System

Abstract

A system is provided.SOLUTION: A system comprising: means for entering a user's profile information; means for having a fashion assistant AI with expert knowledge generate a fashion style recommendation based on the user's profile information; means for using a personality AI to optimize the fashion style recommendation based on the user's past selection history and feedback; means for providing the optimized fashion style recommendation to the user; means for searching for specific clothing from an online store or database based on the fashion style recommendation; and means for displaying the search results to the user and providing a purchase link.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] Conventional fashion selection support systems lack specific suggestions tailored to the user's preferences and personality, making it difficult for users to efficiently find clothes that truly suit them. Furthermore, because individual optimization based on the user's past choices and feedback is not performed, the suggested fashion styles often do not meet the user's expectations. Furthermore, because specific clothing items are not searched or displayed based on the suggested styles, the process leading up to the user's actual purchase is cumbersome. There is a need to address these issues. [Means for solving the problem]

[0005] The present invention provides a system including means for inputting user profile information, means for having a fashion assistant AI with specialized knowledge generate fashion style suggestions based on the user's profile information, means for using personality AI to optimize the fashion style suggestions based on the user's past selection history and feedback, means for providing the optimized fashion style suggestions to the user, means for searching for specific clothes from online stores or databases based on the fashion style suggestions, and means for displaying search results to the user and providing a purchase link.

[0006] This system provides optimal fashion style suggestions based on the user's individual preferences and personality, and allows for smoother searching and purchasing of specific clothing. User feedback is also incorporated, enabling more accurate suggestions. This allows users to efficiently find the clothes that best suit them.

[0007] "User profile information" refers to personal information that forms the basis for fashion style suggestions, such as the user's body type, preferred colors, style, and budget.

[0008] "Fashion assistant AI with specialized knowledge" is an artificial intelligence that has knowledge of fashion trends and styles and suggests fashion styles based on the user's profile information.

[0009] "Personality AI" is an artificial intelligence that optimizes suggested fashion styles based on the user's past selection history and feedback information.

[0010] "Fashion Style Suggestions" refers to fashion options and coordinations that suit a user, generated based on the user's profile information and expertise.

[0011] "Optimization" refers to the process of adjusting and modifying the proposed fashion style to meet the user's preferences and requirements.

[0012] An "online store" refers to a website or platform that sells clothing and other products over the internet.

[0013] A "database" refers to a collection of information that stores user information and fashion item information and is used for searches and suggestions.

[0014] "Purchase Link" refers to an Internet link to a web page that a user visits to actually purchase the suggested clothing item.

[0015] "Feedback" refers to the opinions and ratings provided by users regarding the proposed fashion style. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention relates to a system that helps users find clothes that suit them. Based on user profile information, a fashion assistant AI and a personality AI work together to suggest the optimal fashion style, and then search online stores for specific clothes that match that style and provide them.

[0038] Program processing explanation

[0039] 1. Initial Setup and User Registration

[0040] The terminal displays a profile input form to the user, who then inputs profile information such as his or her body type, favorite colors, style, budget, etc. The terminal then transmits this information to the server.

[0041] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[0042] 2. Dialogue between Expertise AI and Personality AI begins

[0043] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[0044] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[0045] 3. Feedback from personality AI

[0046] The server sends the fashion style suggestions received from the expert knowledge AI to the personality AI, which evaluates the suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[0047] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0048] 4. User feedback and refinement

[0049] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[0050] The server receives the user's feedback and again requests optimization from the fashion assistant AI and personality AI.

[0051] 5. Search and display specific clothing items

[0052] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[0053] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[0054] Specific examples

[0055] Example 1: User A's scenario, who prefers casual style

[0056] 1. Initial Setup and User Registration

[0057] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[0058] The server generates a personality profile based on user A's information and stores it in a database.

[0059] 2. Dialogue between Expertise AI and Personality AI begins

[0060] The server sends User A's profile to the expert knowledge AI and requests casual style fashion suggestions.

[0061] The AI ​​expertise generates casual suggestions for shirts and jeans in blue and green tones.

[0062] 3. Feedback from personality AI

[0063] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[0064] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[0065] The server sends the proposal to the terminal and displays it to User A.

[0066] 4. User feedback and refinement

[0067] User A provides feedback that he would like more variation in the proposals.

[0068] The terminal sends this feedback to the server, which then requests optimization again.

[0069] 5. Search and display specific clothing items

[0070] The server searches for specific clothes from online stores based on the optimized suggestions.

[0071] The device displays multiple search results to User A and provides a purchase link for each item. When User A clicks a link, the device opens a purchase page.

[0072] In this way, users can efficiently find the clothes that best suit them and smoothly proceed to purchasing. The system combines the user's preferences with the latest fashion information to help them select the best clothes.

[0073] The processing flow will be explained below.

[0074] Step 1:

[0075] The terminal displays a profile entry form to the user, in which the user enters profile information such as their body type, favorite colors, style, and budget.

[0076] Step 2:

[0077] The terminal transmits the entered profile information to the server.

[0078] Step 3:

[0079] The server generates a personality profile for the user based on the received profile information, which is then stored in a database.

[0080] Step 4:

[0081] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[0082] Step 5:

[0083] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[0084] Step 6:

[0085] The server sends the fashion style suggestions received from the specialized knowledge AI to the personality AI.

[0086] Step 7:

[0087] The Personality AI evaluates these suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[0088] Step 8:

[0089] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0090] Step 9:

[0091] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[0092] Step 10:

[0093] The server receives the user's feedback and again requests optimization from the fashion assistant AI and personality AI.

[0094] Step 11:

[0095] A new optimized fashion style suggestion is generated, which the server sends back to the terminal and displays to the user.

[0096] Step 12:

[0097] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[0098] Step 13:

[0099] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[0100] Example 1

[0101] 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."

[0102] Conventional fashion suggestion systems often fail to fully consider the individual needs and styles of users, resulting in uniform suggestions. Furthermore, they fail to properly utilize the user's past behavioral data and feedback, resulting in low suggestion accuracy. Furthermore, there is also the problem of it taking a long time to search for specific clothing and provide it to the user. This prevents users from efficiently finding the perfect outfit for them, resulting in low satisfaction.

[0103] 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.

[0104] In this invention, the server includes means for inputting user profile information, means for causing an artificial intelligence with specialized knowledge to generate fashion style suggestions based on the user profile information, means for using an artificial intelligence with personality analysis to optimize the fashion style suggestions based on the user's past selection history and feedback, means for providing the optimized fashion style suggestions to the user, means for searching for specific clothing from a database based on the fashion style suggestions, and means for displaying the search results to the user and providing a purchase link. This allows the server to provide fashion suggestions quickly and accurately, fully meeting the user's individual needs and preferences, and enabling the user to efficiently find the clothes that best suit them.

[0105] "User" refers to an individual who utilizes the system to provide fashion suggestions or search for specific clothing items.

[0106] "Profile Information" refers to data about a user, such as body type, preferred colors, style, budget, etc., that is used to understand the user's preferences and characteristics.

[0107] "Artificial intelligence with specialized knowledge" refers to artificial intelligence that has extensive knowledge and trend data about fashion and is capable of generating fashion style suggestions based on a user's profile information.

[0108] "Personality analysis artificial intelligence" refers to artificial intelligence that evaluates and optimizes fashion style suggestions based on the user's past selection history and feedback information.

[0109] "Optimization" refers to adjusting fashion style suggestions to match a user's preferences based on the user's feedback and past selection history.

[0110] "Database" refers to a repository of information that the system uses to suggest fashion styles and search for specific clothing.

[0111] "Search results" refers to specific clothing information retrieved from databases and online stores and displayed to the user as a list.

[0112] "Buy Link" means a hyperlink that a User can click to directly access the purchase page of the applicable online store to purchase a particular garment.

[0113] MODE FOR CARRYING OUT THE INVENTION

[0114] This invention relates to a system that helps users find clothes that suit them. Based on user profile information, an artificial intelligence with specialized knowledge (hereinafter referred to as "fashion assistant AI") and a personality analysis artificial intelligence (hereinafter referred to as "personality AI") work together to suggest the optimal fashion style, and then searches a database or other source for specific clothes that match that style and provides them.

[0115] 1. Initial Setup and User Registration

[0116] The device displays a profile entry form to the user. This form is often created using HTML and JavaScript (registered trademark). The user enters profile information such as their body type (e.g., slim, chubby), favorite colors (e.g., blue, green), style (e.g., casual, formal), and budget (e.g., under 5,000 yen). The device then sends this information to the server using JavaScript or JSON.

[0117] The server analyzes the received user profile information and stores each item in its own table in the database. Based on this information, a personality profile of the user is generated and stored in the database.

[0118] 2. Fashion Style Proposal Generation

[0119] The server reads the user's personality profile and sends it to the fashion assistant AI, using a prompt such as "Please generate fashion style suggestions based on the profile of user ID 123."

[0120] The fashion assistant AI generates multiple fashion style suggestions based on fashion trend data, the user's body type, preferred colors, style, budget, etc. For example, it suggests a specific style such as "a blue shirt and green jeans."

[0121] 3. Optimization with personality AI

[0122] The server sends the fashion style suggestions received from the fashion assistant AI to the personality AI, along with a prompt message saying, "Please evaluate and optimize this suggestion based on user ID 123's past selection history and feedback."

[0123] The Personality AI evaluates the suggestions based on the user's past selection history and feedback information, and makes adjustments as necessary. For example, this adjustment may include "Since the user previously mainly selected blue, we will strengthen blue-based suggestions."

[0124] The server receives the optimized proposal and sends it to the terminal for display to the user.

[0125] 4. User feedback and refinement

[0126] The user can check the optimized fashion style suggestions displayed on the device and enter feedback, such as "I want more casual items" or "I'm willing to spend a little more."

[0127] The terminal obtains this feedback and sends it to the server.

[0128] The server analyzes the user's feedback and again requests optimization from the fashion assistant AI and personality AI. For example, it generates a specific prompt such as, "User ID 123 wants more casual items, and the budget can be increased to 7,000 yen."

[0129] 5. Search and display specific clothing items

[0130] The server searches for specific clothing items from online stores or internal databases based on the final proposed fashion style, and retrieves matching items from online stores using a RESTful API.

[0131] The device displays the search results to the user. Each clothing item is provided with a purchase link. For example, an image of a blue shirt is displayed with a "Buy here" link.

[0132] When a user clicks on a purchase link, the device opens the linked purchase page, allowing the user to smoothly proceed with the purchase process.

[0133] Prompt Sentence Examples

[0134] "Based on the profile information entered by User A, who is in his 20s and likes casual style, please generate fashion suggestions based on blue and green. The budget is under 5,000 yen."

[0135] "Please increase the variety of casual styles based on user feedback and re-propose them."

[0136] In this way, the system effectively utilizes multiple AI technologies to provide optimal fashion suggestions tailored to the user's needs, allowing the user to efficiently find clothes that suit them and facilitating the purchasing process.

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

[0138] Step 1: Initial Setup and User Registration

[0139] The device presents the user with a profile entry form, written in HTML and with interactive elements added using JavaScript, in which the user enters information such as body type, preferred colors, style, and budget.

[0140] Input: Profile information entered by the user (e.g., body type is slim, favorite colors are blue and green, style is casual, budget is under 5,000 yen).

[0141] The terminal uses JavaScript to format the input data in JSON format and send it to the server.

[0142] The server parses the received JSON data, extracts each item individually, and stores it in a table in the database.

[0143] Data processing: Parse the JSON data and save it as user profile information.

[0144] Output: User profile information stored in a database.

[0145] Step 2: Generate fashion style suggestions

[0146] The server reads the stored user profile information and sends it to the Fashion Assistant AI for use in the next stage.

[0147] Input: User profile information retrieved from the database.

[0148] The server sends a prompt to the fashion assistant AI saying, "Please generate fashion style suggestions based on the profile of user ID 123."

[0149] The fashion assistant AI analyzes user profile information based on a trend database and generates multiple fashion style suggestions.

[0150] Data calculation: Calculate and generate fashion styles using trend data and user profile information.

[0151] Output: Generated fashion style suggestions (e.g., blue shirt and green jeans).

[0152] Step 3: Optimization with personality AI

[0153] The server sends the style suggestions received from the fashion assistant AI to the personality AI.

[0154] Input: Generated fashion style suggestions.

[0155] The server sends a prompt to the personality AI saying, "Please evaluate and optimize this suggestion based on user ID 123's past selection history and feedback."

[0156] Personality AI analyzes the user's past selection history and feedback to evaluate and optimize fashion style suggestions.

[0157] Data calculation: Evaluate and optimize proposals based on user history and feedback.

[0158] Output: Optimized fashion style suggestions.

[0159] Step 4: User feedback and refinement

[0160] The terminal displays the optimized fashion style suggestions to the user.

[0161] The user enters feedback about the suggestion (e.g., I'd like more casual items).

[0162] Input: User feedback.

[0163] The terminal takes this feedback and sends it back to the server.

[0164] The server analyzes the feedback and, if necessary, re-optimizes using the fashion assistant AI and personality AI.

[0165] Data calculation: Analyze feedback and re-adjust / optimize suggestions.

[0166] Output: Re-optimized fashion style suggestions.

[0167] Step 5: Search and view specific clothing items

[0168] The server searches for specific clothes from online stores and databases based on the fully optimized fashion style, and communicates with the online stores using APIs.

[0169] Input: optimized fashion style suggestions.

[0170] Data calculations: Search online stores and internal databases based on suggestions.

[0171] Output: Specific clothing items as search results.

[0172] The terminal displays the search results to the user and provides a purchase link corresponding to each item.

[0173] When a user clicks on a purchase link, the device opens the linked purchase page, allowing the user to access the purchase page directly.

[0174] (Application example 1)

[0175] 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."

[0176] Today's consumers spend a lot of time and effort finding the perfect fashion style. Finding clothes that suit them efficiently can be challenging, especially when shopping in brick-and-mortar stores. Real-time advice and augmented reality suggestions would enhance the consumer experience, but current systems struggle to achieve this. A new system is needed to address these challenges.

[0177] 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.

[0178] In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize the fashion style suggestions based on the user's past selection history and feedback, means for providing the optimized fashion style suggestions to the user, means for searching for specific clothes from an online store or database based on the fashion style suggestions, means for displaying the search results to the user and providing a purchase link, means for suggesting clothes to be worn by the user in a physical store in real time, and means for displaying the suggested information in augmented reality in real time in the physical store. This allows users to efficiently find the best clothes for them in a physical store, and significantly improves the consumer experience through real-time suggestions and augmented reality displays.

[0179] 1. "Means for inputting user profile information" refers to an interface for inputting and collecting personal information such as the user's body type, preferred colors, style, budget, etc.

[0180] 2. "Fashion assistant AI with specialized knowledge" is an artificial intelligence that uses fashion trend data and knowledge to refer to a user's profile information and suggest the most suitable fashion style.

[0181] 3. "Means using personality AI" refers to means that use artificial intelligence to analyze a user's past selection history and feedback information and optimize fashion style suggestions based on that information.

[0182] 4. "Means for providing the user with the above-mentioned optimized fashion style suggestions" refers to an interface that displays and provides the user with fashion style suggestions optimized by personality AI.

[0183] 5. "Means for searching for specific clothing from online stores or databases" refers to means for searching for specific clothing that corresponds to optimal fashion style suggestions using online stores or internal databases.

[0184] 6. "Means for displaying search results to users and providing purchase links" refers to an interface that displays information about clothing searched from online stores and databases to users and provides purchase links for those items.

[0185] 7. "Means for suggesting clothes to be worn by users in real time in a physical store" is a system that suggests the most suitable clothes to users in real time on the spot while they are shopping in a physical store.

[0186] 8. "Means for displaying suggested information in real time using augmented reality within a physical store" refers to a system that uses augmented reality technology to visually display suggested item information in real time when a user checks out a product in a physical store.

[0187] This invention provides an application system for smartphones or smart glasses that allows users to efficiently find the best clothes for themselves in a physical store. This system supports clothing selection in a physical store by linking a fashion assistant AI and a personality AI based on user profile information.

[0188] System configuration

[0189] Hardware:

[0190] Device: Smartphone or smart glasses

[0191] Server: For information processing and data storage

[0192] Network infrastructure: Internet connectivity to send and receive data

[0193] software:

[0194] Fashion Assistant AI: Artificial intelligence that suggests fashion styles based on user profile information

[0195] Personality AI: Artificial intelligence that optimizes fashion style suggestions based on the user's past selection history and feedback information

[0196] Augmented reality (AR) technology: AR software (e.g., Apple's ARKit) that displays recommendations in real time within a physical store.

[0197] System Operation

[0198] 1. Initial setup and user registration:

[0199] First, the terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, budget, etc. This information is sent to the server.

[0200] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[0201] 2. Fashion proposal generation:

[0202] The server requests the fashion assistant AI to generate fashion style suggestions based on the user's personality profile.

[0203] The fashion assistant AI generates multiple suggestions based on current fashion trends, the user's body type, preferred colors, style, and budget.

[0204] 3. Optimize your offers:

[0205] The server sends the generated fashion style suggestions to the personality AI, which optimizes the suggestions based on the user's past selection history and feedback.

[0206] The Personality AI evaluates the suggestions and makes modifications or optimizations as necessary, and the optimized suggestions are sent to the device and displayed to the user.

[0207] 4. Real-time in-store recommendations:

[0208] When a user is shopping in a physical store and looks at products displayed through the smart glasses, the fashion assistant AI and personality AI provide optimized recommendations in real time via AR display.

[0209] 5. Gather feedback and readjust:

[0210] The user enters feedback about the proposed style, and the terminal sends this to the server.

[0211] Based on the feedback, the server again requests optimization from the fashion assistant AI and personality AI.

[0212] 6. Search and view specific clothing:

[0213] The server searches for specific clothing items from online stores and databases based on the optimized fashion style suggestions.

[0214] The terminal displays the search results to the user and provides a purchase link for each clothing item.

[0215] Specific examples

[0216] Example 1: User A's scenario, who prefers casual style

[0217] 1. Initial setup and user registration:

[0218] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[0219] The server generates a personality profile based on user A's information and stores it in a database.

[0220] 2. Fashion proposal generation:

[0221] The server generates casual style fashion suggestions based on the profile of user A.

[0222] The fashion assistant AI suggests casual shirts and jeans in blue and green tones.

[0223] 3. Optimize your offers:

[0224] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[0225] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[0226] The server sends the proposal to the terminal and displays it to User A.

[0227] 4. Real-time in-store recommendations:

[0228] User A uses smart glasses in a physical store to select clothes and check real-time suggested information about potential purchases displayed in AR.

[0229] Example prompt for a generative AI model:

[0230] "Please suggest the best fashion style for the user based on their body type, preferred colors, style, and budget. This suggestion is for a user who prefers casual styles."

[0231] "Optimize your suggestions by taking into account past selection history and feedback information."

[0232] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0233] Step 1:

[0234] Initial Setup and User Registration

[0235] The terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, budget, etc. This information is sent from the terminal to the server.

[0236] Input: Profile information such as user's body type, favorite colors, style, budget, etc.

[0237] Processing: The device collects user input information and sends it to the server, which receives the information and generates a personality profile.

[0238] Output: Personality profile stored in a database

[0239] Step 2:

[0240] Fashion proposal generation

[0241] The server requests the fashion assistant AI to generate fashion style suggestions based on the user's personality profile.

[0242] Enter: personality profile

[0243] Processing: Fashion assistant AI generates multiple fashion style suggestions taking into account fashion trend data, body type, preferred colors, style, and budget.

[0244] Output: Multiple fashion style suggestions

[0245] Step 3:

[0246] Recommendation optimization

[0247] The server sends the generated fashion style suggestions to the personality AI, which optimizes the suggestions based on the user's past selection history and feedback.

[0248] Input: Fashion style suggestions, past selection history, feedback information

[0249] Processing: Personality AI evaluates the suggestions and makes corrections and optimizations as needed.

[0250] Output: Optimized fashion style suggestions

[0251] Step 4:

[0252] Providing optimized proposals

[0253] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0254] Input: Optimized fashion style suggestions

[0255] Processing: The server sends the proposal to the terminal, which displays it to the user.

[0256] Output: Optimized fashion style suggestions displayed to the user

[0257] Step 5:

[0258] Real-time proposals in physical stores

[0259] When a user looks at a product through the smart glasses in a physical store, the information is sent to the server, and suggested information optimized by the fashion assistant AI and personality AI is displayed in real time using AR.

[0260] Input: Product information in physical stores, user location information

[0261] Processing: The Fashion Assistant AI and Personality AI generate real-time suggestions based on the captured information and display them on the user's smart glasses using AR technology.

[0262] Output: Real-time suggested information displayed on smart glasses

[0263] Step 6:

[0264] Gather feedback and refine

[0265] The user enters feedback about the proposed style, and the terminal sends this to the server.

[0266] Input: User feedback

[0267] Processing: Based on the feedback, the server again requests optimization from the fashion assistant AI and personality AI, generating new suggestions.

[0268] Output: Updated fashion style suggestions

[0269] Step 7:

[0270] Search and display specific clothing items

[0271] The server searches for specific clothing items from online stores and databases based on optimized fashion style suggestions and displays them on the device.

[0272] Input: Optimized fashion style suggestions

[0273] Processing: The server searches online stores and databases, collects the appropriate item information, and sends it to the device.

