user, A means for analyzing received image data to generate digital data of skin condition, Based on the generated digital data of skin condition, a means of recommending individual beauty products and beauty methods, A means of providing users with information about beauty products and beauty methods, A means for performing a makeup simulation based on the user's facial data, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, there has been an increasing interest in beauty and health, and customized beauty care tailored to individual needs is demanded. However, conventional beauty advice is uniform and has the problem of being difficult to reflect real-time results. In addition, there is a lack of means for users to easily obtain a high-quality beauty experience at home. As a result, users are in a situation where they have to rely on inefficient beauty methods.

Means for Solving the Problems

[0005] This invention provides a system that receives user image data and attribute information, analyzes it, and generates individualized skin condition data. Based on the analyzed data, it recommends beauty products and methods tailored to each user and provides that information to the user. Furthermore, this system enables makeup simulation using the user's facial data and the generation of meal plans based on lifestyle habits, thereby providing a personalized and advanced beauty experience. As a result, users can efficiently manage their beauty and health with a customized approach from the comfort of their own homes.

[0006] "Image data" refers to photographic data provided by the user, including visual information used for analysis.

[0007] "Attribute information" refers to personal information such as a user's age, gender, and lifestyle, and is supplementary data used for analysis and recommendations.

[0008] "Digital data on skin condition" refers to information that quantifies skin characteristics and health status, obtained as a result of image data analysis.

[0009] "Beauty products" refer to cosmetics and skincare products used to improve the user's skin condition or for cosmetic purposes.

[0010] "Beauty methods" refer to specific practical techniques and procedures for maintaining healthy and beautiful skin.

[0011] "Makeup simulation" refers to a technology that uses a user's facial data to virtually display what they would look like with makeup applied in real time.

[0012] A "meal plan" refers to a customized meal plan suggested based on the user's lifestyle and health condition. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] The system according to the present invention includes multiple components for analyzing the user's skin condition and recommending customized beauty products and treatments. In implementing the system, the user first inputs their image data and attribute information using a terminal. This input information is transmitted by the terminal to the server via a secure communication path.

[0035] The server passes the received image data to an AI engine utilizing computer vision technology to analyze the skin condition. The digital data obtained from the analysis quantifies the user's skin characteristics, and this is used to select beauty products and treatments. For example, if the system determines that the user has dry skin, highly moisturizing skincare products will be recommended.

[0036] The device displays recommendations received from the server to the user, allowing the user to make selections that suit their preferences. Users can also utilize a makeup simulation function, applying various makeup styles to their own face via the device's camera for preview.

[0037] Furthermore, the server creates a meal plan that takes into account the user's lifestyle information and provides it to the terminal. This meal plan is customized to help users maintain their health and achieve a desirable physique, addressing their specific needs.

[0038] This system, through the functions described above, enables users to efficiently and effectively manage their beauty and health at home. Users can improve their daily beauty care and lifestyle by receiving personalized advice from the system.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] Users take or upload a photo of their face using their device and enter personal information such as age, gender, and lifestyle. Once they have finished entering the information, they proceed to submit the data.

[0042] Step 2:

[0043] The device collects image data and attribute information provided by the user and sends it to the server via secure communication. Data transfer is encrypted to protect user privacy.

[0044] Step 3:

[0045] The server passes the transmitted image data to the AI ​​engine, which analyzes the skin condition. The AI ​​engine uses machine learning algorithms to analyze the skin's characteristics and generates digital data such as wrinkles, blemishes, and skin tone.

[0046] Step 4:

[0047] The server uses the generated digital data on the user's skin condition to refer to its built-in database and select recommended beauty products and treatments. For example, if the user has dry skin, products with high moisturizing effects will be selected.

[0048] Step 5:

[0049] The server sends the selected beauty products and advice to the terminal. It also analyzes the user's lifestyle information and generates a healthy meal plan.

[0050] Step 6:

[0051] The device displays beauty product recommendations and meal plans received from the server to the user. This allows the user to review the suggestions and incorporate them into their routine as needed.

[0052] Step 7:

[0053] Users can operate the makeup simulation function and try on virtual makeup on their own face in real time using their device's camera. They can then perform actions to see how the selected makeup style will actually look.

[0054] Step 8:

[0055] The server stores user data and supports updates for future use and new recommendations. It can also offer hairstyle and fashion suggestions as needed.

[0056] (Example 1)

[0057] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0058] The goal is to efficiently provide beauty products, methods, and lifestyle-based plans tailored to each user's individual needs, supporting optimal beauty and health management for each individual. Furthermore, a challenge lies in real-time application of virtual styles to provide a more personalized experience.

[0059] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0060] In this invention, the server includes means for acquiring various types of data and characteristic information, means for analyzing the acquired various types of data to generate digital information of the surface state, and means for recommending personalized products and methods based on the generated digital information of the surface state. This makes it possible to efficiently support beauty and health management that is tailored to the user's needs.

[0061] "Multi-type data" refers to the collective term for various types of information necessary for the system to analyze users, such as image data and attribute information collected from users.

[0062] "Characteristic information" refers to detailed information related to individual needs, such as the user's age, gender, and lifestyle.

[0063] "Digital information on surface condition" refers to information where the analyzed skin condition is quantified and represented digitally.

[0064] "Products and methods" refers to beauty products, beauty treatments, and related lifestyle suggestions recommended based on the individual needs of the user.

[0065] A "generative AI model" refers to an artificial intelligence framework used to generate appropriate products and plans based on user information.

[0066] A "prompt statement" is an instruction given to a generative AI model and is an important element for identifying the content that will be generated.

[0067] The system according to the present invention has comprehensive functions for recommending beauty products and methods according to the individual needs of users. This system is implemented through the cooperation of a terminal and a server.

[0068] First, the user uses their device to input their own image data and characteristic information such as age and lifestyle. This data is transmitted from the device to the server via secure communication. On the device, data input and initial processing are performed, and necessary image data is also collected using the camera function.

[0069] The server analyzes the received image data based on an AI engine. This analysis utilizes computer vision technology and deep learning models. Specifically, it uses libraries and frameworks (e.g., TENSORFLOW®, OpenCV) to generate digital information that quantifies the skin condition from the image. Based on this information, the server uses a generative AI model to recommend the most suitable beauty products and methods. During the generation process, prompt statements are provided to the AI ​​model, and results tailored to the user's needs are generated.

[0070] For example, when the prompt "30 years old, female, dry skin, outdoor habit" is input into the AI ​​model, it generates highly moisturizing beauty products and a suitable meal plan.

[0071] Ultimately, the device displays information received from the server on the user's screen, allowing the user to review recommended products and methods. Furthermore, the device offers a makeup simulation function, enabling real-time virtual makeup application via the camera. This allows users to try out virtual styles and helps them explore the beauty methods best suited to them.

[0072] Thus, the system of the present invention provides users with efficient and effective support for personalized beauty and health management.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The user uses the device to input image data and characteristic information (age, gender, lifestyle, etc.). This input information is temporarily stored within the device, and format conversion and simple validation are performed to ensure data integrity. The input data consists of JPEG image files and JSON characteristic information files.

[0076] Step 2:

[0077] The terminal sends the stored image data and feature information to the server. A TLS-based encryption protocol is used for communication to ensure data security. The input data consists of image files and JSON files, which are formatted on the server for immediate processing and analysis.

[0078] Step 3:

[0079] The server passes the received image data to the AI ​​engine for analysis. The AI ​​engine utilizes a deep learning model (e.g., TensorFlow) to analyze the skin condition from the image and outputs the results as numerical digital data. This data includes attributes such as surface texture, pigmentation, and oil content.

[0080] Step 4:

[0081] The server uses a generative AI model to generate personalized beauty products and methods based on digital data and characteristic information of the user's skin condition. In this process, prompt statements (e.g., "30 years old, female, dry skin") are input into the AI ​​model, and the most suitable content for the user is output. This output includes a product list and recommended usage instructions.

[0082] Step 5:

[0083] The server sends information about the generated beauty products and methods to the device. The data is formatted in HTML or as an in-app GUI component for user readability, and is transmitted encrypted.

[0084] Step 6:

[0085] The device displays received beauty information to the user. The user can view the received information and consider available products and services. The device can also invoke a makeup simulation function and apply virtual makeup to the user's face, allowing them to see the results in real time. The virtual makeup is overlaid onto the video stream captured by the camera, and the results are displayed on the screen.

[0086] (Application Example 1)

[0087] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0088] In today's brick-and-mortar stores, providing customers with the most suitable beauty products and treatments based on their individual skin condition and lifestyle is a challenging task. Furthermore, customers often have limited means to verify the effectiveness of products before actually trying them in-store, leading to lengthy purchase decisions. To address these issues, technology that provides personalized information to customers in real time is necessary.

[0089] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0090] In this invention, the server includes means for receiving image data and attribute information from the user, means for analyzing the received image data to generate digital data on the skin condition, and means for utilizing a visual device to display the information in real time and make product recommendations. This allows customers to instantly receive an assessment of their skin condition and recommendations for appropriate beauty products within the store.

[0091] "Image data" refers to digitized visual information that shows the condition of a user's face and skin.

[0092] "Attribute information" refers to data that shows characteristics of the user, such as age, gender, and skin type.

[0093] "Digital data on skin condition" refers to information that analyzes and quantifies the characteristics of a user's skin.

[0094] "Beauty products and beauty treatments" refer to products and methods used to maintain and improve the health and beauty of the skin.

[0095] "Makeup simulation" is a technology that virtually applies makeup to a facial image and visually confirms its effect.

[0096] "Visual devices" are devices used to display information in real time, and include, for example, smart glasses and displays.

[0097] "In-store inventory" refers to the collection of products that are available for sale and are held in a physical store.

[0098] "Product recommendation" is the act of selecting and presenting appropriate products based on the user's characteristics.

[0099] The system that realizes this application example begins with the user using a visual device provided in the store, specifically smart glasses. The user puts on the smart glasses, and a terminal scans the user's face with a camera. The terminal sends image data and attribute information to a server via a secure communication channel. The server analyzes the image data using software called Python and OpenCV, and generates digital data of the user's skin condition from the received information. An AI model utilizing TensorFlow is used for this process.

[0100] Based on the generated digital data, the server selects the most suitable beauty products for the user from a database and displays the information in real time on the smart glasses' display. For example, if the analysis reveals that the user's skin is dry, products with high moisturizing effects will be recommended. A virtual makeup simulation is also provided so that users can try out the products on the spot and check their effects before purchasing them in a physical store.

[0101] In this way, users receive personalized product recommendations in real time and can instantly select products that meet their needs. Stores can also manage inventory dynamically, contributing to increased sales.

[0102] As a concrete example, a user who is doing their daily shopping and has the question, "My skin has been dry lately, but I don't know what to use," can use the smart glasses in the store to receive recommendations for moisturizing creams and lotions on the spot.

[0103] An example of a prompt sentence to input into the generating AI model would be, "Please recommend the latest moisturizing cream suitable for a female customer with slightly dry skin."

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] The user wears smart glasses, and the device scans the user's face with its camera. The input is an image of the user's face, and the output is the scanned image data. The device collects this image data and prepares to transmit it in the next step.

[0107] Step 2:

[0108] The terminal transmits collected image data and user attribute information to the server via a secure communication path. The input is image data and attribute information, and the output is data transfer to the server. In this step, the data is properly encrypted to prevent unauthorized viewing.

[0109] Step 3:

[0110] The server processes the received image data using Python and OpenCV to begin analyzing the user's skin condition. The input is image data, and the output is digital data of the skin condition. This data analysis uses an AI model powered by TensorFlow to quantify the skin's characteristics.

[0111] Step 4:

[0112] The server selects suitable beauty products from the database based on the generated digital skin condition data. The input is the digital skin condition data, and the output is a list of recommended beauty products. In this step, the products best suited to the user's skin needs are selected.

[0113] Step 5:

[0114] The server transmits information about selected beauty products to the smart glasses display in real time, presenting it to the user. The input is a list of beauty products, and the output is the information displayed through the visual device. The user can review the products here and request more detailed information if needed.

