System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining profile information from a user; means for obtaining an image of clothing and information about the clothing from the user; means for obtaining schedule and destination information from the user; means for obtaining weather forecast information; means for executing an algorithm to generate a proposed coordination; means for displaying the generated coordination proposal to the user; means for sending a consultation request to a professional coordinator and obtaining an answer thereto; and means for displaying the obtained answer to 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] Many people today worry every day about fashion, makeup, and hairstyles, but often have limited access to appropriate advice. They have particular difficulty figuring out how to mix and match the clothes they buy and what style suits them best. However, one-off advice does not adequately solve these problems, and long-term, personalized advice is needed. Additionally, deciding what to wear based on the weather, where you're going, and who you'll be meeting is difficult, and there is a lack of efficient ways to decide on an overall outfit for the day. By solving these issues, the app aims to reduce the burden of daily outfit coordination for users and provide a more comfortable lifestyle. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a system including means for acquiring profile information from a user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather forecast information, means for executing an algorithm for generating suggested outfits, means for displaying the generated outfit suggestions to the user, means for sending a consultation request to a professional outfit coordinator and obtaining a response, and means for displaying the obtained response to the user. This system integrates and analyzes the user's diverse information to suggest optimal fashion, hairstyle, and makeup. Furthermore, by receiving advice from a professional outfit coordinator, the user can receive more detailed advice, which is extremely useful. This allows the user to coordinate their daily outfits efficiently and comfortably.

[0006] "Profile Information" refers to detailed personal information about a User, such as their height, weight, style preferences, skin tone, hairstyle, etc.

[0007] "Clothing images" refers to photos of clothes owned by the user, from which data such as the type, color, and shape of the clothes can be extracted.

[0008] "Schedule" refers to information such as where the user will go that day, people they will meet, and events they will attend.

[0009] "Destination information" refers to detailed location information of where the user is heading.

[0010] "Weather forecast information" refers to forecast data regarding the weather at a specified location, including temperature, probability of precipitation, wind speed, etc.

[0011] An "algorithm" refers to the processing procedures and calculations used to generate optimal combinations of fashion, hairstyle, and makeup based on input data.

[0012] "Coordination suggestions" refer to algorithmically generated suggestions for the best combination of fashion, hairstyle, and makeup for the user.

[0013] A "consultation request" refers to a request from a user to a professional coordinator for more detailed advice.

[0014] A "professional coordinator" is an expert who has specialized knowledge of fashion, hairstyles, and makeup and provides accurate advice to users.

[0015] "Response" refers to advice or insight provided by a professional coordinator in response to a user's consultation request.

[0016] The "system" refers to the overall framework that includes each of the above means and provides users with optimal coordination suggestions and professional advice. [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] The present invention relates to a system that proposes an optimal overall coordination of fashion, hairstyle, makeup, etc. based on individual information of a user. Specific embodiments of the present invention will be described below.

[0039] System configuration and operation

[0040] 1. User information registration

[0041] Users first install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothes and upload them to the app. The device analyzes these images to extract data such as the type, color, and shape of the clothes, and sends this information to the server as well.

[0042] 2. Get schedule and weather information

[0043] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then retrieves weather information for that location from a weather forecast API based on the destination's location information and records it.

[0044] 3. Coordinate Generation

[0045] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. This information is input into an algorithm that generates outfits. The algorithm takes into account past outfit history, current fashion trends, the user's skin tone, and face shape to generate the optimal combination of fashion, hairstyle, and makeup to suggest. The generated outfit suggestions are sent to the device, which displays them to the user.

[0046] 4. Consultation function

[0047] When a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional coordinator. The device sends the consultation request to the server, and the server provides this request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user.

[0048] Specific examples

[0049] A specific example will be given below for explanation.

[0050] Example: User A (25 years old, female) living in Tokyo has plans to have lunch with a friend in Omotesando in three days.

[0051] 1. Information input: Person A uses the app to input plans to have lunch in Omotesando three days later. The device sends this information to the server, which then retrieves weather information for Omotesando.

[0052] 2. Coordination Generation: The server refers to A’s profile and the list of clothes she owns (e.g., a white blouse, denim pants, and sneakers), and, taking into account that the weather is sunny and the temperature is 20 degrees, suggests a combination of a white blouse, denim pants, and sneakers. It also recommends natural makeup and a loose wavy hairstyle.

[0053] 3. Displaying and selecting proposals: The device displays these proposals to Person A, who then accepts all of them.

[0054] 4. Consultation function: If user A feels unsure about her makeup, she can send a consultation request to a professional makeup artist. The device sends the request, the server notifies the makeup artist of the question, and the artist provides advice on adding natural brown eyeshadow.

[0055] 5. Displaying Advice: The device displays advice to Person A, who then follows it to finish applying their makeup.

[0056] This allows users to efficiently complete their outfits for the day. This system reduces the worries users have about their daily fashion and provides personalized total outfits.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] A user installs the app and creates an account on their device. The user enters basic information (name, email address, password), which the device sends to the server to create the account.

[0060] Step 2:

[0061] The user enters profile information such as height, weight, style preferences, skin color, hairstyle, etc. The device sends this information to the server and stores it as the user's profile data.

[0062] Step 3:

[0063] Users take photos of their clothes and upload them to the app. The device analyzes the uploaded images and extracts data such as the type, color, and shape of the clothes. The extracted data is sent from the device to a server and added to the user's clothing list.

[0064] Step 4:

[0065] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends the plan information to the server, and the server retrieves weather information from the weather forecast API based on the location information of the destination.

[0066] Step 5:

[0067] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information, and then runs an algorithm to generate suggested outfits, creating optimal combinations of fashion, hairstyle, and makeup.

[0068] Step 6:

[0069] The server sends the generated coordination suggestions to the terminal, which displays them to the user. The user checks the suggestions and selects an appropriate coordination. The selection result is sent from the terminal to the server and recorded.

[0070] Step 7:

[0071] If the user wants more detailed advice, he / she sends a consultation request to the professional coordinator. The terminal sends the request to the server, and the server notifies the professional coordinator of the consultation content and the user information.

[0072] Step 8:

[0073] A professional coordinator creates advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user. The user then uses the advice to optimize their coordination.

[0074] Example 1

[0075] 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."

[0076] In today's busy lifestyles, it is difficult for users to efficiently coordinate their daily outfits, resulting in significant stress in making choices. There are also limited ways to easily obtain expert advice on fashion and makeup. Given these circumstances, there is a need for a system that can suggest optimal fashion, hairstyle, and makeup outfits tailored to individual user needs, and quickly obtain expert opinions.

[0077] 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.

[0078] In this invention, the server includes means for acquiring profile information from the user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather forecast information, means for executing an algorithm for generating outfit suggestions, means for displaying the generated outfit suggestions to the user, means for sending a consultation request to a professional expert and acquiring a response thereto, and means for displaying the acquired response to the user. This allows the user to receive suggestions for efficient fashion, hairstyle, and makeup coordination tailored to their individual needs, and to receive prompt advice from an expert.

[0079] "User profile information" means basic personal information such as a user's height, weight, style preferences, skin color, hairstyle, etc.

[0080] "Clothing images and clothing information" refers to photos of clothing owned by the user and detailed information such as the type, color, and shape of the clothing.

[0081] "Plan and destination information" is information about the schedule for the day and the places to visit that is entered by the user.

[0082] "Weather forecast information" is information about the weather at a specified location and time, obtained from an external weather forecast API or the like.

[0083] The "algorithm for generating suggested outfits" is a program process that generates optimal combinations of fashion, hairstyle, and makeup based on the user's profile information, clothing list, schedule, destination information, and weather forecast information.

[0084] The "means for displaying generated coordination suggestions to the user" is an interface for displaying the coordination suggestions generated by the algorithm on the user's terminal.

[0085] "Means for sending a consultation request to a professional expert and obtaining a reply" refers to a communication means for sending a consultation from a user to an expert and obtaining a reply from the expert.

[0086] The "means for displaying the obtained answer to the user" is an interface for displaying the advice obtained from the professional expert on the user's device.

[0087] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information. This system includes the following main components:

[0088] 1. User information registration

[0089] Users install a dedicated application on their device and perform the initial setup. At this time, they are required to enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to a server and stored on the server. In addition, users take photos of their clothing and upload them to the app. The device uses image analysis technology to extract information such as the type, color, and shape of the clothing and sends it to the server. This information is stored on the server as the user's basic data.

[0090] 2. Retrieving schedule and weather information

[0091] When a user inputs their plans for the day (destination, people to meet, events, etc.), the device sends that information to the server. The server then obtains weather information from an external weather forecast API based on the destination's location information and stores this information along with the user's plan data. This allows the server to efficiently manage the user's plans for the day and suggest optimal outfits.

[0092] 3. Coordinate Generation

[0093] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. This information is then processed by a generative AI model to generate optimal combinations of fashion, hairstyle, and makeup. The algorithm also takes into account past outfit history, current fashion trends, the user's skin tone, and face shape. The generated outfit suggestions are sent to the device and displayed to the user.

[0094] As a concrete example, consider the case where User A (25 years old, female) living in Tokyo plans to have lunch with a friend in Omotesando three days from now. User A enters this plan through the app, and her device sends this information to the server. The server retrieves weather information for Omotesando and confirms that it is sunny with a temperature of 20 degrees. Next, it references User A's profile information and her clothing list (e.g., white blouse, denim pants, sneakers), and generates optimal outfit suggestions that take the weather information into account. This suggests a combination of a white blouse, denim pants, and sneakers, as well as natural makeup and a loose, wavy hairstyle. The suggestions are displayed on the device, and User A can review and select the suggestions.

[0095] An example of a prompt sentence can be written as follows:

[0096] User A (25 years old, female) is planning to have lunch with a friend in Omotesando in three days. She has a white blouse, denim pants, and sneakers. The weather is sunny and the temperature is 20 degrees. Please suggest the best fashion, makeup, and hairstyle for her.

[0097] 4. Consultation function

[0098] If a user is unsure about the suggested outfit or makeup, they can send a request for advice to a professional expert. The device sends the request to the server, which notifies the professional expert of the request. The expert creates advice based on the user information and the request and sends it back to the server. The server then sends this advice to the device and displays it to the user. This allows the user to complete their outfit based on the detailed advice.

[0099] This system allows users to efficiently complete their outfits for the day, reducing the hassle of daily fashion and allowing them to enjoy personalized, total outfits.

[0100] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0101] Step 1: Register your user information

[0102] 1. Application installation and initial settings

[0103] Users can start using the system by installing a dedicated application on their device and creating an account.

[0104] Input: Profile information such as the user's height, weight, style preferences, skin tone, hairstyle, etc.

[0105] Output: The profile information is saved on the server.

[0106] 2. Enter your profile information

[0107] Users use the application to enter profile information, which the device then sends to the server, which stores the information in a database.

[0108] Input: Profile information.

[0109] Output: The profile information is saved in the database.

[0110] 3. Upload a photo of your outfit

[0111] Users take photos of their clothing and upload them to the app. The device uses image analysis technology to extract information such as the type, color, and shape of the clothing. The extracted information is sent to a server, which stores it in a database.

[0112] Input: Clothing images.

[0113] Output: Clothing information is saved in the database.

[0114] Step 2: Get schedule and weather information

[0115] 1. Enter your schedule

[0116] The user enters their plans for the day (destinations, people to meet, events, etc.) into the app, and the device sends this information to the server.

[0117] Input: User's appointment information.

[0118] Output: The schedule information is saved on the server.

[0119] 2. Obtaining weather information

[0120] The server calls an external weather forecast API based on the destination of the schedule information and obtains weather information for the specified location. This information is stored on the server.

[0121] Input: Destination information.

[0122] Output: Weather forecast information is saved on the server.

[0123] Step 3: Generate coordinates

[0124] 1. Information synthesis and analysis

[0125] The server combines the user's profile information, clothing list, schedule and weather information to input into a generative AI model.

[0126] Input: User profile information, clothing list, schedule, weather information.

[0127] Output: The integrated data is fed into a generative AI model.

[0128] 2. Coordination Proposal Generation

[0129] The generative AI model takes into account past outfit history, the latest fashion trends, and the user's skin tone and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent from the server to the device.

[0130] Input: Integrated data.

[0131] Output: A coordination proposal is generated and sent to the terminal.

[0132] 3. Display of outfits

[0133] The device displays the coordination proposal to the user, who can then review the proposal and choose whether to accept it.

[0134] Input: Coordination suggestions.

[0135] Output: Coordination suggestions are displayed to the user.

[0136] Step 4: Use the consultation feature

[0137] 1. Submit a consultation request

[0138] If a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional from the app, and the device will send the request and user information to the server.

[0139] Input: Consultation request.

[0140] Output: The request is sent to the server.

[0141] 2. Notification to the Expert

[0142] When the server receives the request, it notifies the professional and provides the user information and the request details.

[0143] Input: Consultation request.

[0144] Output: A notification is sent to the expert.

[0145] 3. Creating and sending advice

[0146] The expert creates detailed advice based on the user information and the request content and sends it to the server, which then sends the advice to the device.

[0147] Enter: expert advice.

[0148] Output: Advice is sent to the device via the server.

[0149] 4. Displaying Advice

[0150] The device will display advice to the user, who can then follow the advice to complete their outfit.

[0151] Enter: expert advice.

[0152] Output: The advice is displayed to the user.

[0153] (Application example 1)

[0154] 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."

[0155] Today, when users consider the optimal fashion coordination based on their profile information and the clothes they own, it takes time and effort, and there is no guarantee that the results will be satisfactory. Furthermore, there are limited ways to check outfit combinations without actually trying on clothes, or to visually check the suggested outfits, making it difficult to decide whether to buy or rent. Therefore, there is a need for an efficient, visually confirmable fashion coordination suggestion system.

[0156] 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.

[0157] In this invention, the server includes means for acquiring profile information from a user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather forecast information, means for executing an algorithm for generating coordinated outfits to be suggested, means for displaying the generated coordinated outfit suggestions to the user, means for sending a consultation request to a professional coordinator and acquiring a response, means for displaying the acquired response to the user, augmented reality means for generating an avatar for the user and applying the coordinated outfit to the avatar and displaying it in real space, and means for renting the suggested coordinated outfits. This allows the user to efficiently receive suggestions for optimal fashion coordinated outfits, and visual confirmation makes it easier to decide whether to purchase or rent.

[0158] A "user" is a person who uses the system and provides profile information and information about the clothing they own.

[0159] "Profile Information" refers to detailed personal data such as a user's height, weight, style preferences, skin tone, hairstyle, etc.

[0160] "Images of clothes and information about clothes" refers to photos of each piece of clothing owned by the user and detailed data such as its type, color, shape, etc.

[0161] "Plan and destination information" refers to detailed schedule information such as places the user plans to go to, events, and people they plan to meet in the future.

[0162] "Weather forecast information" is weather forecast data for the location and date and time the user plans to go to.

[0163] "Coordination suggestions" refer to the optimal combination of clothing, hairstyle, makeup, etc. that a user should wear that day based on the user's profile information and weather information obtained.

[0164] An "algorithm" is a computational procedure for generating optimal outfit suggestions based on collected information.

[0165] "Augmented reality means" refers to technology for generating a user's avatar and visually displaying suggested outfits in real space.

[0166] "Means for renting" refers to a function that allows you to temporarily borrow suggested outfits or items.

[0167] The "server" is a device that receives and stores various information sent by users and generates coordination suggestions.

[0168] This system collects detailed user profile information, real-world weather and schedule information, and proposes optimal fashion coordination. This system integrates multiple technologies to enhance user convenience.

[0169] System configuration and operation

[0170] 1. User information registration

[0171] First, the user installs a dedicated application on the device and performs initial setup. The user then enters detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This information is sent from the device to a server and stored. The user also takes pictures of clothes they own and uploads them to the app. The device analyzes these images and extracts information such as the type, color, and shape of the clothes, which is then sent to the server.

[0172] 2. Get schedule and weather information

[0173] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then uses the weather forecast API to obtain and record weather information for the destination based on the location information.

[0174] 3. Coordinate Generation

[0175] The server integrates and analyzes the user's profile information, list of clothing items, schedule and destination information, and weather forecast information. This information is input into an algorithm that generates outfits. The algorithm also takes into account the user's skin tone and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device, which displays them to the user.

[0176] 4. Avatar generation and augmented reality display

[0177] The system generates an avatar for the user and applies the suggested outfits to it. Furthermore, by utilizing augmented reality, users can project the avatar into the real world using smart glasses or a head-mounted display, allowing them to visually check the outfits.

[0178] 5. Rental and consultation features

[0179] There is also a function to temporarily rent suggested outfits and items. If users are unsure about what to wear, they can send a consultation request to a professional coordinator, and the answer will be retrieved and displayed.

[0180] Hardware and software used

[0181] Hardware: Smartphones, smart glasses, head-mounted displays

[0182] Software: Python, OpenCV, ARCore, ARKit, WeatherAPI

[0183] The system processes a variety of data and generates optimal outfits based on that data. Users can visually check the outfits and efficiently choose the outfit that best suits them.

[0184] Specific examples

[0185] For example, say a user has an appointment in Tokyo one day, has light skin tones, and prefers casual clothing. They enter this information into the app. The server then retrieves this information along with the weather forecast for that day. Based on the forecast of a sunny 20-degree weather, the server suggests a white T-shirt, denim shorts, and sneakers. This suggestion is visually displayed as the user's avatar through the smart glasses. If the user is unsure about which accessories to choose, they can consult with a professional coordinator and receive additional suggestions.

[0186] Prompt Sentence Examples

[0187] Based on the user's profile information (height: 165cm, weight: 55kg, preference: casual, skin tone: light, hairstyle: long) and the destination location (Tokyo), generate the best outfit suggestions for a day when the temperature is 20 degrees. The suggestions should include tops, bottoms, and shoes.

[0188] As described above, this system efficiently provides optimal coordination based on detailed user information.

[0189] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0190] Step 1:

[0191] The user installs the application on the device and performs initial setup. The user enters their profile information (height, weight, style preferences, skin color, hairstyle, etc.). The entered profile information is sent from the device to the server and saved on the server. The server processes the entered information by organizing it for each user and registering it in a database.

[0192] Step 2:

[0193] Users take pictures of their clothes and upload them to the app. The device analyzes the uploaded images and extracts detailed data such as the type, color, and shape of the clothes. The extracted data is sent to a server and saved as a list of the user's belongings. A deep learning model is used for the analysis, and the image data is converted into text information.

[0194] Step 3:

[0195] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends this information to the server. The server uses the location information of the destination to obtain and record weather information for that location using a weather forecast API. Specific inputs include date, time, and location information, and the output is weather forecast information data.

[0196] Step 4:

[0197] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. It then runs an algorithm to generate outfits based on this data. The algorithm comprehensively evaluates multiple factors and generates the optimal combination of fashion, hairstyle, and makeup to suggest. The output is a specific outfit suggestion.