[0274] Output: Specific clothing item displayed on device with a link to purchase

[0275] 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.

[0276] This invention relates to a system that proposes a fashion style suitable for a user and searches for and provides specific clothes that match that style from online stores, etc. This invention is characterized by the combination of a feeling engine that recognizes the user's feelings and adjusts the proposed fashion style based on the user's feelings.

[0277] Program processing explanation

[0278] 1. Initial Setup and User Registration

[0279] The terminal displays a profile input form to the user, who then inputs profile information such as his or her body type, favorite colors, style, budget, etc. The terminal then transmits this information to the server.

[0280] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[0281] 2. Dialogue between Expertise AI and Personality AI begins

[0282] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[0283] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[0284] 3. Feedback from personality AI

[0285] The server sends the fashion style suggestions received from the expert knowledge AI to the personality AI, which evaluates the suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[0286] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0287] 4. Emotion Recognition by Emotion Engine

[0288] The device uses a camera to analyze the user's facial expressions and recognize their emotions, or uses voice relative analysis to determine the user's emotions.

[0289] The terminal transmits the recognized emotion information to the server.

[0290] 5. Recalibrate your emotional offers

[0291] The server receives emotional information from the emotion engine and instructs the personality AI and fashion assistant AI to readjust.

[0292] The Personality AI and Fashion Assistant AI will reassess fashion style suggestions based on the user's emotions and revise the suggestions as needed.

[0293] The server sends the retuned proposal to the terminal and displays it to the user.

[0294] 6. Search and display specific clothing items

[0295] The server then searches for specific clothing items from online stores and databases based on the final proposed fashion style.

[0296] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[0297] Specific examples

[0298] Example 1: User A's scenario, who prefers casual style

[0299] 1. Initial Setup and User Registration

[0300] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[0301] The server generates a personality profile based on user A's information and stores it in a database.

[0302] 2. Dialogue between Expertise AI and Personality AI begins

[0303] The server sends User A's profile to the expert knowledge AI and requests casual style fashion suggestions.

[0304] The AI ​​expertise generates casual suggestions for shirts and jeans in blue and green tones.

[0305] 3. Feedback from personality AI

[0306] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[0307] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[0308] The server sends the proposal to the terminal and displays it to User A.

[0309] 4. Emotion Recognition by Emotion Engine

[0310] User A uses the facial expression analysis function, and the device analyzes the emotion and sends it to the server.

[0311] The server receives the emotion information and determines that the emotion is relaxed.

[0312] 5. Recalibrate your emotional offers

[0313] The server instructs the personality AI and expertise AI to readjust based on the relaxed emotion.

[0314] Expertise AI and personality AI reevaluate casual styles that emphasize a relaxed feel and generate optimal suggestions.

[0315] The server sends this re-adjusted proposal to the terminal and re-displays it to User A.

[0316] 6. Search and display specific clothing items

[0317] The server searches online stores for specific clothing items based on the re-tailored suggestions.

[0318] The device displays multiple search results to User A and provides a purchase link for each item. When User A clicks a link, the device opens the purchase page.

[0319] In this way, User A can find the perfect outfit to match his / her emotions and easily proceed to the purchasing process. This system provides a more personalized fashion selection experience by making suggestions that take into account the user's preferences and emotions.

[0320] The processing flow will be explained below.

[0321] Step 1:

[0322] The terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, and budget.

[0323] Step 2:

[0324] The terminal transmits the entered profile information to the server.

[0325] Step 3:

[0326] The server generates a personality profile for the user based on the received profile information and stores this information in a database.

[0327] Step 4:

[0328] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[0329] Step 5:

[0330] The specialized knowledge AI takes into account fashion trend data, the user's body type, preferred colors, style, budget, etc. to generate multiple fashion style suggestions.

[0331] Step 6:

[0332] The server sends the fashion style suggestions received from the specialized knowledge AI to the personality AI.

[0333] Step 7:

[0334] Personality AI evaluates suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[0335] Step 8:

[0336] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0337] Step 9:

[0338] The device sends the facial expressions captured by the user with a camera and recorded voice data to an emotion engine, which analyzes the emotions.

[0339] Step 10:

[0340] The emotion engine analyzes the user's facial expressions and voice data to recognize their emotions. The recognized emotion information is sent to the server via the device.

[0341] Step 11:

[0342] Based on the received emotional information, the server instructs the emotion engine, personality AI, and expertise AI to readjust.

[0343] Step 12:

[0344] Personality AI and expertise AI take into account the user's emotional information to generate new fashion style suggestions.

[0345] Step 13:

[0346] The server sends the re-adjusted fashion style suggestions to the terminal and displays them again to the user.

[0347] Step 14:

[0348] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[0349] Step 15:

[0350] The server again receives user feedback and finalizes the final fashion style suggestions.

[0351] Step 16:

[0352] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[0353] Step 17:

[0354] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks on the purchase link, the device opens a purchase page.

[0355] This process allows users to find the perfect fashion style based on their own feelings and preferences, and easily proceed to purchase.

[0356] Example 2

[0357] 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."

[0358] Conventional fashion suggestion systems only make suggestions based on a user's profile information and past selection history, and lack the ability to readjust based on the user's recent emotions and feedback. As a result, they are unable to provide optimal fashion suggestions that reflect the user's mental state or temporary emotional changes, and an improvement in the user experience is needed.

[0359] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize fashion style suggestions based on the user's past selection history and feedback, means for recognizing the user's emotions using an emotion engine and transmitting the emotion information to the server, means for reevaluating and readjusting the suggestions based on the user's emotion information, means for searching for specific clothes from online stores and databases, and means for displaying search results to the user and providing a purchase link. This enables personalized fashion suggestions that reflect the user's emotions and feedback in real time.

[0360] "User" refers to an individual who wants to use this system to have a fashion style suggested that suits them.

[0361] "Profile Information" refers to information entered by a user that indicates personal attributes and preferences, such as body type, preferred colors, style, budget, etc.

[0362] "Fashion Assistant AI" refers to artificial intelligence that has expertise in fashion and generates fashion style suggestions based on a user's profile information.

[0363] "Personality AI" refers to artificial intelligence that optimizes fashion style suggestions based on a user's past selection history and feedback information.

[0364] An "emotion engine" refers to a system that recognizes a user's emotions by analyzing their facial expressions and voice.

[0365] "Fashion style suggestions" refers to fashion style suggestions generated by the fashion assistant AI based on the user's profile information.

[0366] An "online store" refers to a website or platform that sells clothing and other products over the Internet.

[0367] "Database" refers to digital data storage for storing and managing information such as user profile information, past selection history, and feedback.

[0368] "Purchase Link" refers to a hyperlink to a web page that allows a user to purchase specific clothing items based on the fashion style suggestions.

[0369] "Re-adjustment" refers to the process of reviewing and modifying existing fashion style suggestions based on the user's emotional information.

[0370] MODE FOR CARRYING OUT THE INVENTION

[0371] This invention relates to a system that proposes a fashion style suitable for a user and searches for and provides specific clothes that match that style from online stores, etc. In particular, it is characterized by combining an emotion engine that recognizes the user's emotions and adjusting the proposed fashion style based on the user's emotions.

[0372] System Configuration

[0373] 1. Terminal

[0374] GUI (Graphical User Interface) for displaying the profile entry form

[0375] Hardware equipped with a camera and microphone to analyze the user's facial expressions and voice to recognize emotions

[0376] A communication module that works with the server to send and receive data

[0377] 2. Server

[0378] A database for receiving user profile information and generating a personality profile.

[0379] Fashion assistant AI and personality AI with specialized knowledge

[0380] A processing module for processing the emotional information received from the emotion engine and readjusting the suggestions.

[0381] A search system for searching specific clothing items from online stores and databases and providing the results to users.

[0382] Program processing explanation

[0383] The program processing of this system will be explained in natural language below.

[0384] 1. Initial Setup and User Registration

[0385] The terminal displays a profile entry form to the user, in which the user enters information such as body type, favorite colors, style, and budget.

[0386] The terminal transmits the entered profile information to the server.

[0387] The server generates a personality profile for the user based on the received profile information and stores it in a database.

[0388] 2. Dialogue between Expertise AI and Personality AI begins

[0389] The server sends the generated personality profile to the fashion assistant AI and asks it to suggest a fashion style that suits the user.

[0390] The fashion assistant AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[0391] The fashion assistant AI sends the suggestions to the server.

[0392] 3. Feedback from personality AI

[0393] The server sends the suggestions sent by the fashion assistant AI to the personality AI.

[0394] Personality AI analyzes suggestions based on the user's past selection history and feedback, and optimizes them as needed.

[0395] The server sends the optimized proposal to the terminal and displays it to the user.

[0396] 4. Emotion Recognition by Emotion Engine

[0397] The device uses a camera and microphone to analyze the user's facial expressions and voice and recognize their emotions.

[0398] The terminal transmits the recognized emotion information to the server.

[0399] 5. Recalibrate your emotional offers

[0400] The server receives emotional information from the emotion engine and instructs the personality AI and fashion assistant AI to readjust.

[0401] The Personality AI and Fashion Assistant AI will reassess suggestions based on emotional information and make adjustments as needed.

[0402] The server sends the re-adjusted proposal to the terminal and re-displays it to the user.

[0403] 6. Search and display specific clothing items

[0404] The server then searches for specific clothes from online stores and databases based on the final adjusted fashion style.

[0405] The terminal displays the search results to the user and provides a purchase link for each item.

[0406] When the user clicks on the purchase link, the device opens the purchase page of the corresponding online shop.

[0407] Specific examples

[0408] Example 1: User A's scenario, who prefers casual style

[0409] 1. Initial Setup and User Registration

[0410] User A enters his / her body type (slim), preferred colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and clicks the send button.

[0411] The terminal transmits this information to the server.

[0412] The server generates a personality profile based on user A's information and stores it in a database.

[0413] 2. Dialogue between Expertise AI and Personality AI begins

[0414] The server sends the generated personality profile to the fashion assistant AI and requests casual style fashion suggestions.

[0415] The fashion assistant AI generates casual suggestions for shirts and jeans in blue and green tones.

[0416] The fashion assistant AI sends the suggestions to the server.

[0417] 3. Feedback from personality AI

[0418] The server sends these suggestions to a personality AI, which optimizes them based on past selection history.

[0419] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[0420] The server sends the optimized proposal to the terminal and displays it to User A.

[0421] 4. Emotion Recognition by Emotion Engine

[0422] When User A sees the provided suggestion, the device's camera analyzes his / her facial expressions, which indicate emotions.

[0423] The terminal transmits the analysis results to the server, which determines that User A is relaxed.

[0424] 5. Recalibrate your emotional offers

[0425] The server instructs the personality AI and fashion assistant AI to readjust based on the relaxed emotion.

[0426] Personality AI and fashion assistant AI will reevaluate casual styles that emphasize a relaxed feel and generate optimal suggestions.

[0427] The server sends this re-adjusted proposal to the terminal and re-displays it to User A.

[0428] 6. Search and display specific clothing items

[0429] The server searches online stores for specific clothing items based on the re-tailored suggestions.

[0430] The terminal displays multiple search results to User A and provides a purchase link for each clothing item.

[0431] When User A clicks on the purchase link, the device opens the purchase page of the corresponding online shop.

[0432] Prompt Sentence Examples

[0433] "Based on my profile, please suggest a casual fashion style with blue and green as the main colors. My budget is under 5,000 yen. I would also be happy if the suggested style has a relaxed feel."

[0434] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0435] Step 1:

[0436] Initial Setup and User Registration

[0437] Specific actions

[0438] The terminal displays a profile entry form to the user.

[0439] The user enters profile information such as body type, preferred colors, style, budget, etc., and clicks the submit button.

[0440] input

[0441] Profile information such as your body type, preferred colors, style, budget, etc.

[0442] process

[0443] Format and validate profile data.

[0444] The formatted data is sent to the server via the network.

[0445] output

[0446] User profile information sent to the server

[0447] Step 2:

[0448] Generating a personality profile

[0449] Specific actions

[0450] The server receives the user profile information sent from the terminal.

[0451] input

[0452] User Profile Information

[0453] process

[0454] Analyzes the profile and stores it in the database.

[0455] Generate a personality profile for the user.

[0456] output

[0457] Personality profiles stored in a database

[0458] Step 3:

[0459] Dialogue between expert knowledge AI and personality AI begins

[0460] Specific actions

[0461] The server sends the generated personality profile to the fashion assistant AI.

[0462] input

[0463] Personality Profile

[0464] process

[0465] This involves generating fashion style suggestions using fashion assistant AI.

[0466] It takes into account fashion trend data as well as the user's body type, preferred colors, style, and budget.

[0467] output

[0468] Fashion style suggestions generated by fashion assistant AI

[0469] Style suggestions sent to the server

[0470] Step 4:

[0471] Personality AI feedback

[0472] Specific actions

[0473] The server sends the suggestions received from the fashion assistant AI to the personality AI.

[0474] input

[0475] Fashion style suggestions

[0476] process

[0477] Personality AI evaluates and optimizes suggestions based on past selection history and feedback information.

[0478] output

[0479] Optimized fashion style suggestions

[0480] Optimization suggestions sent to the server

[0481] Step 5:

[0482] Emotion recognition by emotion engine

[0483] Specific actions

[0484] The device uses a camera and microphone to analyze the user's emotions.

[0485] input

[0486] User's facial expression and voice data

[0487] process

[0488] Facial expressions and voice are analyzed using an emotion engine to extract emotional information.

[0489] Emotion information is sent to the server.

[0490] output

[0491] Emotional information sent to the server

[0492] Step 6:

[0493] Recalibrating sentiment-based recommendations

[0494] Specific actions

[0495] The server transmits the emotion information received from the emotion engine to the personality AI and fashion assistant AI.

[0496] input

[0497] emotional information

[0498] process

[0499] Based on emotional information, the personality AI and fashion assistant AI will reevaluate and readjust.

[0500] output

[0501] Re-adjusted fashion style suggestions

[0502] The server sends the retuned proposal to the device.

[0503] Step 7:

[0504] Search and display specific clothing items

[0505] Specific actions

[0506] The server then searches online stores and databases for specific clothing items based on the reworked suggestions.

[0507] input

[0508] Re-adjusted fashion style suggestions

[0509] process

[0510] Performing online store and database searches and retrieving results

[0511] output

[0512] Clothing item search results

[0513] Display search results on your device and provide a purchase link

[0514] Step 8:

[0515] Purchase procedure

[0516] Specific actions

[0517] The user clicks on the purchase link displayed on the terminal.

[0518] input

[0519] Click on the purchase link (selection)

[0520] process

[0521] The device will open the purchase page of the relevant online shop.

[0522] output

[0523] The online shop purchase page will be displayed.

[0524] These are the specific processing steps. In this way, the user is presented with the most suitable fashion style based on their own feelings and feedback, and can purchase specific clothes on the spot.

[0525] (Application example 2)

[0526] 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."

[0527] Conventional fashion suggestion systems can suggest styles based on static information such as a user's preferences and body type, but they cannot adjust the suggestions to take into account the user's emotional state. As a result, they are unable to make suggestions that match the user's mood at any given time, resulting in lower suggestion accuracy and lower satisfaction. Furthermore, they lack the ability to provide real-time fashion suggestions and reflect recognition results in the virtual space, resulting in a poor user experience.

[0528] 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.

[0529] In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize the fashion style suggestions based on the user's past selection history and feedback, means for recognizing the user's emotions using an emotion recognition engine and reevaluating and optimizing the fashion style suggestions based on the emotion information, and means for displaying the emotion-updated fashion style suggestions in a virtual space using a head-mounted display, thereby enabling more personalized fashion style suggestions that reflect the user's emotional state in real time.

[0530] "User profile information" is information about personal attributes such as the user's body type, favorite colors, style, and budget.

[0531] "Fashion assistant AI with specialized knowledge" is an artificial intelligence used to generate fashion style suggestions based on a user's profile information.

[0532] "Fashion style suggestions" refer to styles and coordinations suggested based on the user's personal attributes and preferences.

[0533] The "user's past selection history" is a record of the styles selected and items purchased by the user.

[0534] "Personality AI" is an artificial intelligence that optimizes fashion style suggestions based on the user's past selection history and feedback.

[0535] An "emotion recognition engine" is a technology or software that analyzes a user's facial expressions and voice to recognize their emotions.

[0536] "Emotion information" is data relating to the user's emotional state obtained by an emotion recognition engine.

[0537] "Reevaluate and optimize" means reviewing existing fashion style suggestions based on emotional information and readjusting them to the optimal suggestions for the user.

[0538] A "head-mounted display" is a display device that provides visual information when worn by a user.

[0539] "Virtual space" refers to a virtual 3D environment displayed using a head-mounted display.

[0540] The system for implementing this invention combines a multi-step process including inputting user profile information, generating and optimizing fashion style suggestions, emotion recognition, displaying suggestions in a virtual space, searching for clothing items from online stores, and providing links to purchase them. The specific configuration and operation of the system are described below.

[0541] Hardware and Software

[0542] Hardware:

[0543] Head-mounted displays (e.g., Oculus Rift, Valve Index, HTC Vive)

[0544] Camera and microphone (for emotion recognition)

[0545] software:

[0546] Unity3D (Building a virtual space)

[0547] Azure (registered trademark) Cognitive Services (emotion recognition)

[0548] Amazon Web Services (AWS®) (data management and processing)

[0549] OpenAI® API (fashion suggestion generation)

[0550] Zalando API (clothing data acquisition)

[0551] Program processing explanation

[0552] 1. Initial Setup and User Registration

[0553] Users wear a head-mounted display (HMD) and input their profile information (body type, favorite colors, style, budget, etc.) This information is sent to the AWS server via Azure's API, and the user's profile is stored in a database.

[0554] 2. Dialogue between Expertise AI and Personality AI begins

[0555] The AWS server receives the saved user profile information and requests fashion style suggestions from the OpenAI API, which generates multiple fashion style suggestions based on the trend data and user information.

[0556] 3. Feedback from personality AI

[0557] The AWS server receives the generated fashion style suggestions, which are then evaluated and optimized by the personality AI based on past selection history and feedback. The optimized suggestions are then displayed on the HMD.

[0558] 4. Emotion recognition using an emotion recognition engine

[0559] Using the camera and microphone of the HMD worn by the user, the Azure Cognitive Services emotion analysis API analyzes the user's facial expressions and voice to recognize their emotional state. Emotional information is then sent to the AWS server.

[0560] 5. Recalibrate your emotional recommendations

[0561] Based on the received emotion information, the AWS server requests the OpenAI API to generate and re-evaluate fashion suggestions based on the emotion. The re-adjusted suggestions are then displayed on the HMD.

[0562] 6. Search and display specific clothing items

[0563] The AWS server then uses the Zalando API to search for specific clothing items based on the final tailored fashion style suggestions. The search results are displayed on the HMD, and users can purchase the clothing online via a purchase link.

[0564] Examples and prompts

[0565] Specific examples

[0566] Example 1: User A's scenario, who prefers casual style

[0567] 1. User A enters their body type (normal), preferred colors (red, black), style (formal), and budget (under 10,000 yen), and the information is sent to the AWS server.

[0568] 2. Based on this information, the OpenAI API generates fashion style suggestions.

[0569] 3. Personality AI takes into account past selection history and optimizes suggestions.

[0570] 4. Azure Cognitive Services analyzes the user's emotions from their facial expressions and voice and sends the information to the AWS server.

[0571] 5. Based on the emotion information, the OpenAI API readjusts the fashion suggestions and displays them again on the HMD.

[0572] 6. User A searches for a specific clothing item using the Zalando API and purchases the clothing from the purchase link displayed on the HMD.

[0573] Prompt Sentence Examples

[0574] User Profile:

[0575] Body type: Normal body type

[0576] Favorite colors: Red, black

[0577] Style: Formal

[0578] Budget: Under 10,000 yen

[0579] Emotion information:

[0580] Expression: Relaxed

[0581] Voice analysis: peace of mind

[0582] Suggest a suitable formal fashion style for this user.

[0583] This system can provide more accurate fashion style suggestions that reflect the user's emotional state in real time. In addition, the suggestions change reactively in the virtual space, allowing users to choose the optimal fashion that best suits their emotions.

[0584] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0585] Step 1:

[0586] Users wear a head-mounted display (HMD) and enter their profile information (body type, favorite colors, style, budget, etc.) The entered information is sent to the AWS server via Azure's API.

[0587] Input: User profile information

[0588] Output: User profile information stored in the database

[0589] Action: Displays the profile form and submits the entered data.

[0590] Step 2:

[0591] The AWS server receives the stored user profile information and requests fashion style suggestions from the OpenAI API, which generates multiple fashion style suggestions based on the trend data and user information.

[0592] Input: User profile information, trend data

[0593] Output: Generated fashion style suggestions

[0594] What it does: Sends API requests and receives proposal data

[0595] Step 3:

[0596] The AWS server receives the generated fashion style suggestions, which are then evaluated by the personality AI based on past selection history and feedback, and optimized as needed. The optimized suggestions are then displayed on the HMD.

[0597] Input: Fashion style suggestions, past selection history, feedback information

[0598] Output: Optimized fashion style suggestions

[0599] Operation: Evaluate and optimize proposed data, display on HMD

[0600] Step 4:

[0601] Using the HMD's camera and microphone, the Azure Cognitive Services emotion analysis API analyzes the user's facial expressions and voice to recognize their emotional state, and the emotion information is sent to an AWS server.