[0115] Step 6:

[0116] Based on the information presented, users can select and decide to purchase beauty products. In this step, the store's inventory management system is updated according to the user's selection. Makeup simulations are also available, allowing users to see a virtual effect before making a selection.

[0117] In this way, the system provides personalized services to the user through a series of processes.

[0118] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0119] This invention incorporates an emotion engine that recognizes the user's emotions into a system for suggesting individually customized beauty products and methods based on the user's facial image data and attribute information. The user first inputs their facial photograph and personal information using a terminal and sends it to the server via the terminal. The server receives this data, uses an AI engine to analyze the skin condition, and generates quantified skin condition data.

[0120] Based on the generated data, the server consults a database to recommend beauty products and methods tailored to the user. Specifically, for example, if the analysis reveals that the user's skin is particularly sensitive, hypoallergenic skincare products will be suggested. Furthermore, by incorporating an emotion engine into this process, it becomes possible to analyze the user's emotions from their photos and input data, and provide beauty advice that is further refined to suit the user's psychological state.

[0121] The emotion engine analyzes the user's facial expressions and voice tone through the device's camera and microphone to recognize emotions such as joy, sadness, and surprise. For example, if the emotion engine detects that the user is stressed, it can recommend relaxing products or refreshing beauty treatments. Furthermore, the makeup simulation running on the device can provide virtual makeup in colors and styles that match the user's emotional state.

[0122] Users can review these suggestions on their devices and purchase beauty products or implement beauty treatments according to their preferences. This allows users to receive personalized beauty care tailored to their emotional state from the comfort of their home. This system provides comprehensive beauty care that takes into account the user's physiological and emotional state.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] Users take or upload a photo of their face using their device and enter attribute information such as age, gender, and lifestyle. The entered data is sent from the device to the server.

[0126] Step 2:

[0127] The server retrieves image data and attribute information received from the terminal. The image data is passed to the AI ​​engine, where a detailed analysis of the skin condition is performed. The AI ​​engine quantifies skin wrinkles, blemishes, and tone, and generates this data digitally.

[0128] Step 3:

[0129] The server uses digital data on skin condition obtained from the AI ​​engine to refer to a database and select beauty products and methods suitable for the user. For example, if the analysis reveals that the skin tone is uneven, beauty products that improve skin condition will be recommended.

[0130] Step 4:

[0131] The server uses an emotion engine to analyze the user's emotions from their image and voice data. The emotion engine detects emotional states such as joy, sadness, and stress, and analyzes the results.

[0132] Step 5:

[0133] Based on the analysis results of the emotion engine, the server adjusts recommendations for beauty products and treatments according to the user's emotional state. For example, if the user is feeling stressed, the recommendations may include suggestions for aromatherapy oils with relaxation effects.

[0134] Step 6:

[0135] The server transmits information about selected and tailored beauty products and treatments to the terminal. The terminal displays this information to the user. The user reviews the suggested beauty options and decides to incorporate them into their beauty routine.

[0136] Step 7:

[0137] Users can try out various makeup styles on their faces using the makeup simulation function on their device. This simulation also applies makeup styles based on the results of the emotion engine.

[0138] Step 8:

[0139] Users can improve their daily beauty routines based on the overall suggestions, and the server uses the collected data to analyze and improve the quality of the service.

[0140] (Example 2)

[0141] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0142] This invention aims to solve the problem that current beauty recommendation systems do not adequately consider the user's emotions or individual skin condition, and are limited to recommending a single beauty product or technique. In particular, there is a problem that it is difficult to meet the diverse needs of users because there is a lack of advice based on the user's emotional state.

[0143] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0144] In this invention, the server includes means for receiving visual data and personal information from the user, means for analyzing the received visual data to generate information on the skin condition, and means for analyzing the user's visual data and audio data to recognize emotions. This enables personalized beauty suggestions based on each user's skin condition and emotions.

[0145] "Visual data" refers to image information that shows the user's face and skin condition, and is acquired through a camera.

[0146] "Personal information" refers to information that can individually identify a user, such as their age, gender, and lifestyle.

[0147] "Epidermal condition information" refers to digital representations of skin tone, texture, and moisture level, analyzed by AI.

[0148] "Beauty products" is a general term for products used for caring for skin, hair, etc., and includes skincare products and cosmetics.

[0149] "Beauty techniques" is a general term for methods and techniques used to bring out an individual's beauty.

[0150] "Means of recognizing emotions" refers to technologies that analyze a user's facial expressions and voice to identify their emotions.

[0151] "Cosmetic simulation" is a process that uses digital technology to apply virtual makeup to a user's face and skin.

[0152] This invention is a system for providing beauty recommendations based on a user's personal information and visual data. This system consists of a server, a terminal, and a user.

[0153] The device collects visual data and personal information from the user. This data is acquired through the camera of a smartphone or computer and temporarily stored locally. The user takes a photo of their face and enters information such as age and skin type.

[0154] The terminal sends the collected data to the server using a secure protocol. For example, it is sent as encrypted packet data.

[0155] The server is equipped with an AI engine that analyzes the received data. Software libraries such as TensorFlow and OpenCV are used for the analysis, quantifying skin characteristics. This generates digital information about the epidermal condition.

[0156] The server recommends beauty products and techniques based on digital information. This involves searching a database for products and methods that best reflect the user's skin condition. Furthermore, to recognize emotions, it analyzes the user's facial expressions and voice using tools such as the Azure® Emotion API. Based on these analysis results, the beauty recommendations are refined.

[0157] Users can review the information displayed on their devices, purchase products that suit their needs, and try out new beauty techniques. A cosmetics simulation function is also available, allowing users to virtually try on makeup.

[0158] One example of a prompt might be: "Analyze the user's facial image data, use an AI model to recognize emotions, and generate a prompt message that suggests beauty methods that have a stress-reducing effect."

[0159] In this way, the present invention realizes personalized beauty suggestions based on the user's physiological and emotional state.

[0160] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0161] Step 1:

[0162] Users input visual data and personal information using their devices. Specifically, they take a photo of their face with their smartphone camera and input attribute information such as age and skin type. This information is temporarily stored on the device and retained as JPEG images and text data.

[0163] Step 2:

[0164] The device transmits visual data and personal information collected from the user to the server using a secure protocol (e.g., HTTPS). The input consists of a facial image and text data, and the output is the status of successful transmission to the server. The data is encrypted, and measures are in place to protect user privacy.

[0165] Step 3:

[0166] The server uses an AI engine to analyze the condition of the skin based on the received facial photograph. Specifically, it utilizes libraries such as TensorFlow and OpenCV to quantify skin tone and texture from visual data. The input is a JPEG image of the user, and the output is numerical data of the analyzed skin condition.

[0167] Step 4:

[0168] The server consults a database based on the analyzed information about the skin condition and recommends the most suitable beauty products and techniques. The input is numerical data from the analysis results, and the output is a list of candidate beauty products and techniques. The server generates this list and optimizes it while considering the user's attribute information.

[0169] Step 5:

[0170] The terminal displays recommendations from the server to the user. The user can review the displayed information and select products and technologies that meet their needs. The input is recommendation information from the server, and the output is the products and technologies selected by the user. Specifically, product descriptions and images are presented in a graphical user interface.

[0171] Step 6:

[0172] The device collects the user's facial expressions and voice tone in real time and sends the data to a server for emotion recognition. The input is raw data from the camera and microphone, and the output is the status of completion of transmission to the server.

[0173] Step 7:

[0174] The server uses an emotion engine to analyze the user's emotions and adjusts recommendations accordingly. Input is facial expression and voice data sent from the device, and output is a tailored suggestion of beauty products and technologies. If the user is stressed, recommendations with relaxing effects are prioritized.

[0175] In this way, each step constitutes the overall flow of the system, providing personalized beauty suggestions to the user.

[0176] (Application Example 2)

[0177] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0178] Traditional methods of providing beauty products and services have presented challenges in offering appropriate advice tailored to each user's emotional state and real-time skin condition. Furthermore, the lack of a system in physical stores that allows sales staff to immediately suggest suitable products to customers makes it difficult to improve customer satisfaction.

[0179] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0180] In this invention, the server includes means for receiving image data and attribute information from a user, means for analyzing the received image data to generate digital data on skin condition, and means for analyzing the user's facial features and emotional state in a physical store, enabling sales staff to provide appropriate products and services in real time. This makes it possible to provide personalized beauty products and services to individual users in real time.

[0181] "User-generated image data" refers to digital images provided by users showing the condition of their own face and skin.

[0182] "Attribute information" refers to personal information about a user, such as their age, gender, and lifestyle.

[0183] "Digital data on skin condition" refers to quantified electronic information that indicates the health status of a user's skin.

[0184] "Beauty products and beauty methods" refer to cosmetics and skincare products provided to individual users, as well as the methods used with them.

[0185] "Makeup simulation" is a process that allows users to virtually try out makeup effects based on their facial data.

[0186] "Means for analyzing a user's facial features and emotional state in a physical store" refers to a device or program that recognizes a user's facial expressions and emotions in a physical store and analyzes information based on that.

[0187] "Means to enable salespeople to provide appropriate products and services in real time" refers to a system that supports salespeople in quickly proposing products and services according to the individual needs and current circumstances of each customer.

[0188] To implement this invention, a server, user terminals, and an in-store analysis system are primarily required.

[0189] First, the user uses their device to send their image data and attribute information to the server. This involves capturing a facial image using the device's camera function and uploading the data through a dedicated application. This data is then sent to the server for analysis.

[0190] The server uses an advanced AI engine and image processing libraries (e.g., TensorFlow, OpenCV) to analyze the user's skin condition from received image data and generate it as numerical digital data. Simultaneously, an emotion engine identifies the emotional state from facial expressions and voice data.

[0191] In physical stores, a system is being built that allows sales staff to use hardware such as smart glasses to read customers' facial features and emotional states in real time. This information is sent to a server, and based on the analysis results, the sales staff are recommended the most suitable beauty products and services.

[0192] For example, assuming a customer is looking for skincare products, the server will use their skin condition data to suggest the optimal skincare set in real time. Furthermore, if the analysis indicates the customer is stressed, it will also suggest aromatherapy products with relaxing effects.

[0193] This system utilizes a generative AI model to enable rapid and effective sales support based on prompt messages such as, "Assuming the user's skin condition is sensitive and their emotions are stressed, suggest appropriate hypoallergenic beauty products and relaxation methods."

[0194] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0195] Step 1:

[0196] The device captures the user's facial image and attribute information and sends it to the server. It receives a facial image captured by the camera and attribute information such as age and gender entered by the user as input. It then sends this data to the server as output.

[0197] Step 2:

[0198] The server analyzes received image data using an AI engine (e.g., TensorFlow) to generate digital data on skin condition. It receives a user's facial image as input and analyzes the skin condition based on that image. The output is numerical skin condition data. Specifically, it extracts skin features using a face detection algorithm and evaluates the skin's health.

[0199] Step 3:

[0200] The server uses an emotion engine to identify the user's emotional state from their facial expressions and voice tone. It receives facial images and audio data as input and generates emotional state data as output. Specifically, it applies facial expression analysis and voice tone analysis technologies to recognize emotions such as joy and sadness.

[0201] Step 4:

[0202] The server generates information to recommend to sales staff, selecting the most suitable beauty products and services based on the generated skin condition data and emotional state data. The input is skin condition data and emotional state data. The output is a list of suggested products and services. Specifically, it retrieves appropriate product information by querying the database, and then converts it into a suggestion format that is easy for humans to understand using an AI model that generates prompt messages.

[0203] Step 5:

[0204] The terminal notifies sales staff in the physical store of the suggested information. The input is suggested information from the server, and the output is the display of the information on a display device used by the sales staff. Specifically, the suggested information is displayed on the smart glasses' display, supporting the sales staff in preparing to explain and suggest to the customer.