[0198] Step 5:

[0199] The generated coordination proposal is sent from the server to the terminal, which displays it to the user. The user checks the proposed coordination and, if necessary, sends a consultation request to a professional coordinator. This request is sent from the terminal to the server, which provides the request to the professional coordinator.

[0200] Step 6:

[0201] The professional coordinator creates advice based on the request and sends it to the server, which retrieves the advice and sends it back to the user. Specifically, the professional coordinator evaluates the proposed coordination and provides additional advice.

[0202] Step 7:

[0203] The server generates an avatar for the user and applies the proposed outfits to the avatar. Using augmented reality, the user visually sees the avatar in real space through smart glasses or a head-mounted display. The server sends the generated avatar information to the device, which displays it in the augmented reality environment.

[0204] Step 8:

[0205] When a user wants to temporarily rent a suggested outfit or item, the device sends a rental request to the server. The server processes the request, checks for available items, and provides them to the user. Specifically, it checks the inventory of the suggested item and arranges for delivery.

[0206] 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.

[0207] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments of the present invention are described below.

[0208] System configuration and operation

[0209] 1. User information registration

[0210] Users first install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothes and upload them to the app. The device analyzes these images to extract data such as the type, color, and shape of the clothes, and sends this information to the server as well.

[0211] 2. Get schedule and weather information

[0212] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then retrieves weather information for that location from a weather forecast API based on the destination's location information and records it.

[0213] 3. Acquiring emotional information

[0214] While a user is using the app, the emotion engine collects data (such as facial expressions, voice tone, and input text) to recognize the user's emotions. This data is sent from the device to a server and stored as the user's emotion information.

[0215] 4. Coordinate Generation

[0216] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, weather forecast information, and emotional information. This information is input into an algorithm that generates outfits. The algorithm takes into account past outfit history, current fashion trends, the user's skin tone, and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device, which displays them to the user.

[0217] 5. Consultation function

[0218] When a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional coordinator. The device sends the consultation request to the server, and the server provides this request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user.

[0219] Specific examples

[0220] A specific example will be given below for explanation.

[0221] Example: User B (30 years old, male) living in Tokyo plans to go shopping in Shinjuku with a friend on the weekend.

[0222] 1. Information input: Person B uses the app to input his / her plans to go shopping in Shinjuku on the weekend. The device sends this information to the server, which then retrieves the weather information for Shinjuku.

[0223] 2. Acquisition of emotional information: While B is using the app, the emotion engine analyzes B's emotions from his facial expressions and tone of voice and detects that he is relaxed. This emotional information is sent to the server.

[0224] 3. Coordination Generation: The server refers to B’s profile and the list of clothes she owns (e.g., khaki jacket, black jeans, sneakers), and, taking into account the weather information that it is sunny with a temperature of 18 degrees and her relaxed emotional state, suggests a combination of khaki jacket, black jeans, and sneakers. It also recommends natural makeup and a casual hairstyle.

[0225] 4. Display and select proposals: The device displays the proposals to Person B, who accepts all of them.

[0226] 5. Consultation function: If Person B feels unsure about their styling, they can send a consultation request to a professional fashion coordinator. The device sends the request, and the server notifies the coordinator of the question and Person B's information. The coordinator then provides appropriate advice, which the server sends to the device, and Person B uses the advice to finalize their styling.

[0227] This allows users to enjoy efficient and personalized outfits every day. By taking into account the user's emotional state, the system provides more appropriate and comfortable outfit suggestions.

[0228] The processing flow will be explained below.

[0229] Step 1:

[0230] A user installs the app and creates an account on their device. The user enters basic information (name, email address, password), which the device sends to the server to create the account.

[0231] Step 2:

[0232] The user enters profile information such as height, weight, style preferences, skin color, hairstyle, etc. The device sends this information to the server and stores it as the user's profile data.

[0233] Step 3:

[0234] Users take photos of their clothes and upload them to the app. The device analyzes the uploaded images and extracts data such as the type, color, and shape of the clothes. The extracted data is sent from the device to a server and added to the user's clothing list.

[0235] Step 4:

[0236] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends the plan information to the server, and the server retrieves weather information from the weather forecast API based on the location information of the destination.

[0237] Step 5:

[0238] While a user is using the app, the emotion engine collects data (e.g., facial expressions, voice tone, and input text) to recognize the user's emotions. This emotion data is sent from the device to the server and stored as the user's emotion information.

[0239] Step 6:

[0240] The server analyzes the user's profile information, clothing list, schedule and destination information, weather forecast information, and emotional information, and inputs this information into an algorithm to generate the optimal combination of fashion, hairstyle, and makeup.

[0241] Step 7:

[0242] The server sends the generated coordination suggestions to the terminal, which displays them to the user. The user checks the suggestions and selects an appropriate coordination. The terminal then sends the selection result to the server, where it is recorded.

[0243] Step 8:

[0244] If the user wants more detailed advice, he / she sends a consultation request to the professional coordinator. The terminal sends the request to the server, and the server notifies the professional coordinator of the consultation content and the user information.

[0245] Step 9:

[0246] A professional coordinator creates advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user. The user then uses the advice to optimize their coordination.

[0247] Step 10:

[0248] The user provides emotional feedback on the proposed outfits, and the device sends the emotional feedback to the server, which uses it to optimize future outfit suggestions.

[0249] Example 2

[0250] 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."

[0251] Conventional outfit suggestion systems take into account a user's personal information and the clothing they own, but it is difficult to provide personalized suggestions that comprehensively consider the user's emotional state, detailed schedule, and weather information. As a result, the suggested outfits often do not match the user's situation or emotions, resulting in a lack of satisfaction. Furthermore, there is a lack of a way to obtain advice from experts in real time.

[0252] 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.

[0253] In this invention, the server includes means for acquiring personal information from the user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather information, means for analyzing the emotional state, means for executing an algorithm for generating outfit suggestions, means for displaying the generated outfit suggestions to the user, means for sending a consultation request to an expert and obtaining a response, and means for displaying the obtained response to the user. This enables personalized outfit suggestions that comprehensively consider the user's personal information, clothing, schedule, weather information, and emotional state. Furthermore, by obtaining advice from an expert, the user can achieve a more satisfying outfit.

[0254] A "user" is a person who uses this system to receive coordination suggestions and advice.

[0255] "Personal information" refers to detailed profile information necessary for coordinating outfits, such as the user's height, weight, style preferences, skin color, hairstyle, etc.

[0256] "Images of clothing and information about clothing" refers to photographs of clothing owned by the user, as well as information such as the type, color, and shape of the clothing.

[0257] "Plan and destination information" is information input by the user about the plan and destination for the day, people to meet, events, and the like.

[0258] "Weather information" refers to information about the weather at a location, obtained using a weather forecast API based on the location information of the destination.

[0259] The "means for analyzing emotional state" refers to software or a system that analyzes the user's facial expression, tone of voice, and input text to analyze the user's emotional state.

[0260] The "algorithm for generating outfit suggestions" is a program that combines a user's personal information, a list of clothing items they own, information about their schedule and destination, weather information, and emotional state information to generate optimal fashion, hairstyle, and makeup.

[0261] The "means for displaying the generated coordination proposal to the user" refers to a terminal screen or application for presenting the coordination proposal sent from the server to the user.

[0262] An "expert" is a professional, such as a fashion coordinator, who provides users with advice on coordinating outfits.

[0263] The "means for sending a consultation request and receiving a response" refers to a communication means or system that allows a user to send a consultation request to a specialist and receive a response.

[0264] "Integrated consideration" means comprehensively analyzing the user's personal information, clothing, schedule, weather information, and emotional state, and then providing coordination suggestions and advice based on that analysis.

[0265] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments of the present invention are described in detail below.

[0266] 1. User information registration

[0267] How it works: A user installs the application on their device and creates an account. On their device, they enter detailed profile information, such as their height, weight, style preferences, skin tone, and hairstyle. This profile information is sent from the device to a server and stored as the user's basic data.

[0268] Hardware / software used: Devices (smartphones, tablets), servers, Cloud Vision API.

[0269] A specific example: A user takes a photo of their clothes and uploads it to the app. The device analyzes the image using Cloud Vision API and extracts data such as the type, color, and shape of the clothes. This information is then sent to the server.

[0270] 2. Get schedule and weather information

[0271] How it works: A user enters their plans for the day (destinations, people to meet, events, etc.) into the app. The device then sends this information to the server.

[0272] Hardware / software used: Device, server, weather forecast API (e.g. OpenWeatherMap API).

[0273] Specific example: When a user enters plans to go to a specific place on a specific date, the server retrieves and records the weather information for that place via a weather forecast API.

[0274] 3. Acquiring emotional information

[0275] How it works: Collects data to recognize emotions while users are using the app.

[0276] Hardware / software used: Device camera, microphone, emotion recognition software (e.g. Affectiva SDK).

[0277] A concrete example: A user's facial expressions and tone of voice are captured and analyzed using emotion recognition software. The analyzed data is sent from the device to a server and stored as user emotional information.

[0278] 4. Coordinate Generation

[0279] How it works: The server generates optimal coordination suggestions based on the information it collects.

[0280] Hardware / software used: Server, generative AI model.

[0281] Specific example: The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, weather information, and emotional information. Using a generative AI model, this information is analyzed based on the prompt text to generate outfit suggestions.

[0282] Example prompt: "Please suggest a casual outfit for going to Shinjuku in a relaxed state on a sunny, 18-degree day."

[0283] 5. Proposal display and consultation function

[0284] Behavior: The generated coordination suggestions are displayed to the user, and an expert is consulted if necessary.

[0285] Hardware / software used: terminals, servers.

[0286] Specific example: If a user has questions or concerns about the proposed outfit, the device sends a consultation request to the server. The server provides the request along with the user's information to an expert, and the expert's advice is sent to the device and displayed.

[0287] The system allows users to receive personalized outfit suggestions based on their individual information and emotional state, and also offers expert advice, improving user satisfaction and the quality of their experience.

[0288] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0289] Step 1:

[0290] Registering user information

[0291] Input: User's personal information (height, weight, style preferences, skin tone, hairstyle)

[0292] Specific operation: The user installs and launches the application, creates an account, and the device displays a user information input screen, where the user enters their personal information.

[0293] Data processing / calculation: The device sends the entered personal information to the server.

[0294] Output: The server stores the received personal information in a database.

[0295] Step 2:

[0296] Clothing information registration

[0297] Input: Images of clothing owned by the user

[0298] How it works: The user takes a photo of the garment and uploads it to the app. The device then analyzes the image using image analysis software (e.g., Cloud Vision API).

[0299] Data processing / calculation: The device extracts data such as the type, color, and shape of the clothing from the image and sends it to the server.

[0300] Output: The server stores the received clothing information in a database.

[0301] Step 3:

[0302] Get schedule and weather information

[0303] Input: User's schedule and destination for the day

[0304] Specific operation: The user enters the schedule for the day into the app. The device sends the schedule information to the server.

[0305] Data processing / calculation: The server obtains weather information from a weather forecast API (e.g., OpenWeatherMap API) based on the destination's location information and associates it with the schedule information.

[0306] Output: The weather information obtained by the server is saved in a database.

[0307] Step 4:

[0308] Acquiring emotional information

[0309] Input: User facial expressions, voice tone, input text

[0310] How it works: While the user is using the app, the device's camera and microphone capture the user's facial expressions and voice in real time, while simultaneously monitoring text input.

[0311] Data processing / calculation: The device analyzes the captured data using emotion analysis software (e.g., Affectiva SDK) to generate emotional state information, which is then sent to the server.

[0312] Output: The server stores the received emotional state information in a database.

[0313] Step 5:

[0314] Coordinate generation

[0315] Input: User profile information, clothing list, schedule and destination information, weather information, emotional state information

[0316] Specific operation: The server aggregates all the user's information and generates coordination suggestions using a generative AI model. It inputs the user's information into the AI ​​model using a prompt sentence.

[0317] Data processing / calculation: Based on the prompt, the generative AI model analyzes all information and generates the optimal fashion, hairstyle, and makeup.

[0318] Example prompt: "Please suggest a casual outfit for going to Shinjuku in a relaxed state on a sunny, 18-degree day."

[0319] Output: The server sends the generated coordination proposal to the device.

[0320] Step 6:

[0321] Proposal display and consultation function

[0322] Input: Generated coordination proposal, user consultation request

[0323] Specific operation: The terminal displays the coordination proposals received from the server to the user. If necessary, the user can send a consultation request to an expert from the terminal.

[0324] Data processing / calculation: The server provides the request and user information to the expert and obtains advice from the expert.

[0325] Output: The server sends the advice to the terminal, which displays it to the user.

[0326] Through the above processing steps, users can receive personalized outfit suggestions based on their individual information and emotional state, and can also receive advice from experts.

[0327] (Application example 2)

[0328] 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."

[0329] Conventional fashion coordination systems suggest outfits based on a user's basic profile and clothing information, but it is difficult to provide personalized suggestions that take into account the user's emotional state, specific schedule, or real-time try-on simulations. Furthermore, there are limited opportunities for users to receive direct advice from professional coordinators. This leaves users with a lack of means to select the outfits that best suit them.

[0330] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0331] In this invention, the server includes means for acquiring and analyzing the user's emotional data, means for running a virtual try-on simulation of the generated outfits, and means for sending a consultation request to a professional outfit coordinator and receiving a response. This allows personalized suggestions for fashion, hairstyles, and makeup to be made through a real-time try-on simulation that takes the user's emotional state into consideration. The professional outfit coordinator can also provide specific advice, enabling more appropriate outfit selection.

[0332] "User" refers to an individual who uses the System.

[0333] "Profile information" refers to personal information such as a user's height, weight, preferred style, and skin tone.

[0334] "Images of clothing and information about clothing" refers to photos of clothing that the user has and data related to the clothing.

[0335] "Schedule and destination information" refers to information such as where the user plans to go that day and events they will attend.

[0336] "Weather forecast information" refers to forecast data regarding the weather in a specified area.

[0337] "Emotional data" refers to data related to emotions obtained from a user's facial expressions, tone of voice, etc.

[0338] "Algorithm" refers to the calculation procedure for integrating various acquired data and generating the optimal fashion coordination.

[0339] "Virtual space" refers to a virtual environment in which users interact using avatars.

[0340] "Try-on simulation" refers to the process of virtually fitting clothing onto an avatar in a virtual space.

[0341] A "professional coordinator" is someone with specialized knowledge of fashion and styling.

[0342] "Consultation Request" means a request submitted by a User to a Professional Coordinator for advice.

[0343] This invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments for carrying out this invention are described below.

[0344] System configuration

[0345] This system is realized by using a user terminal, a server, an emotion recognition device (smart glasses or head-mounted display), and a weather forecast API.

[0346] Operating procedure

[0347] 1. User information registration

[0348] First, users install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, and skin tone. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothing and upload them via the app. This image data is analyzed, and data such as the type, color, and shape of the clothing is extracted and sent to the server.

[0349] 2. Acquiring emotional information

[0350] By using the app on a daily basis and wearing an emotion recognition device (smart glasses or a head-mounted display), emotions are recognized from the user's facial expressions and tone of voice. Emotion data is analyzed in real time and sent from the device to a server.

[0351] 3. Obtaining weather information

[0352] When a user inputs their schedule and destination information for the day, the device sends that information to the server, which then uses a weather forecast API to retrieve and record the weather information for the destination.

[0353] 4. Coordinate Generation

[0354] The server integrates and analyzes the user's profile information, registered clothing information, schedule and destination information, weather forecast information, and emotional data. This information is input into an algorithm using a generative AI model to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device and displayed to the user.

[0355] 5. Virtual try-on simulation

[0356] Users can simulate trying on outfits created using an avatar in a virtual space, and visually check the fitting of the clothes in real time through smart glasses or a head-mounted display.

[0357] 6. Consultation function

[0358] When a user has trouble with outfits or makeup, they can send a consultation request to a professional coordinator. The device sends the request to the server, and the server provides the request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device and displays it to the user.

[0359] Specific examples

[0360] A specific scenario is shown below.

[0361] For example, if a user enters "I plan to go shopping with a friend in Tokyo this weekend," the server retrieves Tokyo's weather information (e.g., sunny, 18°C). The emotion recognition device detects that the user is in a relaxed emotional state while using the app, and this information is sent to the server in real time. The server integrates the user's profile information (e.g., height 175cm, weight 70kg, preferred style casual), clothing information, schedule and weather information, and emotional information, and uses a generative AI model to suggest the optimal outfit. In this case, an example outfit might be "blue shirt, black jeans, and sneakers." The user can virtually try on the outfit in real time to check the suggested outfit.

[0362] An example prompt is:

[0363] "Based on the profile of user ID: 12345, please suggest a relaxed yet casual style that would be perfect for shopping in Tokyo. The weather forecast is sunny with a temperature of 18 degrees."

[0364] This allows users to enjoy a more personalized fashion experience.

[0365] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0366] Step 1: Register your user information

[0367] A user installs the application on their device and creates an account. They enter detailed profile information such as their height, weight, style preferences, and skin tone. The entered profile information is sent from the device to the server and stored on the server. The user also uploads photos of clothing they own, and the device performs image analysis to extract data on the type, color, and shape of the clothing and sends it to the server. The input for this step is the user's profile information and clothing information, and the output is the data stored on the server.

[0368] Step 2: Obtaining emotional information

[0369] Emotional information is acquired in real time. While a user uses an app with smart glasses or a head-mounted display, these devices capture the user's facial expressions and voice tone. The device uses an emotion recognition algorithm to analyze the user's emotions from the acquired data and send the results to the server. The input of this step is the user's facial expressions and voice tone data, and the output is the emotional information sent to the server.

[0370] Step 3: Get weather information

[0371] When the user inputs their schedule and destination information for the day into the device, the device sends this to the server. The server uses the weather forecast API to obtain and record weather information for the specified destination. The input for this step is the user's schedule and destination information, as well as data obtained from the weather forecast API, and the output is the obtained weather information.

[0372] Step 4: Generate coordinates

[0373] The server integrates and analyzes the user's profile information, registered clothing information, schedule and destination information, weather forecast information, and emotional data. Using an algorithm based on a generative AI model, it generates optimal fashion, hairstyle, and makeup suggestions from this data. The input for this step is the integrated user data, and the output is the generated outfit suggestions.

[0374] Step 5: View the proposal

[0375] The generated coordination proposal is sent from the server to the terminal and displayed to the user. The input of this step is the generated coordination proposal, and the output is the proposal content displayed on the terminal.

[0376] Step 6: Virtual try-on simulation

[0377] The user simulates trying on the proposed outfit using an avatar in a virtual space. Using smart glasses or a head-mounted display, the user visually checks the fit in real time. The input for this step is the proposed outfit, and the output is the result of the virtual simulation.

[0378] Step 7: Consultation function

[0379] When a user is unsure about how to coordinate, they send a consultation request to a professional coordinator from their terminal to the server. The server provides the request and user information to the professional coordinator and obtains advice from the coordinator. The obtained advice is sent to the terminal via the server and displayed to the user. The input of this step is the user's consultation request and advice from the professional coordinator, and the output is the advice displayed to the user.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] [Second embodiment]

[0384] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0385] 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.