[0602] Input: User's facial expression data, voice data

[0603] Output: Recognized emotion information

[0604] Operation: Camera and microphone data acquisition, emotion analysis, and emotion data transmission

[0605] Step 5:

[0606] Based on the received emotion information, the AWS server requests fashion suggestions from the OpenAI API again, generates and re-evaluates fashion style suggestions according to the emotion, and displays the re-adjusted suggestions on the HMD.

[0607] Input: Emotional information, initial fashion style suggestions

[0608] Output: Reworked fashion style suggestions

[0609] Action: Evaluate and readjust the emotional information, and display it again on the HMD

[0610] Step 6:

[0611] The AWS server then uses the Zalando API to search for specific clothing items based on the final tailored fashion style suggestions. The search results are displayed on the HMD, and users can purchase the clothing online via a purchase link.

[0612] Input: Reworked fashion style suggestions

[0613] Output: Searched clothing items and purchase links

[0614] Operation: Searching for clothing data, generating and displaying purchase links

[0615] 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.

[0616] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0617] 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.

[0618] [Second embodiment]

[0619] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0620] 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.

[0621] 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).

[0622] 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.

[0623] 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.

[0624] 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).

[0625] 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.

[0626] 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.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] 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."

[0631] This invention relates to a system that helps users find clothes that suit them. Based on user profile information, a fashion assistant AI and a personality AI work together to suggest the optimal fashion style, and then search online stores for specific clothes that match that style and provide them.

[0632] Program processing explanation

[0633] 1. Initial Setup and User Registration

[0634] The terminal displays a profile input form to the user, who then inputs profile information such as his or her body type, favorite colors, style, budget, etc. The terminal then transmits this information to the server.

[0635] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[0636] 2. Dialogue between Expertise AI and Personality AI begins

[0637] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[0638] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[0639] 3. Feedback from personality AI

[0640] The server sends the fashion style suggestions received from the expert knowledge AI to the personality AI, which evaluates the suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[0641] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0642] 4. User feedback and refinement

[0643] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[0644] The server receives the user's feedback and again requests optimization from the fashion assistant AI and personality AI.

[0645] 5. Search and display specific clothing items

[0646] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[0647] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[0648] Specific examples

[0649] Example 1: User A's scenario, who prefers casual style

[0650] 1. Initial Setup and User Registration

[0651] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[0652] The server generates a personality profile based on user A's information and stores it in a database.

[0653] 2. Dialogue between Expertise AI and Personality AI begins

[0654] The server sends User A's profile to the expert knowledge AI and requests casual style fashion suggestions.

[0655] The AI ​​expertise generates casual suggestions for shirts and jeans in blue and green tones.

[0656] 3. Feedback from personality AI

[0657] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[0658] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[0659] The server sends the proposal to the terminal and displays it to User A.

[0660] 4. User feedback and refinement

[0661] User A provides feedback that he would like more variation in the proposals.

[0662] The terminal sends this feedback to the server, which then requests optimization again.

[0663] 5. Search and display specific clothing items

[0664] The server searches for specific clothes from online stores based on the optimized suggestions.

[0665] The device displays multiple search results to User A and provides a purchase link for each item. When User A clicks a link, the device opens a purchase page.

[0666] In this way, users can efficiently find the clothes that best suit them and smoothly proceed to purchasing. The system combines the user's preferences with the latest fashion information to help them select the best clothes.

[0667] The processing flow will be explained below.

[0668] Step 1:

[0669] The terminal displays a profile entry form to the user, in which the user enters profile information such as their body type, favorite colors, style, and budget.

[0670] Step 2:

[0671] The terminal transmits the entered profile information to the server.

[0672] Step 3:

[0673] The server generates a personality profile for the user based on the received profile information, which is then stored in a database.

[0674] Step 4:

[0675] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[0676] Step 5:

[0677] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[0678] Step 6:

[0679] The server sends the fashion style suggestions received from the specialized knowledge AI to the personality AI.

[0680] Step 7:

[0681] The Personality AI evaluates these suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[0682] Step 8:

[0683] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0684] Step 9:

[0685] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[0686] Step 10:

[0687] The server receives the user's feedback and again requests optimization from the fashion assistant AI and personality AI.

[0688] Step 11:

[0689] A new optimized fashion style suggestion is generated, which the server sends back to the terminal and displays to the user.

[0690] Step 12:

[0691] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[0692] Step 13:

[0693] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[0694] Example 1

[0695] 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."

[0696] Conventional fashion suggestion systems often fail to fully consider the individual needs and styles of users, resulting in uniform suggestions. Furthermore, they fail to properly utilize the user's past behavioral data and feedback, resulting in low suggestion accuracy. Furthermore, there is also the problem of it taking a long time to search for specific clothing and provide it to the user. This prevents users from efficiently finding the perfect outfit for them, resulting in low satisfaction.

[0697] 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.

[0698] In this invention, the server includes means for inputting user profile information, means for causing an artificial intelligence with specialized knowledge to generate fashion style suggestions based on the user profile information, means for using an artificial intelligence with personality analysis to optimize the fashion style suggestions based on the user's past selection history and feedback, means for providing the optimized fashion style suggestions to the user, means for searching for specific clothing from a database based on the fashion style suggestions, and means for displaying the search results to the user and providing a purchase link. This allows the server to provide fashion suggestions quickly and accurately, fully meeting the user's individual needs and preferences, and enabling the user to efficiently find the clothes that best suit them.

[0699] "User" refers to an individual who utilizes the system to provide fashion suggestions or search for specific clothing items.

[0700] "Profile Information" refers to data about a user, such as body type, preferred colors, style, budget, etc., that is used to understand the user's preferences and characteristics.

[0701] "Artificial intelligence with specialized knowledge" refers to artificial intelligence that has extensive knowledge and trend data about fashion and is capable of generating fashion style suggestions based on a user's profile information.

[0702] "Personality analysis artificial intelligence" refers to artificial intelligence that evaluates and optimizes fashion style suggestions based on the user's past selection history and feedback information.

[0703] "Optimization" refers to adjusting fashion style suggestions to match a user's preferences based on the user's feedback and past selection history.

[0704] "Database" refers to a repository of information that the system uses to suggest fashion styles and search for specific clothing.

[0705] "Search results" refers to specific clothing information retrieved from databases and online stores and displayed to the user as a list.

[0706] "Buy Link" means a hyperlink that a User can click to directly access the purchase page of the applicable online store to purchase a particular garment.

[0707] MODE FOR CARRYING OUT THE INVENTION

[0708] This invention relates to a system that helps users find clothes that suit them. Based on user profile information, an artificial intelligence with specialized knowledge (hereinafter referred to as "fashion assistant AI") and a personality analysis artificial intelligence (hereinafter referred to as "personality AI") work together to suggest the optimal fashion style, and then searches a database or other source for specific clothes that match that style and provides them.

[0709] 1. Initial Setup and User Registration

[0710] The device displays a profile entry form to the user. This form is often created using HTML and JavaScript. The user enters profile information such as their body type (e.g., slim, curvy), favorite colors (e.g., blue, green), style (e.g., casual, formal), and budget (e.g., under 5,000 yen). The device then sends this information to the server using JavaScript or JSON.

[0711] The server analyzes the received user profile information and stores each item in its own table in the database. Based on this information, a personality profile of the user is generated and stored in the database.

[0712] 2. Fashion Style Proposal Generation

[0713] The server reads the user's personality profile and sends it to the fashion assistant AI, using a prompt such as "Please generate fashion style suggestions based on the profile of user ID 123."

[0714] The fashion assistant AI generates multiple fashion style suggestions based on fashion trend data, the user's body type, preferred colors, style, budget, etc. For example, it suggests a specific style such as "a blue shirt and green jeans."

[0715] 3. Optimization with personality AI

[0716] The server sends the fashion style suggestions received from the fashion assistant AI to the personality AI, along with a prompt message saying, "Please evaluate and optimize this suggestion based on user ID 123's past selection history and feedback."

[0717] The Personality AI evaluates the suggestions based on the user's past selection history and feedback information, and makes adjustments as necessary. For example, this adjustment may include "Since the user previously mainly selected blue, we will strengthen blue-based suggestions."

[0718] The server receives the optimized proposal and sends it to the terminal for display to the user.

[0719] 4. User feedback and refinement

[0720] The user can check the optimized fashion style suggestions displayed on the device and enter feedback, such as "I want more casual items" or "I'm willing to spend a little more."

[0721] The terminal obtains this feedback and sends it to the server.

[0722] The server analyzes the user's feedback and again requests optimization from the fashion assistant AI and personality AI. For example, it generates a specific prompt such as, "User ID 123 wants more casual items, and the budget can be increased to 7,000 yen."

[0723] 5. Search and display specific clothing items

[0724] The server searches for specific clothing items from online stores or internal databases based on the final proposed fashion style, and retrieves matching items from online stores using a RESTful API.

[0725] The device displays the search results to the user. Each clothing item is provided with a purchase link. For example, an image of a blue shirt is displayed with a "Buy here" link.

[0726] When a user clicks on a purchase link, the device opens the linked purchase page, allowing the user to smoothly proceed with the purchase process.

[0727] Prompt Sentence Examples

[0728] "Based on the profile information entered by User A, who is in his 20s and likes casual style, please generate fashion suggestions based on blue and green. The budget is under 5,000 yen."

[0729] "Please increase the variety of casual styles based on user feedback and re-propose them."

[0730] In this way, the system effectively utilizes multiple AI technologies to provide optimal fashion suggestions tailored to the user's needs, allowing the user to efficiently find clothes that suit them and facilitating the purchasing process.

[0731] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0732] Step 1: Initial Setup and User Registration

[0733] The device presents the user with a profile entry form, written in HTML and with interactive elements added using JavaScript, in which the user enters information such as body type, preferred colors, style, and budget.

[0734] Input: Profile information entered by the user (e.g., body type is slim, favorite colors are blue and green, style is casual, budget is under 5,000 yen).

[0735] The terminal uses JavaScript to format the input data in JSON format and send it to the server.

[0736] The server parses the received JSON data, extracts each item individually, and stores it in a table in the database.

[0737] Data processing: Parse the JSON data and save it as user profile information.

[0738] Output: User profile information stored in a database.

[0739] Step 2: Generate fashion style suggestions

[0740] The server reads the stored user profile information and sends it to the Fashion Assistant AI for use in the next stage.

[0741] Input: User profile information retrieved from the database.

[0742] The server sends a prompt to the fashion assistant AI saying, "Please generate fashion style suggestions based on the profile of user ID 123."

[0743] The fashion assistant AI analyzes user profile information based on a trend database and generates multiple fashion style suggestions.

[0744] Data calculation: Calculate and generate fashion styles using trend data and user profile information.

[0745] Output: Generated fashion style suggestions (e.g., blue shirt and green jeans).

[0746] Step 3: Optimization with personality AI

[0747] The server sends the style suggestions received from the fashion assistant AI to the personality AI.

[0748] Input: Generated fashion style suggestions.

[0749] The server sends a prompt to the personality AI saying, "Please evaluate and optimize this suggestion based on user ID 123's past selection history and feedback."

[0750] Personality AI analyzes the user's past selection history and feedback to evaluate and optimize fashion style suggestions.

[0751] Data calculation: Evaluate and optimize proposals based on user history and feedback.

[0752] Output: Optimized fashion style suggestions.

[0753] Step 4: User feedback and refinement

[0754] The terminal displays the optimized fashion style suggestions to the user.

[0755] The user enters feedback about the suggestion (e.g., I'd like more casual items).

[0756] Input: User feedback.

[0757] The terminal takes this feedback and sends it back to the server.

[0758] The server analyzes the feedback and, if necessary, re-optimizes using the fashion assistant AI and personality AI.

[0759] Data calculation: Analyze feedback and re-adjust / optimize suggestions.

[0760] Output: Re-optimized fashion style suggestions.

[0761] Step 5: Search and view specific clothing items

[0762] The server searches for specific clothes from online stores and databases based on the fully optimized fashion style, and communicates with the online stores using APIs.

[0763] Input: optimized fashion style suggestions.

[0764] Data calculations: Search online stores and internal databases based on suggestions.

[0765] Output: Specific clothing items as search results.

[0766] The terminal displays the search results to the user and provides a purchase link corresponding to each item.

[0767] When a user clicks on a purchase link, the device opens the linked purchase page, allowing the user to access the purchase page directly.

[0768] (Application example 1)

[0769] 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."

[0770] Today's consumers spend a lot of time and effort finding the perfect fashion style. Finding clothes that suit them efficiently can be challenging, especially when shopping in brick-and-mortar stores. Real-time advice and augmented reality suggestions would enhance the consumer experience, but current systems struggle to achieve this. A new system is needed to address these challenges.

[0771] 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.

[0772] In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize the fashion style suggestions based on the user's past selection history and feedback, means for providing the optimized fashion style suggestions to the user, means for searching for specific clothes from an online store or database based on the fashion style suggestions, means for displaying the search results to the user and providing a purchase link, means for suggesting clothes to be worn by the user in a physical store in real time, and means for displaying the suggested information in augmented reality in real time in the physical store. This allows users to efficiently find the best clothes for them in a physical store, and significantly improves the consumer experience through real-time suggestions and augmented reality displays.

[0773] 1. "Means for inputting user profile information" refers to an interface for inputting and collecting personal information such as the user's body type, preferred colors, style, budget, etc.

[0774] 2. "Fashion assistant AI with specialized knowledge" is an artificial intelligence that uses fashion trend data and knowledge to refer to a user's profile information and suggest the most suitable fashion style.

[0775] 3. "Means using personality AI" refers to means that use artificial intelligence to analyze a user's past selection history and feedback information and optimize fashion style suggestions based on that information.

[0776] 4. "Means for providing the user with the above-mentioned optimized fashion style suggestions" refers to an interface that displays and provides the user with fashion style suggestions optimized by personality AI.

[0777] 5. "Means for searching for specific clothing from online stores or databases" refers to means for searching for specific clothing that corresponds to optimal fashion style suggestions using online stores or internal databases.

[0778] 6. "Means for displaying search results to users and providing purchase links" refers to an interface that displays information about clothing searched from online stores and databases to users and provides purchase links for those items.

[0779] 7. "Means for suggesting clothes to be worn by users in real time in a physical store" is a system that suggests the most suitable clothes to users in real time on the spot while they are shopping in a physical store.

[0780] 8. "Means for displaying suggested information in real time using augmented reality within a physical store" refers to a system that uses augmented reality technology to visually display suggested item information in real time when a user checks out a product in a physical store.

[0781] This invention provides an application system for smartphones or smart glasses that allows users to efficiently find the best clothes for themselves in a physical store. This system supports clothing selection in a physical store by linking a fashion assistant AI and a personality AI based on user profile information.

[0782] System configuration

[0783] Hardware:

[0784] Device: Smartphone or smart glasses

[0785] Server: For information processing and data storage

[0786] Network infrastructure: Internet connectivity to send and receive data

[0787] software:

[0788] Fashion Assistant AI: Artificial intelligence that suggests fashion styles based on user profile information

[0789] Personality AI: Artificial intelligence that optimizes fashion style suggestions based on the user's past selection history and feedback information

[0790] Augmented reality (AR) technology: AR software (e.g., Apple's ARKit) that displays recommendations in real time within a physical store.

[0791] System Operation

[0792] 1. Initial setup and user registration:

[0793] First, the terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, budget, etc. This information is sent to the server.

[0794] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[0795] 2. Fashion proposal generation:

[0796] The server requests the fashion assistant AI to generate fashion style suggestions based on the user's personality profile.

[0797] The fashion assistant AI generates multiple suggestions based on current fashion trends, the user's body type, preferred colors, style, and budget.

[0798] 3. Optimize your offers:

[0799] The server sends the generated fashion style suggestions to the personality AI, which optimizes the suggestions based on the user's past selection history and feedback.

[0800] The Personality AI evaluates the suggestions and makes modifications or optimizations as necessary, and the optimized suggestions are sent to the device and displayed to the user.

[0801] 4. Real-time in-store recommendations:

[0802] When a user is shopping in a physical store and looks at products displayed through the smart glasses, the fashion assistant AI and personality AI provide optimized recommendations in real time via AR display.

[0803] 5. Gather feedback and readjust:

[0804] The user enters feedback about the proposed style, and the terminal sends this to the server.

[0805] Based on the feedback, the server again requests optimization from the fashion assistant AI and personality AI.

[0806] 6. Search and view specific clothing:

[0807] The server searches for specific clothing items from online stores and databases based on the optimized fashion style suggestions.

[0808] The terminal displays the search results to the user and provides a purchase link for each clothing item.

[0809] Specific examples

[0810] Example 1: User A's scenario, who prefers casual style

[0811] 1. Initial setup and user registration:

[0812] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[0813] The server generates a personality profile based on user A's information and stores it in a database.

[0814] 2. Fashion proposal generation:

[0815] The server generates casual style fashion suggestions based on the profile of user A.

[0816] The fashion assistant AI suggests casual shirts and jeans in blue and green tones.

[0817] 3. Optimize your offers:

[0818] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[0819] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[0820] The server sends the proposal to the terminal and displays it to User A.

[0821] 4. Real-time in-store recommendations:

[0822] User A uses smart glasses in a physical store to select clothes and check real-time suggested information about potential purchases displayed in AR.

[0823] Example prompt for a generative AI model:

[0824] "Please suggest the best fashion style for the user based on their body type, preferred colors, style, and budget. This suggestion is for a user who prefers casual styles."

[0825] "Optimize your suggestions by taking into account past selection history and feedback information."

[0826] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0827] Step 1:

[0828] Initial Setup and User Registration

[0829] The terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, budget, etc. This information is sent from the terminal to the server.

[0830] Input: Profile information such as user's body type, favorite colors, style, budget, etc.

[0831] Processing: The device collects user input information and sends it to the server, which receives the information and generates a personality profile.

[0832] Output: Personality profile stored in a database

[0833] Step 2:

[0834] Fashion proposal generation

[0835] The server requests the fashion assistant AI to generate fashion style suggestions based on the user's personality profile.

[0836] Enter: personality profile

[0837] Processing: Fashion assistant AI generates multiple fashion style suggestions taking into account fashion trend data, body type, preferred colors, style, and budget.

[0838] Output: Multiple fashion style suggestions

[0839] Step 3:

[0840] Recommendation optimization

[0841] The server sends the generated fashion style suggestions to the personality AI, which optimizes the suggestions based on the user's past selection history and feedback.

[0842] Input: Fashion style suggestions, past selection history, feedback information

[0843] Processing: Personality AI evaluates the suggestions and makes corrections and optimizations as needed.

[0844] Output: Optimized fashion style suggestions

[0845] Step 4:

[0846] Providing optimized proposals

[0847] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0848] Input: Optimized fashion style suggestions

[0849] Processing: The server sends the proposal to the terminal, which displays it to the user.

[0850] Output: Optimized fashion style suggestions displayed to the user

[0851] Step 5:

[0852] Real-time proposals in physical stores

[0853] When a user looks at a product through the smart glasses in a physical store, the information is sent to the server, and suggested information optimized by the fashion assistant AI and personality AI is displayed in real time using AR.

[0854] Input: Product information in physical stores, user location information

[0855] Processing: The Fashion Assistant AI and Personality AI generate real-time suggestions based on the captured information and display them on the user's smart glasses using AR technology.

[0856] Output: Real-time suggested information displayed on smart glasses

[0857] Step 6:

[0858] Gather feedback and refine

[0859] The user enters feedback about the proposed style, and the terminal sends this to the server.

[0860] Input: User feedback

[0861] Processing: Based on the feedback, the server again requests optimization from the fashion assistant AI and personality AI, generating new suggestions.

[0862] Output: Updated fashion style suggestions

[0863] Step 7:

[0864] Search and display specific clothing items

[0865] The server searches for specific clothing items from online stores and databases based on optimized fashion style suggestions and displays them on the device.

[0866] Input: Optimized fashion style suggestions

[0867] Processing: The server searches online stores and databases, collects the appropriate item information, and sends it to the device.

[0868] Output: Specific clothing item displayed on device with a link to purchase

[0869] 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.

[0870] This invention relates to a system that proposes a fashion style suitable for a user and searches for and provides specific clothes that match that style from online stores, etc. This invention is characterized by the combination of a feeling engine that recognizes the user's feelings and adjusts the proposed fashion style based on the user's feelings.

[0871] Program processing explanation

[0872] 1. Initial Setup and User Registration

[0873] The terminal displays a profile input form to the user, who then inputs profile information such as his or her body type, favorite colors, style, budget, etc. The terminal then transmits this information to the server.

[0874] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[0875] 2. Dialogue between Expertise AI and Personality AI begins

[0876] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[0877] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[0878] 3. Feedback from personality AI

[0879] The server sends the fashion style suggestions received from the expert knowledge AI to the personality AI, which evaluates the suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[0880] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0881] 4. Emotion Recognition by Emotion Engine

[0882] The device uses a camera to analyze the user's facial expressions and recognize their emotions, or uses voice relative analysis to determine the user's emotions.

[0883] The terminal transmits the recognized emotion information to the server.

