System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to input a selfie image and body composition measurement data; means for transmitting the selfie image and the body composition measurement data to a server; means for the server to perform face mapping on the selfie image and analyze body characteristics of the user based on the body composition measurement data; means for the server to compare the analysis result with a latest fashion trend database and propose an optimal fashion, hairstyle, and makeup to the user; and means for transmitting and displaying the proposal to a terminal of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the past, users had to go through the hassle of gathering information from magazines and the Internet and then repeatedly go through trial and error to find the hairstyle, makeup, and fashion that best suits them. It also took a lot of time and effort to choose a beauty salon and fashion items. Furthermore, it was necessary to update styles as needed to accommodate changes in body shape and age, which required a lot of effort. The present invention aims to solve these problems and provide a system that allows users to quickly and easily find the style that best suits them. [Means for solving the problem]

[0005] The system of the present invention comprises the following means: A means is provided for a user to input a selfie image and body composition measurement data and send it to a server; The server is provided with means for face mapping the selfie image and analyzing the user's physical characteristics based on the body composition measurement data; The server then provides means for comparing the analysis results with an up-to-date fashion trend database and suggesting the most suitable fashion, hairstyle, and makeup for the user; A means is provided for sending these suggestions to the user's device and displaying them; The system further comprises means for providing recommended hair salon information based on the user's location information, and means for sending a request to rent the suggested fashion items and providing the rental items. This series of means allows users to easily find the style that best suits them without wasting time or effort.

[0006] A "selfie" is an image taken by a user of their own face using a smartphone or camera.

[0007] "Body composition measurement data" refers to data related to the user's body composition, such as weight, body fat percentage, and muscle mass.

[0008] A "server" is a computer system that receives, analyzes, stores, and transmits the results to a user terminal.

[0009] "Face mapping" is a technology that analyzes the shape and features of a user's face based on a selfie image.

[0010] The "Latest Fashion Trend Database" is a database that contains information on the latest trends and styles.

[0011] The "analysis results" are information about the user's facial and physical characteristics generated by the server based on the selfie image and body composition measurement data.

[0012] "Fashion, hairstyle, and makeup suggestions" refers to information that suggests hairstyles, outfits, and makeup methods that are best suited to the user based on the analysis results and the latest fashion trend database.

[0013] A "terminal" is a device such as a smartphone or computer operated by a user.

[0014] "Recommended hair salon information" is information about hair salons that offer hairstyles and makeup services, selected based on the user's location information.

[0015] "Rental items" are clothing and accessories that users can borrow for a set period of time.

[0016] "Sending a request" is an operation in which a user instructs a server through a terminal to perform a specific action. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] This system allows users to input their selfie photos and body composition measurement data, and based on that information, it suggests optimal fashion, hairstyles, and makeup. The system consists of a user's device, a server, and affiliated beauty salons and rental shops.

[0039] System configuration

[0040] 1. User's device: On a device such as a smartphone or computer, users take a selfie, enter body composition measurement data, and check suggested styles.

[0041] 2. Server: Receives data, analyzes it, compares it with trend information, and generates and sends recommendations.

[0042] 3. Beauty salons and rental shops: Providing services and items based on requests received from the server.

[0043] Program processing

[0044] The program processing within this system will be explained in natural language below.

[0045] 1. User enters data

[0046] Users use a dedicated smart body composition scale to measure their weight, body fat percentage, etc. The measurement data is sent to the user's device.

[0047] Next, the user takes a selfie using the device's camera and uploads it to the app.

[0048] 2. The device sends the data to the server

[0049] The device sends the captured selfie image and body composition measurement data to the server.

[0050] 3. The server analyzes the data

[0051] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color.

[0052] At the same time, body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc.

[0053] 4. The server checks the data against the trend database.

[0054] The server compares facial features and body type data with the latest fashion trend database, and then selects hairstyles, makeup, and fashion items that are best suited to the user.

[0055] 5. The server generates and sends a proposal

[0056] Based on the results of the comparison, the server will suggest the best style for the user, including an image of the hairstyle, detailed makeup instructions, and a combination of fashion items.

[0057] Suggestions are sent to the user's device and displayed through the app.

[0058] 6. Providing beauty salon and rental services

[0059] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[0060] Similarly, for the suggested fashion items, rental services are available, and users can send requests from their devices. The rental shop will then process the delivery of the items.

[0061] Specific examples

[0062] User A (32 years old, female)

[0063] Measure your weight and body fat percentage using a dedicated body composition scale, and upload a selfie photo using your smartphone.

[0064] The server analyzes this data and matches the latest summer fashion trends based on User A's face shape and body type.

[0065] We suggest a lightweight jacket in cool colors, shorts, and natural makeup.

[0066] The server recommends reputable local hair salons and stylists and provides booking links.

[0067] The suggested fashion items will be delivered to your home the next day using a rental service.

[0068] User B (45 years old, male)

[0069] Measure your weight and body fat percentage with a smart body composition scale and upload a selfie using your smartphone.

[0070] The server analyzes the data and matches it with the latest autumn fashion trends based on the sharp features of User B's jawline.

[0071] We suggest a dark green jacket, gray pants, and loafers.

[0072] The server recommends the best two-block hairstyle and provides information on nearby hair salons and a link to make a reservation.

[0073] The suggested fashion items will be delivered to your home the next day using a rental service.

[0074] This allows users to easily enjoy styles that incorporate the latest trends.

[0075] The processing flow will be explained below.

[0076] Step 1:

[0077] The user steps onto the dedicated smart body composition scale and obtains body composition measurement data such as weight, body fat percentage, muscle mass, etc. This data is automatically sent to the user's device.

[0078] Step 2:

[0079] The user launches a dedicated app and takes a selfie with their smartphone camera, which is then uploaded to the app.

[0080] Step 3:

[0081] The device sends the selfie image and body composition measurement data it has acquired to a server. The data is sent using a secure communication protocol, so it arrives safely at the server.

[0082] Step 4:

[0083] The server inputs the received selfie into an AI analysis algorithm to perform face mapping, which extracts features such as the user's facial shape, skin color, and hair texture.

[0084] Step 5:

[0085] The server analyzes the body composition measurement data and determines the user's physical characteristics such as height, weight, body fat percentage, and muscle mass.

[0086] Step 6:

[0087] The server compares the analysis results with a database of current fashion trends, which includes information on the latest hairstyles, makeup, and fashion items.

[0088] Step 7:

[0089] The server selects the hairstyle, makeup, and fashion items that are best suited to the user and generates them as recommendation information.

[0090] Step 8:

[0091] The server generates and sends the recommendation information to the device, which includes images of specific hairstyles, makeup steps, and photos of fashion items and combinations.

[0092] Step 9:

[0093] The device displays the received recommendation information to the user, who can then check the suggested styles via the app.

[0094] Step 10:

[0095] The server provides recommended hair salon information based on the user's location, and if the user wishes, a link to make a reservation at the appropriate salon is also provided.

[0096] Step 11:

[0097] If the user likes the suggested fashion item, they can send a rental request through the app.

[0098] Step 12:

[0099] The server receives the rental request and sends a request for the specified item to the affiliated rental shop.

[0100] Step 13:

[0101] The rental shop will confirm the request and prepare to deliver the specified fashion item to the user's address.

[0102] Step 14:

[0103] The user receives the rented fashion item and uses it for the specified period. After use, the rental item is returned.

[0104] By following these steps, users can easily find the style that best suits them and receive services at a beauty salon. They can also rent suggested fashion items.

[0105] Example 1

[0106] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0107] Conventional systems have had difficulty fully reflecting individual physical characteristics and the latest fashion trends when proposing fashion, hairstyles, and makeup that are suited to a user's appearance. Furthermore, the content of the proposals was limited to static information, and the provision of specific advice and recommendations that were highly practical for users was insufficient. This led to a problem of lower user satisfaction with improvements to their style.

[0108] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0109] In this invention, the server includes means for face mapping a selfie image and analyzing the user's physical characteristics based on body composition measurement data, means for comparing the results with a trend database to suggest optimal fashion, hairstyle, and makeup for the user, and means for automatically generating details of the suggestions using a generative AI model and providing them to the user. This makes it possible to suggest specific styles that reflect individual physical characteristics and the latest trends, as well as provide highly practical, detailed advice.

[0110] A "selfie" refers to an image of a user's face or body taken by the user themselves.

[0111] "Body composition measurement data" refers to data regarding the user's physical composition, such as weight, body fat percentage, and muscle mass.

[0112] "Server" refers to the computer system responsible for analyzing the data it receives, collating it, generating suggestions, and sending them to the user.

[0113] "Face mapping" refers to the process of using image analysis technology to extract facial shapes and features from selfies.

[0114] "Physical characteristics" refers to a user's physical characteristics such as body shape, skin color, and body fat percentage.

[0115] A "trend database" refers to a database that stores information about the latest fashions, hairstyles, and makeup.

[0116] "Fashion" refers to the style of clothing, accessories, etc.

[0117] "Hairstyle" refers to the design or style of a hairstyle.

[0118] "Makeup" refers to the method and style of applying makeup.

[0119] A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to analyze text, images, and data.

[0120] "Suggestions" refers to specific advice and information about fashion, hairstyles, and makeup provided to users.

[0121] "User's device" refers to a device such as a smartphone or computer used by the user.

[0122] "Location Information" means information that indicates a User's current geographic location.

[0123] "Hair Salon Information" refers to data and booking links about hair salons recommended to users.

[0124] "Rental items" refer to fashion items that users can borrow temporarily.

[0125] This invention is a system that allows users to input selfie photos and body composition measurement data, and based on that information, suggests optimal fashion, hairstyles, and makeup. The system is composed of a user's terminal, a server, and affiliated service providers.

[0126] System configuration

[0127] 1. User's Device

[0128] The user's device is a device such as a smartphone or PC. The user uses these devices to take selfies, input body composition measurement data, and check the suggested style. Specific examples include iPhone (registered trademark) and Android (registered trademark) devices.

[0129] 2. Server

[0130] The server receives and analyzes the data, compares it with trend information, and generates and sends proposals. A specific example is an EC2 instance from AWS (registered trademark) that uses cloud services. The server analyzes the data using OpenCV, a facial recognition library, and TENSORFLOW (registered trademark), a machine learning framework, and automatically generates proposal details using a generative AI model (e.g., GPT-3 (registered trademark)).

[0131] 3. Affiliated Service Providers

[0132] The affiliated service providers are beauty salons and fashion rental shops that provide services and items to users. These service providers provide services and items based on requests received from the server.

[0133] Program processing

[0134] The program processing within this system will be explained in natural language below.

[0135] 1. The user enters data

[0136] The user uses a dedicated smart body composition scale (for example, a general body composition scale) to measure weight, body fat percentage, etc. The measurement data is sent to a device (for example, an iPhone).

[0137] Next, the user takes a selfie using the device's camera and uploads it to the app. "Tap the 'Measure' button on the home screen, and once the measurement is complete, the data will be automatically transferred to the app. Then tap the 'Camera' button to take a selfie, and press the 'Upload' button to send the data to the server."

[0138] 2. The device sends the data to the server

[0139] The device sends the selfie image and body composition measurement data captured by the user to a server via Wi-Fi or mobile data communication using an encrypted communication protocol (e.g., HTTPS).

[0140] 3. The server analyzes the data

[0141] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color. The software used here is a facial recognition library (e.g., OpenCV).

[0142] At the same time, the body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc. A machine learning model (for example, a model using TensorFlow) is used for the analysis.

[0143] 4. The server checks the data against the trend database.

[0144] The server compares the facial features and body shape data with the latest fashion trend database (for example, trend information stored in MongoDB), and then selects the best hairstyle, makeup, and fashion item for the user.

[0145] 5. The server generates and sends a proposal

[0146] Based on the matching results, the server suggests the best style for the user. The suggestions include hairstyle images, detailed makeup instructions, and combinations of fashion items. Using a generative AI model (e.g., GPT-3), fashion advice and makeup instructions are written in natural-sounding sentences.

[0147] Suggestions are sent to the user's device and displayed through a dedicated app.

[0148] 6. Provision of Services

[0149] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[0150] Similarly, for the suggested fashion items, rental services (e.g., general rental shops) are available, and a request can be sent from the user terminal. The rental shop will then process the delivery of the item.

[0151] Examples and prompts

[0152] When user A takes photos and enters data

[0153] User A takes measurements using a standard body composition scale, then takes a selfie using an iPhone app. "On the home screen, tap the 'Measure' button, and once the measurement is complete, the data is automatically transferred to the app. Then, tap the 'Camera' button to take a selfie, and press the 'Upload' button to send the data to the server."

[0154] Example prompts for generative AI models

[0155] "User A is a 32-year-old woman who wants to improve her appearance. Please suggest the best summer fashion and makeup for her based on her body composition measurement data and selfies."

[0156] This allows users to easily enjoy styles that incorporate the latest trends.

[0157] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0158] Step 1:

[0159] The user enters data

[0160] Input: Data such as weight and body fat percentage measured by the user using a dedicated smart body composition scale (e.g., a general body composition scale), and a selfie image.

[0161] Specific operation: The user uses a body composition scale to measure their weight and body fat percentage. This measurement data is automatically sent to a smartphone (e.g., iPhone) via Bluetooth. The user then takes a selfie using the smartphone's camera and uploads it to the app. Specifically, the user taps the "Measure" button on the home screen, and once the measurement is complete, the data is transferred to the app. Next, the user taps the "Camera" button to take a selfie, and then presses the "Upload" button to prepare for data transmission.

[0162] Output: Body composition measurement data and selfie images are saved on the user's device.

[0163] Step 2:

[0164] The device sends the data to the server

[0165] Input: Body composition measurement data and selfie images stored on the user's device.

[0166] What it does: Your device sends the stored data to the server over Wi-Fi or mobile data using an encrypted communication protocol (e.g., HTTPS). Specifically, when you tap the "Send Data" button, the data is sent to the server via HTTPS.

[0167] Output: Body composition measurement data and selfie image sent to the server.

[0168] Step 3:

[0169] The server analyzes the data

[0170] Input: Body composition measurement data and selfie image sent to the server.

[0171] How it works: The server analyzes the selfie image using a facial recognition library (e.g., OpenCV). It performs face mapping and extracts features such as the user's facial shape, skin color, and the position of the eyes and nose. In parallel, it applies a machine learning model (e.g., a model using TensorFlow) to the body composition measurement data to analyze the user's body shape, body fat percentage, and muscle mass. This includes applying a face detection algorithm and classifying and regressing the body composition data.

[0172] Output: The user's facial feature data and body shape data.

[0173] Step 4:

[0174] The server checks against the trend database

[0175] Input: User's facial feature data, body shape data, and a database of the latest fashion trends (e.g., trend information stored in MongoDB).

[0176] What it does: The server uses an algorithm to match the information in the trends database with the user's facial features and body data. Specifically, it pulls images of models and fashion items with similar face shapes and body types from the database. This includes image recognition algorithms and calculating a relevance score.

[0177] Output: A list of suggested fashion, hairstyle, and makeup looks that suit the user.

[0178] Step 5:

[0179] The server generates and sends the proposal

[0180] Input: A list of suggested fashion, hairstyle, and makeup looks for the user.

[0181] Specific operation: The server uses a generative AI model (e.g., GPT-3) to generate natural-sounding text about fashion advice and makeup techniques. Using this information, it generates a report proposing the optimal style for the user. This report includes an image of the hairstyle, detailed makeup steps, and a combination of fashion items. The report is then sent to the user's device using the HTTPS protocol. Specifically, it executes the "suggestion generation" function and sends the generated report to the user.

[0182] Output: The proposal report is sent to the user's device and displayed through the app.

[0183] Step 6:

[0184] Hair salon and rental services will be provided.

[0185] Input: Proposal report sent to user, user location information.

[0186] Specific operation: If the user uses a service based on the suggestions, the system will provide recommended hair salon information and display a reservation link. Furthermore, the suggested fashion items are available for rental services (e.g., general rental shops), and the user can send a request from their device. The rental shop will then process the delivery of the items upon receiving the request. Specifically, the user taps the "Send Request" button on the rental service, and the request is sent via the server.

[0187] Output: The user's device will be notified of the completion of the hair salon reservation and the scheduled delivery of the rental items.

[0188] (Application example 1)

[0189] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0190] It is difficult for users to easily find the fashion, hairstyle, and makeup that best suits them. Especially in physical stores, it takes time and effort for users to instantly check, try on, and apply styling that suits them. It is also uncertain whether the styling provided is based on the latest trends. Furthermore, an efficient system is needed to improve the user experience through real-time service provision in physical stores.

[0191] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0192] In this invention, the server includes: means for a user to input a selfie image and body composition measurement data at a physical store; means for transmitting the selfie image and body composition measurement data to the server in real time; means for the server to perform face mapping of the selfie image and analyze the user's physical characteristics based on the body composition measurement data; means for transmitting and displaying the suggestions on a display device in the physical store; means for the server to provide information on recommended beauty salons based on the user's location information; and means for the user to try on the suggested fashion items on the spot and purchase or rent them. This allows the user to receive suggestions for optimal fashion, hairstyles, and makeup based on the latest trends in real time at the physical store, and to try them on and receive treatments on the spot.

[0193] "User" refers to an individual who receives fashion, hairstyle, and makeup suggestions.

[0194] A "selfie" is an image that a user takes of themselves with a camera.

[0195] "Body composition measurement data" refers to data measuring the user's physical characteristics such as weight, body fat percentage, and muscle mass.

[0196] "Brick and mortar store" refers to a retail store that users can physically visit and that provides fashion and beauty-related services.

[0197] "Server" refers to a central processing unit that receives data sent by users, analyzes it, and returns the results.

[0198] "Face mapping" is a technology that analyzes the shape and features of a user's face from an image of their face.

[0199] A "fashion trend database" is a database that stores information on the latest trends in fashion, hairstyles, makeup, and more.

[0200] "Suggestion" refers to the server analyzing the user's data and presenting the most suitable fashion, hairstyle, and makeup.

[0201] "Display device" refers to equipment used to visually communicate the content of proposals to users, including tablets and smart displays.

[0202] "Location information" refers to information about the user's current location, and is data obtained via GPS or Wi-Fi.

[0203] "Beauty salon information" refers to information such as the location of the beauty salon, the services offered, and opening hours.

[0204] "Trying on" refers to the act of a user actually trying on a suggested fashion item.

[0205] "Purchase" refers to the act of a user paying a fee to own a suggested fashion item.

[0206] "Rental" is a service that allows users to borrow fashion items for a certain period of time.

[0207] This system allows users to input selfie photos and body composition measurement data in a physical store, and then suggests optimal fashion, hairstyles, and makeup. This system is comprised of a user terminal, a server, various devices installed in the physical store, and related components.

[0208] User Input

[0209] Users use a smart body composition scale in a physical store to measure their weight, body fat percentage, and other data. The measurement data is sent to a device in the store via Bluetooth or Wi-Fi. Next, the user takes a selfie using a dedicated camera installed in the store.

[0210] Data transmission and analysis

[0211] The in-store device transmits the captured selfie image and body composition measurement data in real time to a server equipped with a high-performance processing unit and AI algorithms (e.g., Python, TensorFlow, OpenCV).

[0212] Data analysis process

[0213] The server first analyzes the selfie image using face mapping technology to extract the user's facial shape and features. Next, it analyzes the user's physical characteristics (body type, body fat percentage, muscle mass, etc.) based on body composition measurement data. The results of this analysis are then compared with the latest fashion trend database (e.g., SQL database).

[0214] Generate and view suggestions

[0215] Based on the analysis results and trend data, the server will suggest the most suitable fashion items, hairstyles, and makeup for the user. The suggestions are sent to a display device (e.g., tablet or smart display) in the store, where the user can view them.

[0216] Proposal implementation and support

[0217] Users can try on suggested fashion items in a physical store and purchase or rent them on the spot. For suggested hairstyles and makeup, the server will provide location-based recommendations for hair salons and display reservation links.

[0218] Specific examples

[0219] User A (30 years old, female):

[0220] Visit a physical store and measure your weight and body fat percentage using a smart body composition scale.

[0221] Take a selfie using the store's dedicated camera.

[0222] The server analyzes the data and, based on face mapping and body composition data, suggests a pastel-colored dress, natural makeup, and a long hairstyle, referencing spring fashion trends.

[0223] Suggestions are displayed on a tablet in the store, and User A tries on the suggested fashion items in a fitting room.

[0224] Purchase your favorite items and get information on recommended hair salons.

[0225] Example prompt sentence:

[0226] "Generate optimal fashion, hairstyle, and makeup suggestions based on user images and body composition data."

[0227] Hardware and Software

[0228] Hardware:

[0229] Smart Body Composition Monitor

[0230] Dedicated camera

[0231] In-store tablets and smart displays

[0232] server

[0233] software:

[0234] Data transmission module (app)

[0235] Data Analysis Program

[0236] Face mapping technology (OpenCV)

[0237] Machine learning model (TensorFlow)

[0238] Display app (React.js or Vue.js)

[0239] This configuration allows users to receive the latest styling suggestions in real time at a physical store, and easily try on and purchase items.

[0240] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0241] Step 1:

[0242] The user visits a physical store and steps onto the smart body composition scale. The scale collects body composition measurement data, such as the user's weight, body fat percentage, and muscle mass. This data is sent to a terminal in the store via Bluetooth or Wi-Fi. The input is the body composition measurement data, and the output is the body composition measurement data sent to the terminal.

[0243] Step 2:

[0244] Users take selfies using a dedicated camera installed in the store. The captured image is saved on a terminal in the store. The input is the selfie image taken by the camera, and the output is the selfie image saved on the terminal.

[0245] Step 3:

[0246] The store terminal transmits the captured selfie image and body composition measurement data to the server in real time. The input is the selfie image and body composition measurement data, and the output is both data transmitted to the server. The terminal does this using a data transmission module.

[0247] Step 4:

[0248] When the server receives the selfie image, it uses face mapping technology (OpenCV) to analyze the shape and features of the user's face. The input is the selfie image, and the output is facial shape and feature data. The server identifies the boundary of the face and detects the positions of the eyes, nose, mouth, etc.