[0386] 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).

[0387] 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.

[0388] 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.

[0389] 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).

[0390] 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.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] 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.

[0395] 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."

[0396] The present invention relates to a system that proposes an optimal overall coordination of fashion, hairstyle, makeup, etc. based on individual information of a user. Specific embodiments of the present invention will be described below.

[0397] System configuration and operation

[0398] 1. User information registration

[0399] Users first install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothes and upload them to the app. The device analyzes these images to extract data such as the type, color, and shape of the clothes, and sends this information to the server as well.

[0400] 2. Get schedule and weather information

[0401] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then retrieves weather information for that location from a weather forecast API based on the destination's location information and records it.

[0402] 3. Coordinate Generation

[0403] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. This information is input into an algorithm that generates outfits. The algorithm takes into account past outfit history, current fashion trends, the user's skin tone, and face shape to generate the optimal combination of fashion, hairstyle, and makeup to suggest. The generated outfit suggestions are sent to the device, which displays them to the user.

[0404] 4. Consultation function

[0405] When a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional coordinator. The device sends the consultation request to the server, and the server provides this request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user.

[0406] Specific examples

[0407] A specific example will be given below for explanation.

[0408] Example: User A (25 years old, female) living in Tokyo has plans to have lunch with a friend in Omotesando in three days.

[0409] 1. Information input: Person A uses the app to input plans to have lunch in Omotesando three days later. The device sends this information to the server, which then retrieves weather information for Omotesando.

[0410] 2. Coordination Generation: The server refers to A’s profile and the list of clothes she owns (e.g., a white blouse, denim pants, and sneakers), and, taking into account that the weather is sunny and the temperature is 20 degrees, suggests a combination of a white blouse, denim pants, and sneakers. It also recommends natural makeup and a loose wavy hairstyle.

[0411] 3. Displaying and selecting proposals: The device displays these proposals to Person A, who then accepts all of them.

[0412] 4. Consultation function: If user A feels unsure about her makeup, she can send a consultation request to a professional makeup artist. The device sends the request, the server notifies the makeup artist of the question, and the artist provides advice on adding natural brown eyeshadow.

[0413] 5. Displaying Advice: The device displays advice to Person A, who then follows it to finish applying their makeup.

[0414] This allows users to efficiently complete their outfits for the day. This system reduces the worries users have about their daily fashion and provides personalized total outfits.

[0415] The processing flow will be explained below.

[0416] Step 1:

[0417] A user installs the app and creates an account on their device. The user enters basic information (name, email address, password), which the device sends to the server to create the account.

[0418] Step 2:

[0419] The user enters profile information such as height, weight, style preferences, skin color, hairstyle, etc. The device sends this information to the server and stores it as the user's profile data.

[0420] Step 3:

[0421] Users take photos of their clothes and upload them to the app. The device analyzes the uploaded images and extracts data such as the type, color, and shape of the clothes. The extracted data is sent from the device to a server and added to the user's clothing list.

[0422] Step 4:

[0423] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends the plan information to the server, and the server retrieves weather information from the weather forecast API based on the location information of the destination.

[0424] Step 5:

[0425] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information, and then runs an algorithm to generate suggested outfits, creating optimal combinations of fashion, hairstyle, and makeup.

[0426] Step 6:

[0427] The server sends the generated coordination suggestions to the terminal, which displays them to the user. The user checks the suggestions and selects an appropriate coordination. The selection result is sent from the terminal to the server and recorded.

[0428] Step 7:

[0429] If the user wants more detailed advice, he / she sends a consultation request to the professional coordinator. The terminal sends the request to the server, and the server notifies the professional coordinator of the consultation content and the user information.

[0430] Step 8:

[0431] A professional coordinator creates advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user. The user then uses the advice to optimize their coordination.

[0432] Example 1

[0433] 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."

[0434] In today's busy lifestyles, it is difficult for users to efficiently coordinate their daily outfits, resulting in significant stress in making choices. There are also limited ways to easily obtain expert advice on fashion and makeup. Given these circumstances, there is a need for a system that can suggest optimal fashion, hairstyle, and makeup outfits tailored to individual user needs, and quickly obtain expert opinions.

[0435] 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.

[0436] In this invention, the server includes means for acquiring profile information from the user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather forecast information, means for executing an algorithm for generating outfit suggestions, means for displaying the generated outfit suggestions to the user, means for sending a consultation request to a professional expert and acquiring a response thereto, and means for displaying the acquired response to the user. This allows the user to receive suggestions for efficient fashion, hairstyle, and makeup coordination tailored to their individual needs, and to receive prompt advice from an expert.

[0437] "User profile information" means basic personal information such as a user's height, weight, style preferences, skin color, hairstyle, etc.

[0438] "Clothing images and clothing information" refers to photos of clothing owned by the user and detailed information such as the type, color, and shape of the clothing.

[0439] "Plan and destination information" is information about the schedule for the day and the places to visit that is entered by the user.

[0440] "Weather forecast information" is information about the weather at a specified location and time, obtained from an external weather forecast API or the like.

[0441] The "algorithm for generating suggested outfits" is a program process that generates optimal combinations of fashion, hairstyle, and makeup based on the user's profile information, clothing list, schedule, destination information, and weather forecast information.

[0442] The "means for displaying generated coordination suggestions to the user" is an interface for displaying the coordination suggestions generated by the algorithm on the user's terminal.

[0443] "Means for sending a consultation request to a professional expert and obtaining a reply" refers to a communication means for sending a consultation from a user to an expert and obtaining a reply from the expert.

[0444] The "means for displaying the obtained answer to the user" is an interface for displaying the advice obtained from the professional expert on the user's device.

[0445] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information. This system includes the following main components:

[0446] 1. User information registration

[0447] Users install a dedicated application on their device and perform the initial setup. At this time, they are required to enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to a server and stored on the server. In addition, users take photos of their clothing and upload them to the app. The device uses image analysis technology to extract information such as the type, color, and shape of the clothing and sends it to the server. This information is stored on the server as the user's basic data.

[0448] 2. Retrieving schedule and weather information

[0449] When a user inputs their plans for the day (destination, people to meet, events, etc.), the device sends that information to the server. The server then obtains weather information from an external weather forecast API based on the destination's location information and stores this information along with the user's plan data. This allows the server to efficiently manage the user's plans for the day and suggest optimal outfits.

[0450] 3. Coordinate Generation

[0451] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. This information is then processed by a generative AI model to generate optimal combinations of fashion, hairstyle, and makeup. The algorithm also takes into account past outfit history, current fashion trends, the user's skin tone, and face shape. The generated outfit suggestions are sent to the device and displayed to the user.

[0452] As a concrete example, consider the case where User A (25 years old, female) living in Tokyo plans to have lunch with a friend in Omotesando three days from now. User A enters this plan through the app, and her device sends this information to the server. The server retrieves weather information for Omotesando and confirms that it is sunny with a temperature of 20 degrees. Next, it references User A's profile information and her clothing list (e.g., white blouse, denim pants, sneakers), and generates optimal outfit suggestions that take the weather information into account. This suggests a combination of a white blouse, denim pants, and sneakers, as well as natural makeup and a loose, wavy hairstyle. The suggestions are displayed on the device, and User A can review and select the suggestions.

[0453] An example of a prompt sentence can be written as follows:

[0454] User A (25 years old, female) is planning to have lunch with a friend in Omotesando in three days. She has a white blouse, denim pants, and sneakers. The weather is sunny and the temperature is 20 degrees. Please suggest the best fashion, makeup, and hairstyle for her.

[0455] 4. Consultation function

[0456] If a user is unsure about the suggested outfit or makeup, they can send a request for advice to a professional expert. The device sends the request to the server, which notifies the professional expert of the request. The expert creates advice based on the user information and the request and sends it back to the server. The server then sends this advice to the device and displays it to the user. This allows the user to complete their outfit based on the detailed advice.

[0457] This system allows users to efficiently complete their outfits for the day, reducing the hassle of daily fashion and allowing them to enjoy personalized, total outfits.

[0458] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0459] Step 1: Register your user information

[0460] 1. Application installation and initial settings

[0461] Users can start using the system by installing a dedicated application on their device and creating an account.

[0462] Input: Profile information such as the user's height, weight, style preferences, skin tone, hairstyle, etc.

[0463] Output: The profile information is saved on the server.

[0464] 2. Enter your profile information

[0465] Users use the application to enter profile information, which the device then sends to the server, which stores the information in a database.

[0466] Input: Profile information.

[0467] Output: The profile information is saved in the database.

[0468] 3. Upload a photo of your outfit

[0469] Users take photos of their clothing and upload them to the app. The device uses image analysis technology to extract information such as the type, color, and shape of the clothing. The extracted information is sent to a server, which stores it in a database.

[0470] Input: Clothing images.

[0471] Output: Clothing information is saved in the database.

[0472] Step 2: Get schedule and weather information

[0473] 1. Enter your schedule

[0474] The user enters their plans for the day (destinations, people to meet, events, etc.) into the app, and the device sends this information to the server.

[0475] Input: User's appointment information.

[0476] Output: The schedule information is saved on the server.

[0477] 2. Obtaining weather information

[0478] The server calls an external weather forecast API based on the destination of the schedule information and obtains weather information for the specified location. This information is stored on the server.

[0479] Input: Destination information.

[0480] Output: Weather forecast information is saved on the server.

[0481] Step 3: Generate coordinates

[0482] 1. Information synthesis and analysis

[0483] The server combines the user's profile information, clothing list, schedule and weather information to input into a generative AI model.

[0484] Input: User profile information, clothing list, schedule, weather information.

[0485] Output: The integrated data is fed into a generative AI model.

[0486] 2. Coordination Proposal Generation

[0487] The generative AI model takes into account past outfit history, the latest fashion trends, and the user's skin tone and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent from the server to the device.

[0488] Input: Integrated data.

[0489] Output: A coordination proposal is generated and sent to the terminal.

[0490] 3. Display of outfits

[0491] The device displays the coordination proposal to the user, who can then review the proposal and choose whether to accept it.

[0492] Input: Coordination suggestions.

[0493] Output: Coordination suggestions are displayed to the user.

[0494] Step 4: Use the consultation feature

[0495] 1. Submit a consultation request

[0496] If a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional from the app, and the device will send the request and user information to the server.

[0497] Input: Consultation request.

[0498] Output: The request is sent to the server.

[0499] 2. Notification to the Expert

[0500] When the server receives the request, it notifies the professional and provides the user information and the request details.

[0501] Input: Consultation request.

[0502] Output: A notification is sent to the expert.

[0503] 3. Creating and sending advice

[0504] The expert creates detailed advice based on the user information and the request content and sends it to the server, which then sends the advice to the device.

[0505] Enter: expert advice.

[0506] Output: Advice is sent to the device via the server.

[0507] 4. Displaying Advice

[0508] The device will display advice to the user, who can then follow the advice to complete their outfit.

[0509] Enter: expert advice.

[0510] Output: The advice is displayed to the user.

[0511] (Application example 1)

[0512] 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."

[0513] Today, when users consider the optimal fashion coordination based on their profile information and the clothes they own, it takes time and effort, and there is no guarantee that the results will be satisfactory. Furthermore, there are limited ways to check outfit combinations without actually trying on clothes, or to visually check the suggested outfits, making it difficult to decide whether to buy or rent. Therefore, there is a need for an efficient, visually confirmable fashion coordination suggestion system.

[0514] 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.

[0515] In this invention, the server includes means for acquiring profile information from a user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather forecast information, means for executing an algorithm for generating coordinated outfits to be suggested, means for displaying the generated coordinated outfit suggestions to the user, means for sending a consultation request to a professional coordinator and acquiring a response, means for displaying the acquired response to the user, augmented reality means for generating an avatar for the user and applying the coordinated outfit to the avatar and displaying it in real space, and means for renting the suggested coordinated outfits. This allows the user to efficiently receive suggestions for optimal fashion coordinated outfits, and visual confirmation makes it easier to decide whether to purchase or rent.

[0516] A "user" is a person who uses the system and provides profile information and information about the clothing they own.

[0517] "Profile Information" refers to detailed personal data such as a user's height, weight, style preferences, skin tone, hairstyle, etc.

[0518] "Images of clothes and information about clothes" refers to photos of each piece of clothing owned by the user and detailed data such as its type, color, shape, etc.

[0519] "Plan and destination information" refers to detailed schedule information such as places the user plans to go to, events, and people they plan to meet in the future.

[0520] "Weather forecast information" is weather forecast data for the location and date and time the user plans to go to.

[0521] "Coordination suggestions" refer to the optimal combination of clothing, hairstyle, makeup, etc. that a user should wear that day based on the user's profile information and weather information obtained.

[0522] An "algorithm" is a computational procedure for generating optimal outfit suggestions based on collected information.

[0523] "Augmented reality means" refers to technology for generating a user's avatar and visually displaying suggested outfits in real space.

[0524] "Means for renting" refers to a function that allows you to temporarily borrow suggested outfits or items.

[0525] The "server" is a device that receives and stores various information sent by users and generates coordination suggestions.

[0526] This system collects detailed user profile information, real-world weather and schedule information, and proposes optimal fashion coordination. This system integrates multiple technologies to enhance user convenience.

[0527] System configuration and operation

[0528] 1. User information registration

[0529] First, the user installs a dedicated application on the device and performs initial setup. The user then enters detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This information is sent from the device to a server and stored. The user also takes pictures of clothes they own and uploads them to the app. The device analyzes these images and extracts information such as the type, color, and shape of the clothes, which is then sent to the server.

[0530] 2. Get schedule and weather information

[0531] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then uses the weather forecast API to obtain and record weather information for the destination based on the location information.

[0532] 3. Coordinate Generation

[0533] The server integrates and analyzes the user's profile information, list of clothing items, schedule and destination information, and weather forecast information. This information is input into an algorithm that generates outfits. The algorithm also takes into account the user's skin tone and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device, which displays them to the user.

[0534] 4. Avatar generation and augmented reality display

[0535] The system generates an avatar for the user and applies the suggested outfits to it. Furthermore, by utilizing augmented reality, users can project the avatar into the real world using smart glasses or a head-mounted display, allowing them to visually check the outfits.

[0536] 5. Rental and consultation features

[0537] There is also a function to temporarily rent suggested outfits and items. If users are unsure about what to wear, they can send a consultation request to a professional coordinator, and the answer will be retrieved and displayed.

[0538] Hardware and software used

[0539] Hardware: Smartphones, smart glasses, head-mounted displays

[0540] Software: Python, OpenCV, ARCore, ARKit, WeatherAPI

[0541] The system processes a variety of data and generates optimal outfits based on that data. Users can visually check the outfits and efficiently choose the outfit that best suits them.

[0542] Specific examples

[0543] For example, say a user has an appointment in Tokyo one day, has light skin tones, and prefers casual clothing. They enter this information into the app. The server then retrieves this information along with the weather forecast for that day. Based on the forecast of a sunny 20-degree weather, the server suggests a white T-shirt, denim shorts, and sneakers. This suggestion is visually displayed as the user's avatar through the smart glasses. If the user is unsure about which accessories to choose, they can consult with a professional coordinator and receive additional suggestions.

[0544] Prompt Sentence Examples

[0545] Based on the user's profile information (height: 165cm, weight: 55kg, preference: casual, skin tone: light, hairstyle: long) and the destination location (Tokyo), generate the best outfit suggestions for a day when the temperature is 20 degrees. The suggestions should include tops, bottoms, and shoes.

[0546] As described above, this system efficiently provides optimal coordination based on detailed user information.

[0547] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0548] Step 1:

[0549] The user installs the application on the device and performs initial setup. The user enters their profile information (height, weight, style preferences, skin color, hairstyle, etc.). The entered profile information is sent from the device to the server and saved on the server. The server processes the entered information by organizing it for each user and registering it in a database.

[0550] Step 2:

[0551] Users take pictures of their clothes and upload them to the app. The device analyzes the uploaded images and extracts detailed data such as the type, color, and shape of the clothes. The extracted data is sent to a server and saved as a list of the user's belongings. A deep learning model is used for the analysis, and the image data is converted into text information.

[0552] Step 3:

[0553] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends this information to the server. The server uses the location information of the destination to obtain and record weather information for that location using a weather forecast API. Specific inputs include date, time, and location information, and the output is weather forecast information data.

[0554] Step 4:

[0555] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. It then runs an algorithm to generate outfits based on this data. The algorithm comprehensively evaluates multiple factors and generates the optimal combination of fashion, hairstyle, and makeup to suggest. The output is a specific outfit suggestion.

[0556] Step 5:

[0557] The generated coordination proposal is sent from the server to the terminal, which displays it to the user. The user checks the proposed coordination and, if necessary, sends a consultation request to a professional coordinator. This request is sent from the terminal to the server, which provides the request to the professional coordinator.

[0558] Step 6:

[0559] The professional coordinator creates advice based on the request and sends it to the server, which retrieves the advice and sends it back to the user. Specifically, the professional coordinator evaluates the proposed coordination and provides additional advice.

[0560] Step 7:

[0561] The server generates an avatar for the user and applies the proposed outfits to the avatar. Using augmented reality, the user visually sees the avatar in real space through smart glasses or a head-mounted display. The server sends the generated avatar information to the device, which displays it in the augmented reality environment.

[0562] Step 8:

[0563] When a user wants to temporarily rent a suggested outfit or item, the device sends a rental request to the server. The server processes the request, checks for available items, and provides them to the user. Specifically, it checks the inventory of the suggested item and arranges for delivery.

[0564] 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.

[0565] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments of the present invention are described below.

[0566] System configuration and operation

[0567] 1. User information registration

[0568] Users first install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothes and upload them to the app. The device analyzes these images to extract data such as the type, color, and shape of the clothes, and sends this information to the server as well.

[0569] 2. Get schedule and weather information

[0570] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then retrieves weather information for that location from a weather forecast API based on the destination's location information and records it.

[0571] 3. Acquiring emotional information

[0572] While a user is using the app, the emotion engine collects data (such as facial expressions, voice tone, and input text) to recognize the user's emotions. This data is sent from the device to a server and stored as the user's emotion information.

[0573] 4. Coordinate Generation

[0574] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, weather forecast information, and emotional information. This information is input into an algorithm that generates outfits. The algorithm takes into account past outfit history, current fashion trends, the user's skin tone, and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device, which displays them to the user.

[0575] 5. Consultation function

[0576] When a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional coordinator. The device sends the consultation request to the server, and the server provides this request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user.

[0577] Specific examples

[0578] A specific example will be given below for explanation.

[0579] Example: User B (30 years old, male) living in Tokyo plans to go shopping in Shinjuku with a friend on the weekend.

[0580] 1. Information input: Person B uses the app to input his / her plans to go shopping in Shinjuku on the weekend. The device sends this information to the server, which then retrieves the weather information for Shinjuku.

[0581] 2. Acquisition of emotional information: While B is using the app, the emotion engine analyzes B's emotions from his facial expressions and tone of voice and detects that he is relaxed. This emotional information is sent to the server.