[0884] 5. Recalibrate your emotional offers

[0885] The server receives emotional information from the emotion engine and instructs the personality AI and fashion assistant AI to readjust.

[0886] The Personality AI and Fashion Assistant AI will reassess fashion style suggestions based on the user's emotions and revise the suggestions as needed.

[0887] The server sends the retuned proposal to the terminal and displays it to the user.

[0888] 6. Search and display specific clothing items

[0889] The server then searches for specific clothing items from online stores and databases based on the final proposed fashion style.

[0890] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[0891] Specific examples

[0892] Example 1: User A's scenario, who prefers casual style

[0893] 1. Initial Setup and User Registration

[0894] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[0895] The server generates a personality profile based on user A's information and stores it in a database.

[0896] 2. Dialogue between Expertise AI and Personality AI begins

[0897] The server sends User A's profile to the expert knowledge AI and requests casual style fashion suggestions.

[0898] The AI ​​expertise generates casual suggestions for shirts and jeans in blue and green tones.

[0899] 3. Feedback from personality AI

[0900] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[0901] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[0902] The server sends the proposal to the terminal and displays it to User A.

[0903] 4. Emotion Recognition by Emotion Engine

[0904] User A uses the facial expression analysis function, and the device analyzes the emotion and sends it to the server.

[0905] The server receives the emotion information and determines that the emotion is relaxed.

[0906] 5. Recalibrate your emotional offers

[0907] The server instructs the personality AI and expertise AI to readjust based on the relaxed emotion.

[0908] Expertise AI and personality AI reevaluate casual styles that emphasize a relaxed feel and generate optimal suggestions.

[0909] The server sends this re-adjusted proposal to the terminal and re-displays it to User A.

[0910] 6. Search and display specific clothing items

[0911] The server searches online stores for specific clothing items based on the re-tailored suggestions.

[0912] The device displays multiple search results to User A and provides a purchase link for each item. When User A clicks a link, the device opens the purchase page.

[0913] In this way, User A can find the perfect outfit to match his / her emotions and easily proceed to the purchasing process. This system provides a more personalized fashion selection experience by making suggestions that take into account the user's preferences and emotions.

[0914] The processing flow will be explained below.

[0915] Step 1:

[0916] The terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, and budget.

[0917] Step 2:

[0918] The terminal transmits the entered profile information to the server.

[0919] Step 3:

[0920] The server generates a personality profile for the user based on the received profile information and stores this information in a database.

[0921] Step 4:

[0922] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[0923] Step 5:

[0924] The specialized knowledge AI takes into account fashion trend data, the user's body type, preferred colors, style, budget, etc. to generate multiple fashion style suggestions.

[0925] Step 6:

[0926] The server sends the fashion style suggestions received from the specialized knowledge AI to the personality AI.

[0927] Step 7:

[0928] Personality AI evaluates suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[0929] Step 8:

[0930] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[0931] Step 9:

[0932] The device sends the facial expressions captured by the user with a camera and recorded voice data to an emotion engine, which analyzes the emotions.

[0933] Step 10:

[0934] The emotion engine analyzes the user's facial expressions and voice data to recognize their emotions. The recognized emotion information is sent to the server via the device.

[0935] Step 11:

[0936] Based on the received emotional information, the server instructs the emotion engine, personality AI, and expertise AI to readjust.

[0937] Step 12:

[0938] Personality AI and expertise AI take into account the user's emotional information to generate new fashion style suggestions.

[0939] Step 13:

[0940] The server sends the re-adjusted fashion style suggestions to the terminal and displays them again to the user.

[0941] Step 14:

[0942] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[0943] Step 15:

[0944] The server again receives user feedback and finalizes the final fashion style suggestions.

[0945] Step 16:

[0946] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[0947] Step 17:

[0948] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks on the purchase link, the device opens a purchase page.

[0949] This process allows users to find the perfect fashion style based on their own feelings and preferences, and easily proceed to purchase.

[0950] Example 2

[0951] 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."

[0952] Conventional fashion suggestion systems only make suggestions based on a user's profile information and past selection history, and lack the ability to readjust based on the user's recent emotions and feedback. As a result, they are unable to provide optimal fashion suggestions that reflect the user's mental state or temporary emotional changes, and an improvement in the user experience is needed.

[0953] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize fashion style suggestions based on the user's past selection history and feedback, means for recognizing the user's emotions using an emotion engine and transmitting the emotion information to the server, means for reevaluating and readjusting the suggestions based on the user's emotion information, means for searching for specific clothes from online stores and databases, and means for displaying search results to the user and providing a purchase link. This enables personalized fashion suggestions that reflect the user's emotions and feedback in real time.

[0954] "User" refers to an individual who wants to use this system to have a fashion style suggested that suits them.

[0955] "Profile Information" refers to information entered by a user that indicates personal attributes and preferences, such as body type, preferred colors, style, budget, etc.

[0956] "Fashion Assistant AI" refers to artificial intelligence that has expertise in fashion and generates fashion style suggestions based on a user's profile information.

[0957] "Personality AI" refers to artificial intelligence that optimizes fashion style suggestions based on a user's past selection history and feedback information.

[0958] An "emotion engine" refers to a system that recognizes a user's emotions by analyzing their facial expressions and voice.

[0959] "Fashion style suggestions" refers to fashion style suggestions generated by the fashion assistant AI based on the user's profile information.

[0960] An "online store" refers to a website or platform that sells clothing and other products over the Internet.

[0961] "Database" refers to digital data storage for storing and managing information such as user profile information, past selection history, and feedback.

[0962] "Purchase Link" refers to a hyperlink to a web page that allows a user to purchase specific clothing items based on the fashion style suggestions.

[0963] "Re-adjustment" refers to the process of reviewing and modifying existing fashion style suggestions based on the user's emotional information.

[0964] MODE FOR CARRYING OUT THE INVENTION

[0965] This invention relates to a system that proposes a fashion style suitable for a user and searches for and provides specific clothes that match that style from online stores, etc. In particular, it is characterized by combining an emotion engine that recognizes the user's emotions and adjusting the proposed fashion style based on the user's emotions.

[0966] System Configuration

[0967] 1. Terminal

[0968] GUI (Graphical User Interface) for displaying the profile entry form

[0969] Hardware equipped with a camera and microphone to analyze the user's facial expressions and voice to recognize emotions

[0970] A communication module that works with the server to send and receive data

[0971] 2. Server

[0972] A database for receiving user profile information and generating a personality profile.

[0973] Fashion assistant AI and personality AI with specialized knowledge

[0974] A processing module for processing the emotional information received from the emotion engine and readjusting the suggestions.

[0975] A search system for searching specific clothing items from online stores and databases and providing the results to users.

[0976] Program processing explanation

[0977] The program processing of this system will be explained in natural language below.

[0978] 1. Initial Setup and User Registration

[0979] The terminal displays a profile entry form to the user, in which the user enters information such as body type, favorite colors, style, and budget.

[0980] The terminal transmits the entered profile information to the server.

[0981] The server generates a personality profile for the user based on the received profile information and stores it in a database.

[0982] 2. Dialogue between Expertise AI and Personality AI begins

[0983] The server sends the generated personality profile to the fashion assistant AI and asks it to suggest a fashion style that suits the user.

[0984] The fashion assistant AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[0985] The fashion assistant AI sends the suggestions to the server.

[0986] 3. Feedback from personality AI

[0987] The server sends the suggestions sent by the fashion assistant AI to the personality AI.

[0988] Personality AI analyzes suggestions based on the user's past selection history and feedback, and optimizes them as needed.

[0989] The server sends the optimized proposal to the terminal and displays it to the user.

[0990] 4. Emotion Recognition by Emotion Engine

[0991] The device uses a camera and microphone to analyze the user's facial expressions and voice and recognize their emotions.

[0992] The terminal transmits the recognized emotion information to the server.

[0993] 5. Recalibrate your emotional offers

[0994] The server receives emotional information from the emotion engine and instructs the personality AI and fashion assistant AI to readjust.

[0995] The Personality AI and Fashion Assistant AI will reassess suggestions based on emotional information and make adjustments as needed.

[0996] The server sends the re-adjusted proposal to the terminal and re-displays it to the user.

[0997] 6. Search and display specific clothing items

[0998] The server then searches for specific clothes from online stores and databases based on the final adjusted fashion style.

[0999] The terminal displays the search results to the user and provides a purchase link for each item.

[1000] When the user clicks on the purchase link, the device opens the purchase page of the corresponding online shop.

[1001] Specific examples

[1002] Example 1: User A's scenario, who prefers casual style

[1003] 1. Initial Setup and User Registration

[1004] User A enters his / her body type (slim), preferred colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and clicks the send button.

[1005] The terminal transmits this information to the server.

[1006] The server generates a personality profile based on user A's information and stores it in a database.

[1007] 2. Dialogue between Expertise AI and Personality AI begins

[1008] The server sends the generated personality profile to the fashion assistant AI and requests casual style fashion suggestions.

[1009] The fashion assistant AI generates casual suggestions for shirts and jeans in blue and green tones.

[1010] The fashion assistant AI sends the suggestions to the server.

[1011] 3. Feedback from personality AI

[1012] The server sends these suggestions to a personality AI, which optimizes them based on past selection history.

[1013] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[1014] The server sends the optimized proposal to the terminal and displays it to User A.

[1015] 4. Emotion Recognition by Emotion Engine

[1016] When User A sees the provided suggestion, the device's camera analyzes his / her facial expressions, which indicate emotions.

[1017] The terminal transmits the analysis results to the server, which determines that User A is relaxed.

[1018] 5. Recalibrate your emotional offers

[1019] The server instructs the personality AI and fashion assistant AI to readjust based on the relaxed emotion.

[1020] Personality AI and fashion assistant AI will reevaluate casual styles that emphasize a relaxed feel and generate optimal suggestions.

[1021] The server sends this re-adjusted proposal to the terminal and re-displays it to User A.

[1022] 6. Search and display specific clothing items

[1023] The server searches online stores for specific clothing items based on the re-tailored suggestions.

[1024] The terminal displays multiple search results to User A and provides a purchase link for each clothing item.

[1025] When User A clicks on the purchase link, the device opens the purchase page of the corresponding online shop.

[1026] Prompt Sentence Examples

[1027] "Based on my profile, please suggest a casual fashion style with blue and green as the main colors. My budget is under 5,000 yen. I would also be happy if the suggested style has a relaxed feel."

[1028] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1029] Step 1:

[1030] Initial Setup and User Registration

[1031] Specific actions

[1032] The terminal displays a profile entry form to the user.

[1033] The user enters profile information such as body type, preferred colors, style, budget, etc., and clicks the submit button.

[1034] input

[1035] Profile information such as your body type, preferred colors, style, budget, etc.

[1036] process

[1037] Format and validate profile data.

[1038] The formatted data is sent to the server via the network.

[1039] output

[1040] User profile information sent to the server

[1041] Step 2:

[1042] Generating a personality profile

[1043] Specific actions

[1044] The server receives the user profile information sent from the terminal.

[1045] input

[1046] User Profile Information

[1047] process

[1048] Analyzes the profile and stores it in the database.

[1049] Generate a personality profile for the user.

[1050] output

[1051] Personality profiles stored in a database

[1052] Step 3:

[1053] Dialogue between expert knowledge AI and personality AI begins

[1054] Specific actions

[1055] The server sends the generated personality profile to the fashion assistant AI.

[1056] input

[1057] Personality Profile

[1058] process

[1059] This involves generating fashion style suggestions using fashion assistant AI.

[1060] It takes into account fashion trend data as well as the user's body type, preferred colors, style, and budget.

[1061] output

[1062] Fashion style suggestions generated by fashion assistant AI

[1063] Style suggestions sent to the server

[1064] Step 4:

[1065] Personality AI feedback

[1066] Specific actions

[1067] The server sends the suggestions received from the fashion assistant AI to the personality AI.

[1068] input

[1069] Fashion style suggestions

[1070] process

[1071] Personality AI evaluates and optimizes suggestions based on past selection history and feedback information.

[1072] output

[1073] Optimized fashion style suggestions

[1074] Optimization suggestions sent to the server

[1075] Step 5:

[1076] Emotion recognition by emotion engine

[1077] Specific actions

[1078] The device uses a camera and microphone to analyze the user's emotions.

[1079] input

[1080] User's facial expression and voice data

[1081] process

[1082] Facial expressions and voice are analyzed using an emotion engine to extract emotional information.

[1083] Emotion information is sent to the server.

[1084] output

[1085] Emotional information sent to the server

[1086] Step 6:

[1087] Recalibrating sentiment-based recommendations

[1088] Specific actions

[1089] The server transmits the emotion information received from the emotion engine to the personality AI and fashion assistant AI.

[1090] input

[1091] emotional information

[1092] process

[1093] Based on emotional information, the personality AI and fashion assistant AI will reevaluate and readjust.

[1094] output

[1095] Re-adjusted fashion style suggestions

[1096] The server sends the retuned proposal to the device.

[1097] Step 7:

[1098] Search and display specific clothing items

[1099] Specific actions

[1100] The server then searches online stores and databases for specific clothing items based on the reworked suggestions.

[1101] input

[1102] Re-adjusted fashion style suggestions

[1103] process

[1104] Performing online store and database searches and retrieving results

[1105] output

[1106] Clothing item search results

[1107] Display search results on your device and provide a purchase link

[1108] Step 8:

[1109] Purchase procedure

[1110] Specific actions

[1111] The user clicks on the purchase link displayed on the terminal.

[1112] input

[1113] Click on the purchase link (selection)

[1114] process

[1115] The device will open the purchase page of the relevant online shop.

[1116] output

[1117] The online shop purchase page will be displayed.

[1118] These are the specific processing steps. In this way, the user is presented with the most suitable fashion style based on their own feelings and feedback, and can purchase specific clothes on the spot.

[1119] (Application example 2)

[1120] 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."

[1121] Conventional fashion suggestion systems can suggest styles based on static information such as a user's preferences and body type, but they cannot adjust the suggestions to take into account the user's emotional state. As a result, they are unable to make suggestions that match the user's mood at any given time, resulting in lower suggestion accuracy and lower satisfaction. Furthermore, they lack the ability to provide real-time fashion suggestions and reflect recognition results in the virtual space, resulting in a poor user experience.

[1122] 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.

[1123] In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize the fashion style suggestions based on the user's past selection history and feedback, means for recognizing the user's emotions using an emotion recognition engine and reevaluating and optimizing the fashion style suggestions based on the emotion information, and means for displaying the emotion-updated fashion style suggestions in a virtual space using a head-mounted display, thereby enabling more personalized fashion style suggestions that reflect the user's emotional state in real time.

[1124] "User profile information" is information about personal attributes such as the user's body type, favorite colors, style, and budget.

[1125] "Fashion assistant AI with specialized knowledge" is an artificial intelligence used to generate fashion style suggestions based on a user's profile information.

[1126] "Fashion style suggestions" refer to styles and coordinations suggested based on the user's personal attributes and preferences.

[1127] The "user's past selection history" is a record of the styles selected and items purchased by the user.

[1128] "Personality AI" is an artificial intelligence that optimizes fashion style suggestions based on the user's past selection history and feedback.

[1129] An "emotion recognition engine" is a technology or software that analyzes a user's facial expressions and voice to recognize their emotions.

[1130] "Emotion information" is data relating to the user's emotional state obtained by an emotion recognition engine.

[1131] "Reevaluate and optimize" means reviewing existing fashion style suggestions based on emotional information and readjusting them to the optimal suggestions for the user.

[1132] A "head-mounted display" is a display device that provides visual information when worn by a user.

[1133] "Virtual space" refers to a virtual 3D environment displayed using a head-mounted display.

[1134] The system for implementing this invention combines a multi-step process including inputting user profile information, generating and optimizing fashion style suggestions, emotion recognition, displaying suggestions in a virtual space, searching for clothing items from online stores, and providing links to purchase them. The specific configuration and operation of the system are described below.

[1135] Hardware and Software

[1136] Hardware:

[1137] Head-mounted displays (e.g., Oculus Rift, Valve Index, HTC Vive)

[1138] Camera and microphone (for emotion recognition)

[1139] software:

[1140] Unity3D (Building a virtual space)

[1141] Azure Cognitive Services (emotion recognition)

[1142] Amazon Web Services (AWS) (data management and processing)

[1143] OpenAI API (fashion suggestion generation)

[1144] Zalando API (clothing data acquisition)

[1145] Program processing explanation

[1146] 1. Initial Setup and User Registration

[1147] Users wear a head-mounted display (HMD) and input their profile information (body type, favorite colors, style, budget, etc.) This information is sent to the AWS server via Azure's API, and the user's profile is stored in a database.

[1148] 2. Dialogue between Expertise AI and Personality AI begins

[1149] The AWS server receives the saved user profile information and requests fashion style suggestions from the OpenAI API, which generates multiple fashion style suggestions based on the trend data and user information.

[1150] 3. Feedback from personality AI

[1151] The AWS server receives the generated fashion style suggestions, which are then evaluated and optimized by the personality AI based on past selection history and feedback. The optimized suggestions are then displayed on the HMD.

[1152] 4. Emotion recognition using an emotion recognition engine

[1153] Using the camera and microphone of the HMD worn by the user, the Azure Cognitive Services emotion analysis API analyzes the user's facial expressions and voice to recognize their emotional state. Emotional information is then sent to the AWS server.

[1154] 5. Recalibrate your emotional recommendations

[1155] Based on the received emotion information, the AWS server requests the OpenAI API to generate and re-evaluate fashion suggestions based on the emotion. The re-adjusted suggestions are then displayed on the HMD.

[1156] 6. Search and display specific clothing items

[1157] The AWS server then uses the Zalando API to search for specific clothing items based on the final tailored fashion style suggestions. The search results are displayed on the HMD, and users can purchase the clothing online via a purchase link.

[1158] Examples and prompts

[1159] Specific examples

[1160] Example 1: User A's scenario, who prefers casual style

[1161] 1. User A enters their body type (normal), preferred colors (red, black), style (formal), and budget (under 10,000 yen), and the information is sent to the AWS server.

[1162] 2. Based on this information, the OpenAI API generates fashion style suggestions.

[1163] 3. Personality AI takes into account past selection history and optimizes suggestions.

[1164] 4. Azure Cognitive Services analyzes the user's emotions from their facial expressions and voice and sends the information to the AWS server.

[1165] 5. Based on the emotion information, the OpenAI API readjusts the fashion suggestions and displays them again on the HMD.

[1166] 6. User A searches for a specific clothing item using the Zalando API and purchases the clothing from the purchase link displayed on the HMD.

[1167] Prompt Sentence Examples

[1168] User Profile:

[1169] Body type: Normal body type

[1170] Favorite colors: Red, black

[1171] Style: Formal

[1172] Budget: Under 10,000 yen

[1173] Emotion information:

[1174] Expression: Relaxed

[1175] Voice analysis: peace of mind

[1176] Suggest a suitable formal fashion style for this user.

[1177] This system can provide more accurate fashion style suggestions that reflect the user's emotional state in real time. In addition, the suggestions change reactively in the virtual space, allowing users to choose the optimal fashion that best suits their emotions.

[1178] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1179] Step 1:

[1180] Users wear a head-mounted display (HMD) and enter their profile information (body type, favorite colors, style, budget, etc.) The entered information is sent to the AWS server via Azure's API.

[1181] Input: User profile information

[1182] Output: User profile information stored in the database

[1183] Action: Displays the profile form and submits the entered data.

[1184] Step 2:

[1185] The AWS server receives the stored user profile information and requests fashion style suggestions from the OpenAI API, which generates multiple fashion style suggestions based on the trend data and user information.

[1186] Input: User profile information, trend data

[1187] Output: Generated fashion style suggestions

[1188] What it does: Sends API requests and receives proposal data

[1189] Step 3:

[1190] The AWS server receives the generated fashion style suggestions, which are then evaluated by the personality AI based on past selection history and feedback, and optimized as needed. The optimized suggestions are then displayed on the HMD.

[1191] Input: Fashion style suggestions, past selection history, feedback information

[1192] Output: Optimized fashion style suggestions

[1193] Operation: Evaluate and optimize proposed data, display on HMD

[1194] Step 4:

[1195] Using the HMD's camera and microphone, the Azure Cognitive Services emotion analysis API analyzes the user's facial expressions and voice to recognize their emotional state, and the emotion information is sent to an AWS server.

[1196] Input: User's facial expression data, voice data

[1197] Output: Recognized emotion information

[1198] Operation: Camera and microphone data acquisition, emotion analysis, and emotion data transmission

[1199] Step 5:

[1200] Based on the received emotion information, the AWS server requests fashion suggestions from the OpenAI API again, generates and re-evaluates fashion style suggestions according to the emotion, and displays the re-adjusted suggestions on the HMD.

[1201] Input: Emotional information, initial fashion style suggestions

[1202] Output: Reworked fashion style suggestions

[1203] Action: Evaluate and readjust the emotional information, and display it again on the HMD

[1204] Step 6:

[1205] The AWS server then uses the Zalando API to search for specific clothing items based on the final tailored fashion style suggestions. The search results are displayed on the HMD, and users can purchase the clothing online via a purchase link.

[1206] Input: Reworked fashion style suggestions

[1207] Output: Searched clothing items and purchase links

[1208] Operation: Searching for clothing data, generating and displaying purchase links

[1209] 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.

[1210] 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.

[1211] 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.