[0205] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0206] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0207] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0208] [Second Embodiment]

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

[0210] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0211] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0212] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0213] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0214] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0215] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0216] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0217] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0218] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0219] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0220] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0221] The system according to the present invention includes multiple components for analyzing the user's skin condition and recommending customized beauty products and treatments. In implementing the system, the user first inputs their image data and attribute information using a terminal. This input information is transmitted by the terminal to the server via a secure communication path.

[0222] The server passes the received image data to an AI engine utilizing computer vision technology to analyze the skin condition. The digital data obtained from the analysis quantifies the user's skin characteristics, and this is used to select beauty products and treatments. For example, if the system determines that the user has dry skin, highly moisturizing skincare products will be recommended.

[0223] The device displays recommendations received from the server to the user, allowing the user to make selections that suit their preferences. Users can also utilize a makeup simulation function, applying various makeup styles to their own face via the device's camera for preview.

[0224] Furthermore, the server creates a meal plan that takes into account the user's lifestyle information and provides it to the terminal. This meal plan is customized to help users maintain their health and achieve a desirable physique, addressing their specific needs.

[0225] This system, through the functions described above, enables users to efficiently and effectively manage their beauty and health at home. Users can improve their daily beauty care and lifestyle by receiving personalized advice from the system.

[0226] The following describes the processing flow.

[0227] Step 1:

[0228] Users take or upload a photo of their face using their device and enter personal information such as age, gender, and lifestyle. Once they have finished entering the information, they proceed to submit the data.

[0229] Step 2:

[0230] The device collects image data and attribute information provided by the user and sends it to the server via secure communication. Data transfer is encrypted to protect user privacy.

[0231] Step 3:

[0232] The server passes the transmitted image data to the AI ​​engine, which analyzes the skin condition. The AI ​​engine uses machine learning algorithms to analyze the skin's characteristics and generates digital data such as wrinkles, blemishes, and skin tone.

[0233] Step 4:

[0234] The server uses the generated digital data on the user's skin condition to refer to its built-in database and select recommended beauty products and treatments. For example, if the user has dry skin, products with high moisturizing effects will be selected.

[0235] Step 5:

[0236] The server sends the selected beauty products and advice to the terminal. It also analyzes the user's lifestyle information and generates a healthy meal plan.

[0237] Step 6:

[0238] The device displays beauty product recommendations and meal plans received from the server to the user. This allows the user to review the suggestions and incorporate them into their routine as needed.

[0239] Step 7:

[0240] Users can operate the makeup simulation function and try on virtual makeup on their own face in real time using their device's camera. They can then perform actions to see how the selected makeup style will actually look.

[0241] Step 8:

[0242] The server stores user data and supports updates for future use and new recommendations. It can also offer hairstyle and fashion suggestions as needed.

[0243] (Example 1)

[0244] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0245] The goal is to efficiently provide beauty products, methods, and lifestyle-based plans tailored to each user's individual needs, supporting optimal beauty and health management for each individual. Furthermore, a challenge lies in real-time application of virtual styles to provide a more personalized experience.

[0246] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0247] In this invention, the server includes means for acquiring various types of data and characteristic information, means for analyzing the acquired various types of data to generate digital information of the surface state, and means for recommending personalized products and methods based on the generated digital information of the surface state. This makes it possible to efficiently support beauty and health management that is tailored to the user's needs.

[0248] "Multi-type data" refers to the collective term for various types of information necessary for the system to analyze users, such as image data and attribute information collected from users.

[0249] "Characteristic information" refers to detailed information related to individual needs, such as the user's age, gender, and lifestyle.

[0250] "Digital information on surface condition" refers to information where the analyzed skin condition is quantified and represented digitally.

[0251] "Products and methods" refers to beauty products, beauty treatments, and related lifestyle suggestions recommended based on the individual needs of the user.

[0252] A "generative AI model" refers to an artificial intelligence framework used to generate appropriate products and plans based on user information.

[0253] A "prompt statement" is an instruction given to a generative AI model and is an important element for identifying the content that will be generated.

[0254] The system according to the present invention has comprehensive functions for recommending beauty products and methods according to the individual needs of users. This system is implemented through the cooperation of a terminal and a server.

[0255] First, the user uses their device to input their own image data and characteristic information such as age and lifestyle. This data is transmitted from the device to the server via secure communication. On the device, data input and initial processing are performed, and necessary image data is also collected using the camera function.

[0256] The server analyzes the received image data based on its AI engine. This analysis utilizes computer vision technology and deep learning models. Specifically, it uses libraries and frameworks (e.g., TensorFlow, OpenCV) to generate digital information that quantifies the skin condition from the image. Based on this information, the server uses a generative AI model to recommend the most suitable beauty products and methods. During the generation process, prompts are provided to the AI ​​model, and results are generated that are tailored to the user's needs.

[0257] For example, when the prompt "30 years old, female, dry skin, outdoor habit" is input into the AI ​​model, it generates highly moisturizing beauty products and a suitable meal plan.

[0258] Ultimately, the device displays information received from the server on the user's screen, allowing the user to review recommended products and methods. Furthermore, the device offers a makeup simulation function, enabling real-time virtual makeup application via the camera. This allows users to try out virtual styles and helps them explore the beauty methods best suited to them.

[0259] Thus, the system of the present invention provides users with efficient and effective support for personalized beauty and health management.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The user uses the device to input image data and characteristic information (age, gender, lifestyle, etc.). This input information is temporarily stored within the device, and format conversion and simple validation are performed to ensure data integrity. The input data consists of JPEG image files and JSON characteristic information files.

[0263] Step 2:

[0264] The terminal sends the stored image data and feature information to the server. A TLS-based encryption protocol is used for communication to ensure data security. The input data consists of image files and JSON files, which are formatted on the server for immediate processing and analysis.

[0265] Step 3:

[0266] The server passes the received image data to the AI ​​engine for analysis. The AI ​​engine utilizes a deep learning model (e.g., TensorFlow) to analyze the skin condition from the image and outputs the results as numerical digital data. This data includes attributes such as surface texture, pigmentation, and oil content.

[0267] Step 4:

[0268] The server uses a generative AI model to generate personalized beauty products and methods based on digital data and characteristic information of the user's skin condition. In this process, prompt statements (e.g., "30 years old, female, dry skin") are input into the AI ​​model, and the most suitable content for the user is output. This output includes a product list and recommended usage instructions.

[0269] Step 5:

[0270] The server sends information about the generated beauty products and methods to the device. The data is formatted in HTML or as an in-app GUI component for user readability, and is transmitted encrypted.

[0271] Step 6:

[0272] The device displays received beauty information to the user. The user can view the received information and consider available products and services. The device can also invoke a makeup simulation function and apply virtual makeup to the user's face, allowing them to see the results in real time. The virtual makeup is overlaid onto the video stream captured by the camera, and the results are displayed on the screen.

[0273] (Application Example 1)

[0274] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0275] In today's brick-and-mortar stores, providing customers with the most suitable beauty products and treatments based on their individual skin condition and lifestyle is a challenging task. Furthermore, customers often have limited means to verify the effectiveness of products before actually trying them in-store, leading to lengthy purchase decisions. To address these issues, technology that provides personalized information to customers in real time is necessary.

[0276] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0277] In this invention, the server includes means for receiving image data and attribute information from the user, means for analyzing the received image data to generate digital data on the skin condition, and means for utilizing a visual device to display the information in real time and make product recommendations. This allows customers to instantly receive an assessment of their skin condition and recommendations for appropriate beauty products within the store.

[0278] "Image data" refers to digitized visual information that shows the condition of a user's face and skin.

[0279] "Attribute information" refers to data that shows characteristics of the user, such as age, gender, and skin type.

[0280] "Digital data on skin condition" refers to information that analyzes and quantifies the characteristics of a user's skin.

[0281] "Beauty products and beauty treatments" refer to products and methods used to maintain and improve the health and beauty of the skin.

[0282] "Makeup simulation" is a technology that virtually applies makeup to a facial image and visually confirms its effect.

[0283] "Visual devices" are devices used to display information in real time, and include, for example, smart glasses and displays.

[0284] "In-store inventory" refers to the collection of salable products held in physical stores.

[0285] "Product recommendation" refers to the act of selecting and presenting appropriate products based on user characteristics.

[0286] The system that realizes this application example starts with the user using a visual device provided in the store, specifically smart glasses. The user wears the smart glasses, and the terminal scans the user's face with a camera. The terminal transmits the image data and attribute information to the server through a secure communication path. The server analyzes the image data using software such as Python and OpenCV, and generates digital data on the user's skin condition from the received information. An AI model utilizing TensorFlow is used for this process.

[0287] Based on the generated digital data, the server selects the most suitable beauty products for the user from the database and displays the information on the display of the smart glasses in real time. For example, if it is analyzed that the user's skin is dry, products with high moisturizing effects are recommended. Also, a virtual makeup simulation for the user to try on products on the spot is provided, enabling the user to confirm the effects before purchasing products in a physical store.

[0288] In this way, the user can receive real-time recommendations for personalized products and immediately select products that meet their needs. The store side can also manage inventory dynamically, contributing to increased sales.

[0289] As a specific example, it can be mentioned that a user who has the question "Recently my skin is dry, but I don't know what to use" during daily shopping can receive on-site recommendations for moisturizing creams and lotions by using the store's smart glasses.

[0290] An example of a prompt sentence to input into the generating AI model would be, "Please recommend the latest moisturizing cream suitable for a female customer with slightly dry skin."

[0291] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0292] Step 1:

[0293] The user wears smart glasses, and the device scans the user's face with its camera. The input is an image of the user's face, and the output is the scanned image data. The device collects this image data and prepares to transmit it in the next step.

[0294] Step 2:

[0295] The terminal transmits collected image data and user attribute information to the server via a secure communication path. The input is image data and attribute information, and the output is data transfer to the server. In this step, the data is properly encrypted to prevent unauthorized viewing.

[0296] Step 3:

[0297] The server processes the received image data using Python and OpenCV to begin analyzing the user's skin condition. The input is image data, and the output is digital data of the skin condition. This data analysis uses an AI model powered by TensorFlow to quantify the skin's characteristics.

[0298] Step 4:

[0299] The server selects suitable beauty products from the database based on the generated digital skin condition data. The input is the digital skin condition data, and the output is a list of recommended beauty products. In this step, the products best suited to the user's skin needs are selected.

[0300] Step 5:

[0301] The server transmits information about selected beauty products to the smart glasses display in real time, presenting it to the user. The input is a list of beauty products, and the output is the information displayed through the visual device. The user can review the products here and request more detailed information if needed.

[0302] Step 6:

[0303] Based on the information presented, users can select and decide to purchase beauty products. In this step, the store's inventory management system is updated according to the user's selection. Makeup simulations are also available, allowing users to see a virtual effect before making a selection.

[0304] In this way, the system provides personalized services to the user through a series of processes.

[0305] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0306] This invention incorporates an emotion engine that recognizes the user's emotions into a system for suggesting individually customized beauty products and methods based on the user's facial image data and attribute information. The user first inputs their facial photograph and personal information using a terminal and sends it to the server via the terminal. The server receives this data, uses an AI engine to analyze the skin condition, and generates quantified skin condition data.

[0307] Based on the generated data, the server refers to the database to recommend beauty products and methods suitable for the user. Specifically, for example, if it is analyzed that the user's skin is particularly sensitive, low-irritant skin care products will be proposed. And when an emotion engine is added to this process, it becomes possible to analyze emotions from the user's photos and input data, and further adjust and provide beauty advice according to the user's psychological state.

[0308] The emotion engine analyzes the user's expressions and voice tones through the terminal's camera and microphone, and recognizes emotions such as joy, sadness, and surprise. For example, when the emotion engine recognizes that the user is feeling stressed, it can recommend products with a relaxing effect or beauty methods that can refresh. Furthermore, the makeup simulation executed on the terminal can also provide virtual makeup in colors and styles that match the user's emotional state.

[0309] The user can check these proposed contents on their own terminal and purchase beauty products or implement beauty methods according to their preferences. As a result, without leaving home, the user can receive personalized beauty care that suits their emotions. This system provides comprehensive beauty care considering the user's physical and emotional states.

