system

Abstract

Provide a system. 【Solution means】Means for receiving an image captured by a user, Means for analyzing the received image and extracting attribute information of clothing, Means for storing the extracted attribute information, Means for the user to input TPO, weather, and style information, Means for proposing an optimal piece of clothing based on the input information and the stored attribute information, Means for displaying the proposed piece of clothing to the user and allowing selection, Means for obtaining data of partnering stores to propose new products, Means for displaying the proposed new products and providing purchase links, A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern busy lives, people often struggle to decide what to wear daily. On the other hand, since clothing selection is greatly influenced by TPO, weather, and personal style, it is difficult to make quick and accurate clothing choices, wasting a lot of time. Also, while people want to make the most of the clothes they have, there may be a demand for proposals of new items. It is desired to provide a system that efficiently and accurately supports clothing selection for users with such problems.

Means for Solving the Problems

[0005] The present invention is a system that includes means for receiving images taken by a user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information and stored attribute information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, and means for displaying the suggested new products and providing purchase links. This allows the user to efficiently utilize the clothes they already own and receive suggestions for new items.

[0006] A "user" refers to an individual who uses the system to choose their own clothing.

[0007] "Image" refers to digital data captured by a user using a webcam or smartphone camera to save visual information about their clothing.

[0008] "Attribute information" refers to the characteristics of clothing, such as color, shape, material, brand, and style, extracted by the AI ​​image analysis module.

[0009] "TPO" is an abbreviation for Time, Place, and Occasion, and refers to the environment and purpose in which clothing is chosen.

[0010] "Weather" refers to the meteorological conditions that users need to consider when choosing their clothing.

[0011] "Style" refers to a user's preferences and fashion trends when selecting clothing.

[0012] "Suggested means" refers to the methods and mechanisms by which the AI ​​styling module generates and presents the most suitable clothing for the user.

[0013] "Partner shops" refer to online stores and physical stores that are integrated with the system to provide users with new fashion items.

[0014] A "database" refers to a storage device within a system used to store and manage attribute information of clothing owned by a user.

[0015] A "purchase link" refers to a URL or interface that allows a user to access the website or application of a partner shop in order to purchase a new item that has been suggested to them. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system that uses a webcam or smartphone app to load images of the user's clothing into AI, and then suggests the most suitable outfit based on the occasion, weather, and style. Furthermore, it also supports the suggestion and purchase of new fashion items.

[0038] The basic configuration of this system includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for saving the extracted attribute information, means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information and saved attribute information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops in order to suggest new products, and means for displaying the suggested new products and providing purchase links.

[0039] Program Processing Description

[0040] 1. System startup and login

[0041] Terminal:

[0042] The user launches the app, enters their username and password on the login screen, and presses the login button.

[0043] server:

[0044] The system receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[0045] 2. Upload images of clothing

[0046] Terminal:

[0047] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[0048] server:

[0049] The system receives image data and sends it to the AI ​​image analysis module.

[0050] 3. Data analysis of clothing

[0051] server:

[0052] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[0053] 4. Entering user information

[0054] Terminal:

[0055] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[0056] server:

[0057] Receives information entered by the user.

[0058] 5. Generating Recommended Clothing

[0059] server:

[0060] The system retrieves data on the user's clothing from a database. Based on the user's input regarding occasion, weather, and style, an AI styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[0061] 6. Display and selection of recommended clothing.

[0062] Terminal:

[0063] The system displays a list of recommended outfit combinations, and users can tap on a suggested outfit to view details. They can then tap on their chosen outfit to complete the confirmation.

[0064] 7. Suggestions from the shop

[0065] server:

[0066] Based on the user's chosen style and past selections, the app generates new suggestions. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[0067] 8. Viewing and purchasing shop suggestions

[0068] Terminal:

[0069] A list of suggested products is displayed, and detailed information (price, brand, reviews, etc.) can be viewed for each product. Selecting a product you wish to purchase and clicking the "Purchase" button will redirect you to the partner shop's website or application.

[0070] Specific example

[0071] Example 1: Uploading images of clothing

[0072] Terminal:

[0073] Launch the app and log in.

[0074] Select "Upload clothing," take a picture of the blue shirt, and upload it.

[0075] server:

[0076] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[0077] Example 2: Generating Recommended Clothing

[0078] Terminal:

[0079] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[0080] server:

[0081] The system retrieves information on a blue shirt, black pants, and white sneakers from a database. An AI styling module then suggests the optimal combination of these items based on the input data. The overall outfit information is then sent to the app.

[0082] Example 3: Shop proposal

[0083] server:

[0084] Based on the user's past choices and casual style, the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[0085] Terminal:

[0086] The suggested product list is displayed, and detailed information can be viewed. Clicking on a product you like will take you to the purchase page. In this way, users can easily combine outfits that suit their style, and new items can be suggested and purchased.

[0087] This system is designed to support users' busy lifestyles and help them use their time efficiently. It encourages users to make the most of their existing clothing while also providing suggestions for new fashion items, allowing them to always enjoy the latest styles.

[0088] The following describes the processing flow.

[0089] Step 1:

[0090] Terminal:

[0091] The user launches the app, enters their username and password on the login screen, and presses the login button.

[0092] server:

[0093] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[0094] Step 2:

[0095] Terminal:

[0096] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[0097] server:

[0098] The server receives the image data and sends it to the AI ​​image analysis module.

[0099] Step 3:

[0100] server:

[0101] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[0102] Step 4:

[0103] Terminal:

[0104] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[0105] server:

[0106] The server receives the information entered by the user.

[0107] Step 5:

[0108] server:

[0109] The server retrieves data on the user's clothing from the database. Based on the user's input regarding occasion, weather, and style, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[0110] Step 6:

[0111] Terminal:

[0112] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[0113] Step 7:

[0114] server:

[0115] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[0116] Step 8:

[0117] Terminal:

[0118] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[0119] (Example 1)

[0120] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0121] Conventional clothing suggestion systems often fail to adequately personalize user outfit combinations and suggest new items, posing a challenge to improving user satisfaction. Furthermore, the lack of automatic generation of optimal outfits based on time, place, occasion, weather, and preferred style meant they could not efficiently support users' busy lifestyles.

[0122] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0123] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images to extract clothing attribute information, and means for storing the extracted attribute information. This allows for detailed storage of information about the user's clothing in a database, enabling analysis based on individual attributes. The invention also includes means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information and stored attribute information, means for displaying the suggested outfits to the user and allowing them to select one, means for generating the most suitable outfit using a generative AI model based on the TPO, weather, and style information entered by the user, and means for suggesting new fashion items based on the user's past choices and style. This enables the suggestion of the most suitable outfit tailored to the user's individual needs and the constant suggestion of new styles, significantly improving user satisfaction.

[0124] A "user" is an individual or group that uses this system.

[0125] "Captured images" refer to image data acquired by the user using the camera function of the system.

[0126] "Means of receiving" refers to the function or device that allows a server to receive data sent by a user.

[0127] "Means of analysis" refers to a function or technology used by a system to analyze received image data and extract specific information.

[0128] "Clothing attribute information" refers to information about the characteristics of clothing, such as color, shape, material, brand, and style.

[0129] "Means of storage" refers to a function or device for storing extracted information in a database or storage device.

[0130] "TPO" is an abbreviation for Time, Place, and Occasion, and it is a set of criteria for determining appropriate attire for a particular situation.

[0131] "Style information" refers to information about the type and design of clothing based on the user's preferences and current trends.

[0132] "Means of suggesting the optimal outfit" refers to a function or technology that presents clothing combinations suitable for a user based on information entered by the user and stored attribute information.

[0133] "Means of displaying and allowing selection" refers to a function or device that visually presents suggested clothing to the user and allows them to make a selection from among them.

[0134] A "partner retailer" is a store or company that collaborates with this system to provide product data and propose new products to users.

[0135] A "generative AI model" refers to an algorithm or technology that uses artificial intelligence to generate the most suitable clothing based on input data.

[0136] "Means of providing a purchase link" refers to a function or technology that displays a link so that a user can access the purchase page of a suggested product.

[0137] "Past choices" refers to clothing and styling information that the user previously selected within the system.

[0138] This invention is a system that uses a webcam or smartphone app to read images of the user's clothing into an AI, and then suggests the most suitable outfit based on the occasion, weather, and style. Furthermore, it also supports the suggestion and purchase of new fashion items.

[0139] System Configuration

[0140] This system includes the following components:

[0141] Means for receiving images of clothing

[0142] A method for analyzing received images and extracting clothing attribute information.

[0143] Means for saving extracted attribute information

[0144] A means for users to input TPO (Time, Place, Occasion), weather, and style information.

[0145] A method for suggesting the most suitable clothing based on input information and stored attribute information.

[0146] A means of displaying suggested clothing to the user and allowing them to select from it.

[0147] Means of acquiring data from partner retailers in order to propose new products.

[0148] A means of displaying proposed new products and providing purchase links.

[0149] A method for generating the optimal outfit using a generative AI model based on user-inputted information regarding time, place, occasion, weather, and style.

[0150] A method for suggesting new fashion items based on the user's past choices and style.

[0151] Program processing flow

[0152] The system program operates in the following sequence:

[0153] 1. System startup and login

[0154] Terminal:

[0155] The user launches the app, enters their username and password on the login screen, and presses the login button.

[0156] server:

[0157] The server receives the username and password, queries the authentication server, and performs authentication. If authentication is successful, it generates a session ID and retrieves user information.

[0158] 2. Upload images of clothing

[0159] Terminal:

[0160] The user selects the "Upload Clothing" option from the menu, activates the camera, takes a picture of the clothing, and taps the "Upload" button.

[0161] server:

[0162] The server receives the image data and sends it to the AI ​​image analysis module.

[0163] 3. Data analysis of clothing

[0164] server:

[0165] The AI ​​image analysis module processes image data and analyzes attributes such as the color, shape, material, brand, and style of the clothing.

[0166] server:

[0167] The analyzed attribute information is saved to the database.

[0168] 4. Entering user information

[0169] Terminal:

[0170] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and taps the "Submit" button.

[0171] server:

[0172] Receive information entered by the user and save it to the database.

[0173] 5. Generating Recommended Clothing

[0174] server:

[0175] The server retrieves data on the user's clothing from the database. The AI ​​styling module generates the optimal outfit combination based on the inputted TPO (Time, Place, Occasion), weather, and style information.

[0176] server:

[0177] The generated clothing data is sent to the terminal.

[0178] 6. Display and selection of recommended clothing.

[0179] Terminal:

[0180] The suggested outfits are displayed to the user in a list, and the user can view the details of each item. The user taps the selected outfit to complete the confirmation.

[0181] 7. Suggestions from the shop

[0182] server:

[0183] Based on the user's chosen style and past selection data, the system generates suggestions for new fashion items. It retrieves the latest product data from partner retailers, selects products that suit the user, and sends them to their device.

[0184] 8. Viewing and purchasing shop suggestions

[0185] Terminal:

[0186] The system displays a list of suggested products, allowing users to view detailed information about each item. When a user selects a product they wish to purchase and clicks the "Buy" button, they are redirected to the partner retailer's website or application.

[0187] Specific example

[0188] Example 1: Uploading images of clothing

[0189] Terminal:

[0190] The user launches the app and logs in. They select "Upload clothing," take a photo of a blue shirt, and click the "Upload" button.

[0191] server:

[0192] The server receives the image and sends it to an AI image analysis module. It identifies the color as blue, the shape as long-sleeved, and the material as cotton, and stores this information in a database.

[0193] Example 2: Generating Recommended Clothing

[0194] Terminal:

[0195] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[0196] server:

[0197] The server retrieves information about a blue shirt, black pants, and white sneakers from the database. The AI ​​styling module then suggests the optimal combination of these items based on the input data. The overall outfit information is then sent to the app.

[0198] Example 3: Shop proposal

[0199] server:

[0200] Based on the user's past choices and casual style, the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner retailers and sends it to the app.

[0201] Terminal:

[0202] View the suggested product list and check the details. Click on a product you like to go to the purchase page.

[0203] Example of a prompt

[0204] "What's the perfect outfit for a picnic? Something casual for a sunny day."

[0205] "Based on styles you've chosen in the past, please suggest new items that are suitable for today's weather."

[0206] In summary, this system is designed to efficiently support users' busy lifestyles, encourage them to make the most of their existing clothing, and provide suggestions for new fashion items.

[0207] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0208] Step 1: System startup and login

[0209] Terminal:

[0210] The user taps the app on their smartphone to launch it. The launch screen appears, followed by the login screen. The user enters their username and password on the login screen and taps the login button.

[0211] Input: Username, Password

[0212] Output: Sending authentication information

[0213] server:

[0214] The server receives the username and password. It queries the authentication server and compares the received authentication information with the database information. If authentication is successful, it generates a session ID and retrieves user information (name, profile picture, etc.). If authentication fails, it generates an error message and sends it to the terminal.

[0215] Input: Username, Password

[0216] Data processing: Verify authentication information in the database.

[0217] Output: Session ID, User information (if authentication is successful), Error message (if authentication fails)

[0218] Step 2: Upload images of clothing

[0219] Terminal:

[0220] The user selects the "Upload Clothing" option from the menu and taps the "Launch Camera" button. The camera launches, and the user takes a picture of their clothing. After taking the picture, tap the "Upload" button.

[0221] Input: Image of clothing

[0222] Output: Sending image data

[0223] server:

[0224] The server receives the image data and sends it to the AI ​​image analysis module.

[0225] Input: Image data of clothing

[0226] Data processing: Preparing for AI analysis of image data

[0227] Output: Retrieval of analysis results

[0228] Step 3: Analyzing clothing data

[0229] server:

[0230] The AI ​​image analysis module processes the received image data and analyzes attributes such as the color, shape, material, brand, and style of the clothing.

[0231] Input: Image data of clothing

[0232] Data processing: Attribute extraction using AI image analysis module

[0233] Output: Clothing attribute information

[0234] server:

[0235] The analyzed attribute information is saved to a database. The saved information includes clothing identification IDs, attribute information, and user IDs.

[0236] Input: Clothing attribute information

[0237] Data processing: Attribute information stored in a database.

[0238] Output: Save complete flag

[0239] Step 4: Enter user information

[0240] Terminal:

[0241] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then taps the "Submit" button.

[0242] Input: Information such as TPO (Time, Place, Occasion), destination, weather, and style.

[0243] Output: Send input information

[0244] server:

[0245] Receive information entered by the user and save it to the database.

[0246] Input: Information such as TPO (Time, Place, Occasion), destination, weather, and style.

[0247] Data processing: Storing input information in a database.

[0248] Output: Save complete flag

[0249] Step 5: Generating Recommended Clothing

[0250] server:

[0251] The server retrieves data on the user's clothing from the database. The AI ​​styling module generates the optimal outfit combination based on the user's input regarding time, place, occasion, weather, and style.

[0252] Input: TPO (Time, Place, Occasion), weather, style, attribute information of user-owned clothing

[0253] Data processing: Optimal clothing generation using AI styling module

[0254] Output: Recommended clothing data

[0255] server:

[0256] The generated recommended clothing data is sent to the device.

[0257] Input: Recommended clothing data

[0258] Output: Send recommended clothing

[0259] Step 6: Recommended clothing display and selection

[0260] Terminal:

[0261] A list of recommended outfit combinations is displayed to the user. The user can review the details of each item and tap their chosen outfit to complete the confirmation.

[0262] Input: Recommended clothing data

[0263] Output: Data for the selected clothing

[0264] Step 7: Proposal from the shop

[0265] server:

[0266] Based on past choices and styles, it generates suggestions for new fashion items. It retrieves the latest product data from partner retailers and selects products that suit the user. This product information is then sent to the user's device.

[0267] Input: Past selection data, latest product data

[0268] Data processing: New item suggestion generation, product data acquisition.

[0269] Output: Send the proposed product list.

[0270] Step 8: View and purchase shop suggestions

[0271] Terminal:

[0272] The user is shown a list of suggested products, and can view detailed information about each product. When they select a product they wish to purchase and tap the "Purchase" button, they are redirected to the partner retailer's website or application.

[0273] Input: Proposed product list

[0274] Output: Redirect to the purchase page

[0275] Through the steps described above, this system can efficiently support users in receiving clothing suggestions and purchasing new fashion items.

[0276] (Application Example 1)

[0277] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0278] Traditional clothing suggestion systems can suggest the best outfits based on images taken by the user at home and other input information, but they lack the real-time information needed when choosing new clothes in a physical store. Therefore, users find it difficult to effectively coordinate their existing wardrobe with new purchases, resulting in a less-than-ideal shopping experience. Furthermore, the lack of support for immediate purchases in physical stores makes smooth purchasing difficult.

[0279] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0280] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images to extract clothing attribute information, and means for storing the extracted attribute information. This allows the user to receive suggestions for new clothing items in a physical store based on their existing clothing data, and to see coordinated outfits displayed on the spot. Furthermore, by including means for acquiring data from partner companies to suggest new products, and including payment means for purchasing suggested products in-store, the user can receive coordinated outfit suggestions and make immediate purchases in real time, enjoying a comfortable and efficient shopping experience.

[0281] "Means for receiving images taken by users" refers to a function that allows users to send images taken using their smartphones or cameras to the system, and for the system to receive those images.

[0282] The means for "analyzing the received image to extract attribute information of clothing" refers to the function of the system to analyze the received image data using AI and image recognition technology and extract information such as the color, shape, material, brand, and style of the clothing.

[0283] The means for "storing the extracted attribute information" refers to the function for recording the attribute information of clothing obtained through analysis in a storage device such as a database.

[0284] The means for "the user to input TPO, weather, and style information" refers to the function for the user to input information regarding a specific situation, weather conditions, and preferred fashion style into the system.

[0285] The means for "proposing the optimal clothing" refers to the function for proposing the optimal combination of clothing based on the TPO, weather, and style information input by the user and the stored attribute information of the clothing.

[0286] The means for "displaying and allowing the user to select clothing" refers to the function for the system to visually show the combination of clothing proposed to the user and enable the user to select from it.

[0287] The means for "acquiring data of partner merchants" refers to the function for the system to acquire the latest product data from partner shops and merchants in order to propose new products and fashion items.

[0288] The means for "providing a purchase link" refers to the function for providing a link or interface for the user to purchase the proposed new product and supporting online shopping and in-store purchases.

[0289] The means for "performing in a physical store" refers to the function for the user to receive proposals for new clothing and view coordinates while being in a physical store in real time.

[0290] "Payment methods" refers to the function that allows users to instantly purchase products offered within a store by completing the payment process. This function supports various payment methods such as credit cards, mobile payments, and digital wallets.