[0249] Step 5:

[0250] Next, the server analyzes the user's physical characteristics based on the body composition measurement data. The input is the body composition measurement data, and the output is detailed physical characteristic data such as body type, body fat percentage, and muscle mass. The server analyzes weight, body fat percentage, and muscle mass to create a body type profile for the user.

[0251] Step 6:

[0252] The server compares the analyzed facial feature data and physical characteristic data with the latest fashion trend database (SQL database). The input is facial feature data and physical characteristic data, and the output is suggested data based on the most suitable fashion trends. The server compares each data point with the trend information for each item and generates the optimal styling.

[0253] Step 7:

[0254] The server sends the generated proposals to a display device (tablet or smart display) in the store. The input is the proposal data, and the output is the proposal content displayed on the display device. The server sends the proposal content in JSON format, which the display device receives and displays visually.

[0255] Step 8:

[0256] The user reviews the displayed suggestions and tries on the suggested fashion items. The input is the suggestions and the items tried on, and the output is the user's feedback. The user tries on the items in the fitting room to check the fit and style.

[0257] Step 9:

[0258] If the user purchases or rents the suggested item, the server provides recommended salon information based on the user's location. The input is the user's location and the suggested item, and the output is salon information. The server searches for the most suitable salon based on the user's current location and the suggested item, and provides a link to make a reservation.

[0259] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0260] This is a new invention that combines an emotion engine with a system that allows users to input selfie photos and body composition measurement data and then suggests optimal fashion, hairstyles, and makeup based on that information. The system consists of a user's device, a server, an emotion engine, and affiliated beauty salons and rental shops.

[0261] System configuration

[0262] 1. User's device: On a device such as a smartphone or PC, users take selfies, input body composition measurement data, use the function to recognize the user's emotions, and check suggested styles.

[0263] 2. Server: Receives and analyzes data, recognizes emotions using the emotion engine, compares it with trend information, and generates and sends suggestions.

[0264] 3. Emotion Engine: Analyzes selfies and recognizes the user's emotional state.

[0265] 4. Beauty salons and rental shops: Providing services and items based on requests received from the server.

[0266] Program processing

[0267] The program processing within this system will be explained in natural language below.

[0268] 1. User enters data

[0269] Users use a dedicated smart body composition scale to measure their weight, body fat percentage, etc. The measurement data is sent to the user's device.

[0270] Next, the user takes a selfie with their device's camera and uploads it to the app.

[0271] 2. The device sends the data to the server

[0272] The device transmits the acquired selfie image, body composition measurement data, location information, and emotion data extracted by the emotion engine to the server.

[0273] 3. The server analyzes the data

[0274] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color.

[0275] At the same time, body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc.

[0276] 4. Emotion engine recognizes emotions

[0277] The server uses an emotion engine to recognize the user's emotions from the selfie image, using technology to determine emotions such as happiness, sadness, and surprise from the user's facial expressions.

[0278] 5. The server checks the data against the trend database.

[0279] The server compares the user's facial features, body type, and emotional data with the latest fashion trend database, and then selects the hairstyle, makeup, and fashion items that are best suited to the user.

[0280] 6. The server generates and sends a proposal

[0281] Based on the matching results, the server will suggest the best style for the user, including images of hairstyles, makeup routines, and photos and combinations of fashion items.

[0282] Based on emotional data, the suggested styles are adjusted to adapt to the user's current mental state.

[0283] Suggestions are sent to the user's device and displayed through the app.

[0284] 7. Providing beauty salon and rental services

[0285] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[0286] Similarly, the suggested fashion items are available for rental service, and users can send a request from their device. The rental shop will then process the delivery of the items.

[0287] Specific examples

[0288] User C (28 years old, female)

[0289] The user measures her weight and body fat percentage using a dedicated body composition scale, and uploads a selfie with her smartphone. The emotion engine detects the emotion of joy from her facial expression.

[0290] The server analyzes this data and matches the latest spring fashion trends based on User C's face shape and body type.

[0291] A light-colored dress, a casual jacket, and natural makeup are suggested, creating a style that brings out her joyful emotions.

[0292] The server recommends reputable local hair salons and stylists and provides booking links.

[0293] The suggested fashion items will be delivered to your home the next day using a rental service.

[0294] User D (35 years old, male)

[0295] The smart body composition scale measures his weight and body fat percentage, and he uploads a selfie with his smartphone. The emotion engine detects his fatigue and stress from his facial expressions.

[0296] The server analyzes the data and matches the latest fall fashion trends based on User D's face shape and body type.

[0297] A dark suit, a muted tie, and a simple hairstyle are recommended, all of which will help him look less tired.

[0298] In addition, it also provides information on nearby stores suitable for relaxation services and refreshing.

[0299] The suggested fashion items will be delivered to your home the next day using a rental service.

[0300] This allows users to easily find the perfect style that suits their emotional state and receive services at a beauty salon. Users can also rent suggested fashion items.

[0301] The processing flow will be explained below.

[0302] Step 1:

[0303] The user steps onto the dedicated smart body composition scale and obtains body composition measurement data such as weight, body fat percentage, muscle mass, etc. This data is automatically sent to the user's device.

[0304] Step 2:

[0305] The user launches a dedicated app and takes a selfie with their smartphone camera, which is then uploaded to the app.

[0306] Step 3:

[0307] The device sends the selfie image and body composition measurement data it has acquired to a server. The data is sent using a secure communication protocol, so it arrives safely at the server.

[0308] Step 4:

[0309] The server inputs the received selfie into an AI analysis algorithm to perform face mapping, which extracts features such as the user's facial shape, skin color, and hair texture.

[0310] Step 5:

[0311] The server analyzes the body composition measurement data and determines the user's physical characteristics such as height, weight, body fat percentage, and muscle mass.

[0312] Step 6:

[0313] The server inputs the selfie image into the emotion engine to recognize the user's emotions. The emotion engine determines the user's emotional state, such as joy, sadness, surprise, or anger, from their facial expressions.

[0314] Step 7:

[0315] The server compares the analysis results and emotional data with the latest fashion trend database, which includes information on the latest hairstyles, makeup, and fashion items.

[0316] Step 8:

[0317] The server selects the hairstyle, makeup, and fashion items that are best suited to the user and generates recommendations. Based on the emotional data, the server adjusts the recommendations to suit the user's specific emotional state.

[0318] Step 9:

[0319] The server generates and sends the recommendation information to the device, which includes images of specific hairstyles, makeup steps, and photos of fashion items and combinations.

[0320] Step 10:

[0321] The device displays the received recommendation information to the user, who can then check the suggested styles via the app and select the most appropriate suggestion based on their emotional state.

[0322] Step 11:

[0323] The server provides recommended hair salon information based on the user's location, and if the user wishes, a link to make a reservation at the appropriate salon is also provided.

[0324] Step 12:

[0325] If the user likes the suggested fashion item, they can send a rental request through the app.

[0326] Step 13:

[0327] The server receives the rental request and sends a request for the specified item to the affiliated rental shop.

[0328] Step 14:

[0329] The rental shop will confirm the request and prepare to deliver the specified fashion item to the user's address.

[0330] Step 15:

[0331] The user receives the rented fashion item and uses it for the specified period. After use, the rental item is returned.

[0332] By following these steps, users can easily find the style that best suits them and receive services at a beauty salon. They can also rent the suggested fashion items. The introduction of an emotion engine makes it possible to provide detailed suggestions based on the user's emotional state.

[0333] Example 2

[0334] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0335] Conventional fashion suggestion systems primarily make suggestions based on the user's physical characteristics and facial shape, without taking into account the user's emotional state. This can result in suggested styles that do not match the user's psychological state, resulting in reduced user satisfaction. Furthermore, when users wish to use specific services or products based on the suggestions, they must individually search for information and make reservations, which is inconvenient.

[0336] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0337] In this invention, the server includes means for face mapping a selfie image, analyzing physical characteristics based on body composition measurement data, and recognizing an emotional state using an emotion engine, means for comparing the analysis results and the emotional state with the latest fashion trend database to suggest optimal fashion, hairstyle, and makeup, and means for transmitting and displaying the suggestions to the user's terminal. This makes it possible to suggest styles that are adapted to the user's psychological state, and furthermore, by linking with information on beauty salons and fashion item rental services, it is possible to provide users with advanced and personalized services.

[0338] A "user" is a person who uses the system to input a selfie and body composition data and receive style suggestions.

[0339] A "selfie" is a photograph of the face or upper body taken by the user, and is data used for face mapping and emotion recognition.

[0340] "Body composition measurement data" refers to data relating to the user's body composition, such as weight, body fat percentage, and muscle mass, and is data used to analyze physical characteristics.

[0341] "Transmission means" refers to the function for transferring the selfie image, body composition measurement data, and emotion data to the server.

[0342] "Analysis means" refers to the algorithms and modules that process selfie images and body composition measurement data within the server and identify the user's facial shape and physical characteristics.

[0343] "Emotion engine" refers to the technology and algorithms used to extract and analyze a user's emotions from selfie images.

[0344] "Matching means" refers to an information processing function that matches the analysis results and emotional state with a fashion trend database and selects the most suitable fashion, hairstyle, and makeup for the user.

[0345] "Suggestion means" refers to a function for transmitting and displaying the fashion, hairstyle, and makeup suggestions generated by the server to the user's terminal.

[0346] "Location information" refers to information about a geographical location obtained from a user's device, and is data used to provide beauty salon information.

[0347] "Beauty salon information" is information about facilities that offer specific beauty services suggested based on the user's location information.

[0348] A "rental request" is a request submitted by a user to temporarily borrow a suggested fashion item.

[0349] "Rental Items" are fashion items that users can temporarily borrow through rental requests.

[0350] This system allows users to input selfie images, body composition measurement data, and emotion data extracted from the images, and then suggests optimal fashion, hairstyle, and makeup based on that information. The system consists of a user terminal, a server, an emotion engine, and affiliated beauty salons and rental shops.

[0351] User terminal

[0352] Using a device such as a smartphone or PC, the user takes a selfie, inputs body composition measurement data, executes a function that recognizes the user's emotions, and checks the suggested style. The user uses a smart body composition scale to measure data such as weight and body fat percentage. This measurement data is sent to the user's smartphone via Bluetooth. The user then takes a selfie using the smartphone camera and uploads it to a specific app.

[0353] server

[0354] The server stores the received selfie image, body composition measurement data, and emotion data in a connected database. Analysis of the received data is also performed on the server. Specifically, the server uses an image processing algorithm to perform face mapping and extract features such as the user's facial shape and skin color. At the same time, it analyzes the body composition measurement data to determine the user's body type, body fat percentage, and muscle mass.

[0355] The server then uses an emotion engine to recognize the user's emotions from the selfie. This emotion engine is a technology that determines emotions such as joy, sadness, and surprise from the user's facial expressions. The server then compares the analysis results and emotional state with the latest fashion trend database to suggest hairstyles, makeup, and fashion items that are best suited to the user. Suggestions include images of hairstyles, makeup steps, and photos and combinations of fashion items. Based on the emotion data, the suggested styles are adjusted to adapt to the user's current mental state. Suggestions are sent to the user's device and displayed through the app.

[0356] Hair salons and rental shops

[0357] If the user wishes to use the service based on the suggestions, the server provides information on recommended beauty salons and displays a reservation link. Furthermore, the suggested fashion items are available for rental, and a request can be sent from the user's device. The rental shop then processes the delivery of the items upon receiving the request.

[0358] Specific examples

[0359] User C (28 years old, female)

[0360] The user measures their weight and body fat percentage with a dedicated body composition scale, takes a selfie with their smartphone, and uploads it to the app. The emotion engine detects the emotion of joy from their facial expression.

[0361] The server analyzes this data and matches it with the latest spring fashion trends based on User C's face shape and body type.

[0362] We suggest a light-colored dress, a casual jacket, and natural makeup, which will bring out her joyful emotions.

[0363] The server recommends reputable local hair salons and stylists and provides booking links.

[0364] The suggested fashion items will be delivered to your home the next day using a rental service.

[0365] User D (35 years old, male)

[0366] The smart body composition scale measures his weight and body fat percentage, and he takes a selfie with his smartphone and uploads it. The emotion engine detects emotions such as fatigue and stress from his facial expressions.

[0367] The server analyzes the data and matches it with the latest fall fashion trends based on User D's face shape and body type.

[0368] A dark suit, a muted tie, and a simple hairstyle are recommended, which will help him look less tired.

[0369] In addition, it also provides information on nearby stores suitable for relaxation services and refreshing.

[0370] The suggested fashion items will be delivered to your home the next day using a rental service.

[0371] Prompt Sentence Examples

[0372] "A 28-year-old female user measured her weight and body fat percentage using a dedicated body composition scale and uploaded a selfie with her smartphone. The emotion engine detected the emotion of joy from her facial expression. Based on this user's face shape and body type, please match the latest spring fashion trends and suggest a bright-colored dress and natural makeup."

[0373] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0374] Step 1: User takes a selfie and enters body composition measurement data

[0375] The user uses a dedicated smart body composition scale to measure data such as weight and body fat percentage. This measurement data is sent to the user's smartphone via Bluetooth. The user then takes a selfie using the smartphone camera and uploads it to a dedicated app. This provides the selfie image and body composition measurement data as input data.

[0376] Step 2: The device sends the data to the server

[0377] The device sends the captured selfie image, body composition measurement data, location information, and emotion data extracted by the emotion engine to the server. Specifically, all data collected by the smartphone application (images, measurement data, location information, emotion data) is securely sent to the server using the HTTPS protocol. This sends the input data to the server.

[0378] Step 3: The server parses the data

[0379] The server performs face mapping based on the received selfie image, extracting features such as the user's facial shape, skin color, and contours. A facial recognition module is used for this analysis. At the same time, body composition measurement data is analyzed to determine the user's body type, body fat percentage, and muscle mass. Specifically, the face mapping algorithm analyzes the selfie image and identifies facial feature points (such as the position of the eyes, nose, and mouth), and the body composition data analysis module calculates the user's physical characteristics based on the measurement data. This outputs facial shape data and physical characteristic data.

[0380] Step 4: The emotion engine recognizes the emotion

[0381] The server recognizes the user's emotions from the selfie image through the emotion engine. The emotion engine analyzes the user's facial expressions from the image and determines emotions such as joy, sadness, and surprise. Specifically, the emotion engine analyzes the subtle movements of the face to evaluate the user's emotional state, which then outputs the user's emotional data.

[0382] Step 5: The server checks against the trend database

[0383] The server compares the user's facial features, body type data, and emotional data with the latest fashion trend database. This allows the system to select the hairstyle, makeup, and fashion items that are best suited to the user. Specifically, the server executes a database query to search the latest fashion trend information and identify the most suitable style. This results in the output of optimized fashion suggestion data.

[0384] Step 6: Server generates and sends proposal

[0385] Based on the matching results, the server suggests the optimal style for the user. The suggestions include images of hairstyles, makeup routines, and photos and combinations of fashion items. Based on emotional data, the suggested style is adjusted to suit the user's current mental state. Specifically, the server encodes the suggested data in JSON format and sends it to the smartphone app via push notification. The suggested data is then displayed on the user's device.

[0386] Step 7: Provide beauty salon and rental services

[0387] If the user wishes to use a service based on the suggestions, the server provides information about recommended beauty salons and displays a reservation link. Furthermore, rental services are available for the suggested fashion items, and a request can be sent from the user's device. The rental shop receives the request and arranges for delivery of the items. Specifically, the server analyzes reputation data for nearby beauty salons, selects the most suitable salon, and displays it to the user. The rental request is also linked to the rental shop's system, which checks inventory and initiates delivery procedures. This allows users to easily use the appropriate beauty services and fashion items.

[0388] (Application example 2)

[0389] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0390] In today's world, selecting the best fashion, hairstyle, and makeup for each individual user can be difficult given the wide variety of options and trend information available. While it is important to provide style suggestions that take into account each user's emotional state and physical characteristics, systems that can effectively reflect these are still lacking. Furthermore, there is a need for a simple way to actually apply the suggested styles (by making a salon appointment or renting fashion items).

[0391] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for comparing the analysis results and the emotion data recognized by the emotion engine with the latest fashion trend database and suggesting optimal fashion, hairstyle, and makeup for the user, means for virtually displaying the suggested styles on the user's terminal in real time, and means for transmitting and displaying the suggestions on the user's terminal. This enables the system to suggest optimal styles based on the user's emotional state and physical characteristics and to enable the user to virtually try on those styles.

[0392] A "user terminal" is an electronic device used by a user to operate the device, such as a smartphone or a personal computer.

[0393] A "server" is a computer system that receives data, analyzes it, recognizes emotions, generates suggestions, and transmits the information to the user's device.

[0394] A "selfie" refers to a photograph of the user's face taken by the user themselves, and is used to analyze facial features.

[0395] "Body composition measurement data" is measurement data that indicates the user's physical characteristics such as weight and body fat percentage.

[0396] "Face mapping" is a technology that analyzes the shape and features of a user's face based on a selfie image.

[0397] The "Emotion Engine" is a technology that analyzes and recognizes a user's emotional state from selfie images.

[0398] The "Fashion Trend Database" is a database that stores information on the latest fashions, hairstyles, and makeup.

[0399] "Virtual display means" refers to a technology that allows users to virtually visualize styles that they have not actually tried and check them on their device.

[0400] "Location Information" is data that indicates a user's current geographic location.

[0401] "Beauty salon information" is information about a beauty salon, including the salon name, location, reservation status, and the like.

[0402] "Fashion items" are fashion-related products such as clothing and accessories.

[0403] "Rental" refers to a service in which users temporarily borrow fashion items to use for a certain period of time.

[0404] This system uses a user's selfie photos and body composition measurement data to suggest optimal fashion, hairstyles, and makeup, and combines it with an emotion engine. The system consists of a user's device, a server, an emotion engine, and affiliated beauty salons and rental shops.

[0405] System configuration

[0406] 1. User Device

[0407] Input method: Users take selfies and input body composition measurement data using devices such as smartphones and PCs. Specific devices include iPhones, Android smartphones, and Windows PCs.

[0408] Virtual display means: The system has the function of visualizing the proposed style in real time on the device, allowing users to virtually try out the style.

[0409] 2. Server

[0410] Analysis method: The server performs face mapping based on the uploaded selfie image and analyzes the user's facial shape and features. It also analyzes physical characteristics based on body composition measurement data. The server processes data using cloud services such as Google Cloud Platform and AWS.

[0411] Emotion Recognition: Recognize the user's emotional state from selfies through an emotion engine, built using machine learning libraries such as TensorFlow.

[0412] Matching: The analysis results and sentiment data are matched with the latest fashion trend database to suggest the most suitable fashion, hairstyle, and makeup for the user. The trend database collects the latest industry information and is updated regularly.

[0413] 3. Affiliated hair salons and rental shops

[0414] Information provision: Based on the user's location, the service provides recommended hair salons. Hair salons are registered in a database in advance and selected based on ratings and user feedback.

[0415] Rental service: Users can submit rental requests for suggested fashion items, which are then sent to affiliated rental shops, which then process the delivery of the items.

[0416] Specific examples

[0417] User C (28 years old, female):

[0418] She measures her weight and body fat percentage with a dedicated body composition scale and uploads a selfie with her smartphone. The emotion engine detects the emotion of joy from her facial expression. The server analyzes this data and matches the latest spring fashion trends based on User C's face shape and body type. It suggests a bright-colored dress, a casual jacket, and natural makeup. This selects a style that will bring out her emotion of joy. The server then provides information on reputable local hair salons and displays a link to make a reservation. The suggested fashion items are delivered to her home the next day using a rental service.

[0419] User D (35 years old, male):

[0420] The user measures his weight and body fat percentage with a smart body composition scale and uploads a selfie image on his smartphone. The emotion engine detects feelings of fatigue and stress from his facial expressions. The server analyzes the data and matches the latest autumn fashion trends based on User D's facial shape and body type. It suggests a dark-colored suit, a tie in a muted tone, and a simple hairstyle. This selects a style that will relieve his fatigue. It also provides information on nearby stores suitable for relaxation services and refreshing. The suggested fashion items are delivered to his home the next day using a rental service.

[0421] Prompt Sentence Examples

[0422] "We analyzed User A's selfies and identified her happy emotions. Based on the latest spring fashion trends, we suggest the following style. A casual navy cardigan and denim combination with a striped shirt would look good on her."

[0423] This allows users to easily find the style that best suits their emotional state and physical characteristics, and also makes it easier to use services at beauty salons and rent fashion items.

[0424] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0425] Step 1:

[0426] Users take a selfie using a device such as a smartphone or PC, and a dedicated smart body composition scale acquires body composition measurement data such as weight and body fat percentage. The user's device receives this data and uploads the selfie and body composition measurement data to the app. The input data is the selfie and body composition measurement data, and the output is the uploaded user data.

[0427] Step 2:

[0428] The user device sends the uploaded selfie image and body composition measurement data to the server using a secure communication protocol (e.g., HTTPS). The input data are the selfie image and body composition measurement data obtained in the previous step, and the output is the data transferred to the server.

[0429] Step 3:

[0430] The server performs face mapping based on the received selfie image. This face mapping uses image processing libraries such as OpenCV to analyze the shape and features of the face. The input data is the selfie image, and the output is data that shows the shape and features of the user's face.

[0431] Step 4:

[0432] The server analyzes the body composition measurement data and identifies the user's physical characteristics (body type, body fat percentage, muscle mass, etc.). Data science tools (e.g., Pandas, NumPy) are used for the analysis. The input data is the body composition measurement data, and the output is the analyzed physical characteristic data.

[0433] Step 5:

[0434] The server uses an emotion engine to recognize the user's emotional state from the selfie image. It uses deep learning libraries such as TensorFlow to run emotion recognition models and identify emotions such as joy, sadness, and surprise. The input data is the selfie image, and the output is the recognized emotion data.

[0435] Step 6:

[0436] The server compares the user's facial features, physical characteristics, and emotional data with the latest fashion trend database. The fashion trend database is managed on the cloud and updated with the latest industry information. The input data is face mapping data, physical characteristics data, and emotional data, and the output is data suggesting the most suitable fashion, hairstyle, and makeup for the user.