[1212] [Third embodiment]

[1213] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1214] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1215] 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).

[1216] 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.

[1217] 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.

[1218] 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).

[1219] 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.

[1220] 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.

[1221] 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.

[1222] 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.

[1223] 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.

[1224] 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."

[1225] This invention relates to a system that helps users find clothes that suit them. Based on user profile information, a fashion assistant AI and a personality AI work together to suggest the optimal fashion style, and then search online stores for specific clothes that match that style and provide them.

[1226] Program processing explanation

[1227] 1. Initial Setup and User Registration

[1228] The terminal displays a profile input form to the user, who then inputs profile information such as his or her body type, favorite colors, style, budget, etc. The terminal then transmits this information to the server.

[1229] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[1230] 2. Dialogue between Expertise AI and Personality AI begins

[1231] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[1232] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[1233] 3. Feedback from personality AI

[1234] The server sends the fashion style suggestions received from the expert knowledge AI to the personality AI, which evaluates the suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[1235] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[1236] 4. User feedback and refinement

[1237] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[1238] The server receives the user's feedback and again requests optimization from the fashion assistant AI and personality AI.

[1239] 5. Search and display specific clothing items

[1240] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[1241] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[1242] Specific examples

[1243] Example 1: User A's scenario, who prefers casual style

[1244] 1. Initial Setup and User Registration

[1245] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[1246] The server generates a personality profile based on user A's information and stores it in a database.

[1247] 2. Dialogue between Expertise AI and Personality AI begins

[1248] The server sends User A's profile to the expert knowledge AI and requests casual style fashion suggestions.

[1249] The AI ​​expertise generates casual suggestions for shirts and jeans in blue and green tones.

[1250] 3. Feedback from personality AI

[1251] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[1252] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[1253] The server sends the proposal to the terminal and displays it to User A.

[1254] 4. User feedback and refinement

[1255] User A provides feedback that he would like more variation in the proposals.

[1256] The terminal sends this feedback to the server, which then requests optimization again.

[1257] 5. Search and display specific clothing items

[1258] The server searches for specific clothes from online stores based on the optimized suggestions.

[1259] The device displays multiple search results to User A and provides a purchase link for each item. When User A clicks a link, the device opens a purchase page.

[1260] In this way, users can efficiently find the clothes that best suit them and smoothly proceed to purchasing. The system combines the user's preferences with the latest fashion information to help them select the best clothes.

[1261] The processing flow will be explained below.

[1262] Step 1:

[1263] The terminal displays a profile entry form to the user, in which the user enters profile information such as their body type, favorite colors, style, and budget.

[1264] Step 2:

[1265] The terminal transmits the entered profile information to the server.

[1266] Step 3:

[1267] The server generates a personality profile for the user based on the received profile information, which is then stored in a database.

[1268] Step 4:

[1269] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[1270] Step 5:

[1271] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[1272] Step 6:

[1273] The server sends the fashion style suggestions received from the specialized knowledge AI to the personality AI.

[1274] Step 7:

[1275] The Personality AI evaluates these suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[1276] Step 8:

[1277] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[1278] Step 9:

[1279] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[1280] Step 10:

[1281] The server receives the user's feedback and again requests optimization from the fashion assistant AI and personality AI.

[1282] Step 11:

[1283] A new optimized fashion style suggestion is generated, which the server sends back to the terminal and displays to the user.

[1284] Step 12:

[1285] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[1286] Step 13:

[1287] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[1288] Example 1

[1289] 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."

[1290] Conventional fashion suggestion systems often fail to fully consider the individual needs and styles of users, resulting in uniform suggestions. Furthermore, they fail to properly utilize the user's past behavioral data and feedback, resulting in low suggestion accuracy. Furthermore, there is also the problem of it taking a long time to search for specific clothing and provide it to the user. This prevents users from efficiently finding the perfect outfit for them, resulting in low satisfaction.

[1291] 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.

[1292] In this invention, the server includes means for inputting user profile information, means for causing an artificial intelligence with specialized knowledge to generate fashion style suggestions based on the user profile information, means for using an artificial intelligence with personality analysis to optimize the fashion style suggestions based on the user's past selection history and feedback, means for providing the optimized fashion style suggestions to the user, means for searching for specific clothing from a database based on the fashion style suggestions, and means for displaying the search results to the user and providing a purchase link. This allows the server to provide fashion suggestions quickly and accurately, fully meeting the user's individual needs and preferences, and enabling the user to efficiently find the clothes that best suit them.

[1293] "User" refers to an individual who utilizes the system to provide fashion suggestions or search for specific clothing items.

[1294] "Profile Information" refers to data about a user, such as body type, preferred colors, style, budget, etc., that is used to understand the user's preferences and characteristics.

[1295] "Artificial intelligence with specialized knowledge" refers to artificial intelligence that has extensive knowledge and trend data about fashion and is capable of generating fashion style suggestions based on a user's profile information.

[1296] "Personality analysis artificial intelligence" refers to artificial intelligence that evaluates and optimizes fashion style suggestions based on the user's past selection history and feedback information.

[1297] "Optimization" refers to adjusting fashion style suggestions to match a user's preferences based on the user's feedback and past selection history.

[1298] "Database" refers to a repository of information that the system uses to suggest fashion styles and search for specific clothing.

[1299] "Search results" refers to specific clothing information retrieved from databases and online stores and displayed to the user as a list.

[1300] "Buy Link" means a hyperlink that a User can click to directly access the purchase page of the applicable online store to purchase a particular garment.

[1301] MODE FOR CARRYING OUT THE INVENTION

[1302] This invention relates to a system that helps users find clothes that suit them. Based on user profile information, an artificial intelligence with specialized knowledge (hereinafter referred to as "fashion assistant AI") and a personality analysis artificial intelligence (hereinafter referred to as "personality AI") work together to suggest the optimal fashion style, and then searches a database or other source for specific clothes that match that style and provides them.

[1303] 1. Initial Setup and User Registration

[1304] The device displays a profile entry form to the user. This form is often created using HTML and JavaScript. The user enters profile information such as their body type (e.g., slim, curvy), favorite colors (e.g., blue, green), style (e.g., casual, formal), and budget (e.g., under 5,000 yen). The device then sends this information to the server using JavaScript or JSON.

[1305] The server analyzes the received user profile information and stores each item in its own table in the database. Based on this information, a personality profile of the user is generated and stored in the database.

[1306] 2. Fashion Style Proposal Generation

[1307] The server reads the user's personality profile and sends it to the fashion assistant AI, using a prompt such as "Please generate fashion style suggestions based on the profile of user ID 123."

[1308] The fashion assistant AI generates multiple fashion style suggestions based on fashion trend data, the user's body type, preferred colors, style, budget, etc. For example, it suggests a specific style such as "a blue shirt and green jeans."

[1309] 3. Optimization with personality AI

[1310] The server sends the fashion style suggestions received from the fashion assistant AI to the personality AI, along with a prompt message saying, "Please evaluate and optimize this suggestion based on user ID 123's past selection history and feedback."

[1311] The Personality AI evaluates the suggestions based on the user's past selection history and feedback information, and makes adjustments as necessary. For example, this adjustment may include "Since the user previously mainly selected blue, we will strengthen blue-based suggestions."

[1312] The server receives the optimized proposal and sends it to the terminal for display to the user.

[1313] 4. User feedback and refinement

[1314] The user can check the optimized fashion style suggestions displayed on the device and enter feedback, such as "I want more casual items" or "I'm willing to spend a little more."

[1315] The terminal obtains this feedback and sends it to the server.

[1316] The server analyzes the user's feedback and again requests optimization from the fashion assistant AI and personality AI. For example, it generates a specific prompt such as, "User ID 123 wants more casual items, and the budget can be increased to 7,000 yen."

[1317] 5. Search and display specific clothing items

[1318] The server searches for specific clothing items from online stores or internal databases based on the final proposed fashion style, and retrieves matching items from online stores using a RESTful API.

[1319] The device displays the search results to the user. Each clothing item is provided with a purchase link. For example, an image of a blue shirt is displayed with a "Buy here" link.

[1320] When a user clicks on a purchase link, the device opens the linked purchase page, allowing the user to smoothly proceed with the purchase process.

[1321] Prompt Sentence Examples

[1322] "Based on the profile information entered by User A, who is in his 20s and likes casual style, please generate fashion suggestions based on blue and green. The budget is under 5,000 yen."

[1323] "Please increase the variety of casual styles based on user feedback and re-propose them."

[1324] In this way, the system effectively utilizes multiple AI technologies to provide optimal fashion suggestions tailored to the user's needs, allowing the user to efficiently find clothes that suit them and facilitating the purchasing process.

[1325] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1326] Step 1: Initial Setup and User Registration

[1327] The device presents the user with a profile entry form, written in HTML and with interactive elements added using JavaScript, in which the user enters information such as body type, preferred colors, style, and budget.

[1328] Input: Profile information entered by the user (e.g., body type is slim, favorite colors are blue and green, style is casual, budget is under 5,000 yen).

[1329] The terminal uses JavaScript to format the input data in JSON format and send it to the server.

[1330] The server parses the received JSON data, extracts each item individually, and stores it in a table in the database.

[1331] Data processing: Parse the JSON data and save it as user profile information.

[1332] Output: User profile information stored in a database.

[1333] Step 2: Generate fashion style suggestions

[1334] The server reads the stored user profile information and sends it to the Fashion Assistant AI for use in the next stage.

[1335] Input: User profile information retrieved from the database.

[1336] The server sends a prompt to the fashion assistant AI saying, "Please generate fashion style suggestions based on the profile of user ID 123."

[1337] The fashion assistant AI analyzes user profile information based on a trend database and generates multiple fashion style suggestions.

[1338] Data calculation: Calculate and generate fashion styles using trend data and user profile information.

[1339] Output: Generated fashion style suggestions (e.g., blue shirt and green jeans).

[1340] Step 3: Optimization with personality AI

[1341] The server sends the style suggestions received from the fashion assistant AI to the personality AI.

[1342] Input: Generated fashion style suggestions.

[1343] The server sends a prompt to the personality AI saying, "Please evaluate and optimize this suggestion based on user ID 123's past selection history and feedback."

[1344] Personality AI analyzes the user's past selection history and feedback to evaluate and optimize fashion style suggestions.

[1345] Data calculation: Evaluate and optimize proposals based on user history and feedback.

[1346] Output: Optimized fashion style suggestions.

[1347] Step 4: User feedback and refinement

[1348] The terminal displays the optimized fashion style suggestions to the user.

[1349] The user enters feedback about the suggestion (e.g., I'd like more casual items).

[1350] Input: User feedback.

[1351] The terminal takes this feedback and sends it back to the server.

[1352] The server analyzes the feedback and, if necessary, re-optimizes using the fashion assistant AI and personality AI.

[1353] Data calculation: Analyze feedback and re-adjust / optimize suggestions.

[1354] Output: Re-optimized fashion style suggestions.

[1355] Step 5: Search and view specific clothing items

[1356] The server searches for specific clothes from online stores and databases based on the fully optimized fashion style, and communicates with the online stores using APIs.

[1357] Input: optimized fashion style suggestions.

[1358] Data calculations: Search online stores and internal databases based on suggestions.

[1359] Output: Specific clothing items as search results.

[1360] The terminal displays the search results to the user and provides a purchase link corresponding to each item.

[1361] When a user clicks on a purchase link, the device opens the linked purchase page, allowing the user to access the purchase page directly.

[1362] (Application example 1)

[1363] 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."

[1364] Today's consumers spend a lot of time and effort finding the perfect fashion style. Finding clothes that suit them efficiently can be challenging, especially when shopping in brick-and-mortar stores. Real-time advice and augmented reality suggestions would enhance the consumer experience, but current systems struggle to achieve this. A new system is needed to address these challenges.

[1365] 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.

[1366] In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize the fashion style suggestions based on the user's past selection history and feedback, means for providing the optimized fashion style suggestions to the user, means for searching for specific clothes from an online store or database based on the fashion style suggestions, means for displaying the search results to the user and providing a purchase link, means for suggesting clothes to be worn by the user in a physical store in real time, and means for displaying the suggested information in augmented reality in real time in the physical store. This allows users to efficiently find the best clothes for them in a physical store, and significantly improves the consumer experience through real-time suggestions and augmented reality displays.

[1367] 1. "Means for inputting user profile information" refers to an interface for inputting and collecting personal information such as the user's body type, preferred colors, style, budget, etc.

[1368] 2. "Fashion assistant AI with specialized knowledge" is an artificial intelligence that uses fashion trend data and knowledge to refer to a user's profile information and suggest the most suitable fashion style.

[1369] 3. "Means using personality AI" refers to means that use artificial intelligence to analyze a user's past selection history and feedback information and optimize fashion style suggestions based on that information.

[1370] 4. "Means for providing the user with the above-mentioned optimized fashion style suggestions" refers to an interface that displays and provides the user with fashion style suggestions optimized by personality AI.

[1371] 5. "Means for searching for specific clothing from online stores or databases" refers to means for searching for specific clothing that corresponds to optimal fashion style suggestions using online stores or internal databases.

[1372] 6. "Means for displaying search results to users and providing purchase links" refers to an interface that displays information about clothing searched from online stores and databases to users and provides purchase links for those items.

[1373] 7. "Means for suggesting clothes to be worn by users in real time in a physical store" is a system that suggests the most suitable clothes to users in real time on the spot while they are shopping in a physical store.

[1374] 8. "Means for displaying suggested information in real time using augmented reality within a physical store" refers to a system that uses augmented reality technology to visually display suggested item information in real time when a user checks out a product in a physical store.

[1375] This invention provides an application system for smartphones or smart glasses that allows users to efficiently find the best clothes for themselves in a physical store. This system supports clothing selection in a physical store by linking a fashion assistant AI and a personality AI based on user profile information.

[1376] System configuration

[1377] Hardware:

[1378] Device: Smartphone or smart glasses

[1379] Server: For information processing and data storage

[1380] Network infrastructure: Internet connectivity to send and receive data

[1381] software:

[1382] Fashion Assistant AI: Artificial intelligence that suggests fashion styles based on user profile information

[1383] Personality AI: Artificial intelligence that optimizes fashion style suggestions based on the user's past selection history and feedback information

[1384] Augmented reality (AR) technology: AR software (e.g., Apple's ARKit) that displays recommendations in real time within a physical store.

[1385] System Operation

[1386] 1. Initial setup and user registration:

[1387] First, the terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, budget, etc. This information is sent to the server.

[1388] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[1389] 2. Fashion proposal generation:

[1390] The server requests the fashion assistant AI to generate fashion style suggestions based on the user's personality profile.

[1391] The fashion assistant AI generates multiple suggestions based on current fashion trends, the user's body type, preferred colors, style, and budget.

[1392] 3. Optimize your offers:

[1393] The server sends the generated fashion style suggestions to the personality AI, which optimizes the suggestions based on the user's past selection history and feedback.

[1394] The Personality AI evaluates the suggestions and makes modifications or optimizations as necessary, and the optimized suggestions are sent to the device and displayed to the user.

[1395] 4. Real-time in-store recommendations:

[1396] When a user is shopping in a physical store and looks at products displayed through the smart glasses, the fashion assistant AI and personality AI provide optimized recommendations in real time via AR display.

[1397] 5. Gather feedback and readjust:

[1398] The user enters feedback about the proposed style, and the terminal sends this to the server.

[1399] Based on the feedback, the server again requests optimization from the fashion assistant AI and personality AI.

[1400] 6. Search and view specific clothing:

[1401] The server searches for specific clothing items from online stores and databases based on the optimized fashion style suggestions.

[1402] The terminal displays the search results to the user and provides a purchase link for each clothing item.

[1403] Specific examples

[1404] Example 1: User A's scenario, who prefers casual style

[1405] 1. Initial setup and user registration:

[1406] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[1407] The server generates a personality profile based on user A's information and stores it in a database.

[1408] 2. Fashion proposal generation:

[1409] The server generates casual style fashion suggestions based on the profile of user A.

[1410] The fashion assistant AI suggests casual shirts and jeans in blue and green tones.

[1411] 3. Optimize your offers:

[1412] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[1413] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[1414] The server sends the proposal to the terminal and displays it to User A.

[1415] 4. Real-time in-store recommendations:

[1416] User A uses smart glasses in a physical store to select clothes and check real-time suggested information about potential purchases displayed in AR.

[1417] Example prompt for a generative AI model:

[1418] "Please suggest the best fashion style for the user based on their body type, preferred colors, style, and budget. This suggestion is for a user who prefers casual styles."

[1419] "Optimize your suggestions by taking into account past selection history and feedback information."

[1420] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1421] Step 1:

[1422] Initial Setup and User Registration

[1423] The terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, budget, etc. This information is sent from the terminal to the server.

[1424] Input: Profile information such as user's body type, favorite colors, style, budget, etc.

[1425] Processing: The device collects user input information and sends it to the server, which receives the information and generates a personality profile.

[1426] Output: Personality profile stored in a database

[1427] Step 2:

[1428] Fashion proposal generation

[1429] The server requests the fashion assistant AI to generate fashion style suggestions based on the user's personality profile.

[1430] Enter: personality profile

[1431] Processing: Fashion assistant AI generates multiple fashion style suggestions taking into account fashion trend data, body type, preferred colors, style, and budget.

[1432] Output: Multiple fashion style suggestions

[1433] Step 3:

[1434] Recommendation optimization

[1435] The server sends the generated fashion style suggestions to the personality AI, which optimizes the suggestions based on the user's past selection history and feedback.

[1436] Input: Fashion style suggestions, past selection history, feedback information

[1437] Processing: Personality AI evaluates the suggestions and makes corrections and optimizations as needed.

[1438] Output: Optimized fashion style suggestions

[1439] Step 4:

[1440] Providing optimized proposals

[1441] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[1442] Input: Optimized fashion style suggestions

[1443] Processing: The server sends the proposal to the terminal, which displays it to the user.

[1444] Output: Optimized fashion style suggestions displayed to the user

[1445] Step 5:

[1446] Real-time proposals in physical stores

[1447] When a user looks at a product through the smart glasses in a physical store, the information is sent to the server, and suggested information optimized by the fashion assistant AI and personality AI is displayed in real time using AR.

[1448] Input: Product information in physical stores, user location information

[1449] Processing: The Fashion Assistant AI and Personality AI generate real-time suggestions based on the captured information and display them on the user's smart glasses using AR technology.

[1450] Output: Real-time suggested information displayed on smart glasses

[1451] Step 6:

[1452] Gather feedback and refine

[1453] The user enters feedback about the proposed style, and the terminal sends this to the server.

[1454] Input: User feedback

[1455] Processing: Based on the feedback, the server again requests optimization from the fashion assistant AI and personality AI, generating new suggestions.

[1456] Output: Updated fashion style suggestions

[1457] Step 7:

[1458] Search and display specific clothing items

[1459] The server searches for specific clothing items from online stores and databases based on optimized fashion style suggestions and displays them on the device.

[1460] Input: Optimized fashion style suggestions

[1461] Processing: The server searches online stores and databases, collects the appropriate item information, and sends it to the device.

[1462] Output: Specific clothing item displayed on device with a link to purchase

[1463] 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.

[1464] This invention relates to a system that proposes a fashion style suitable for a user and searches for and provides specific clothes that match that style from online stores, etc. This invention is characterized by the combination of a feeling engine that recognizes the user's feelings and adjusts the proposed fashion style based on the user's feelings.

[1465] Program processing explanation

[1466] 1. Initial Setup and User Registration

[1467] The terminal displays a profile input form to the user, who then inputs profile information such as his or her body type, favorite colors, style, budget, etc. The terminal then transmits this information to the server.

[1468] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[1469] 2. Dialogue between Expertise AI and Personality AI begins

[1470] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[1471] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[1472] 3. Feedback from personality AI

[1473] The server sends the fashion style suggestions received from the expert knowledge AI to the personality AI, which evaluates the suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[1474] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[1475] 4. Emotion Recognition by Emotion Engine

[1476] The device uses a camera to analyze the user's facial expressions and recognize their emotions, or uses voice relative analysis to determine the user's emotions.

[1477] The terminal transmits the recognized emotion information to the server.

[1478] 5. Recalibrate your emotional offers

[1479] The server receives emotional information from the emotion engine and instructs the personality AI and fashion assistant AI to readjust.

[1480] The Personality AI and Fashion Assistant AI will reassess fashion style suggestions based on the user's emotions and revise the suggestions as needed.

[1481] The server sends the retuned proposal to the terminal and displays it to the user.

[1482] 6. Search and display specific clothing items

[1483] The server then searches for specific clothing items from online stores and databases based on the final proposed fashion style.

[1484] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[1485] Specific examples

[1486] Example 1: User A's scenario, who prefers casual style

[1487] 1. Initial Setup and User Registration

[1488] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[1489] The server generates a personality profile based on user A's information and stores it in a database.

[1490] 2. Dialogue between Expertise AI and Personality AI begins

[1491] The server sends User A's profile to the expert knowledge AI and requests casual style fashion suggestions.

[1492] The AI ​​expertise generates casual suggestions for shirts and jeans in blue and green tones.

[1493] 3. Feedback from personality AI

[1494] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[1495] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[1496] The server sends the proposal to the terminal and displays it to User A.

[1497] 4. Emotion Recognition by Emotion Engine

[1498] User A uses the facial expression analysis function, and the device analyzes the emotion and sends it to the server.