[0291] The system for implementing this invention comprises a series of means for receiving images taken by a user, analyzing those images to extract clothing attribute information, and storing this information. It also includes means for the user to input TPO (Time, Place, Occasion), weather, and style information, for which the most suitable clothing is suggested, and for the user to see and select the suggested clothing. Furthermore, it includes means for acquiring data from partner companies to suggest new products, for displaying the suggested new products, and for providing purchase links. As an important element, it also includes means for suggesting new clothing in a physical store based on the user's clothing data, for displaying coordinated outfits on the spot, and for payment methods for purchasing the suggested products in the store.

[0292] Processing details

[0293] 1. Device startup and user authentication:

[0294] The terminal uses a mobile device such as a smartphone or smart glasses, and the user logs in to the launched application. The username and password are sent to the authentication server. If authentication is successful, the server starts a session and retrieves user information. Specifically, authentication technologies such as OAuth 2.0 and JWT (JSON Web Token) are used.

[0295] 2. Image upload and analysis:

[0296] Users take pictures of new clothing items in a physical store using the camera on their smartphone or smart glasses. The device sends the image data to a server, which processes the images using an AI image analysis module to extract clothing attribute information (color, shape, material, brand, style). Deep learning technologies such as Convolutional Neural Networks (CNNs) are used.

[0297] 3. Storing attribute data and user information:

[0298] The extracted clothing attribute information is stored in a database. Relational databases or NoSQL databases are often used. The user then enters information such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual) into a form, which the server receives and stores.

[0299] 4. Outfit suggestions:

[0300] The server compares the stored user clothing data with newly entered information and uses an AI styling module to generate the optimal clothing combination. At this stage, the generative AI model and inference module previously used as training data are utilized.

[0301] 5. Displaying coordinated outfits and payment within physical stores:

[0302] The user's device displays suggested outfits. The user reviews the suggested outfits and, if they like them, proceeds with the purchase. Mobile payments utilize NFC (Near Field Communication) technology or QR code (registered trademark) payment.

[0303] Specific example

[0304] Example 1: In-store image scanning and analysis

[0305] 1. Device: The user launches the app and logs in.

[0306] 2. Terminal: Take a picture of the red dress inside the store and send it to the server.

[0307] 3. Server: Sends the image to an AI image analysis module for analysis, determining that the color is red, the shape is a dress, and the material is silk.

[0308] Example 2: Coordination Proposal and Purchase

[0309] 1. Terminal: The user inputs TPO (formal dinner), weather (sunny), and preferred style (elegant).

[0310] 2. Server: Based on the analysis data and user information, generate proposals for white high heels and a gold clutch bag and send them to the terminal.

[0311] 3. Terminal: The recommended coordination is displayed, and the user directly performs mobile payment.

[0312] Examples of Prompt Texts for the Generated AI Model

[0313] Prompt text for an application that recommends new items and coordinates in a physical store based on the clothing data of the user:

[0314] 1. User Information:

[0315] Owned clothing: blue shirt, black pants, white sneakers

[0316] 2. New Item:

[0317] Red dress

[0318] 3. Event Information:

[0319] TPO: Formal dinner

[0320] Weather: Sunny

[0321] Preferred style: Elegant

[0322] 4. Coordination to be presented:

[0323] A blue shirt, black pants, white sneakers, and a clutch bag and jewelry to match the red dress.

[0324] Based on the above information, we will suggest the most suitable outfit and encourage users to purchase it at a physical store.

[0325] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0326] Step 1:

[0327] System startup and user authentication

[0328] Input: The user activates their smartphone or smart glasses and enters their username and password into the application.

[0329] Specific operation: The terminal sends user authentication information to the server. The server queries the authentication server to verify that the username and password match.

[0330] Output: If authentication is successful, a session is started and user information is sent from the server to the terminal. If it fails, an authentication error message is displayed on the terminal.

[0331] Step 2:

[0332] Upload image

[0333] Input: The user takes pictures of new clothing items in a physical store using the camera on their smartphone or smart glasses.

[0334] Specific operation: The device sends the captured image data to the server.

[0335] Output: Image data is received by the server and sent to the next analysis step.

[0336] Step 3:

[0337] Image analysis and attribute extraction

[0338] Input: Image data received by the server.

[0339] Specific operation: The server uses an AI image analysis module to process image data and extract attributes such as the color, shape, material, brand, and style of the clothing.

[0340] Output: The attribute information of the extracted clothing items is saved to the database.

[0341] Step 4:

[0342] Entering user information

[0343] Input: The user enters information into the application such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual).

[0344] Specific operation: The terminal sends the information entered by the user to the server.

[0345] Output: The server saves the received user's TPO, weather, and style information to the database.

[0346] Step 5:

[0347] Coordination generation

[0348] Input: Saved user clothing data and newly entered TPO, weather, and style information.

[0349] Specific operation: The server uses an AI styling module to match input information with stored data and generate the optimal clothing combination.

[0350] Output: The optimal clothing combination is sent to the device.

[0351] Step 6:

[0352] Display and select outfits

[0353] Input: Information on the optimal clothing combination sent from the server.

[0354] Specific operation: The device displays clothing suggestions to the user. The user makes a selection from these suggestions.

[0355] Output: Details of the clothing selected by the user are saved on the device.

[0356] Step 7:

[0357] Proposal for a new product

[0358] Input: User selection information, past selections, and style information.

[0359] Specific operation: The server retrieves new product data from partner vendors and suggests the most suitable new products based on the user's style and past choices.

[0360] Output: New product suggestion information is sent to the terminal.

[0361] Step 8:

[0362] Display and purchase of product suggestions.

[0363] Input: New product suggestion information sent from the server.

[0364] Specific operation: The terminal displays a list of new products and provides detailed information about each product. The user selects the product they wish to purchase and proceeds with the payment process.

[0365] Output: The selected items are displayed in the store, and the user completes the payment process. If a mobile payment system is used, the purchase record is saved on the server.

[0366] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0367] This invention is a system that uses a webcam or smartphone app to input images of the user's clothing into an AI, and then suggests the most suitable outfit based on the occasion, weather, style, and the user's emotions. Furthermore, it also supports the suggestion and purchase of new fashion items.

[0368] The basic configuration of this system includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, an emotion engine that recognizes the user's emotions, means for suggesting the most suitable outfit based on the input information, stored attribute information, and emotion information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, and means for displaying the suggested new products and providing purchase links.

[0369] Program Processing Description

[0370] 1. System startup and login

[0371] Terminal:

[0372] The user launches the app, enters their username and password on the login screen, and presses the login button.

[0373] server:

[0374] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[0375] 2. Upload images of clothing

[0376] Terminal:

[0377] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[0378] server:

[0379] The server receives the image data and sends it to the AI ​​image analysis module.

[0380] 3. Data analysis of clothing

[0381] server:

[0382] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[0383] 4. Entering user information

[0384] Terminal:

[0385] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[0386] server:

[0387] The server receives the information entered by the user.

[0388] 5. Acquisition and analysis of emotional information

[0389] Terminal:

[0390] The user activates the emotion recognition module and either shows their face to the camera or inputs voice.

[0391] server:

[0392] The emotion engine analyzes emotional information from the user's facial expressions and voice, and stores that information.

[0393] 6. Generating Recommended Clothing

[0394] server:

[0395] The server retrieves data on the user's clothing from the database. Based on the user's input regarding time, place, occasion, weather, style, and emotional state, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[0396] 7. Display and selection of recommended clothing.

[0397] Terminal:

[0398] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[0399] 8. Suggestions from the shop

[0400] server:

[0401] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[0402] 9. Displaying and purchasing shop suggestions

[0403] Terminal:

[0404] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[0405] Specific example

[0406] Example 1: Uploading images of clothing

[0407] Terminal:

[0408] Launch the app and log in. Select "Upload Clothing" from the menu, take a picture of a blue shirt, and upload it.

[0409] server:

[0410] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[0411] Example 2: Acquisition and analysis of emotional information

[0412] Terminal:

[0413] The user activates the emotion recognition module and displays their face towards the camera.

[0414] server:

[0415] The emotion engine analyzes facial expression data and determines if the user is feeling "joy." This information is then stored in a database.

[0416] Example 3: Generating Recommended Clothing

[0417] Terminal:

[0418] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[0419] server:

[0420] The system retrieves information about a blue shirt, black pants, and white sneakers from a database. An AI styling module then considers emotional information to suggest the optimal combination of these items. The overall coordination information is then sent to the app.

[0421] Example 4: Shop proposal

[0422] server:

[0423] Based on the user's past choices and situations in which they feel "joy," the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[0424] Terminal:

[0425] The suggested product list is displayed, and users can view detailed information. Clicking on a favorite item takes them to the purchase page. In this way, users can easily combine outfits that suit their style, and receive and purchase new item suggestions. By utilizing emotional information, more personalized suggestions become possible.

[0426] The following describes the processing flow.

[0427] Step 1:

[0428] Terminal:

[0429] The user launches the app, enters their username and password on the login screen, and presses the login button.

[0430] server:

[0431] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[0432] Step 2:

[0433] Terminal:

[0434] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[0435] server:

[0436] The server receives the image data and sends it to the AI ​​image analysis module.

[0437] Step 3:

[0438] server:

[0439] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[0440] Step 4:

[0441] Terminal:

[0442] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[0443] server:

[0444] The server receives the information entered by the user.

[0445] Step 5:

[0446] Terminal:

[0447] The user activates the emotion recognition module and either shows their face to the camera or inputs voice.

[0448] server:

[0449] The emotion engine analyzes emotional information from the user's facial expressions and voice, and stores that information.

[0450] Step 6:

[0451] server:

[0452] The server retrieves data on the user's clothing from the database. Based on the user's input regarding time, place, occasion, weather, style, and emotional state, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[0453] Step 7:

[0454] Terminal:

[0455] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[0456] Step 8:

[0457] server:

[0458] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[0459] Step 9:

[0460] Terminal:

[0461] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[0462] (Example 2)

[0463] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0464] Conventional clothing suggestion systems were limited to analyzing images of clothes owned by the user to obtain attribute information, and had the problem of not being able to make suggestions that appropriately considered information such as the user's emotions, TPO (Time, Place, Occasion), weather, and style. Furthermore, the suggestion of new fashion items and the provision of purchase links were limited, and it was not possible to improve the overall user experience.

[0465] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0466] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, means for acquiring and analyzing the user's emotional information using an emotional engine, means for suggesting the most suitable outfit based on the input information, stored attribute information, and acquired emotional information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, and means for displaying the suggested new products and providing purchase links. This enables personalized clothing suggestions that meet the diverse needs and circumstances of the user, as well as the smooth purchase of new fashion items.

[0467] "Means for receiving images taken by the user" refers to the functions of equipment and software that allow a user to send image data of their clothing, taken with a smartphone or camera, to a system and receive that data.

[0468] "Means for analyzing received images and extracting clothing attribute information" refers to a function that uses AI image analysis technology to automatically identify attributes such as the color, shape, material, brand, and style of clothing from received image data.

[0469] "Means for saving extracted attribute information" refers to a function for saving the clothing attribute information obtained through analysis to a storage device such as a database.

[0470] "Means for users to input TPO, weather, and style information" refers to an interface (e.g., a form, a dropdown menu, a checkbox, etc.) for users to input information such as events or situations (TPO), weather, and preferred style.

[0471] "Means for acquiring and analyzing user emotional information using an emotion engine" refers to a function that captures the user's facial expressions and voice using a camera and microphone, and analyzes the user's current emotional state using an emotion recognition algorithm.

[0472] "Means of suggesting the optimal outfit based on input information, stored attribute information, and acquired emotional information" refers to algorithms and software functions that integrate and comprehensively analyze user-inputted information such as TPO (Time, Place, Occasion), weather, and style, as well as stored clothing attribute information and user emotional information, to generate the optimal outfit combination.

[0473] "A means of displaying suggested outfits to the user and allowing them to select" refers to a function that displays the optimal outfit combinations generated by the system on the user interface, allowing the user to select from among them.

[0474] "Means of acquiring data from partner shops to propose new products" refers to a function that obtains the latest product information from partner online shops and stores and proposes new fashion items to users.

[0475] "A means of displaying suggested new products and providing purchase links" refers to a function that displays suggested new fashion items to the user in the user interface and provides a link to the purchase page for those products.

[0476] This invention's system uses a webcam or smartphone app to read images of the user's clothing into an AI, and then suggests the most suitable outfit based on TPO (Time, Place, Occasion), weather, style, and the user's emotions. Furthermore, it also supports the suggestion and purchase of new fashion items.

[0477] Basic configuration

[0478] This system includes the following means:

[0479] 1. Means for receiving images taken by the user

[0480] This refers to the function of devices and software that allow users to send image data of their clothing, taken with their smartphones or cameras, to a system, and receive that data.

[0481] 2. Means for analyzing received images and extracting clothing attribute information.

[0482] This function uses AI image analysis technology to automatically identify attributes such as the color, shape, material, brand, and style of clothing from received image data. Specifically, it can utilize machine learning frameworks such as TENSORFLOW® and PyTorch.

[0483] 3. Means for saving extracted attribute information

[0484] This function allows you to save the clothing attribute information obtained through analysis to a database (e.g., MySQL®, PostgreSQL).

[0485] 4. Means for users to input TPO, weather, and style information

[0486] This is an interface (e.g., a form, a dropdown menu, a checkbox, etc.) for users to input information such as the event or situation (TPO), weather, and preferred style.

[0487] 5. Means for acquiring and analyzing user emotional information using an emotion engine.

[0488] This feature uses a camera and microphone to capture the user's facial expressions and voice, and then analyzes the user's current emotional state using an emotion recognition algorithm. Specifically, it can utilize emotion recognition APIs such as FaceAPI and EmotionAPI.

[0489] 6. A means of suggesting the most suitable clothing based on the input information, stored attribute information, and acquired emotional information.

[0490] This refers to algorithms and software functions that integrate and comprehensively analyze user-entered information such as TPO (Time, Place, Occasion), weather, and style, as well as saved clothing attribute information and user sentiment information, to generate the optimal clothing combination. Specifically, algorithm implementations using Python or frameworks such as Django can be utilized.

[0491] 7. A means of displaying suggested clothing to the user and allowing them to select it.

[0492] This feature displays the system's generated optimal clothing combinations in the user interface (e.g., mobile app, web app), allowing the user to select from them.

[0493] 8. Means of obtaining data from partner shops in order to propose new products.

[0494] This function retrieves the latest product information from partner online shops and stores and suggests new fashion items to users.

[0495] 9. Means of displaying proposed new products and providing purchase links

[0496] This function displays suggested new fashion items to the user in the user interface and provides a link to the product's purchase page.

[0497] Specific example

[0498] Example 1: Uploading images of clothing

[0499] Terminal:

[0500] The user launches the app and logs in. From the menu, they select "Upload Clothing," take a picture of a blue shirt, and upload it.

[0501] server:

[0502] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[0503] Example 2: Acquisition and analysis of emotional information

[0504] Terminal:

[0505] The user activates the emotion recognition module and displays their face towards the camera.

[0506] server:

[0507] The emotion engine analyzes facial expression data and determines if the user is feeling "joy." This information is then stored in a database.

[0508] Example 3: Generating Recommended Clothing

[0509] Terminal:

[0510] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[0511] server:

[0512] The system retrieves information about a blue shirt, black pants, and white sneakers from a database. An AI styling module then considers emotional information to suggest the optimal combination of these items. The overall coordination information is then sent to the app.

[0513] Example 4: Shop proposal

[0514] server:

[0515] Based on the user's past choices and situations in which they feel "joy," the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[0516] Terminal:

[0517] The suggested product list is displayed, and users can view detailed information. Clicking on a favorite item takes them to the purchase page. In this way, users can easily combine outfits that suit their style, and receive and purchase new item suggestions. By utilizing emotional information, more personalized suggestions become possible.

[0518] Example of a prompt

[0519] "Please provide a user interface design proposal that prioritizes ease of use and visibility."

[0520] In this way, by using appropriate hardware and software, it is possible to realize a system that supports users in finding the optimal clothing to meet their diverse needs and in purchasing new fashion items.

[0521] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0522] Step 1: System startup and login

[0523] Terminal:

[0524] The user launches the app, and the login screen is displayed.

[0525] The user enters their username and password and clicks the "Login" button.

[0526] server:

[0527] The server receives the entered username and password.

[0528] The server queries the authentication server to authenticate the user.

[0529] Input: Username, Password

[0530] Data processing: Comparison with user information in the database

[0531] Output: Authentication success or failure result

[0532] If authentication is successful, the server starts a session, retrieves user information (e.g., past uploaded data and stored attribute information), and sends it to the device.

[0533] Specific actions:

[0534] When a user opens the app on their smartphone and enters their email address and password, that information is sent to the server. Once authenticated, the user's personalized home screen is displayed.

[0535] Step 2: Upload images of clothing

[0536] Terminal:

[0537] The user selects "Upload clothing" from the menu.

[0538] Press the "Start Camera" button to activate the camera.

[0539] The user takes a picture of their clothes and presses the "Upload" button.

[0540] server:

[0541] The server receives image data sent from the terminal.

[0542] Input: Image data

[0543] Data processing: Compression and conversion of image data

[0544] Output: Compressed image data

[0545] The image data is sent to the AI ​​image analysis module.

[0546] Specific actions:

[0547] When a user takes a picture of a blue shirt and uploads it to the system, the image data is sent to the server and image analysis begins.

[0548] Step 3: Analyzing clothing data

[0549] server:

[0550] The AI ​​image analysis module analyzes images of clothing and extracts attributes such as color, shape, material, brand, and style.

[0551] Input: Compressed image data

[0552] Data processing: AI-based image analysis (e.g., color recognition, shape recognition)

[0553] Output: Clothing attribute information (e.g., Color: Blue, Style: Long-sleeved, Material: Cotton)

[0554] The extracted attribute information is saved to the database.

[0555] Specific actions:

[0556] The AI ​​analyzes the image, automatically identifying detailed information such as the color, shape, and material of the blue shirt uploaded by the user, and saving it to the system's database.

[0557] Step 4: Enter user information

[0558] Terminal:

[0559] The user selects "Enter Styling Information" from the menu.

[0560] The user enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), preferred style (e.g., casual) into the form and presses the "Submit" button.

[0561] server:

[0562] Receive the information entered in the form.

[0563] Input: User's TPO (Time, Place, Occasion), weather, and style information

[0564] Data processing: Temporary storage of information

[0565] Output: Verification results of temporarily saved information

[0566] The received information is saved to a temporary data store.

[0567] Specific actions:

[0568] The user selects and enters their chosen picnic destination, the weather in the park, and their preferred style.