[0437] Step 7:

[0438] The server sends the generated proposal to the user's device, which then virtually displays the proposed style in real time, allowing the user to virtually try out the proposed style. The input data is the proposal data, and the output is the virtual style displayed on the user's device.

[0439] Step 8:

[0440] If the user accepts the proposed style, the user device sends a request to the affiliated hair salon or rental shop. The input data is the user's request, and the output is the salon reservation information and the delivery procedure for the rental items.

[0441] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0442] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0443] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0444] [Second embodiment]

[0445] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0446] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0447] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0448] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0449] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0450] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0451] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0452] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0453] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0454] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0455] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0456] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0457] This system allows users to input their selfie photos and body composition measurement data, and based on that information, it suggests optimal fashion, hairstyles, and makeup. The system consists of a user's device, a server, and affiliated beauty salons and rental shops.

[0458] System configuration

[0459] 1. User's device: On a device such as a smartphone or computer, users take a selfie, enter body composition measurement data, and check suggested styles.

[0460] 2. Server: Receives data, analyzes it, compares it with trend information, and generates and sends recommendations.

[0461] 3. Beauty salons and rental shops: Providing services and items based on requests received from the server.

[0462] Program processing

[0463] The program processing within this system will be explained in natural language below.

[0464] 1. User enters data

[0465] Users use a dedicated smart body composition scale to measure their weight, body fat percentage, etc. The measurement data is sent to the user's device.

[0466] Next, the user takes a selfie using the device's camera and uploads it to the app.

[0467] 2. The device sends the data to the server

[0468] The device sends the captured selfie image and body composition measurement data to the server.

[0469] 3. The server analyzes the data

[0470] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color.

[0471] At the same time, body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc.

[0472] 4. The server checks the data against the trend database.

[0473] The server compares facial features and body type data with the latest fashion trend database, and then selects hairstyles, makeup, and fashion items that are best suited to the user.

[0474] 5. The server generates and sends a proposal

[0475] Based on the results of the comparison, the server will suggest the best style for the user, including an image of the hairstyle, detailed makeup instructions, and a combination of fashion items.

[0476] Suggestions are sent to the user's device and displayed through the app.

[0477] 6. Providing beauty salon and rental services

[0478] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[0479] Similarly, for the suggested fashion items, rental services are available, and users can send requests from their devices. The rental shop will then process the delivery of the items.

[0480] Specific examples

[0481] User A (32 years old, female)

[0482] Measure your weight and body fat percentage using a dedicated body composition scale, and upload a selfie photo using your smartphone.

[0483] The server analyzes this data and matches the latest summer fashion trends based on User A's face shape and body type.

[0484] We suggest a lightweight jacket in cool colors, shorts, and natural makeup.

[0485] The server recommends reputable local hair salons and stylists and provides booking links.

[0486] The suggested fashion items will be delivered to your home the next day using a rental service.

[0487] User B (45 years old, male)

[0488] Measure your weight and body fat percentage with a smart body composition scale and upload a selfie using your smartphone.

[0489] The server analyzes the data and matches it with the latest autumn fashion trends based on the sharp features of User B's jawline.

[0490] We suggest a dark green jacket, gray pants, and loafers.

[0491] The server recommends the best two-block hairstyle and provides information on nearby hair salons and a link to make a reservation.

[0492] The suggested fashion items will be delivered to your home the next day using a rental service.

[0493] This allows users to easily enjoy styles that incorporate the latest trends.

[0494] The processing flow will be explained below.

[0495] Step 1:

[0496] The user steps onto the dedicated smart body composition scale and obtains body composition measurement data such as weight, body fat percentage, muscle mass, etc. This data is automatically sent to the user's device.

[0497] Step 2:

[0498] The user launches a dedicated app and takes a selfie with their smartphone camera, which is then uploaded to the app.

[0499] Step 3:

[0500] The device sends the selfie image and body composition measurement data it has acquired to a server. The data is sent using a secure communication protocol, so it arrives safely at the server.

[0501] Step 4:

[0502] The server inputs the received selfie into an AI analysis algorithm to perform face mapping, which extracts features such as the user's facial shape, skin color, and hair texture.

[0503] Step 5:

[0504] The server analyzes the body composition measurement data and determines the user's physical characteristics such as height, weight, body fat percentage, and muscle mass.

[0505] Step 6:

[0506] The server compares the analysis results with a database of current fashion trends, which includes information on the latest hairstyles, makeup, and fashion items.

[0507] Step 7:

[0508] The server selects the hairstyle, makeup, and fashion items that are best suited to the user and generates them as recommendation information.

[0509] Step 8:

[0510] The server generates and sends the recommendation information to the device, which includes images of specific hairstyles, makeup steps, and photos of fashion items and combinations.

[0511] Step 9:

[0512] The device displays the received recommendation information to the user, who can then check the suggested styles via the app.

[0513] Step 10:

[0514] The server provides recommended hair salon information based on the user's location, and if the user wishes, a link to make a reservation at the appropriate salon is also provided.

[0515] Step 11:

[0516] If the user likes the suggested fashion item, they can send a rental request through the app.

[0517] Step 12:

[0518] The server receives the rental request and sends a request for the specified item to the affiliated rental shop.

[0519] Step 13:

[0520] The rental shop will confirm the request and prepare to deliver the specified fashion item to the user's address.

[0521] Step 14:

[0522] The user receives the rented fashion item and uses it for the specified period. After use, the rental item is returned.

[0523] By following these steps, users can easily find the style that best suits them and receive services at a beauty salon. They can also rent suggested fashion items.

[0524] Example 1

[0525] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0526] Conventional systems have had difficulty fully reflecting individual physical characteristics and the latest fashion trends when proposing fashion, hairstyles, and makeup that are suited to a user's appearance. Furthermore, the content of the proposals was limited to static information, and the provision of specific advice and recommendations that were highly practical for users was insufficient. This led to a problem of lower user satisfaction with improvements to their style.

[0527] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0528] In this invention, the server includes means for face mapping a selfie image and analyzing the user's physical characteristics based on body composition measurement data, means for comparing the results with a trend database to suggest optimal fashion, hairstyle, and makeup for the user, and means for automatically generating details of the suggestions using a generative AI model and providing them to the user. This makes it possible to suggest specific styles that reflect individual physical characteristics and the latest trends, as well as provide highly practical, detailed advice.

[0529] A "selfie" refers to an image of a user's face or body taken by the user themselves.

[0530] "Body composition measurement data" refers to data regarding the user's physical composition, such as weight, body fat percentage, and muscle mass.

[0531] "Server" refers to the computer system responsible for analyzing the data it receives, collating it, generating suggestions, and sending them to the user.

[0532] "Face mapping" refers to the process of using image analysis technology to extract facial shapes and features from selfies.

[0533] "Physical characteristics" refers to a user's physical characteristics such as body shape, skin color, and body fat percentage.

[0534] A "trend database" refers to a database that stores information about the latest fashions, hairstyles, and makeup.

[0535] "Fashion" refers to the style of clothing, accessories, etc.

[0536] "Hairstyle" refers to the design or style of a hairstyle.

[0537] "Makeup" refers to the method and style of applying makeup.

[0538] A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to analyze text, images, and data.

[0539] "Suggestions" refers to specific advice and information about fashion, hairstyles, and makeup provided to users.

[0540] "User's device" refers to a device such as a smartphone or computer used by the user.

[0541] "Location Information" means information that indicates a User's current geographic location.

[0542] "Hair Salon Information" refers to data and booking links about hair salons recommended to users.

[0543] "Rental items" refer to fashion items that users can borrow temporarily.

[0544] This invention is a system that allows users to input selfie photos and body composition measurement data, and based on that information, suggests optimal fashion, hairstyles, and makeup. The system is composed of a user's terminal, a server, and affiliated service providers.

[0545] System configuration

[0546] 1. User's Device

[0547] The user's device is a device such as a smartphone or PC. The user uses these devices to take selfies, input body composition measurement data, and check the suggested style. Specific examples include iPhones and Android devices.

[0548] 2. Server

[0549] The server receives and analyzes the data, compares it with trend information, and generates and sends proposals. A specific example is an EC2 instance on AWS, which uses cloud services. The server analyzes the data using OpenCV, a facial recognition library, and TensorFlow, a machine learning framework, and automatically generates details of the proposals using a generative AI model (e.g., GPT-3).

[0550] 3. Affiliated Service Providers

[0551] The affiliated service providers are beauty salons and fashion rental shops that provide services and items to users. These service providers provide services and items based on requests received from the server.

[0552] Program processing

[0553] The program processing within this system will be explained in natural language below.

[0554] 1. The user enters data

[0555] The user uses a dedicated smart body composition scale (for example, a general body composition scale) to measure weight, body fat percentage, etc. The measurement data is sent to a device (for example, an iPhone).

[0556] Next, the user takes a selfie using the device's camera and uploads it to the app. "Tap the 'Measure' button on the home screen, and once the measurement is complete, the data will be automatically transferred to the app. Then tap the 'Camera' button to take a selfie, and press the 'Upload' button to send the data to the server."

[0557] 2. The device sends the data to the server

[0558] The device sends the selfie image and body composition measurement data captured by the user to a server via Wi-Fi or mobile data communication using an encrypted communication protocol (e.g., HTTPS).

[0559] 3. The server analyzes the data

[0560] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color. The software used here is a facial recognition library (e.g., OpenCV).

[0561] At the same time, the body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc. A machine learning model (for example, a model using TensorFlow) is used for the analysis.

[0562] 4. The server checks the data against the trend database.

[0563] The server compares the facial features and body shape data with the latest fashion trend database (for example, trend information stored in MongoDB), and then selects the best hairstyle, makeup, and fashion item for the user.

[0564] 5. The server generates and sends a proposal

[0565] Based on the matching results, the server suggests the best style for the user. The suggestions include hairstyle images, detailed makeup instructions, and combinations of fashion items. Using a generative AI model (e.g., GPT-3), fashion advice and makeup instructions are written in natural-sounding sentences.

[0566] Suggestions are sent to the user's device and displayed through a dedicated app.

[0567] 6. Provision of Services

[0568] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[0569] Similarly, for the suggested fashion items, rental services (e.g., general rental shops) are available, and a request can be sent from the user terminal. The rental shop will then process the delivery of the item.

[0570] Examples and prompts

[0571] When user A takes photos and enters data

[0572] User A takes measurements using a standard body composition scale, then takes a selfie using an iPhone app. "On the home screen, tap the 'Measure' button, and once the measurement is complete, the data is automatically transferred to the app. Then, tap the 'Camera' button to take a selfie, and press the 'Upload' button to send the data to the server."

[0573] Example prompts for generative AI models

[0574] "User A is a 32-year-old woman who wants to improve her appearance. Please suggest the best summer fashion and makeup for her based on her body composition measurement data and selfies."

[0575] This allows users to easily enjoy styles that incorporate the latest trends.

[0576] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0577] Step 1:

[0578] The user enters data

[0579] Input: Data such as weight and body fat percentage measured by the user using a dedicated smart body composition scale (e.g., a general body composition scale), and a selfie image.

[0580] Specific operation: The user uses a body composition scale to measure their weight and body fat percentage. This measurement data is automatically sent to a smartphone (e.g., iPhone) via Bluetooth. The user then takes a selfie using the smartphone's camera and uploads it to the app. Specifically, the user taps the "Measure" button on the home screen, and once the measurement is complete, the data is transferred to the app. Next, the user taps the "Camera" button to take a selfie, and then presses the "Upload" button to prepare for data transmission.

[0581] Output: Body composition measurement data and selfie images are saved on the user's device.

[0582] Step 2:

[0583] The device sends the data to the server

[0584] Input: Body composition measurement data and selfie images stored on the user's device.

[0585] What it does: Your device sends the stored data to the server over Wi-Fi or mobile data using an encrypted communication protocol (e.g., HTTPS). Specifically, when you tap the "Send Data" button, the data is sent to the server via HTTPS.

[0586] Output: Body composition measurement data and selfie image sent to the server.

[0587] Step 3:

[0588] The server analyzes the data

[0589] Input: Body composition measurement data and selfie image sent to the server.

[0590] How it works: The server analyzes the selfie image using a facial recognition library (e.g., OpenCV). It performs face mapping and extracts features such as the user's facial shape, skin color, and the position of the eyes and nose. In parallel, it applies a machine learning model (e.g., a model using TensorFlow) to the body composition measurement data to analyze the user's body shape, body fat percentage, and muscle mass. This includes applying a face detection algorithm and classifying and regressing the body composition data.

[0591] Output: The user's facial feature data and body shape data.

[0592] Step 4:

[0593] The server checks against the trend database

[0594] Input: User's facial feature data, body shape data, and a database of the latest fashion trends (e.g., trend information stored in MongoDB).

[0595] What it does: The server uses an algorithm to match the information in the trends database with the user's facial features and body data. Specifically, it pulls images of models and fashion items with similar face shapes and body types from the database. This includes image recognition algorithms and calculating a relevance score.

[0596] Output: A list of suggested fashion, hairstyle, and makeup looks that suit the user.

[0597] Step 5:

[0598] The server generates and sends the proposal

[0599] Input: A list of suggested fashion, hairstyle, and makeup looks for the user.

[0600] Specific operation: The server uses a generative AI model (e.g., GPT-3) to generate natural-sounding text about fashion advice and makeup techniques. Using this information, it generates a report proposing the optimal style for the user. This report includes an image of the hairstyle, detailed makeup steps, and a combination of fashion items. The report is then sent to the user's device using the HTTPS protocol. Specifically, it executes the "suggestion generation" function and sends the generated report to the user.

[0601] Output: The proposal report is sent to the user's device and displayed through the app.

[0602] Step 6:

[0603] Hair salon and rental services will be provided.

[0604] Input: Proposal report sent to user, user location information.

[0605] Specific operation: If the user uses a service based on the suggestions, the system will provide recommended hair salon information and display a reservation link. Furthermore, the suggested fashion items are available for rental services (e.g., general rental shops), and the user can send a request from their device. The rental shop will then process the delivery of the items upon receiving the request. Specifically, the user taps the "Send Request" button on the rental service, and the request is sent via the server.

[0606] Output: The user's device will be notified of the completion of the hair salon reservation and the scheduled delivery of the rental items.

[0607] (Application example 1)

[0608] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0609] It is difficult for users to easily find the fashion, hairstyle, and makeup that best suits them. Especially in physical stores, it takes time and effort for users to instantly check, try on, and apply styling that suits them. It is also uncertain whether the styling provided is based on the latest trends. Furthermore, an efficient system is needed to improve the user experience through real-time service provision in physical stores.

[0610] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0611] In this invention, the server includes: means for a user to input a selfie image and body composition measurement data at a physical store; means for transmitting the selfie image and body composition measurement data to the server in real time; means for the server to perform face mapping of the selfie image and analyze the user's physical characteristics based on the body composition measurement data; means for transmitting and displaying the suggestions on a display device in the physical store; means for the server to provide information on recommended beauty salons based on the user's location information; and means for the user to try on the suggested fashion items on the spot and purchase or rent them. This allows the user to receive suggestions for optimal fashion, hairstyles, and makeup based on the latest trends in real time at the physical store, and to try them on and receive treatments on the spot.

[0612] "User" refers to an individual who receives fashion, hairstyle, and makeup suggestions.

[0613] A "selfie" is an image that a user takes of themselves with a camera.

[0614] "Body composition measurement data" refers to data measuring the user's physical characteristics such as weight, body fat percentage, and muscle mass.

[0615] "Brick and mortar store" refers to a retail store that users can physically visit and that provides fashion and beauty-related services.

[0616] "Server" refers to a central processing unit that receives data sent by users, analyzes it, and returns the results.

[0617] "Face mapping" is a technology that analyzes the shape and features of a user's face from an image of their face.

[0618] A "fashion trend database" is a database that stores information on the latest trends in fashion, hairstyles, makeup, and more.

[0619] "Suggestion" refers to the server analyzing the user's data and presenting the most suitable fashion, hairstyle, and makeup.

[0620] "Display device" refers to equipment used to visually communicate the content of proposals to users, including tablets and smart displays.

[0621] "Location information" refers to information about the user's current location, and is data obtained via GPS or Wi-Fi.

[0622] "Beauty salon information" refers to information such as the location of the beauty salon, the services offered, and opening hours.

[0623] "Trying on" refers to the act of a user actually trying on a suggested fashion item.

[0624] "Purchase" refers to the act of a user paying a fee to own a suggested fashion item.

[0625] "Rental" is a service that allows users to borrow fashion items for a certain period of time.

[0626] This system allows users to input selfie photos and body composition measurement data in a physical store, and then suggests optimal fashion, hairstyles, and makeup. This system is comprised of a user terminal, a server, various devices installed in the physical store, and related components.

[0627] User Input

[0628] Users use a smart body composition scale in a physical store to measure their weight, body fat percentage, and other data. The measurement data is sent to a device in the store via Bluetooth or Wi-Fi. Next, the user takes a selfie using a dedicated camera installed in the store.

[0629] Data transmission and analysis

[0630] The in-store device transmits the captured selfie image and body composition measurement data in real time to a server equipped with a high-performance processing unit and AI algorithms (e.g., Python, TensorFlow, OpenCV).

[0631] Data analysis process

[0632] The server first analyzes the selfie image using face mapping technology to extract the user's facial shape and features. Next, it analyzes the user's physical characteristics (body type, body fat percentage, muscle mass, etc.) based on body composition measurement data. The results of this analysis are then compared with the latest fashion trend database (e.g., SQL database).

[0633] Generate and view suggestions

[0634] Based on the analysis results and trend data, the server will suggest the most suitable fashion items, hairstyles, and makeup for the user. The suggestions are sent to a display device (e.g., tablet or smart display) in the store, where the user can view them.

[0635] Proposal implementation and support

[0636] Users can try on suggested fashion items in a physical store and purchase or rent them on the spot. For suggested hairstyles and makeup, the server will provide location-based recommendations for hair salons and display reservation links.

[0637] Specific examples

[0638] User A (30 years old, female):

[0639] Visit a physical store and measure your weight and body fat percentage using a smart body composition scale.

[0640] Take a selfie using the store's dedicated camera.

[0641] The server analyzes the data and, based on face mapping and body composition data, suggests a pastel-colored dress, natural makeup, and a long hairstyle, referencing spring fashion trends.

[0642] Suggestions are displayed on a tablet in the store, and User A tries on the suggested fashion items in a fitting room.

[0643] Purchase your favorite items and get information on recommended hair salons.

[0644] Example prompt sentence:

[0645] "Generate optimal fashion, hairstyle, and makeup suggestions based on user images and body composition data."

[0646] Hardware and Software

[0647] Hardware:

[0648] Smart Body Composition Monitor

[0649] Dedicated camera

[0650] In-store tablets and smart displays

[0651] server

[0652] software:

[0653] Data transmission module (app)

[0654] Data Analysis Program

[0655] Face mapping technology (OpenCV)

[0656] Machine learning model (TensorFlow)

[0657] Display app (React.js or Vue.js)

[0658] This configuration allows users to receive the latest styling suggestions in real time at a physical store, and easily try on and purchase items.

[0659] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0660] Step 1:

[0661] The user visits a physical store and steps onto the smart body composition scale. The scale collects body composition measurement data, such as the user's weight, body fat percentage, and muscle mass. This data is sent to a terminal in the store via Bluetooth or Wi-Fi. The input is the body composition measurement data, and the output is the body composition measurement data sent to the terminal.

[0662] Step 2:

[0663] Users take selfies using a dedicated camera installed in the store. The captured image is saved on a terminal in the store. The input is the selfie image taken by the camera, and the output is the selfie image saved on the terminal.

[0664] Step 3:

[0665] The store terminal transmits the captured selfie image and body composition measurement data to the server in real time. The input is the selfie image and body composition measurement data, and the output is both data transmitted to the server. The terminal does this using a data transmission module.

[0666] Step 4:

[0667] When the server receives the selfie image, it uses face mapping technology (OpenCV) to analyze the shape and features of the user's face. The input is the selfie image, and the output is facial shape and feature data. The server identifies the boundary of the face and detects the positions of the eyes, nose, mouth, etc.

[0668] Step 5:

[0669] Next, the server analyzes the user's physical characteristics based on the body composition measurement data. The input is the body composition measurement data, and the output is detailed physical characteristic data such as body type, body fat percentage, and muscle mass. The server analyzes weight, body fat percentage, and muscle mass to create a body type profile for the user.

[0670] Step 6:

[0671] The server compares the analyzed facial feature data and physical characteristic data with the latest fashion trend database (SQL database). The input is facial feature data and physical characteristic data, and the output is suggested data based on the most suitable fashion trends. The server compares each data point with the trend information for each item and generates the optimal styling.

[0672] Step 7:

[0673] The server sends the generated proposals to a display device (tablet or smart display) in the store. The input is the proposal data, and the output is the proposal content displayed on the display device. The server sends the proposal content in JSON format, which the display device receives and displays visually.

[0674] Step 8:

[0675] The user reviews the displayed suggestions and tries on the suggested fashion items. The input is the suggestions and the items tried on, and the output is the user's feedback. The user tries on the items in the fitting room to check the fit and style.

[0676] Step 9:

[0677] If the user purchases or rents the suggested item, the server provides recommended salon information based on the user's location. The input is the user's location and the suggested item, and the output is salon information. The server searches for the most suitable salon based on the user's current location and the suggested item, and provides a link to make a reservation.

[0678] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0679] This is a new invention that combines an emotion engine with a system that allows users to input selfie photos and body composition measurement data and then suggests optimal fashion, hairstyles, and makeup based on that information. The system consists of a user's device, a server, an emotion engine, and affiliated beauty salons and rental shops.

[0680] System configuration

[0681] 1. User's device: On a device such as a smartphone or PC, users take selfies, input body composition measurement data, use the function to recognize the user's emotions, and check suggested styles.

[0682] 2. Server: Receives and analyzes data, recognizes emotions using the emotion engine, compares it with trend information, and generates and sends suggestions.

[0683] 3. Emotion Engine: Analyzes selfies and recognizes the user's emotional state.