[0310] The processing flow will be described below.

[0311] Step 1:

[0312] The user uses the terminal to take or upload a photo of their face and input attribute information such as age, gender, and lifestyle habits. The input data is sent from the terminal to the server.

[0313] Step 2:

[0314] The server retrieves image data and attribute information received from the terminal. The image data is passed to the AI ​​engine, where a detailed analysis of the skin condition is performed. The AI ​​engine quantifies skin wrinkles, blemishes, and tone, and generates this data digitally.

[0315] Step 3:

[0316] The server uses digital data on skin condition obtained from the AI ​​engine to refer to a database and select beauty products and methods suitable for the user. For example, if the analysis reveals that the skin tone is uneven, beauty products that improve skin condition will be recommended.

[0317] Step 4:

[0318] The server uses an emotion engine to analyze the user's emotions from their image and voice data. The emotion engine detects emotional states such as joy, sadness, and stress, and analyzes the results.

[0319] Step 5:

[0320] Based on the analysis results of the emotion engine, the server adjusts recommendations for beauty products and treatments according to the user's emotional state. For example, if the user is feeling stressed, the recommendations may include suggestions for aromatherapy oils with relaxation effects.

[0321] Step 6:

[0322] The server transmits information about selected and tailored beauty products and treatments to the terminal. The terminal displays this information to the user. The user reviews the suggested beauty options and decides to incorporate them into their beauty routine.

[0323] Step 7:

[0324] Users can try out various makeup styles on their faces using the makeup simulation function on their device. This simulation also applies makeup styles based on the results of the emotion engine.

[0325] Step 8:

[0326] Users can improve their daily beauty routines based on the overall suggestions, and the server uses the collected data to analyze and improve the quality of the service.

[0327] (Example 2)

[0328] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0329] This invention aims to solve the problem that current beauty recommendation systems do not adequately consider the user's emotions or individual skin condition, and are limited to recommending a single beauty product or technique. In particular, there is a problem that it is difficult to meet the diverse needs of users because there is a lack of advice based on the user's emotional state.

[0330] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0331] In this invention, the server includes means for receiving visual data and personal information from the user, means for analyzing the received visual data to generate information on the skin condition, and means for analyzing the user's visual data and audio data to recognize emotions. This enables personalized beauty suggestions based on each user's skin condition and emotions.

[0332] "Visual data" refers to image information that shows the user's face and skin condition, and is acquired through a camera.

[0333] "Personal information" refers to information that can individually identify a user, such as their age, gender, and lifestyle.

[0334] "Epidermal condition information" refers to digital representations of skin tone, texture, and moisture level, analyzed by AI.

[0335] "Beauty products" is a general term for products used for caring for skin, hair, etc., and includes skincare products and cosmetics.

[0336] "Beauty techniques" is a general term for methods and techniques used to bring out an individual's beauty.

[0337] "Means of recognizing emotions" refers to technologies that analyze a user's facial expressions and voice to identify their emotions.

[0338] "Cosmetic simulation" is a process that uses digital technology to apply virtual makeup to a user's face and skin.

[0339] This invention is a system for providing beauty recommendations based on a user's personal information and visual data. This system consists of a server, a terminal, and a user.

[0340] The device collects visual data and personal information from the user. This data is acquired through the camera of a smartphone or computer and temporarily stored locally. The user takes a photo of their face and enters information such as age and skin type.

[0341] The terminal sends the collected data to the server using a secure protocol. For example, it is sent as encrypted packet data.

[0342] The server is equipped with an AI engine that analyzes the received data. Software libraries such as TensorFlow and OpenCV are used for the analysis, quantifying skin characteristics. This generates digital information about the epidermal condition.

[0343] The server recommends beauty products and techniques based on digital information. This involves searching a database for products and methods that best reflect the user's skin condition. Furthermore, to recognize emotions, it analyzes the user's facial expressions and voice using tools such as the Azure Emotion API. Based on these analysis results, the beauty recommendations are refined.

[0344] Users can review the information displayed on their devices, purchase products that suit their needs, and try out new beauty techniques. A cosmetics simulation function is also available, allowing users to virtually try on makeup.

[0345] One example of a prompt might be: "Analyze the user's facial image data, use an AI model to recognize emotions, and generate a prompt message that suggests beauty methods that have a stress-reducing effect."

[0346] In this way, the present invention realizes personalized beauty suggestions based on the user's physiological and emotional state.

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

[0348] Step 1:

[0349] Users input visual data and personal information using their devices. Specifically, they take a photo of their face with their smartphone camera and input attribute information such as age and skin type. This information is temporarily stored on the device and retained as JPEG images and text data.

[0350] Step 2:

[0351] The device transmits visual data and personal information collected from the user to the server using a secure protocol (e.g., HTTPS). The input consists of a facial image and text data, and the output is the status of successful transmission to the server. The data is encrypted, and measures are in place to protect user privacy.

[0352] Step 3:

[0353] The server uses an AI engine to analyze the condition of the skin based on the received facial photograph. Specifically, it utilizes libraries such as TensorFlow and OpenCV to quantify skin tone and texture from visual data. The input is a JPEG image of the user, and the output is numerical data of the analyzed skin condition.

[0354] Step 4:

[0355] The server consults a database based on the analyzed information about the skin condition and recommends the most suitable beauty products and techniques. The input is numerical data from the analysis results, and the output is a list of candidate beauty products and techniques. The server generates this list and optimizes it while considering the user's attribute information.

[0356] Step 5:

[0357] The terminal displays recommendations from the server to the user. The user can review the displayed information and select products and technologies that meet their needs. The input is recommendation information from the server, and the output is the products and technologies selected by the user. Specifically, product descriptions and images are presented in a graphical user interface.

[0358] Step 6:

[0359] The device collects the user's facial expressions and voice tone in real time and sends the data to a server for emotion recognition. The input is raw data from the camera and microphone, and the output is the status of completion of transmission to the server.

[0360] Step 7:

[0361] The server uses an emotion engine to analyze the user's emotions and adjusts recommendations accordingly. Input is facial expression and voice data sent from the device, and output is a tailored suggestion of beauty products and technologies. If the user is stressed, recommendations with relaxing effects are prioritized.

[0362] In this way, each step constitutes the overall flow of the system, providing personalized beauty suggestions to the user.

[0363] (Application Example 2)

[0364] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0365] Traditional methods of providing beauty products and services have presented challenges in offering appropriate advice tailored to each user's emotional state and real-time skin condition. Furthermore, the lack of a system in physical stores that allows sales staff to immediately suggest suitable products to customers makes it difficult to improve customer satisfaction.

[0366] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0367] In this invention, the server includes means for receiving image data and attribute information from a user, means for analyzing the received image data to generate digital data on skin condition, and means for analyzing the user's facial features and emotional state in a physical store, enabling sales staff to provide appropriate products and services in real time. This makes it possible to provide personalized beauty products and services to individual users in real time.

[0368] "User-generated image data" refers to digital images provided by users showing the condition of their own face and skin.

[0369] "Attribute information" refers to personal information about a user, such as their age, gender, and lifestyle.

[0370] "Digital data on skin condition" refers to quantified electronic information that indicates the health status of a user's skin.

[0371] "Beauty products and beauty methods" refer to cosmetics and skincare products provided to individual users, as well as the methods used with them.

[0372] "Makeup simulation" is a process that allows users to virtually try out makeup effects based on their facial data.

[0373] "Means for analyzing a user's facial features and emotional state in a physical store" refers to a device or program that recognizes a user's facial expressions and emotions in a physical store and analyzes information based on that.

[0374] "Means to enable salespeople to provide appropriate products and services in real time" refers to a system that supports salespeople in quickly proposing products and services according to the individual needs and current circumstances of each customer.

[0375] To implement this invention, a server, user terminals, and an in-store analysis system are primarily required.

[0376] First, the user uses their device to send their image data and attribute information to the server. This involves capturing a facial image using the device's camera function and uploading the data through a dedicated application. This data is then sent to the server for analysis.

[0377] The server uses an advanced AI engine and image processing libraries (e.g., TensorFlow, OpenCV) to analyze the user's skin condition from received image data and generate it as numerical digital data. Simultaneously, an emotion engine identifies the emotional state from facial expressions and voice data.

[0378] In physical stores, a system is being built that allows sales staff to use hardware such as smart glasses to read customers' facial features and emotional states in real time. This information is sent to a server, and based on the analysis results, the sales staff are recommended the most suitable beauty products and services.

[0379] For example, assuming a customer is looking for skincare products, the server will use their skin condition data to suggest the optimal skincare set in real time. Furthermore, if the analysis indicates the customer is stressed, it will also suggest aromatherapy products with relaxing effects.

[0380] This system utilizes a generative AI model to enable rapid and effective sales support based on prompt messages such as, "Assuming the user's skin condition is sensitive and their emotions are stressed, suggest appropriate hypoallergenic beauty products and relaxation methods."

[0381] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0382] Step 1:

[0383] The device captures the user's facial image and attribute information and sends it to the server. It receives a facial image captured by the camera and attribute information such as age and gender entered by the user as input. It then sends this data to the server as output.

[0384] Step 2:

[0385] The server analyzes received image data using an AI engine (e.g., TensorFlow) to generate digital data on skin condition. It receives a user's facial image as input and analyzes the skin condition based on that image. The output is numerical skin condition data. Specifically, it extracts skin features using a face detection algorithm and evaluates the skin's health.

[0386] Step 3:

[0387] The server uses an emotion engine to identify the user's emotional state from their facial expressions and voice tone. It receives facial images and audio data as input and generates emotional state data as output. Specifically, it applies facial expression analysis and voice tone analysis technologies to recognize emotions such as joy and sadness.

[0388] Step 4:

[0389] The server generates information to recommend to sales staff, selecting the most suitable beauty products and services based on the generated skin condition data and emotional state data. The input is skin condition data and emotional state data. The output is a list of suggested products and services. Specifically, it retrieves appropriate product information by querying the database, and then converts it into a suggestion format that is easy for humans to understand using an AI model that generates prompt messages.

[0390] Step 5:

[0391] The terminal notifies sales staff in the physical store of the suggested information. The input is suggested information from the server, and the output is the display of the information on a display device used by the sales staff. Specifically, the suggested information is displayed on the smart glasses' display, supporting the sales staff in preparing to explain and suggest to the customer.

[0392] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0393] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0394] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0395] [Third Embodiment]

[0396] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0397] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0398] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0399] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0400] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0401] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0402] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0403] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0404] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0405] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0406] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0407] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0408] The system according to the present invention includes multiple components for analyzing the user's skin condition and recommending customized beauty products and treatments. In implementing the system, the user first inputs their image data and attribute information using a terminal. This input information is transmitted by the terminal to the server via a secure communication path.

[0409] The server passes the received image data to an AI engine utilizing computer vision technology to analyze the skin condition. The digital data obtained from the analysis quantifies the user's skin characteristics, and this is used to select beauty products and treatments. For example, if the system determines that the user has dry skin, highly moisturizing skincare products will be recommended.

[0410] The device displays recommendations received from the server to the user, allowing the user to make selections that suit their preferences. Users can also utilize a makeup simulation function, applying various makeup styles to their own face via the device's camera for preview.

[0411] Furthermore, the server creates a meal plan that takes into account the user's lifestyle information and provides it to the terminal. This meal plan is customized to help users maintain their health and achieve a desirable physique, addressing their specific needs.

[0412] This system, through the functions described above, enables users to efficiently and effectively manage their beauty and health at home. Users can improve their daily beauty care and lifestyle by receiving personalized advice from the system.

[0413] The following describes the processing flow.

[0414] Step 1:

[0415] Users take or upload a photo of their face using their device and enter personal information such as age, gender, and lifestyle. Once they have finished entering the information, they proceed to submit the data.

[0416] Step 2:

[0417] The device collects image data and attribute information provided by the user and sends it to the server via secure communication. Data transfer is encrypted to protect user privacy.