[1499] The server receives the emotion information and determines that the emotion is relaxed.

[1500] 5. Recalibrate your emotional offers

[1501] The server instructs the personality AI and expertise AI to readjust based on the relaxed emotion.

[1502] Expertise AI and personality AI reevaluate casual styles that emphasize a relaxed feel and generate optimal suggestions.

[1503] The server sends this re-adjusted proposal to the terminal and re-displays it to User A.

[1504] 6. Search and display specific clothing items

[1505] The server searches online stores for specific clothing items based on the re-tailored suggestions.

[1506] The device displays multiple search results to User A and provides a purchase link for each item. When User A clicks a link, the device opens the purchase page.

[1507] In this way, User A can find the perfect outfit to match his / her emotions and easily proceed to the purchasing process. This system provides a more personalized fashion selection experience by making suggestions that take into account the user's preferences and emotions.

[1508] The processing flow will be explained below.

[1509] Step 1:

[1510] The terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, and budget.

[1511] Step 2:

[1512] The terminal transmits the entered profile information to the server.

[1513] Step 3:

[1514] The server generates a personality profile for the user based on the received profile information and stores this information in a database.

[1515] Step 4:

[1516] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[1517] Step 5:

[1518] The specialized knowledge AI takes into account fashion trend data, the user's body type, preferred colors, style, budget, etc. to generate multiple fashion style suggestions.

[1519] Step 6:

[1520] The server sends the fashion style suggestions received from the specialized knowledge AI to the personality AI.

[1521] Step 7:

[1522] Personality AI evaluates suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[1523] Step 8:

[1524] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[1525] Step 9:

[1526] The device sends the facial expressions captured by the user with a camera and recorded voice data to an emotion engine, which analyzes the emotions.

[1527] Step 10:

[1528] The emotion engine analyzes the user's facial expressions and voice data to recognize their emotions. The recognized emotion information is sent to the server via the device.

[1529] Step 11:

[1530] Based on the received emotional information, the server instructs the emotion engine, personality AI, and expertise AI to readjust.

[1531] Step 12:

[1532] Personality AI and expertise AI take into account the user's emotional information to generate new fashion style suggestions.

[1533] Step 13:

[1534] The server sends the re-adjusted fashion style suggestions to the terminal and displays them again to the user.

[1535] Step 14:

[1536] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[1537] Step 15:

[1538] The server again receives user feedback and finalizes the final fashion style suggestions.

[1539] Step 16:

[1540] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[1541] Step 17:

[1542] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks on the purchase link, the device opens a purchase page.

[1543] This process allows users to find the perfect fashion style based on their own feelings and preferences, and easily proceed to purchase.

[1544] Example 2

[1545] 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."

[1546] Conventional fashion suggestion systems only make suggestions based on a user's profile information and past selection history, and lack the ability to readjust based on the user's recent emotions and feedback. As a result, they are unable to provide optimal fashion suggestions that reflect the user's mental state or temporary emotional changes, and an improvement in the user experience is needed.

[1547] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize fashion style suggestions based on the user's past selection history and feedback, means for recognizing the user's emotions using an emotion engine and transmitting the emotion information to the server, means for reevaluating and readjusting the suggestions based on the user's emotion information, means for searching for specific clothes from online stores and databases, and means for displaying search results to the user and providing a purchase link. This enables personalized fashion suggestions that reflect the user's emotions and feedback in real time.

[1548] "User" refers to an individual who wants to use this system to have a fashion style suggested that suits them.

[1549] "Profile Information" refers to information entered by a user that indicates personal attributes and preferences, such as body type, preferred colors, style, budget, etc.

[1550] "Fashion Assistant AI" refers to artificial intelligence that has expertise in fashion and generates fashion style suggestions based on a user's profile information.

[1551] "Personality AI" refers to artificial intelligence that optimizes fashion style suggestions based on a user's past selection history and feedback information.

[1552] An "emotion engine" refers to a system that recognizes a user's emotions by analyzing their facial expressions and voice.

[1553] "Fashion style suggestions" refers to fashion style suggestions generated by the fashion assistant AI based on the user's profile information.

[1554] An "online store" refers to a website or platform that sells clothing and other products over the Internet.

[1555] "Database" refers to digital data storage for storing and managing information such as user profile information, past selection history, and feedback.

[1556] "Purchase Link" refers to a hyperlink to a web page that allows a user to purchase specific clothing items based on the fashion style suggestions.

[1557] "Re-adjustment" refers to the process of reviewing and modifying existing fashion style suggestions based on the user's emotional information.

[1558] MODE FOR CARRYING OUT THE INVENTION

[1559] This invention relates to a system that proposes a fashion style suitable for a user and searches for and provides specific clothes that match that style from online stores, etc. In particular, it is characterized by combining an emotion engine that recognizes the user's emotions and adjusting the proposed fashion style based on the user's emotions.

[1560] System Configuration

[1561] 1. Terminal

[1562] GUI (Graphical User Interface) for displaying the profile entry form

[1563] Hardware equipped with a camera and microphone to analyze the user's facial expressions and voice to recognize emotions

[1564] A communication module that works with the server to send and receive data

[1565] 2. Server

[1566] A database for receiving user profile information and generating a personality profile.

[1567] Fashion assistant AI and personality AI with specialized knowledge

[1568] A processing module for processing the emotional information received from the emotion engine and readjusting the suggestions.

[1569] A search system for searching specific clothing items from online stores and databases and providing the results to users.

[1570] Program processing explanation

[1571] The program processing of this system will be explained in natural language below.

[1572] 1. Initial Setup and User Registration

[1573] The terminal displays a profile entry form to the user, in which the user enters information such as body type, favorite colors, style, and budget.

[1574] The terminal transmits the entered profile information to the server.

[1575] The server generates a personality profile for the user based on the received profile information and stores it in a database.

[1576] 2. Dialogue between Expertise AI and Personality AI begins

[1577] The server sends the generated personality profile to the fashion assistant AI and asks it to suggest a fashion style that suits the user.

[1578] The fashion assistant AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[1579] The fashion assistant AI sends the suggestions to the server.

[1580] 3. Feedback from personality AI

[1581] The server sends the suggestions sent by the fashion assistant AI to the personality AI.

[1582] Personality AI analyzes suggestions based on the user's past selection history and feedback, and optimizes them as needed.

[1583] The server sends the optimized proposal to the terminal and displays it to the user.

[1584] 4. Emotion Recognition by Emotion Engine

[1585] The device uses a camera and microphone to analyze the user's facial expressions and voice and recognize their emotions.

[1586] The terminal transmits the recognized emotion information to the server.

[1587] 5. Recalibrate your emotional offers

[1588] The server receives emotional information from the emotion engine and instructs the personality AI and fashion assistant AI to readjust.

[1589] The Personality AI and Fashion Assistant AI will reassess suggestions based on emotional information and make adjustments as needed.

[1590] The server sends the re-adjusted proposal to the terminal and re-displays it to the user.

[1591] 6. Search and display specific clothing items

[1592] The server then searches for specific clothes from online stores and databases based on the final adjusted fashion style.

[1593] The terminal displays the search results to the user and provides a purchase link for each item.

[1594] When the user clicks on the purchase link, the device opens the purchase page of the corresponding online shop.

[1595] Specific examples

[1596] Example 1: User A's scenario, who prefers casual style

[1597] 1. Initial Setup and User Registration

[1598] User A enters his / her body type (slim), preferred colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and clicks the send button.

[1599] The terminal transmits this information to the server.

[1600] The server generates a personality profile based on user A's information and stores it in a database.

[1601] 2. Dialogue between Expertise AI and Personality AI begins

[1602] The server sends the generated personality profile to the fashion assistant AI and requests casual style fashion suggestions.

[1603] The fashion assistant AI generates casual suggestions for shirts and jeans in blue and green tones.

[1604] The fashion assistant AI sends the suggestions to the server.

[1605] 3. Feedback from personality AI

[1606] The server sends these suggestions to a personality AI, which optimizes them based on past selection history.

[1607] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[1608] The server sends the optimized proposal to the terminal and displays it to User A.

[1609] 4. Emotion Recognition by Emotion Engine

[1610] When User A sees the provided suggestion, the device's camera analyzes his / her facial expressions, which indicate emotions.

[1611] The terminal transmits the analysis results to the server, which determines that User A is relaxed.

[1612] 5. Recalibrate your emotional offers

[1613] The server instructs the personality AI and fashion assistant AI to readjust based on the relaxed emotion.

[1614] Personality AI and fashion assistant AI will reevaluate casual styles that emphasize a relaxed feel and generate optimal suggestions.

[1615] The server sends this re-adjusted proposal to the terminal and re-displays it to User A.

[1616] 6. Search and display specific clothing items

[1617] The server searches online stores for specific clothing items based on the re-tailored suggestions.

[1618] The terminal displays multiple search results to User A and provides a purchase link for each clothing item.

[1619] When User A clicks on the purchase link, the device opens the purchase page of the corresponding online shop.

[1620] Prompt Sentence Examples

[1621] "Based on my profile, please suggest a casual fashion style with blue and green as the main colors. My budget is under 5,000 yen. I would also be happy if the suggested style has a relaxed feel."

[1622] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1623] Step 1:

[1624] Initial Setup and User Registration

[1625] Specific actions

[1626] The terminal displays a profile entry form to the user.

[1627] The user enters profile information such as body type, preferred colors, style, budget, etc., and clicks the submit button.

[1628] input

[1629] Profile information such as your body type, preferred colors, style, budget, etc.

[1630] process

[1631] Format and validate profile data.

[1632] The formatted data is sent to the server via the network.

[1633] output

[1634] User profile information sent to the server

[1635] Step 2:

[1636] Generating a personality profile

[1637] Specific actions

[1638] The server receives the user profile information sent from the terminal.

[1639] input

[1640] User Profile Information

[1641] process

[1642] Analyzes the profile and stores it in the database.

[1643] Generate a personality profile for the user.

[1644] output

[1645] Personality profiles stored in a database

[1646] Step 3:

[1647] Dialogue between expert knowledge AI and personality AI begins

[1648] Specific actions

[1649] The server sends the generated personality profile to the fashion assistant AI.

[1650] input

[1651] Personality Profile

[1652] process

[1653] This involves generating fashion style suggestions using fashion assistant AI.

[1654] It takes into account fashion trend data as well as the user's body type, preferred colors, style, and budget.

[1655] output

[1656] Fashion style suggestions generated by fashion assistant AI

[1657] Style suggestions sent to the server

[1658] Step 4:

[1659] Personality AI feedback

[1660] Specific actions

[1661] The server sends the suggestions received from the fashion assistant AI to the personality AI.

[1662] input

[1663] Fashion style suggestions

[1664] process

[1665] Personality AI evaluates and optimizes suggestions based on past selection history and feedback information.

[1666] output

[1667] Optimized fashion style suggestions

[1668] Optimization suggestions sent to the server

[1669] Step 5:

[1670] Emotion recognition by emotion engine

[1671] Specific actions

[1672] The device uses a camera and microphone to analyze the user's emotions.

[1673] input

[1674] User's facial expression and voice data

[1675] process

[1676] Facial expressions and voice are analyzed using an emotion engine to extract emotional information.

[1677] Emotion information is sent to the server.

[1678] output

[1679] Emotional information sent to the server

[1680] Step 6:

[1681] Recalibrating sentiment-based recommendations

[1682] Specific actions

[1683] The server transmits the emotion information received from the emotion engine to the personality AI and fashion assistant AI.

[1684] input

[1685] emotional information

[1686] process

[1687] Based on emotional information, the personality AI and fashion assistant AI will reevaluate and readjust.

[1688] output

[1689] Re-adjusted fashion style suggestions

[1690] The server sends the retuned proposal to the device.

[1691] Step 7:

[1692] Search and display specific clothing items

[1693] Specific actions

[1694] The server then searches online stores and databases for specific clothing items based on the reworked suggestions.

[1695] input

[1696] Re-adjusted fashion style suggestions

[1697] process

[1698] Performing online store and database searches and retrieving results

[1699] output

[1700] Clothing item search results

[1701] Display search results on your device and provide a purchase link

[1702] Step 8:

[1703] Purchase procedure

[1704] Specific actions

[1705] The user clicks on the purchase link displayed on the terminal.

[1706] input

[1707] Click on the purchase link (selection)

[1708] process

[1709] The device will open the purchase page of the relevant online shop.

[1710] output

[1711] The online shop purchase page will be displayed.

[1712] These are the specific processing steps. In this way, the user is presented with the most suitable fashion style based on their own feelings and feedback, and can purchase specific clothes on the spot.

[1713] (Application example 2)

[1714] 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."

[1715] Conventional fashion suggestion systems can suggest styles based on static information such as a user's preferences and body type, but they cannot adjust the suggestions to take into account the user's emotional state. As a result, they are unable to make suggestions that match the user's mood at any given time, resulting in lower suggestion accuracy and lower satisfaction. Furthermore, they lack the ability to provide real-time fashion suggestions and reflect recognition results in the virtual space, resulting in a poor user experience.

[1716] 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.

[1717] In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize the fashion style suggestions based on the user's past selection history and feedback, means for recognizing the user's emotions using an emotion recognition engine and reevaluating and optimizing the fashion style suggestions based on the emotion information, and means for displaying the emotion-updated fashion style suggestions in a virtual space using a head-mounted display, thereby enabling more personalized fashion style suggestions that reflect the user's emotional state in real time.

[1718] "User profile information" is information about personal attributes such as the user's body type, favorite colors, style, and budget.

[1719] "Fashion assistant AI with specialized knowledge" is an artificial intelligence used to generate fashion style suggestions based on a user's profile information.

[1720] "Fashion style suggestions" refer to styles and coordinations suggested based on the user's personal attributes and preferences.

[1721] The "user's past selection history" is a record of the styles selected and items purchased by the user.

[1722] "Personality AI" is an artificial intelligence that optimizes fashion style suggestions based on the user's past selection history and feedback.

[1723] An "emotion recognition engine" is a technology or software that analyzes a user's facial expressions and voice to recognize their emotions.

[1724] "Emotion information" is data relating to the user's emotional state obtained by an emotion recognition engine.

[1725] "Reevaluate and optimize" means reviewing existing fashion style suggestions based on emotional information and readjusting them to the optimal suggestions for the user.

[1726] A "head-mounted display" is a display device that provides visual information when worn by a user.

[1727] "Virtual space" refers to a virtual 3D environment displayed using a head-mounted display.

[1728] The system for implementing this invention combines a multi-step process including inputting user profile information, generating and optimizing fashion style suggestions, emotion recognition, displaying suggestions in a virtual space, searching for clothing items from online stores, and providing links to purchase them. The specific configuration and operation of the system are described below.

[1729] Hardware and Software

[1730] Hardware:

[1731] Head-mounted displays (e.g., Oculus Rift, Valve Index, HTC Vive)

[1732] Camera and microphone (for emotion recognition)

[1733] software:

[1734] Unity3D (Building a virtual space)

[1735] Azure Cognitive Services (emotion recognition)

[1736] Amazon Web Services (AWS) (data management and processing)

[1737] OpenAI API (fashion suggestion generation)

[1738] Zalando API (clothing data acquisition)

[1739] Program processing explanation

[1740] 1. Initial Setup and User Registration

[1741] Users wear a head-mounted display (HMD) and input their profile information (body type, favorite colors, style, budget, etc.) This information is sent to the AWS server via Azure's API, and the user's profile is stored in a database.

[1742] 2. Dialogue between Expertise AI and Personality AI begins

[1743] The AWS server receives the saved user profile information and requests fashion style suggestions from the OpenAI API, which generates multiple fashion style suggestions based on the trend data and user information.

[1744] 3. Feedback from personality AI

[1745] The AWS server receives the generated fashion style suggestions, which are then evaluated and optimized by the personality AI based on past selection history and feedback. The optimized suggestions are then displayed on the HMD.

[1746] 4. Emotion recognition using an emotion recognition engine

[1747] Using the camera and microphone of the HMD worn by the user, the Azure Cognitive Services emotion analysis API analyzes the user's facial expressions and voice to recognize their emotional state. Emotional information is then sent to the AWS server.

[1748] 5. Recalibrate your emotional recommendations

[1749] Based on the received emotion information, the AWS server requests the OpenAI API to generate and re-evaluate fashion suggestions based on the emotion. The re-adjusted suggestions are then displayed on the HMD.

[1750] 6. Search and display specific clothing items

[1751] The AWS server then uses the Zalando API to search for specific clothing items based on the final tailored fashion style suggestions. The search results are displayed on the HMD, and users can purchase the clothing online via a purchase link.

[1752] Examples and prompts

[1753] Specific examples

[1754] Example 1: User A's scenario, who prefers casual style

[1755] 1. User A enters their body type (normal), preferred colors (red, black), style (formal), and budget (under 10,000 yen), and the information is sent to the AWS server.

[1756] 2. Based on this information, the OpenAI API generates fashion style suggestions.

[1757] 3. Personality AI takes into account past selection history and optimizes suggestions.

[1758] 4. Azure Cognitive Services analyzes the user's emotions from their facial expressions and voice and sends the information to the AWS server.

[1759] 5. Based on the emotion information, the OpenAI API readjusts the fashion suggestions and displays them again on the HMD.

[1760] 6. User A searches for a specific clothing item using the Zalando API and purchases the clothing from the purchase link displayed on the HMD.

[1761] Prompt Sentence Examples

[1762] User Profile:

[1763] Body type: Normal body type

[1764] Favorite colors: Red, black

[1765] Style: Formal

[1766] Budget: Under 10,000 yen

[1767] Emotion information:

[1768] Expression: Relaxed

[1769] Voice analysis: peace of mind

[1770] Suggest a suitable formal fashion style for this user.

[1771] This system can provide more accurate fashion style suggestions that reflect the user's emotional state in real time. In addition, the suggestions change reactively in the virtual space, allowing users to choose the optimal fashion that best suits their emotions.

[1772] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1773] Step 1:

[1774] Users wear a head-mounted display (HMD) and enter their profile information (body type, favorite colors, style, budget, etc.) The entered information is sent to the AWS server via Azure's API.

[1775] Input: User profile information

[1776] Output: User profile information stored in the database

[1777] Action: Displays the profile form and submits the entered data.

[1778] Step 2:

[1779] The AWS server receives the stored user profile information and requests fashion style suggestions from the OpenAI API, which generates multiple fashion style suggestions based on the trend data and user information.

[1780] Input: User profile information, trend data

[1781] Output: Generated fashion style suggestions

[1782] What it does: Sends API requests and receives proposal data

[1783] Step 3:

[1784] The AWS server receives the generated fashion style suggestions, which are then evaluated by the personality AI based on past selection history and feedback, and optimized as needed. The optimized suggestions are then displayed on the HMD.

[1785] Input: Fashion style suggestions, past selection history, feedback information

[1786] Output: Optimized fashion style suggestions

[1787] Operation: Evaluate and optimize proposed data, display on HMD

[1788] Step 4:

[1789] Using the HMD's camera and microphone, the Azure Cognitive Services emotion analysis API analyzes the user's facial expressions and voice to recognize their emotional state, and the emotion information is sent to an AWS server.

[1790] Input: User's facial expression data, voice data

[1791] Output: Recognized emotion information

[1792] Operation: Camera and microphone data acquisition, emotion analysis, and emotion data transmission

[1793] Step 5:

[1794] Based on the received emotion information, the AWS server requests fashion suggestions from the OpenAI API again, generates and re-evaluates fashion style suggestions according to the emotion, and displays the re-adjusted suggestions on the HMD.

[1795] Input: Emotional information, initial fashion style suggestions

[1796] Output: Reworked fashion style suggestions

[1797] Action: Evaluate and readjust the emotional information, and display it again on the HMD

[1798] Step 6:

[1799] The AWS server then uses the Zalando API to search for specific clothing items based on the final tailored fashion style suggestions. The search results are displayed on the HMD, and users can purchase the clothing online via a purchase link.

[1800] Input: Reworked fashion style suggestions

[1801] Output: Searched clothing items and purchase links

[1802] Operation: Searching for clothing data, generating and displaying purchase links

[1803] 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.

[1804] 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.

[1805] 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.

[1806] [Fourth embodiment]

[1807] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1808] 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.

[1809] 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).

[1810] 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.

[1811] 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.

[1812] 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).

[1813] 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.

[1814] 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.

[1815] 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.

[1816] 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.

[1817] 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.

[1818] 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.

[1819] 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."

[1820] This invention relates to a system that helps users find clothes that suit them. Based on user profile information, a fashion assistant AI and a personality AI work together to suggest the optimal fashion style, and then search online stores for specific clothes that match that style and provide them.

[1821] Program processing explanation

[1822] 1. Initial Setup and User Registration

[1823] The terminal displays a profile input form to the user, who then inputs profile information such as his or her body type, favorite colors, style, budget, etc. The terminal then transmits this information to the server.

[1824] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[1825] 2. Dialogue between Expertise AI and Personality AI begins

[1826] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[1827] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[1828] 3. Feedback from personality AI

[1829] The server sends the fashion style suggestions received from the expert knowledge AI to the personality AI, which evaluates the suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[1830] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[1831] 4. User feedback and refinement

[1832] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[1833] The server receives the user's feedback and again requests optimization from the fashion assistant AI and personality AI.