[0684] 4. Beauty salons and rental shops: Providing services and items based on requests received from the server.

[0685] Program processing

[0686] The program processing within this system will be explained in natural language below.

[0687] 1. User enters data

[0688] Users use a dedicated smart body composition scale to measure their weight, body fat percentage, etc. The measurement data is sent to the user's device.

[0689] Next, the user takes a selfie with their device's camera and uploads it to the app.

[0690] 2. The device sends the data to the server

[0691] The device transmits the acquired selfie image, body composition measurement data, location information, and emotion data extracted by the emotion engine to the server.

[0692] 3. The server analyzes the data

[0693] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color.

[0694] At the same time, body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc.

[0695] 4. Emotion engine recognizes emotions

[0696] The server uses an emotion engine to recognize the user's emotions from the selfie image, using technology to determine emotions such as happiness, sadness, and surprise from the user's facial expressions.

[0697] 5. The server checks the data against the trend database.

[0698] The server compares the user's facial features, body type, and emotional data with the latest fashion trend database, and then selects the hairstyle, makeup, and fashion items that are best suited to the user.

[0699] 6. The server generates and sends a proposal

[0700] Based on the matching results, the server will suggest the best style for the user, including images of hairstyles, makeup routines, and photos and combinations of fashion items.

[0701] Based on emotional data, the suggested styles are adjusted to adapt to the user's current mental state.

[0702] Suggestions are sent to the user's device and displayed through the app.

[0703] 7. Providing beauty salon and rental services

[0704] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[0705] Similarly, the suggested fashion items are available for rental service, and users can send a request from their device. The rental shop will then process the delivery of the items.

[0706] Specific examples

[0707] User C (28 years old, female)

[0708] The user measures her weight and body fat percentage using a dedicated body composition scale, and uploads a selfie with her smartphone. The emotion engine detects the emotion of joy from her facial expression.

[0709] The server analyzes this data and matches the latest spring fashion trends based on User C's face shape and body type.

[0710] A light-colored dress, a casual jacket, and natural makeup are suggested, creating a style that brings out her joyful emotions.

[0711] The server recommends reputable local hair salons and stylists and provides booking links.

[0712] The suggested fashion items will be delivered to your home the next day using a rental service.

[0713] User D (35 years old, male)

[0714] The smart body composition scale measures his weight and body fat percentage, and he uploads a selfie with his smartphone. The emotion engine detects his fatigue and stress from his facial expressions.

[0715] The server analyzes the data and matches the latest fall fashion trends based on User D's face shape and body type.

[0716] A dark suit, a muted tie, and a simple hairstyle are recommended, all of which will help him look less tired.

[0717] In addition, it also provides information on nearby stores suitable for relaxation services and refreshing.

[0718] The suggested fashion items will be delivered to your home the next day using a rental service.

[0719] This allows users to easily find the perfect style that suits their emotional state and receive services at a beauty salon. Users can also rent suggested fashion items.

[0720] The processing flow will be explained below.

[0721] Step 1:

[0722] The user steps onto the dedicated smart body composition scale and obtains body composition measurement data such as weight, body fat percentage, muscle mass, etc. This data is automatically sent to the user's device.

[0723] Step 2:

[0724] The user launches a dedicated app and takes a selfie with their smartphone camera, which is then uploaded to the app.

[0725] Step 3:

[0726] The device sends the selfie image and body composition measurement data it has acquired to a server. The data is sent using a secure communication protocol, so it arrives safely at the server.

[0727] Step 4:

[0728] The server inputs the received selfie into an AI analysis algorithm to perform face mapping, which extracts features such as the user's facial shape, skin color, and hair texture.

[0729] Step 5:

[0730] The server analyzes the body composition measurement data and determines the user's physical characteristics such as height, weight, body fat percentage, and muscle mass.

[0731] Step 6:

[0732] The server inputs the selfie image into the emotion engine to recognize the user's emotions. The emotion engine determines the user's emotional state, such as joy, sadness, surprise, or anger, from their facial expressions.

[0733] Step 7:

[0734] The server compares the analysis results and emotional data with the latest fashion trend database, which includes information on the latest hairstyles, makeup, and fashion items.

[0735] Step 8:

[0736] The server selects the hairstyle, makeup, and fashion items that are best suited to the user and generates recommendations. Based on the emotional data, the server adjusts the recommendations to suit the user's specific emotional state.

[0737] Step 9:

[0738] The server generates and sends the recommendation information to the device, which includes images of specific hairstyles, makeup steps, and photos of fashion items and combinations.

[0739] Step 10:

[0740] The device displays the received recommendation information to the user, who can then check the suggested styles via the app and select the most appropriate suggestion based on their emotional state.

[0741] Step 11:

[0742] The server provides recommended hair salon information based on the user's location, and if the user wishes, a link to make a reservation at the appropriate salon is also provided.

[0743] Step 12:

[0744] If the user likes the suggested fashion item, they can send a rental request through the app.

[0745] Step 13:

[0746] The server receives the rental request and sends a request for the specified item to the affiliated rental shop.

[0747] Step 14:

[0748] The rental shop will confirm the request and prepare to deliver the specified fashion item to the user's address.

[0749] Step 15:

[0750] The user receives the rented fashion item and uses it for the specified period. After use, the rental item is returned.

[0751] By following these steps, users can easily find the style that best suits them and receive services at a beauty salon. They can also rent the suggested fashion items. The introduction of an emotion engine makes it possible to provide detailed suggestions based on the user's emotional state.

[0752] Example 2

[0753] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0754] Conventional fashion suggestion systems primarily make suggestions based on the user's physical characteristics and facial shape, without taking into account the user's emotional state. This can result in suggested styles that do not match the user's psychological state, resulting in reduced user satisfaction. Furthermore, when users wish to use specific services or products based on the suggestions, they must individually search for information and make reservations, which is inconvenient.

[0755] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0756] In this invention, the server includes means for face mapping a selfie image, analyzing physical characteristics based on body composition measurement data, and recognizing an emotional state using an emotion engine, means for comparing the analysis results and the emotional state with the latest fashion trend database to suggest optimal fashion, hairstyle, and makeup, and means for transmitting and displaying the suggestions to the user's terminal. This makes it possible to suggest styles that are adapted to the user's psychological state, and furthermore, by linking with information on beauty salons and fashion item rental services, it is possible to provide users with advanced and personalized services.

[0757] A "user" is a person who uses the system to input a selfie and body composition data and receive style suggestions.

[0758] A "selfie" is a photograph of the face or upper body taken by the user, and is data used for face mapping and emotion recognition.

[0759] "Body composition measurement data" refers to data relating to the user's body composition, such as weight, body fat percentage, and muscle mass, and is data used to analyze physical characteristics.

[0760] "Transmission means" refers to the function for transferring the selfie image, body composition measurement data, and emotion data to the server.

[0761] "Analysis means" refers to the algorithms and modules that process selfie images and body composition measurement data within the server and identify the user's facial shape and physical characteristics.

[0762] "Emotion engine" refers to the technology and algorithms used to extract and analyze a user's emotions from selfie images.

[0763] "Matching means" refers to an information processing function that matches the analysis results and emotional state with a fashion trend database and selects the most suitable fashion, hairstyle, and makeup for the user.

[0764] "Suggestion means" refers to a function for transmitting and displaying the fashion, hairstyle, and makeup suggestions generated by the server to the user's terminal.

[0765] "Location information" refers to information about a geographical location obtained from a user's device, and is data used to provide beauty salon information.

[0766] "Beauty salon information" is information about facilities that offer specific beauty services suggested based on the user's location information.

[0767] A "rental request" is a request submitted by a user to temporarily borrow a suggested fashion item.

[0768] "Rental Items" are fashion items that users can temporarily borrow through rental requests.

[0769] This system allows users to input selfie images, body composition measurement data, and emotion data extracted from the images, and then suggests optimal fashion, hairstyle, and makeup based on that information. The system consists of a user terminal, a server, an emotion engine, and affiliated beauty salons and rental shops.

[0770] User terminal

[0771] Using a device such as a smartphone or PC, the user takes a selfie, inputs body composition measurement data, executes a function that recognizes the user's emotions, and checks the suggested style. The user uses a smart body composition scale to measure data such as weight and body fat percentage. This measurement data is sent to the user's smartphone via Bluetooth. The user then takes a selfie using the smartphone camera and uploads it to a specific app.

[0772] server

[0773] The server stores the received selfie image, body composition measurement data, and emotion data in a connected database. Analysis of the received data is also performed on the server. Specifically, the server uses an image processing algorithm to perform face mapping and extract features such as the user's facial shape and skin color. At the same time, it analyzes the body composition measurement data to determine the user's body type, body fat percentage, and muscle mass.

[0774] The server then uses an emotion engine to recognize the user's emotions from the selfie. This emotion engine is a technology that determines emotions such as joy, sadness, and surprise from the user's facial expressions. The server then compares the analysis results and emotional state with the latest fashion trend database to suggest hairstyles, makeup, and fashion items that are best suited to the user. Suggestions include images of hairstyles, makeup steps, and photos and combinations of fashion items. Based on the emotion data, the suggested styles are adjusted to adapt to the user's current mental state. Suggestions are sent to the user's device and displayed through the app.

[0775] Hair salons and rental shops

[0776] If the user wishes to use the service based on the suggestions, the server provides information on recommended beauty salons and displays a reservation link. Furthermore, the suggested fashion items are available for rental, and a request can be sent from the user's device. The rental shop then processes the delivery of the items upon receiving the request.

[0777] Specific examples

[0778] User C (28 years old, female)

[0779] The user measures their weight and body fat percentage with a dedicated body composition scale, takes a selfie with their smartphone, and uploads it to the app. The emotion engine detects the emotion of joy from their facial expression.

[0780] The server analyzes this data and matches it with the latest spring fashion trends based on User C's face shape and body type.

[0781] We suggest a light-colored dress, a casual jacket, and natural makeup, which will bring out her joyful emotions.

[0782] The server recommends reputable local hair salons and stylists and provides booking links.

[0783] The suggested fashion items will be delivered to your home the next day using a rental service.

[0784] User D (35 years old, male)

[0785] The smart body composition scale measures his weight and body fat percentage, and he takes a selfie with his smartphone and uploads it. The emotion engine detects emotions such as fatigue and stress from his facial expressions.

[0786] The server analyzes the data and matches it with the latest fall fashion trends based on User D's face shape and body type.

[0787] A dark suit, a muted tie, and a simple hairstyle are recommended, which will help him look less tired.

[0788] In addition, it also provides information on nearby stores suitable for relaxation services and refreshing.

[0789] The suggested fashion items will be delivered to your home the next day using a rental service.

[0790] Prompt Sentence Examples

[0791] "A 28-year-old female user measured her weight and body fat percentage using a dedicated body composition scale and uploaded a selfie with her smartphone. The emotion engine detected the emotion of joy from her facial expression. Based on this user's face shape and body type, please match the latest spring fashion trends and suggest a bright-colored dress and natural makeup."

[0792] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0793] Step 1: User takes a selfie and enters body composition measurement data

[0794] The user uses a dedicated smart body composition scale to measure data such as weight and body fat percentage. This measurement data is sent to the user's smartphone via Bluetooth. The user then takes a selfie using the smartphone camera and uploads it to a dedicated app. This provides the selfie image and body composition measurement data as input data.

[0795] Step 2: The device sends the data to the server

[0796] The device sends the captured selfie image, body composition measurement data, location information, and emotion data extracted by the emotion engine to the server. Specifically, all data collected by the smartphone application (images, measurement data, location information, emotion data) is securely sent to the server using the HTTPS protocol. This sends the input data to the server.

[0797] Step 3: The server parses the data

[0798] The server performs face mapping based on the received selfie image, extracting features such as the user's facial shape, skin color, and contours. A facial recognition module is used for this analysis. At the same time, body composition measurement data is analyzed to determine the user's body type, body fat percentage, and muscle mass. Specifically, the face mapping algorithm analyzes the selfie image and identifies facial feature points (such as the position of the eyes, nose, and mouth), and the body composition data analysis module calculates the user's physical characteristics based on the measurement data. This outputs facial shape data and physical characteristic data.

[0799] Step 4: The emotion engine recognizes the emotion

[0800] The server recognizes the user's emotions from the selfie image through the emotion engine. The emotion engine analyzes the user's facial expressions from the image and determines emotions such as joy, sadness, and surprise. Specifically, the emotion engine analyzes the subtle movements of the face to evaluate the user's emotional state, which then outputs the user's emotional data.

[0801] Step 5: The server checks against the trend database

[0802] The server compares the user's facial features, body type data, and emotional data with the latest fashion trend database. This allows the system to select the hairstyle, makeup, and fashion items that are best suited to the user. Specifically, the server executes a database query to search the latest fashion trend information and identify the most suitable style. This results in the output of optimized fashion suggestion data.

[0803] Step 6: Server generates and sends proposal

[0804] Based on the matching results, the server suggests the optimal style for the user. The suggestions include images of hairstyles, makeup routines, and photos and combinations of fashion items. Based on emotional data, the suggested style is adjusted to suit the user's current mental state. Specifically, the server encodes the suggested data in JSON format and sends it to the smartphone app via push notification. The suggested data is then displayed on the user's device.

[0805] Step 7: Provide beauty salon and rental services

[0806] If the user wishes to use a service based on the suggestions, the server provides information about recommended beauty salons and displays a reservation link. Furthermore, rental services are available for the suggested fashion items, and a request can be sent from the user's device. The rental shop receives the request and arranges for delivery of the items. Specifically, the server analyzes reputation data for nearby beauty salons, selects the most suitable salon, and displays it to the user. The rental request is also linked to the rental shop's system, which checks inventory and initiates delivery procedures. This allows users to easily use the appropriate beauty services and fashion items.

[0807] (Application example 2)

[0808] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0809] In today's world, selecting the best fashion, hairstyle, and makeup for each individual user can be difficult given the wide variety of options and trend information available. While it is important to provide style suggestions that take into account each user's emotional state and physical characteristics, systems that can effectively reflect these are still lacking. Furthermore, there is a need for a simple way to actually apply the suggested styles (by making a salon appointment or renting fashion items).

[0810] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for comparing the analysis results and the emotion data recognized by the emotion engine with the latest fashion trend database and suggesting optimal fashion, hairstyle, and makeup for the user, means for virtually displaying the suggested styles on the user's terminal in real time, and means for transmitting and displaying the suggestions on the user's terminal. This enables the system to suggest optimal styles based on the user's emotional state and physical characteristics and to enable the user to virtually try on those styles.

[0811] A "user terminal" is an electronic device used by a user to operate the device, such as a smartphone or a personal computer.

[0812] A "server" is a computer system that receives data, analyzes it, recognizes emotions, generates suggestions, and transmits the information to the user's device.

[0813] A "selfie" refers to a photograph of the user's face taken by the user themselves, and is used to analyze facial features.

[0814] "Body composition measurement data" is measurement data that indicates the user's physical characteristics such as weight and body fat percentage.

[0815] "Face mapping" is a technology that analyzes the shape and features of a user's face based on a selfie image.

[0816] The "Emotion Engine" is a technology that analyzes and recognizes a user's emotional state from selfie images.

[0817] The "Fashion Trend Database" is a database that stores information on the latest fashions, hairstyles, and makeup.

[0818] "Virtual display means" refers to a technology that allows users to virtually visualize styles that they have not actually tried and check them on their device.

[0819] "Location Information" is data that indicates a user's current geographic location.

[0820] "Beauty salon information" is information about a beauty salon, including the salon name, location, reservation status, and the like.

[0821] "Fashion items" are fashion-related products such as clothing and accessories.

[0822] "Rental" refers to a service in which users temporarily borrow fashion items to use for a certain period of time.

[0823] This system uses a user's selfie photos and body composition measurement data to suggest optimal fashion, hairstyles, and makeup, and combines it with an emotion engine. The system consists of a user's device, a server, an emotion engine, and affiliated beauty salons and rental shops.

[0824] System configuration

[0825] 1. User Device

[0826] Input method: Users take selfies and input body composition measurement data using devices such as smartphones and PCs. Specific devices include iPhones, Android smartphones, and Windows PCs.

[0827] Virtual display means: The system has the function of visualizing the proposed style in real time on the device, allowing users to virtually try out the style.

[0828] 2. Server

[0829] Analysis method: The server performs face mapping based on the uploaded selfie image and analyzes the user's facial shape and features. It also analyzes physical characteristics based on body composition measurement data. The server processes data using cloud services such as Google Cloud Platform and AWS.

[0830] Emotion Recognition: Recognize the user's emotional state from selfies through an emotion engine, built using machine learning libraries such as TensorFlow.

[0831] Matching: The analysis results and sentiment data are matched with the latest fashion trend database to suggest the most suitable fashion, hairstyle, and makeup for the user. The trend database collects the latest industry information and is updated regularly.

[0832] 3. Affiliated hair salons and rental shops

[0833] Information provision: Based on the user's location, the service provides recommended hair salons. Hair salons are registered in a database in advance and selected based on ratings and user feedback.

[0834] Rental service: Users can submit rental requests for suggested fashion items, which are then sent to affiliated rental shops, which then process the delivery of the items.

[0835] Specific examples

[0836] User C (28 years old, female):

[0837] She measures her weight and body fat percentage with a dedicated body composition scale and uploads a selfie with her smartphone. The emotion engine detects the emotion of joy from her facial expression. The server analyzes this data and matches the latest spring fashion trends based on User C's face shape and body type. It suggests a bright-colored dress, a casual jacket, and natural makeup. This selects a style that will bring out her emotion of joy. The server then provides information on reputable local hair salons and displays a link to make a reservation. The suggested fashion items are delivered to her home the next day using a rental service.

[0838] User D (35 years old, male):

[0839] The user measures his weight and body fat percentage with a smart body composition scale and uploads a selfie image on his smartphone. The emotion engine detects feelings of fatigue and stress from his facial expressions. The server analyzes the data and matches the latest autumn fashion trends based on User D's facial shape and body type. It suggests a dark-colored suit, a tie in a muted tone, and a simple hairstyle. This selects a style that will relieve his fatigue. It also provides information on nearby stores suitable for relaxation services and refreshing. The suggested fashion items are delivered to his home the next day using a rental service.

[0840] Prompt Sentence Examples

[0841] "We analyzed User A's selfies and identified her happy emotions. Based on the latest spring fashion trends, we suggest the following style. A casual navy cardigan and denim combination with a striped shirt would look good on her."

[0842] This allows users to easily find the style that best suits their emotional state and physical characteristics, and also makes it easier to use services at beauty salons and rent fashion items.

[0843] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0844] Step 1:

[0845] Users take a selfie using a device such as a smartphone or PC, and a dedicated smart body composition scale acquires body composition measurement data such as weight and body fat percentage. The user's device receives this data and uploads the selfie and body composition measurement data to the app. The input data is the selfie and body composition measurement data, and the output is the uploaded user data.

[0846] Step 2:

[0847] The user device sends the uploaded selfie image and body composition measurement data to the server using a secure communication protocol (e.g., HTTPS). The input data are the selfie image and body composition measurement data obtained in the previous step, and the output is the data transferred to the server.

[0848] Step 3:

[0849] The server performs face mapping based on the received selfie image. This face mapping uses image processing libraries such as OpenCV to analyze the shape and features of the face. The input data is the selfie image, and the output is data that shows the shape and features of the user's face.

[0850] Step 4:

[0851] The server analyzes the body composition measurement data and identifies the user's physical characteristics (body type, body fat percentage, muscle mass, etc.). Data science tools (e.g., Pandas, NumPy) are used for the analysis. The input data is the body composition measurement data, and the output is the analyzed physical characteristic data.

[0852] Step 5:

[0853] The server uses an emotion engine to recognize the user's emotional state from the selfie image. It uses deep learning libraries such as TensorFlow to run emotion recognition models and identify emotions such as joy, sadness, and surprise. The input data is the selfie image, and the output is the recognized emotion data.

[0854] Step 6:

[0855] The server compares the user's facial features, physical characteristics, and emotional data with the latest fashion trend database. The fashion trend database is managed on the cloud and updated with the latest industry information. The input data is face mapping data, physical characteristics data, and emotional data, and the output is data suggesting the most suitable fashion, hairstyle, and makeup for the user.

[0856] Step 7:

[0857] The server sends the generated proposal to the user's device, which then virtually displays the proposed style in real time, allowing the user to virtually try out the proposed style. The input data is the proposal data, and the output is the virtual style displayed on the user's device.

[0858] Step 8:

[0859] If the user accepts the proposed style, the user device sends a request to the affiliated hair salon or rental shop. The input data is the user's request, and the output is the salon reservation information and the delivery procedure for the rental items.

[0860] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0861] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0862] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0863] [Third embodiment]

[0864] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0865] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0866] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0867] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0868] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0869] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0870] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0871] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0872] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0873] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0874] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0875] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0876] This system allows users to input their selfie photos and body composition measurement data, and based on that information, it suggests optimal fashion, hairstyles, and makeup. The system consists of a user's device, a server, and affiliated beauty salons and rental shops.

[0877] System configuration

[0878] 1. User's device: On a device such as a smartphone or computer, users take a selfie, enter body composition measurement data, and check suggested styles.

[0879] 2. Server: Receives data, analyzes it, compares it with trend information, and generates and sends recommendations.

[0880] 3. Beauty salons and rental shops: Providing services and items based on requests received from the server.

[0881] Program processing

[0882] The program processing within this system will be explained in natural language below.

[0883] 1. User enters data

[0884] Users use a dedicated smart body composition scale to measure their weight, body fat percentage, etc. The measurement data is sent to the user's device.

[0885] Next, the user takes a selfie using the device's camera and uploads it to the app.

[0886] 2. The device sends the data to the server

[0887] The device sends the captured selfie image and body composition measurement data to the server.

[0888] 3. The server analyzes the data

[0889] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color.

[0890] At the same time, body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc.

[0891] 4. The server checks the data against the trend database.

[0892] The server compares facial features and body type data with the latest fashion trend database, and then selects hairstyles, makeup, and fashion items that are best suited to the user.