[0569] Step 5: Acquisition and analysis of emotional information

[0570] Terminal:

[0571] The user activates the emotion recognition module.

[0572] The user either shows their face to the camera or inputs voice.

[0573] server:

[0574] It receives facial expressions and voice data.

[0575] Input: Facial expression data, audio data

[0576] Data processing: Analysis using an emotion engine

[0577] Output: User emotion information (e.g., "joy")

[0578] The emotion engine analyzes data to identify and store the emotions the user is currently feeling.

[0579] Specific actions:

[0580] When a user smiles at the camera, the system analyzes that expression as "joy" and saves that information.

[0581] Step 6: Generating Recommended Clothing

[0582] server:

[0583] Retrieve data on the clothing owned by the user from the database (e.g., blue shirt, black pants, white sneakers).

[0584] Input: User's owned clothing data

[0585] Data processing: Generating appropriate combinations for each outfit.

[0586] Output: Recommended clothing combination (e.g., blue shirt, black pants, white sneakers)

[0587] Based on the user's input regarding time, place, occasion, weather, style, and emotional information, the AI ​​styling module generates the optimal outfit.

[0588] Send the suggested outfit combinations to the app.

[0589] Specific actions:

[0590] The server retrieves information about a blue shirt, black pants, and white sneakers from the database and suggests the most appropriate casual outfit, taking into account the occasion, time, place, and mood.

[0591] Step 7: Recommended clothing display and selection

[0592] Terminal:

[0593] A list of recommended clothing combinations will be displayed.

[0594] The user selects one outfit from the suggested options and then checks the details.

[0595] Tap the selected outfit to complete the confirmation.

[0596] Specific actions:

[0597] The user reviews the clothing combinations suggested by the app (blue shirt, black pants, white sneakers) and taps the one they like best.

[0598] Step 8: Suggestions from the shop

[0599] server:

[0600] Based on the user's chosen style and past selection data, new suggestions are generated.

[0601] Input: Past selection data, user style information

[0602] Data processing: Filtering and selecting new fashion items

[0603] Output: Suggested new items (e.g., hat, sunglasses)

[0604] The app retrieves the latest item information from partner shops and sends it to the app.

[0605] Specific actions:

[0606] Based on items the user has previously selected and their current styling information, the system suggests the latest hats, sunglasses, and other items obtained from partner shops.

[0607] Step 9: View and purchase shop suggestions

[0608] Terminal:

[0609] Display a list of suggested products.

[0610] Check detailed information about each product (price, brand, reviews, etc.).

[0611] After selecting the product you want to purchase and clicking the "Purchase" button, you will be redirected to the partner shop's website or application.

[0612] Specific actions:

[0613] The user clicks on a pair of sunglasses they like from the list of suggested products and checks the details. Once they decide to purchase, they click the "Purchase" button to proceed to the purchase page of the partner shop.

[0614] (Application Example 2)

[0615] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0616] In recent years, fashion choices have diversified according to users' styles and preferences, and choosing clothing based on TPO (time, place, and purpose) and weather has become particularly important. However, conventional systems have difficulty appropriately analyzing the attributes of a user's clothing and providing coordinated outfit suggestions that take into account the user's emotional information. Furthermore, there is a lack of effective means to suggest new products. As a result, users are unable to choose clothing that best suits their style and are dissatisfied with their purchases of new fashion items.

[0617] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0618] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information, stored attribute information, and emotional information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, means for displaying the suggested new products and providing purchase links, means for acquiring and analyzing emotional information, and means for suggesting new fashion items based on past selections. As a result, the user can easily choose the most suitable outfit from their existing wardrobe, and also easily receive personalized suggestions that take emotional information into account, as well as purchase new fashion items.

[0619] "Means for receiving images taken by a user" refers to functions or devices that allow a user to send images taken with a smartphone or camera to a system and receive those images.

[0620] "Means for analyzing received images and extracting clothing attribute information" refers to functions or devices that use AI or image analysis technology to extract attribute information such as the color, shape, material, brand, and style of clothing based on received images.

[0621] "Means for saving extracted attribute information" refers to functions or devices for saving the clothing attribute information obtained through analysis to a database or storage.

[0622] "Means for users to input TPO, weather, and style information" refers to interfaces or devices that allow users to input information about their intended use (time, place, purpose), weather, and preferred style into the system.

[0623] "A means of suggesting the optimal outfit based on input information, stored attribute information, and emotional information" refers to a function or device that generates the optimal combination from stored clothing attribute information based on the TPO, weather, style information, and emotional data entered by the user.

[0624] "Means for displaying and allowing users to select suggested clothing" refers to interfaces or devices that visually display generated clothing suggestions to the user, allowing the user to select from among them.

[0625] "Means of acquiring data from partner shops in order to propose new products" refers to functions and devices for acquiring data on the latest fashion items from partner online shops and retail stores.

[0626] "Means for displaying proposed new products and providing purchase links" refers to interfaces or devices that display information about newly acquired fashion items to the user and provide links for purchasing them.

[0627] "Means for acquiring and analyzing emotional information" refers to functions or devices that acquire and analyze a user's emotions at a given time, such as from their facial expressions or voice data.

[0628] "Means of suggesting new fashion items based on past choices" refers to functions or devices that recommend new fashion items based on the user's past clothing selection data and purchase history.

[0629] The system implementing this invention aims to suggest the most suitable clothing by taking images of the user's clothing, which are then analyzed by AI, and to also recommend new products. This system consists of three main elements: a server, a terminal, and the user.

[0630] Server roles and processing

[0631] The server performs the following roles:

[0632] 1. Receiving images taken by users: To receive images taken by users with their smartphones or cameras, the image data is processed using a web framework such as Flask.

[0633] 2. Image Analysis: The received images are analyzed to extract clothing attribute information. Specifically, image analysis libraries such as OpenCV are used to obtain information such as color, shape, material, brand, and style.

[0634] 3. Saving attribute information: The extracted attribute information is saved to a database. SQL or NoSQL databases are used as the database.

[0635] 4. Information Integration and Analysis: The system receives user-inputted TPO (Time, Place, and Occasion), weather, style information, and emotional information, and integrates and analyzes this information with stored clothing attribute data. This process utilizes generative AI models and emotional analysis APIs.

[0636] 5. Clothing Suggestions: Based on integrated information, the AI ​​styling module suggests the most suitable outfit for the user.

[0637] 6. New Product Suggestions: Obtain the latest product data from partner shops and recommend products based on the user's past choices and sentiment information.

[0638] In this way, the system provides users with suggestions for the most suitable clothing and recommendations for new products.

[0639] Terminal roles and processing

[0640] Smartphones and other devices perform the following roles:

[0641] 1. Image capture and transmission: The user uses their smartphone camera to take a picture of the clothing they are wearing. The captured image is sent to the server via the application.

[0642] 2. Information Input: Provide an interface for the user to input TPO (Time, Place, Purpose), weather, and style information. It also activates an emotion recognition module, either by capturing facial expressions with the camera or inputting voice.

[0643] 3. Receiving and displaying suggestions: The system receives and displays a list of optimal clothing suggestions sent from the server. The user reviews and selects from the suggested clothing combinations.

[0644] 4. Display of new products and provision of purchase links: The interface displays information about new products sent from the server and provides purchase links.

[0645] This allows the terminal to function as an interface with the user, handling information input and receiving / displaying suggestions.

[0646] User roles and operations

[0647] The user performs the following actions:

[0648] 1. Launching the application and logging in: First, launch the application and log in by entering your username and password on the login screen.

[0649] 2. Take and upload images: Select the "Upload clothing" option from the menu, activate your smartphone's camera, take a picture of your clothing, and click the "Upload" button.

[0650] 3. Entering Information: Select "Enter Styling Information" from the menu, enter the time, place, occasion, weather, and style information, and press the "Submit" button.

[0651] 4. Acquiring emotion information: Activate the emotion recognition module and either show your face to the camera or input voice.

[0652] 5. Review and Select Suggestions: Review the list of recommended clothing combinations and make your selection. Also, review the suggested new items and purchase the ones you like.

[0653] Examples of specific cases and prompt statements

[0654] Example 1: Uploading images of clothing

[0655] The user launches the application and logs in. From the menu, they select "Upload Clothing," take a picture of a blue shirt, and upload it.

[0656] Example 2: Acquisition of emotional information

[0657] The user activates the emotion recognition module and displays their face towards the camera.

[0658] Example of a prompt

[0659] 1. "I'm planning a picnic on a sunny day; could you suggest some casual outfits?"

[0660] 2. "Based on your current emotions, please suggest the best outfit using the clothes you own."

[0661] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0662] Step 1:

[0663] The user launches the application, enters their username and password on the login screen, and presses the login button. The server receives the username and password, authenticates the user, and starts a session. It retrieves user information and notifies the terminal of the successful login.

[0664] Input: Username, Password

[0665] Data processing and calculation: Username and password verification, session initiation.

[0666] Output: Login success notification

[0667] Step 2:

[0668] The user selects the "Upload Clothing" option from the menu, activates their smartphone's camera to take a picture of their clothing, and clicks the "Upload" button. The device sends the image data to the server, and the server receives the image.

[0669] Input: Captured image

[0670] Data processing and calculation: Receiving and saving images.

[0671] Output: Image save confirmation notification

[0672] Step 3:

[0673] The server uses an AI image analysis module to analyze received images and extract attribute information such as color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[0674] Input: Received image

[0675] Data processing and calculation: Image analysis, extraction of attribute information.

[0676] Output: Saving attribute information

[0677] Step 4:

[0678] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and presses the "Submit" button. The terminal sends the entered information to the server.

[0679] Input: TPO (Time, Place, Occasion), weather, style information

[0680] Data processing and calculation: Information reception

[0681] Output: Information storage, confirmation notification

[0682] Step 5:

[0683] The user activates the emotion recognition module and either shows their face to the camera or inputs voice. The device sends the image or voice data to the server, where the server's emotion engine analyzes it, extracts emotion information, and stores it in a database.

[0684] Input: User's facial expression image or audio data

[0685] Data processing and calculation: emotion analysis, extraction of emotional information.

[0686] Output: Storage of emotional information, confirmation notification

[0687] Step 6:

[0688] The server retrieves data on the user's clothing, the user's input regarding occasion (TPO), weather, style, and emotional state from the database. The AI ​​styling module then generates the optimal clothing combination based on this information and sends it to the application.

[0689] Input: Clothing data, occasion (TPO), weather, style information, emotional information

[0690] Data processing and calculation: Generating clothing combinations

[0691] Output: Suggestions for the best outfit

[0692] Step 7:

[0693] The device displays a list of recommended clothing combinations, and the user taps on a suggested outfit to view details and then taps on their chosen outfit to confirm.

[0694] Input: Suggestions for the best outfit

[0695] Data processing and calculation: Information display

[0696] Output: Confirmation of detailed information, notification of selection completion.

[0697] Step 8:

[0698] The server suggests new fashion items based on the user's chosen style and past selections. It retrieves the latest item information from partner shops and sends products that match the user's style to the application.

[0699] Input: Past selection data, partner shop data

[0700] Data processing and calculations: Proposal of new products

[0701] Output: Send new product information

[0702] Step 9:

[0703] The device displays a list of suggested products, and the user reviews detailed information about each product (price, brand, reviews, etc.), selects the product they wish to purchase, and presses the "Purchase" button. This redirects them to the partner shop's website or application.

[0704] Input: New product information

[0705] Data Processing / Calculation: Displaying Detailed Information

[0706] Output: Redirection to purchase link

[0707] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0708] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0709] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0710] [Second Embodiment]

[0711] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0712] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0713] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0714] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0715] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0716] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0717] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0718] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0719] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0720] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0721] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0722] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0723] This invention is a system that uses a webcam or smartphone app to load images of the user's clothing into AI, and then suggests the most suitable outfit based on the occasion, weather, and style. Furthermore, it also supports the suggestion and purchase of new fashion items.

[0724] The basic configuration of this system includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for saving the extracted attribute information, means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information and saved attribute information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops in order to suggest new products, and means for displaying the suggested new products and providing purchase links.

[0725] Program Processing Description

[0726] 1. System startup and login

[0727] Terminal:

[0728] The user launches the app, enters their username and password on the login screen, and presses the login button.

[0729] server:

[0730] The system receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[0731] 2. Upload images of clothing

[0732] Terminal:

[0733] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[0734] server:

[0735] The system receives image data and sends it to the AI ​​image analysis module.

[0736] 3. Data analysis of clothing

[0737] server:

[0738] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[0739] 4. Entering user information

[0740] Terminal:

[0741] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[0742] server:

[0743] Receives information entered by the user.

[0744] 5. Generating Recommended Clothing

[0745] server:

[0746] The system retrieves data on the user's clothing from a database. Based on the user's input regarding occasion, weather, and style, an AI styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[0747] 6. Display and selection of recommended clothing.

[0748] Terminal:

[0749] The system displays a list of recommended outfit combinations, and users can tap on a suggested outfit to view details. They can then tap on their chosen outfit to complete the confirmation.

[0750] 7. Suggestions from the shop

[0751] server:

[0752] Based on the user's chosen style and past selections, the app generates new suggestions. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[0753] 8. Viewing and purchasing shop suggestions

[0754] Terminal:

[0755] A list of suggested products is displayed, and detailed information (price, brand, reviews, etc.) can be viewed for each product. Selecting a product you wish to purchase and clicking the "Purchase" button will redirect you to the partner shop's website or application.

[0756] Specific example

[0757] Example 1: Uploading images of clothing

[0758] Terminal:

[0759] Launch the app and log in.

[0760] Select "Upload clothing," take a picture of the blue shirt, and upload it.

[0761] server:

[0762] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[0763] Example 2: Generating Recommended Clothing

[0764] Terminal:

[0765] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[0766] server:

[0767] The system retrieves information on a blue shirt, black pants, and white sneakers from a database. An AI styling module then suggests the optimal combination of these items based on the input data. The overall outfit information is then sent to the app.

[0768] Example 3: Shop proposal

[0769] server:

[0770] Based on the user's past choices and casual style, the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[0771] Terminal:

[0772] The suggested product list is displayed, and detailed information can be viewed. Clicking on a product you like will take you to the purchase page. In this way, users can easily combine outfits that suit their style, and new items can be suggested and purchased.

[0773] This system is designed to support users' busy lifestyles and help them use their time efficiently. It encourages users to make the most of their existing clothing while also providing suggestions for new fashion items, allowing them to always enjoy the latest styles.

[0774] The following describes the processing flow.

[0775] Step 1:

[0776] Terminal:

[0777] The user launches the app, enters their username and password on the login screen, and presses the login button.

[0778] server:

[0779] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[0780] Step 2:

[0781] Terminal:

[0782] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[0783] server:

[0784] The server receives the image data and sends it to the AI ​​image analysis module.

[0785] Step 3:

[0786] server:

[0787] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[0788] Step 4:

[0789] Terminal:

[0790] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[0791] server:

[0792] The server receives the information entered by the user.

[0793] Step 5:

[0794] server:

[0795] The server retrieves data on the user's clothing from the database. Based on the user's input regarding occasion, weather, and style, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[0796] Step 6:

[0797] Terminal:

[0798] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[0799] Step 7:

[0800] server:

[0801] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[0802] Step 8:

[0803] Terminal:

[0804] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[0805] (Example 1)

[0806] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0807] Conventional clothing suggestion systems often fail to adequately personalize user outfit combinations and suggest new items, posing a challenge to improving user satisfaction. Furthermore, the lack of automatic generation of optimal outfits based on time, place, occasion, weather, and preferred style meant they could not efficiently support users' busy lifestyles.

[0808] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0809] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images to extract clothing attribute information, and means for storing the extracted attribute information. This allows for detailed storage of information about the user's clothing in a database, enabling analysis based on individual attributes. The invention also includes means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information and stored attribute information, means for displaying the suggested outfits to the user and allowing them to select one, means for generating the most suitable outfit using a generative AI model based on the TPO, weather, and style information entered by the user, and means for suggesting new fashion items based on the user's past choices and style. This enables the suggestion of the most suitable outfit tailored to the user's individual needs and the constant suggestion of new styles, significantly improving user satisfaction.

[0810] A "user" is an individual or group that uses this system.

[0811] "Captured images" refer to image data acquired by the user using the camera function of the system.

[0812] "Means of receiving" refers to the function or device that allows a server to receive data sent by a user.

[0813] "Means of analysis" refers to a function or technology used by a system to analyze received image data and extract specific information.

[0814] "Clothing attribute information" refers to information about the characteristics of clothing, such as color, shape, material, brand, and style.

[0815] "Means of storage" refers to a function or device for storing extracted information in a database or storage device.

[0816] "TPO" is an abbreviation for Time, Place, and Occasion, and it is a set of criteria for determining appropriate attire for a particular situation.

[0817] "Style information" refers to information about the type and design of clothing based on the user's preferences and current trends.

[0818] "Means of suggesting the optimal outfit" refers to a function or technology that presents clothing combinations suitable for a user based on information entered by the user and stored attribute information.

[0819] "Means of displaying and allowing selection" refers to a function or device that visually presents suggested clothing to the user and allows them to make a selection from among them.

[0820] A "partner retailer" is a store or company that collaborates with this system to provide product data and propose new products to users.

[0821] A "generative AI model" refers to an algorithm or technology that uses artificial intelligence to generate the most suitable clothing based on input data.

[0822] "Means of providing a purchase link" refers to a function or technology that displays a link so that a user can access the purchase page of a suggested product.

[0823] "Past choices" refers to clothing and styling information that the user previously selected within the system.

[0824] This invention is a system that uses a webcam or smartphone app to read images of the user's clothing into an AI, and then suggests the most suitable outfit based on the occasion, weather, and style. Furthermore, it also supports the suggestion and purchase of new fashion items.

[0825] System Configuration

[0826] This system includes the following components:

[0827] Means for receiving images of clothing

[0828] A method for analyzing received images and extracting clothing attribute information.

[0829] Means for saving extracted attribute information

[0830] A means for users to input TPO (Time, Place, Occasion), weather, and style information.

[0831] A method for suggesting the most suitable clothing based on input information and stored attribute information.

[0832] A means of displaying suggested clothing to the user and allowing them to select from it.

[0833] Means of acquiring data from partner retailers in order to propose new products.

[0834] A means of displaying proposed new products and providing purchase links.

[0835] A method for generating the optimal outfit using a generative AI model based on user-inputted information regarding time, place, occasion, weather, and style.

[0836] A method for suggesting new fashion items based on the user's past choices and style.

[0837] Program processing flow

[0838] The system program operates in the following sequence:

[0839] 1. System startup and login

[0840] Terminal:

[0841] The user launches the app, enters their username and password on the login screen, and presses the login button.