[1834] 5. Search and display specific clothing items

[1835] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[1836] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[1837] Specific examples

[1838] Example 1: User A's scenario, who prefers casual style

[1839] 1. Initial Setup and User Registration

[1840] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[1841] The server generates a personality profile based on user A's information and stores it in a database.

[1842] 2. Dialogue between Expertise AI and Personality AI begins

[1843] The server sends User A's profile to the expert knowledge AI and requests casual style fashion suggestions.

[1844] The AI ​​expertise generates casual suggestions for shirts and jeans in blue and green tones.

[1845] 3. Feedback from personality AI

[1846] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[1847] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[1848] The server sends the proposal to the terminal and displays it to User A.

[1849] 4. User feedback and refinement

[1850] User A provides feedback that he would like more variation in the proposals.

[1851] The terminal sends this feedback to the server, which then requests optimization again.

[1852] 5. Search and display specific clothing items

[1853] The server searches for specific clothes from online stores based on the optimized suggestions.

[1854] The device displays multiple search results to User A and provides a purchase link for each item. When User A clicks a link, the device opens a purchase page.

[1855] In this way, users can efficiently find the clothes that best suit them and smoothly proceed to purchasing. The system combines the user's preferences with the latest fashion information to help them select the best clothes.

[1856] The processing flow will be explained below.

[1857] Step 1:

[1858] The terminal displays a profile entry form to the user, in which the user enters profile information such as their body type, favorite colors, style, and budget.

[1859] Step 2:

[1860] The terminal transmits the entered profile information to the server.

[1861] Step 3:

[1862] The server generates a personality profile for the user based on the received profile information, which is then stored in a database.

[1863] Step 4:

[1864] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[1865] Step 5:

[1866] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[1867] Step 6:

[1868] The server sends the fashion style suggestions received from the specialized knowledge AI to the personality AI.

[1869] Step 7:

[1870] The Personality AI evaluates these suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[1871] Step 8:

[1872] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[1873] Step 9:

[1874] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[1875] Step 10:

[1876] The server receives the user's feedback and again requests optimization from the fashion assistant AI and personality AI.

[1877] Step 11:

[1878] A new optimized fashion style suggestion is generated, which the server sends back to the terminal and displays to the user.

[1879] Step 12:

[1880] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[1881] Step 13:

[1882] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[1883] Example 1

[1884] 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."

[1885] Conventional fashion suggestion systems often fail to fully consider the individual needs and styles of users, resulting in uniform suggestions. Furthermore, they fail to properly utilize the user's past behavioral data and feedback, resulting in low suggestion accuracy. Furthermore, there is also the problem of it taking a long time to search for specific clothing and provide it to the user. This prevents users from efficiently finding the perfect outfit for them, resulting in low satisfaction.

[1886] 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.

[1887] In this invention, the server includes means for inputting user profile information, means for causing an artificial intelligence with specialized knowledge to generate fashion style suggestions based on the user profile information, means for using an artificial intelligence with personality analysis to optimize the fashion style suggestions based on the user's past selection history and feedback, means for providing the optimized fashion style suggestions to the user, means for searching for specific clothing from a database based on the fashion style suggestions, and means for displaying the search results to the user and providing a purchase link. This allows the server to provide fashion suggestions quickly and accurately, fully meeting the user's individual needs and preferences, and enabling the user to efficiently find the clothes that best suit them.

[1888] "User" refers to an individual who utilizes the system to provide fashion suggestions or search for specific clothing items.

[1889] "Profile Information" refers to data about a user, such as body type, preferred colors, style, budget, etc., that is used to understand the user's preferences and characteristics.

[1890] "Artificial intelligence with specialized knowledge" refers to artificial intelligence that has extensive knowledge and trend data about fashion and is capable of generating fashion style suggestions based on a user's profile information.

[1891] "Personality analysis artificial intelligence" refers to artificial intelligence that evaluates and optimizes fashion style suggestions based on the user's past selection history and feedback information.

[1892] "Optimization" refers to adjusting fashion style suggestions to match a user's preferences based on the user's feedback and past selection history.

[1893] "Database" refers to a repository of information that the system uses to suggest fashion styles and search for specific clothing.

[1894] "Search results" refers to specific clothing information retrieved from databases and online stores and displayed to the user as a list.

[1895] "Buy Link" means a hyperlink that a User can click to directly access the purchase page of the applicable online store to purchase a particular garment.

[1896] MODE FOR CARRYING OUT THE INVENTION

[1897] This invention relates to a system that helps users find clothes that suit them. Based on user profile information, an artificial intelligence with specialized knowledge (hereinafter referred to as "fashion assistant AI") and a personality analysis artificial intelligence (hereinafter referred to as "personality AI") work together to suggest the optimal fashion style, and then searches a database or other source for specific clothes that match that style and provides them.

[1898] 1. Initial Setup and User Registration

[1899] The device displays a profile entry form to the user. This form is often created using HTML and JavaScript. The user enters profile information such as their body type (e.g., slim, curvy), favorite colors (e.g., blue, green), style (e.g., casual, formal), and budget (e.g., under 5,000 yen). The device then sends this information to the server using JavaScript or JSON.

[1900] The server analyzes the received user profile information and stores each item in its own table in the database. Based on this information, a personality profile of the user is generated and stored in the database.

[1901] 2. Fashion Style Proposal Generation

[1902] The server reads the user's personality profile and sends it to the fashion assistant AI, using a prompt such as "Please generate fashion style suggestions based on the profile of user ID 123."

[1903] The fashion assistant AI generates multiple fashion style suggestions based on fashion trend data, the user's body type, preferred colors, style, budget, etc. For example, it suggests a specific style such as "a blue shirt and green jeans."

[1904] 3. Optimization with personality AI

[1905] The server sends the fashion style suggestions received from the fashion assistant AI to the personality AI, along with a prompt message saying, "Please evaluate and optimize this suggestion based on user ID 123's past selection history and feedback."

[1906] The Personality AI evaluates the suggestions based on the user's past selection history and feedback information, and makes adjustments as necessary. For example, this adjustment may include "Since the user previously mainly selected blue, we will strengthen blue-based suggestions."

[1907] The server receives the optimized proposal and sends it to the terminal for display to the user.

[1908] 4. User feedback and refinement

[1909] The user can check the optimized fashion style suggestions displayed on the device and enter feedback, such as "I want more casual items" or "I'm willing to spend a little more."

[1910] The terminal obtains this feedback and sends it to the server.

[1911] The server analyzes the user's feedback and again requests optimization from the fashion assistant AI and personality AI. For example, it generates a specific prompt such as, "User ID 123 wants more casual items, and the budget can be increased to 7,000 yen."

[1912] 5. Search and display specific clothing items

[1913] The server searches for specific clothing items from online stores or internal databases based on the final proposed fashion style, and retrieves matching items from online stores using a RESTful API.

[1914] The device displays the search results to the user. Each clothing item is provided with a purchase link. For example, an image of a blue shirt is displayed with a "Buy here" link.

[1915] When a user clicks on a purchase link, the device opens the linked purchase page, allowing the user to smoothly proceed with the purchase process.

[1916] Prompt Sentence Examples

[1917] "Based on the profile information entered by User A, who is in his 20s and likes casual style, please generate fashion suggestions based on blue and green. The budget is under 5,000 yen."

[1918] "Please increase the variety of casual styles based on user feedback and re-propose them."

[1919] In this way, the system effectively utilizes multiple AI technologies to provide optimal fashion suggestions tailored to the user's needs, allowing the user to efficiently find clothes that suit them and facilitating the purchasing process.

[1920] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1921] Step 1: Initial Setup and User Registration

[1922] The device presents the user with a profile entry form, written in HTML and with interactive elements added using JavaScript, in which the user enters information such as body type, preferred colors, style, and budget.

[1923] Input: Profile information entered by the user (e.g., body type is slim, favorite colors are blue and green, style is casual, budget is under 5,000 yen).

[1924] The terminal uses JavaScript to format the input data in JSON format and send it to the server.

[1925] The server parses the received JSON data, extracts each item individually, and stores it in a table in the database.

[1926] Data processing: Parse the JSON data and save it as user profile information.

[1927] Output: User profile information stored in a database.

[1928] Step 2: Generate fashion style suggestions

[1929] The server reads the stored user profile information and sends it to the Fashion Assistant AI for use in the next stage.

[1930] Input: User profile information retrieved from the database.

[1931] The server sends a prompt to the fashion assistant AI saying, "Please generate fashion style suggestions based on the profile of user ID 123."

[1932] The fashion assistant AI analyzes user profile information based on a trend database and generates multiple fashion style suggestions.

[1933] Data calculation: Calculate and generate fashion styles using trend data and user profile information.

[1934] Output: Generated fashion style suggestions (e.g., blue shirt and green jeans).

[1935] Step 3: Optimization with personality AI

[1936] The server sends the style suggestions received from the fashion assistant AI to the personality AI.

[1937] Input: Generated fashion style suggestions.

[1938] The server sends a prompt to the personality AI saying, "Please evaluate and optimize this suggestion based on user ID 123's past selection history and feedback."

[1939] Personality AI analyzes the user's past selection history and feedback to evaluate and optimize fashion style suggestions.

[1940] Data calculation: Evaluate and optimize proposals based on user history and feedback.

[1941] Output: Optimized fashion style suggestions.

[1942] Step 4: User feedback and refinement

[1943] The terminal displays the optimized fashion style suggestions to the user.

[1944] The user enters feedback about the suggestion (e.g., I'd like more casual items).

[1945] Input: User feedback.

[1946] The terminal takes this feedback and sends it back to the server.

[1947] The server analyzes the feedback and, if necessary, re-optimizes using the fashion assistant AI and personality AI.

[1948] Data calculation: Analyze feedback and re-adjust / optimize suggestions.

[1949] Output: Re-optimized fashion style suggestions.

[1950] Step 5: Search and view specific clothing items

[1951] The server searches for specific clothes from online stores and databases based on the fully optimized fashion style, and communicates with the online stores using APIs.

[1952] Input: optimized fashion style suggestions.

[1953] Data calculations: Search online stores and internal databases based on suggestions.

[1954] Output: Specific clothing items as search results.

[1955] The terminal displays the search results to the user and provides a purchase link corresponding to each item.

[1956] When a user clicks on a purchase link, the device opens the linked purchase page, allowing the user to access the purchase page directly.

[1957] (Application example 1)

[1958] 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."

[1959] Today's consumers spend a lot of time and effort finding the perfect fashion style. Finding clothes that suit them efficiently can be challenging, especially when shopping in brick-and-mortar stores. Real-time advice and augmented reality suggestions would enhance the consumer experience, but current systems struggle to achieve this. A new system is needed to address these challenges.

[1960] 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.

[1961] In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize the fashion style suggestions based on the user's past selection history and feedback, means for providing the optimized fashion style suggestions to the user, means for searching for specific clothes from an online store or database based on the fashion style suggestions, means for displaying the search results to the user and providing a purchase link, means for suggesting clothes to be worn by the user in a physical store in real time, and means for displaying the suggested information in augmented reality in real time in the physical store. This allows users to efficiently find the best clothes for them in a physical store, and significantly improves the consumer experience through real-time suggestions and augmented reality displays.

[1962] 1. "Means for inputting user profile information" refers to an interface for inputting and collecting personal information such as the user's body type, preferred colors, style, budget, etc.

[1963] 2. "Fashion assistant AI with specialized knowledge" is an artificial intelligence that uses fashion trend data and knowledge to refer to a user's profile information and suggest the most suitable fashion style.

[1964] 3. "Means using personality AI" refers to means that use artificial intelligence to analyze a user's past selection history and feedback information and optimize fashion style suggestions based on that information.

[1965] 4. "Means for providing the user with the above-mentioned optimized fashion style suggestions" refers to an interface that displays and provides the user with fashion style suggestions optimized by personality AI.

[1966] 5. "Means for searching for specific clothing from online stores or databases" refers to means for searching for specific clothing that corresponds to optimal fashion style suggestions using online stores or internal databases.

[1967] 6. "Means for displaying search results to users and providing purchase links" refers to an interface that displays information about clothing searched from online stores and databases to users and provides purchase links for those items.

[1968] 7. "Means for suggesting clothes to be worn by users in real time in a physical store" is a system that suggests the most suitable clothes to users in real time on the spot while they are shopping in a physical store.

[1969] 8. "Means for displaying suggested information in real time using augmented reality within a physical store" refers to a system that uses augmented reality technology to visually display suggested item information in real time when a user checks out a product in a physical store.

[1970] This invention provides an application system for smartphones or smart glasses that allows users to efficiently find the best clothes for themselves in a physical store. This system supports clothing selection in a physical store by linking a fashion assistant AI and a personality AI based on user profile information.

[1971] System configuration

[1972] Hardware:

[1973] Device: Smartphone or smart glasses

[1974] Server: For information processing and data storage

[1975] Network infrastructure: Internet connectivity to send and receive data

[1976] software:

[1977] Fashion Assistant AI: Artificial intelligence that suggests fashion styles based on user profile information

[1978] Personality AI: Artificial intelligence that optimizes fashion style suggestions based on the user's past selection history and feedback information

[1979] Augmented reality (AR) technology: AR software (e.g., Apple's ARKit) that displays recommendations in real time within a physical store.

[1980] System Operation

[1981] 1. Initial setup and user registration:

[1982] First, the terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, budget, etc. This information is sent to the server.

[1983] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[1984] 2. Fashion proposal generation:

[1985] The server requests the fashion assistant AI to generate fashion style suggestions based on the user's personality profile.

[1986] The fashion assistant AI generates multiple suggestions based on current fashion trends, the user's body type, preferred colors, style, and budget.

[1987] 3. Optimize your offers:

[1988] The server sends the generated fashion style suggestions to the personality AI, which optimizes the suggestions based on the user's past selection history and feedback.

[1989] The Personality AI evaluates the suggestions and makes modifications or optimizations as necessary, and the optimized suggestions are sent to the device and displayed to the user.

[1990] 4. Real-time in-store recommendations:

[1991] When a user is shopping in a physical store and looks at products displayed through the smart glasses, the fashion assistant AI and personality AI provide optimized recommendations in real time via AR display.

[1992] 5. Gather feedback and readjust:

[1993] The user enters feedback about the proposed style, and the terminal sends this to the server.

[1994] Based on the feedback, the server again requests optimization from the fashion assistant AI and personality AI.

[1995] 6. Search and view specific clothing:

[1996] The server searches for specific clothing items from online stores and databases based on the optimized fashion style suggestions.

[1997] The terminal displays the search results to the user and provides a purchase link for each clothing item.

[1998] Specific examples

[1999] Example 1: User A's scenario, who prefers casual style

[2000] 1. Initial setup and user registration:

[2001] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[2002] The server generates a personality profile based on user A's information and stores it in a database.

[2003] 2. Fashion proposal generation:

[2004] The server generates casual style fashion suggestions based on the profile of user A.

[2005] The fashion assistant AI suggests casual shirts and jeans in blue and green tones.

[2006] 3. Optimize your offers:

[2007] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[2008] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[2009] The server sends the proposal to the terminal and displays it to User A.

[2010] 4. Real-time in-store recommendations:

[2011] User A uses smart glasses in a physical store to select clothes and check real-time suggested information about potential purchases displayed in AR.

[2012] Example prompt for a generative AI model:

[2013] "Please suggest the best fashion style for the user based on their body type, preferred colors, style, and budget. This suggestion is for a user who prefers casual styles."

[2014] "Optimize your suggestions by taking into account past selection history and feedback information."

[2015] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2016] Step 1:

[2017] Initial Setup and User Registration

[2018] The terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, budget, etc. This information is sent from the terminal to the server.

[2019] Input: Profile information such as user's body type, favorite colors, style, budget, etc.

[2020] Processing: The device collects user input information and sends it to the server, which receives the information and generates a personality profile.

[2021] Output: Personality profile stored in a database

[2022] Step 2:

[2023] Fashion proposal generation

[2024] The server requests the fashion assistant AI to generate fashion style suggestions based on the user's personality profile.

[2025] Enter: personality profile

[2026] Processing: Fashion assistant AI generates multiple fashion style suggestions taking into account fashion trend data, body type, preferred colors, style, and budget.

[2027] Output: Multiple fashion style suggestions

[2028] Step 3:

[2029] Recommendation optimization

[2030] The server sends the generated fashion style suggestions to the personality AI, which optimizes the suggestions based on the user's past selection history and feedback.

[2031] Input: Fashion style suggestions, past selection history, feedback information

[2032] Processing: Personality AI evaluates the suggestions and makes corrections and optimizations as needed.

[2033] Output: Optimized fashion style suggestions

[2034] Step 4:

[2035] Providing optimized proposals

[2036] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[2037] Input: Optimized fashion style suggestions

[2038] Processing: The server sends the proposal to the terminal, which displays it to the user.

[2039] Output: Optimized fashion style suggestions displayed to the user

[2040] Step 5:

[2041] Real-time proposals in physical stores

[2042] When a user looks at a product through the smart glasses in a physical store, the information is sent to the server, and suggested information optimized by the fashion assistant AI and personality AI is displayed in real time using AR.

[2043] Input: Product information in physical stores, user location information

[2044] Processing: The Fashion Assistant AI and Personality AI generate real-time suggestions based on the captured information and display them on the user's smart glasses using AR technology.

[2045] Output: Real-time suggested information displayed on smart glasses

[2046] Step 6:

[2047] Gather feedback and refine

[2048] The user enters feedback about the proposed style, and the terminal sends this to the server.

[2049] Input: User feedback

[2050] Processing: Based on the feedback, the server again requests optimization from the fashion assistant AI and personality AI, generating new suggestions.

[2051] Output: Updated fashion style suggestions

[2052] Step 7:

[2053] Search and display specific clothing items

[2054] The server searches for specific clothing items from online stores and databases based on optimized fashion style suggestions and displays them on the device.

[2055] Input: Optimized fashion style suggestions

[2056] Processing: The server searches online stores and databases, collects the appropriate item information, and sends it to the device.

[2057] Output: Specific clothing item displayed on device with a link to purchase

[2058] 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.

[2059] This invention relates to a system that proposes a fashion style suitable for a user and searches for and provides specific clothes that match that style from online stores, etc. This invention is characterized by the combination of a feeling engine that recognizes the user's feelings and adjusts the proposed fashion style based on the user's feelings.

[2060] Program processing explanation

[2061] 1. Initial Setup and User Registration

[2062] The terminal displays a profile input form to the user, who then inputs profile information such as his or her body type, favorite colors, style, budget, etc. The terminal then transmits this information to the server.

[2063] The server generates a personality profile for the user based on the received user profile information and stores it in a database.

[2064] 2. Dialogue between Expertise AI and Personality AI begins

[2065] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[2066] The expert knowledge AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[2067] 3. Feedback from personality AI

[2068] The server sends the fashion style suggestions received from the expert knowledge AI to the personality AI, which evaluates the suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[2069] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[2070] 4. Emotion Recognition by Emotion Engine

[2071] The device uses a camera to analyze the user's facial expressions and recognize their emotions, or uses voice relative analysis to determine the user's emotions.

[2072] The terminal transmits the recognized emotion information to the server.

[2073] 5. Recalibrate your emotional offers

[2074] The server receives emotional information from the emotion engine and instructs the personality AI and fashion assistant AI to readjust.

[2075] The Personality AI and Fashion Assistant AI will reassess fashion style suggestions based on the user's emotions and revise the suggestions as needed.

[2076] The server sends the retuned proposal to the terminal and displays it to the user.

[2077] 6. Search and display specific clothing items

[2078] The server then searches for specific clothing items from online stores and databases based on the final proposed fashion style.

[2079] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks a purchase link, the device opens the purchase page of the linked item.

[2080] Specific examples

[2081] Example 1: User A's scenario, who prefers casual style

[2082] 1. Initial Setup and User Registration

[2083] User A inputs his / her body type (slim), favorite colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and transmits the information to the server.

[2084] The server generates a personality profile based on user A's information and stores it in a database.

[2085] 2. Dialogue between Expertise AI and Personality AI begins

[2086] The server sends User A's profile to the expert knowledge AI and requests casual style fashion suggestions.

[2087] The AI ​​expertise generates casual suggestions for shirts and jeans in blue and green tones.

[2088] 3. Feedback from personality AI

[2089] The server sends these suggestions to a personality AI that optimizes them based on the user's past choices.

[2090] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[2091] The server sends the proposal to the terminal and displays it to User A.

[2092] 4. Emotion Recognition by Emotion Engine

[2093] User A uses the facial expression analysis function, and the device analyzes the emotion and sends it to the server.

[2094] The server receives the emotion information and determines that the emotion is relaxed.

[2095] 5. Recalibrate your emotional offers

[2096] The server instructs the personality AI and expertise AI to readjust based on the relaxed emotion.

[2097] Expertise AI and personality AI reevaluate casual styles that emphasize a relaxed feel and generate optimal suggestions.

[2098] The server sends this re-adjusted proposal to the terminal and re-displays it to User A.

[2099] 6. Search and display specific clothing items

[2100] The server searches online stores for specific clothing items based on the re-tailored suggestions.

[2101] The device displays multiple search results to User A and provides a purchase link for each item. When User A clicks a link, the device opens the purchase page.

[2102] In this way, User A can find the perfect outfit to match his / her emotions and easily proceed to the purchasing process. This system provides a more personalized fashion selection experience by making suggestions that take into account the user's preferences and emotions.