[0418] Step 3:

[0419] The server passes the transmitted image data to the AI ​​engine, which analyzes the skin condition. The AI ​​engine uses machine learning algorithms to analyze the skin's characteristics and generates digital data such as wrinkles, blemishes, and skin tone.

[0420] Step 4:

[0421] The server uses the generated digital data on the user's skin condition to refer to its built-in database and select recommended beauty products and treatments. For example, if the user has dry skin, products with high moisturizing effects will be selected.

[0422] Step 5:

[0423] The server sends the selected beauty products and advice to the terminal. It also analyzes the user's lifestyle information and generates a healthy meal plan.

[0424] Step 6:

[0425] The device displays beauty product recommendations and meal plans received from the server to the user. This allows the user to review the suggestions and incorporate them into their routine as needed.

[0426] Step 7:

[0427] Users can operate the makeup simulation function and try on virtual makeup on their own face in real time using their device's camera. They can then perform actions to see how the selected makeup style will actually look.

[0428] Step 8:

[0429] The server stores user data and supports updates for future use and new recommendations. It can also offer hairstyle and fashion suggestions as needed.

[0430] (Example 1)

[0431] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0432] The goal is to efficiently provide beauty products, methods, and lifestyle-based plans tailored to each user's individual needs, supporting optimal beauty and health management for each individual. Furthermore, a challenge lies in real-time application of virtual styles to provide a more personalized experience.

[0433] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0434] In this invention, the server includes means for acquiring various types of data and characteristic information, means for analyzing the acquired various types of data to generate digital information of the surface state, and means for recommending personalized products and methods based on the generated digital information of the surface state. This makes it possible to efficiently support beauty and health management that is tailored to the user's needs.

[0435] "Multi-type data" refers to the collective term for various types of information necessary for the system to analyze users, such as image data and attribute information collected from users.

[0436] "Characteristic information" refers to detailed information related to individual needs, such as the user's age, gender, and lifestyle.

[0437] "Digital information on surface condition" refers to information where the analyzed skin condition is quantified and represented digitally.

[0438] "Products and methods" refers to beauty products, beauty treatments, and related lifestyle suggestions recommended based on the individual needs of the user.

[0439] A "generative AI model" refers to an artificial intelligence framework used to generate appropriate products and plans based on user information.

[0440] A "prompt statement" is an instruction given to a generative AI model and is an important element for identifying the content that will be generated.

[0441] The system according to the present invention has comprehensive functions for recommending beauty products and methods according to the individual needs of users. This system is implemented through the cooperation of a terminal and a server.

[0442] First, the user uses their device to input their own image data and characteristic information such as age and lifestyle. This data is transmitted from the device to the server via secure communication. On the device, data input and initial processing are performed, and necessary image data is also collected using the camera function.

[0443] The server analyzes the received image data based on its AI engine. This analysis utilizes computer vision technology and deep learning models. Specifically, it uses libraries and frameworks (e.g., TensorFlow, OpenCV) to generate digital information that quantifies the skin condition from the image. Based on this information, the server uses a generative AI model to recommend the most suitable beauty products and methods. During the generation process, prompts are provided to the AI ​​model, and results are generated that are tailored to the user's needs.

[0444] For example, when the prompt "30 years old, female, dry skin, outdoor habit" is input into the AI ​​model, it generates highly moisturizing beauty products and a suitable meal plan.

[0445] Ultimately, the device displays information received from the server on the user's screen, allowing the user to review recommended products and methods. Furthermore, the device offers a makeup simulation function, enabling real-time virtual makeup application via the camera. This allows users to try out virtual styles and helps them explore the beauty methods best suited to them.

[0446] Thus, the system of the present invention provides users with efficient and effective support for personalized beauty and health management.

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

[0448] Step 1:

[0449] The user uses the device to input image data and characteristic information (age, gender, lifestyle, etc.). This input information is temporarily stored within the device, and format conversion and simple validation are performed to ensure data integrity. The input data consists of JPEG image files and JSON characteristic information files.

[0450] Step 2:

[0451] The terminal sends the stored image data and feature information to the server. A TLS-based encryption protocol is used for communication to ensure data security. The input data consists of image files and JSON files, which are formatted on the server for immediate processing and analysis.

[0452] Step 3:

[0453] The server passes the received image data to the AI ​​engine for analysis. The AI ​​engine utilizes a deep learning model (e.g., TensorFlow) to analyze the skin condition from the image and outputs the results as numerical digital data. This data includes attributes such as surface texture, pigmentation, and oil content.

[0454] Step 4:

[0455] The server uses a generative AI model to generate personalized beauty products and methods based on digital data and characteristic information of the user's skin condition. In this process, prompt statements (e.g., "30 years old, female, dry skin") are input into the AI ​​model, and the most suitable content for the user is output. This output includes a product list and recommended usage instructions.

[0456] Step 5:

[0457] The server sends information about the generated beauty products and methods to the device. The data is formatted in HTML or as an in-app GUI component for user readability, and is transmitted encrypted.

[0458] Step 6:

[0459] The device displays received beauty information to the user. The user can view the received information and consider available products and services. The device can also invoke a makeup simulation function and apply virtual makeup to the user's face, allowing them to see the results in real time. The virtual makeup is overlaid onto the video stream captured by the camera, and the results are displayed on the screen.

[0460] (Application Example 1)

[0461] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0462] In today's brick-and-mortar stores, providing customers with the most suitable beauty products and treatments based on their individual skin condition and lifestyle is a challenging task. Furthermore, customers often have limited means to verify the effectiveness of products before actually trying them in-store, leading to lengthy purchase decisions. To address these issues, technology that provides personalized information to customers in real time is necessary.

[0463] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0464] In this invention, the server includes means for receiving image data and attribute information from the user, means for analyzing the received image data to generate digital data on the skin condition, and means for utilizing a visual device to display the information in real time and make product recommendations. This allows customers to instantly receive an assessment of their skin condition and recommendations for appropriate beauty products within the store.

[0465] "Image data" refers to digitized visual information that shows the condition of a user's face and skin.

[0466] "Attribute information" refers to data that shows characteristics of the user, such as age, gender, and skin type.

[0467] "Digital data on skin condition" refers to information that analyzes and quantifies the characteristics of a user's skin.

[0468] "Beauty products and beauty treatments" refer to products and methods used to maintain and improve the health and beauty of the skin.

[0469] "Makeup simulation" is a technology that virtually applies makeup to a facial image and visually confirms its effect.

[0470] "Visual devices" are devices used to display information in real time, and include, for example, smart glasses and displays.

[0471] "In-store inventory" refers to the collection of products that are available for sale and are held in a physical store.

[0472] "Product recommendation" is the act of selecting and presenting appropriate products based on the user's characteristics.

[0473] The system that realizes this application example begins with the user using a visual device provided in the store, specifically smart glasses. The user puts on the smart glasses, and a terminal scans the user's face with a camera. The terminal sends image data and attribute information to a server via a secure communication channel. The server analyzes the image data using software called Python and OpenCV, and generates digital data of the user's skin condition from the received information. An AI model utilizing TensorFlow is used for this process.

[0474] Based on the generated digital data, the server selects the most suitable beauty products for the user from a database and displays the information in real time on the smart glasses' display. For example, if the analysis reveals that the user's skin is dry, products with high moisturizing effects will be recommended. A virtual makeup simulation is also provided so that users can try out the products on the spot and check their effects before purchasing them in a physical store.

[0475] In this way, users receive personalized product recommendations in real time and can instantly select products that meet their needs. Stores can also manage inventory dynamically, contributing to increased sales.

[0476] A concrete example is a user who, while doing their daily shopping, wonders, "My skin has been dry lately, but I don't know what to use." They can then use the smart glasses in the store to receive recommendations for moisturizing creams and lotions on the spot.

[0477] An example of a prompt sentence to input into the generating AI model would be, "Please recommend the latest moisturizing cream suitable for a female customer with slightly dry skin."

[0478] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0479] Step 1:

[0480] The user wears smart glasses, and the device scans the user's face with its camera. The input is an image of the user's face, and the output is the scanned image data. The device collects this image data and prepares to send it in the next step.

[0481] Step 2:

[0482] The terminal transmits collected image data and user attribute information to the server via a secure communication path. The input is image data and attribute information, and the output is data transfer to the server. In this step, the data is properly encrypted to prevent unauthorized viewing.

[0483] Step 3:

[0484] The server processes the received image data using Python and OpenCV to begin analyzing the user's skin condition. The input is image data, and the output is digital data of the skin condition. This data analysis uses an AI model powered by TensorFlow to quantify the skin's characteristics.

[0485] Step 4:

[0486] The server selects suitable beauty products from the database based on the generated digital skin condition data. The input is the digital skin condition data, and the output is a list of recommended beauty products. In this step, the products best suited to the user's skin needs are selected.

[0487] Step 5:

[0488] The server transmits information about selected beauty products to the smart glasses display in real time, presenting it to the user. The input is a list of beauty products, and the output is the information displayed through the visual device. The user can then review the products and request more detailed information if needed.

[0489] Step 6:

[0490] Based on the information presented, users can select and decide to purchase beauty products. In this step, the store's inventory management system is updated according to the user's selection. Makeup simulations are also available, allowing users to see a virtual effect before making a selection.

[0491] In this way, the system provides personalized services to the user through a series of processes.

[0492] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0493] This invention incorporates an emotion engine that recognizes the user's emotions into a system for suggesting individually customized beauty products and methods based on the user's facial image data and attribute information. The user first inputs their facial photograph and personal information using a terminal and sends it to the server via the terminal. The server receives this data, uses an AI engine to analyze the skin condition, and generates quantified skin condition data.

[0494] Based on the generated data, the server consults a database to recommend beauty products and methods tailored to the user. Specifically, for example, if the analysis reveals that the user's skin is particularly sensitive, hypoallergenic skincare products will be suggested. Furthermore, by incorporating an emotion engine into this process, it becomes possible to analyze the user's emotions from their photos and input data, and provide beauty advice that is further refined to suit the user's psychological state.

[0495] The emotion engine analyzes the user's facial expressions and voice tone through the device's camera and microphone to recognize emotions such as joy, sadness, and surprise. For example, if the emotion engine detects that the user is stressed, it can recommend relaxing products or refreshing beauty treatments. Furthermore, the makeup simulation running on the device can provide virtual makeup in colors and styles that match the user's emotional state.

[0496] Users can review these suggestions on their devices and purchase beauty products or implement beauty treatments according to their preferences. This allows users to receive personalized beauty care tailored to their emotional state from the comfort of their home. This system provides comprehensive beauty care that takes into account the user's physiological and emotional state.

[0497] The following describes the processing flow.

[0498] Step 1:

[0499] Users take or upload a photo of their face using their device and enter attribute information such as age, gender, and lifestyle. The entered data is sent from the device to the server.

[0500] Step 2:

[0501] The server retrieves image data and attribute information received from the terminal. The image data is passed to the AI ​​engine, where a detailed analysis of the skin condition is performed. The AI ​​engine quantifies skin wrinkles, blemishes, and tone, and generates this data digitally.

[0502] Step 3:

[0503] The server uses digital data on skin condition obtained from the AI ​​engine to refer to a database and select beauty products and methods suitable for the user. For example, if the analysis reveals that the skin tone is uneven, beauty products that improve skin condition will be recommended.

[0504] Step 4:

[0505] The server uses an emotion engine to analyze the user's emotions from their image and audio data. The emotion engine detects emotional states such as joy, sadness, and stress, and analyzes the results.

[0506] Step 5:

[0507] Based on the analysis results of the emotion engine, the server adjusts recommendations for beauty products and treatments according to the user's emotional state. For example, if the user is feeling stressed, the recommendations may include suggestions for aromatherapy oils with relaxation effects.

[0508] Step 6:

[0509] The server transmits information about selected and tailored beauty products and treatments to the terminal. The terminal displays this information to the user. The user reviews the suggested beauty options and decides to incorporate them into their beauty routine.

[0510] Step 7:

[0511] Users can try out various makeup styles on their faces using the makeup simulation function on their device. This simulation also applies makeup styles based on the results of the emotion engine.