[0842] server:

[0843] The server receives the username and password, queries the authentication server, and performs authentication. If authentication is successful, it generates a session ID and retrieves user information.

[0844] 2. Upload images of clothing

[0845] Terminal:

[0846] The user selects the "Upload Clothing" option from the menu, activates the camera, takes a picture of the clothing, and taps the "Upload" button.

[0847] server:

[0848] The server receives the image data and sends it to the AI ​​image analysis module.

[0849] 3. Data analysis of clothing

[0850] server:

[0851] The AI ​​image analysis module processes image data and analyzes attributes such as the color, shape, material, brand, and style of the clothing.

[0852] server:

[0853] The analyzed attribute information is saved to the database.

[0854] 4. Entering user information

[0855] Terminal:

[0856] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and taps the "Submit" button.

[0857] server:

[0858] Receive information entered by the user and save it to the database.

[0859] 5. Generating Recommended Clothing

[0860] server:

[0861] The server retrieves data on the user's clothing from the database. The AI ​​styling module generates the optimal outfit combination based on the inputted TPO (Time, Place, Occasion), weather, and style information.

[0862] server:

[0863] The generated clothing data is sent to the terminal.

[0864] 6. Display and selection of recommended clothing.

[0865] Terminal:

[0866] The suggested outfits are displayed to the user in a list, and the user can view the details of each item. The user taps the selected outfit to complete the confirmation.

[0867] 7. Suggestions from the shop

[0868] server:

[0869] Based on the user's chosen style and past selection data, the system generates suggestions for new fashion items. It retrieves the latest product data from partner retailers, selects products that suit the user, and sends them to their device.

[0870] 8. Viewing and purchasing shop suggestions

[0871] Terminal:

[0872] The system displays a list of suggested products, allowing users to view detailed information about each item. When a user selects a product they wish to purchase and clicks the "Buy" button, they are redirected to the partner retailer's website or application.

[0873] Specific example

[0874] Example 1: Uploading images of clothing

[0875] Terminal:

[0876] The user launches the app and logs in. They select "Upload clothing," take a photo of a blue shirt, and click the "Upload" button.

[0877] server:

[0878] The server receives the image and sends it to an AI image analysis module. It identifies the color as blue, the shape as long-sleeved, and the material as cotton, and stores this information in a database.

[0879] Example 2: Generating Recommended Clothing

[0880] Terminal:

[0881] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[0882] server:

[0883] The server retrieves information about a blue shirt, black pants, and white sneakers from the database. The AI ​​styling module then suggests the optimal combination of these items based on the input data. The overall outfit information is then sent to the app.

[0884] Example 3: Shop proposal

[0885] server:

[0886] Based on the user's past choices and casual style, the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner retailers and sends it to the app.

[0887] Terminal:

[0888] View the suggested product list and check the details. Click on a product you like to go to the purchase page.

[0889] Example of a prompt

[0890] "What's the perfect outfit for a picnic? Something casual for a sunny day."

[0891] "Based on styles you've chosen in the past, please suggest new items that are suitable for today's weather."

[0892] In summary, this system is designed to efficiently support users' busy lifestyles, encourage them to make the most of their existing clothing, and provide suggestions for new fashion items.

[0893] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0894] Step 1: System startup and login

[0895] Terminal:

[0896] The user taps the app on their smartphone to launch it. The launch screen appears, followed by the login screen. The user enters their username and password on the login screen and taps the login button.

[0897] Input: Username, Password

[0898] Output: Sending authentication information

[0899] server:

[0900] The server receives the username and password. It queries the authentication server and compares the received authentication information with the database information. If authentication is successful, it generates a session ID and retrieves user information (name, profile picture, etc.). If authentication fails, it generates an error message and sends it to the terminal.

[0901] Input: Username, Password

[0902] Data processing: Verify authentication information in the database.

[0903] Output: Session ID, User information (if authentication is successful), Error message (if authentication fails)

[0904] Step 2: Upload images of clothing

[0905] Terminal:

[0906] The user selects the "Upload Clothing" option from the menu and taps the "Launch Camera" button. The camera launches, and the user takes a picture of their clothing. After taking the picture, tap the "Upload" button.

[0907] Input: Image of clothing

[0908] Output: Sending image data

[0909] server:

[0910] The server receives the image data and sends it to the AI ​​image analysis module.

[0911] Input: Image data of clothing

[0912] Data processing: Preparing for AI analysis of image data

[0913] Output: Retrieval of analysis results

[0914] Step 3: Analyzing clothing data

[0915] server:

[0916] The AI ​​image analysis module processes the received image data and analyzes attributes such as the color, shape, material, brand, and style of the clothing.

[0917] Input: Image data of clothing

[0918] Data processing: Attribute extraction using AI image analysis module

[0919] Output: Clothing attribute information

[0920] server:

[0921] The analyzed attribute information is saved to a database. The saved information includes clothing identification IDs, attribute information, and user IDs.

[0922] Input: Clothing attribute information

[0923] Data processing: Attribute information stored in a database.

[0924] Output: Save complete flag

[0925] Step 4: Enter user information

[0926] Terminal:

[0927] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then taps the "Submit" button.

[0928] Input: Information such as TPO (Time, Place, Occasion), destination, weather, and style.

[0929] Output: Send input information

[0930] server:

[0931] Receive information entered by the user and save it to the database.

[0932] Input: Information such as TPO (Time, Place, Occasion), destination, weather, and style.

[0933] Data processing: Storing input information in a database.

[0934] Output: Save complete flag

[0935] Step 5: Generating Recommended Clothing

[0936] server:

[0937] The server retrieves data on the user's clothing from the database. The AI ​​styling module generates the optimal outfit combination based on the user's input regarding time, place, occasion, weather, and style.

[0938] Input: TPO (Time, Place, Occasion), weather, style, attribute information of user-owned clothing

[0939] Data processing: Optimal clothing generation using AI styling module

[0940] Output: Recommended clothing data

[0941] server:

[0942] The generated recommended clothing data is sent to the device.

[0943] Input: Recommended clothing data

[0944] Output: Send recommended clothing

[0945] Step 6: Recommended clothing display and selection

[0946] Terminal:

[0947] A list of recommended outfit combinations is displayed to the user. The user can review the details of each item and tap their chosen outfit to complete the confirmation.

[0948] Input: Recommended clothing data

[0949] Output: Data for the selected clothing

[0950] Step 7: Proposal from the shop

[0951] server:

[0952] Based on past choices and styles, it generates suggestions for new fashion items. It retrieves the latest product data from partner retailers and selects products that suit the user. This product information is then sent to the user's device.

[0953] Input: Past selection data, latest product data

[0954] Data processing: New item suggestion generation, product data acquisition.

[0955] Output: Send the proposed product list.

[0956] Step 8: View and purchase shop suggestions

[0957] Terminal:

[0958] The user is shown a list of suggested products, and can view detailed information about each product. When they select a product they wish to purchase and tap the "Purchase" button, they are redirected to the partner retailer's website or application.

[0959] Input: Proposed product list

[0960] Output: Redirect to the purchase page

[0961] Through the steps described above, this system can efficiently support users in receiving clothing suggestions and purchasing new fashion items.

[0962] (Application Example 1)

[0963] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0964] Traditional clothing suggestion systems can suggest the best outfits based on images taken by the user at home and other input information, but they lack the real-time information needed when choosing new clothes in a physical store. Therefore, users find it difficult to effectively coordinate their existing wardrobe with new purchases, resulting in a less-than-ideal shopping experience. Furthermore, the lack of support for immediate purchases in physical stores makes smooth purchasing difficult.

[0965] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0966] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images to extract clothing attribute information, and means for storing the extracted attribute information. This allows the user to receive suggestions for new clothing items in a physical store based on their existing clothing data, and to see coordinated outfits displayed on the spot. Furthermore, by including means for acquiring data from partner companies to suggest new products, and including payment means for purchasing suggested products in-store, the user can receive coordinated outfit suggestions and make immediate purchases in real time, enjoying a comfortable and efficient shopping experience.

[0967] "Means for receiving images taken by users" refers to a function that allows users to send images taken using their smartphones or cameras to the system, and for the system to receive those images.

[0968] "Means for analyzing received images and extracting clothing attribute information" refers to a function in which the system analyzes received image data using AI or image recognition technology to extract information such as the color, shape, material, brand, and style of the clothing.

[0969] "Means for saving extracted attribute information" refers to a function for recording the attribute information of clothing obtained through analysis into a storage device such as a database.

[0970] "A means for users to input TPO, weather, and style information" refers to a function that allows users to input information about specific situations, weather conditions, and preferred fashion styles into the system.

[0971] The "means of suggesting the optimal outfit" refers to a function that suggests the most suitable outfit combination based on the user's inputted TPO (Time, Place, Occasion), weather, and style information, as well as saved clothing attribute information.

[0972] "A means of displaying and allowing users to select clothing" refers to a function that visually presents the system with suggested clothing combinations to the user, allowing the user to select from among them.

[0973] "Means of acquiring data from partner companies" refers to a function that allows the system to acquire the latest product data from partner shops and companies in order to propose new products and fashion items.

[0974] "Means of providing purchase links" refers to functions that provide users with links or interfaces to purchase suggested new products, thereby supporting online shopping and in-store purchases.

[0975] "Methods implemented in physical stores" refers to a function that allows users to receive new clothing suggestions and check outfit combinations in real time while they are in a physical store.

[0976] "Payment methods" refers to the function that allows users to instantly purchase products offered within a store by completing the payment process. This function supports various payment methods such as credit cards, mobile payments, and digital wallets.

[0977] The system for implementing this invention comprises a series of means for receiving images taken by a user, analyzing those images to extract clothing attribute information, and storing this information. It also includes means for the user to input TPO (Time, Place, Occasion), weather, and style information, for which the most suitable clothing is suggested, and for the user to see and select the suggested clothing. Furthermore, it includes means for acquiring data from partner companies to suggest new products, for displaying the suggested new products, and for providing purchase links. As an important element, it also includes means for suggesting new clothing in a physical store based on the user's clothing data, for displaying coordinated outfits on the spot, and for payment methods for purchasing the suggested products in the store.

[0978] Processing details

[0979] 1. Device startup and user authentication:

[0980] The terminal uses a mobile device such as a smartphone or smart glasses, and the user logs in to the launched application. The username and password are sent to the authentication server. If authentication is successful, the server starts a session and retrieves user information. Specifically, authentication technologies such as OAuth 2.0 and JWT (JSON Web Token) are used.

[0981] 2. Image upload and analysis:

[0982] Users take pictures of new clothing items in a physical store using the camera on their smartphone or smart glasses. The device sends the image data to a server, which processes the images using an AI image analysis module to extract clothing attribute information (color, shape, material, brand, style). Deep learning technologies such as Convolutional Neural Networks (CNNs) are used.

[0983] 3. Storing attribute data and user information:

[0984] The extracted clothing attribute information is stored in a database. Relational databases or NoSQL databases are often used. The user then enters information such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual) into a form, which the server receives and stores.

[0985] 4. Outfit suggestions:

[0986] The server compares the stored user clothing data with newly entered information and uses an AI styling module to generate the optimal clothing combination. At this stage, the generative AI model and inference module previously used as training data are utilized.

[0987] 5. Displaying coordinated outfits and payment within physical stores:

[0988] The user's device displays suggested outfits. The user reviews the suggested outfits and, if they like them, proceeds with the purchase. Mobile payments utilize NFC (Near Field Communication) technology or QR code payments.

[0989] Specific example

[0990] Example 1: In-store image scanning and analysis

[0991] 1. Device: The user launches the app and logs in.

[0992] 2. Terminal: Take a picture of the red dress inside the store and send it to the server.

[0993] 3. Server: Sends the image to an AI image analysis module for analysis, determining that the color is red, the shape is a dress, and the material is silk.

[0994] Example 2: Outfit suggestions and purchase

[0995] 1. Terminal: The user enters TPO (formal dinner), weather (sunny), and preferred style (elegant).

[0996] 2. Server: Based on the analysis data and user information, it generates suggestions for white high heels and a gold clutch bag and sends them to the terminal.

[0997] 3. Device: Recommended outfits are displayed, and the user proceeds with mobile payment.

[0998] Examples of prompts for generative AI models

[0999] The prompt text for an application that recommends new items and outfit combinations in a physical store based on the user's clothing data:

[1000] 1. User Information:

[1001] Clothing owned: Blue shirt, black pants, white sneakers

[1002] 2. New items:

[1003] red dress

[1004] 3. Event Information:

[1005] TPO: Formal dinner

[1006] Weather: Sunny

[1007] Preferred style: Elegant

[1008] 4. Proposed outfit:

[1009] A blue shirt, black pants, white sneakers, and a clutch bag and jewelry to match the red dress.

[1010] Based on the above information, we will suggest the most suitable outfit and encourage users to purchase it at a physical store.

[1011] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1012] Step 1:

[1013] System startup and user authentication

[1014] Input: The user activates their smartphone or smart glasses and enters their username and password into the application.

[1015] Specific operation: The terminal sends user authentication information to the server. The server queries the authentication server to verify that the username and password match.

[1016] Output: If authentication is successful, a session is started and user information is sent from the server to the terminal. If it fails, an authentication error message is displayed on the terminal.

[1017] Step 2:

[1018] Upload image

[1019] Input: The user takes pictures of new clothing items in a physical store using the camera on their smartphone or smart glasses.

[1020] Specific operation: The device sends the captured image data to the server.

[1021] Output: Image data is received by the server and sent to the next analysis step.

[1022] Step 3:

[1023] Image analysis and attribute extraction

[1024] Input: Image data received by the server.

[1025] Specific operation: The server uses an AI image analysis module to process image data and extract attributes such as the color, shape, material, brand, and style of the clothing.

[1026] Output: The attribute information of the extracted clothing items is saved to the database.

[1027] Step 4:

[1028] Entering user information

[1029] Input: The user enters information into the application such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual).

[1030] Specific operation: The terminal sends the information entered by the user to the server.

[1031] Output: The server saves the received user's TPO, weather, and style information to the database.

[1032] Step 5:

[1033] Coordination generation

[1034] Input: Saved user clothing data and newly entered TPO, weather, and style information.

[1035] Specific operation: The server uses an AI styling module to match input information with stored data and generate the optimal clothing combination.

[1036] Output: The optimal clothing combination is sent to the device.

[1037] Step 6:

[1038] Display and select outfits

[1039] Input: Information on the optimal clothing combination sent from the server.

[1040] Specific operation: The device displays clothing suggestions to the user. The user makes a selection from these suggestions.

[1041] Output: Details of the clothing selected by the user are saved on the device.

[1042] Step 7:

[1043] Proposal for a new product

[1044] Input: User selection information, past selections, and style information.

[1045] Specific operation: The server retrieves new product data from partner vendors and suggests the most suitable new products based on the user's style and past choices.

[1046] Output: New product suggestion information is sent to the terminal.

[1047] Step 8:

[1048] Display and purchase of product suggestions.

[1049] Input: New product suggestion information sent from the server.

[1050] Specific operation: The terminal displays a list of new products and provides detailed information about each product. The user selects the product they wish to purchase and proceeds with the payment process.

[1051] Output: The selected items are displayed in the store, and the user completes the payment process. If a mobile payment system is used, the purchase record is saved on the server.

[1052] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1053] This invention is a system that uses a webcam or smartphone app to input images of the user's clothing into an AI, and then suggests the most suitable outfit based on the occasion, weather, style, and the user's emotions. Furthermore, it also supports the suggestion and purchase of new fashion items.

[1054] The basic configuration of this system includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, an emotion engine that recognizes the user's emotions, means for suggesting the most suitable outfit based on the input information, stored attribute information, and emotion information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, and means for displaying the suggested new products and providing purchase links.

[1055] Program Processing Description

[1056] 1. System startup and login

[1057] Terminal:

[1058] The user launches the app, enters their username and password on the login screen, and presses the login button.

[1059] server:

[1060] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[1061] 2. Upload images of clothing

[1062] Terminal:

[1063] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[1064] server:

[1065] The server receives the image data and sends it to the AI ​​image analysis module.

[1066] 3. Data analysis of clothing

[1067] server:

[1068] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[1069] 4. Entering user information

[1070] Terminal:

[1071] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[1072] server:

[1073] The server receives the information entered by the user.

[1074] 5. Acquisition and analysis of emotional information

[1075] Terminal:

[1076] The user activates the emotion recognition module and either shows their face to the camera or inputs voice.

[1077] server:

[1078] The emotion engine analyzes emotional information from the user's facial expressions and voice, and stores that information.

[1079] 6. Generating Recommended Clothing

[1080] server:

[1081] The server retrieves data on the user's clothing from the database. Based on the user's input regarding time, place, occasion, weather, style, and emotional state, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[1082] 7. Display and selection of recommended clothing.

[1083] Terminal:

[1084] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[1085] 8. Suggestions from the shop

[1086] server:

[1087] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[1088] 9. Displaying and purchasing shop suggestions

[1089] Terminal:

[1090] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[1091] Specific example

[1092] Example 1: Uploading images of clothing

[1093] Terminal:

[1094] Launch the app and log in. Select "Upload Clothing" from the menu, take a picture of a blue shirt, and upload it.

[1095] server:

[1096] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[1097] Example 2: Acquisition and analysis of emotional information

[1098] Terminal:

[1099] The user activates the emotion recognition module and displays their face towards the camera.

[1100] server:

[1101] The emotion engine analyzes facial expression data and determines if the user is feeling "joy." This information is then stored in a database.

[1102] Example 3: Generating Recommended Clothing

[1103] Terminal:

[1104] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[1105] server:

[1106] The system retrieves information about a blue shirt, black pants, and white sneakers from a database. An AI styling module then considers emotional information to suggest the optimal combination of these items. The overall coordination information is then sent to the app.

[1107] Example 4: Shop proposal

[1108] server:

[1109] Based on the user's past choices and situations in which they feel "joy," the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[1110] Terminal:

[1111] The suggested product list is displayed, and users can view detailed information. Clicking on a favorite item takes them to the purchase page. In this way, users can easily combine outfits that suit their style, and receive and purchase new item suggestions. By utilizing emotional information, more personalized suggestions become possible.

[1112] The following describes the processing flow.

[1113] Step 1:

[1114] Terminal:

[1115] The user launches the app, enters their username and password on the login screen, and presses the login button.

[1116] server:

[1117] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[1118] Step 2:

[1119] Terminal:

[1120] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[1121] server:

[1122] The server receives the image data and sends it to the AI ​​image analysis module.

[1123] Step 3:

[1124] server:

[1125] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[1126] Step 4:

[1127] Terminal:

[1128] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[1129] server:

[1130] The server receives the information entered by the user.