[0582] 3. Coordination Generation: The server refers to B’s profile and the list of clothes she owns (e.g., khaki jacket, black jeans, sneakers), and, taking into account the weather information that it is sunny with a temperature of 18 degrees and her relaxed emotional state, suggests a combination of khaki jacket, black jeans, and sneakers. It also recommends natural makeup and a casual hairstyle.

[0583] 4. Display and select proposals: The device displays the proposals to Person B, who accepts all of them.

[0584] 5. Consultation function: If Person B feels unsure about their styling, they can send a consultation request to a professional fashion coordinator. The device sends the request, and the server notifies the coordinator of the question and Person B's information. The coordinator then provides appropriate advice, which the server sends to the device, and Person B uses the advice to finalize their styling.

[0585] This allows users to enjoy efficient and personalized outfits every day. By taking into account the user's emotional state, the system provides more appropriate and comfortable outfit suggestions.

[0586] The processing flow will be explained below.

[0587] Step 1:

[0588] A user installs the app and creates an account on their device. The user enters basic information (name, email address, password), which the device sends to the server to create the account.

[0589] Step 2:

[0590] The user enters profile information such as height, weight, style preferences, skin color, hairstyle, etc. The device sends this information to the server and stores it as the user's profile data.

[0591] Step 3:

[0592] Users take photos of their clothes and upload them to the app. The device analyzes the uploaded images and extracts data such as the type, color, and shape of the clothes. The extracted data is sent from the device to a server and added to the user's clothing list.

[0593] Step 4:

[0594] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends the plan information to the server, and the server retrieves weather information from the weather forecast API based on the location information of the destination.

[0595] Step 5:

[0596] While a user is using the app, the emotion engine collects data (e.g., facial expressions, voice tone, and input text) to recognize the user's emotions. This emotion data is sent from the device to the server and stored as the user's emotion information.

[0597] Step 6:

[0598] The server analyzes the user's profile information, clothing list, schedule and destination information, weather forecast information, and emotional information, and inputs this information into an algorithm to generate the optimal combination of fashion, hairstyle, and makeup.

[0599] Step 7:

[0600] The server sends the generated coordination suggestions to the terminal, which displays them to the user. The user checks the suggestions and selects an appropriate coordination. The terminal then sends the selection result to the server, where it is recorded.

[0601] Step 8:

[0602] If the user wants more detailed advice, he / she sends a consultation request to the professional coordinator. The terminal sends the request to the server, and the server notifies the professional coordinator of the consultation content and the user information.

[0603] Step 9:

[0604] A professional coordinator creates advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user. The user then uses the advice to optimize their coordination.

[0605] Step 10:

[0606] The user provides emotional feedback on the proposed outfits, and the device sends the emotional feedback to the server, which uses it to optimize future outfit suggestions.

[0607] Example 2

[0608] 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."

[0609] Conventional outfit suggestion systems take into account a user's personal information and the clothing they own, but it is difficult to provide personalized suggestions that comprehensively consider the user's emotional state, detailed schedule, and weather information. As a result, the suggested outfits often do not match the user's situation or emotions, resulting in a lack of satisfaction. Furthermore, there is a lack of a way to obtain advice from experts in real time.

[0610] 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.

[0611] In this invention, the server includes means for acquiring personal information from the user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather information, means for analyzing the emotional state, means for executing an algorithm for generating outfit suggestions, means for displaying the generated outfit suggestions to the user, means for sending a consultation request to an expert and obtaining a response, and means for displaying the obtained response to the user. This enables personalized outfit suggestions that comprehensively consider the user's personal information, clothing, schedule, weather information, and emotional state. Furthermore, by obtaining advice from an expert, the user can achieve a more satisfying outfit.

[0612] A "user" is a person who uses this system to receive coordination suggestions and advice.

[0613] "Personal information" refers to detailed profile information necessary for coordinating outfits, such as the user's height, weight, style preferences, skin color, hairstyle, etc.

[0614] "Images of clothing and information about clothing" refers to photographs of clothing owned by the user, as well as information such as the type, color, and shape of the clothing.

[0615] "Plan and destination information" is information input by the user about the plan and destination for the day, people to meet, events, and the like.

[0616] "Weather information" refers to information about the weather at a location, obtained using a weather forecast API based on the location information of the destination.

[0617] The "means for analyzing emotional state" refers to software or a system that analyzes the user's facial expression, tone of voice, and input text to analyze the user's emotional state.

[0618] The "algorithm for generating outfit suggestions" is a program that combines a user's personal information, a list of clothing items they own, information about their schedule and destination, weather information, and emotional state information to generate optimal fashion, hairstyle, and makeup.

[0619] The "means for displaying the generated coordination proposal to the user" refers to a terminal screen or application for presenting the coordination proposal sent from the server to the user.

[0620] An "expert" is a professional, such as a fashion coordinator, who provides users with advice on coordinating outfits.

[0621] The "means for sending a consultation request and receiving a response" refers to a communication means or system that allows a user to send a consultation request to a specialist and receive a response.

[0622] "Integrated consideration" means comprehensively analyzing the user's personal information, clothing, schedule, weather information, and emotional state, and then providing coordination suggestions and advice based on that analysis.

[0623] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments of the present invention are described in detail below.

[0624] 1. User information registration

[0625] How it works: A user installs the application on their device and creates an account. On their device, they enter detailed profile information, such as their height, weight, style preferences, skin tone, and hairstyle. This profile information is sent from the device to a server and stored as the user's basic data.

[0626] Hardware / software used: Devices (smartphones, tablets), servers, Cloud Vision API.

[0627] A specific example: A user takes a photo of their clothes and uploads it to the app. The device analyzes the image using Cloud Vision API and extracts data such as the type, color, and shape of the clothes. This information is then sent to the server.

[0628] 2. Get schedule and weather information

[0629] How it works: A user enters their plans for the day (destinations, people to meet, events, etc.) into the app. The device then sends this information to the server.

[0630] Hardware / software used: Device, server, weather forecast API (e.g. OpenWeatherMap API).

[0631] Specific example: When a user enters plans to go to a specific place on a specific date, the server retrieves and records the weather information for that place via a weather forecast API.

[0632] 3. Acquiring emotional information

[0633] How it works: Collects data to recognize emotions while users are using the app.

[0634] Hardware / software used: Device camera, microphone, emotion recognition software (e.g. Affectiva SDK).

[0635] A concrete example: A user's facial expressions and tone of voice are captured and analyzed using emotion recognition software. The analyzed data is sent from the device to a server and stored as user emotional information.

[0636] 4. Coordinate Generation

[0637] How it works: The server generates optimal coordination suggestions based on the information it collects.

[0638] Hardware / software used: Server, generative AI model.

[0639] Specific example: The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, weather information, and emotional information. Using a generative AI model, this information is analyzed based on the prompt text to generate outfit suggestions.

[0640] Example prompt: "Please suggest a casual outfit for going to Shinjuku in a relaxed state on a sunny, 18-degree day."

[0641] 5. Proposal display and consultation function

[0642] Behavior: The generated coordination suggestions are displayed to the user, and an expert is consulted if necessary.

[0643] Hardware / software used: terminals, servers.

[0644] Specific example: If a user has questions or concerns about the proposed outfit, the device sends a consultation request to the server. The server provides the request along with the user's information to an expert, and the expert's advice is sent to the device and displayed.

[0645] The system allows users to receive personalized outfit suggestions based on their individual information and emotional state, and also offers expert advice, improving user satisfaction and the quality of their experience.

[0646] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0647] Step 1:

[0648] Registering user information

[0649] Input: User's personal information (height, weight, style preferences, skin tone, hairstyle)

[0650] Specific operation: The user installs and launches the application, creates an account, and the device displays a user information input screen, where the user enters their personal information.

[0651] Data processing / calculation: The device sends the entered personal information to the server.

[0652] Output: The server stores the received personal information in a database.

[0653] Step 2:

[0654] Clothing information registration

[0655] Input: Images of clothing owned by the user

[0656] How it works: The user takes a photo of the garment and uploads it to the app. The device then analyzes the image using image analysis software (e.g., Cloud Vision API).

[0657] Data processing / calculation: The device extracts data such as the type, color, and shape of the clothing from the image and sends it to the server.

[0658] Output: The server stores the received clothing information in a database.

[0659] Step 3:

[0660] Get schedule and weather information

[0661] Input: User's schedule and destination for the day

[0662] Specific operation: The user enters the schedule for the day into the app. The device sends the schedule information to the server.

[0663] Data processing / calculation: The server obtains weather information from a weather forecast API (e.g., OpenWeatherMap API) based on the destination's location information and associates it with the schedule information.

[0664] Output: The weather information obtained by the server is saved in a database.

[0665] Step 4:

[0666] Acquiring emotional information

[0667] Input: User facial expressions, voice tone, input text

[0668] How it works: While the user is using the app, the device's camera and microphone capture the user's facial expressions and voice in real time, while simultaneously monitoring text input.

[0669] Data processing / calculation: The device analyzes the captured data using emotion analysis software (e.g., Affectiva SDK) to generate emotional state information, which is then sent to the server.

[0670] Output: The server stores the received emotional state information in a database.

[0671] Step 5:

[0672] Coordinate generation

[0673] Input: User profile information, clothing list, schedule and destination information, weather information, emotional state information

[0674] Specific operation: The server aggregates all the user's information and generates coordination suggestions using a generative AI model. It inputs the user's information into the AI ​​model using a prompt sentence.

[0675] Data processing / calculation: Based on the prompt, the generative AI model analyzes all information and generates the optimal fashion, hairstyle, and makeup.

[0676] Example prompt: "Please suggest a casual outfit for going to Shinjuku in a relaxed state on a sunny, 18-degree day."

[0677] Output: The server sends the generated coordination proposal to the device.

[0678] Step 6:

[0679] Proposal display and consultation function

[0680] Input: Generated coordination proposal, user consultation request

[0681] Specific operation: The terminal displays the coordination proposals received from the server to the user. If necessary, the user can send a consultation request to an expert from the terminal.

[0682] Data processing / calculation: The server provides the request and user information to the expert and obtains advice from the expert.

[0683] Output: The server sends the advice to the terminal, which displays it to the user.

[0684] Through the above processing steps, users can receive personalized outfit suggestions based on their individual information and emotional state, and can also receive advice from experts.

[0685] (Application example 2)

[0686] 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."

[0687] Conventional fashion coordination systems suggest outfits based on a user's basic profile and clothing information, but it is difficult to provide personalized suggestions that take into account the user's emotional state, specific schedule, or real-time try-on simulations. Furthermore, there are limited opportunities for users to receive direct advice from professional coordinators. This leaves users with a lack of means to select the outfits that best suit them.

[0688] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0689] In this invention, the server includes means for acquiring and analyzing the user's emotional data, means for running a virtual try-on simulation of the generated outfits, and means for sending a consultation request to a professional outfit coordinator and receiving a response. This allows personalized suggestions for fashion, hairstyles, and makeup to be made through a real-time try-on simulation that takes the user's emotional state into consideration. The professional outfit coordinator can also provide specific advice, enabling more appropriate outfit selection.

[0690] "User" refers to an individual who uses the System.

[0691] "Profile information" refers to personal information such as a user's height, weight, preferred style, and skin tone.

[0692] "Images of clothing and information about clothing" refers to photos of clothing that the user has and data related to the clothing.

[0693] "Schedule and destination information" refers to information such as where the user plans to go that day and events they will attend.

[0694] "Weather forecast information" refers to forecast data regarding the weather in a specified area.

[0695] "Emotional data" refers to data related to emotions obtained from a user's facial expressions, tone of voice, etc.

[0696] "Algorithm" refers to the calculation procedure for integrating various acquired data and generating the optimal fashion coordination.

[0697] "Virtual space" refers to a virtual environment in which users interact using avatars.

[0698] "Try-on simulation" refers to the process of virtually fitting clothing onto an avatar in a virtual space.

[0699] A "professional coordinator" is someone with specialized knowledge of fashion and styling.

[0700] "Consultation Request" means a request submitted by a User to a Professional Coordinator for advice.

[0701] This invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments for carrying out this invention are described below.

[0702] System configuration

[0703] This system is realized by using a user terminal, a server, an emotion recognition device (smart glasses or head-mounted display), and a weather forecast API.

[0704] Operating procedure

[0705] 1. User information registration

[0706] First, users install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, and skin tone. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothing and upload them via the app. This image data is analyzed, and data such as the type, color, and shape of the clothing is extracted and sent to the server.

[0707] 2. Acquiring emotional information

[0708] By using the app on a daily basis and wearing an emotion recognition device (smart glasses or a head-mounted display), emotions are recognized from the user's facial expressions and tone of voice. Emotion data is analyzed in real time and sent from the device to a server.

[0709] 3. Obtaining weather information

[0710] When a user inputs their schedule and destination information for the day, the device sends that information to the server, which then uses a weather forecast API to retrieve and record the weather information for the destination.

[0711] 4. Coordinate Generation

[0712] The server integrates and analyzes the user's profile information, registered clothing information, schedule and destination information, weather forecast information, and emotional data. This information is input into an algorithm using a generative AI model to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device and displayed to the user.

[0713] 5. Virtual try-on simulation

[0714] Users can simulate trying on outfits created using an avatar in a virtual space, and visually check the fitting of the clothes in real time through smart glasses or a head-mounted display.

[0715] 6. Consultation function

[0716] When a user has trouble with outfits or makeup, they can send a consultation request to a professional coordinator. The device sends the request to the server, and the server provides the request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device and displays it to the user.

[0717] Specific examples

[0718] A specific scenario is shown below.

[0719] For example, if a user enters "I plan to go shopping with a friend in Tokyo this weekend," the server retrieves Tokyo's weather information (e.g., sunny, 18°C). The emotion recognition device detects that the user is in a relaxed emotional state while using the app, and this information is sent to the server in real time. The server integrates the user's profile information (e.g., height 175cm, weight 70kg, preferred style casual), clothing information, schedule and weather information, and emotional information, and uses a generative AI model to suggest the optimal outfit. In this case, an example outfit might be "blue shirt, black jeans, and sneakers." The user can virtually try on the outfit in real time to check the suggested outfit.

[0720] An example prompt is:

[0721] "Based on the profile of user ID: 12345, please suggest a relaxed yet casual style that would be perfect for shopping in Tokyo. The weather forecast is sunny with a temperature of 18 degrees."

[0722] This allows users to enjoy a more personalized fashion experience.

[0723] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0724] Step 1: Register your user information

[0725] A user installs the application on their device and creates an account. They enter detailed profile information such as their height, weight, style preferences, and skin tone. The entered profile information is sent from the device to the server and stored on the server. The user also uploads photos of clothing they own, and the device performs image analysis to extract data on the type, color, and shape of the clothing and sends it to the server. The input for this step is the user's profile information and clothing information, and the output is the data stored on the server.

[0726] Step 2: Obtaining emotional information

[0727] Emotional information is acquired in real time. While a user uses an app with smart glasses or a head-mounted display, these devices capture the user's facial expressions and voice tone. The device uses an emotion recognition algorithm to analyze the user's emotions from the acquired data and send the results to the server. The input of this step is the user's facial expressions and voice tone data, and the output is the emotional information sent to the server.

[0728] Step 3: Get weather information

[0729] When the user inputs their schedule and destination information for the day into the device, the device sends this to the server. The server uses the weather forecast API to obtain and record weather information for the specified destination. The input for this step is the user's schedule and destination information, as well as data obtained from the weather forecast API, and the output is the obtained weather information.

[0730] Step 4: Generate coordinates

[0731] The server integrates and analyzes the user's profile information, registered clothing information, schedule and destination information, weather forecast information, and emotional data. Using an algorithm based on a generative AI model, it generates optimal fashion, hairstyle, and makeup suggestions from this data. The input for this step is the integrated user data, and the output is the generated outfit suggestions.

[0732] Step 5: View the proposal

[0733] The generated coordination proposal is sent from the server to the terminal and displayed to the user. The input of this step is the generated coordination proposal, and the output is the proposal content displayed on the terminal.

[0734] Step 6: Virtual try-on simulation

[0735] The user simulates trying on the proposed outfit using an avatar in a virtual space. Using smart glasses or a head-mounted display, the user visually checks the fit in real time. The input for this step is the proposed outfit, and the output is the result of the virtual simulation.

[0736] Step 7: Consultation function

[0737] When a user is unsure about how to coordinate, they send a consultation request to a professional coordinator from their terminal to the server. The server provides the request and user information to the professional coordinator and obtains advice from the coordinator. The obtained advice is sent to the terminal via the server and displayed to the user. The input of this step is the user's consultation request and advice from the professional coordinator, and the output is the advice displayed to the user.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] [Third embodiment]

[0742] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0743] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0744] 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).

[0745] 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.

[0746] 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.

[0747] 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).

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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."

[0754] The present invention relates to a system that proposes an optimal overall coordination of fashion, hairstyle, makeup, etc. based on individual information of a user. Specific embodiments of the present invention will be described below.

[0755] System configuration and operation

[0756] 1. User information registration

[0757] Users first install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothes and upload them to the app. The device analyzes these images to extract data such as the type, color, and shape of the clothes, and sends this information to the server as well.

[0758] 2. Get schedule and weather information

[0759] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then retrieves weather information for that location from a weather forecast API based on the destination's location information and records it.

[0760] 3. Coordinate Generation

[0761] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. This information is input into an algorithm that generates outfits. The algorithm takes into account past outfit history, current fashion trends, the user's skin tone, and face shape to generate the optimal combination of fashion, hairstyle, and makeup to suggest. The generated outfit suggestions are sent to the device, which displays them to the user.

[0762] 4. Consultation function

[0763] When a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional coordinator. The device sends the consultation request to the server, and the server provides this request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user.

[0764] Specific examples

[0765] A specific example will be given below for explanation.

[0766] Example: User A (25 years old, female) living in Tokyo has plans to have lunch with a friend in Omotesando in three days.

[0767] 1. Information input: Person A uses the app to input plans to have lunch in Omotesando three days later. The device sends this information to the server, which then retrieves weather information for Omotesando.

[0768] 2. Coordination Generation: The server refers to A’s profile and the list of clothes she owns (e.g., a white blouse, denim pants, and sneakers), and, taking into account that the weather is sunny and the temperature is 20 degrees, suggests a combination of a white blouse, denim pants, and sneakers. It also recommends natural makeup and a loose wavy hairstyle.

[0769] 3. Displaying and selecting proposals: The device displays these proposals to Person A, who then accepts all of them.

[0770] 4. Consultation function: If user A feels unsure about her makeup, she can send a consultation request to a professional makeup artist. The device sends the request, the server notifies the makeup artist of the question, and the artist provides advice on adding natural brown eyeshadow.

[0771] 5. Displaying Advice: The device displays advice to Person A, who then follows it to finish applying their makeup.

[0772] This allows users to efficiently complete their outfits for the day. This system reduces the worries users have about their daily fashion and provides personalized total outfits.