[0512] Step 8:

[0513] Users can improve their daily beauty routines based on the overall suggestions, and the server uses the collected data to analyze and improve the quality of the service.

[0514] (Example 2)

[0515] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0516] This invention aims to solve the problem that current beauty recommendation systems do not adequately consider the user's emotions or individual skin condition, and are limited to recommending a single beauty product or technique. In particular, there is a problem that it is difficult to meet the diverse needs of users because there is a lack of advice based on the user's emotional state.

[0517] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0518] In this invention, the server includes means for receiving visual data and personal information from the user, means for analyzing the received visual data to generate information on the skin condition, and means for analyzing the user's visual data and audio data to recognize emotions. This enables personalized beauty suggestions based on each user's skin condition and emotions.

[0519] "Visual data" refers to image information that shows the user's face and skin condition, and is acquired through a camera.

[0520] "Personal information" refers to information that can individually identify a user, such as their age, gender, and lifestyle.

[0521] "Epidermal condition information" refers to digital representations of skin tone, texture, and moisture level, analyzed by AI.

[0522] "Beauty products" is a general term for products used for caring for skin, hair, etc., and includes skincare products and cosmetics.

[0523] "Beauty techniques" is a general term for methods and techniques used to bring out an individual's beauty.

[0524] "Means of recognizing emotions" refers to technologies that analyze a user's facial expressions and voice to identify their emotions.

[0525] "Cosmetic simulation" is a process that uses digital technology to apply virtual makeup to a user's face and skin.

[0526] This invention is a system for providing beauty recommendations based on a user's personal information and visual data. This system consists of a server, a terminal, and a user.

[0527] The device collects visual data and personal information from the user. This data is acquired through the camera of a smartphone or computer and temporarily stored locally. The user takes a photo of their face and enters information such as age and skin type.

[0528] The terminal sends the collected data to the server using a secure protocol. For example, it is sent as encrypted packet data.

[0529] The server is equipped with an AI engine that analyzes the received data. Software libraries such as TensorFlow and OpenCV are used for the analysis, quantifying skin characteristics. This generates digital information about the epidermal condition.

[0530] The server recommends beauty products and techniques based on digital information. This involves searching a database for products and methods that best reflect the user's skin condition. Furthermore, to recognize emotions, it analyzes the user's facial expressions and voice using tools such as the Azure Emotion API. Based on these analysis results, the beauty recommendations are refined.

[0531] Users can review the information displayed on their devices, purchase products that suit their needs, and try out new beauty techniques. A cosmetics simulation function is also available, allowing users to virtually try on makeup.

[0532] A concrete example of a prompt could be: "Analyze the user's facial image data, recognize their emotions using an AI model, and generate a prompt message that suggests beauty methods that have a stress-reducing effect."

[0533] In this way, the present invention realizes personalized beauty suggestions based on the user's physiological and emotional state.

[0534] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0535] Step 1:

[0536] Users input visual data and personal information using their devices. Specifically, they take a photo of their face with their smartphone camera and input attribute information such as age and skin type. This information is temporarily stored on the device and retained as JPEG images and text data.

[0537] Step 2:

[0538] The device transmits visual data and personal information collected from the user to the server using a secure protocol (e.g., HTTPS). The input consists of a facial image and text data, and the output is the status of successful transmission to the server. The data is encrypted, and measures are in place to protect user privacy.

[0539] Step 3:

[0540] The server uses an AI engine to analyze the condition of the skin based on the received facial photograph. Specifically, it utilizes libraries such as TensorFlow and OpenCV to quantify skin tone and texture from visual data. The input is a JPEG image of the user, and the output is numerical data of the analyzed skin condition.

[0541] Step 4:

[0542] The server consults a database based on the analyzed epidermal condition information and recommends the most suitable beauty products and techniques. The input is numerical data from the analysis results, and the output is a list of candidate beauty products and techniques. The server generates this list and optimizes it considering the user's attribute information.

[0543] Step 5:

[0544] The terminal displays recommendations from the server to the user. The user can review the displayed information and select products and technologies that meet their needs. The input is recommendation information from the server, and the output is the products and technologies selected by the user. Specifically, product descriptions and images are presented on a graphical user interface.

[0545] Step 6:

[0546] The device collects the user's facial expressions and voice tone in real time and sends the data to a server for emotion recognition. The input is raw data from the camera and microphone, and the output is the status of completion of transmission to the server.

[0547] Step 7:

[0548] The server uses an emotion engine to analyze the user's emotions and adjusts recommendations accordingly. Input is facial expression and voice data sent from the device, and output is a tailored suggestion of beauty products and technologies. If the user is stressed, recommendations with relaxing effects are prioritized.

[0549] In this way, each step constitutes the overall flow of the system, providing personalized beauty suggestions to the user.

[0550] (Application Example 2)

[0551] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0552] Traditional methods of providing beauty products and services have presented challenges in offering appropriate advice tailored to each user's emotional state and real-time skin condition. Furthermore, the lack of a system in physical stores that allows sales staff to immediately suggest suitable products to customers makes it difficult to improve customer satisfaction.

[0553] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0554] In this invention, the server includes means for receiving image data and attribute information from a user, means for analyzing the received image data to generate digital data on skin condition, and means for analyzing the user's facial features and emotional state in a physical store, enabling sales staff to provide appropriate products and services in real time. This makes it possible to provide personalized beauty products and services to individual users in real time.

[0555] "User-generated image data" refers to digital images provided by users showing the condition of their own face and skin.

[0556] "Attribute information" refers to personal information about a user, such as their age, gender, and lifestyle.

[0557] "Digital data on skin condition" refers to quantified electronic information that indicates the health status of a user's skin.

[0558] "Beauty products and beauty methods" refer to cosmetics and skincare products provided to individual users, as well as the methods used with them.

[0559] "Makeup simulation" is a process that allows users to virtually try out makeup effects based on their facial data.

[0560] "Means for analyzing a user's facial features and emotional state in a physical store" refers to a device or program that recognizes a user's facial expressions and emotions in a physical store and analyzes information based on that.

[0561] "Means to enable salespeople to provide appropriate products and services in real time" refers to a system that supports salespeople in quickly proposing products and services according to the individual needs and current circumstances of each customer.

[0562] To implement this invention, a server, user terminals, and an in-store analysis system are primarily required.

[0563] First, the user uses their device to send their image data and attribute information to the server. This involves capturing a facial image using the device's camera function and uploading the data through a dedicated application. This data is then sent to the server for analysis.

[0564] The server uses an advanced AI engine and image processing libraries (e.g., TensorFlow, OpenCV) to analyze the user's skin condition from received image data and generate it as numerical digital data. Simultaneously, an emotion engine identifies the emotional state from facial expressions and voice data.

[0565] In physical stores, a system is being built where sales staff use hardware such as smart glasses to read customers' facial features and emotional states in real time. This information is sent to a server, and based on the analysis results, the sales staff are recommended the most suitable beauty products and services.

[0566] For example, assuming a customer is looking for skincare products, the server will use their skin condition data to suggest the optimal skincare set in real time. Furthermore, if the analysis indicates the customer is stressed, it will also suggest aromatherapy products with relaxing effects.

[0567] This system utilizes a generative AI model to enable rapid and effective sales support based on prompt messages such as, "Assuming the user's skin condition is sensitive and their emotions are stressed, suggest appropriate hypoallergenic beauty products and relaxation methods."

[0568] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0569] Step 1:

[0570] The device captures the user's facial image and attribute information and sends it to the server. It receives a facial image captured by the camera and attribute information such as age and gender entered by the user as input. It then sends this data to the server as output.

[0571] Step 2:

[0572] The server analyzes received image data using an AI engine (e.g., TensorFlow) to generate digital data on skin condition. It receives a user's facial image as input and analyzes the skin condition based on that image. The output is numerical skin condition data. Specifically, it extracts skin features using a face detection algorithm and evaluates the skin's health.

[0573] Step 3:

[0574] The server uses an emotion engine to identify the user's emotional state from their facial expressions and voice tone. It receives facial images and audio data as input and generates emotional state data as output. Specifically, it applies facial expression analysis and voice tone analysis technologies to recognize emotions such as joy and sadness.

[0575] Step 4:

[0576] The server generates information to recommend to sales staff, selecting the most suitable beauty products and services based on the generated skin condition data and emotional state data. The input is skin condition data and emotional state data. The output is a list of suggested products and services. Specifically, it retrieves appropriate product information by querying the database, and then converts it into a suggestion format that is easy for humans to understand using an AI model that generates prompt messages.

[0577] Step 5:

[0578] The terminal notifies sales staff in the physical store of the suggested information. The input is suggested information from the server, and the output is the display of the information on a display device used by the sales staff. Specifically, the suggested information is displayed on the smart glasses' display, supporting the sales staff in preparing to explain and suggest to the customer.

[0579] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0580] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0581] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0582] [Fourth Embodiment]

[0583] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0584] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0585] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0586] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0587] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0588] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0589] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0590] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0591] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0592] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0593] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0594] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0595] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0596] The system according to the present invention includes multiple components for analyzing the user's skin condition and recommending customized beauty products and treatments. In implementing the system, the user first inputs their image data and attribute information using a terminal. This input information is transmitted by the terminal to the server via a secure communication path.

[0597] The server passes the received image data to an AI engine utilizing computer vision technology to analyze the skin condition. The digital data obtained from the analysis quantifies the user's skin characteristics, and this is used to select beauty products and treatments. For example, if the system determines that the user has dry skin, highly moisturizing skincare products will be recommended.

[0598] The device displays recommendations received from the server to the user, allowing the user to make selections that suit their preferences. Users can also utilize a makeup simulation function, applying various makeup styles to their own face via the device's camera for preview.

[0599] Furthermore, the server creates a meal plan that takes into account the user's lifestyle information and provides it to the terminal. This meal plan is customized to help users maintain their health and achieve a desirable physique, addressing their specific needs.

[0600] This system, through the functions described above, enables users to efficiently and effectively manage their beauty and health at home. Users can improve their daily beauty care and lifestyle by receiving personalized advice from the system.

[0601] The following describes the processing flow.

[0602] Step 1:

[0603] Users take or upload a photo of their face using their device and enter personal information such as age, gender, and lifestyle. Once they have finished entering the information, they proceed to submit the data.

[0604] Step 2:

[0605] The device collects image data and attribute information provided by the user and sends it to the server via secure communication. Data transfer is encrypted to protect user privacy.

[0606] Step 3:

[0607] The server passes the transmitted image data to the AI ​​engine, which analyzes the skin condition. The AI ​​engine uses machine learning algorithms to analyze the skin's characteristics and generates digital data such as wrinkles, blemishes, and skin tone.

[0608] Step 4:

[0609] The server uses the generated digital data on the user's skin condition to refer to its built-in database and select recommended beauty products and treatments. For example, if the user has dry skin, products with high moisturizing effects will be selected.

[0610] Step 5:

[0611] The server sends the selected beauty products and advice to the terminal. It also analyzes the user's lifestyle information and generates a healthy meal plan.

[0612] Step 6:

[0613] The device displays beauty product recommendations and meal plans received from the server to the user. This allows the user to review the suggestions and incorporate them into their routine as needed.

[0614] Step 7:

[0615] Users can operate the makeup simulation function and try on virtual makeup on their own face in real time using their device's camera. They can then perform actions to see how the selected makeup style will actually look.

[0616] Step 8:

[0617] The server stores user data and supports updates for future use and new recommendations. It can also offer hairstyle and fashion suggestions as needed.

[0618] (Example 1)

[0619] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0620] The goal is to efficiently provide beauty products, methods, and lifestyle-based plans tailored to each user's individual needs, supporting optimal beauty and health management for each individual. Furthermore, a challenge lies in real-time application of virtual styles to provide a more personalized experience.

[0621] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0622] In this invention, the server includes means for acquiring various types of data and characteristic information, means for analyzing the acquired various types of data to generate digital information of the surface state, and means for recommending personalized products and methods based on the generated digital information of the surface state. This makes it possible to efficiently support beauty and health management that is tailored to the user's needs.