[1131] Step 5:

[1132] Terminal:

[1133] The user activates the emotion recognition module and either shows their face to the camera or inputs voice.

[1134] server:

[1135] The emotion engine analyzes emotional information from the user's facial expressions and voice, and stores that information.

[1136] Step 6:

[1137] server:

[1138] The server retrieves data on the user's clothing from the database. Based on the user's input regarding time, place, occasion, weather, style, and emotional state, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[1139] Step 7:

[1140] Terminal:

[1141] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[1142] Step 8:

[1143] server:

[1144] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[1145] Step 9:

[1146] Terminal:

[1147] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[1148] (Example 2)

[1149] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1150] Conventional clothing suggestion systems were limited to analyzing images of clothes owned by the user to obtain attribute information, and had the problem of not being able to make suggestions that appropriately considered information such as the user's emotions, TPO (Time, Place, Occasion), weather, and style. Furthermore, the suggestion of new fashion items and the provision of purchase links were limited, and it was not possible to improve the overall user experience.

[1151] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1152] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, means for acquiring and analyzing the user's emotional information using an emotional engine, means for suggesting the most suitable outfit based on the input information, stored attribute information, and acquired emotional information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, and means for displaying the suggested new products and providing purchase links. This enables personalized clothing suggestions that meet the diverse needs and circumstances of the user, as well as the smooth purchase of new fashion items.

[1153] "Means for receiving images taken by the user" refers to the functions of equipment and software that allow a user to send image data of their clothing, taken with a smartphone or camera, to a system and receive that data.

[1154] "Means for analyzing received images and extracting clothing attribute information" refers to a function that uses AI image analysis technology to automatically identify attributes such as the color, shape, material, brand, and style of clothing from received image data.

[1155] "Means for saving extracted attribute information" refers to a function for saving the clothing attribute information obtained through analysis to a storage device such as a database.

[1156] "Means for users to input TPO, weather, and style information" refers to an interface (e.g., a form, a dropdown menu, a checkbox, etc.) for users to input information such as events or situations (TPO), weather, and preferred style.

[1157] "Means for acquiring and analyzing user emotional information using an emotion engine" refers to a function that captures the user's facial expressions and voice using a camera and microphone, and analyzes the user's current emotional state using an emotion recognition algorithm.

[1158] "Means of suggesting the optimal outfit based on input information, stored attribute information, and acquired emotional information" refers to algorithms and software functions that integrate and comprehensively analyze user-inputted information such as TPO (Time, Place, Occasion), weather, and style, as well as stored clothing attribute information and user emotional information, to generate the optimal outfit combination.

[1159] "A means of displaying suggested outfits to the user and allowing them to select" refers to a function that displays the optimal outfit combinations generated by the system on the user interface, allowing the user to select from among them.

[1160] "Means of acquiring data from partner shops to propose new products" refers to a function that obtains the latest product information from partner online shops and stores and proposes new fashion items to users.

[1161] "A means of displaying suggested new products and providing purchase links" refers to a function that displays suggested new fashion items to the user in the user interface and provides a link to the purchase page for those products.

[1162] This invention's system uses a webcam or smartphone app to read images of the user's clothing into an AI, and then suggests the most suitable outfit based on TPO (Time, Place, Occasion), weather, style, and the user's emotions. Furthermore, it also supports the suggestion and purchase of new fashion items.

[1163] Basic configuration

[1164] This system includes the following means:

[1165] 1. Means for receiving images taken by the user

[1166] This refers to the function of devices and software that allow users to send image data of their clothing, taken with their smartphones or cameras, to a system, and receive that data.

[1167] 2. Means for analyzing received images and extracting clothing attribute information.

[1168] This function uses AI image analysis technology to automatically identify attributes such as the color, shape, material, brand, and style of clothing from received image data. Specifically, it can utilize machine learning frameworks such as TensorFlow and PyTorch.

[1169] 3. Means for saving extracted attribute information

[1170] This function allows you to save the clothing attribute information obtained through analysis to a database (e.g., MySQL, PostgreSQL).

[1171] 4. Means for users to input TPO, weather, and style information

[1172] This is an interface (e.g., a form, a dropdown menu, a checkbox, etc.) for users to input information such as the event or situation (TPO), weather, and preferred style.

[1173] 5. Means for acquiring and analyzing user emotional information using an emotion engine.

[1174] This feature uses a camera and microphone to capture the user's facial expressions and voice, and then analyzes the user's current emotional state using an emotion recognition algorithm. Specifically, it can utilize emotion recognition APIs such as FaceAPI and EmotionAPI.

[1175] 6. A means of suggesting the most suitable clothing based on the input information, stored attribute information, and acquired emotional information.

[1176] This refers to algorithms and software functions that integrate and comprehensively analyze user-entered information such as TPO (Time, Place, Occasion), weather, and style, as well as saved clothing attribute information and user sentiment information, to generate the optimal clothing combination. Specifically, algorithm implementations using Python or frameworks such as Django can be utilized.

[1177] 7. A means of displaying suggested clothing to the user and allowing them to select it.

[1178] This feature displays the system's generated optimal clothing combinations in the user interface (e.g., mobile app, web app), allowing the user to select from them.

[1179] 8. Means of obtaining data from partner shops in order to propose new products.

[1180] This function retrieves the latest product information from partner online shops and stores and suggests new fashion items to users.

[1181] 9. Means of displaying proposed new products and providing purchase links

[1182] This function displays suggested new fashion items to the user in the user interface and provides a link to the product's purchase page.

[1183] Specific example

[1184] Example 1: Uploading images of clothing

[1185] Terminal:

[1186] The user launches the app and logs in. From the menu, they select "Upload Clothing," take a picture of a blue shirt, and upload it.

[1187] server:

[1188] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[1189] Example 2: Acquisition and analysis of emotional information

[1190] Terminal:

[1191] The user activates the emotion recognition module and displays their face towards the camera.

[1192] server:

[1193] The emotion engine analyzes facial expression data and determines if the user is feeling "joy." This information is then stored in a database.

[1194] Example 3: Generating Recommended Clothing

[1195] Terminal:

[1196] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[1197] server:

[1198] The system retrieves information about a blue shirt, black pants, and white sneakers from a database. An AI styling module then considers emotional information to suggest the optimal combination of these items. The overall coordination information is then sent to the app.

[1199] Example 4: Shop proposal

[1200] server:

[1201] Based on the user's past choices and situations in which they feel "joy," the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[1202] Terminal:

[1203] The suggested product list is displayed, and users can view detailed information. Clicking on a favorite item takes them to the purchase page. In this way, users can easily combine outfits that suit their style, and receive and purchase new item suggestions. By utilizing emotional information, more personalized suggestions become possible.

[1204] Example of a prompt

[1205] "Please provide a user interface design proposal that prioritizes ease of use and visibility."

[1206] In this way, by using appropriate hardware and software, it is possible to realize a system that supports users in finding the optimal clothing to meet their diverse needs and in purchasing new fashion items.

[1207] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1208] Step 1: System startup and login

[1209] Terminal:

[1210] The user launches the app, and the login screen is displayed.

[1211] The user enters their username and password and clicks the "Login" button.

[1212] server:

[1213] The server receives the entered username and password.

[1214] The server queries the authentication server to authenticate the user.

[1215] Input: Username, Password

[1216] Data processing: Comparison with user information in the database

[1217] Output: Authentication success or failure result

[1218] If authentication is successful, the server starts a session, retrieves user information (e.g., past uploaded data and stored attribute information), and sends it to the device.

[1219] Specific actions:

[1220] When a user opens the app on their smartphone and enters their email address and password, that information is sent to the server. Once authenticated, the user's personalized home screen is displayed.

[1221] Step 2: Upload images of clothing

[1222] Terminal:

[1223] The user selects "Upload clothing" from the menu.

[1224] Press the "Start Camera" button to activate the camera.

[1225] The user takes a picture of their clothes and presses the "Upload" button.

[1226] server:

[1227] The server receives image data sent from the terminal.

[1228] Input: Image data

[1229] Data processing: Compression and conversion of image data

[1230] Output: Compressed image data

[1231] The image data is sent to the AI ​​image analysis module.

[1232] Specific actions:

[1233] When a user takes a picture of a blue shirt and uploads it to the system, the image data is sent to the server and image analysis begins.

[1234] Step 3: Analyzing clothing data

[1235] server:

[1236] The AI ​​image analysis module analyzes images of clothing and extracts attributes such as color, shape, material, brand, and style.

[1237] Input: Compressed image data

[1238] Data processing: AI-based image analysis (e.g., color recognition, shape recognition)

[1239] Output: Clothing attribute information (e.g., Color: Blue, Style: Long-sleeved, Material: Cotton)

[1240] The extracted attribute information is saved to the database.

[1241] Specific actions:

[1242] The AI ​​analyzes the image, automatically identifying detailed information such as the color, shape, and material of the blue shirt uploaded by the user, and saving it to the system's database.

[1243] Step 4: Enter user information

[1244] Terminal:

[1245] The user selects "Enter Styling Information" from the menu.

[1246] The user enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), preferred style (e.g., casual) into the form and presses the "Submit" button.

[1247] server:

[1248] Receive the information entered in the form.

[1249] Input: User's TPO (Time, Place, Occasion), weather, and style information

[1250] Data processing: Temporary storage of information

[1251] Output: Verification results of temporarily saved information

[1252] The received information is saved to a temporary data store.

[1253] Specific actions:

[1254] The user selects and enters their chosen picnic destination, the weather in the park, and their preferred style.

[1255] Step 5: Acquisition and analysis of emotional information

[1256] Terminal:

[1257] The user activates the emotion recognition module.

[1258] The user either shows their face to the camera or inputs voice.

[1259] server:

[1260] It receives facial expressions and voice data.

[1261] Input: Facial expression data, audio data

[1262] Data processing: Analysis using an emotion engine

[1263] Output: User emotion information (e.g., "joy")

[1264] The emotion engine analyzes data to identify and store the emotions the user is currently feeling.

[1265] Specific actions:

[1266] When a user smiles at the camera, the system analyzes that expression as "joy" and saves that information.

[1267] Step 6: Generating Recommended Clothing

[1268] server:

[1269] Retrieve data on the clothing owned by the user from the database (e.g., blue shirt, black pants, white sneakers).

[1270] Input: User's owned clothing data

[1271] Data processing: Generating appropriate combinations for each outfit.

[1272] Output: Recommended clothing combination (e.g., blue shirt, black pants, white sneakers)

[1273] Based on the user's input regarding time, place, occasion, weather, style, and emotional information, the AI ​​styling module generates the optimal outfit.

[1274] Send the suggested outfit combinations to the app.

[1275] Specific actions:

[1276] The server retrieves information about a blue shirt, black pants, and white sneakers from the database and suggests the most appropriate casual outfit, taking into account the occasion, time, place, and mood.

[1277] Step 7: Recommended clothing display and selection

[1278] Terminal:

[1279] A list of recommended clothing combinations will be displayed.

[1280] The user selects one outfit from the suggested options and then checks the details.

[1281] Tap the selected outfit to complete the confirmation.

[1282] Specific actions:

[1283] The user reviews the clothing combinations suggested by the app (blue shirt, black pants, white sneakers) and taps the one they like best.

[1284] Step 8: Suggestions from the shop

[1285] server:

[1286] Based on the user's chosen style and past selection data, new suggestions are generated.

[1287] Input: Past selection data, user style information

[1288] Data processing: Filtering and selecting new fashion items

[1289] Output: Suggested new items (e.g., hat, sunglasses)

[1290] The app retrieves the latest item information from partner shops and sends it to the app.

[1291] Specific actions:

[1292] Based on items the user has previously selected and their current styling information, the system suggests the latest hats, sunglasses, and other items obtained from partner shops.

[1293] Step 9: View and purchase shop suggestions

[1294] Terminal:

[1295] Display a list of suggested products.

[1296] Check detailed information about each product (price, brand, reviews, etc.).

[1297] After selecting the product you want to purchase and clicking the "Purchase" button, you will be redirected to the partner shop's website or application.

[1298] Specific actions:

[1299] The user clicks on a pair of sunglasses they like from the list of suggested products and checks the details. Once they decide to purchase, they click the "Purchase" button to proceed to the purchase page of the partner shop.

[1300] (Application Example 2)

[1301] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1302] In recent years, fashion choices have diversified according to users' styles and preferences, and choosing clothing based on TPO (time, place, and purpose) and weather has become particularly important. However, conventional systems have difficulty appropriately analyzing the attributes of a user's clothing and providing coordinated outfit suggestions that take into account the user's emotional information. Furthermore, there is a lack of effective means to suggest new products. As a result, users are unable to choose clothing that best suits their style and are dissatisfied with their purchases of new fashion items.

[1303] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1304] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information, stored attribute information, and emotional information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, means for displaying the suggested new products and providing purchase links, means for acquiring and analyzing emotional information, and means for suggesting new fashion items based on past selections. As a result, the user can easily choose the most suitable outfit from their existing wardrobe, and also easily receive personalized suggestions that take emotional information into account, as well as purchase new fashion items.

[1305] "Means for receiving images taken by a user" refers to functions or devices that allow a user to send images taken with a smartphone or camera to a system and receive those images.

[1306] "Means for analyzing received images and extracting clothing attribute information" refers to functions or devices that use AI or image analysis technology to extract attribute information such as the color, shape, material, brand, and style of clothing based on received images.

[1307] "Means for saving extracted attribute information" refers to functions or devices for saving the clothing attribute information obtained through analysis to a database or storage.

[1308] "Means for users to input TPO, weather, and style information" refers to interfaces or devices that allow users to input information about their intended use (time, place, purpose), weather, and preferred style into the system.

[1309] "A means of suggesting the optimal outfit based on input information, stored attribute information, and emotional information" refers to a function or device that generates the optimal combination from stored clothing attribute information based on the TPO, weather, style information, and emotional data entered by the user.

[1310] "Means for displaying and allowing users to select suggested clothing" refers to interfaces or devices that visually display generated clothing suggestions to the user, allowing the user to select from among them.

[1311] "Means of acquiring data from partner shops in order to propose new products" refers to functions and devices for acquiring data on the latest fashion items from partner online shops and retail stores.

[1312] "Means for displaying proposed new products and providing purchase links" refers to interfaces or devices that display information about newly acquired fashion items to the user and provide links for purchasing them.

[1313] "Means for acquiring and analyzing emotional information" refers to functions or devices that acquire and analyze a user's emotions at a given time, such as from their facial expressions or voice data.

[1314] "Means of suggesting new fashion items based on past choices" refers to functions or devices that recommend new fashion items based on the user's past clothing selection data and purchase history.

[1315] The system implementing this invention aims to suggest the most suitable clothing by taking images of the user's clothing, which are then analyzed by AI, and to also recommend new products. This system consists of three main elements: a server, a terminal, and the user.

[1316] Server roles and processing

[1317] The server performs the following roles:

[1318] 1. Receiving images taken by users: To receive images taken by users with their smartphones or cameras, the image data is processed using a web framework such as Flask.

[1319] 2. Image Analysis: The received images are analyzed to extract clothing attribute information. Specifically, image analysis libraries such as OpenCV are used to obtain information such as color, shape, material, brand, and style.

[1320] 3. Saving attribute information: The extracted attribute information is saved to a database. SQL or NoSQL databases are used as the database.

[1321] 4. Information Integration and Analysis: The system receives user-inputted TPO (Time, Place, and Occasion), weather, style information, and emotional information, and integrates and analyzes this information with stored clothing attribute data. This process utilizes generative AI models and emotional analysis APIs.

[1322] 5. Clothing Suggestions: Based on integrated information, the AI ​​styling module suggests the most suitable outfit for the user.

[1323] 6. New Product Suggestions: Obtain the latest product data from partner shops and recommend products based on the user's past choices and sentiment information.

[1324] In this way, the system provides users with suggestions for the most suitable clothing and recommendations for new products.

[1325] Terminal roles and processing

[1326] Smartphones and other devices perform the following roles:

[1327] 1. Image capture and transmission: The user uses their smartphone camera to take a picture of the clothing they are wearing. The captured image is sent to the server via the application.

[1328] 2. Information Input: Provide an interface for the user to input TPO (Time, Place, Purpose), weather, and style information. It also activates an emotion recognition module, either by capturing facial expressions with the camera or inputting voice.

[1329] 3. Receiving and displaying suggestions: The system receives and displays a list of optimal clothing suggestions sent from the server. The user reviews and selects from the suggested clothing combinations.

[1330] 4. Display of new products and provision of purchase links: The interface displays information about new products sent from the server and provides purchase links.

[1331] This allows the terminal to function as an interface with the user, handling information input and receiving / displaying suggestions.

[1332] User roles and operations

[1333] The user performs the following actions:

[1334] 1. Launching the application and logging in: First, launch the application and log in by entering your username and password on the login screen.

[1335] 2. Take and upload images: Select the "Upload clothing" option from the menu, activate your smartphone's camera, take a picture of your clothing, and click the "Upload" button.

[1336] 3. Entering Information: Select "Enter Styling Information" from the menu, enter the time, place, occasion, weather, and style information, and press the "Submit" button.

[1337] 4. Acquiring emotion information: Activate the emotion recognition module and either show your face to the camera or input voice.

[1338] 5. Review and Select Suggestions: Review the list of recommended clothing combinations and make your selection. Also, review the suggested new items and purchase the ones you like.

[1339] Examples of specific cases and prompt statements

[1340] Example 1: Uploading images of clothing

[1341] The user launches the application and logs in. From the menu, they select "Upload Clothing," take a picture of a blue shirt, and upload it.

[1342] Example 2: Acquisition of emotional information

[1343] The user activates the emotion recognition module and displays their face towards the camera.

[1344] Example of a prompt

[1345] 1. "I'm planning a picnic on a sunny day; could you suggest some casual outfits?"

[1346] 2. "Based on your current emotions, please suggest the best outfit using the clothes you own."

[1347] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1348] Step 1:

[1349] The user launches the application, enters their username and password on the login screen, and presses the login button. The server receives the username and password, authenticates the user, and starts a session. It retrieves user information and notifies the terminal of the successful login.

[1350] Input: Username, Password

[1351] Data processing and calculation: Username and password verification, session initiation.

[1352] Output: Login success notification

[1353] Step 2:

[1354] The user selects the "Upload Clothing" option from the menu, activates their smartphone's camera to take a picture of their clothing, and clicks the "Upload" button. The device sends the image data to the server, and the server receives the image.

[1355] Input: Captured image

[1356] Data processing and calculation: Receiving and saving images.

[1357] Output: Image save confirmation notification

[1358] Step 3:

[1359] The server uses an AI image analysis module to analyze received images and extract attribute information such as color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[1360] Input: Received image

[1361] Data processing and calculation: Image analysis, extraction of attribute information.