[0773] The processing flow will be explained below.

[0774] Step 1:

[0775] A user installs the app and creates an account on their device. The user enters basic information (name, email address, password), which the device sends to the server to create the account.

[0776] Step 2:

[0777] The user enters profile information such as height, weight, style preferences, skin color, hairstyle, etc. The device sends this information to the server and stores it as the user's profile data.

[0778] Step 3:

[0779] Users take photos of their clothes and upload them to the app. The device analyzes the uploaded images and extracts data such as the type, color, and shape of the clothes. The extracted data is sent from the device to a server and added to the user's clothing list.

[0780] Step 4:

[0781] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends the plan information to the server, and the server retrieves weather information from the weather forecast API based on the location information of the destination.

[0782] Step 5:

[0783] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information, and then runs an algorithm to generate suggested outfits, creating optimal combinations of fashion, hairstyle, and makeup.

[0784] Step 6:

[0785] The server sends the generated coordination suggestions to the terminal, which displays them to the user. The user checks the suggestions and selects an appropriate coordination. The selection result is sent from the terminal to the server and recorded.

[0786] Step 7:

[0787] If the user wants more detailed advice, he / she sends a consultation request to the professional coordinator. The terminal sends the request to the server, and the server notifies the professional coordinator of the consultation content and the user information.

[0788] Step 8:

[0789] A professional coordinator creates advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user. The user then uses the advice to optimize their coordination.

[0790] Example 1

[0791] 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."

[0792] In today's busy lifestyles, it is difficult for users to efficiently coordinate their daily outfits, resulting in significant stress in making choices. There are also limited ways to easily obtain expert advice on fashion and makeup. Given these circumstances, there is a need for a system that can suggest optimal fashion, hairstyle, and makeup outfits tailored to individual user needs, and quickly obtain expert opinions.

[0793] 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.

[0794] In this invention, the server includes means for acquiring profile information from the user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather forecast information, means for executing an algorithm for generating outfit suggestions, means for displaying the generated outfit suggestions to the user, means for sending a consultation request to a professional expert and acquiring a response thereto, and means for displaying the acquired response to the user. This allows the user to receive suggestions for efficient fashion, hairstyle, and makeup coordination tailored to their individual needs, and to receive prompt advice from an expert.

[0795] "User profile information" means basic personal information such as a user's height, weight, style preferences, skin color, hairstyle, etc.

[0796] "Clothing images and clothing information" refers to photos of clothing owned by the user and detailed information such as the type, color, and shape of the clothing.

[0797] "Plan and destination information" is information about the schedule for the day and the places to visit that is entered by the user.

[0798] "Weather forecast information" is information about the weather at a specified location and time, obtained from an external weather forecast API or the like.

[0799] The "algorithm for generating suggested outfits" is a program process that generates optimal combinations of fashion, hairstyle, and makeup based on the user's profile information, clothing list, schedule, destination information, and weather forecast information.

[0800] The "means for displaying generated coordination suggestions to the user" is an interface for displaying the coordination suggestions generated by the algorithm on the user's terminal.

[0801] "Means for sending a consultation request to a professional expert and obtaining a reply" refers to a communication means for sending a consultation from a user to an expert and obtaining a reply from the expert.

[0802] The "means for displaying the obtained answer to the user" is an interface for displaying the advice obtained from the professional expert on the user's device.

[0803] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information. This system includes the following main components:

[0804] 1. User information registration

[0805] Users install a dedicated application on their device and perform the initial setup. At this time, they are required to enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to a server and stored on the server. In addition, users take photos of their clothing and upload them to the app. The device uses image analysis technology to extract information such as the type, color, and shape of the clothing and sends it to the server. This information is stored on the server as the user's basic data.

[0806] 2. Retrieving schedule and weather information

[0807] When a user inputs their plans for the day (destination, people to meet, events, etc.), the device sends that information to the server. The server then obtains weather information from an external weather forecast API based on the destination's location information and stores this information along with the user's plan data. This allows the server to efficiently manage the user's plans for the day and suggest optimal outfits.

[0808] 3. Coordinate Generation

[0809] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. This information is then processed by a generative AI model to generate optimal combinations of fashion, hairstyle, and makeup. The algorithm also takes into account past outfit history, current fashion trends, the user's skin tone, and face shape. The generated outfit suggestions are sent to the device and displayed to the user.

[0810] As a concrete example, consider the case where User A (25 years old, female) living in Tokyo plans to have lunch with a friend in Omotesando three days from now. User A enters this plan through the app, and her device sends this information to the server. The server retrieves weather information for Omotesando and confirms that it is sunny with a temperature of 20 degrees. Next, it references User A's profile information and her clothing list (e.g., white blouse, denim pants, sneakers), and generates optimal outfit suggestions that take the weather information into account. This suggests a combination of a white blouse, denim pants, and sneakers, as well as natural makeup and a loose, wavy hairstyle. The suggestions are displayed on the device, and User A can review and select the suggestions.

[0811] An example of a prompt sentence can be written as follows:

[0812] User A (25 years old, female) is planning to have lunch with a friend in Omotesando in three days. She has a white blouse, denim pants, and sneakers. The weather is sunny and the temperature is 20 degrees. Please suggest the best fashion, makeup, and hairstyle for her.

[0813] 4. Consultation function

[0814] If a user is unsure about the suggested outfit or makeup, they can send a request for advice to a professional expert. The device sends the request to the server, which notifies the professional expert of the request. The expert creates advice based on the user information and the request and sends it back to the server. The server then sends this advice to the device and displays it to the user. This allows the user to complete their outfit based on the detailed advice.

[0815] This system allows users to efficiently complete their outfits for the day, reducing the hassle of daily fashion and allowing them to enjoy personalized, total outfits.

[0816] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0817] Step 1: Register your user information

[0818] 1. Application installation and initial settings

[0819] Users can start using the system by installing a dedicated application on their device and creating an account.

[0820] Input: Profile information such as the user's height, weight, style preferences, skin tone, hairstyle, etc.

[0821] Output: The profile information is saved on the server.

[0822] 2. Enter your profile information

[0823] Users use the application to enter profile information, which the device then sends to the server, which stores the information in a database.

[0824] Input: Profile information.

[0825] Output: The profile information is saved in the database.

[0826] 3. Upload a photo of your outfit

[0827] Users take photos of their clothing and upload them to the app. The device uses image analysis technology to extract information such as the type, color, and shape of the clothing. The extracted information is sent to a server, which stores it in a database.

[0828] Input: Clothing images.

[0829] Output: Clothing information is saved in the database.

[0830] Step 2: Get schedule and weather information

[0831] 1. Enter your schedule

[0832] The user enters their plans for the day (destinations, people to meet, events, etc.) into the app, and the device sends this information to the server.

[0833] Input: User's appointment information.

[0834] Output: The schedule information is saved on the server.

[0835] 2. Obtaining weather information

[0836] The server calls an external weather forecast API based on the destination of the schedule information and obtains weather information for the specified location. This information is stored on the server.

[0837] Input: Destination information.

[0838] Output: Weather forecast information is saved on the server.

[0839] Step 3: Generate coordinates

[0840] 1. Information synthesis and analysis

[0841] The server combines the user's profile information, clothing list, schedule and weather information to input into a generative AI model.

[0842] Input: User profile information, clothing list, schedule, weather information.

[0843] Output: The integrated data is fed into a generative AI model.

[0844] 2. Coordination Proposal Generation

[0845] The generative AI model takes into account past outfit history, the latest fashion trends, and the user's skin tone and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent from the server to the device.

[0846] Input: Integrated data.

[0847] Output: A coordination proposal is generated and sent to the terminal.

[0848] 3. Display of outfits

[0849] The device displays the coordination proposal to the user, who can then review the proposal and choose whether to accept it.

[0850] Input: Coordination suggestions.

[0851] Output: Coordination suggestions are displayed to the user.

[0852] Step 4: Use the consultation feature

[0853] 1. Submit a consultation request

[0854] If a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional from the app, and the device will send the request and user information to the server.

[0855] Input: Consultation request.

[0856] Output: The request is sent to the server.

[0857] 2. Notification to the Expert

[0858] When the server receives the request, it notifies the professional and provides the user information and the request details.

[0859] Input: Consultation request.

[0860] Output: A notification is sent to the expert.

[0861] 3. Creating and sending advice

[0862] The expert creates detailed advice based on the user information and the request content and sends it to the server, which then sends the advice to the device.

[0863] Enter: expert advice.

[0864] Output: Advice is sent to the device via the server.

[0865] 4. Displaying Advice

[0866] The device will display advice to the user, who can then follow the advice to complete their outfit.

[0867] Enter: expert advice.

[0868] Output: The advice is displayed to the user.

[0869] (Application example 1)

[0870] 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."

[0871] Today, when users consider the optimal fashion coordination based on their profile information and the clothes they own, it takes time and effort, and there is no guarantee that the results will be satisfactory. Furthermore, there are limited ways to check outfit combinations without actually trying on clothes, or to visually check the suggested outfits, making it difficult to decide whether to buy or rent. Therefore, there is a need for an efficient, visually confirmable fashion coordination suggestion system.

[0872] 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.

[0873] In this invention, the server includes means for acquiring profile information from a user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather forecast information, means for executing an algorithm for generating coordinated outfits to be suggested, means for displaying the generated coordinated outfit suggestions to the user, means for sending a consultation request to a professional coordinator and acquiring a response, means for displaying the acquired response to the user, augmented reality means for generating an avatar for the user and applying the coordinated outfit to the avatar and displaying it in real space, and means for renting the suggested coordinated outfits. This allows the user to efficiently receive suggestions for optimal fashion coordinated outfits, and visual confirmation makes it easier to decide whether to purchase or rent.

[0874] A "user" is a person who uses the system and provides profile information and information about the clothing they own.

[0875] "Profile Information" refers to detailed personal data such as a user's height, weight, style preferences, skin tone, hairstyle, etc.

[0876] "Images of clothes and information about clothes" refers to photos of each piece of clothing owned by the user and detailed data such as its type, color, shape, etc.

[0877] "Plan and destination information" refers to detailed schedule information such as places the user plans to go to, events, and people they plan to meet in the future.

[0878] "Weather forecast information" is weather forecast data for the location and date and time the user plans to go to.

[0879] "Coordination suggestions" refer to the optimal combination of clothing, hairstyle, makeup, etc. that a user should wear that day based on the user's profile information and weather information obtained.

[0880] An "algorithm" is a computational procedure for generating optimal outfit suggestions based on collected information.

[0881] "Augmented reality means" refers to technology for generating a user's avatar and visually displaying suggested outfits in real space.

[0882] "Means for renting" refers to a function that allows you to temporarily borrow suggested outfits or items.

[0883] The "server" is a device that receives and stores various information sent by users and generates coordination suggestions.

[0884] This system collects detailed user profile information, real-world weather and schedule information, and proposes optimal fashion coordination. This system integrates multiple technologies to enhance user convenience.

[0885] System configuration and operation

[0886] 1. User information registration

[0887] First, the user installs a dedicated application on the device and performs initial setup. The user then enters detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This information is sent from the device to a server and stored. The user also takes pictures of clothes they own and uploads them to the app. The device analyzes these images and extracts information such as the type, color, and shape of the clothes, which is then sent to the server.

[0888] 2. Get schedule and weather information

[0889] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then uses the weather forecast API to obtain and record weather information for the destination based on the location information.

[0890] 3. Coordinate Generation

[0891] The server integrates and analyzes the user's profile information, list of clothing items, schedule and destination information, and weather forecast information. This information is input into an algorithm that generates outfits. The algorithm also takes into account the user's skin tone and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device, which displays them to the user.

[0892] 4. Avatar generation and augmented reality display

[0893] The system generates an avatar for the user and applies the suggested outfits to it. Furthermore, by utilizing augmented reality, users can project the avatar into the real world using smart glasses or a head-mounted display, allowing them to visually check the outfits.

[0894] 5. Rental and consultation features

[0895] There is also a function to temporarily rent suggested outfits and items. If users are unsure about what to wear, they can send a consultation request to a professional coordinator, and the answer will be retrieved and displayed.

[0896] Hardware and software used

[0897] Hardware: Smartphones, smart glasses, head-mounted displays

[0898] Software: Python, OpenCV, ARCore, ARKit, WeatherAPI

[0899] The system processes a variety of data and generates optimal outfits based on that data. Users can visually check the outfits and efficiently choose the outfit that best suits them.

[0900] Specific examples

[0901] For example, say a user has an appointment in Tokyo one day, has light skin tones, and prefers casual clothing. They enter this information into the app. The server then retrieves this information along with the weather forecast for that day. Based on the forecast of a sunny 20-degree weather, the server suggests a white T-shirt, denim shorts, and sneakers. This suggestion is visually displayed as the user's avatar through the smart glasses. If the user is unsure about which accessories to choose, they can consult with a professional coordinator and receive additional suggestions.

[0902] Prompt Sentence Examples

[0903] Based on the user's profile information (height: 165cm, weight: 55kg, preference: casual, skin tone: light, hairstyle: long) and the destination location (Tokyo), generate the best outfit suggestions for a day when the temperature is 20 degrees. The suggestions should include tops, bottoms, and shoes.

[0904] As described above, this system efficiently provides optimal coordination based on detailed user information.

[0905] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0906] Step 1:

[0907] The user installs the application on the device and performs initial setup. The user enters their profile information (height, weight, style preferences, skin color, hairstyle, etc.). The entered profile information is sent from the device to the server and saved on the server. The server processes the entered information by organizing it for each user and registering it in a database.

[0908] Step 2:

[0909] Users take pictures of their clothes and upload them to the app. The device analyzes the uploaded images and extracts detailed data such as the type, color, and shape of the clothes. The extracted data is sent to a server and saved as a list of the user's belongings. A deep learning model is used for the analysis, and the image data is converted into text information.

[0910] Step 3:

[0911] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends this information to the server. The server uses the location information of the destination to obtain and record weather information for that location using a weather forecast API. Specific inputs include date, time, and location information, and the output is weather forecast information data.

[0912] Step 4:

[0913] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. It then runs an algorithm to generate outfits based on this data. The algorithm comprehensively evaluates multiple factors and generates the optimal combination of fashion, hairstyle, and makeup to suggest. The output is a specific outfit suggestion.

[0914] Step 5:

[0915] The generated coordination proposal is sent from the server to the terminal, which displays it to the user. The user checks the proposed coordination and, if necessary, sends a consultation request to a professional coordinator. This request is sent from the terminal to the server, which provides the request to the professional coordinator.

[0916] Step 6:

[0917] The professional coordinator creates advice based on the request and sends it to the server, which retrieves the advice and sends it back to the user. Specifically, the professional coordinator evaluates the proposed coordination and provides additional advice.

[0918] Step 7:

[0919] The server generates an avatar for the user and applies the proposed outfits to the avatar. Using augmented reality, the user visually sees the avatar in real space through smart glasses or a head-mounted display. The server sends the generated avatar information to the device, which displays it in the augmented reality environment.

[0920] Step 8:

[0921] When a user wants to temporarily rent a suggested outfit or item, the device sends a rental request to the server. The server processes the request, checks for available items, and provides them to the user. Specifically, it checks the inventory of the suggested item and arranges for delivery.

[0922] 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.

[0923] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments of the present invention are described below.

[0924] System configuration and operation

[0925] 1. User information registration

[0926] Users first install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothes and upload them to the app. The device analyzes these images to extract data such as the type, color, and shape of the clothes, and sends this information to the server as well.

[0927] 2. Get schedule and weather information

[0928] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then retrieves weather information for that location from a weather forecast API based on the destination's location information and records it.

[0929] 3. Acquiring emotional information

[0930] While a user is using the app, the emotion engine collects data (such as facial expressions, voice tone, and input text) to recognize the user's emotions. This data is sent from the device to a server and stored as the user's emotion information.

[0931] 4. Coordinate Generation

[0932] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, weather forecast information, and emotional information. This information is input into an algorithm that generates outfits. The algorithm takes into account past outfit history, current fashion trends, the user's skin tone, and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device, which displays them to the user.

[0933] 5. Consultation function

[0934] When a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional coordinator. The device sends the consultation request to the server, and the server provides this request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user.

[0935] Specific examples

[0936] A specific example will be given below for explanation.

[0937] Example: User B (30 years old, male) living in Tokyo plans to go shopping in Shinjuku with a friend on the weekend.

[0938] 1. Information input: Person B uses the app to input his / her plans to go shopping in Shinjuku on the weekend. The device sends this information to the server, which then retrieves the weather information for Shinjuku.

[0939] 2. Acquisition of emotional information: While B is using the app, the emotion engine analyzes B's emotions from his facial expressions and tone of voice and detects that he is relaxed. This emotional information is sent to the server.

[0940] 3. Coordination Generation: The server refers to B’s profile and the list of clothes she owns (e.g., khaki jacket, black jeans, sneakers), and, taking into account the weather information that it is sunny with a temperature of 18 degrees and her relaxed emotional state, suggests a combination of khaki jacket, black jeans, and sneakers. It also recommends natural makeup and a casual hairstyle.

[0941] 4. Display and select proposals: The device displays the proposals to Person B, who accepts all of them.

[0942] 5. Consultation function: If Person B feels unsure about their styling, they can send a consultation request to a professional fashion coordinator. The device sends the request, and the server notifies the coordinator of the question and Person B's information. The coordinator then provides appropriate advice, which the server sends to the device, and Person B uses the advice to finalize their styling.

[0943] This allows users to enjoy efficient and personalized outfits every day. By taking into account the user's emotional state, the system provides more appropriate and comfortable outfit suggestions.

[0944] The processing flow will be explained below.

[0945] Step 1:

[0946] A user installs the app and creates an account on their device. The user enters basic information (name, email address, password), which the device sends to the server to create the account.

[0947] Step 2:

[0948] The user enters profile information such as height, weight, style preferences, skin color, hairstyle, etc. The device sends this information to the server and stores it as the user's profile data.

[0949] Step 3:

[0950] Users take photos of their clothes and upload them to the app. The device analyzes the uploaded images and extracts data such as the type, color, and shape of the clothes. The extracted data is sent from the device to a server and added to the user's clothing list.

[0951] Step 4:

[0952] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends the plan information to the server, and the server retrieves weather information from the weather forecast API based on the location information of the destination.

[0953] Step 5:

[0954] While a user is using the app, the emotion engine collects data (e.g., facial expressions, voice tone, and input text) to recognize the user's emotions. This emotion data is sent from the device to the server and stored as the user's emotion information.

[0955] Step 6:

[0956] The server analyzes the user's profile information, clothing list, schedule and destination information, weather forecast information, and emotional information, and inputs this information into an algorithm to generate the optimal combination of fashion, hairstyle, and makeup.

[0957] Step 7:

[0958] The server sends the generated coordination suggestions to the terminal, which displays them to the user. The user checks the suggestions and selects an appropriate coordination. The terminal then sends the selection result to the server, where it is recorded.