[0623] "Multi-type data" refers to the collective term for various types of information necessary for the system to analyze users, such as image data and attribute information collected from users.

[0624] "Characteristic information" refers to detailed information related to individual needs, such as the user's age, gender, and lifestyle.

[0625] "Digital information on surface condition" refers to information where the analyzed skin condition is quantified and represented digitally.

[0626] "Products and methods" refers to beauty products, beauty treatments, and related lifestyle suggestions recommended based on the individual needs of the user.

[0627] A "generative AI model" refers to an artificial intelligence framework used to generate appropriate products and plans based on user information.

[0628] A "prompt statement" is an instruction given to a generative AI model and is an important element for identifying the content that will be generated.

[0629] The system according to the present invention has comprehensive functions for recommending beauty products and methods according to the individual needs of users. This system is implemented through the cooperation of a terminal and a server.

[0630] First, the user uses their device to input their own image data and characteristic information such as age and lifestyle. This data is transmitted from the device to the server via secure communication. On the device, data input and initial processing are performed, and necessary image data is also collected using the camera function.

[0631] The server analyzes the received image data based on its AI engine. This analysis utilizes computer vision technology and deep learning models. Specifically, it uses libraries and frameworks (e.g., TensorFlow, OpenCV) to generate digital information that quantifies the skin condition from the image. Based on this information, the server uses a generative AI model to recommend the most suitable beauty products and methods. During the generation process, prompts are provided to the AI ​​model, and results are generated that are tailored to the user's needs.

[0632] For example, when the prompt "30 years old, female, dry skin, outdoor habit" is input into the AI ​​model, it generates highly moisturizing beauty products and a suitable meal plan.

[0633] Ultimately, the device displays information received from the server on the user's screen, allowing the user to review recommended products and methods. Furthermore, the device offers a makeup simulation function, enabling real-time virtual makeup application via the camera. This allows users to try out virtual styles and helps them explore the beauty methods best suited to them.

[0634] Thus, the system of the present invention provides users with efficient and effective support for personalized beauty and health management.

[0635] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0636] Step 1:

[0637] The user uses the device to input image data and characteristic information (age, gender, lifestyle, etc.). This input information is temporarily stored within the device, and format conversion and simple validation are performed to ensure data integrity. The input data consists of JPEG image files and JSON characteristic information files.

[0638] Step 2:

[0639] The terminal sends the stored image data and feature information to the server. A TLS-based encryption protocol is used for communication to ensure data security. The input data consists of image files and JSON files, which are formatted on the server for immediate processing and analysis.

[0640] Step 3:

[0641] The server passes the received image data to the AI ​​engine for analysis. The AI ​​engine utilizes a deep learning model (e.g., TensorFlow) to analyze the skin condition from the image and outputs the results as numerical digital data. This data includes attributes such as surface texture, pigmentation, and oil content.

[0642] Step 4:

[0643] The server uses a generative AI model to generate personalized beauty products and methods based on digital data and characteristic information of the user's skin condition. In this process, prompt statements (e.g., "30 years old, female, dry skin") are input into the AI ​​model, and the most suitable content for the user is output. This output includes a product list and recommended usage instructions.

[0644] Step 5:

[0645] The server sends information about the generated beauty products and methods to the device. The data is formatted in HTML or as an in-app GUI component for user readability, and is transmitted encrypted.

[0646] Step 6:

[0647] The device displays received beauty information to the user. The user can view the received information and consider available products and services. The device can also invoke a makeup simulation function and apply virtual makeup to the user's face, allowing them to see the results in real time. The virtual makeup is overlaid onto the video stream captured by the camera, and the results are displayed on the screen.

[0648] (Application Example 1)

[0649] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0650] In today's brick-and-mortar stores, providing customers with the most suitable beauty products and treatments based on their individual skin condition and lifestyle is a challenging task. Furthermore, customers often have limited means to verify the effectiveness of products before actually trying them in-store, leading to lengthy purchase decisions. To address these issues, technology that provides personalized information to customers in real time is necessary.

[0651] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0652] In this invention, the server includes means for receiving image data and attribute information from the user, means for analyzing the received image data to generate digital data on the skin condition, and means for utilizing a visual device to display the information in real time and make product recommendations. This allows customers to instantly receive an assessment of their skin condition and recommendations for appropriate beauty products within the store.

[0653] "Image data" refers to digitized visual information that shows the condition of a user's face and skin.

[0654] "Attribute information" refers to data that shows characteristics of the user, such as age, gender, and skin type.

[0655] "Digital data on skin condition" refers to information that analyzes and quantifies the characteristics of a user's skin.

[0656] "Beauty products and beauty treatments" refer to products and methods used to maintain and improve the health and beauty of the skin.

[0657] "Makeup simulation" is a technology that virtually applies makeup to a facial image and visually confirms its effect.

[0658] "Visual devices" are devices used to display information in real time, and include, for example, smart glasses and displays.

[0659] "In-store inventory" refers to the collection of products that are available for sale and are held in a physical store.

[0660] "Product recommendation" is the act of selecting and presenting appropriate products based on the user's characteristics.

[0661] The system that realizes this application example begins with the user using a visual device provided in the store, specifically smart glasses. The user puts on the smart glasses, and a terminal scans the user's face with a camera. The terminal sends image data and attribute information to a server via a secure communication channel. The server analyzes the image data using software called Python and OpenCV, and generates digital data of the user's skin condition from the received information. An AI model utilizing TensorFlow is used for this process.

[0662] Based on the generated digital data, the server selects the most suitable beauty products for the user from a database and displays the information in real time on the smart glasses' display. For example, if the analysis reveals that the user's skin is dry, products with high moisturizing effects will be recommended. A virtual makeup simulation is also provided so that users can try out the products on the spot and check their effects before purchasing them in a physical store.

[0663] In this way, users receive personalized product recommendations in real time and can instantly select products that meet their needs. Stores can also manage inventory dynamically, contributing to increased sales.

[0664] A concrete example is a user who, while doing their daily shopping, wonders, "My skin has been dry lately, but I don't know what to use." They can then use the smart glasses in the store to receive recommendations for moisturizing creams and lotions on the spot.

[0665] An example of a prompt sentence to input into the generating AI model would be, "Please recommend the latest moisturizing cream suitable for a female customer with slightly dry skin."

[0666] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0667] Step 1:

[0668] The user wears smart glasses, and the device scans the user's face with its camera. The input is an image of the user's face, and the output is the scanned image data. The device collects this image data and prepares to send it in the next step.

[0669] Step 2:

[0670] The terminal transmits collected image data and user attribute information to the server via a secure communication path. The input is image data and attribute information, and the output is data transfer to the server. In this step, the data is properly encrypted to prevent unauthorized viewing.

[0671] Step 3:

[0672] The server processes the received image data using Python and OpenCV to begin analyzing the user's skin condition. The input is image data, and the output is digital data of the skin condition. This data analysis uses an AI model powered by TensorFlow to quantify the skin's characteristics.

[0673] Step 4:

[0674] The server selects suitable beauty products from the database based on the generated digital skin condition data. The input is the digital skin condition data, and the output is a list of recommended beauty products. In this step, the products best suited to the user's skin needs are selected.

[0675] Step 5:

[0676] The server transmits information about selected beauty products to the smart glasses display in real time, presenting it to the user. The input is a list of beauty products, and the output is the information displayed through the visual device. The user can then review the products and request more detailed information if needed.

[0677] Step 6:

[0678] Based on the information presented, users can select and decide to purchase beauty products. In this step, the store's inventory management system is updated according to the user's selection. Makeup simulations are also available, allowing users to see a virtual effect before making a selection.

[0679] In this way, the system provides personalized services to the user through a series of processes.

[0680] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0681] This invention incorporates an emotion engine that recognizes the user's emotions into a system for suggesting individually customized beauty products and methods based on the user's facial image data and attribute information. The user first inputs their facial photograph and personal information using a terminal and sends it to the server via the terminal. The server receives this data, uses an AI engine to analyze the skin condition, and generates quantified skin condition data.

[0682] Based on the generated data, the server consults a database to recommend beauty products and methods tailored to the user. Specifically, for example, if the analysis reveals that the user's skin is particularly sensitive, hypoallergenic skincare products will be suggested. Furthermore, by incorporating an emotion engine into this process, it becomes possible to analyze the user's emotions from their photos and input data, and provide beauty advice that is further refined to suit the user's psychological state.

[0683] The emotion engine analyzes the user's facial expressions and voice tone through the device's camera and microphone to recognize emotions such as joy, sadness, and surprise. For example, if the emotion engine detects that the user is stressed, it can recommend relaxing products or refreshing beauty treatments. Furthermore, the makeup simulation running on the device can provide virtual makeup in colors and styles that match the user's emotional state.

[0684] Users can review these suggestions on their devices and purchase beauty products or implement beauty treatments according to their preferences. This allows users to receive personalized beauty care tailored to their emotional state from the comfort of their home. This system provides comprehensive beauty care that takes into account the user's physiological and emotional state.

[0685] The following describes the processing flow.

[0686] Step 1:

[0687] Users take or upload a photo of their face using their device and enter attribute information such as age, gender, and lifestyle. The entered data is sent from the device to the server.

[0688] Step 2:

[0689] The server retrieves image data and attribute information received from the terminal. The image data is passed to the AI ​​engine, where a detailed analysis of the skin condition is performed. The AI ​​engine quantifies skin wrinkles, blemishes, and tone, and generates this data digitally.

[0690] Step 3:

[0691] The server uses digital data on skin condition obtained from the AI ​​engine to refer to a database and select beauty products and methods suitable for the user. For example, if the analysis reveals that the skin tone is uneven, beauty products that improve skin condition will be recommended.

[0692] Step 4:

[0693] The server uses an emotion engine to analyze the user's emotions from their image and audio data. The emotion engine detects emotional states such as joy, sadness, and stress, and analyzes the results.

[0694] Step 5:

[0695] Based on the analysis results of the emotion engine, the server adjusts recommendations for beauty products and treatments according to the user's emotional state. For example, if the user is feeling stressed, the recommendations may include suggestions for aromatherapy oils with relaxation effects.

[0696] Step 6:

[0697] The server transmits information about selected and tailored beauty products and treatments to the terminal. The terminal displays this information to the user. The user reviews the suggested beauty options and decides to incorporate them into their beauty routine.

[0698] Step 7:

[0699] Users can try out various makeup styles on their faces using the makeup simulation function on their device. This simulation also applies makeup styles based on the results of the emotion engine.

[0700] Step 8:

[0701] Users can improve their daily beauty routines based on the overall suggestions, and the server uses the collected data to analyze and improve the quality of the service.

[0702] (Example 2)

[0703] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0704] This invention aims to solve the problem that current beauty recommendation systems do not adequately consider the user's emotions or individual skin condition, and are limited to recommending a single beauty product or technique. In particular, there is a problem that it is difficult to meet the diverse needs of users because there is a lack of advice based on the user's emotional state.

[0705] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0706] In this invention, the server includes means for receiving visual data and personal information from the user, means for analyzing the received visual data to generate information on the skin condition, and means for analyzing the user's visual data and audio data to recognize emotions. This enables personalized beauty suggestions based on each user's skin condition and emotions.

[0707] "Visual data" refers to image information that shows the user's face and skin condition, and is acquired through a camera.

[0708] "Personal information" refers to information that can individually identify a user, such as their age, gender, and lifestyle.

[0709] "Epidermal condition information" refers to digital representations of skin tone, texture, and moisture level, analyzed by AI.

[0710] "Beauty products" is a general term for products used for caring for skin, hair, etc., and includes skincare products and cosmetics.

[0711] "Beauty techniques" is a general term for methods and techniques used to bring out an individual's beauty.

[0712] "Means of recognizing emotions" refers to technologies that analyze a user's facial expressions and voice to identify their emotions.

[0713] "Cosmetic simulation" is a process that uses digital technology to apply virtual makeup to a user's face and skin.

[0714] This invention is a system for providing beauty recommendations based on a user's personal information and visual data. This system consists of a server, a terminal, and a user.