[1362] Output: Saving attribute information

[1363] Step 4:

[1364] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and presses the "Submit" button. The terminal sends the entered information to the server.

[1365] Input: TPO (Time, Place, Occasion), weather, style information

[1366] Data processing and calculation: Information reception

[1367] Output: Information storage, confirmation notification

[1368] Step 5:

[1369] The user activates the emotion recognition module and either shows their face to the camera or inputs voice. The device sends the image or voice data to the server, where the server's emotion engine analyzes it, extracts emotion information, and stores it in a database.

[1370] Input: User's facial expression image or audio data

[1371] Data processing and calculation: emotion analysis, extraction of emotional information.

[1372] Output: Storage of emotional information, confirmation notification

[1373] Step 6:

[1374] The server retrieves data on the user's clothing, the user's input regarding occasion (TPO), weather, style, and emotional state from the database. The AI ​​styling module then generates the optimal clothing combination based on this information and sends it to the application.

[1375] Input: Clothing data, occasion (TPO), weather, style information, emotional information

[1376] Data processing and calculation: Generating clothing combinations

[1377] Output: Suggestions for the best outfit

[1378] Step 7:

[1379] The device displays a list of recommended clothing combinations, and the user taps on a suggested outfit to view details and then taps on their chosen outfit to confirm.

[1380] Input: Suggestions for the best outfit

[1381] Data processing and calculation: Information display

[1382] Output: Confirmation of detailed information, notification of selection completion.

[1383] Step 8:

[1384] The server suggests new fashion items based on the user's chosen style and past selections. It retrieves the latest item information from partner shops and sends products that match the user's style to the application.

[1385] Input: Past selection data, partner shop data

[1386] Data processing and calculations: Proposal of new products

[1387] Output: Send new product information

[1388] Step 9:

[1389] The device displays a list of suggested products, and the user reviews detailed information about each product (price, brand, reviews, etc.), selects the product they wish to purchase, and presses the "Purchase" button. This redirects them to the partner shop's website or application.

[1390] Input: New product information

[1391] Data Processing / Calculation: Displaying Detailed Information

[1392] Output: Redirection to purchase link

[1393] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1394] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1395] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1396] [Third Embodiment]

[1397] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1398] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1399] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1400] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1401] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1402] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1403] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1404] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1405] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1406] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1407] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1408] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1409] This invention is a system that uses a webcam or smartphone app to load images of the user's clothing into AI, and then suggests the most suitable outfit based on the occasion, weather, and style. Furthermore, it also supports the suggestion and purchase of new fashion items.

[1410] The basic configuration of this system includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for saving the extracted attribute information, means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information and saved attribute information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops in order to suggest new products, and means for displaying the suggested new products and providing purchase links.

[1411] Program Processing Description

[1412] 1. System startup and login

[1413] Terminal:

[1414] The user launches the app, enters their username and password on the login screen, and presses the login button.

[1415] server:

[1416] The system receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[1417] 2. Upload images of clothing

[1418] Terminal:

[1419] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[1420] server:

[1421] The system receives image data and sends it to the AI ​​image analysis module.

[1422] 3. Data analysis of clothing

[1423] server:

[1424] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[1425] 4. Entering user information

[1426] Terminal:

[1427] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[1428] server:

[1429] Receives information entered by the user.

[1430] 5. Generating Recommended Clothing

[1431] server:

[1432] The system retrieves data on the user's clothing from a database. Based on the user's input regarding occasion, weather, and style, an AI styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[1433] 6. Display and selection of recommended clothing.

[1434] Terminal:

[1435] The system displays a list of recommended outfit combinations, and users can tap on a suggested outfit to view details. They can then tap on their chosen outfit to complete the confirmation.

[1436] 7. Suggestions from the shop

[1437] server:

[1438] Based on the user's chosen style and past selections, the app generates new suggestions. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[1439] 8. Viewing and purchasing shop suggestions

[1440] Terminal:

[1441] A list of suggested products is displayed, and detailed information (price, brand, reviews, etc.) can be viewed for each product. Selecting a product you wish to purchase and clicking the "Purchase" button will redirect you to the partner shop's website or application.

[1442] Specific example

[1443] Example 1: Uploading images of clothing

[1444] Terminal:

[1445] Launch the app and log in.

[1446] Select "Upload clothing," take a picture of the blue shirt, and upload it.

[1447] server:

[1448] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[1449] Example 2: Generating Recommended Clothing

[1450] Terminal:

[1451] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[1452] server:

[1453] The system retrieves information on a blue shirt, black pants, and white sneakers from a database. An AI styling module then suggests the optimal combination of these items based on the input data. The overall outfit information is then sent to the app.

[1454] Example 3: Shop proposal

[1455] server:

[1456] Based on the user's past choices and casual style, the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[1457] Terminal:

[1458] The suggested product list is displayed, and detailed information can be viewed. Clicking on a product you like will take you to the purchase page. In this way, users can easily combine outfits that suit their style, and new items can be suggested and purchased.

[1459] This system is designed to support users' busy lifestyles and help them use their time efficiently. It encourages users to make the most of their existing clothing while also providing suggestions for new fashion items, allowing them to always enjoy the latest styles.

[1460] The following describes the processing flow.

[1461] Step 1:

[1462] Terminal:

[1463] The user launches the app, enters their username and password on the login screen, and presses the login button.

[1464] server:

[1465] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[1466] Step 2:

[1467] Terminal:

[1468] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[1469] server:

[1470] The server receives the image data and sends it to the AI ​​image analysis module.

[1471] Step 3:

[1472] server:

[1473] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[1474] Step 4:

[1475] Terminal:

[1476] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[1477] server:

[1478] The server receives the information entered by the user.

[1479] Step 5:

[1480] server:

[1481] The server retrieves data on the user's clothing from the database. Based on the user's input regarding occasion, weather, and style, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[1482] Step 6:

[1483] Terminal:

[1484] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[1485] Step 7:

[1486] server:

[1487] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[1488] Step 8:

[1489] Terminal:

[1490] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[1491] (Example 1)

[1492] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1493] Conventional clothing suggestion systems often fail to adequately personalize user outfit combinations and suggest new items, posing a challenge to improving user satisfaction. Furthermore, the lack of automatic generation of optimal outfits based on time, place, occasion, weather, and preferred style meant they could not efficiently support users' busy lifestyles.

[1494] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1495] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images to extract clothing attribute information, and means for storing the extracted attribute information. This allows for detailed storage of information about the user's clothing in a database, enabling analysis based on individual attributes. The invention also includes means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information and stored attribute information, means for displaying the suggested outfits to the user and allowing them to select one, means for generating the most suitable outfit using a generative AI model based on the TPO, weather, and style information entered by the user, and means for suggesting new fashion items based on the user's past choices and style. This enables the suggestion of the most suitable outfit tailored to the user's individual needs and the constant suggestion of new styles, significantly improving user satisfaction.

[1496] A "user" is an individual or group that uses this system.

[1497] "Captured images" refer to image data acquired by the user using the camera function of the system.

[1498] "Means of receiving" refers to the function or device that allows a server to receive data sent by a user.

[1499] "Means of analysis" refers to a function or technology used by a system to analyze received image data and extract specific information.

[1500] "Clothing attribute information" refers to information about the characteristics of clothing, such as color, shape, material, brand, and style.

[1501] "Means of storage" refers to a function or device for storing extracted information in a database or storage device.

[1502] "TPO" is an abbreviation for Time, Place, and Occasion, and it is a set of criteria for determining appropriate attire for a particular situation.

[1503] "Style information" refers to information about the type and design of clothing based on the user's preferences and current trends.

[1504] "Means of suggesting the optimal outfit" refers to a function or technology that presents clothing combinations suitable for a user based on information entered by the user and stored attribute information.

[1505] "Means of displaying and allowing selection" refers to a function or device that visually presents suggested clothing to the user and allows them to make a selection from among them.

[1506] A "partner retailer" is a store or company that collaborates with this system to provide product data and propose new products to users.

[1507] A "generative AI model" refers to an algorithm or technology that uses artificial intelligence to generate the most suitable clothing based on input data.

[1508] "Means of providing a purchase link" refers to a function or technology that displays a link so that a user can access the purchase page of a suggested product.

[1509] "Past choices" refers to clothing and styling information that the user previously selected within the system.

[1510] This invention is a system that uses a webcam or smartphone app to read images of the user's clothing into an AI, and then suggests the most suitable outfit based on the occasion, weather, and style. Furthermore, it also supports the suggestion and purchase of new fashion items.

[1511] System Configuration

[1512] This system includes the following components:

[1513] Means for receiving images of clothing

[1514] A method for analyzing received images and extracting clothing attribute information.

[1515] Means for saving extracted attribute information

[1516] A means for users to input TPO (Time, Place, Occasion), weather, and style information.

[1517] A method for suggesting the most suitable clothing based on input information and stored attribute information.

[1518] A means of displaying suggested clothing to the user and allowing them to select from it.

[1519] Means of acquiring data from partner retailers in order to propose new products.

[1520] A means of displaying proposed new products and providing purchase links.

[1521] A method for generating the optimal outfit using a generative AI model based on user-inputted information regarding time, place, occasion, weather, and style.

[1522] A method for suggesting new fashion items based on the user's past choices and style.

[1523] Program processing flow

[1524] The system program operates in the following sequence:

[1525] 1. System startup and login

[1526] Terminal:

[1527] The user launches the app, enters their username and password on the login screen, and presses the login button.

[1528] server:

[1529] The server receives the username and password, queries the authentication server, and performs authentication. If authentication is successful, it generates a session ID and retrieves user information.

[1530] 2. Upload images of clothing

[1531] Terminal:

[1532] The user selects the "Upload Clothing" option from the menu, activates the camera, takes a picture of the clothing, and taps the "Upload" button.

[1533] server:

[1534] The server receives the image data and sends it to the AI ​​image analysis module.

[1535] 3. Data analysis of clothing

[1536] server:

[1537] The AI ​​image analysis module processes image data and analyzes attributes such as the color, shape, material, brand, and style of the clothing.

[1538] server:

[1539] The analyzed attribute information is saved to the database.

[1540] 4. Entering user information

[1541] Terminal:

[1542] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and taps the "Submit" button.

[1543] server:

[1544] Receive information entered by the user and save it to the database.

[1545] 5. Generating Recommended Clothing

[1546] server:

[1547] The server retrieves data on the user's clothing from the database. The AI ​​styling module generates the optimal outfit combination based on the inputted TPO (Time, Place, Occasion), weather, and style information.

[1548] server:

[1549] The generated clothing data is sent to the terminal.

[1550] 6. Display and selection of recommended clothing.

[1551] Terminal:

[1552] The suggested outfits are displayed to the user in a list, and the user can view the details of each item. The user taps the selected outfit to complete the confirmation.

[1553] 7. Suggestions from the shop

[1554] server:

[1555] Based on the user's chosen style and past selection data, the system generates suggestions for new fashion items. It retrieves the latest product data from partner retailers, selects products that suit the user, and sends them to their device.

[1556] 8. Viewing and purchasing shop suggestions

[1557] Terminal:

[1558] The system displays a list of suggested products, allowing users to view detailed information about each item. When a user selects a product they wish to purchase and clicks the "Buy" button, they are redirected to the partner retailer's website or application.

[1559] Specific example

[1560] Example 1: Uploading images of clothing

[1561] Terminal:

[1562] The user launches the app and logs in. They select "Upload clothing," take a photo of a blue shirt, and click the "Upload" button.

[1563] server:

[1564] The server receives the image and sends it to an AI image analysis module. It identifies the color as blue, the shape as long-sleeved, and the material as cotton, and stores this information in a database.

[1565] Example 2: Generating Recommended Clothing

[1566] Terminal:

[1567] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[1568] server:

[1569] The server retrieves information about a blue shirt, black pants, and white sneakers from the database. The AI ​​styling module then suggests the optimal combination of these items based on the input data. The overall outfit information is then sent to the app.

[1570] Example 3: Shop proposal

[1571] server:

[1572] Based on the user's past choices and casual style, the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner retailers and sends it to the app.

[1573] Terminal:

[1574] View the suggested product list and check the details. Click on a product you like to go to the purchase page.

[1575] Example of a prompt

[1576] "What's the perfect outfit for a picnic? Something casual for a sunny day."

[1577] "Based on styles you've chosen in the past, please suggest new items that are suitable for today's weather."

[1578] In summary, this system is designed to efficiently support users' busy lifestyles, encourage them to make the most of their existing clothing, and provide suggestions for new fashion items.

[1579] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1580] Step 1: System startup and login

[1581] Terminal:

[1582] The user taps the app on their smartphone to launch it. The launch screen appears, followed by the login screen. The user enters their username and password on the login screen and taps the login button.

[1583] Input: Username, Password

[1584] Output: Sending authentication information

[1585] server:

[1586] The server receives the username and password. It queries the authentication server and compares the received authentication information with the database information. If authentication is successful, it generates a session ID and retrieves user information (name, profile picture, etc.). If authentication fails, it generates an error message and sends it to the terminal.

[1587] Input: Username, Password

[1588] Data processing: Verify authentication information in the database.

[1589] Output: Session ID, User information (if authentication is successful), Error message (if authentication fails)

[1590] Step 2: Upload images of clothing

[1591] Terminal:

[1592] The user selects the "Upload Clothing" option from the menu and taps the "Launch Camera" button. The camera launches, and the user takes a picture of their clothing. After taking the picture, tap the "Upload" button.

[1593] Input: Image of clothing

[1594] Output: Sending image data

[1595] server:

[1596] The server receives the image data and sends it to the AI ​​image analysis module.

[1597] Input: Image data of clothing

[1598] Data processing: Preparing for AI analysis of image data

[1599] Output: Retrieval of analysis results

[1600] Step 3: Analyzing clothing data

[1601] server:

[1602] The AI ​​image analysis module processes the received image data and analyzes attributes such as the color, shape, material, brand, and style of the clothing.

[1603] Input: Image data of clothing

[1604] Data processing: Attribute extraction using AI image analysis module

[1605] Output: Clothing attribute information

[1606] server:

[1607] The analyzed attribute information is saved to a database. The saved information includes clothing identification IDs, attribute information, and user IDs.

[1608] Input: Clothing attribute information

[1609] Data processing: Attribute information stored in a database.

[1610] Output: Save complete flag

[1611] Step 4: Enter user information

[1612] Terminal:

[1613] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then taps the "Submit" button.

[1614] Input: Information such as TPO (Time, Place, Occasion), destination, weather, and style.

[1615] Output: Send input information

[1616] server:

[1617] Receive information entered by the user and save it to the database.

[1618] Input: Information such as TPO (Time, Place, Occasion), destination, weather, and style.

[1619] Data processing: Storing input information in a database.

[1620] Output: Save complete flag

[1621] Step 5: Generating Recommended Clothing

[1622] server:

[1623] The server retrieves data on the user's clothing from the database. The AI ​​styling module generates the optimal outfit combination based on the user's input regarding time, place, occasion, weather, and style.

[1624] Input: TPO (Time, Place, Occasion), weather, style, attribute information of user-owned clothing

[1625] Data processing: Optimal clothing generation using AI styling module

[1626] Output: Recommended clothing data

[1627] server:

[1628] The generated recommended clothing data is sent to the device.

[1629] Input: Recommended clothing data

[1630] Output: Send recommended clothing

[1631] Step 6: Recommended clothing display and selection

[1632] Terminal:

[1633] A list of recommended outfit combinations is displayed to the user. The user can review the details of each item and tap their chosen outfit to complete the confirmation.

[1634] Input: Recommended clothing data

[1635] Output: Data for the selected clothing

[1636] Step 7: Proposal from the shop

[1637] server:

[1638] Based on past choices and styles, it generates suggestions for new fashion items. It retrieves the latest product data from partner retailers and selects products that suit the user. This product information is then sent to the user's device.

[1639] Input: Past selection data, latest product data

[1640] Data processing: New item suggestion generation, product data acquisition.

[1641] Output: Send the proposed product list.

[1642] Step 8: View and purchase shop suggestions

[1643] Terminal:

[1644] The user is shown a list of suggested products, and can view detailed information about each product. When they select a product they wish to purchase and tap the "Purchase" button, they are redirected to the partner retailer's website or application.

[1645] Input: Proposed product list

[1646] Output: Redirect to the purchase page

[1647] Through the steps described above, this system can efficiently support users in receiving clothing suggestions and purchasing new fashion items.

[1648] (Application Example 1)

[1649] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1650] Traditional clothing suggestion systems can suggest the best outfits based on images taken by the user at home and other input information, but they lack the real-time information needed when choosing new clothes in a physical store. Therefore, users find it difficult to effectively coordinate their existing wardrobe with new purchases, resulting in a less-than-ideal shopping experience. Furthermore, the lack of support for immediate purchases in physical stores makes smooth purchasing difficult.

[1651] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1652] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images to extract clothing attribute information, and means for storing the extracted attribute information. This allows the user to receive suggestions for new clothing items in a physical store based on their existing clothing data, and to see coordinated outfits displayed on the spot. Furthermore, by including means for acquiring data from partner companies to suggest new products, and including payment means for purchasing suggested products in-store, the user can receive coordinated outfit suggestions and make immediate purchases in real time, enjoying a comfortable and efficient shopping experience.

[1653] "Means for receiving images taken by users" refers to a function that allows users to send images taken using their smartphones or cameras to the system, and for the system to receive those images.

[1654] "Means for analyzing received images and extracting clothing attribute information" refers to a function in which the system analyzes received image data using AI or image recognition technology to extract information such as the color, shape, material, brand, and style of the clothing.

[1655] "Means for saving extracted attribute information" refers to a function for recording the attribute information of clothing obtained through analysis into a storage device such as a database.

[1656] "A means for users to input TPO, weather, and style information" refers to a function that allows users to input information about specific situations, weather conditions, and preferred fashion styles into the system.

[1657] The "means of suggesting the optimal outfit" refers to a function that suggests the most suitable outfit combination based on the user's inputted TPO (Time, Place, Occasion), weather, and style information, as well as saved clothing attribute information.

[1658] "A means of displaying and allowing users to select clothing" refers to a function that visually presents the system with suggested clothing combinations to the user, allowing the user to select from among them.

[1659] "Means of acquiring data from partner companies" refers to a function that allows the system to acquire the latest product data from partner shops and companies in order to propose new products and fashion items.

[1660] "Means of providing purchase links" refers to functions that provide users with links or interfaces to purchase suggested new products, thereby supporting online shopping and in-store purchases.

[1661] "Methods implemented in physical stores" refers to a function that allows users to receive new clothing suggestions and check outfit combinations in real time while they are in a physical store.