[0959] Step 8:

[0960] If the user wants more detailed advice, he / she sends a consultation request to the professional coordinator. The terminal sends the request to the server, and the server notifies the professional coordinator of the consultation content and the user information.

[0961] Step 9:

[0962] A professional coordinator creates advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user. The user then uses the advice to optimize their coordination.

[0963] Step 10:

[0964] The user provides emotional feedback on the proposed outfits, and the device sends the emotional feedback to the server, which uses it to optimize future outfit suggestions.

[0965] Example 2

[0966] 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."

[0967] Conventional outfit suggestion systems take into account a user's personal information and the clothing they own, but it is difficult to provide personalized suggestions that comprehensively consider the user's emotional state, detailed schedule, and weather information. As a result, the suggested outfits often do not match the user's situation or emotions, resulting in a lack of satisfaction. Furthermore, there is a lack of a way to obtain advice from experts in real time.

[0968] 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.

[0969] In this invention, the server includes means for acquiring personal information from the user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather information, means for analyzing the emotional state, means for executing an algorithm for generating outfit suggestions, means for displaying the generated outfit suggestions to the user, means for sending a consultation request to an expert and obtaining a response, and means for displaying the obtained response to the user. This enables personalized outfit suggestions that comprehensively consider the user's personal information, clothing, schedule, weather information, and emotional state. Furthermore, by obtaining advice from an expert, the user can achieve a more satisfying outfit.

[0970] A "user" is a person who uses this system to receive coordination suggestions and advice.

[0971] "Personal information" refers to detailed profile information necessary for coordinating outfits, such as the user's height, weight, style preferences, skin color, hairstyle, etc.

[0972] "Images of clothing and information about clothing" refers to photographs of clothing owned by the user, as well as information such as the type, color, and shape of the clothing.

[0973] "Plan and destination information" is information input by the user about the plan and destination for the day, people to meet, events, and the like.

[0974] "Weather information" refers to information about the weather at a location, obtained using a weather forecast API based on the location information of the destination.

[0975] The "means for analyzing emotional state" refers to software or a system that analyzes the user's facial expression, tone of voice, and input text to analyze the user's emotional state.

[0976] The "algorithm for generating outfit suggestions" is a program that combines a user's personal information, a list of clothing items they own, information about their schedule and destination, weather information, and emotional state information to generate optimal fashion, hairstyle, and makeup.

[0977] The "means for displaying the generated coordination proposal to the user" refers to a terminal screen or application for presenting the coordination proposal sent from the server to the user.

[0978] An "expert" is a professional, such as a fashion coordinator, who provides users with advice on coordinating outfits.

[0979] The "means for sending a consultation request and receiving a response" refers to a communication means or system that allows a user to send a consultation request to a specialist and receive a response.

[0980] "Integrated consideration" means comprehensively analyzing the user's personal information, clothing, schedule, weather information, and emotional state, and then providing coordination suggestions and advice based on that analysis.

[0981] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments of the present invention are described in detail below.

[0982] 1. User information registration

[0983] How it works: A user installs the application on their device and creates an account. On their device, they enter detailed profile information, such as their height, weight, style preferences, skin tone, and hairstyle. This profile information is sent from the device to a server and stored as the user's basic data.

[0984] Hardware / software used: Devices (smartphones, tablets), servers, Cloud Vision API.

[0985] A specific example: A user takes a photo of their clothes and uploads it to the app. The device analyzes the image using Cloud Vision API and extracts data such as the type, color, and shape of the clothes. This information is then sent to the server.

[0986] 2. Get schedule and weather information

[0987] How it works: A user enters their plans for the day (destinations, people to meet, events, etc.) into the app. The device then sends this information to the server.

[0988] Hardware / software used: Device, server, weather forecast API (e.g. OpenWeatherMap API).

[0989] Specific example: When a user enters plans to go to a specific place on a specific date, the server retrieves and records the weather information for that place via a weather forecast API.

[0990] 3. Acquiring emotional information

[0991] How it works: Collects data to recognize emotions while users are using the app.

[0992] Hardware / software used: Device camera, microphone, emotion recognition software (e.g. Affectiva SDK).

[0993] A concrete example: A user's facial expressions and tone of voice are captured and analyzed using emotion recognition software. The analyzed data is sent from the device to a server and stored as user emotional information.

[0994] 4. Coordinate Generation

[0995] How it works: The server generates optimal coordination suggestions based on the information it collects.

[0996] Hardware / software used: Server, generative AI model.

[0997] Specific example: The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, weather information, and emotional information. Using a generative AI model, this information is analyzed based on the prompt text to generate outfit suggestions.

[0998] Example prompt: "Please suggest a casual outfit for going to Shinjuku in a relaxed state on a sunny, 18-degree day."

[0999] 5. Proposal display and consultation function

[1000] Behavior: The generated coordination suggestions are displayed to the user, and an expert is consulted if necessary.

[1001] Hardware / software used: terminals, servers.

[1002] Specific example: If a user has questions or concerns about the proposed outfit, the device sends a consultation request to the server. The server provides the request along with the user's information to an expert, and the expert's advice is sent to the device and displayed.

[1003] The system allows users to receive personalized outfit suggestions based on their individual information and emotional state, and also offers expert advice, improving user satisfaction and the quality of their experience.

[1004] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1005] Step 1:

[1006] Registering user information

[1007] Input: User's personal information (height, weight, style preferences, skin tone, hairstyle)

[1008] Specific operation: The user installs and launches the application, creates an account, and the device displays a user information input screen, where the user enters their personal information.

[1009] Data processing / calculation: The device sends the entered personal information to the server.

[1010] Output: The server stores the received personal information in a database.

[1011] Step 2:

[1012] Clothing information registration

[1013] Input: Images of clothing owned by the user

[1014] How it works: The user takes a photo of the garment and uploads it to the app. The device then analyzes the image using image analysis software (e.g., Cloud Vision API).

[1015] Data processing / calculation: The device extracts data such as the type, color, and shape of the clothing from the image and sends it to the server.

[1016] Output: The server stores the received clothing information in a database.

[1017] Step 3:

[1018] Get schedule and weather information

[1019] Input: User's schedule and destination for the day

[1020] Specific operation: The user enters the schedule for the day into the app. The device sends the schedule information to the server.

[1021] Data processing / calculation: The server obtains weather information from a weather forecast API (e.g., OpenWeatherMap API) based on the destination's location information and associates it with the schedule information.

[1022] Output: The weather information obtained by the server is saved in a database.

[1023] Step 4:

[1024] Acquiring emotional information

[1025] Input: User facial expressions, voice tone, input text

[1026] How it works: While the user is using the app, the device's camera and microphone capture the user's facial expressions and voice in real time, while simultaneously monitoring text input.

[1027] Data processing / calculation: The device analyzes the captured data using emotion analysis software (e.g., Affectiva SDK) to generate emotional state information, which is then sent to the server.

[1028] Output: The server stores the received emotional state information in a database.

[1029] Step 5:

[1030] Coordinate generation

[1031] Input: User profile information, clothing list, schedule and destination information, weather information, emotional state information

[1032] Specific operation: The server aggregates all the user's information and generates coordination suggestions using a generative AI model. It inputs the user's information into the AI ​​model using a prompt sentence.

[1033] Data processing / calculation: Based on the prompt, the generative AI model analyzes all information and generates the optimal fashion, hairstyle, and makeup.

[1034] Example prompt: "Please suggest a casual outfit for going to Shinjuku in a relaxed state on a sunny, 18-degree day."

[1035] Output: The server sends the generated coordination proposal to the device.

[1036] Step 6:

[1037] Proposal display and consultation function

[1038] Input: Generated coordination proposal, user consultation request

[1039] Specific operation: The terminal displays the coordination proposals received from the server to the user. If necessary, the user can send a consultation request to an expert from the terminal.

[1040] Data processing / calculation: The server provides the request and user information to the expert and obtains advice from the expert.

[1041] Output: The server sends the advice to the terminal, which displays it to the user.

[1042] Through the above processing steps, users can receive personalized outfit suggestions based on their individual information and emotional state, and can also receive advice from experts.

[1043] (Application example 2)

[1044] 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."

[1045] Conventional fashion coordination systems suggest outfits based on a user's basic profile and clothing information, but it is difficult to provide personalized suggestions that take into account the user's emotional state, specific schedule, or real-time try-on simulations. Furthermore, there are limited opportunities for users to receive direct advice from professional coordinators. This leaves users with a lack of means to select the outfits that best suit them.

[1046] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1047] In this invention, the server includes means for acquiring and analyzing the user's emotional data, means for running a virtual try-on simulation of the generated outfits, and means for sending a consultation request to a professional outfit coordinator and receiving a response. This allows personalized suggestions for fashion, hairstyles, and makeup to be made through a real-time try-on simulation that takes the user's emotional state into consideration. The professional outfit coordinator can also provide specific advice, enabling more appropriate outfit selection.

[1048] "User" refers to an individual who uses the System.

[1049] "Profile information" refers to personal information such as a user's height, weight, preferred style, and skin tone.

[1050] "Images of clothing and information about clothing" refers to photos of clothing that the user has and data related to the clothing.

[1051] "Schedule and destination information" refers to information such as where the user plans to go that day and events they will attend.

[1052] "Weather forecast information" refers to forecast data regarding the weather in a specified area.

[1053] "Emotional data" refers to data related to emotions obtained from a user's facial expressions, tone of voice, etc.

[1054] "Algorithm" refers to the calculation procedure for integrating various acquired data and generating the optimal fashion coordination.

[1055] "Virtual space" refers to a virtual environment in which users interact using avatars.

[1056] "Try-on simulation" refers to the process of virtually fitting clothing onto an avatar in a virtual space.

[1057] A "professional coordinator" is someone with specialized knowledge of fashion and styling.

[1058] "Consultation Request" means a request submitted by a User to a Professional Coordinator for advice.

[1059] This invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments for carrying out this invention are described below.

[1060] System configuration

[1061] This system is realized by using a user terminal, a server, an emotion recognition device (smart glasses or head-mounted display), and a weather forecast API.

[1062] Operating procedure

[1063] 1. User information registration

[1064] First, users install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, and skin tone. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothing and upload them via the app. This image data is analyzed, and data such as the type, color, and shape of the clothing is extracted and sent to the server.

[1065] 2. Acquiring emotional information

[1066] By using the app on a daily basis and wearing an emotion recognition device (smart glasses or a head-mounted display), emotions are recognized from the user's facial expressions and tone of voice. Emotion data is analyzed in real time and sent from the device to a server.

[1067] 3. Obtaining weather information

[1068] When a user inputs their schedule and destination information for the day, the device sends that information to the server, which then uses a weather forecast API to retrieve and record the weather information for the destination.

[1069] 4. Coordinate Generation

[1070] The server integrates and analyzes the user's profile information, registered clothing information, schedule and destination information, weather forecast information, and emotional data. This information is input into an algorithm using a generative AI model to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device and displayed to the user.

[1071] 5. Virtual try-on simulation

[1072] Users can simulate trying on outfits created using an avatar in a virtual space, and visually check the fitting of the clothes in real time through smart glasses or a head-mounted display.

[1073] 6. Consultation function

[1074] When a user has trouble with outfits or makeup, they can send a consultation request to a professional coordinator. The device sends the request to the server, and the server provides the request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device and displays it to the user.

[1075] Specific examples

[1076] A specific scenario is shown below.

[1077] For example, if a user enters "I plan to go shopping with a friend in Tokyo this weekend," the server retrieves Tokyo's weather information (e.g., sunny, 18°C). The emotion recognition device detects that the user is in a relaxed emotional state while using the app, and this information is sent to the server in real time. The server integrates the user's profile information (e.g., height 175cm, weight 70kg, preferred style casual), clothing information, schedule and weather information, and emotional information, and uses a generative AI model to suggest the optimal outfit. In this case, an example outfit might be "blue shirt, black jeans, and sneakers." The user can virtually try on the outfit in real time to check the suggested outfit.

[1078] An example prompt is:

[1079] "Based on the profile of user ID: 12345, please suggest a relaxed yet casual style that would be perfect for shopping in Tokyo. The weather forecast is sunny with a temperature of 18 degrees."

[1080] This allows users to enjoy a more personalized fashion experience.

[1081] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1082] Step 1: Register your user information

[1083] A user installs the application on their device and creates an account. They enter detailed profile information such as their height, weight, style preferences, and skin tone. The entered profile information is sent from the device to the server and stored on the server. The user also uploads photos of clothing they own, and the device performs image analysis to extract data on the type, color, and shape of the clothing and sends it to the server. The input for this step is the user's profile information and clothing information, and the output is the data stored on the server.

[1084] Step 2: Obtaining emotional information

[1085] Emotional information is acquired in real time. While a user uses an app with smart glasses or a head-mounted display, these devices capture the user's facial expressions and voice tone. The device uses an emotion recognition algorithm to analyze the user's emotions from the acquired data and send the results to the server. The input of this step is the user's facial expressions and voice tone data, and the output is the emotional information sent to the server.

[1086] Step 3: Get weather information

[1087] When the user inputs their schedule and destination information for the day into the device, the device sends this to the server. The server uses the weather forecast API to obtain and record weather information for the specified destination. The input for this step is the user's schedule and destination information, as well as data obtained from the weather forecast API, and the output is the obtained weather information.

[1088] Step 4: Generate coordinates

[1089] The server integrates and analyzes the user's profile information, registered clothing information, schedule and destination information, weather forecast information, and emotional data. Using an algorithm based on a generative AI model, it generates optimal fashion, hairstyle, and makeup suggestions from this data. The input for this step is the integrated user data, and the output is the generated outfit suggestions.

[1090] Step 5: View the proposal

[1091] The generated coordination proposal is sent from the server to the terminal and displayed to the user. The input of this step is the generated coordination proposal, and the output is the proposal content displayed on the terminal.

[1092] Step 6: Virtual try-on simulation

[1093] The user simulates trying on the proposed outfit using an avatar in a virtual space. Using smart glasses or a head-mounted display, the user visually checks the fit in real time. The input for this step is the proposed outfit, and the output is the result of the virtual simulation.

[1094] Step 7: Consultation function

[1095] When a user is unsure about how to coordinate, they send a consultation request to a professional coordinator from their terminal to the server. The server provides the request and user information to the professional coordinator and obtains advice from the coordinator. The obtained advice is sent to the terminal via the server and displayed to the user. The input of this step is the user's consultation request and advice from the professional coordinator, and the output is the advice displayed to the user.

[1096] 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.

[1097] 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.

[1098] 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.

[1099] [Fourth embodiment]

[1100] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1101] 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.

[1102] 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).

[1103] 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.

[1104] 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.

[1105] 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).

[1106] 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.

[1107] 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.

[1108] 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.

[1109] 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.

[1110] 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.

[1111] 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.

[1112] 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."

[1113] The present invention relates to a system that proposes an optimal overall coordination of fashion, hairstyle, makeup, etc. based on individual information of a user. Specific embodiments of the present invention will be described below.

[1114] System configuration and operation

[1115] 1. User information registration

[1116] Users first install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothes and upload them to the app. The device analyzes these images to extract data such as the type, color, and shape of the clothes, and sends this information to the server as well.

[1117] 2. Get schedule and weather information

[1118] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then retrieves weather information for that location from a weather forecast API based on the destination's location information and records it.

[1119] 3. Coordinate Generation

[1120] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. This information is input into an algorithm that generates outfits. The algorithm takes into account past outfit history, current fashion trends, the user's skin tone, and face shape to generate the optimal combination of fashion, hairstyle, and makeup to suggest. The generated outfit suggestions are sent to the device, which displays them to the user.

[1121] 4. Consultation function

[1122] When a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional coordinator. The device sends the consultation request to the server, and the server provides this request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user.

[1123] Specific examples

[1124] A specific example will be given below for explanation.

[1125] Example: User A (25 years old, female) living in Tokyo has plans to have lunch with a friend in Omotesando in three days.

[1126] 1. Information input: Person A uses the app to input plans to have lunch in Omotesando three days later. The device sends this information to the server, which then retrieves weather information for Omotesando.

[1127] 2. Coordination Generation: The server refers to A’s profile and the list of clothes she owns (e.g., a white blouse, denim pants, and sneakers), and, taking into account that the weather is sunny and the temperature is 20 degrees, suggests a combination of a white blouse, denim pants, and sneakers. It also recommends natural makeup and a loose wavy hairstyle.

[1128] 3. Displaying and selecting proposals: The device displays these proposals to Person A, who then accepts all of them.

[1129] 4. Consultation function: If user A feels unsure about her makeup, she can send a consultation request to a professional makeup artist. The device sends the request, the server notifies the makeup artist of the question, and the artist provides advice on adding natural brown eyeshadow.

[1130] 5. Displaying Advice: The device displays advice to Person A, who then follows it to finish applying their makeup.

[1131] This allows users to efficiently complete their outfits for the day. This system reduces the worries users have about their daily fashion and provides personalized total outfits.

[1132] The processing flow will be explained below.

[1133] Step 1:

[1134] A user installs the app and creates an account on their device. The user enters basic information (name, email address, password), which the device sends to the server to create the account.

[1135] Step 2:

[1136] The user enters profile information such as height, weight, style preferences, skin color, hairstyle, etc. The device sends this information to the server and stores it as the user's profile data.

[1137] Step 3:

[1138] Users take photos of their clothes and upload them to the app. The device analyzes the uploaded images and extracts data such as the type, color, and shape of the clothes. The extracted data is sent from the device to a server and added to the user's clothing list.

[1139] Step 4:

[1140] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends the plan information to the server, and the server retrieves weather information from the weather forecast API based on the location information of the destination.

[1141] Step 5:

[1142] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information, and then runs an algorithm to generate suggested outfits, creating optimal combinations of fashion, hairstyle, and makeup.

[1143] Step 6:

[1144] The server sends the generated coordination suggestions to the terminal, which displays them to the user. The user checks the suggestions and selects an appropriate coordination. The selection result is sent from the terminal to the server and recorded.

[1145] Step 7:

[1146] If the user wants more detailed advice, he / she sends a consultation request to the professional coordinator. The terminal sends the request to the server, and the server notifies the professional coordinator of the consultation content and the user information.

[1147] Step 8:

[1148] A professional coordinator creates advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user. The user then uses the advice to optimize their coordination.

[1149] Example 1

[1150] 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."

[1151] In today's busy lifestyles, it is difficult for users to efficiently coordinate their daily outfits, resulting in significant stress in making choices. There are also limited ways to easily obtain expert advice on fashion and makeup. Given these circumstances, there is a need for a system that can suggest optimal fashion, hairstyle, and makeup outfits tailored to individual user needs, and quickly obtain expert opinions.

[1152] 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.

[1153] In this invention, the server includes means for acquiring profile information from the user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather forecast information, means for executing an algorithm for generating outfit suggestions, means for displaying the generated outfit suggestions to the user, means for sending a consultation request to a professional expert and acquiring a response thereto, and means for displaying the acquired response to the user. This allows the user to receive suggestions for efficient fashion, hairstyle, and makeup coordination tailored to their individual needs, and to receive prompt advice from an expert.