[0893] 5. The server generates and sends a proposal

[0894] Based on the results of the comparison, the server will suggest the best style for the user, including an image of the hairstyle, detailed makeup instructions, and a combination of fashion items.

[0895] Suggestions are sent to the user's device and displayed through the app.

[0896] 6. Providing beauty salon and rental services

[0897] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[0898] Similarly, for the suggested fashion items, rental services are available, and users can send requests from their devices. The rental shop will then process the delivery of the items.

[0899] Specific examples

[0900] User A (32 years old, female)

[0901] Measure your weight and body fat percentage using a dedicated body composition scale, and upload a selfie photo using your smartphone.

[0902] The server analyzes this data and matches the latest summer fashion trends based on User A's face shape and body type.

[0903] We suggest a lightweight jacket in cool colors, shorts, and natural makeup.

[0904] The server recommends reputable local hair salons and stylists and provides booking links.

[0905] The suggested fashion items will be delivered to your home the next day using a rental service.

[0906] User B (45 years old, male)

[0907] Measure your weight and body fat percentage with a smart body composition scale and upload a selfie using your smartphone.

[0908] The server analyzes the data and matches it with the latest autumn fashion trends based on the sharp features of User B's jawline.

[0909] We suggest a dark green jacket, gray pants, and loafers.

[0910] The server recommends the best two-block hairstyle and provides information on nearby hair salons and a link to make a reservation.

[0911] The suggested fashion items will be delivered to your home the next day using a rental service.

[0912] This allows users to easily enjoy styles that incorporate the latest trends.

[0913] The processing flow will be explained below.

[0914] Step 1:

[0915] The user steps onto the dedicated smart body composition scale and obtains body composition measurement data such as weight, body fat percentage, muscle mass, etc. This data is automatically sent to the user's device.

[0916] Step 2:

[0917] The user launches a dedicated app and takes a selfie with their smartphone camera, which is then uploaded to the app.

[0918] Step 3:

[0919] The device sends the selfie image and body composition measurement data it has acquired to a server. The data is sent using a secure communication protocol, so it arrives safely at the server.

[0920] Step 4:

[0921] The server inputs the received selfie into an AI analysis algorithm to perform face mapping, which extracts features such as the user's facial shape, skin color, and hair texture.

[0922] Step 5:

[0923] The server analyzes the body composition measurement data and determines the user's physical characteristics such as height, weight, body fat percentage, and muscle mass.

[0924] Step 6:

[0925] The server compares the analysis results with a database of current fashion trends, which includes information on the latest hairstyles, makeup, and fashion items.

[0926] Step 7:

[0927] The server selects the hairstyle, makeup, and fashion items that are best suited to the user and generates them as recommendation information.

[0928] Step 8:

[0929] The server generates and sends the recommendation information to the device, which includes images of specific hairstyles, makeup steps, and photos of fashion items and combinations.

[0930] Step 9:

[0931] The device displays the received recommendation information to the user, who can then check the suggested styles via the app.

[0932] Step 10:

[0933] The server provides recommended hair salon information based on the user's location, and if the user wishes, a link to make a reservation at the appropriate salon is also provided.

[0934] Step 11:

[0935] If the user likes the suggested fashion item, they can send a rental request through the app.

[0936] Step 12:

[0937] The server receives the rental request and sends a request for the specified item to the affiliated rental shop.

[0938] Step 13:

[0939] The rental shop will confirm the request and prepare to deliver the specified fashion item to the user's address.

[0940] Step 14:

[0941] The user receives the rented fashion item and uses it for the specified period. After use, the rental item is returned.

[0942] By following these steps, users can easily find the style that best suits them and receive services at a beauty salon. They can also rent suggested fashion items.

[0943] Example 1

[0944] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0945] Conventional systems have had difficulty fully reflecting individual physical characteristics and the latest fashion trends when proposing fashion, hairstyles, and makeup that are suited to a user's appearance. Furthermore, the content of the proposals was limited to static information, and the provision of specific advice and recommendations that were highly practical for users was insufficient. This led to a problem of lower user satisfaction with improvements to their style.

[0946] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0947] In this invention, the server includes means for face mapping a selfie image and analyzing the user's physical characteristics based on body composition measurement data, means for comparing the results with a trend database to suggest optimal fashion, hairstyle, and makeup for the user, and means for automatically generating details of the suggestions using a generative AI model and providing them to the user. This makes it possible to suggest specific styles that reflect individual physical characteristics and the latest trends, as well as provide highly practical, detailed advice.

[0948] A "selfie" refers to an image of a user's face or body taken by the user themselves.

[0949] "Body composition measurement data" refers to data regarding the user's physical composition, such as weight, body fat percentage, and muscle mass.

[0950] "Server" refers to the computer system responsible for analyzing the data it receives, collating it, generating suggestions, and sending them to the user.

[0951] "Face mapping" refers to the process of using image analysis technology to extract facial shapes and features from selfies.

[0952] "Physical characteristics" refers to a user's physical characteristics such as body shape, skin color, and body fat percentage.

[0953] A "trend database" refers to a database that stores information about the latest fashions, hairstyles, and makeup.

[0954] "Fashion" refers to the style of clothing, accessories, etc.

[0955] "Hairstyle" refers to the design or style of a hairstyle.

[0956] "Makeup" refers to the method and style of applying makeup.

[0957] A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to analyze text, images, and data.

[0958] "Suggestions" refers to specific advice and information about fashion, hairstyles, and makeup provided to users.

[0959] "User's device" refers to a device such as a smartphone or computer used by the user.

[0960] "Location Information" means information that indicates a User's current geographic location.

[0961] "Hair Salon Information" refers to data and booking links about hair salons recommended to users.

[0962] "Rental items" refer to fashion items that users can borrow temporarily.

[0963] This invention is a system that allows users to input selfie photos and body composition measurement data, and based on that information, suggests optimal fashion, hairstyles, and makeup. The system is composed of a user's terminal, a server, and affiliated service providers.

[0964] System configuration

[0965] 1. User's Device

[0966] The user's device is a device such as a smartphone or PC. The user uses these devices to take selfies, input body composition measurement data, and check the suggested style. Specific examples include iPhones and Android devices.

[0967] 2. Server

[0968] The server receives and analyzes the data, compares it with trend information, and generates and sends proposals. A specific example is an EC2 instance on AWS, which uses cloud services. The server analyzes the data using OpenCV, a facial recognition library, and TensorFlow, a machine learning framework, and automatically generates details of the proposals using a generative AI model (e.g., GPT-3).

[0969] 3. Affiliated Service Providers

[0970] The affiliated service providers are beauty salons and fashion rental shops that provide services and items to users. These service providers provide services and items based on requests received from the server.

[0971] Program processing

[0972] The program processing within this system will be explained in natural language below.

[0973] 1. The user enters data

[0974] The user uses a dedicated smart body composition scale (for example, a general body composition scale) to measure weight, body fat percentage, etc. The measurement data is sent to a device (for example, an iPhone).

[0975] Next, the user takes a selfie using the device's camera and uploads it to the app. "Tap the 'Measure' button on the home screen, and once the measurement is complete, the data will be automatically transferred to the app. Then tap the 'Camera' button to take a selfie, and press the 'Upload' button to send the data to the server."

[0976] 2. The device sends the data to the server

[0977] The device sends the selfie image and body composition measurement data captured by the user to a server via Wi-Fi or mobile data communication using an encrypted communication protocol (e.g., HTTPS).

[0978] 3. The server analyzes the data

[0979] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color. The software used here is a facial recognition library (e.g., OpenCV).

[0980] At the same time, the body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc. A machine learning model (for example, a model using TensorFlow) is used for the analysis.

[0981] 4. The server checks the data against the trend database.

[0982] The server compares the facial features and body shape data with the latest fashion trend database (for example, trend information stored in MongoDB), and then selects the best hairstyle, makeup, and fashion item for the user.

[0983] 5. The server generates and sends a proposal

[0984] Based on the matching results, the server suggests the best style for the user. The suggestions include hairstyle images, detailed makeup instructions, and combinations of fashion items. Using a generative AI model (e.g., GPT-3), fashion advice and makeup instructions are written in natural-sounding sentences.

[0985] Suggestions are sent to the user's device and displayed through a dedicated app.

[0986] 6. Provision of Services

[0987] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[0988] Similarly, for the suggested fashion items, rental services (e.g., general rental shops) are available, and a request can be sent from the user terminal. The rental shop will then process the delivery of the item.

[0989] Examples and prompts

[0990] When user A takes photos and enters data

[0991] User A takes measurements using a standard body composition scale, then takes a selfie using an iPhone app. "On the home screen, tap the 'Measure' button, and once the measurement is complete, the data is automatically transferred to the app. Then, tap the 'Camera' button to take a selfie, and press the 'Upload' button to send the data to the server."

[0992] Example prompts for generative AI models

[0993] "User A is a 32-year-old woman who wants to improve her appearance. Please suggest the best summer fashion and makeup for her based on her body composition measurement data and selfies."

[0994] This allows users to easily enjoy styles that incorporate the latest trends.

[0995] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0996] Step 1:

[0997] The user enters data

[0998] Input: Data such as weight and body fat percentage measured by the user using a dedicated smart body composition scale (e.g., a general body composition scale), and a selfie image.

[0999] Specific operation: The user uses a body composition scale to measure their weight and body fat percentage. This measurement data is automatically sent to a smartphone (e.g., iPhone) via Bluetooth. The user then takes a selfie using the smartphone's camera and uploads it to the app. Specifically, the user taps the "Measure" button on the home screen, and once the measurement is complete, the data is transferred to the app. Next, the user taps the "Camera" button to take a selfie, and then presses the "Upload" button to prepare for data transmission.

[1000] Output: Body composition measurement data and selfie images are saved on the user's device.

[1001] Step 2:

[1002] The device sends the data to the server

[1003] Input: Body composition measurement data and selfie images stored on the user's device.

[1004] What it does: Your device sends the stored data to the server over Wi-Fi or mobile data using an encrypted communication protocol (e.g., HTTPS). Specifically, when you tap the "Send Data" button, the data is sent to the server via HTTPS.

[1005] Output: Body composition measurement data and selfie image sent to the server.

[1006] Step 3:

[1007] The server analyzes the data

[1008] Input: Body composition measurement data and selfie image sent to the server.

[1009] How it works: The server analyzes the selfie image using a facial recognition library (e.g., OpenCV). It performs face mapping and extracts features such as the user's facial shape, skin color, and the position of the eyes and nose. In parallel, it applies a machine learning model (e.g., a model using TensorFlow) to the body composition measurement data to analyze the user's body shape, body fat percentage, and muscle mass. This includes applying a face detection algorithm and classifying and regressing the body composition data.

[1010] Output: The user's facial feature data and body shape data.

[1011] Step 4:

[1012] The server checks against the trend database

[1013] Input: User's facial feature data, body shape data, and a database of the latest fashion trends (e.g., trend information stored in MongoDB).

[1014] What it does: The server uses an algorithm to match the information in the trends database with the user's facial features and body data. Specifically, it pulls images of models and fashion items with similar face shapes and body types from the database. This includes image recognition algorithms and calculating a relevance score.

[1015] Output: A list of suggested fashion, hairstyle, and makeup looks that suit the user.

[1016] Step 5:

[1017] The server generates and sends the proposal

[1018] Input: A list of suggested fashion, hairstyle, and makeup looks for the user.

[1019] Specific operation: The server uses a generative AI model (e.g., GPT-3) to generate natural-sounding text about fashion advice and makeup techniques. Using this information, it generates a report proposing the optimal style for the user. This report includes an image of the hairstyle, detailed makeup steps, and a combination of fashion items. The report is then sent to the user's device using the HTTPS protocol. Specifically, it executes the "suggestion generation" function and sends the generated report to the user.

[1020] Output: The proposal report is sent to the user's device and displayed through the app.

[1021] Step 6:

[1022] Hair salon and rental services will be provided.

[1023] Input: Proposal report sent to user, user location information.

[1024] Specific operation: If the user uses a service based on the suggestions, the system will provide recommended hair salon information and display a reservation link. Furthermore, the suggested fashion items are available for rental services (e.g., general rental shops), and the user can send a request from their device. The rental shop will then process the delivery of the items upon receiving the request. Specifically, the user taps the "Send Request" button on the rental service, and the request is sent via the server.

[1025] Output: The user's device will be notified of the completion of the hair salon reservation and the scheduled delivery of the rental items.

[1026] (Application example 1)

[1027] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1028] It is difficult for users to easily find the fashion, hairstyle, and makeup that best suits them. Especially in physical stores, it takes time and effort for users to instantly check, try on, and apply styling that suits them. It is also uncertain whether the styling provided is based on the latest trends. Furthermore, an efficient system is needed to improve the user experience through real-time service provision in physical stores.

[1029] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1030] In this invention, the server includes: means for a user to input a selfie image and body composition measurement data at a physical store; means for transmitting the selfie image and body composition measurement data to the server in real time; means for the server to perform face mapping of the selfie image and analyze the user's physical characteristics based on the body composition measurement data; means for transmitting and displaying the suggestions on a display device in the physical store; means for the server to provide information on recommended beauty salons based on the user's location information; and means for the user to try on the suggested fashion items on the spot and purchase or rent them. This allows the user to receive suggestions for optimal fashion, hairstyles, and makeup based on the latest trends in real time at the physical store, and to try them on and receive treatments on the spot.

[1031] "User" refers to an individual who receives fashion, hairstyle, and makeup suggestions.

[1032] A "selfie" is an image that a user takes of themselves with a camera.

[1033] "Body composition measurement data" refers to data measuring the user's physical characteristics such as weight, body fat percentage, and muscle mass.

[1034] "Brick and mortar store" refers to a retail store that users can physically visit and that provides fashion and beauty-related services.

[1035] "Server" refers to a central processing unit that receives data sent by users, analyzes it, and returns the results.

[1036] "Face mapping" is a technology that analyzes the shape and features of a user's face from an image of their face.

[1037] A "fashion trend database" is a database that stores information on the latest trends in fashion, hairstyles, makeup, and more.

[1038] "Suggestion" refers to the server analyzing the user's data and presenting the most suitable fashion, hairstyle, and makeup.

[1039] "Display device" refers to equipment used to visually communicate the content of proposals to users, including tablets and smart displays.

[1040] "Location information" refers to information about the user's current location, and is data obtained via GPS or Wi-Fi.

[1041] "Beauty salon information" refers to information such as the location of the beauty salon, the services offered, and opening hours.

[1042] "Trying on" refers to the act of a user actually trying on a suggested fashion item.

[1043] "Purchase" refers to the act of a user paying a fee to own a suggested fashion item.

[1044] "Rental" is a service that allows users to borrow fashion items for a certain period of time.

[1045] This system allows users to input selfie photos and body composition measurement data in a physical store, and then suggests optimal fashion, hairstyles, and makeup. This system is comprised of a user terminal, a server, various devices installed in the physical store, and related components.

[1046] User Input

[1047] Users use a smart body composition scale in a physical store to measure their weight, body fat percentage, and other data. The measurement data is sent to a device in the store via Bluetooth or Wi-Fi. Next, the user takes a selfie using a dedicated camera installed in the store.

[1048] Data transmission and analysis

[1049] The in-store device transmits the captured selfie image and body composition measurement data in real time to a server equipped with a high-performance processing unit and AI algorithms (e.g., Python, TensorFlow, OpenCV).

[1050] Data analysis process

[1051] The server first analyzes the selfie image using face mapping technology to extract the user's facial shape and features. Next, it analyzes the user's physical characteristics (body type, body fat percentage, muscle mass, etc.) based on body composition measurement data. The results of this analysis are then compared with the latest fashion trend database (e.g., SQL database).

[1052] Generate and view suggestions

[1053] Based on the analysis results and trend data, the server will suggest the most suitable fashion items, hairstyles, and makeup for the user. The suggestions are sent to a display device (e.g., tablet or smart display) in the store, where the user can view them.

[1054] Proposal implementation and support

[1055] Users can try on suggested fashion items in a physical store and purchase or rent them on the spot. For suggested hairstyles and makeup, the server will provide location-based recommendations for hair salons and display reservation links.

[1056] Specific examples

[1057] User A (30 years old, female):

[1058] Visit a physical store and measure your weight and body fat percentage using a smart body composition scale.

[1059] Take a selfie using the store's dedicated camera.

[1060] The server analyzes the data and, based on face mapping and body composition data, suggests a pastel-colored dress, natural makeup, and a long hairstyle, referencing spring fashion trends.

[1061] Suggestions are displayed on a tablet in the store, and User A tries on the suggested fashion items in a fitting room.

[1062] Purchase your favorite items and get information on recommended hair salons.

[1063] Example prompt sentence:

[1064] "Generate optimal fashion, hairstyle, and makeup suggestions based on user images and body composition data."

[1065] Hardware and Software

[1066] Hardware:

[1067] Smart Body Composition Monitor

[1068] Dedicated camera

[1069] In-store tablets and smart displays

[1070] server

[1071] software:

[1072] Data transmission module (app)

[1073] Data Analysis Program

[1074] Face mapping technology (OpenCV)

[1075] Machine learning model (TensorFlow)

[1076] Display app (React.js or Vue.js)

[1077] This configuration allows users to receive the latest styling suggestions in real time at a physical store, and easily try on and purchase items.

[1078] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1079] Step 1:

[1080] The user visits a physical store and steps onto the smart body composition scale. The scale collects body composition measurement data, such as the user's weight, body fat percentage, and muscle mass. This data is sent to a terminal in the store via Bluetooth or Wi-Fi. The input is the body composition measurement data, and the output is the body composition measurement data sent to the terminal.

[1081] Step 2:

[1082] Users take selfies using a dedicated camera installed in the store. The captured image is saved on a terminal in the store. The input is the selfie image taken by the camera, and the output is the selfie image saved on the terminal.

[1083] Step 3:

[1084] The store terminal transmits the captured selfie image and body composition measurement data to the server in real time. The input is the selfie image and body composition measurement data, and the output is both data transmitted to the server. The terminal does this using a data transmission module.

[1085] Step 4:

[1086] When the server receives the selfie image, it uses face mapping technology (OpenCV) to analyze the shape and features of the user's face. The input is the selfie image, and the output is facial shape and feature data. The server identifies the boundary of the face and detects the positions of the eyes, nose, mouth, etc.

[1087] Step 5:

[1088] Next, the server analyzes the user's physical characteristics based on the body composition measurement data. The input is the body composition measurement data, and the output is detailed physical characteristic data such as body type, body fat percentage, and muscle mass. The server analyzes weight, body fat percentage, and muscle mass to create a body type profile for the user.

[1089] Step 6:

[1090] The server compares the analyzed facial feature data and physical characteristic data with the latest fashion trend database (SQL database). The input is facial feature data and physical characteristic data, and the output is suggested data based on the most suitable fashion trends. The server compares each data point with the trend information for each item and generates the optimal styling.

[1091] Step 7:

[1092] The server sends the generated proposals to a display device (tablet or smart display) in the store. The input is the proposal data, and the output is the proposal content displayed on the display device. The server sends the proposal content in JSON format, which the display device receives and displays visually.

[1093] Step 8:

[1094] The user reviews the displayed suggestions and tries on the suggested fashion items. The input is the suggestions and the items tried on, and the output is the user's feedback. The user tries on the items in the fitting room to check the fit and style.

[1095] Step 9:

[1096] If the user purchases or rents the suggested item, the server provides recommended salon information based on the user's location. The input is the user's location and the suggested item, and the output is salon information. The server searches for the most suitable salon based on the user's current location and the suggested item, and provides a link to make a reservation.

[1097] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1098] This is a new invention that combines an emotion engine with a system that allows users to input selfie photos and body composition measurement data and then suggests optimal fashion, hairstyles, and makeup based on that information. The system consists of a user's device, a server, an emotion engine, and affiliated beauty salons and rental shops.

[1099] System configuration

[1100] 1. User's device: On a device such as a smartphone or PC, users take selfies, input body composition measurement data, use the function to recognize the user's emotions, and check suggested styles.

[1101] 2. Server: Receives and analyzes data, recognizes emotions using the emotion engine, compares it with trend information, and generates and sends suggestions.

[1102] 3. Emotion Engine: Analyzes selfies and recognizes the user's emotional state.

[1103] 4. Beauty salons and rental shops: Providing services and items based on requests received from the server.

[1104] Program processing

[1105] The program processing within this system will be explained in natural language below.

[1106] 1. User enters data

[1107] Users use a dedicated smart body composition scale to measure their weight, body fat percentage, etc. The measurement data is sent to the user's device.

[1108] Next, the user takes a selfie with their device's camera and uploads it to the app.

[1109] 2. The device sends the data to the server

[1110] The device transmits the acquired selfie image, body composition measurement data, location information, and emotion data extracted by the emotion engine to the server.

[1111] 3. The server analyzes the data

[1112] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color.

[1113] At the same time, body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc.

[1114] 4. Emotion engine recognizes emotions

[1115] The server uses an emotion engine to recognize the user's emotions from the selfie image, using technology to determine emotions such as happiness, sadness, and surprise from the user's facial expressions.

[1116] 5. The server checks the data against the trend database.

[1117] The server compares the user's facial features, body type, and emotional data with the latest fashion trend database, and then selects the hairstyle, makeup, and fashion items that are best suited to the user.

[1118] 6. The server generates and sends a proposal

[1119] Based on the matching results, the server will suggest the best style for the user, including images of hairstyles, makeup routines, and photos and combinations of fashion items.

[1120] Based on emotional data, the suggested styles are adjusted to adapt to the user's current mental state.

[1121] Suggestions are sent to the user's device and displayed through the app.

[1122] 7. Providing beauty salon and rental services

[1123] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[1124] Similarly, the suggested fashion items are available for rental service, and users can send a request from their device. The rental shop will then process the delivery of the items.

[1125] Specific examples

[1126] User C (28 years old, female)

[1127] The user measures her weight and body fat percentage using a dedicated body composition scale, and uploads a selfie with her smartphone. The emotion engine detects the emotion of joy from her facial expression.

[1128] The server analyzes this data and matches the latest spring fashion trends based on User C's face shape and body type.

[1129] A light-colored dress, a casual jacket, and natural makeup are suggested, creating a style that brings out her joyful emotions.