[2103] The processing flow will be explained below.

[2104] Step 1:

[2105] The terminal displays a profile input form to the user, and the user inputs profile information such as their body type, favorite colors, style, and budget.

[2106] Step 2:

[2107] The terminal transmits the entered profile information to the server.

[2108] Step 3:

[2109] The server generates a personality profile for the user based on the received profile information and stores this information in a database.

[2110] Step 4:

[2111] The server sends the user's personality profile to a fashion assistant AI with specialized knowledge and requests it to generate fashion style suggestions that suit the user.

[2112] Step 5:

[2113] The specialized knowledge AI takes into account fashion trend data, the user's body type, preferred colors, style, budget, etc. to generate multiple fashion style suggestions.

[2114] Step 6:

[2115] The server sends the fashion style suggestions received from the specialized knowledge AI to the personality AI.

[2116] Step 7:

[2117] Personality AI evaluates suggestions based on the user's past selection history and feedback information, and makes corrections and optimizations as necessary.

[2118] Step 8:

[2119] The server sends the optimized fashion style suggestions to the terminal and displays them to the user.

[2120] Step 9:

[2121] The device sends the facial expressions captured by the user with a camera and recorded voice data to an emotion engine, which analyzes the emotions.

[2122] Step 10:

[2123] The emotion engine analyzes the user's facial expressions and voice data to recognize their emotions. The recognized emotion information is sent to the server via the device.

[2124] Step 11:

[2125] Based on the received emotional information, the server instructs the emotion engine, personality AI, and expertise AI to readjust.

[2126] Step 12:

[2127] Personality AI and expertise AI take into account the user's emotional information to generate new fashion style suggestions.

[2128] Step 13:

[2129] The server sends the re-adjusted fashion style suggestions to the terminal and displays them again to the user.

[2130] Step 14:

[2131] The user inputs feedback about the displayed fashion style suggestions, and the terminal transmits this feedback to the server.

[2132] Step 15:

[2133] The server again receives user feedback and finalizes the final fashion style suggestions.

[2134] Step 16:

[2135] The server then searches for specific clothing items from online stores and internal databases based on the final proposed fashion style.

[2136] Step 17:

[2137] The device displays the search results to the user and provides a purchase link for each clothing item. When the user clicks on the purchase link, the device opens a purchase page.

[2138] This process allows users to find the perfect fashion style based on their own feelings and preferences, and easily proceed to purchase.

[2139] Example 2

[2140] 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."

[2141] Conventional fashion suggestion systems only make suggestions based on a user's profile information and past selection history, and lack the ability to readjust based on the user's recent emotions and feedback. As a result, they are unable to provide optimal fashion suggestions that reflect the user's mental state or temporary emotional changes, and an improvement in the user experience is needed.

[2142] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize fashion style suggestions based on the user's past selection history and feedback, means for recognizing the user's emotions using an emotion engine and transmitting the emotion information to the server, means for reevaluating and readjusting the suggestions based on the user's emotion information, means for searching for specific clothes from online stores and databases, and means for displaying search results to the user and providing a purchase link. This enables personalized fashion suggestions that reflect the user's emotions and feedback in real time.

[2143] "User" refers to an individual who wants to use this system to have a fashion style suggested that suits them.

[2144] "Profile Information" refers to information entered by a user that indicates personal attributes and preferences, such as body type, preferred colors, style, budget, etc.

[2145] "Fashion Assistant AI" refers to artificial intelligence that has expertise in fashion and generates fashion style suggestions based on a user's profile information.

[2146] "Personality AI" refers to artificial intelligence that optimizes fashion style suggestions based on a user's past selection history and feedback information.

[2147] An "emotion engine" refers to a system that recognizes a user's emotions by analyzing their facial expressions and voice.

[2148] "Fashion style suggestions" refers to fashion style suggestions generated by the fashion assistant AI based on the user's profile information.

[2149] An "online store" refers to a website or platform that sells clothing and other products over the Internet.

[2150] "Database" refers to digital data storage for storing and managing information such as user profile information, past selection history, and feedback.

[2151] "Purchase Link" refers to a hyperlink to a web page that allows a user to purchase specific clothing items based on the fashion style suggestions.

[2152] "Re-adjustment" refers to the process of reviewing and modifying existing fashion style suggestions based on the user's emotional information.

[2153] MODE FOR CARRYING OUT THE INVENTION

[2154] This invention relates to a system that proposes a fashion style suitable for a user and searches for and provides specific clothes that match that style from online stores, etc. In particular, it is characterized by combining an emotion engine that recognizes the user's emotions and adjusting the proposed fashion style based on the user's emotions.

[2155] System Configuration

[2156] 1. Terminal

[2157] GUI (Graphical User Interface) for displaying the profile entry form

[2158] Hardware equipped with a camera and microphone to analyze the user's facial expressions and voice to recognize emotions

[2159] A communication module that works with the server to send and receive data

[2160] 2. Server

[2161] A database for receiving user profile information and generating a personality profile.

[2162] Fashion assistant AI and personality AI with specialized knowledge

[2163] A processing module for processing the emotional information received from the emotion engine and readjusting the suggestions.

[2164] A search system for searching specific clothing items from online stores and databases and providing the results to users.

[2165] Program processing explanation

[2166] The program processing of this system will be explained in natural language below.

[2167] 1. Initial Setup and User Registration

[2168] The terminal displays a profile entry form to the user, in which the user enters information such as body type, favorite colors, style, and budget.

[2169] The terminal transmits the entered profile information to the server.

[2170] The server generates a personality profile for the user based on the received profile information and stores it in a database.

[2171] 2. Dialogue between Expertise AI and Personality AI begins

[2172] The server sends the generated personality profile to the fashion assistant AI and asks it to suggest a fashion style that suits the user.

[2173] The fashion assistant AI generates multiple fashion style suggestions by taking into account fashion trend data, the user's body type, preferred colors, style, budget, etc.

[2174] The fashion assistant AI sends the suggestions to the server.

[2175] 3. Feedback from personality AI

[2176] The server sends the suggestions sent by the fashion assistant AI to the personality AI.

[2177] Personality AI analyzes suggestions based on the user's past selection history and feedback, and optimizes them as needed.

[2178] The server sends the optimized proposal to the terminal and displays it to the user.

[2179] 4. Emotion Recognition by Emotion Engine

[2180] The device uses a camera and microphone to analyze the user's facial expressions and voice and recognize their emotions.

[2181] The terminal transmits the recognized emotion information to the server.

[2182] 5. Recalibrate your emotional offers

[2183] The server receives emotional information from the emotion engine and instructs the personality AI and fashion assistant AI to readjust.

[2184] The Personality AI and Fashion Assistant AI will reassess suggestions based on emotional information and make adjustments as needed.

[2185] The server sends the re-adjusted proposal to the terminal and re-displays it to the user.

[2186] 6. Search and display specific clothing items

[2187] The server then searches for specific clothes from online stores and databases based on the final adjusted fashion style.

[2188] The terminal displays the search results to the user and provides a purchase link for each item.

[2189] When the user clicks on the purchase link, the device opens the purchase page of the corresponding online shop.

[2190] Specific examples

[2191] Example 1: User A's scenario, who prefers casual style

[2192] 1. Initial Setup and User Registration

[2193] User A enters his / her body type (slim), preferred colors (blue, green), style (casual), and budget (under 5,000 yen) into the terminal and clicks the send button.

[2194] The terminal transmits this information to the server.

[2195] The server generates a personality profile based on user A's information and stores it in a database.

[2196] 2. Dialogue between Expertise AI and Personality AI begins

[2197] The server sends the generated personality profile to the fashion assistant AI and requests casual style fashion suggestions.

[2198] The fashion assistant AI generates casual suggestions for shirts and jeans in blue and green tones.

[2199] The fashion assistant AI sends the suggestions to the server.

[2200] 3. Feedback from personality AI

[2201] The server sends these suggestions to a personality AI, which optimizes them based on past selection history.

[2202] The personality AI determines that the suggestions match User A's preferences and sends the optimized suggestions to the server.

[2203] The server sends the optimized proposal to the terminal and displays it to User A.

[2204] 4. Emotion Recognition by Emotion Engine

[2205] When User A sees the provided suggestion, the device's camera analyzes his / her facial expressions, which indicate emotions.

[2206] The terminal transmits the analysis results to the server, which determines that User A is relaxed.

[2207] 5. Recalibrate your emotional offers

[2208] The server instructs the personality AI and fashion assistant AI to readjust based on the relaxed emotion.

[2209] Personality AI and fashion assistant AI will reevaluate casual styles that emphasize a relaxed feel and generate optimal suggestions.

[2210] The server sends this re-adjusted proposal to the terminal and re-displays it to User A.

[2211] 6. Search and display specific clothing items

[2212] The server searches online stores for specific clothing items based on the re-tailored suggestions.

[2213] The terminal displays multiple search results to User A and provides a purchase link for each clothing item.

[2214] When User A clicks on the purchase link, the device opens the purchase page of the corresponding online shop.

[2215] Prompt Sentence Examples

[2216] "Based on my profile, please suggest a casual fashion style with blue and green as the main colors. My budget is under 5,000 yen. I would also be happy if the suggested style has a relaxed feel."

[2217] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2218] Step 1:

[2219] Initial Setup and User Registration

[2220] Specific actions

[2221] The terminal displays a profile entry form to the user.

[2222] The user enters profile information such as body type, preferred colors, style, budget, etc., and clicks the submit button.

[2223] input

[2224] Profile information such as your body type, preferred colors, style, budget, etc.

[2225] process

[2226] Format and validate profile data.

[2227] The formatted data is sent to the server via the network.

[2228] output

[2229] User profile information sent to the server

[2230] Step 2:

[2231] Generating a personality profile

[2232] Specific actions

[2233] The server receives the user profile information sent from the terminal.

[2234] input

[2235] User Profile Information

[2236] process

[2237] Analyzes the profile and stores it in the database.

[2238] Generate a personality profile for the user.

[2239] output

[2240] Personality profiles stored in a database

[2241] Step 3:

[2242] Dialogue between expert knowledge AI and personality AI begins

[2243] Specific actions

[2244] The server sends the generated personality profile to the fashion assistant AI.

[2245] input

[2246] Personality Profile

[2247] process

[2248] This involves generating fashion style suggestions using fashion assistant AI.

[2249] It takes into account fashion trend data as well as the user's body type, preferred colors, style, and budget.

[2250] output

[2251] Fashion style suggestions generated by fashion assistant AI

[2252] Style suggestions sent to the server

[2253] Step 4:

[2254] Personality AI feedback

[2255] Specific actions

[2256] The server sends the suggestions received from the fashion assistant AI to the personality AI.

[2257] input

[2258] Fashion style suggestions

[2259] process

[2260] Personality AI evaluates and optimizes suggestions based on past selection history and feedback information.

[2261] output

[2262] Optimized fashion style suggestions

[2263] Optimization suggestions sent to the server

[2264] Step 5:

[2265] Emotion recognition by emotion engine

[2266] Specific actions

[2267] The device uses a camera and microphone to analyze the user's emotions.

[2268] input

[2269] User's facial expression and voice data

[2270] process

[2271] Facial expressions and voice are analyzed using an emotion engine to extract emotional information.

[2272] Emotion information is sent to the server.

[2273] output

[2274] Emotional information sent to the server

[2275] Step 6:

[2276] Recalibrating sentiment-based recommendations

[2277] Specific actions

[2278] The server transmits the emotion information received from the emotion engine to the personality AI and fashion assistant AI.

[2279] input

[2280] emotional information

[2281] process

[2282] Based on emotional information, the personality AI and fashion assistant AI will reevaluate and readjust.

[2283] output

[2284] Re-adjusted fashion style suggestions

[2285] The server sends the retuned proposal to the device.

[2286] Step 7:

[2287] Search and display specific clothing items

[2288] Specific actions

[2289] The server then searches online stores and databases for specific clothing items based on the reworked suggestions.

[2290] input

[2291] Re-adjusted fashion style suggestions

[2292] process

[2293] Performing online store and database searches and retrieving results

[2294] output

[2295] Clothing item search results

[2296] Display search results on your device and provide a purchase link

[2297] Step 8:

[2298] Purchase procedure

[2299] Specific actions

[2300] The user clicks on the purchase link displayed on the terminal.

[2301] input

[2302] Click on the purchase link (selection)

[2303] process

[2304] The device will open the purchase page of the relevant online shop.

[2305] output

[2306] The online shop purchase page will be displayed.

[2307] These are the specific processing steps. In this way, the user is presented with the most suitable fashion style based on their own feelings and feedback, and can purchase specific clothes on the spot.

[2308] (Application example 2)

[2309] 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."

[2310] Conventional fashion suggestion systems can suggest styles based on static information such as a user's preferences and body type, but they cannot adjust the suggestions to take into account the user's emotional state. As a result, they are unable to make suggestions that match the user's mood at any given time, resulting in lower suggestion accuracy and lower satisfaction. Furthermore, they lack the ability to provide real-time fashion suggestions and reflect recognition results in the virtual space, resulting in a poor user experience.

[2311] 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.

[2312] In this invention, the server includes means for inputting user profile information, means for causing a fashion assistant AI with specialized knowledge to generate fashion style suggestions based on the user's profile information, means for using a personality AI to optimize the fashion style suggestions based on the user's past selection history and feedback, means for recognizing the user's emotions using an emotion recognition engine and reevaluating and optimizing the fashion style suggestions based on the emotion information, and means for displaying the emotion-updated fashion style suggestions in a virtual space using a head-mounted display, thereby enabling more personalized fashion style suggestions that reflect the user's emotional state in real time.

[2313] "User profile information" is information about personal attributes such as the user's body type, favorite colors, style, and budget.

[2314] "Fashion assistant AI with specialized knowledge" is an artificial intelligence used to generate fashion style suggestions based on a user's profile information.

[2315] "Fashion style suggestions" refer to styles and coordinations suggested based on the user's personal attributes and preferences.

[2316] The "user's past selection history" is a record of the styles selected and items purchased by the user.

[2317] "Personality AI" is an artificial intelligence that optimizes fashion style suggestions based on the user's past selection history and feedback.

[2318] An "emotion recognition engine" is a technology or software that analyzes a user's facial expressions and voice to recognize their emotions.

[2319] "Emotion information" is data relating to the user's emotional state obtained by an emotion recognition engine.

[2320] "Reevaluate and optimize" means reviewing existing fashion style suggestions based on emotional information and readjusting them to the optimal suggestions for the user.

[2321] A "head-mounted display" is a display device that provides visual information when worn by a user.

[2322] "Virtual space" refers to a virtual 3D environment displayed using a head-mounted display.

[2323] The system for implementing this invention combines a multi-step process including inputting user profile information, generating and optimizing fashion style suggestions, emotion recognition, displaying suggestions in a virtual space, searching for clothing items from online stores, and providing links to purchase them. The specific configuration and operation of the system are described below.

[2324] Hardware and Software

[2325] Hardware:

[2326] Head-mounted displays (e.g., Oculus Rift, Valve Index, HTC Vive)

[2327] Camera and microphone (for emotion recognition)

[2328] software:

[2329] Unity3D (Building a virtual space)

[2330] Azure Cognitive Services (emotion recognition)

[2331] Amazon Web Services (AWS) (data management and processing)

[2332] OpenAI API (fashion suggestion generation)

[2333] Zalando API (clothing data acquisition)

[2334] Program processing explanation

[2335] 1. Initial Setup and User Registration

[2336] Users wear a head-mounted display (HMD) and input their profile information (body type, favorite colors, style, budget, etc.) This information is sent to the AWS server via Azure's API, and the user's profile is stored in a database.

[2337] 2. Dialogue between Expertise AI and Personality AI begins

[2338] The AWS server receives the saved user profile information and requests fashion style suggestions from the OpenAI API, which generates multiple fashion style suggestions based on the trend data and user information.

[2339] 3. Feedback from personality AI

[2340] The AWS server receives the generated fashion style suggestions, which are then evaluated and optimized by the personality AI based on past selection history and feedback. The optimized suggestions are then displayed on the HMD.

[2341] 4. Emotion recognition using an emotion recognition engine

[2342] Using the camera and microphone of the HMD worn by the user, the Azure Cognitive Services emotion analysis API analyzes the user's facial expressions and voice to recognize their emotional state. Emotional information is then sent to the AWS server.

[2343] 5. Recalibrate your emotional recommendations

[2344] Based on the received emotion information, the AWS server requests the OpenAI API to generate and re-evaluate fashion suggestions based on the emotion. The re-adjusted suggestions are then displayed on the HMD.

[2345] 6. Search and display specific clothing items

[2346] The AWS server then uses the Zalando API to search for specific clothing items based on the final tailored fashion style suggestions. The search results are displayed on the HMD, and users can purchase the clothing online via a purchase link.

[2347] Examples and prompts

[2348] Specific examples

[2349] Example 1: User A's scenario, who prefers casual style

[2350] 1. User A enters their body type (normal), preferred colors (red, black), style (formal), and budget (under 10,000 yen), and the information is sent to the AWS server.

[2351] 2. Based on this information, the OpenAI API generates fashion style suggestions.

[2352] 3. Personality AI takes into account past selection history and optimizes suggestions.

[2353] 4. Azure Cognitive Services analyzes the user's emotions from their facial expressions and voice and sends the information to the AWS server.

[2354] 5. Based on the emotion information, the OpenAI API readjusts the fashion suggestions and displays them again on the HMD.

[2355] 6. User A searches for a specific clothing item using the Zalando API and purchases the clothing from the purchase link displayed on the HMD.

[2356] Prompt Sentence Examples

[2357] User Profile:

[2358] Body type: Normal body type

[2359] Favorite colors: Red, black

[2360] Style: Formal

[2361] Budget: Under 10,000 yen

[2362] Emotion information:

[2363] Expression: Relaxed

[2364] Voice analysis: peace of mind

[2365] Suggest a suitable formal fashion style for this user.

[2366] This system can provide more accurate fashion style suggestions that reflect the user's emotional state in real time. In addition, the suggestions change reactively in the virtual space, allowing users to choose the optimal fashion that best suits their emotions.

[2367] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2368] Step 1:

[2369] Users wear a head-mounted display (HMD) and enter their profile information (body type, favorite colors, style, budget, etc.) The entered information is sent to the AWS server via Azure's API.

[2370] Input: User profile information

[2371] Output: User profile information stored in the database

[2372] Action: Displays the profile form and submits the entered data.

[2373] Step 2:

[2374] The AWS server receives the stored user profile information and requests fashion style suggestions from the OpenAI API, which generates multiple fashion style suggestions based on the trend data and user information.

[2375] Input: User profile information, trend data

[2376] Output: Generated fashion style suggestions

[2377] What it does: Sends API requests and receives proposal data

[2378] Step 3:

[2379] The AWS server receives the generated fashion style suggestions, which are then evaluated by the personality AI based on past selection history and feedback, and optimized as needed. The optimized suggestions are then displayed on the HMD.

[2380] Input: Fashion style suggestions, past selection history, feedback information

[2381] Output: Optimized fashion style suggestions

[2382] Operation: Evaluate and optimize proposed data, display on HMD

[2383] Step 4:

[2384] Using the HMD's camera and microphone, the Azure Cognitive Services emotion analysis API analyzes the user's facial expressions and voice to recognize their emotional state, and the emotion information is sent to an AWS server.

[2385] Input: User's facial expression data, voice data

[2386] Output: Recognized emotion information

[2387] Operation: Camera and microphone data acquisition, emotion analysis, and emotion data transmission

[2388] Step 5:

[2389] Based on the received emotion information, the AWS server requests fashion suggestions from the OpenAI API again, generates and re-evaluates fashion style suggestions according to the emotion, and displays the re-adjusted suggestions on the HMD.

[2390] Input: Emotional information, initial fashion style suggestions

[2391] Output: Reworked fashion style suggestions

[2392] Action: Evaluate and readjust the emotional information, and display it again on the HMD

[2393] Step 6:

[2394] The AWS server then uses the Zalando API to search for specific clothing items based on the final tailored fashion style suggestions. The search results are displayed on the HMD, and users can purchase the clothing online via a purchase link.

[2395] Input: Reworked fashion style suggestions

[2396] Output: Searched clothing items and purchase links

[2397] Operation: Searching for clothing data, generating and displaying purchase links

[2398] 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.

[2399] 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.

[2400] 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.

[2401] 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.

[2402] 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.

[2403] 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.

[2404] 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).

[2405] 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.

[2406] 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."

[2407] 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.

[2408] 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).

[2409] 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.

[2410] 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.

[2411] 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.

[2412] 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.

[2413] 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.

[2414] The hardware resource that executes the specific processing may...

Claims

1. means for inputting user profile information; A means for having a fashion assistant AI with specialized knowledge generate fashion style suggestions based on a user's profile information; A means for using personality AI to optimize fashion style suggestions based on a user's past selection history and feedback; means for providing the optimized fashion style suggestions to a user; A means to search for specific clothes from online stores or databases based on the above fashion style suggestions; means for displaying said search results to a user and providing a purchase link; A system including:

2. The system of claim 1 , further comprising means for collecting user feedback and re-optimizing fashion style suggestions based on said feedback.

3. The system of claim 1 , further comprising means for considering fashion trend data when generating said fashion style suggestions.

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