[1154] "User profile information" means basic personal information such as a user's height, weight, style preferences, skin color, hairstyle, etc.

[1155] "Clothing images and clothing information" refers to photos of clothing owned by the user and detailed information such as the type, color, and shape of the clothing.

[1156] "Plan and destination information" is information about the schedule for the day and the places to visit that is entered by the user.

[1157] "Weather forecast information" is information about the weather at a specified location and time, obtained from an external weather forecast API or the like.

[1158] The "algorithm for generating suggested outfits" is a program process that generates optimal combinations of fashion, hairstyle, and makeup based on the user's profile information, clothing list, schedule, destination information, and weather forecast information.

[1159] The "means for displaying generated coordination suggestions to the user" is an interface for displaying the coordination suggestions generated by the algorithm on the user's terminal.

[1160] "Means for sending a consultation request to a professional expert and obtaining a reply" refers to a communication means for sending a consultation from a user to an expert and obtaining a reply from the expert.

[1161] The "means for displaying the obtained answer to the user" is an interface for displaying the advice obtained from the professional expert on the user's device.

[1162] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information. This system includes the following main components:

[1163] 1. User information registration

[1164] Users install a dedicated application on their device and perform the initial setup. At this time, they are required to enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to a server and stored on the server. In addition, users take photos of their clothing and upload them to the app. The device uses image analysis technology to extract information such as the type, color, and shape of the clothing and sends it to the server. This information is stored on the server as the user's basic data.

[1165] 2. Retrieving schedule and weather information

[1166] When a user inputs their plans for the day (destination, people to meet, events, etc.), the device sends that information to the server. The server then obtains weather information from an external weather forecast API based on the destination's location information and stores this information along with the user's plan data. This allows the server to efficiently manage the user's plans for the day and suggest optimal outfits.

[1167] 3. Coordinate Generation

[1168] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. This information is then processed by a generative AI model to generate optimal combinations of fashion, hairstyle, and makeup. The algorithm also takes into account past outfit history, current fashion trends, the user's skin tone, and face shape. The generated outfit suggestions are sent to the device and displayed to the user.

[1169] As a concrete example, consider the case where User A (25 years old, female) living in Tokyo plans to have lunch with a friend in Omotesando three days from now. User A enters this plan through the app, and her device sends this information to the server. The server retrieves weather information for Omotesando and confirms that it is sunny with a temperature of 20 degrees. Next, it references User A's profile information and her clothing list (e.g., white blouse, denim pants, sneakers), and generates optimal outfit suggestions that take the weather information into account. This suggests a combination of a white blouse, denim pants, and sneakers, as well as natural makeup and a loose, wavy hairstyle. The suggestions are displayed on the device, and User A can review and select the suggestions.

[1170] An example of a prompt sentence can be written as follows:

[1171] User A (25 years old, female) is planning to have lunch with a friend in Omotesando in three days. She has a white blouse, denim pants, and sneakers. The weather is sunny and the temperature is 20 degrees. Please suggest the best fashion, makeup, and hairstyle for her.

[1172] 4. Consultation function

[1173] If a user is unsure about the suggested outfit or makeup, they can send a request for advice to a professional expert. The device sends the request to the server, which notifies the professional expert of the request. The expert creates advice based on the user information and the request and sends it back to the server. The server then sends this advice to the device and displays it to the user. This allows the user to complete their outfit based on the detailed advice.

[1174] This system allows users to efficiently complete their outfits for the day, reducing the hassle of daily fashion and allowing them to enjoy personalized, total outfits.

[1175] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1176] Step 1: Register your user information

[1177] 1. Application installation and initial settings

[1178] Users can start using the system by installing a dedicated application on their device and creating an account.

[1179] Input: Profile information such as the user's height, weight, style preferences, skin tone, hairstyle, etc.

[1180] Output: The profile information is saved on the server.

[1181] 2. Enter your profile information

[1182] Users use the application to enter profile information, which the device then sends to the server, which stores the information in a database.

[1183] Input: Profile information.

[1184] Output: The profile information is saved in the database.

[1185] 3. Upload a photo of your outfit

[1186] Users take photos of their clothing and upload them to the app. The device uses image analysis technology to extract information such as the type, color, and shape of the clothing. The extracted information is sent to a server, which stores it in a database.

[1187] Input: Clothing images.

[1188] Output: Clothing information is saved in the database.

[1189] Step 2: Get schedule and weather information

[1190] 1. Enter your schedule

[1191] The user enters their plans for the day (destinations, people to meet, events, etc.) into the app, and the device sends this information to the server.

[1192] Input: User's appointment information.

[1193] Output: The schedule information is saved on the server.

[1194] 2. Obtaining weather information

[1195] The server calls an external weather forecast API based on the destination of the schedule information and obtains weather information for the specified location. This information is stored on the server.

[1196] Input: Destination information.

[1197] Output: Weather forecast information is saved on the server.

[1198] Step 3: Generate coordinates

[1199] 1. Information synthesis and analysis

[1200] The server combines the user's profile information, clothing list, schedule and weather information to input into a generative AI model.

[1201] Input: User profile information, clothing list, schedule, weather information.

[1202] Output: The integrated data is fed into a generative AI model.

[1203] 2. Coordination Proposal Generation

[1204] The generative AI model takes into account past outfit history, the latest fashion trends, and the user's skin tone and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent from the server to the device.

[1205] Input: Integrated data.

[1206] Output: A coordination proposal is generated and sent to the terminal.

[1207] 3. Display of outfits

[1208] The device displays the coordination proposal to the user, who can then review the proposal and choose whether to accept it.

[1209] Input: Coordination suggestions.

[1210] Output: Coordination suggestions are displayed to the user.

[1211] Step 4: Use the consultation feature

[1212] 1. Submit a consultation request

[1213] If a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional from the app, and the device will send the request and user information to the server.

[1214] Input: Consultation request.

[1215] Output: The request is sent to the server.

[1216] 2. Notification to the Expert

[1217] When the server receives the request, it notifies the professional and provides the user information and the request details.

[1218] Input: Consultation request.

[1219] Output: A notification is sent to the expert.

[1220] 3. Creating and sending advice

[1221] The expert creates detailed advice based on the user information and the request content and sends it to the server, which then sends the advice to the device.

[1222] Enter: expert advice.

[1223] Output: Advice is sent to the device via the server.

[1224] 4. Displaying Advice

[1225] The device will display advice to the user, who can then follow the advice to complete their outfit.

[1226] Enter: expert advice.

[1227] Output: The advice is displayed to the user.

[1228] (Application example 1)

[1229] 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."

[1230] Today, when users consider the optimal fashion coordination based on their profile information and the clothes they own, it takes time and effort, and there is no guarantee that the results will be satisfactory. Furthermore, there are limited ways to check outfit combinations without actually trying on clothes, or to visually check the suggested outfits, making it difficult to decide whether to buy or rent. Therefore, there is a need for an efficient, visually confirmable fashion coordination suggestion system.

[1231] 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.

[1232] In this invention, the server includes means for acquiring profile information from a user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather forecast information, means for executing an algorithm for generating coordinated outfits to be suggested, means for displaying the generated coordinated outfit suggestions to the user, means for sending a consultation request to a professional coordinator and acquiring a response, means for displaying the acquired response to the user, augmented reality means for generating an avatar for the user and applying the coordinated outfit to the avatar and displaying it in real space, and means for renting the suggested coordinated outfits. This allows the user to efficiently receive suggestions for optimal fashion coordinated outfits, and visual confirmation makes it easier to decide whether to purchase or rent.

[1233] A "user" is a person who uses the system and provides profile information and information about the clothing they own.

[1234] "Profile Information" refers to detailed personal data such as a user's height, weight, style preferences, skin tone, hairstyle, etc.

[1235] "Images of clothes and information about clothes" refers to photos of each piece of clothing owned by the user and detailed data such as its type, color, shape, etc.

[1236] "Plan and destination information" refers to detailed schedule information such as places the user plans to go to, events, and people they plan to meet in the future.

[1237] "Weather forecast information" is weather forecast data for the location and date and time the user plans to go to.

[1238] "Coordination suggestions" refer to the optimal combination of clothing, hairstyle, makeup, etc. that a user should wear that day based on the user's profile information and weather information obtained.

[1239] An "algorithm" is a computational procedure for generating optimal outfit suggestions based on collected information.

[1240] "Augmented reality means" refers to technology for generating a user's avatar and visually displaying suggested outfits in real space.

[1241] "Means for renting" refers to a function that allows you to temporarily borrow suggested outfits or items.

[1242] The "server" is a device that receives and stores various information sent by users and generates coordination suggestions.

[1243] This system collects detailed user profile information, real-world weather and schedule information, and proposes optimal fashion coordination. This system integrates multiple technologies to enhance user convenience.

[1244] System configuration and operation

[1245] 1. User information registration

[1246] First, the user installs a dedicated application on the device and performs initial setup. The user then enters detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This information is sent from the device to a server and stored. The user also takes pictures of clothes they own and uploads them to the app. The device analyzes these images and extracts information such as the type, color, and shape of the clothes, which is then sent to the server.

[1247] 2. Get schedule and weather information

[1248] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then uses the weather forecast API to obtain and record weather information for the destination based on the location information.

[1249] 3. Coordinate Generation

[1250] The server integrates and analyzes the user's profile information, list of clothing items, schedule and destination information, and weather forecast information. This information is input into an algorithm that generates outfits. The algorithm also takes into account the user's skin tone and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device, which displays them to the user.

[1251] 4. Avatar generation and augmented reality display

[1252] The system generates an avatar for the user and applies the suggested outfits to it. Furthermore, by utilizing augmented reality, users can project the avatar into the real world using smart glasses or a head-mounted display, allowing them to visually check the outfits.

[1253] 5. Rental and consultation features

[1254] There is also a function to temporarily rent suggested outfits and items. If users are unsure about what to wear, they can send a consultation request to a professional coordinator, and the answer will be retrieved and displayed.

[1255] Hardware and software used

[1256] Hardware: Smartphones, smart glasses, head-mounted displays

[1257] Software: Python, OpenCV, ARCore, ARKit, WeatherAPI

[1258] The system processes a variety of data and generates optimal outfits based on that data. Users can visually check the outfits and efficiently choose the outfit that best suits them.

[1259] Specific examples

[1260] For example, say a user has an appointment in Tokyo one day, has light skin tones, and prefers casual clothing. They enter this information into the app. The server then retrieves this information along with the weather forecast for that day. Based on the forecast of a sunny 20-degree weather, the server suggests a white T-shirt, denim shorts, and sneakers. This suggestion is visually displayed as the user's avatar through the smart glasses. If the user is unsure about which accessories to choose, they can consult with a professional coordinator and receive additional suggestions.

[1261] Prompt Sentence Examples

[1262] Based on the user's profile information (height: 165cm, weight: 55kg, preference: casual, skin tone: light, hairstyle: long) and the destination location (Tokyo), generate the best outfit suggestions for a day when the temperature is 20 degrees. The suggestions should include tops, bottoms, and shoes.

[1263] As described above, this system efficiently provides optimal coordination based on detailed user information.

[1264] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1265] Step 1:

[1266] The user installs the application on the device and performs initial setup. The user enters their profile information (height, weight, style preferences, skin color, hairstyle, etc.). The entered profile information is sent from the device to the server and saved on the server. The server processes the entered information by organizing it for each user and registering it in a database.

[1267] Step 2:

[1268] Users take pictures of their clothes and upload them to the app. The device analyzes the uploaded images and extracts detailed data such as the type, color, and shape of the clothes. The extracted data is sent to a server and saved as a list of the user's belongings. A deep learning model is used for the analysis, and the image data is converted into text information.

[1269] Step 3:

[1270] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends this information to the server. The server uses the location information of the destination to obtain and record weather information for that location using a weather forecast API. Specific inputs include date, time, and location information, and the output is weather forecast information data.

[1271] Step 4:

[1272] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, and weather forecast information. It then runs an algorithm to generate outfits based on this data. The algorithm comprehensively evaluates multiple factors and generates the optimal combination of fashion, hairstyle, and makeup to suggest. The output is a specific outfit suggestion.

[1273] Step 5:

[1274] The generated coordination proposal is sent from the server to the terminal, which displays it to the user. The user checks the proposed coordination and, if necessary, sends a consultation request to a professional coordinator. This request is sent from the terminal to the server, which provides the request to the professional coordinator.

[1275] Step 6:

[1276] The professional coordinator creates advice based on the request and sends it to the server, which retrieves the advice and sends it back to the user. Specifically, the professional coordinator evaluates the proposed coordination and provides additional advice.

[1277] Step 7:

[1278] The server generates an avatar for the user and applies the proposed outfits to the avatar. Using augmented reality, the user visually sees the avatar in real space through smart glasses or a head-mounted display. The server sends the generated avatar information to the device, which displays it in the augmented reality environment.

[1279] Step 8:

[1280] When a user wants to temporarily rent a suggested outfit or item, the device sends a rental request to the server. The server processes the request, checks for available items, and provides them to the user. Specifically, it checks the inventory of the suggested item and arranges for delivery.

[1281] 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.

[1282] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments of the present invention are described below.

[1283] System configuration and operation

[1284] 1. User information registration

[1285] Users first install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, skin color, and hairstyle. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothes and upload them to the app. The device analyzes these images to extract data such as the type, color, and shape of the clothes, and sends this information to the server as well.

[1286] 2. Get schedule and weather information

[1287] When a user inputs their plans for the day (destinations, people to meet, events, etc.), the device sends that information to the server. The server then retrieves weather information for that location from a weather forecast API based on the destination's location information and records it.

[1288] 3. Acquiring emotional information

[1289] While a user is using the app, the emotion engine collects data (such as facial expressions, voice tone, and input text) to recognize the user's emotions. This data is sent from the device to a server and stored as the user's emotion information.

[1290] 4. Coordinate Generation

[1291] The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, weather forecast information, and emotional information. This information is input into an algorithm that generates outfits. The algorithm takes into account past outfit history, current fashion trends, the user's skin tone, and face shape to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device, which displays them to the user.

[1292] 5. Consultation function

[1293] When a user is unsure about the suggested outfit or makeup, they can send a consultation request to a professional coordinator. The device sends the consultation request to the server, and the server provides this request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user.

[1294] Specific examples

[1295] A specific example will be given below for explanation.

[1296] Example: User B (30 years old, male) living in Tokyo plans to go shopping in Shinjuku with a friend on the weekend.

[1297] 1. Information input: Person B uses the app to input his / her plans to go shopping in Shinjuku on the weekend. The device sends this information to the server, which then retrieves the weather information for Shinjuku.

[1298] 2. Acquisition of emotional information: While B is using the app, the emotion engine analyzes B's emotions from his facial expressions and tone of voice and detects that he is relaxed. This emotional information is sent to the server.

[1299] 3. Coordination Generation: The server refers to B’s profile and the list of clothes she owns (e.g., khaki jacket, black jeans, sneakers), and, taking into account the weather information that it is sunny with a temperature of 18 degrees and her relaxed emotional state, suggests a combination of khaki jacket, black jeans, and sneakers. It also recommends natural makeup and a casual hairstyle.

[1300] 4. Display and select proposals: The device displays the proposals to Person B, who accepts all of them.

[1301] 5. Consultation function: If Person B feels unsure about their styling, they can send a consultation request to a professional fashion coordinator. The device sends the request, and the server notifies the coordinator of the question and Person B's information. The coordinator then provides appropriate advice, which the server sends to the device, and Person B uses the advice to finalize their styling.

[1302] This allows users to enjoy efficient and personalized outfits every day. By taking into account the user's emotional state, the system provides more appropriate and comfortable outfit suggestions.

[1303] The processing flow will be explained below.

[1304] Step 1:

[1305] A user installs the app and creates an account on their device. The user enters basic information (name, email address, password), which the device sends to the server to create the account.

[1306] Step 2:

[1307] The user enters profile information such as height, weight, style preferences, skin color, hairstyle, etc. The device sends this information to the server and stores it as the user's profile data.

[1308] Step 3:

[1309] Users take photos of their clothes and upload them to the app. The device analyzes the uploaded images and extracts data such as the type, color, and shape of the clothes. The extracted data is sent from the device to a server and added to the user's clothing list.

[1310] Step 4:

[1311] The user inputs their plans for the day (destination, people to meet, events, etc.). The device sends the plan information to the server, and the server retrieves weather information from the weather forecast API based on the location information of the destination.

[1312] Step 5:

[1313] While a user is using the app, the emotion engine collects data (e.g., facial expressions, voice tone, and input text) to recognize the user's emotions. This emotion data is sent from the device to the server and stored as the user's emotion information.

[1314] Step 6:

[1315] The server analyzes the user's profile information, clothing list, schedule and destination information, weather forecast information, and emotional information, and inputs this information into an algorithm to generate the optimal combination of fashion, hairstyle, and makeup.

[1316] Step 7:

[1317] The server sends the generated coordination suggestions to the terminal, which displays them to the user. The user checks the suggestions and selects an appropriate coordination. The terminal then sends the selection result to the server, where it is recorded.

[1318] Step 8:

[1319] If the user wants more detailed advice, he / she sends a consultation request to the professional coordinator. The terminal sends the request to the server, and the server notifies the professional coordinator of the consultation content and the user information.

[1320] Step 9:

[1321] A professional coordinator creates advice for the user and sends it to the server. The server then sends the advice to the device, which displays it to the user. The user then uses the advice to optimize their coordination.

[1322] Step 10:

[1323] The user provides emotional feedback on the proposed outfits, and the device sends the emotional feedback to the server, which uses it to optimize future outfit suggestions.

[1324] Example 2

[1325] 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."

[1326] Conventional outfit suggestion systems take into account a user's personal information and the clothing they own, but it is difficult to provide personalized suggestions that comprehensively consider the user's emotional state, detailed schedule, and weather information. As a result, the suggested outfits often do not match the user's situation or emotions, resulting in a lack of satisfaction. Furthermore, there is a lack of a way to obtain advice from experts in real time.

[1327] 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.

[1328] In this invention, the server includes means for acquiring personal information from the user, means for acquiring clothing images and information about the clothing from the user, means for acquiring schedule and destination information from the user, means for acquiring weather information, means for analyzing the emotional state, means for executing an algorithm for generating outfit suggestions, means for displaying the generated outfit suggestions to the user, means for sending a consultation request to an expert and obtaining a response, and means for displaying the obtained response to the user. This enables personalized outfit suggestions that comprehensively consider the user's personal information, clothing, schedule, weather information, and emotional state. Furthermore, by obtaining advice from an expert, the user can achieve a more satisfying outfit.

[1329] A "user" is a person who uses this system to receive coordination suggestions and advice.

[1330] "Personal information" refers to detailed profile information necessary for coordinating outfits, such as the user's height, weight, style preferences, skin color, hairstyle, etc.

[1331] "Images of clothing and information about clothing" refers to photographs of clothing owned by the user, as well as information such as the type, color, and shape of the clothing.

[1332] "Plan and destination information" is information input by the user about the plan and destination for the day, people to meet, events, and the like.