[1662] "Payment methods" refers to the function that allows users to instantly purchase products offered within a store by completing the payment process. This function supports various payment methods such as credit cards, mobile payments, and digital wallets.

[1663] The system for implementing this invention comprises a series of means for receiving images taken by a user, analyzing those images to extract clothing attribute information, and storing this information. It also includes means for the user to input TPO (Time, Place, Occasion), weather, and style information, for which the most suitable clothing is suggested, and for the user to see and select the suggested clothing. Furthermore, it includes means for acquiring data from partner companies to suggest new products, for displaying the suggested new products, and for providing purchase links. As an important element, it also includes means for suggesting new clothing in a physical store based on the user's clothing data, for displaying coordinated outfits on the spot, and for payment methods for purchasing the suggested products in the store.

[1664] Processing details

[1665] 1. Device startup and user authentication:

[1666] The terminal uses a mobile device such as a smartphone or smart glasses, and the user logs in to the launched application. The username and password are sent to the authentication server. If authentication is successful, the server starts a session and retrieves user information. Specifically, authentication technologies such as OAuth 2.0 and JWT (JSON Web Token) are used.

[1667] 2. Image upload and analysis:

[1668] Users take pictures of new clothing items in a physical store using the camera on their smartphone or smart glasses. The device sends the image data to a server, which processes the images using an AI image analysis module to extract clothing attribute information (color, shape, material, brand, style). Deep learning technologies such as Convolutional Neural Networks (CNNs) are used.

[1669] 3. Storing attribute data and user information:

[1670] The extracted clothing attribute information is stored in a database. Relational databases or NoSQL databases are often used. The user then enters information such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual) into a form, which the server receives and stores.

[1671] 4. Outfit suggestions:

[1672] The server compares the stored user clothing data with newly entered information and uses an AI styling module to generate the optimal clothing combination. At this stage, the generative AI model and inference module previously used as training data are utilized.

[1673] 5. Displaying coordinated outfits and payment within physical stores:

[1674] The user's device displays suggested outfits. The user reviews the suggested outfits and, if they like them, proceeds with the purchase. Mobile payments utilize NFC (Near Field Communication) technology or QR code payments.

[1675] Specific example

[1676] Example 1: In-store image scanning and analysis

[1677] 1. Device: The user launches the app and logs in.

[1678] 2. Terminal: Take a picture of the red dress inside the store and send it to the server.

[1679] 3. Server: Sends the image to an AI image analysis module for analysis, determining that the color is red, the shape is a dress, and the material is silk.

[1680] Example 2: Outfit suggestions and purchase

[1681] 1. Terminal: The user enters TPO (formal dinner), weather (sunny), and preferred style (elegant).

[1682] 2. Server: Based on the analysis data and user information, it generates suggestions for white high heels and a gold clutch bag and sends them to the terminal.

[1683] 3. Device: Recommended outfits are displayed, and the user proceeds with mobile payment.

[1684] Examples of prompts for generative AI models

[1685] The prompt text for an application that recommends new items and outfit combinations in a physical store based on the user's clothing data:

[1686] 1. User Information:

[1687] Clothing owned: Blue shirt, black pants, white sneakers

[1688] 2. New items:

[1689] red dress

[1690] 3. Event Information:

[1691] TPO: Formal dinner

[1692] Weather: Sunny

[1693] Preferred style: Elegant

[1694] 4. Proposed outfit:

[1695] A blue shirt, black pants, white sneakers, and a clutch bag and jewelry to match the red dress.

[1696] Based on the above information, we will suggest the most suitable outfit and encourage users to purchase it at a physical store.

[1697] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1698] Step 1:

[1699] System startup and user authentication

[1700] Input: The user activates their smartphone or smart glasses and enters their username and password into the application.

[1701] Specific operation: The terminal sends user authentication information to the server. The server queries the authentication server to verify that the username and password match.

[1702] Output: If authentication is successful, a session is started and user information is sent from the server to the terminal. If it fails, an authentication error message is displayed on the terminal.

[1703] Step 2:

[1704] Upload image

[1705] Input: The user takes pictures of new clothing items in a physical store using the camera on their smartphone or smart glasses.

[1706] Specific operation: The device sends the captured image data to the server.

[1707] Output: Image data is received by the server and sent to the next analysis step.

[1708] Step 3:

[1709] Image analysis and attribute extraction

[1710] Input: Image data received by the server.

[1711] Specific operation: The server uses an AI image analysis module to process image data and extract attributes such as the color, shape, material, brand, and style of the clothing.

[1712] Output: The attribute information of the extracted clothing items is saved to the database.

[1713] Step 4:

[1714] Entering user information

[1715] Input: The user enters information into the application such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual).

[1716] Specific operation: The terminal sends the information entered by the user to the server.

[1717] Output: The server saves the received user's TPO, weather, and style information to the database.

[1718] Step 5:

[1719] Coordination generation

[1720] Input: Saved user clothing data and newly entered TPO, weather, and style information.

[1721] Specific operation: The server uses an AI styling module to match input information with stored data and generate the optimal clothing combination.

[1722] Output: The optimal clothing combination is sent to the device.

[1723] Step 6:

[1724] Display and select outfits

[1725] Input: Information on the optimal clothing combination sent from the server.

[1726] Specific operation: The device displays clothing suggestions to the user. The user makes a selection from these suggestions.

[1727] Output: Details of the clothing selected by the user are saved on the device.

[1728] Step 7:

[1729] Proposal for a new product

[1730] Input: User selection information, past selections, and style information.

[1731] Specific operation: The server retrieves new product data from partner vendors and suggests the most suitable new products based on the user's style and past choices.

[1732] Output: New product suggestion information is sent to the terminal.

[1733] Step 8:

[1734] Display and purchase of product suggestions.

[1735] Input: New product suggestion information sent from the server.

[1736] Specific operation: The terminal displays a list of new products and provides detailed information about each product. The user selects the product they wish to purchase and proceeds with the payment process.

[1737] Output: The selected items are displayed in the store, and the user completes the payment process. If a mobile payment system is used, the purchase record is saved on the server.

[1738] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1739] This invention is a system that uses a webcam or smartphone app to input images of the user's clothing into an AI, and then suggests the most suitable outfit based on the occasion, weather, style, and the user's emotions. Furthermore, it also supports the suggestion and purchase of new fashion items.

[1740] The basic configuration of this system includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, an emotion engine that recognizes the user's emotions, means for suggesting the most suitable outfit based on the input information, stored attribute information, and emotion information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, and means for displaying the suggested new products and providing purchase links.

[1741] Program Processing Description

[1742] 1. System startup and login

[1743] Terminal:

[1744] The user launches the app, enters their username and password on the login screen, and presses the login button.

[1745] server:

[1746] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[1747] 2. Upload images of clothing

[1748] Terminal:

[1749] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[1750] server:

[1751] The server receives the image data and sends it to the AI ​​image analysis module.

[1752] 3. Data analysis of clothing

[1753] server:

[1754] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[1755] 4. Entering user information

[1756] Terminal:

[1757] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[1758] server:

[1759] The server receives the information entered by the user.

[1760] 5. Acquisition and analysis of emotional information

[1761] Terminal:

[1762] The user activates the emotion recognition module and either shows their face to the camera or inputs voice.

[1763] server:

[1764] The emotion engine analyzes emotional information from the user's facial expressions and voice, and stores that information.

[1765] 6. Generating Recommended Clothing

[1766] server:

[1767] The server retrieves data on the user's clothing from the database. Based on the user's input regarding time, place, occasion, weather, style, and emotional state, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[1768] 7. Display and selection of recommended clothing.

[1769] Terminal:

[1770] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[1771] 8. Suggestions from the shop

[1772] server:

[1773] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[1774] 9. Displaying and purchasing shop suggestions

[1775] Terminal:

[1776] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[1777] Specific example

[1778] Example 1: Uploading images of clothing

[1779] Terminal:

[1780] Launch the app and log in. Select "Upload Clothing" from the menu, take a picture of a blue shirt, and upload it.

[1781] server:

[1782] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[1783] Example 2: Acquisition and analysis of emotional information

[1784] Terminal:

[1785] The user activates the emotion recognition module and displays their face towards the camera.

[1786] server:

[1787] The emotion engine analyzes facial expression data and determines if the user is feeling "joy." This information is then stored in a database.

[1788] Example 3: Generating Recommended Clothing

[1789] Terminal:

[1790] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[1791] server:

[1792] The system retrieves information about a blue shirt, black pants, and white sneakers from a database. An AI styling module then considers emotional information to suggest the optimal combination of these items. The overall coordination information is then sent to the app.

[1793] Example 4: Shop proposal

[1794] server:

[1795] Based on the user's past choices and situations in which they feel "joy," the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[1796] Terminal:

[1797] The suggested product list is displayed, and users can view detailed information. Clicking on a favorite item takes them to the purchase page. In this way, users can easily combine outfits that suit their style, and receive and purchase new item suggestions. By utilizing emotional information, more personalized suggestions become possible.

[1798] The following describes the processing flow.

[1799] Step 1:

[1800] Terminal:

[1801] The user launches the app, enters their username and password on the login screen, and presses the login button.

[1802] server:

[1803] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[1804] Step 2:

[1805] Terminal:

[1806] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[1807] server:

[1808] The server receives the image data and sends it to the AI ​​image analysis module.

[1809] Step 3:

[1810] server:

[1811] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[1812] Step 4:

[1813] Terminal:

[1814] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[1815] server:

[1816] The server receives the information entered by the user.

[1817] Step 5:

[1818] Terminal:

[1819] The user activates the emotion recognition module and either shows their face to the camera or inputs voice.

[1820] server:

[1821] The emotion engine analyzes emotional information from the user's facial expressions and voice, and stores that information.

[1822] Step 6:

[1823] server:

[1824] The server retrieves data on the user's clothing from the database. Based on the user's input regarding time, place, occasion, weather, style, and emotional state, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[1825] Step 7:

[1826] Terminal:

[1827] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[1828] Step 8:

[1829] server:

[1830] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[1831] Step 9:

[1832] Terminal:

[1833] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[1834] (Example 2)

[1835] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1836] Conventional clothing suggestion systems were limited to analyzing images of clothes owned by the user to obtain attribute information, and had the problem of not being able to make suggestions that appropriately considered information such as the user's emotions, TPO (Time, Place, Occasion), weather, and style. Furthermore, the suggestion of new fashion items and the provision of purchase links were limited, and it was not possible to improve the overall user experience.

[1837] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1838] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, means for acquiring and analyzing the user's emotional information using an emotional engine, means for suggesting the most suitable outfit based on the input information, stored attribute information, and acquired emotional information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, and means for displaying the suggested new products and providing purchase links. This enables personalized clothing suggestions that meet the diverse needs and circumstances of the user, as well as the smooth purchase of new fashion items.

[1839] "Means for receiving images taken by the user" refers to the functions of equipment and software that allow a user to send image data of their clothing, taken with a smartphone or camera, to a system and receive that data.

[1840] "Means for analyzing received images and extracting clothing attribute information" refers to a function that uses AI image analysis technology to automatically identify attributes such as the color, shape, material, brand, and style of clothing from received image data.

[1841] "Means for saving extracted attribute information" refers to a function for saving the clothing attribute information obtained through analysis to a storage device such as a database.

[1842] "Means for users to input TPO, weather, and style information" refers to an interface (e.g., a form, a dropdown menu, a checkbox, etc.) for users to input information such as events or situations (TPO), weather, and preferred style.

[1843] "Means for acquiring and analyzing user emotional information using an emotion engine" refers to a function that captures the user's facial expressions and voice using a camera and microphone, and analyzes the user's current emotional state using an emotion recognition algorithm.

[1844] "Means of suggesting the optimal outfit based on input information, stored attribute information, and acquired emotional information" refers to algorithms and software functions that integrate and comprehensively analyze user-inputted information such as TPO (Time, Place, Occasion), weather, and style, as well as stored clothing attribute information and user emotional information, to generate the optimal outfit combination.

[1845] "A means of displaying suggested outfits to the user and allowing them to select" refers to a function that displays the optimal outfit combinations generated by the system on the user interface, allowing the user to select from among them.

[1846] "Means of acquiring data from partner shops to propose new products" refers to a function that obtains the latest product information from partner online shops and stores and proposes new fashion items to users.

[1847] "A means of displaying suggested new products and providing purchase links" refers to a function that displays suggested new fashion items to the user in the user interface and provides a link to the purchase page for those products.

[1848] This invention's system uses a webcam or smartphone app to read images of the user's clothing into an AI, and then suggests the most suitable outfit based on TPO (Time, Place, Occasion), weather, style, and the user's emotions. Furthermore, it also supports the suggestion and purchase of new fashion items.

[1849] Basic configuration

[1850] This system includes the following means:

[1851] 1. Means for receiving images taken by the user

[1852] This refers to the function of devices and software that allow users to send image data of their clothing, taken with their smartphones or cameras, to a system, and receive that data.

[1853] 2. Means for analyzing received images and extracting clothing attribute information.

[1854] This function uses AI image analysis technology to automatically identify attributes such as the color, shape, material, brand, and style of clothing from received image data. Specifically, it can utilize machine learning frameworks such as TensorFlow and PyTorch.

[1855] 3. Means for saving extracted attribute information

[1856] This function allows you to save the clothing attribute information obtained through analysis to a database (e.g., MySQL, PostgreSQL).

[1857] 4. Means for users to input TPO, weather, and style information

[1858] This is an interface (e.g., a form, a dropdown menu, a checkbox, etc.) for users to input information such as the event or situation (TPO), weather, and preferred style.

[1859] 5. Means for acquiring and analyzing user emotional information using an emotion engine.

[1860] This feature uses a camera and microphone to capture the user's facial expressions and voice, and then analyzes the user's current emotional state using an emotion recognition algorithm. Specifically, it can utilize emotion recognition APIs such as FaceAPI and EmotionAPI.

[1861] 6. A means of suggesting the most suitable clothing based on the input information, stored attribute information, and acquired emotional information.

[1862] This refers to algorithms and software functions that integrate and comprehensively analyze user-entered information such as TPO (Time, Place, Occasion), weather, and style, as well as saved clothing attribute information and user sentiment information, to generate the optimal clothing combination. Specifically, algorithm implementations using Python or frameworks such as Django can be utilized.

[1863] 7. A means of displaying suggested clothing to the user and allowing them to select it.

[1864] This feature displays the system's generated optimal clothing combinations in the user interface (e.g., mobile app, web app), allowing the user to select from them.

[1865] 8. Means of obtaining data from partner shops in order to propose new products.

[1866] This function retrieves the latest product information from partner online shops and stores and suggests new fashion items to users.

[1867] 9. Means of displaying proposed new products and providing purchase links

[1868] This function displays suggested new fashion items to the user in the user interface and provides a link to the product's purchase page.

[1869] Specific example

[1870] Example 1: Uploading images of clothing

[1871] Terminal:

[1872] The user launches the app and logs in. From the menu, they select "Upload Clothing," take a picture of a blue shirt, and upload it.

[1873] server:

[1874] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[1875] Example 2: Acquisition and analysis of emotional information

[1876] Terminal:

[1877] The user activates the emotion recognition module and displays their face towards the camera.

[1878] server:

[1879] The emotion engine analyzes facial expression data and determines if the user is feeling "joy." This information is then stored in a database.

[1880] Example 3: Generating Recommended Clothing

[1881] Terminal:

[1882] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[1883] server:

[1884] The system retrieves information about a blue shirt, black pants, and white sneakers from a database. An AI styling module then considers emotional information to suggest the optimal combination of these items. The overall coordination information is then sent to the app.

[1885] Example 4: Shop proposal

[1886] server:

[1887] Based on the user's past choices and situations in which they feel "joy," the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[1888] Terminal:

[1889] The suggested product list is displayed, and users can view detailed information. Clicking on a favorite item takes them to the purchase page. In this way, users can easily combine outfits that suit their style, and receive and purchase new item suggestions. By utilizing emotional information, more personalized suggestions become possible.

[1890] Example of a prompt

[1891] "Please provide a user interface design proposal that prioritizes ease of use and visibility."

[1892] In this way, by using appropriate hardware and software, it is possible to realize a system that supports users in finding the optimal clothing to meet their diverse needs and in purchasing new fashion items.

[1893] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1894] Step 1: System startup and login

[1895] Terminal:

[1896] The user launches the app, and the login screen is displayed.

[1897] The user enters their username and password and clicks the "Login" button.

[1898] server:

[1899] The server receives the entered username and password.

[1900] The server queries the authentication server to authenticate the user.

[1901] Input: Username, Password

[1902] Data processing: Comparison with user information in the database

[1903] Output: Authentication success or failure result

[1904] If authentication is successful, the server starts a session, retrieves user information (e.g., past uploaded data and stored attribute information), and sends it to the device.

[1905] Specific actions:

[1906] When a user opens the app on their smartphone and enters their email address and password, that information is sent to the server. Once authenticated, the user's personalized home screen is displayed.

[1907] Step 2: Upload images of clothing

[1908] Terminal:

[1909] The user selects "Upload clothing" from the menu.

[1910] Press the "Start Camera" button to activate the camera.

[1911] The user takes a picture of their clothes and presses the "Upload" button.

[1912] server:

[1913] The server receives image data sent from the terminal.

[1914] Input: Image data

[1915] Data processing: Compression and conversion of image data

[1916] Output: Compressed image data

[1917] The image data is sent to the AI ​​image analysis module.

[1918] Specific actions:

[1919] When a user takes a picture of a blue shirt and uploads it to the system, the image data is sent to the server and image analysis begins.

[1920] Step 3: Analyzing clothing data

[1921] server:

[1922] The AI ​​image analysis module analyzes images of clothing and extracts attributes such as color, shape, material, brand, and style.

[1923] Input: Compressed image data

[1924] Data processing: AI-based image analysis (e.g., color recognition, shape recognition)

[1925] Output: Clothing attribute information (e.g., Color: Blue, Style: Long-sleeved, Material: Cotton)

[1926] The extracted attribute information is saved to the database.

[1927] Specific actions:

[1928] The AI ​​analyzes the image, automatically identifying detailed information such as the color, shape, and material of the blue shirt uploaded by the user, and saving it to the system's database.

[1929] Step 4: Enter user information

[1930] Terminal:

[1931] The user selects "Enter Styling Information" from the menu.

[1932] The user enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), preferred style (e.g., casual) into the form and presses the "Submit" button.

[1933] server:

[1934] Receive the information entered in the form.

[1935] Input: User's TPO (Time, Place, Occasion), weather, and style information

[1936] Data processing: Temporary storage of information

[1937] Output: Verification results of temporarily saved information

[1938] The received information is saved to a temporary data store.