[1130] The server recommends reputable local hair salons and stylists and provides booking links.

[1131] The suggested fashion items will be delivered to your home the next day using a rental service.

[1132] User D (35 years old, male)

[1133] The smart body composition scale measures his weight and body fat percentage, and he uploads a selfie with his smartphone. The emotion engine detects his fatigue and stress from his facial expressions.

[1134] The server analyzes the data and matches the latest fall fashion trends based on User D's face shape and body type.

[1135] A dark suit, a muted tie, and a simple hairstyle are recommended, all of which will help him look less tired.

[1136] In addition, it also provides information on nearby stores suitable for relaxation services and refreshing.

[1137] The suggested fashion items will be delivered to your home the next day using a rental service.

[1138] This allows users to easily find the perfect style that suits their emotional state and receive services at a beauty salon. Users can also rent suggested fashion items.

[1139] The processing flow will be explained below.

[1140] Step 1:

[1141] The user steps onto the dedicated smart body composition scale and obtains body composition measurement data such as weight, body fat percentage, muscle mass, etc. This data is automatically sent to the user's device.

[1142] Step 2:

[1143] The user launches a dedicated app and takes a selfie with their smartphone camera, which is then uploaded to the app.

[1144] Step 3:

[1145] The device sends the selfie image and body composition measurement data it has acquired to a server. The data is sent using a secure communication protocol, so it arrives safely at the server.

[1146] Step 4:

[1147] The server inputs the received selfie into an AI analysis algorithm to perform face mapping, which extracts features such as the user's facial shape, skin color, and hair texture.

[1148] Step 5:

[1149] The server analyzes the body composition measurement data and determines the user's physical characteristics such as height, weight, body fat percentage, and muscle mass.

[1150] Step 6:

[1151] The server inputs the selfie image into the emotion engine to recognize the user's emotions. The emotion engine determines the user's emotional state, such as joy, sadness, surprise, or anger, from their facial expressions.

[1152] Step 7:

[1153] The server compares the analysis results and emotional data with the latest fashion trend database, which includes information on the latest hairstyles, makeup, and fashion items.

[1154] Step 8:

[1155] The server selects the hairstyle, makeup, and fashion items that are best suited to the user and generates recommendations. Based on the emotional data, the server adjusts the recommendations to suit the user's specific emotional state.

[1156] Step 9:

[1157] The server generates and sends the recommendation information to the device, which includes images of specific hairstyles, makeup steps, and photos of fashion items and combinations.

[1158] Step 10:

[1159] The device displays the received recommendation information to the user, who can then check the suggested styles via the app and select the most appropriate suggestion based on their emotional state.

[1160] Step 11:

[1161] The server provides recommended hair salon information based on the user's location, and if the user wishes, a link to make a reservation at the appropriate salon is also provided.

[1162] Step 12:

[1163] If the user likes the suggested fashion item, they can send a rental request through the app.

[1164] Step 13:

[1165] The server receives the rental request and sends a request for the specified item to the affiliated rental shop.

[1166] Step 14:

[1167] The rental shop will confirm the request and prepare to deliver the specified fashion item to the user's address.

[1168] Step 15:

[1169] The user receives the rented fashion item and uses it for the specified period. After use, the rental item is returned.

[1170] By following these steps, users can easily find the style that best suits them and receive services at a beauty salon. They can also rent the suggested fashion items. The introduction of an emotion engine makes it possible to provide detailed suggestions based on the user's emotional state.

[1171] Example 2

[1172] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1173] Conventional fashion suggestion systems primarily make suggestions based on the user's physical characteristics and facial shape, without taking into account the user's emotional state. This can result in suggested styles that do not match the user's psychological state, resulting in reduced user satisfaction. Furthermore, when users wish to use specific services or products based on the suggestions, they must individually search for information and make reservations, which is inconvenient.

[1174] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1175] In this invention, the server includes means for face mapping a selfie image, analyzing physical characteristics based on body composition measurement data, and recognizing an emotional state using an emotion engine, means for comparing the analysis results and the emotional state with the latest fashion trend database to suggest optimal fashion, hairstyle, and makeup, and means for transmitting and displaying the suggestions to the user's terminal. This makes it possible to suggest styles that are adapted to the user's psychological state, and furthermore, by linking with information on beauty salons and fashion item rental services, it is possible to provide users with advanced and personalized services.

[1176] A "user" is a person who uses the system to input a selfie and body composition data and receive style suggestions.

[1177] A "selfie" is a photograph of the face or upper body taken by the user, and is data used for face mapping and emotion recognition.

[1178] "Body composition measurement data" refers to data relating to the user's body composition, such as weight, body fat percentage, and muscle mass, and is data used to analyze physical characteristics.

[1179] "Transmission means" refers to the function for transferring the selfie image, body composition measurement data, and emotion data to the server.

[1180] "Analysis means" refers to the algorithms and modules that process selfie images and body composition measurement data within the server and identify the user's facial shape and physical characteristics.

[1181] "Emotion engine" refers to the technology and algorithms used to extract and analyze a user's emotions from selfie images.

[1182] "Matching means" refers to an information processing function that matches the analysis results and emotional state with a fashion trend database and selects the most suitable fashion, hairstyle, and makeup for the user.

[1183] "Suggestion means" refers to a function for transmitting and displaying the fashion, hairstyle, and makeup suggestions generated by the server to the user's terminal.

[1184] "Location information" refers to information about a geographical location obtained from a user's device, and is data used to provide beauty salon information.

[1185] "Beauty salon information" is information about facilities that offer specific beauty services suggested based on the user's location information.

[1186] A "rental request" is a request submitted by a user to temporarily borrow a suggested fashion item.

[1187] "Rental Items" are fashion items that users can temporarily borrow through rental requests.

[1188] This system allows users to input selfie images, body composition measurement data, and emotion data extracted from the images, and then suggests optimal fashion, hairstyle, and makeup based on that information. The system consists of a user terminal, a server, an emotion engine, and affiliated beauty salons and rental shops.

[1189] User terminal

[1190] Using a device such as a smartphone or PC, the user takes a selfie, inputs body composition measurement data, executes a function that recognizes the user's emotions, and checks the suggested style. The user uses a smart body composition scale to measure data such as weight and body fat percentage. This measurement data is sent to the user's smartphone via Bluetooth. The user then takes a selfie using the smartphone camera and uploads it to a specific app.

[1191] server

[1192] The server stores the received selfie image, body composition measurement data, and emotion data in a connected database. Analysis of the received data is also performed on the server. Specifically, the server uses an image processing algorithm to perform face mapping and extract features such as the user's facial shape and skin color. At the same time, it analyzes the body composition measurement data to determine the user's body type, body fat percentage, and muscle mass.

[1193] The server then uses an emotion engine to recognize the user's emotions from the selfie. This emotion engine is a technology that determines emotions such as joy, sadness, and surprise from the user's facial expressions. The server then compares the analysis results and emotional state with the latest fashion trend database to suggest hairstyles, makeup, and fashion items that are best suited to the user. Suggestions include images of hairstyles, makeup steps, and photos and combinations of fashion items. Based on the emotion data, the suggested styles are adjusted to adapt to the user's current mental state. Suggestions are sent to the user's device and displayed through the app.

[1194] Hair salons and rental shops

[1195] If the user wishes to use the service based on the suggestions, the server provides information on recommended beauty salons and displays a reservation link. Furthermore, the suggested fashion items are available for rental, and a request can be sent from the user's device. The rental shop then processes the delivery of the items upon receiving the request.

[1196] Specific examples

[1197] User C (28 years old, female)

[1198] The user measures their weight and body fat percentage with a dedicated body composition scale, takes a selfie with their smartphone, and uploads it to the app. The emotion engine detects the emotion of joy from their facial expression.

[1199] The server analyzes this data and matches it with the latest spring fashion trends based on User C's face shape and body type.

[1200] We suggest a light-colored dress, a casual jacket, and natural makeup, which will bring out her joyful emotions.

[1201] The server recommends reputable local hair salons and stylists and provides booking links.

[1202] The suggested fashion items will be delivered to your home the next day using a rental service.

[1203] User D (35 years old, male)

[1204] The smart body composition scale measures his weight and body fat percentage, and he takes a selfie with his smartphone and uploads it. The emotion engine detects emotions such as fatigue and stress from his facial expressions.

[1205] The server analyzes the data and matches it with the latest fall fashion trends based on User D's face shape and body type.

[1206] A dark suit, a muted tie, and a simple hairstyle are recommended, which will help him look less tired.

[1207] In addition, it also provides information on nearby stores suitable for relaxation services and refreshing.

[1208] The suggested fashion items will be delivered to your home the next day using a rental service.

[1209] Prompt Sentence Examples

[1210] "A 28-year-old female user measured her weight and body fat percentage using a dedicated body composition scale and uploaded a selfie with her smartphone. The emotion engine detected the emotion of joy from her facial expression. Based on this user's face shape and body type, please match the latest spring fashion trends and suggest a bright-colored dress and natural makeup."

[1211] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1212] Step 1: User takes a selfie and enters body composition measurement data

[1213] The user uses a dedicated smart body composition scale to measure data such as weight and body fat percentage. This measurement data is sent to the user's smartphone via Bluetooth. The user then takes a selfie using the smartphone camera and uploads it to a dedicated app. This provides the selfie image and body composition measurement data as input data.

[1214] Step 2: The device sends the data to the server

[1215] The device sends the captured selfie image, body composition measurement data, location information, and emotion data extracted by the emotion engine to the server. Specifically, all data collected by the smartphone application (images, measurement data, location information, emotion data) is securely sent to the server using the HTTPS protocol. This sends the input data to the server.

[1216] Step 3: The server parses the data

[1217] The server performs face mapping based on the received selfie image, extracting features such as the user's facial shape, skin color, and contours. A facial recognition module is used for this analysis. At the same time, body composition measurement data is analyzed to determine the user's body type, body fat percentage, and muscle mass. Specifically, the face mapping algorithm analyzes the selfie image and identifies facial feature points (such as the position of the eyes, nose, and mouth), and the body composition data analysis module calculates the user's physical characteristics based on the measurement data. This outputs facial shape data and physical characteristic data.

[1218] Step 4: The emotion engine recognizes the emotion

[1219] The server recognizes the user's emotions from the selfie image through the emotion engine. The emotion engine analyzes the user's facial expressions from the image and determines emotions such as joy, sadness, and surprise. Specifically, the emotion engine analyzes the subtle movements of the face to evaluate the user's emotional state, which then outputs the user's emotional data.

[1220] Step 5: The server checks against the trend database

[1221] The server compares the user's facial features, body type data, and emotional data with the latest fashion trend database. This allows the system to select the hairstyle, makeup, and fashion items that are best suited to the user. Specifically, the server executes a database query to search the latest fashion trend information and identify the most suitable style. This results in the output of optimized fashion suggestion data.

[1222] Step 6: Server generates and sends proposal

[1223] Based on the matching results, the server suggests the optimal style for the user. The suggestions include images of hairstyles, makeup routines, and photos and combinations of fashion items. Based on emotional data, the suggested style is adjusted to suit the user's current mental state. Specifically, the server encodes the suggested data in JSON format and sends it to the smartphone app via push notification. The suggested data is then displayed on the user's device.

[1224] Step 7: Provide beauty salon and rental services

[1225] If the user wishes to use a service based on the suggestions, the server provides information about recommended beauty salons and displays a reservation link. Furthermore, rental services are available for the suggested fashion items, and a request can be sent from the user's device. The rental shop receives the request and arranges for delivery of the items. Specifically, the server analyzes reputation data for nearby beauty salons, selects the most suitable salon, and displays it to the user. The rental request is also linked to the rental shop's system, which checks inventory and initiates delivery procedures. This allows users to easily use the appropriate beauty services and fashion items.

[1226] (Application example 2)

[1227] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1228] In today's world, selecting the best fashion, hairstyle, and makeup for each individual user can be difficult given the wide variety of options and trend information available. While it is important to provide style suggestions that take into account each user's emotional state and physical characteristics, systems that can effectively reflect these are still lacking. Furthermore, there is a need for a simple way to actually apply the suggested styles (by making a salon appointment or renting fashion items).

[1229] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for comparing the analysis results and the emotion data recognized by the emotion engine with the latest fashion trend database and suggesting optimal fashion, hairstyle, and makeup for the user, means for virtually displaying the suggested styles on the user's terminal in real time, and means for transmitting and displaying the suggestions on the user's terminal. This enables the system to suggest optimal styles based on the user's emotional state and physical characteristics and to enable the user to virtually try on those styles.

[1230] A "user terminal" is an electronic device used by a user to operate the device, such as a smartphone or a personal computer.

[1231] A "server" is a computer system that receives data, analyzes it, recognizes emotions, generates suggestions, and transmits the information to the user's device.

[1232] A "selfie" refers to a photograph of the user's face taken by the user themselves, and is used to analyze facial features.

[1233] "Body composition measurement data" is measurement data that indicates the user's physical characteristics such as weight and body fat percentage.

[1234] "Face mapping" is a technology that analyzes the shape and features of a user's face based on a selfie image.

[1235] The "Emotion Engine" is a technology that analyzes and recognizes a user's emotional state from selfie images.

[1236] The "Fashion Trend Database" is a database that stores information on the latest fashions, hairstyles, and makeup.

[1237] "Virtual display means" refers to a technology that allows users to virtually visualize styles that they have not actually tried and check them on their device.

[1238] "Location Information" is data that indicates a user's current geographic location.

[1239] "Beauty salon information" is information about a beauty salon, including the salon name, location, reservation status, and the like.

[1240] "Fashion items" are fashion-related products such as clothing and accessories.

[1241] "Rental" refers to a service in which users temporarily borrow fashion items to use for a certain period of time.

[1242] This system uses a user's selfie photos and body composition measurement data to suggest optimal fashion, hairstyles, and makeup, and combines it with an emotion engine. The system consists of a user's device, a server, an emotion engine, and affiliated beauty salons and rental shops.

[1243] System configuration

[1244] 1. User Device

[1245] Input method: Users take selfies and input body composition measurement data using devices such as smartphones and PCs. Specific devices include iPhones, Android smartphones, and Windows PCs.

[1246] Virtual display means: The system has the function of visualizing the proposed style in real time on the device, allowing users to virtually try out the style.

[1247] 2. Server

[1248] Analysis method: The server performs face mapping based on the uploaded selfie image and analyzes the user's facial shape and features. It also analyzes physical characteristics based on body composition measurement data. The server processes data using cloud services such as Google Cloud Platform and AWS.

[1249] Emotion Recognition: Recognize the user's emotional state from selfies through an emotion engine, built using machine learning libraries such as TensorFlow.

[1250] Matching: The analysis results and sentiment data are matched with the latest fashion trend database to suggest the most suitable fashion, hairstyle, and makeup for the user. The trend database collects the latest industry information and is updated regularly.

[1251] 3. Affiliated hair salons and rental shops

[1252] Information provision: Based on the user's location, the service provides recommended hair salons. Hair salons are registered in a database in advance and selected based on ratings and user feedback.

[1253] Rental service: Users can submit rental requests for suggested fashion items, which are then sent to affiliated rental shops, which then process the delivery of the items.

[1254] Specific examples

[1255] User C (28 years old, female):

[1256] She measures her weight and body fat percentage with a dedicated body composition scale and uploads a selfie with her smartphone. The emotion engine detects the emotion of joy from her facial expression. The server analyzes this data and matches the latest spring fashion trends based on User C's face shape and body type. It suggests a bright-colored dress, a casual jacket, and natural makeup. This selects a style that will bring out her emotion of joy. The server then provides information on reputable local hair salons and displays a link to make a reservation. The suggested fashion items are delivered to her home the next day using a rental service.

[1257] User D (35 years old, male):

[1258] The user measures his weight and body fat percentage with a smart body composition scale and uploads a selfie image on his smartphone. The emotion engine detects feelings of fatigue and stress from his facial expressions. The server analyzes the data and matches the latest autumn fashion trends based on User D's facial shape and body type. It suggests a dark-colored suit, a tie in a muted tone, and a simple hairstyle. This selects a style that will relieve his fatigue. It also provides information on nearby stores suitable for relaxation services and refreshing. The suggested fashion items are delivered to his home the next day using a rental service.

[1259] Prompt Sentence Examples

[1260] "We analyzed User A's selfies and identified her happy emotions. Based on the latest spring fashion trends, we suggest the following style. A casual navy cardigan and denim combination with a striped shirt would look good on her."

[1261] This allows users to easily find the style that best suits their emotional state and physical characteristics, and also makes it easier to use services at beauty salons and rent fashion items.

[1262] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1263] Step 1:

[1264] Users take a selfie using a device such as a smartphone or PC, and a dedicated smart body composition scale acquires body composition measurement data such as weight and body fat percentage. The user's device receives this data and uploads the selfie and body composition measurement data to the app. The input data is the selfie and body composition measurement data, and the output is the uploaded user data.

[1265] Step 2:

[1266] The user device sends the uploaded selfie image and body composition measurement data to the server using a secure communication protocol (e.g., HTTPS). The input data are the selfie image and body composition measurement data obtained in the previous step, and the output is the data transferred to the server.

[1267] Step 3:

[1268] The server performs face mapping based on the received selfie image. This face mapping uses image processing libraries such as OpenCV to analyze the shape and features of the face. The input data is the selfie image, and the output is data that shows the shape and features of the user's face.

[1269] Step 4:

[1270] The server analyzes the body composition measurement data and identifies the user's physical characteristics (body type, body fat percentage, muscle mass, etc.). Data science tools (e.g., Pandas, NumPy) are used for the analysis. The input data is the body composition measurement data, and the output is the analyzed physical characteristic data.

[1271] Step 5:

[1272] The server uses an emotion engine to recognize the user's emotional state from the selfie image. It uses deep learning libraries such as TensorFlow to run emotion recognition models and identify emotions such as joy, sadness, and surprise. The input data is the selfie image, and the output is the recognized emotion data.

[1273] Step 6:

[1274] The server compares the user's facial features, physical characteristics, and emotional data with the latest fashion trend database. The fashion trend database is managed on the cloud and updated with the latest industry information. The input data is face mapping data, physical characteristics data, and emotional data, and the output is data suggesting the most suitable fashion, hairstyle, and makeup for the user.

[1275] Step 7:

[1276] The server sends the generated proposal to the user's device, which then virtually displays the proposed style in real time, allowing the user to virtually try out the proposed style. The input data is the proposal data, and the output is the virtual style displayed on the user's device.

[1277] Step 8:

[1278] If the user accepts the proposed style, the user device sends a request to the affiliated hair salon or rental shop. The input data is the user's request, and the output is the salon reservation information and the delivery procedure for the rental items.

[1279] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1280] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1281] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1282] [Fourth embodiment]

[1283] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1284] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1285] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1286] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1287] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1288] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1289] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1290] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1291] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1292] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1293] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1294] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1295] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1296] This system allows users to input their selfie photos and body composition measurement data, and based on that information, it suggests optimal fashion, hairstyles, and makeup. The system consists of a user's device, a server, and affiliated beauty salons and rental shops.

[1297] System configuration

[1298] 1. User's device: On a device such as a smartphone or computer, users take a selfie, enter body composition measurement data, and check suggested styles.

[1299] 2. Server: Receives data, analyzes it, compares it with trend information, and generates and sends recommendations.

[1300] 3. Beauty salons and rental shops: Providing services and items based on requests received from the server.

[1301] Program processing

[1302] The program processing within this system will be explained in natural language below.

[1303] 1. User enters data

[1304] Users use a dedicated smart body composition scale to measure their weight, body fat percentage, etc. The measurement data is sent to the user's device.

[1305] Next, the user takes a selfie using the device's camera and uploads it to the app.

[1306] 2. The device sends the data to the server

[1307] The device sends the captured selfie image and body composition measurement data to the server.

[1308] 3. The server analyzes the data

[1309] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color.

[1310] At the same time, body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc.

[1311] 4. The server checks the data against the trend database.

[1312] The server compares facial features and body type data with the latest fashion trend database, and then selects hairstyles, makeup, and fashion items that are best suited to the user.

[1313] 5. The server generates and sends a proposal

[1314] Based on the results of the comparison, the server will suggest the best style for the user, including an image of the hairstyle, detailed makeup instructions, and a combination of fashion items.

[1315] Suggestions are sent to the user's device and displayed through the app.

[1316] 6. Providing beauty salon and rental services

[1317] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[1318] Similarly, for the suggested fashion items, rental services are available, and users can send requests from their devices. The rental shop will then process the delivery of the items.

[1319] Specific examples

[1320] User A (32 years old, female)

[1321] Measure your weight and body fat percentage using a dedicated body composition scale, and upload a selfie photo using your smartphone.

[1322] The server analyzes this data and matches the latest summer fashion trends based on User A's face shape and body type.

[1323] We suggest a lightweight jacket in cool colors, shorts, and natural makeup.

[1324] The server recommends reputable local hair salons and stylists and provides booking links.

[1325] The suggested fashion items will be delivered to your home the next day using a rental service.

[1326] User B (45 years old, male)

[1327] Measure your weight and body fat percentage with a smart body composition scale and upload a selfie using your smartphone.

[1328] The server analyzes the data and matches it with the latest autumn fashion trends based on the sharp features of User B's jawline.

[1329] We suggest a dark green jacket, gray pants, and loafers.

[1330] The server recommends the best two-block hairstyle and provides information on nearby hair salons and a link to make a reservation.

[1331] The suggested fashion items will be delivered to your home the next day using a rental service.

[1332] This allows users to easily enjoy styles that incorporate the latest trends.

[1333] The processing flow will be explained below.

[1334] Step 1:

[1335] The user steps onto the dedicated smart body composition scale and obtains body composition measurement data such as weight, body fat percentage, muscle mass, etc. This data is automatically sent to the user's device.

[1336] Step 2:

[1337] The user launches a dedicated app and takes a selfie with their smartphone camera, which is then uploaded to the app.

[1338] Step 3:

[1339] The device sends the selfie image and body composition measurement data it has acquired to a server. The data is sent using a secure communication protocol, so it arrives safely at the server.