[1333] "Weather information" refers to information about the weather at a location, obtained using a weather forecast API based on the location information of the destination.

[1334] The "means for analyzing emotional state" refers to software or a system that analyzes the user's facial expression, tone of voice, and input text to analyze the user's emotional state.

[1335] The "algorithm for generating outfit suggestions" is a program that combines a user's personal information, a list of clothing items they own, information about their schedule and destination, weather information, and emotional state information to generate optimal fashion, hairstyle, and makeup.

[1336] The "means for displaying the generated coordination proposal to the user" refers to a terminal screen or application for presenting the coordination proposal sent from the server to the user.

[1337] An "expert" is a professional, such as a fashion coordinator, who provides users with advice on coordinating outfits.

[1338] The "means for sending a consultation request and receiving a response" refers to a communication means or system that allows a user to send a consultation request to a specialist and receive a response.

[1339] "Integrated consideration" means comprehensively analyzing the user's personal information, clothing, schedule, weather information, and emotional state, and then providing coordination suggestions and advice based on that analysis.

[1340] The present invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments of the present invention are described in detail below.

[1341] 1. User information registration

[1342] How it works: A user installs the application on their device and creates an account. On their device, they enter detailed profile information, such as their height, weight, style preferences, skin tone, and hairstyle. This profile information is sent from the device to a server and stored as the user's basic data.

[1343] Hardware / software used: Devices (smartphones, tablets), servers, Cloud Vision API.

[1344] A specific example: A user takes a photo of their clothes and uploads it to the app. The device analyzes the image using Cloud Vision API and extracts data such as the type, color, and shape of the clothes. This information is then sent to the server.

[1345] 2. Get schedule and weather information

[1346] How it works: A user enters their plans for the day (destinations, people to meet, events, etc.) into the app. The device then sends this information to the server.

[1347] Hardware / software used: Device, server, weather forecast API (e.g. OpenWeatherMap API).

[1348] Specific example: When a user enters plans to go to a specific place on a specific date, the server retrieves and records the weather information for that place via a weather forecast API.

[1349] 3. Acquiring emotional information

[1350] How it works: Collects data to recognize emotions while users are using the app.

[1351] Hardware / software used: Device camera, microphone, emotion recognition software (e.g. Affectiva SDK).

[1352] A concrete example: A user's facial expressions and tone of voice are captured and analyzed using emotion recognition software. The analyzed data is sent from the device to a server and stored as user emotional information.

[1353] 4. Coordinate Generation

[1354] How it works: The server generates optimal coordination suggestions based on the information it collects.

[1355] Hardware / software used: Server, generative AI model.

[1356] Specific example: The server integrates and analyzes the user's profile information, clothing list, schedule and destination information, weather information, and emotional information. Using a generative AI model, this information is analyzed based on the prompt text to generate outfit suggestions.

[1357] Example prompt: "Please suggest a casual outfit for going to Shinjuku in a relaxed state on a sunny, 18-degree day."

[1358] 5. Proposal display and consultation function

[1359] Behavior: The generated coordination suggestions are displayed to the user, and an expert is consulted if necessary.

[1360] Hardware / software used: terminals, servers.

[1361] Specific example: If a user has questions or concerns about the proposed outfit, the device sends a consultation request to the server. The server provides the request along with the user's information to an expert, and the expert's advice is sent to the device and displayed.

[1362] The system allows users to receive personalized outfit suggestions based on their individual information and emotional state, and also offers expert advice, improving user satisfaction and the quality of their experience.

[1363] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1364] Step 1:

[1365] Registering user information

[1366] Input: User's personal information (height, weight, style preferences, skin tone, hairstyle)

[1367] Specific operation: The user installs and launches the application, creates an account, and the device displays a user information input screen, where the user enters their personal information.

[1368] Data processing / calculation: The device sends the entered personal information to the server.

[1369] Output: The server stores the received personal information in a database.

[1370] Step 2:

[1371] Clothing information registration

[1372] Input: Images of clothing owned by the user

[1373] How it works: The user takes a photo of the garment and uploads it to the app. The device then analyzes the image using image analysis software (e.g., Cloud Vision API).

[1374] Data processing / calculation: The device extracts data such as the type, color, and shape of the clothing from the image and sends it to the server.

[1375] Output: The server stores the received clothing information in a database.

[1376] Step 3:

[1377] Get schedule and weather information

[1378] Input: User's schedule and destination for the day

[1379] Specific operation: The user enters the schedule for the day into the app. The device sends the schedule information to the server.

[1380] Data processing / calculation: The server obtains weather information from a weather forecast API (e.g., OpenWeatherMap API) based on the destination's location information and associates it with the schedule information.

[1381] Output: The weather information obtained by the server is saved in a database.

[1382] Step 4:

[1383] Acquiring emotional information

[1384] Input: User facial expressions, voice tone, input text

[1385] How it works: While the user is using the app, the device's camera and microphone capture the user's facial expressions and voice in real time, while simultaneously monitoring text input.

[1386] Data processing / calculation: The device analyzes the captured data using emotion analysis software (e.g., Affectiva SDK) to generate emotional state information, which is then sent to the server.

[1387] Output: The server stores the received emotional state information in a database.

[1388] Step 5:

[1389] Coordinate generation

[1390] Input: User profile information, clothing list, schedule and destination information, weather information, emotional state information

[1391] Specific operation: The server aggregates all the user's information and generates coordination suggestions using a generative AI model. It inputs the user's information into the AI ​​model using a prompt sentence.

[1392] Data processing / calculation: Based on the prompt, the generative AI model analyzes all information and generates the optimal fashion, hairstyle, and makeup.

[1393] Example prompt: "Please suggest a casual outfit for going to Shinjuku in a relaxed state on a sunny, 18-degree day."

[1394] Output: The server sends the generated coordination proposal to the device.

[1395] Step 6:

[1396] Proposal display and consultation function

[1397] Input: Generated coordination proposal, user consultation request

[1398] Specific operation: The terminal displays the coordination proposals received from the server to the user. If necessary, the user can send a consultation request to an expert from the terminal.

[1399] Data processing / calculation: The server provides the request and user information to the expert and obtains advice from the expert.

[1400] Output: The server sends the advice to the terminal, which displays it to the user.

[1401] Through the above processing steps, users can receive personalized outfit suggestions based on their individual information and emotional state, and can also receive advice from experts.

[1402] (Application example 2)

[1403] 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."

[1404] Conventional fashion coordination systems suggest outfits based on a user's basic profile and clothing information, but it is difficult to provide personalized suggestions that take into account the user's emotional state, specific schedule, or real-time try-on simulations. Furthermore, there are limited opportunities for users to receive direct advice from professional coordinators. This leaves users with a lack of means to select the outfits that best suit them.

[1405] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1406] In this invention, the server includes means for acquiring and analyzing the user's emotional data, means for running a virtual try-on simulation of the generated outfits, and means for sending a consultation request to a professional outfit coordinator and receiving a response. This allows personalized suggestions for fashion, hairstyles, and makeup to be made through a real-time try-on simulation that takes the user's emotional state into consideration. The professional outfit coordinator can also provide specific advice, enabling more appropriate outfit selection.

[1407] "User" refers to an individual who uses the System.

[1408] "Profile information" refers to personal information such as a user's height, weight, preferred style, and skin tone.

[1409] "Images of clothing and information about clothing" refers to photos of clothing that the user has and data related to the clothing.

[1410] "Schedule and destination information" refers to information such as where the user plans to go that day and events they will attend.

[1411] "Weather forecast information" refers to forecast data regarding the weather in a specified area.

[1412] "Emotional data" refers to data related to emotions obtained from a user's facial expressions, tone of voice, etc.

[1413] "Algorithm" refers to the calculation procedure for integrating various acquired data and generating the optimal fashion coordination.

[1414] "Virtual space" refers to a virtual environment in which users interact using avatars.

[1415] "Try-on simulation" refers to the process of virtually fitting clothing onto an avatar in a virtual space.

[1416] A "professional coordinator" is someone with specialized knowledge of fashion and styling.

[1417] "Consultation Request" means a request submitted by a User to a Professional Coordinator for advice.

[1418] This invention relates to a system that proposes a comprehensive coordination of optimal fashion, hairstyle, makeup, etc. based on individual user information, and further provides more personalized proposals by recognizing and considering the user's emotions. Specific embodiments for carrying out this invention are described below.

[1419] System configuration

[1420] This system is realized by using a user terminal, a server, an emotion recognition device (smart glasses or head-mounted display), and a weather forecast API.

[1421] Operating procedure

[1422] 1. User information registration

[1423] First, users install the application on their device and perform the initial setup. When creating an account on the device, users enter detailed profile information such as height, weight, style preferences, and skin tone. This profile information is sent from the device to the server and saved as the user's basic data. Users also take photos of their own clothing and upload them via the app. This image data is analyzed, and data such as the type, color, and shape of the clothing is extracted and sent to the server.

[1424] 2. Acquiring emotional information

[1425] By using the app on a daily basis and wearing an emotion recognition device (smart glasses or a head-mounted display), emotions are recognized from the user's facial expressions and tone of voice. Emotion data is analyzed in real time and sent from the device to a server.

[1426] 3. Obtaining weather information

[1427] When a user inputs their schedule and destination information for the day, the device sends that information to the server, which then uses a weather forecast API to retrieve and record the weather information for the destination.

[1428] 4. Coordinate Generation

[1429] The server integrates and analyzes the user's profile information, registered clothing information, schedule and destination information, weather forecast information, and emotional data. This information is input into an algorithm using a generative AI model to generate optimal combinations of fashion, hairstyle, and makeup. The generated outfit suggestions are sent to the device and displayed to the user.

[1430] 5. Virtual try-on simulation

[1431] Users can simulate trying on outfits created using an avatar in a virtual space, and visually check the fitting of the clothes in real time through smart glasses or a head-mounted display.

[1432] 6. Consultation function

[1433] When a user has trouble with outfits or makeup, they can send a consultation request to a professional coordinator. The device sends the request to the server, and the server provides the request and the user's information to the professional coordinator. The coordinator then creates detailed advice for the user and sends it to the server. The server then sends the advice to the device and displays it to the user.

[1434] Specific examples

[1435] A specific scenario is shown below.

[1436] For example, if a user enters "I plan to go shopping with a friend in Tokyo this weekend," the server retrieves Tokyo's weather information (e.g., sunny, 18°C). The emotion recognition device detects that the user is in a relaxed emotional state while using the app, and this information is sent to the server in real time. The server integrates the user's profile information (e.g., height 175cm, weight 70kg, preferred style casual), clothing information, schedule and weather information, and emotional information, and uses a generative AI model to suggest the optimal outfit. In this case, an example outfit might be "blue shirt, black jeans, and sneakers." The user can virtually try on the outfit in real time to check the suggested outfit.

[1437] An example prompt is:

[1438] "Based on the profile of user ID: 12345, please suggest a relaxed yet casual style that would be perfect for shopping in Tokyo. The weather forecast is sunny with a temperature of 18 degrees."

[1439] This allows users to enjoy a more personalized fashion experience.

[1440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1441] Step 1: Register your user information

[1442] A user installs the application on their device and creates an account. They enter detailed profile information such as their height, weight, style preferences, and skin tone. The entered profile information is sent from the device to the server and stored on the server. The user also uploads photos of clothing they own, and the device performs image analysis to extract data on the type, color, and shape of the clothing and sends it to the server. The input for this step is the user's profile information and clothing information, and the output is the data stored on the server.

[1443] Step 2: Obtaining emotional information

[1444] Emotional information is acquired in real time. While a user uses an app with smart glasses or a head-mounted display, these devices capture the user's facial expressions and voice tone. The device uses an emotion recognition algorithm to analyze the user's emotions from the acquired data and send the results to the server. The input of this step is the user's facial expressions and voice tone data, and the output is the emotional information sent to the server.

[1445] Step 3: Get weather information

[1446] When the user inputs their schedule and destination information for the day into the device, the device sends this to the server. The server uses the weather forecast API to obtain and record weather information for the specified destination. The input for this step is the user's schedule and destination information, as well as data obtained from the weather forecast API, and the output is the obtained weather information.

[1447] Step 4: Generate coordinates

[1448] The server integrates and analyzes the user's profile information, registered clothing information, schedule and destination information, weather forecast information, and emotional data. Using an algorithm based on a generative AI model, it generates optimal fashion, hairstyle, and makeup suggestions from this data. The input for this step is the integrated user data, and the output is the generated outfit suggestions.

[1449] Step 5: View the proposal

[1450] The generated coordination proposal is sent from the server to the terminal and displayed to the user. The input of this step is the generated coordination proposal, and the output is the proposal content displayed on the terminal.

[1451] Step 6: Virtual try-on simulation

[1452] The user simulates trying on the proposed outfit using an avatar in a virtual space. Using smart glasses or a head-mounted display, the user visually checks the fit in real time. The input for this step is the proposed outfit, and the output is the result of the virtual simulation.

[1453] Step 7: Consultation function

[1454] When a user is unsure about how to coordinate, they send a consultation request to a professional coordinator from their terminal to the server. The server provides the request and user information to the professional coordinator and obtains advice from the coordinator. The obtained advice is sent to the terminal via the server and displayed to the user. The input of this step is the user's consultation request and advice from the professional coordinator, and the output is the advice displayed to the user.

[1455] 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.

[1456] 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.

[1457] 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.

[1458] 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.

[1459] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1460] 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.

[1461] 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).

[1462] 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.

[1463] 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."

[1464] 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.

[1465] 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).

[1466] 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.

[1467] 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.

[1468] 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.

[1469] 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.

[1470] 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.

[1471] 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.

[1472] 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.

[1473] 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.

[1474] 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.

[1475] 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.

[1476] The following is further disclosed regarding the above embodiment.

[1477] (Claim 1)

[1478] a means for obtaining profile information from users;

[1479] A means for acquiring images of clothes and information about clothes from a user;

[1480] means for obtaining schedule and destination information from a user;

[1481] A means for obtaining weather forecast information;

[1482] means for executing an algorithm for generating suggested coordinates;

[1483] a means for displaying the generated coordination proposal to a user;

[1484] A means to submit consultation requests to professional coordinators and obtain their responses;

[1485] a means of displaying the obtained answers to the user;

[1486] A system including:

[1487] (Claim 2)

[1488] 2. The system of claim 1, wherein the algorithm for generating outfit suggestions integrates and analyzes the user's profile information, a list of clothing items, schedule and destination information, and weather forecast information.

[1489] (Claim 3)

[1490] 10. The system of claim 1, further comprising: means for obtaining weather forecast information from an API.

[1491] "Example 1"

[1492] (Claim 1)

[1493] a means for obtaining profile information from users;

[1494] means for obtaining images of clothing items and information about the clothing items from a user;

[1495] means for obtaining schedule and destination information from a user;

[1496] A means for obtaining weather forecast information;

[1497] means for executing an algorithm for generating suggested coordinates;

[1498] a means for displaying the generated coordination proposal to a user;

[1499] A means to submit consultation requests to professional experts and receive their responses;

[1500] a means of displaying the obtained answers to the user;

[1501] A system including:

[1502] (Claim 2)

[1503] 2. The system of claim 1, wherein the algorithm for generating outfit suggestions integrates and analyzes the user's profile information, a list of clothing items owned, schedule and destination information, and weather forecast information.

[1504] (Claim 3)

[1505] 10. The system of claim 1, further comprising: means for obtaining weather forecast information from an API.

[1506] "Application Example 1"

[1507] (Claim 1)

[1508] a means for obtaining profile information from users;

[1509] A means for acquiring images of clothes and information about clothes from a user;

[1510] means for obtaining schedule and destination information from a user;

[1511] A means for obtaining weather forecast information;

[1512] means for executing an algorithm for generating suggested coordinates;

[1513] a means for displaying the generated coordination proposal to a user;

[1514] A means to submit consultation requests to professional coordinators and obtain their responses;

[1515] a means of displaying the obtained answers to the user;

[1516] an augmented reality means for generating an avatar of the user and applying coordinates to the avatar to display it in real space;

[1517] A means for renting the suggested outfit;

[1518] A system including:

[1519] (Claim 2)

[1520] 2. The system of claim 1, wherein the algorithm for generating outfit suggestions integrates and analyzes the user's profile information, a list of clothing items, schedule and destination information, and weather forecast information.

[1521] (Claim 3)

[1522] 10. The system of claim 1, further comprising: means for obtaining weather forecast information from an API.

[1523] "Example 2: Combining Emotion Engines"

[1524] (Claim 1)

[1525] A means for obtaining personal information from a user;

[1526] A means for acquiring images of clothing and information about the clothing from a user;

[1527] means for acquiring schedule and destination information from a user;

[1528] a means for obtaining weather information;

[1529] a means for analyzing an emotional state;

[1530] means for executing an algorithm for generating coordination suggestions;

[1531] means for displaying the generated coordination proposal to a user;

[1532] a means for submitting consultation requests to experts and obtaining their responses;

[1533] means for displaying the obtained answers to the user;

[1534] A system including:

[1535] (Claim 2)

[1536] 2. The system of claim 1, wherein the algorithm for generating outfit suggestions integrates and analyzes the user's personal information, clothing inventory, schedule and destination information, weather information, and emotional state information.

[1537] (Claim 3)

[1538] 10. The system of claim 1, further comprising: means for obtaining weather information from an API.

[1539] "Application example 2 when combining emotion engines"

[1540] (Claim 1)

[1541] a means for obtaining profile information from users;

[1542] A means for acquiring images of clothing and information about the clothing from a user;

[1543] means for obtaining schedule and destination information from a user;

[1544] A means for obtaining weather forecast information;

[1545] A means of acquiring and analyzing user emotion data;

[1546] means for executing an algorithm for generating suggested coordinates;

[1547] a means for displaying the generated coordination proposal to a user;

[1548] A means for simulating the generated outfits in a virtual space,

[1549] A means to submit consultation requests to professional coordinators and obtain their responses;

[1550] a means of displaying the obtained answers to the user;

[1551] A system including:

[1552] (Claim 2)

[1553] The system of claim 1, wherein the algorithm for generating outfit suggestions integrates and analyzes the user's profile information, clothing list, schedule and destination information, weather forecast information, and emotional data.

[1554] (Claim 3)

[1555] 10. The system of claim 1, further comprising: means for obtaining weather forecast information from an API. [Explanation of symbols]

[1556] 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 obtaining profile information from users; A means for acquiring images of clothes and information about clothes from a user; means for obtaining schedule and destination information from a user; A means for obtaining weather forecast information; means for executing an algorithm for generating suggested coordinates; a means for displaying the generated coordination proposal to a user; A means to submit consultation requests to professional coordinators and obtain their responses; a means of displaying the obtained answers to the user; A system including:

2. 2. The system of claim 1, wherein the algorithm for generating outfit suggestions integrates and analyzes the user's profile information, a list of clothes owned, schedule and destination information, and weather forecast information.

3. The system of claim 1 , further comprising: means for obtaining weather forecast information from an API.

Images