[0715] The device collects visual data and personal information from the user. This data is acquired through the camera of a smartphone or computer and temporarily stored locally. The user takes a photo of their face and enters information such as age and skin type.

[0716] The terminal sends the collected data to the server using a secure protocol. For example, it is sent as encrypted packet data.

[0717] The server is equipped with an AI engine that analyzes the received data. Software libraries such as TensorFlow and OpenCV are used for the analysis, quantifying skin characteristics. This generates digital information about the epidermal condition.

[0718] The server recommends beauty products and techniques based on digital information. This involves searching a database for products and methods that best reflect the user's skin condition. Furthermore, to recognize emotions, it analyzes the user's facial expressions and voice using tools such as the Azure Emotion API. Based on these analysis results, the beauty recommendations are refined.

[0719] Users can review the information displayed on their devices, purchase products that suit their needs, and try out new beauty techniques. A cosmetics simulation function is also available, allowing users to virtually try on makeup.

[0720] A concrete example of a prompt could be: "Analyze the user's facial image data, recognize their emotions using an AI model, and generate a prompt message that suggests beauty methods that have a stress-reducing effect."

[0721] In this way, the present invention realizes personalized beauty suggestions based on the user's physiological and emotional state.

[0722] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0723] Step 1:

[0724] Users input visual data and personal information using their devices. Specifically, they take a photo of their face with their smartphone camera and input attribute information such as age and skin type. This information is temporarily stored on the device and retained as JPEG images and text data.

[0725] Step 2:

[0726] The device transmits visual data and personal information collected from the user to the server using a secure protocol (e.g., HTTPS). The input consists of a facial image and text data, and the output is the status of successful transmission to the server. The data is encrypted, and measures are in place to protect user privacy.

[0727] Step 3:

[0728] The server uses an AI engine to analyze the condition of the skin based on the received facial photograph. Specifically, it utilizes libraries such as TensorFlow and OpenCV to quantify skin tone and texture from visual data. The input is a JPEG image of the user, and the output is numerical data of the analyzed skin condition.

[0729] Step 4:

[0730] The server consults a database based on the analyzed epidermal condition information and recommends the most suitable beauty products and techniques. The input is numerical data from the analysis results, and the output is a list of candidate beauty products and techniques. The server generates this list and optimizes it considering the user's attribute information.

[0731] Step 5:

[0732] The terminal displays recommendations from the server to the user. The user can review the displayed information and select products and technologies that meet their needs. The input is recommendation information from the server, and the output is the products and technologies selected by the user. Specifically, product descriptions and images are presented on a graphical user interface.

[0733] Step 6:

[0734] The device collects the user's facial expressions and voice tone in real time and sends the data to a server for emotion recognition. The input is raw data from the camera and microphone, and the output is the status of completion of transmission to the server.

[0735] Step 7:

[0736] The server uses an emotion engine to analyze the user's emotions and adjusts recommendations accordingly. Input is facial expression and voice data sent from the device, and output is a tailored suggestion of beauty products and technologies. If the user is stressed, recommendations with relaxing effects are prioritized.

[0737] In this way, each step constitutes the overall flow of the system, providing personalized beauty suggestions to the user.

[0738] (Application Example 2)

[0739] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0740] Traditional methods of providing beauty products and services have presented challenges in offering appropriate advice tailored to each user's emotional state and real-time skin condition. Furthermore, the lack of a system in physical stores that allows sales staff to immediately suggest suitable products to customers makes it difficult to improve customer satisfaction.

[0741] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0742] In this invention, the server includes means for receiving image data and attribute information from a user, means for analyzing the received image data to generate digital data on skin condition, and means for analyzing the user's facial features and emotional state in a physical store, enabling sales staff to provide appropriate products and services in real time. This makes it possible to provide personalized beauty products and services to individual users in real time.

[0743] "User-generated image data" refers to digital images provided by users showing the condition of their own face and skin.

[0744] "Attribute information" refers to personal information about a user, such as their age, gender, and lifestyle.

[0745] "Digital data on skin condition" refers to quantified electronic information that indicates the health status of a user's skin.

[0746] "Beauty products and beauty methods" refer to cosmetics and skincare products provided to individual users, as well as the methods used with them.

[0747] "Makeup simulation" is a process that allows users to virtually try out makeup effects based on their facial data.

[0748] "Means for analyzing a user's facial features and emotional state in a physical store" refers to a device or program that recognizes a user's facial expressions and emotions in a physical store and analyzes information based on that.

[0749] "Means to enable salespeople to provide appropriate products and services in real time" refers to a system that supports salespeople in quickly proposing products and services according to the individual needs and current circumstances of each customer.

[0750] To implement this invention, a server, user terminals, and an in-store analysis system are primarily required.

[0751] First, the user uses their device to send their image data and attribute information to the server. This involves capturing a facial image using the device's camera function and uploading the data through a dedicated application. This data is then sent to the server for analysis.

[0752] The server uses an advanced AI engine and image processing libraries (e.g., TensorFlow, OpenCV) to analyze the user's skin condition from received image data and generate it as numerical digital data. Simultaneously, an emotion engine identifies the emotional state from facial expressions and voice data.

[0753] In physical stores, a system is being built where sales staff use hardware such as smart glasses to read customers' facial features and emotional states in real time. This information is sent to a server, and based on the analysis results, the sales staff are recommended the most suitable beauty products and services.

[0754] For example, assuming a customer is looking for skincare products, the server will use their skin condition data to suggest the optimal skincare set in real time. Furthermore, if the analysis indicates the customer is stressed, it will also suggest aromatherapy products with relaxing effects.

[0755] This system utilizes a generative AI model to enable rapid and effective sales support based on prompt messages such as, "Assuming the user's skin condition is sensitive and their emotions are stressed, suggest appropriate hypoallergenic beauty products and relaxation methods."

[0756] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0757] Step 1:

[0758] The device captures the user's facial image and attribute information and sends it to the server. It receives a facial image captured by the camera and attribute information such as age and gender entered by the user as input. It then sends this data to the server as output.

[0759] Step 2:

[0760] The server analyzes received image data using an AI engine (e.g., TensorFlow) to generate digital data on skin condition. It receives a user's facial image as input and analyzes the skin condition based on that image. The output is numerical skin condition data. Specifically, it extracts skin features using a face detection algorithm and evaluates the skin's health.

[0761] Step 3:

[0762] The server uses an emotion engine to identify the user's emotional state from their facial expressions and voice tone. It receives facial images and audio data as input and generates emotional state data as output. Specifically, it applies facial expression analysis and voice tone analysis technologies to recognize emotions such as joy and sadness.

[0763] Step 4:

[0764] The server generates information to recommend to sales staff, selecting the most suitable beauty products and services based on the generated skin condition data and emotional state data. The input is skin condition data and emotional state data. The output is a list of suggested products and services. Specifically, it retrieves appropriate product information by querying the database, and then converts it into a suggestion format that is easy for humans to understand using an AI model that generates prompt messages.

[0765] Step 5:

[0766] The terminal notifies sales staff in the physical store of the suggested information. The input is suggested information from the server, and the output is the display of the information on a display device used by the sales staff. Specifically, the suggested information is displayed on the smart glasses' display, supporting the sales staff in preparing to explain and suggest to the customer.

[0767] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0768] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0769] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0770] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0771] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0772] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0773] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0774] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0775] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0776] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0777] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0778] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0779] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0780] 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.

[0781] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0782] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0783] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0784] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0785] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0786] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0787] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0788] The following is further disclosed regarding the embodiments described above.

[0789] (Claim 1)

[0790] A means for receiving image data and attribute information from a user,

[0791] A means for analyzing received image data to generate digital data of skin condition,

[0792] Based on the generated digital data of skin condition, a means of recommending individual beauty products and beauty methods,

[0793] A means of providing users with information about beauty products and beauty methods,

[0794] A means for performing a makeup simulation based on the user's facial data,

[0795] A system that includes this.

[0796] (Claim 2)

[0797] The system according to claim 1, comprising means for generating an individualized meal plan based on the user's lifestyle information.

[0798] (Claim 3)

[0799] The system according to claim 1, comprising means for displaying virtualized beauty items and clothing on actual facial data in real time.

[0800] "Example 1"

[0801] (Claim 1)

[0802] A means of acquiring various types of data and characteristic information from users,

[0803] A means for analyzing various acquired data to generate digital information on the surface state,

[0804] A means of recommending personalized products and methods based on the generated digital information of the surface state,

[0805] Means of providing users with information about products and methods,

[0806] A means of simulating a virtualized style based on the user's facial data,

[0807] A method for utilizing a generated AI model by making full use of analysis results and prompt messages,

[0808] A system that includes this.

[0809] (Claim 2)

[0810] The system according to claim 1, comprising means for generating personalized plans based on user behavior information.

[0811] (Claim 3)

[0812] The system according to claim 1, comprising means for sequentially displaying three-dimensionalized ornaments and clothing on actual facial data.

[0813] "Application Example 1"

[0814] (Claim 1)

[0815] A means for receiving image data and attribute information from a user,

[0816] A means for analyzing received image data to generate digital data of skin condition,

[0817] Based on the generated digital data of skin condition, a means of recommending individual beauty products and beauty methods,

[0818] A means of providing users with information about beauty products and beauty methods,

[0819] A means for performing a makeup simulation based on the user's facial data,

[0820] A means of utilizing visual devices to display information in real time and recommend products,

[0821] A system that includes this.

[0822] (Claim 2)

[0823] The system according to claim 1, comprising means for generating an individualized meal plan based on the user's lifestyle information.

[0824] (Claim 3)

[0825] The system according to claim 1, comprising means for displaying virtualized beauty items and clothing on actual facial data in real time, and means for presenting appropriate product information from in-store inventory.

[0826] "Example 2 of combining an emotion engine"

[0827] (Claim 1)

[0828] Means for receiving visual data and personal information from users,

[0829] A means for analyzing received visual data to generate information about the state of the epidermis,

[0830] A means of recommending individual beauty products and beauty techniques based on the generated information on the condition of the epidermis,

[0831] A means of providing users with information about beauty products and beauty techniques,

[0832] A means of recognizing emotions by analyzing the user's visual and audio data,

[0833] A means of adjusting beauty products and techniques according to recognized emotions,

[0834] A means for performing cosmetic simulations based on the user's visual data,

[0835] A system that includes this.

[0836] (Claim 2)

[0837] The system according to claim 1, comprising means for generating an individualized meal plan based on the user's lifestyle information.

[0838] (Claim 3)

[0839] The system according to claim 1, comprising means for instantly displaying virtualized beauty tools and exteriors on actual visual data.

[0840] "Application example 2 when combining with an emotional engine"

[0841] (Claim 1)

[0842] A means for receiving image data and attribute information from a user,

[0843] A means for analyzing received image data to generate digital data of skin condition,

[0844] Based on the generated digital data of skin condition, a means of recommending individual beauty products and beauty methods,

[0845] A means of providing users with information about beauty products and beauty methods,

[0846] A means for performing a makeup simulation based on the user's facial data,

[0847] A means to analyze a user's facial features and emotional state in a physical store, enabling sales staff to provide appropriate products and services in real time.

[0848] A system that includes this.

[0849] (Claim 2)

[0850] The system according to claim 1, comprising means for generating an individualized meal plan based on the user's lifestyle information.

[0851] (Claim 3)

[0852] The system according to claim 1, comprising means for displaying virtualized beauty items and clothing on actual facial data in real time. [Explanation of symbols]

[0853] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving image data and attribute information from a user, A means for analyzing received image data to generate digital data of skin condition, Based on the generated digital data of skin condition, a means of recommending individual beauty products and beauty methods, A means of providing users with information about beauty products and beauty methods, A means for performing a makeup simulation based on the user's facial data, A system that includes this.

2. The system according to claim 1, comprising means for generating an individualized meal plan based on the user's lifestyle information.

3. The system according to claim 1, comprising means for displaying virtualized beauty items and clothing on actual facial data in real time.

Images