[1340] Step 4:

[1341] The server inputs the received selfie into an AI analysis algorithm to perform face mapping, which extracts features such as the user's facial shape, skin color, and hair texture.

[1342] Step 5:

[1343] The server analyzes the body composition measurement data and determines the user's physical characteristics such as height, weight, body fat percentage, and muscle mass.

[1344] Step 6:

[1345] The server compares the analysis results with a database of current fashion trends, which includes information on the latest hairstyles, makeup, and fashion items.

[1346] Step 7:

[1347] The server selects the hairstyle, makeup, and fashion items that are best suited to the user and generates them as recommendation information.

[1348] Step 8:

[1349] The server generates and sends the recommendation information to the device, which includes images of specific hairstyles, makeup steps, and photos of fashion items and combinations.

[1350] Step 9:

[1351] The device displays the received recommendation information to the user, who can then check the suggested styles via the app.

[1352] Step 10:

[1353] The server provides recommended hair salon information based on the user's location, and if the user wishes, a link to make a reservation at the appropriate salon is also provided.

[1354] Step 11:

[1355] If the user likes the suggested fashion item, they can send a rental request through the app.

[1356] Step 12:

[1357] The server receives the rental request and sends a request for the specified item to the affiliated rental shop.

[1358] Step 13:

[1359] The rental shop will confirm the request and prepare to deliver the specified fashion item to the user's address.

[1360] Step 14:

[1361] The user receives the rented fashion item and uses it for the specified period. After use, the rental item is returned.

[1362] By following these steps, users can easily find the style that best suits them and receive services at a beauty salon. They can also rent suggested fashion items.

[1363] Example 1

[1364] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1365] Conventional systems have had difficulty fully reflecting individual physical characteristics and the latest fashion trends when proposing fashion, hairstyles, and makeup that are suited to a user's appearance. Furthermore, the content of the proposals was limited to static information, and the provision of specific advice and recommendations that were highly practical for users was insufficient. This led to a problem of lower user satisfaction with improvements to their style.

[1366] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1367] In this invention, the server includes means for face mapping a selfie image and analyzing the user's physical characteristics based on body composition measurement data, means for comparing the results with a trend database to suggest optimal fashion, hairstyle, and makeup for the user, and means for automatically generating details of the suggestions using a generative AI model and providing them to the user. This makes it possible to suggest specific styles that reflect individual physical characteristics and the latest trends, as well as provide highly practical, detailed advice.

[1368] A "selfie" refers to an image of a user's face or body taken by the user themselves.

[1369] "Body composition measurement data" refers to data regarding the user's physical composition, such as weight, body fat percentage, and muscle mass.

[1370] "Server" refers to the computer system responsible for analyzing the data it receives, collating it, generating suggestions, and sending them to the user.

[1371] "Face mapping" refers to the process of using image analysis technology to extract facial shapes and features from selfies.

[1372] "Physical characteristics" refers to a user's physical characteristics such as body shape, skin color, and body fat percentage.

[1373] A "trend database" refers to a database that stores information about the latest fashions, hairstyles, and makeup.

[1374] "Fashion" refers to the style of clothing, accessories, etc.

[1375] "Hairstyle" refers to the design or style of a hairstyle.

[1376] "Makeup" refers to the method and style of applying makeup.

[1377] A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to analyze text, images, and data.

[1378] "Suggestions" refers to specific advice and information about fashion, hairstyles, and makeup provided to users.

[1379] "User's device" refers to a device such as a smartphone or computer used by the user.

[1380] "Location Information" means information that indicates a User's current geographic location.

[1381] "Hair Salon Information" refers to data and booking links about hair salons recommended to users.

[1382] "Rental items" refer to fashion items that users can borrow temporarily.

[1383] This invention is a system that allows users to input selfie photos and body composition measurement data, and based on that information, suggests optimal fashion, hairstyles, and makeup. The system is composed of a user's terminal, a server, and affiliated service providers.

[1384] System configuration

[1385] 1. User's Device

[1386] The user's device is a device such as a smartphone or PC. The user uses these devices to take selfies, input body composition measurement data, and check the suggested style. Specific examples include iPhones and Android devices.

[1387] 2. Server

[1388] The server receives and analyzes the data, compares it with trend information, and generates and sends proposals. A specific example is an EC2 instance on AWS, which uses cloud services. The server analyzes the data using OpenCV, a facial recognition library, and TensorFlow, a machine learning framework, and automatically generates details of the proposals using a generative AI model (e.g., GPT-3).

[1389] 3. Affiliated Service Providers

[1390] The affiliated service providers are beauty salons and fashion rental shops that provide services and items to users. These service providers provide services and items based on requests received from the server.

[1391] Program processing

[1392] The program processing within this system will be explained in natural language below.

[1393] 1. The user enters data

[1394] The user uses a dedicated smart body composition scale (for example, a general body composition scale) to measure weight, body fat percentage, etc. The measurement data is sent to a device (for example, an iPhone).

[1395] Next, the user takes a selfie using the device's camera and uploads it to the app. "Tap the 'Measure' button on the home screen, and once the measurement is complete, the data will be automatically transferred to the app. Then tap the 'Camera' button to take a selfie, and press the 'Upload' button to send the data to the server."

[1396] 2. The device sends the data to the server

[1397] The device sends the selfie image and body composition measurement data captured by the user to a server via Wi-Fi or mobile data communication using an encrypted communication protocol (e.g., HTTPS).

[1398] 3. The server analyzes the data

[1399] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color. The software used here is a facial recognition library (e.g., OpenCV).

[1400] At the same time, the body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc. A machine learning model (for example, a model using TensorFlow) is used for the analysis.

[1401] 4. The server checks the data against the trend database.

[1402] The server compares the facial features and body shape data with the latest fashion trend database (for example, trend information stored in MongoDB), and then selects the best hairstyle, makeup, and fashion item for the user.

[1403] 5. The server generates and sends a proposal

[1404] Based on the matching results, the server suggests the best style for the user. The suggestions include hairstyle images, detailed makeup instructions, and combinations of fashion items. Using a generative AI model (e.g., GPT-3), fashion advice and makeup instructions are written in natural-sounding sentences.

[1405] Suggestions are sent to the user's device and displayed through a dedicated app.

[1406] 6. Provision of Services

[1407] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[1408] Similarly, for the suggested fashion items, rental services (e.g., general rental shops) are available, and a request can be sent from the user terminal. The rental shop will then process the delivery of the item.

[1409] Examples and prompts

[1410] When user A takes photos and enters data

[1411] User A takes measurements using a standard body composition scale, then takes a selfie using an iPhone app. "On the home screen, tap the 'Measure' button, and once the measurement is complete, the data is automatically transferred to the app. Then, tap the 'Camera' button to take a selfie, and press the 'Upload' button to send the data to the server."

[1412] Example prompts for generative AI models

[1413] "User A is a 32-year-old woman who wants to improve her appearance. Please suggest the best summer fashion and makeup for her based on her body composition measurement data and selfies."

[1414] This allows users to easily enjoy styles that incorporate the latest trends.

[1415] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1416] Step 1:

[1417] The user enters data

[1418] Input: Data such as weight and body fat percentage measured by the user using a dedicated smart body composition scale (e.g., a general body composition scale), and a selfie image.

[1419] Specific operation: The user uses a body composition scale to measure their weight and body fat percentage. This measurement data is automatically sent to a smartphone (e.g., iPhone) via Bluetooth. The user then takes a selfie using the smartphone's camera and uploads it to the app. Specifically, the user taps the "Measure" button on the home screen, and once the measurement is complete, the data is transferred to the app. Next, the user taps the "Camera" button to take a selfie, and then presses the "Upload" button to prepare for data transmission.

[1420] Output: Body composition measurement data and selfie images are saved on the user's device.

[1421] Step 2:

[1422] The device sends the data to the server

[1423] Input: Body composition measurement data and selfie images stored on the user's device.

[1424] What it does: Your device sends the stored data to the server over Wi-Fi or mobile data using an encrypted communication protocol (e.g., HTTPS). Specifically, when you tap the "Send Data" button, the data is sent to the server via HTTPS.

[1425] Output: Body composition measurement data and selfie image sent to the server.

[1426] Step 3:

[1427] The server analyzes the data

[1428] Input: Body composition measurement data and selfie image sent to the server.

[1429] How it works: The server analyzes the selfie image using a facial recognition library (e.g., OpenCV). It performs face mapping and extracts features such as the user's facial shape, skin color, and the position of the eyes and nose. In parallel, it applies a machine learning model (e.g., a model using TensorFlow) to the body composition measurement data to analyze the user's body shape, body fat percentage, and muscle mass. This includes applying a face detection algorithm and classifying and regressing the body composition data.

[1430] Output: The user's facial feature data and body shape data.

[1431] Step 4:

[1432] The server checks against the trend database

[1433] Input: User's facial feature data, body shape data, and a database of the latest fashion trends (e.g., trend information stored in MongoDB).

[1434] What it does: The server uses an algorithm to match the information in the trends database with the user's facial features and body data. Specifically, it pulls images of models and fashion items with similar face shapes and body types from the database. This includes image recognition algorithms and calculating a relevance score.

[1435] Output: A list of suggested fashion, hairstyle, and makeup looks that suit the user.

[1436] Step 5:

[1437] The server generates and sends the proposal

[1438] Input: A list of suggested fashion, hairstyle, and makeup looks for the user.

[1439] Specific operation: The server uses a generative AI model (e.g., GPT-3) to generate natural-sounding text about fashion advice and makeup techniques. Using this information, it generates a report proposing the optimal style for the user. This report includes an image of the hairstyle, detailed makeup steps, and a combination of fashion items. The report is then sent to the user's device using the HTTPS protocol. Specifically, it executes the "suggestion generation" function and sends the generated report to the user.

[1440] Output: The proposal report is sent to the user's device and displayed through the app.

[1441] Step 6:

[1442] Hair salon and rental services will be provided.

[1443] Input: Proposal report sent to user, user location information.

[1444] Specific operation: If the user uses a service based on the suggestions, the system will provide recommended hair salon information and display a reservation link. Furthermore, the suggested fashion items are available for rental services (e.g., general rental shops), and the user can send a request from their device. The rental shop will then process the delivery of the items upon receiving the request. Specifically, the user taps the "Send Request" button on the rental service, and the request is sent via the server.

[1445] Output: The user's device will be notified of the completion of the hair salon reservation and the scheduled delivery of the rental items.

[1446] (Application example 1)

[1447] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1448] It is difficult for users to easily find the fashion, hairstyle, and makeup that best suits them. Especially in physical stores, it takes time and effort for users to instantly check, try on, and apply styling that suits them. It is also uncertain whether the styling provided is based on the latest trends. Furthermore, an efficient system is needed to improve the user experience through real-time service provision in physical stores.

[1449] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1450] In this invention, the server includes: means for a user to input a selfie image and body composition measurement data at a physical store; means for transmitting the selfie image and body composition measurement data to the server in real time; means for the server to perform face mapping of the selfie image and analyze the user's physical characteristics based on the body composition measurement data; means for transmitting and displaying the suggestions on a display device in the physical store; means for the server to provide information on recommended beauty salons based on the user's location information; and means for the user to try on the suggested fashion items on the spot and purchase or rent them. This allows the user to receive suggestions for optimal fashion, hairstyles, and makeup based on the latest trends in real time at the physical store, and to try them on and receive treatments on the spot.

[1451] "User" refers to an individual who receives fashion, hairstyle, and makeup suggestions.

[1452] A "selfie" is an image that a user takes of themselves with a camera.

[1453] "Body composition measurement data" refers to data measuring the user's physical characteristics such as weight, body fat percentage, and muscle mass.

[1454] "Brick and mortar store" refers to a retail store that users can physically visit and that provides fashion and beauty-related services.

[1455] "Server" refers to a central processing unit that receives data sent by users, analyzes it, and returns the results.

[1456] "Face mapping" is a technology that analyzes the shape and features of a user's face from an image of their face.

[1457] A "fashion trend database" is a database that stores information on the latest trends in fashion, hairstyles, makeup, and more.

[1458] "Suggestion" refers to the server analyzing the user's data and presenting the most suitable fashion, hairstyle, and makeup.

[1459] "Display device" refers to equipment used to visually communicate the content of proposals to users, including tablets and smart displays.

[1460] "Location information" refers to information about the user's current location, and is data obtained via GPS or Wi-Fi.

[1461] "Beauty salon information" refers to information such as the location of the beauty salon, the services offered, and opening hours.

[1462] "Trying on" refers to the act of a user actually trying on a suggested fashion item.

[1463] "Purchase" refers to the act of a user paying a fee to own a suggested fashion item.

[1464] "Rental" is a service that allows users to borrow fashion items for a certain period of time.

[1465] This system allows users to input selfie photos and body composition measurement data in a physical store, and then suggests optimal fashion, hairstyles, and makeup. This system is comprised of a user terminal, a server, various devices installed in the physical store, and related components.

[1466] User Input

[1467] Users use a smart body composition scale in a physical store to measure their weight, body fat percentage, and other data. The measurement data is sent to a device in the store via Bluetooth or Wi-Fi. Next, the user takes a selfie using a dedicated camera installed in the store.

[1468] Data transmission and analysis

[1469] The in-store device transmits the captured selfie image and body composition measurement data in real time to a server equipped with a high-performance processing unit and AI algorithms (e.g., Python, TensorFlow, OpenCV).

[1470] Data analysis process

[1471] The server first analyzes the selfie image using face mapping technology to extract the user's facial shape and features. Next, it analyzes the user's physical characteristics (body type, body fat percentage, muscle mass, etc.) based on body composition measurement data. The results of this analysis are then compared with the latest fashion trend database (e.g., SQL database).

[1472] Generate and view suggestions

[1473] Based on the analysis results and trend data, the server will suggest the most suitable fashion items, hairstyles, and makeup for the user. The suggestions are sent to a display device (e.g., tablet or smart display) in the store, where the user can view them.

[1474] Proposal implementation and support

[1475] Users can try on suggested fashion items in a physical store and purchase or rent them on the spot. For suggested hairstyles and makeup, the server will provide location-based recommendations for hair salons and display reservation links.

[1476] Specific examples

[1477] User A (30 years old, female):

[1478] Visit a physical store and measure your weight and body fat percentage using a smart body composition scale.

[1479] Take a selfie using the store's dedicated camera.

[1480] The server analyzes the data and, based on face mapping and body composition data, suggests a pastel-colored dress, natural makeup, and a long hairstyle, referencing spring fashion trends.

[1481] Suggestions are displayed on a tablet in the store, and User A tries on the suggested fashion items in a fitting room.

[1482] Purchase your favorite items and get information on recommended hair salons.

[1483] Example prompt sentence:

[1484] "Generate optimal fashion, hairstyle, and makeup suggestions based on user images and body composition data."

[1485] Hardware and Software

[1486] Hardware:

[1487] Smart Body Composition Monitor

[1488] Dedicated camera

[1489] In-store tablets and smart displays

[1490] server

[1491] software:

[1492] Data transmission module (app)

[1493] Data Analysis Program

[1494] Face mapping technology (OpenCV)

[1495] Machine learning model (TensorFlow)

[1496] Display app (React.js or Vue.js)

[1497] This configuration allows users to receive the latest styling suggestions in real time at a physical store, and easily try on and purchase items.

[1498] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1499] Step 1:

[1500] The user visits a physical store and steps onto the smart body composition scale. The scale collects body composition measurement data, such as the user's weight, body fat percentage, and muscle mass. This data is sent to a terminal in the store via Bluetooth or Wi-Fi. The input is the body composition measurement data, and the output is the body composition measurement data sent to the terminal.

[1501] Step 2:

[1502] Users take selfies using a dedicated camera installed in the store. The captured image is saved on a terminal in the store. The input is the selfie image taken by the camera, and the output is the selfie image saved on the terminal.

[1503] Step 3:

[1504] The store terminal transmits the captured selfie image and body composition measurement data to the server in real time. The input is the selfie image and body composition measurement data, and the output is both data transmitted to the server. The terminal does this using a data transmission module.

[1505] Step 4:

[1506] When the server receives the selfie image, it uses face mapping technology (OpenCV) to analyze the shape and features of the user's face. The input is the selfie image, and the output is facial shape and feature data. The server identifies the boundary of the face and detects the positions of the eyes, nose, mouth, etc.

[1507] Step 5:

[1508] Next, the server analyzes the user's physical characteristics based on the body composition measurement data. The input is the body composition measurement data, and the output is detailed physical characteristic data such as body type, body fat percentage, and muscle mass. The server analyzes weight, body fat percentage, and muscle mass to create a body type profile for the user.

[1509] Step 6:

[1510] The server compares the analyzed facial feature data and physical characteristic data with the latest fashion trend database (SQL database). The input is facial feature data and physical characteristic data, and the output is suggested data based on the most suitable fashion trends. The server compares each data point with the trend information for each item and generates the optimal styling.

[1511] Step 7:

[1512] The server sends the generated proposals to a display device (tablet or smart display) in the store. The input is the proposal data, and the output is the proposal content displayed on the display device. The server sends the proposal content in JSON format, which the display device receives and displays visually.

[1513] Step 8:

[1514] The user reviews the displayed suggestions and tries on the suggested fashion items. The input is the suggestions and the items tried on, and the output is the user's feedback. The user tries on the items in the fitting room to check the fit and style.

[1515] Step 9:

[1516] If the user purchases or rents the suggested item, the server provides recommended salon information based on the user's location. The input is the user's location and the suggested item, and the output is salon information. The server searches for the most suitable salon based on the user's current location and the suggested item, and provides a link to make a reservation.

[1517] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1518] This is a new invention that combines an emotion engine with a system that allows users to input selfie photos and body composition measurement data and then suggests optimal fashion, hairstyles, and makeup based on that information. The system consists of a user's device, a server, an emotion engine, and affiliated beauty salons and rental shops.

[1519] System configuration

[1520] 1. User's device: On a device such as a smartphone or PC, users take selfies, input body composition measurement data, use the function to recognize the user's emotions, and check suggested styles.

[1521] 2. Server: Receives and analyzes data, recognizes emotions using the emotion engine, compares it with trend information, and generates and sends suggestions.

[1522] 3. Emotion Engine: Analyzes selfies and recognizes the user's emotional state.

[1523] 4. Beauty salons and rental shops: Providing services and items based on requests received from the server.

[1524] Program processing

[1525] The program processing within this system will be explained in natural language below.

[1526] 1. User enters data

[1527] Users use a dedicated smart body composition scale to measure their weight, body fat percentage, etc. The measurement data is sent to the user's device.

[1528] Next, the user takes a selfie with their device's camera and uploads it to the app.

[1529] 2. The device sends the data to the server

[1530] The device transmits the acquired selfie image, body composition measurement data, location information, and emotion data extracted by the emotion engine to the server.

[1531] 3. The server analyzes the data

[1532] The server performs face mapping based on the received selfie image and extracts features such as the user's facial shape and skin color.

[1533] At the same time, body composition measurement data is analyzed to determine the user's body shape, body fat percentage, muscle mass, etc.

[1534] 4. Emotion engine recognizes emotions

[1535] The server uses an emotion engine to recognize the user's emotions from the selfie image, using technology to determine emotions such as happiness, sadness, and surprise from the user's facial expressions.

[1536] 5. The server checks the data against the trend database.

[1537] The server compares the user's facial features, body type, and emotional data with the latest fashion trend database, and then selects the hairstyle, makeup, and fashion items that are best suited to the user.

[1538] 6. The server generates and sends a proposal

[1539] Based on the matching results, the server will suggest the best style for the user, including images of hairstyles, makeup routines, and photos and combinations of fashion items.

[1540] Based on emotional data, the suggested styles are adjusted to adapt to the user's current mental state.

[1541] Suggestions are sent to the user's device and displayed through the app.

[1542] 7. Providing beauty salon and rental services

[1543] If the user wishes to use a service based on the suggestions, they will be provided with recommended salon information and a booking link.

[1544] Similarly, the suggested fashion items are available for rental service, and users can send a request from their device. The rental shop will then process the delivery of the items.

[1545] Specific examples

[1546] User C (28 years old, female)

[1547] The user measures her weight and body fat percentage using a dedicated body composition scale, and uploads a selfie with her smartphone. The emotion engine detects the emotion of joy from her facial expression.

[1548] The server analyzes this data and matches the latest spring fashion trends based on User C's face shape and body type.

[1549] A light-colored dress, a casual jacket, and natural makeup are suggested, creating a style that brings out her joyful emotions.

[1550] The server recommends reputable local hair salons and stylists and provides booking links.

[1551] The suggested fashion items will be delivered to your home the next day using a rental service.

[1552] User D (35 years old, male)

[1553] The smart body composition scale measures his weight and body fat percentage, and he uploads a selfie with his smartphone. The emotion engine detects his fatigue and stress from his facial expressions.

[1554] The server analyzes the data and matches the latest fall fashion trends based on User D's face shape and body type.

[1555] A dark suit, a muted tie, and a simple hairstyle are recommended, all of which will help him look less tired.

[1556] In addition, it also provides information on nearby stores suitable for relaxation services and refreshing.

[1557] The suggested fashion items will be delivered to your home the next day using a rental service.

[1558] This allows users to easily find the perfect style that suits their emotional state and receive services at a beauty salon. Users can also rent suggested fashion items.

[1559] The processing flow will be explained below.

[1560] Step 1:

[1561] The user steps onto the dedicated smart body composition scale and obtains body composition measurement data such as weight, body fat percentage, muscle mass, etc. This data is automatically sent to the user's device.

[1562] Step 2:

[1563] The user launches a dedicated app and takes a selfie with their smartphone camera, which is then uploaded to the app.

[1564] Step 3:

[1565] The device sends the selfie image and body composition measurement data it has acquired to a server. The data is sent using a secure communication protocol, so it arrives safely at the server.

[1566] Step 4:

[1567] The server inputs the received selfie into an AI analysis algorithm to perform face mapping, which extracts features such as the user's facial shape, skin color, and hair texture.

[1568] Step 5:

[1569] The server analyzes the body composition measurement data and determines the user's physical characteristics such as height, weight, body fat percentage, and muscle mass.

[1570] Step 6:

[1571] The server inputs the selfie image into the emotion engine to recognize the user's emotions. The emotion engine determines the user's emotional state, such as joy, sadness, surprise, or anger, from their facial expressions.

[1572] Step 7:

[1573] The server compares the analysis results and emotional data with the latest fashion trend database, which includes information on the latest hairstyles, makeup, and fashion items.

[1574] Step 8:

[1575] The server selects the hairstyle, makeup, and fashion items that are best suited to the user and generates recommendations. Based on the emotional data, the server adjusts the recommendations to suit the user's specific emotional state.

[1576] Step 9:

[1577] The server generates and sends the recommendation information to the device, which includes images of specific hairstyles, makeup steps, and photos of fashion items and combinations.

[1578] Step 10:

[1579] The device displays the received recommendation information to the user, who can then check the suggested styles via the app and select the most appropriate suggestion based on their emotional state.

[1580] Step 11:

[1581] The server provides recommended hair salon information based on the user's location, and if the user wishes, a link to make a reservation at the appropriate salon is also provided.

[1582] Step 12:

[1583] If the user likes the suggested fashion item, they can send a rental request through the app.

[1584] Step 13:

[1585] The server receives the rental request and sends a request for the specified item to the affiliated rental shop.

[1586] Step 14:

[1587] The rental shop will confirm the request and prepare to deliver the specified fashion item to the user's address.

[1588] Step 15:

[1589] The user receives the rented fashion item and uses it for the specified period. After use, the rental item is returned.

[1590] By following these steps, users can easily find the style that best suits them and receive services at a beauty salon. They can also rent the suggested fashion items. The introduction of an emotion engine makes it possible to provide detailed suggestions based on the user's emotional state.

[1591] Example 2

[1592] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1593] Conventional fashion suggestion systems primarily make suggestions based on the user's physical characteristics and facial shape, without taking into account the user's emotional state. This can result in suggested styles that do not match the user's psychological state, resulting in reduced user satisfaction. Furthermore, when users wish to use specific services or products based on the suggestions, they must individually search for information and make reservations, which is inconvenient.

[1594] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1595] In this invention, the server includes means for face mapping a selfie image, analyzing physical characteristics based on body composition measurement data, and recognizing an emotional state using an emotion engine, means for comparing the analysis results and the emotional state with the latest fashion trend database to suggest optimal fashion, hairstyle, and makeup, and means for transmitting and displaying the suggestions to the user's terminal. This makes it possible to suggest styles that are adapted to the user's psychological state, and furthermore, by linking with information on beauty salons and fashion item rental services, it is possible to provide users with advanced and personalized services.

[1596] A "user" is a person who uses the system to input a selfie and body composition data and receive style suggestions.

[1597] A "selfie" is a photograph of the face or upper body taken by the user, and is data used for face mapping and emotion recognition.

[1598] "Body composition measurement data" refers to data relating to the user's body composition, such as weight, body fat percentage, and muscle mass, and is data used to analyze physical characteristics.

[1599] "Transmission means" refers to the function for transferring the selfie image, body composition measurement data, and emotion data to the server.

[1600] "Analysis means" refers to the algorithms and modules that process selfie images and body composition measurement data within the server and identify the user's facial shape and physical characteristics.

[1601] "Emotion engine" refers to the technology and algorithms used to extract and analyze a user's emotions from selfie images.

[1602] "Matching means" refers to an information processing function that matches the analysis results and emotional state with a fashion trend database and selects the most suitable fashion, hairstyle, and makeup for the user.

[1603] "Suggestion means" refers to a function for transmitting and displaying the fashion, hairstyle, and makeup suggestions generated by the server to the user's terminal.

[1604] "Location information" refers to information about a geographical location obtained from a user's device, and is data used to provide beauty salon information.

[1605] "Beauty salon information" is information about facilities that offer specific beauty services suggested based on the user's location information.

[1606] A "rental request" is a request submitted by a user to temporarily borrow a suggested fashion item.

[1607] "Rental Items" are fashion items that users can temporarily borrow through rental requests.

[1608] This system allows users to input selfie images, body composition measurement data, and emotion data extracted from the images, and then suggests optimal fashion, hairstyle, and makeup based on that information. The system consists of a user terminal, a server, an emotion engine, and affiliated beauty salons and rental shops.

[1609] User terminal

[1610] Using a device such as a smartphone or PC, the user takes a selfie, inputs body composition measurement data, executes a function that recognizes the user's emotions, and checks the suggested style. The user uses a smart body composition scale to measure data such as weight and body fat percentage. This measurement data is sent to the user's smartphone via Bluetooth. The user then takes a selfie using the smartphone camera and uploads it to a specific app.

[1611] server

[1612] The server stores the received selfie image, body composition measurement data, and emotion data in a connected database. Analysis of the received data is also performed on the server. Specifically, the server uses an image processing algorithm to perform face mapping and extract features such as the user's facial shape and skin color. At the same time, it analyzes the body composition measurement data to determine the user's body type, body fat percentage, and muscle mass.

[1613] The server then uses an emotion engine to recognize the user's emotions from the selfie. This emotion engine is a technology that determines emotions such as joy, sadness, and surprise from the user's facial expressions. The server then compares the analysis results and emotional state with the latest fashion trend database to suggest hairstyles, makeup, and fashion items that are best suited to the user. Suggestions include images of hairstyles, makeup steps, and photos and combinations of fashion items. Based on the emotion data, the suggested styles are adjusted to adapt to the user's current mental state. Suggestions are sent to the user's device and displayed through the app.

[1614] Hair salons and rental shops

[1615] If the user wishes to use the service based on the suggestions, the server provides information on recommended beauty salons and displays a reservation link. Furthermore, the suggested fashion items are available for rental, and a request can be sent from the user's device. The rental shop then processes the delivery of the items upon receiving the request.

[1616] Specific examples

[1617] User C (28 years old, female)

[1618] The user measures their weight and body fat percentage with a dedicated body composition scale, takes a selfie with their smartphone, and uploads it to the app. The emotion engine detects the emotion of joy from their facial expression.

[1619] The server analyzes this data and matches it with the latest spring fashion trends based on User C's face shape and body type.

[1620] We suggest a light-colored dress, a casual jacket, and natural makeup, which will bring out her joyful emotions.

[1621] The server recommends reputable local hair salons and stylists and provides booking links.

[1622] The suggested fashion items will be delivered to your home the next day using a rental service.

[1623] User D (35 years old, male)

[1624] The smart body composition scale measures his weight and body fat percentage, and he takes a selfie with his smartphone and uploads it. The emotion engine detects emotions such as fatigue and stress from his facial expressions.

[1625] The server analyzes the data and matches it with the latest fall fashion trends based on User D's face shape and body type.

[1626] A dark suit, a muted tie, and a simple hairstyle are recommended, which will help him look less tired.

[1627] In addition, it also provides information on nearby stores suitable for relaxation services and refreshing.

[1628] The suggested fashion items will be delivered to your home the next day using a rental service.

[1629] Prompt Sentence Examples

[1630] "A 28-year-old female user measured her weight and body fat percentage using a dedicated body composition scale and uploaded a selfie with her smartphone. The emotion engine detected the emotion of joy from her facial expression. Based on this user's face shape and body type, please match the latest spring fashion trends and suggest a bright-colored dress and natural makeup."

[1631] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1632] Step 1: User takes a selfie and enters body composition measurement data

[1633] The user uses a dedicated smart body composition scale to measure data such as weight and body fat percentage. This measurement data is sent to the user's smartphone via Bluetooth. The user then takes a selfie using the smartphone camera and uploads it to a dedicated app. This provides the selfie image and body composition measurement data as input data.

[1634] Step 2: The device sends the data to the server

[1635] The device sends the captured selfie image, body composition measurement data, location information, and emotion data extracted by the emotion engine to the server. Specifically, all data collected by the smartphone application (images, measurement data, location information, emotion data) is securely sent to the server using the HTTPS protocol. This sends the input data to the server.

[1636] Step 3: The server parses the data

[1637] The server performs face mapping based on the received selfie image, extracting features such as the user's facial shape, skin color, and contours. A facial recognition module is used for this analysis. At the same time, body composition measurement data is analyzed to determine the user's body type, body fat percentage, and muscle mass. Specifically, the face mapping algorithm analyzes the selfie image and identifies facial feature points (such as the position of the eyes, nose, and mouth), and the body composition data analysis module calculates the user's physical characteristics based on the measurement data. This outputs facial shape data and physical characteristic data.

[1638] Step 4: The emotion engine recognizes the emotion

[1639] The server recognizes the user's emotions from the selfie image through the emotion engine. The emotion engine analyzes the user's facial expressions from the image and determines emotions such as joy, sadness, and surprise. Specifically, the emotion engine analyzes the subtle movements of the face to evaluate the user's emotional state, which then outputs the user's emotional data.

[1640] Step 5: The server checks against the trend database

[1641] The server compares the user's facial features, body type data, and emotional data with the latest fashion trend database. This allows the system to select the hairstyle, makeup, and fashion items that are best suited to the user. Specifically, the server executes a database query to search the latest fashion trend information and identify the most suitable style. This results in the output of optimized fashion suggestion data.

[1642] Step 6: Server generates and sends proposal

[1643] Based on the matching results, the server suggests the optimal style for the user. The suggestions include images of hairstyles, makeup routines, and photos and combinations of fashion items. Based on emotional data, the suggested style is adjusted to suit the user's current mental state. Specifically, the server encodes the suggested data in JSON format and sends it to the smartphone app via push notification. The suggested data is then displayed on the user's device.

[1644] Step 7: Provide beauty salon and rental services

[1645] If the user wishes to use a service based on the suggestions, the server provides information about recommended beauty salons and displays a reservation link. Furthermore, rental services are available for the suggested fashion items, and a request can be sent from the user's device. The rental shop receives the request and arranges for delivery of the items. Specifically, the server analyzes reputation data for nearby beauty salons, selects the most suitable salon, and displays it to the user. The rental request is also linked to the rental shop's system, which checks inventory and initiates delivery procedures. This allows users to easily use the appropriate beauty services and fashion items.

[1646] (Application example 2)

[1647] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1648] In today's world, selecting the best fashion, hairstyle, and makeup for each individual user can be difficult given the wide variety of options and trend information available. While it is important to provide style suggestions that take into account each user's emotional state and physical characteristics, systems that can effectively reflect these are still lacking. Furthermore, there is a need for a simple way to actually apply the suggested styles (by making a salon appointment or renting fashion items).

[1649] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for comparing the analysis results and the emotion data recognized by the emotion engine with the latest fashion trend database and suggesting optimal fashion, hairstyle, and makeup for the user, means for virtually displaying the suggested styles on the user's terminal in real time, and means for transmitting and displaying the suggestions on the user's terminal. This enables the system to suggest optimal styles based on the user's emotional state and physical characteristics and to enable the user to virtually try on those styles.

[1650] A "user terminal" is an electronic device used by a user to operate the device, such as a smartphone or a personal computer.

[1651] A "server" is a computer system that receives data, analyzes it, recognizes emotions, generates suggestions, and transmits the information to the user's device.

[1652] A "selfie" refers to a photograph of the user's face taken by the user themselves, and is used to analyze facial features.

[1653] "Body composition measurement data" is measurement data that indicates the user's physical characteristics such as weight and body fat percentage.

[1654] "Face mapping" is a technology that analyzes the shape and features of a user's face based on a selfie image.

[1655] The "Emotion Engine" is a technology that analyzes and recognizes a user's emotional state from selfie images.

[1656] The "Fashion Trend Database" is a database that stores information on the latest fashions, hairstyles, and makeup.

[1657] "Virtual display means" refers to a technology that allows users to virtually visualize styles that they have not actually tried and check them on their device.

[1658] "Location Information" is data that indicates a user's current geographic location.

[1659] "Beauty salon information" is information about a beauty salon, including the salon name, location, reservation status, and the like.

[1660] "Fashion items" are fashion-related products such as clothing and accessories.

[1661] "Rental" refers to a service in which users temporarily borrow fashion items to use for a certain period of time.

[1662] This system uses a user's selfie photos and body composition measurement data to suggest optimal fashion, hairstyles, and makeup, and combines it with an emotion engine. The system consists of a user's device, a server, an emotion engine, and affiliated beauty salons and rental shops.

[1663] System configuration

[1664] 1. User Device

[1665] Input method: Users take selfies and input body composition measurement data using devices such as smartphones and PCs. Specific devices include iPhones, Android smartphones, and Windows PCs.

[1666] Virtual display means: The system has the function of visualizing the proposed style in real time on the device, allowing users to virtually try out the style.

[1667] 2. Server

[1668] Analysis method: The server performs face mapping based on the uploaded selfie image and analyzes the user's facial shape and features. It also analyzes physical characteristics based on body composition measurement data. The server processes data using cloud services such as Google Cloud Platform and AWS.

[1669] Emotion Recognition: Recognize the user's emotional state from selfies through an emotion engine, built using machine learning libraries such as TensorFlow.

[1670] Matching: The analysis results and sentiment data are matched with the latest fashion trend database to suggest the most suitable fashion, hairstyle, and makeup for the user. The trend database collects the latest industry information and is updated regularly.

[1671] 3. Affiliated hair salons and rental shops

[1672] Information provision: Based on the user's location, the service provides recommended hair salons. Hair salons are registered in a database in advance and selected based on ratings and user feedback.

[1673] Rental service: Users can submit rental requests for suggested fashion items, which are then sent to affiliated rental shops, which then process the delivery of the items.

[1674] Specific examples

[1675] User C (28 years old, female):

[1676] She measures her weight and body fat percentage with a dedicated body composition scale and uploads a selfie with her smartphone. The emotion engine detects the emotion of joy from her facial expression. The server analyzes this data and matches the latest spring fashion trends based on User C's face shape and body type. It suggests a bright-colored dress, a casual jacket, and natural makeup. This selects a style that will bring out her emotion of joy. The server then provides information on reputable local hair salons and displays a link to make a reservation. The suggested fashion items are delivered to her home the next day using a rental service.

[1677] User D (35 years old, male):

[1678] The user measures his weight and body fat percentage with a smart body composition scale and uploads a selfie image on his smartphone. The emotion engine detects feelings of fatigue and stress from his facial expressions. The server analyzes the data and matches the latest autumn fashion trends based on User D's facial shape and body type. It suggests a dark-colored suit, a tie in a muted tone, and a simple hairstyle. This selects a style that will relieve his fatigue. It also provides information on nearby stores suitable for relaxation services and refreshing. The suggested fashion items are delivered to his home the next day using a rental service.

[1679] Prompt Sentence Examples

[1680] "We analyzed User A's selfies and identified her happy emotions. Based on the latest spring fashion trends, we suggest the following style. A casual navy cardigan and denim combination with a striped shirt would look good on her."

[1681] This allows users to easily find the style that best suits their emotional state and physical characteristics, and also makes it easier to use services at beauty salons and rent fashion items.

[1682] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1683] Step 1:

[1684] Users take a selfie using a device such as a smartphone or PC, and a dedicated smart body composition scale acquires body composition measurement data such as weight and body fat percentage. The user's device receives this data and uploads the selfie and body composition measurement data to the app. The input data is the selfie and body composition measurement data, and the output is the uploaded user data.

[1685] Step 2:

[1686] The user device sends the uploaded selfie image and body composition measurement data to the server using a secure communication protocol (e.g., HTTPS). The input data are the selfie image and body composition measurement data obtained in the previous step, and the output is the data transferred to the server.

[1687] Step 3:

[1688] The server performs face mapping based on the received selfie image. This face mapping uses image processing libraries such as OpenCV to analyze the shape and features of the face. The input data is the selfie image, and the output is data that shows the shape and features of the user's face.

[1689] Step 4:

[1690] The server analyzes the body composition measurement data and identifies the user's physical characteristics (body type, body fat percentage, muscle mass, etc.). Data science tools (e.g., Pandas, NumPy) are used for the analysis. The input data is the body composition measurement data, and the output is the analyzed physical characteristic data.

[1691] Step 5:

[1692] The server uses an emotion engine to recognize the user's emotional state from the selfie image. It uses deep learning libraries such as TensorFlow to run emotion recognition models and identify emotions such as joy, sadness, and surprise. The input data is the selfie image, and the output is the recognized emotion data.

[1693] Step 6:

[1694] The server compares the user's facial features, physical characteristics, and emotional data with the latest fashion trend database. The fashion trend database is managed on the cloud and updated with the latest industry information. The input data is face mapping data, physical characteristics data, and emotional data, and the output is data suggesting the most suitable fashion, hairstyle, and makeup for the user.

[1695] Step 7:

[1696] The server sends the generated proposal to the user's device, which then virtually displays the proposed style in real time, allowing the user to virtually try out the proposed style. The input data is the proposal data, and the output is the virtual style displayed on the user's device.

[1697] Step 8:

[1698] If the user accepts the proposed style, the user device sends a request to the affiliated hair salon or rental shop. The input data is the user's request, and the output is the salon reservation information and the delivery procedure for the rental items.

[1699] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1700] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1701] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1702] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1703] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1704] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1705] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1706] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1707] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1708] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1709] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1710] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1711] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1712] 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.

[1713] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1714] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1715] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1716] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1717] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1718] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1719] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1720] The following is further disclosed regarding the above embodiment.

[1721] (Claim 1)

[1722] A means for users to input selfie images and body composition measurement data;

[1723] means for transmitting the selfie image and body composition measurement data to a server;

[1724] a means for the server to perform face mapping of the selfie image and analyze the user's physical characteristics based on the body composition measurement data;

[1725] means for the server to compare the analysis results with the latest fashion trend database and suggest the most suitable fashion, hairstyle, and makeup to the user;

[1726] The system includes means for transmitting and displaying the suggestions on a user's terminal.

[1727] (Claim 2)

[1728] The system according to claim 1, wherein the server further comprises means for providing recommended beauty salon information based on the user's location information.

[1729] (Claim 3)

[1730] 10. The system of claim 1, further comprising means for the user to submit a request to rent a suggested fashion item and to provide the rental item.

[1731] "Example 1"

[1732] (Claim 1)

[1733] A means for users to input selfie images and body composition measurement data;

[1734] means for transmitting the selfie image and body composition measurement data to a server;

[1735] a means for the server to perform face mapping of the selfie image and analyze the user's physical characteristics based on the body composition measurement data;

[1736] means for the server to compare the analysis results with a trend database and suggest optimal fashion, hairstyle, and makeup to the user;

[1737] A means to automatically generate details of the proposal using a generative AI model and provide them to users;

[1738] The system includes means for transmitting and displaying the suggestions on a user's terminal.

[1739] (Claim 2)

[1740] The system according to claim 1, wherein the server further comprises means for providing recommended beauty salon information based on the user's location information.

[1741] (Claim 3)

[1742] 10. The system of claim 1, further comprising means for the user to submit a request to rent a suggested fashion item and to provide the rental item.

[1743] "Application Example 1"

[1744] (Claim 1)

[1745] A means for users to input selfie images and body composition measurement data in a physical store;

[1746] means for transmitting the selfie image and body composition measurement data to a server in real time;

[1747] a means for the server to perform face mapping of the selfie image and analyze the user's physical characteristics based on the body composition measurement data;

[1748] means for the server to compare the analysis results with the latest fashion trend database and suggest the most suitable fashion, hairstyle, and makeup to the user;

[1749] The system includes means for transmitting and displaying the offers on a display device within the physical store.

[1750] (Claim 2)

[1751] The system according to claim 1, wherein the server further comprises means for providing recommended beauty salon information based on the user's location information.

[1752] (Claim 3)

[1753] The system according to claim 1, further comprising means for the user to try on the suggested fashion items on the spot and purchase or rent them.

[1754] "Example 2: Combining Emotion Engines"

[1755] (Claim 1)

[1756] A means for a user to input a selfie image, body composition measurement data, and emotion data extracted from the image;

[1757] means for transmitting the selfie image, body composition measurement data, and emotion data to a server;

[1758] a means for the server to perform face mapping of the selfie image, analyze physical characteristics based on the body composition measurement data, and recognize an emotional state using an emotion engine;

[1759] means for the server to compare the analysis results and the emotional state with a database of the latest fashion trends and suggest the most suitable fashion, hairstyle, and makeup to the user;

[1760] The system includes means for transmitting and displaying the suggestions on a user's terminal.

[1761] (Claim 2)

[1762] The system according to claim 1, wherein the server further comprises means for providing recommended beauty salon information based on the user's location information.

[1763] (Claim 3)

[1764] 10. The system of claim 1, further comprising means for the user to submit a request to rent a suggested fashion item and to provide the rental item.

[1765] "Application example 2 when combining emotion engines"

[1766] (Claim 1)

[1767] A means for users to input selfie images and body composition measurement data;

[1768] means for transmitting the selfie image and body composition measurement data to a server;

[1769] a means for the server to perform face mapping of the selfie image and analyze the user's physical characteristics based on the body composition measurement data;

[1770] means for the server to compare the analysis result and the emotion data recognized by the emotion engine with the latest fashion trend database and suggest the most suitable fashion, hairstyle, and makeup to the user;

[1771] A means for virtually displaying the proposed style on a user device in real time;

[1772] The system includes means for transmitting and displaying the suggestions on a user's terminal.

[1773] (Claim 2)

[1774] The system according to claim 1, wherein the server further comprises means for providing recommended beauty salon information based on the user's location information.

[1775] (Claim 3)

[1776] 10. The system of claim 1, further comprising means for the user to submit a request to rent a suggested fashion item and to provide the rental item. [Explanation of symbols]

[1777] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to input selfie images and body composition measurement data; means for transmitting the selfie image and body composition measurement data to a server; a means for the server to perform face mapping of the selfie image and analyze the user's physical characteristics based on the body composition measurement data; means for the server to compare the analysis results with the latest fashion trend database and suggest the most suitable fashion, hairstyle, and makeup to the user; The system includes means for transmitting and displaying the suggestions on a user's terminal.

2. The system according to claim 1 , wherein the server further comprises means for providing recommended beauty salon information based on the user's location information.

3. The system of claim 1 further comprising means for the user to submit a request to rent a suggested fashion item and to provide the rental item.

Images