[1939] Specific actions:

[1940] The user selects and enters their chosen picnic destination, the weather in the park, and their preferred style.

[1941] Step 5: Acquisition and analysis of emotional information

[1942] Terminal:

[1943] The user activates the emotion recognition module.

[1944] The user either shows their face to the camera or inputs voice.

[1945] server:

[1946] It receives facial expressions and voice data.

[1947] Input: Facial expression data, audio data

[1948] Data processing: Analysis using an emotion engine

[1949] Output: User emotion information (e.g., "joy")

[1950] The emotion engine analyzes data to identify and store the emotions the user is currently feeling.

[1951] Specific actions:

[1952] When a user smiles at the camera, the system analyzes that expression as "joy" and saves that information.

[1953] Step 6: Generating Recommended Clothing

[1954] server:

[1955] Retrieve data on the clothing owned by the user from the database (e.g., blue shirt, black pants, white sneakers).

[1956] Input: User's owned clothing data

[1957] Data processing: Generating appropriate combinations for each outfit.

[1958] Output: Recommended clothing combination (e.g., blue shirt, black pants, white sneakers)

[1959] Based on the user's input regarding time, place, occasion, weather, style, and emotional information, the AI ​​styling module generates the optimal outfit.

[1960] Send the suggested outfit combinations to the app.

[1961] Specific actions:

[1962] The server retrieves information about a blue shirt, black pants, and white sneakers from the database and suggests the most appropriate casual outfit, taking into account the occasion, time, place, and mood.

[1963] Step 7: Recommended clothing display and selection

[1964] Terminal:

[1965] A list of recommended clothing combinations will be displayed.

[1966] The user selects one outfit from the suggested options and then checks the details.

[1967] Tap the selected outfit to complete the confirmation.

[1968] Specific actions:

[1969] The user reviews the clothing combinations suggested by the app (blue shirt, black pants, white sneakers) and taps the one they like best.

[1970] Step 8: Suggestions from the shop

[1971] server:

[1972] Based on the user's chosen style and past selection data, new suggestions are generated.

[1973] Input: Past selection data, user style information

[1974] Data processing: Filtering and selecting new fashion items

[1975] Output: Suggested new items (e.g., hat, sunglasses)

[1976] The app retrieves the latest item information from partner shops and sends it to the app.

[1977] Specific actions:

[1978] Based on items the user has previously selected and their current styling information, the system suggests the latest hats, sunglasses, and other items obtained from partner shops.

[1979] Step 9: View and purchase shop suggestions

[1980] Terminal:

[1981] Display a list of suggested products.

[1982] Check detailed information about each product (price, brand, reviews, etc.).

[1983] After selecting the product you want to purchase and clicking the "Purchase" button, you will be redirected to the partner shop's website or application.

[1984] Specific actions:

[1985] The user clicks on a pair of sunglasses they like from the list of suggested products and checks the details. Once they decide to purchase, they click the "Purchase" button to proceed to the purchase page of the partner shop.

[1986] (Application Example 2)

[1987] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1988] In recent years, fashion choices have diversified according to users' styles and preferences, and choosing clothing based on TPO (time, place, and purpose) and weather has become particularly important. However, conventional systems have difficulty appropriately analyzing the attributes of a user's clothing and providing coordinated outfit suggestions that take into account the user's emotional information. Furthermore, there is a lack of effective means to suggest new products. As a result, users are unable to choose clothing that best suits their style and are dissatisfied with their purchases of new fashion items.

[1989] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1990] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information, stored attribute information, and emotional information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, means for displaying the suggested new products and providing purchase links, means for acquiring and analyzing emotional information, and means for suggesting new fashion items based on past selections. As a result, the user can easily choose the most suitable outfit from their existing wardrobe, and also easily receive personalized suggestions that take emotional information into account, as well as purchase new fashion items.

[1991] "Means for receiving images taken by a user" refers to functions or devices that allow a user to send images taken with a smartphone or camera to a system and receive those images.

[1992] "Means for analyzing received images and extracting clothing attribute information" refers to functions or devices that use AI or image analysis technology to extract attribute information such as the color, shape, material, brand, and style of clothing based on received images.

[1993] "Means for saving extracted attribute information" refers to functions or devices for saving the clothing attribute information obtained through analysis to a database or storage.

[1994] "Means for users to input TPO, weather, and style information" refers to interfaces or devices that allow users to input information about their intended use (time, place, purpose), weather, and preferred style into the system.

[1995] "A means of suggesting the optimal outfit based on input information, stored attribute information, and emotional information" refers to a function or device that generates the optimal combination from stored clothing attribute information based on the TPO, weather, style information, and emotional data entered by the user.

[1996] "Means for displaying and allowing users to select suggested clothing" refers to interfaces or devices that visually display generated clothing suggestions to the user, allowing the user to select from among them.

[1997] "Means of acquiring data from partner shops in order to propose new products" refers to functions and devices for acquiring data on the latest fashion items from partner online shops and retail stores.

[1998] "Means for displaying proposed new products and providing purchase links" refers to interfaces or devices that display information about newly acquired fashion items to the user and provide links for purchasing them.

[1999] "Means for acquiring and analyzing emotional information" refers to functions or devices that acquire and analyze a user's emotions at a given time, such as from their facial expressions or voice data.

[2000] "Means of suggesting new fashion items based on past choices" refers to functions or devices that recommend new fashion items based on the user's past clothing selection data and purchase history.

[2001] The system implementing this invention aims to suggest the most suitable clothing by taking images of the user's clothing, which are then analyzed by AI, and to also recommend new products. This system consists of three main elements: a server, a terminal, and the user.

[2002] Server roles and processing

[2003] The server performs the following roles:

[2004] 1. Receiving images taken by users: To receive images taken by users with their smartphones or cameras, the image data is processed using a web framework such as Flask.

[2005] 2. Image Analysis: The received images are analyzed to extract clothing attribute information. Specifically, image analysis libraries such as OpenCV are used to obtain information such as color, shape, material, brand, and style.

[2006] 3. Saving attribute information: The extracted attribute information is saved to a database. SQL or NoSQL databases are used as the database.

[2007] 4. Information Integration and Analysis: The system receives user-inputted TPO (Time, Place, and Occasion), weather, style information, and emotional information, and integrates and analyzes this information with stored clothing attribute data. This process utilizes generative AI models and emotional analysis APIs.

[2008] 5. Clothing Suggestions: Based on integrated information, the AI ​​styling module suggests the most suitable outfit for the user.

[2009] 6. New Product Suggestions: Obtain the latest product data from partner shops and recommend products based on the user's past choices and sentiment information.

[2010] In this way, the system provides users with suggestions for the most suitable clothing and recommendations for new products.

[2011] Terminal roles and processing

[2012] Smartphones and other devices perform the following roles:

[2013] 1. Image capture and transmission: The user uses their smartphone camera to take a picture of the clothing they are wearing. The captured image is sent to the server via the application.

[2014] 2. Information Input: Provide an interface for the user to input TPO (Time, Place, Purpose), weather, and style information. It also activates an emotion recognition module, either by capturing facial expressions with the camera or inputting voice.

[2015] 3. Receiving and displaying suggestions: The system receives and displays a list of optimal clothing suggestions sent from the server. The user reviews and selects from the suggested clothing combinations.

[2016] 4. Display of new products and provision of purchase links: The interface displays information about new products sent from the server and provides purchase links.

[2017] This allows the terminal to function as an interface with the user, handling information input and receiving / displaying suggestions.

[2018] User roles and operations

[2019] The user performs the following actions:

[2020] 1. Launching the application and logging in: First, launch the application and log in by entering your username and password on the login screen.

[2021] 2. Take and upload images: Select the "Upload clothing" option from the menu, activate your smartphone's camera, take a picture of your clothing, and click the "Upload" button.

[2022] 3. Entering Information: Select "Enter Styling Information" from the menu, enter the time, place, occasion, weather, and style information, and press the "Submit" button.

[2023] 4. Acquiring emotion information: Activate the emotion recognition module and either show your face to the camera or input voice.

[2024] 5. Review and Select Suggestions: Review the list of recommended clothing combinations and make your selection. Also, review the suggested new items and purchase the ones you like.

[2025] Examples of specific cases and prompt statements

[2026] Example 1: Uploading images of clothing

[2027] The user launches the application and logs in. From the menu, they select "Upload Clothing," take a picture of a blue shirt, and upload it.

[2028] Example 2: Acquisition of emotional information

[2029] The user activates the emotion recognition module and displays their face towards the camera.

[2030] Example of a prompt

[2031] 1. "I'm planning a picnic on a sunny day; could you suggest some casual outfits?"

[2032] 2. "Based on your current emotions, please suggest the best outfit using the clothes you own."

[2033] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2034] Step 1:

[2035] The user launches the application, enters their username and password on the login screen, and presses the login button. The server receives the username and password, authenticates the user, and starts a session. It retrieves user information and notifies the terminal of the successful login.

[2036] Input: Username, Password

[2037] Data processing and calculation: Username and password verification, session initiation.

[2038] Output: Login success notification

[2039] Step 2:

[2040] The user selects the "Upload Clothing" option from the menu, activates their smartphone's camera to take a picture of their clothing, and clicks the "Upload" button. The device sends the image data to the server, and the server receives the image.

[2041] Input: Captured image

[2042] Data processing and calculation: Receiving and saving images.

[2043] Output: Image save confirmation notification

[2044] Step 3:

[2045] The server uses an AI image analysis module to analyze received images and extract attribute information such as color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[2046] Input: Received image

[2047] Data processing and calculation: Image analysis, extraction of attribute information.

[2048] Output: Saving attribute information

[2049] Step 4:

[2050] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and presses the "Submit" button. The terminal sends the entered information to the server.

[2051] Input: TPO (Time, Place, Occasion), weather, style information

[2052] Data processing and calculation: Information reception

[2053] Output: Information storage, confirmation notification

[2054] Step 5:

[2055] The user activates the emotion recognition module and either shows their face to the camera or inputs voice. The device sends the image or voice data to the server, where the server's emotion engine analyzes it, extracts emotion information, and stores it in a database.

[2056] Input: User's facial expression image or audio data

[2057] Data processing and calculation: emotion analysis, extraction of emotional information.

[2058] Output: Storage of emotional information, confirmation notification

[2059] Step 6:

[2060] The server retrieves data on the user's clothing, the user's input regarding occasion (TPO), weather, style, and emotional state from the database. The AI ​​styling module then generates the optimal clothing combination based on this information and sends it to the application.

[2061] Input: Clothing data, occasion (TPO), weather, style information, emotional information

[2062] Data processing and calculation: Generating clothing combinations

[2063] Output: Suggestions for the best outfit

[2064] Step 7:

[2065] The device displays a list of recommended clothing combinations, and the user taps on a suggested outfit to view details and then taps on their chosen outfit to confirm.

[2066] Input: Suggestions for the best outfit

[2067] Data processing and calculation: Information display

[2068] Output: Confirmation of detailed information, notification of selection completion.

[2069] Step 8:

[2070] The server suggests new fashion items based on the user's chosen style and past selections. It retrieves the latest item information from partner shops and sends products that match the user's style to the application.

[2071] Input: Past selection data, partner shop data

[2072] Data processing and calculations: Proposal of new products

[2073] Output: Send new product information

[2074] Step 9:

[2075] The device displays a list of suggested products, and the user reviews detailed information about each product (price, brand, reviews, etc.), selects the product they wish to purchase, and presses the "Purchase" button. This redirects them to the partner shop's website or application.

[2076] Input: New product information

[2077] Data Processing / Calculation: Displaying Detailed Information

[2078] Output: Redirection to purchase link

[2079] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2080] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2081] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[2082] [Fourth Embodiment]

[2083] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[2084] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[2085] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2086] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[2087] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[2088] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[2089] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[2090] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[2091] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[2092] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[2093] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2094] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[2095] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2096] This invention is a system that uses a webcam or smartphone app to load images of the user's clothing into AI, and then suggests the most suitable outfit based on the occasion, weather, and style. Furthermore, it also supports the suggestion and purchase of new fashion items.

[2097] The basic configuration of this system includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for saving the extracted attribute information, means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information and saved attribute information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops in order to suggest new products, and means for displaying the suggested new products and providing purchase links.

[2098] Program Processing Description

[2099] 1. System startup and login

[2100] Terminal:

[2101] The user launches the app, enters their username and password on the login screen, and presses the login button.

[2102] server:

[2103] The system receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[2104] 2. Upload images of clothing

[2105] Terminal:

[2106] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[2107] server:

[2108] The system receives image data and sends it to the AI ​​image analysis module.

[2109] 3. Data analysis of clothing

[2110] server:

[2111] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[2112] 4. Entering user information

[2113] Terminal:

[2114] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[2115] server:

[2116] Receives information entered by the user.

[2117] 5. Generating Recommended Clothing

[2118] server:

[2119] The system retrieves data on the user's clothing from a database. Based on the user's input regarding occasion, weather, and style, an AI styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[2120] 6. Display and selection of recommended clothing.

[2121] Terminal:

[2122] The system displays a list of recommended outfit combinations, and users can tap on a suggested outfit to view details. They can then tap on their chosen outfit to complete the confirmation.

[2123] 7. Suggestions from the shop

[2124] server:

[2125] Based on the user's chosen style and past selections, the app generates new suggestions. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[2126] 8. Viewing and purchasing shop suggestions

[2127] Terminal:

[2128] A list of suggested products is displayed, and detailed information (price, brand, reviews, etc.) can be viewed for each product. Selecting a product you wish to purchase and clicking the "Purchase" button will redirect you to the partner shop's website or application.

[2129] Specific example

[2130] Example 1: Uploading images of clothing

[2131] Terminal:

[2132] Launch the app and log in.

[2133] Select "Upload clothing," take a picture of the blue shirt, and upload it.

[2134] server:

[2135] The system receives an image and sends it to an AI image analysis module. It identifies the image as follows: color: blue, shape: long sleeves, material: cotton, and saves it to the database.

[2136] Example 2: Generating Recommended Clothing

[2137] Terminal:

[2138] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[2139] server:

[2140] The system retrieves information on a blue shirt, black pants, and white sneakers from a database. An AI styling module then suggests the optimal combination of these items based on the input data. The overall outfit information is then sent to the app.

[2141] Example 3: Shop proposal

[2142] server:

[2143] Based on the user's past choices and casual style, the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner shops and sends it to the app.

[2144] Terminal:

[2145] The suggested product list is displayed, and detailed information can be viewed. Clicking on a product you like will take you to the purchase page. In this way, users can easily combine outfits that suit their style, and new items can be suggested and purchased.

[2146] This system is designed to support users' busy lifestyles and help them use their time efficiently. It encourages users to make the most of their existing clothing while also providing suggestions for new fashion items, allowing them to always enjoy the latest styles.

[2147] The following describes the processing flow.

[2148] Step 1:

[2149] Terminal:

[2150] The user launches the app, enters their username and password on the login screen, and presses the login button.

[2151] server:

[2152] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[2153] Step 2:

[2154] Terminal:

[2155] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[2156] server:

[2157] The server receives the image data and sends it to the AI ​​image analysis module.

[2158] Step 3:

[2159] server:

[2160] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[2161] Step 4:

[2162] Terminal:

[2163] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[2164] server:

[2165] The server receives the information entered by the user.

[2166] Step 5:

[2167] server:

[2168] The server retrieves data on the user's clothing from the database. Based on the user's input regarding occasion, weather, and style, the AI ​​styling module generates the optimal outfit. It creates a recommended outfit combination and sends it to the app.

[2169] Step 6:

[2170] Terminal:

[2171] The device displays a list of recommended clothing combinations. The user taps on a suggested outfit to view details. They tap on their chosen outfit to complete the confirmation.

[2172] Step 7:

[2173] server:

[2174] The server generates new suggestions based on the user's chosen style and past selections. It retrieves the latest item information from partner shops, selects products that match the user's style, and sends them to the app.

[2175] Step 8:

[2176] Terminal:

[2177] The device displays a list of suggested products, allowing users to view detailed information about each item (price, brand, reviews, etc.). When the user selects a product they wish to purchase and presses the "Purchase" button, they are redirected to the partner shop's website or application.

[2178] (Example 1)

[2179] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2180] Conventional clothing suggestion systems often fail to adequately personalize user outfit combinations and suggest new items, posing a challenge to improving user satisfaction. Furthermore, the lack of automatic generation of optimal outfits based on time, place, occasion, weather, and preferred style meant they could not efficiently support users' busy lifestyles.

[2181] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[2182] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images to extract clothing attribute information, and means for storing the extracted attribute information. This allows for detailed storage of information about the user's clothing in a database, enabling analysis based on individual attributes. The invention also includes means for the user to input TPO, weather, and style information, means for suggesting the most suitable outfit based on the input information and stored attribute information, means for displaying the suggested outfits to the user and allowing them to select one, means for generating the most suitable outfit using a generative AI model based on the TPO, weather, and style information entered by the user, and means for suggesting new fashion items based on the user's past choices and style. This enables the suggestion of the most suitable outfit tailored to the user's individual needs and the constant suggestion of new styles, significantly improving user satisfaction.

[2183] A "user" is an individual or group that uses this system.

[2184] "Captured images" refer to image data acquired by the user using the camera function of the system.

[2185] "Means of receiving" refers to the function or device that allows a server to receive data sent by a user.

[2186] "Means of analysis" refers to a function or technology used by a system to analyze received image data and extract specific information.

[2187] "Clothing attribute information" refers to information about the characteristics of clothing, such as color, shape, material, brand, and style.

[2188] "Means of storage" refers to a function or device for storing extracted information in a database or storage device.

[2189] "TPO" is an abbreviation for Time, Place, and Occasion, and it is a set of criteria for determining appropriate attire for a particular situation.

[2190] "Style information" refers to information about the type and design of clothing based on the user's preferences and current trends.

[2191] "Means of suggesting the optimal outfit" refers to a function or technology that presents clothing combinations suitable for a user based on information entered by the user and stored attribute information.

[2192] "Means of displaying and allowing selection" refers to a function or device that visually presents suggested clothing to the user and allows them to make a selection from among them.

[2193] A "partner retailer" is a store or company that collaborates with this system to provide product data and propose new products to users.

[2194] A "generative AI model" refers to an algorithm or technology that uses artificial intelligence to generate the most suitable clothing based on input data.

[2195] "Means of providing a purchase link" refers to a function or technology that displays a link so that a user can access the purchase page of a suggested product.

[2196] "Past choices" refers to clothing and styling information that the user previously selected within the system.

[2197] This invention is a system that uses a webcam or smartphone app to read images of the user's clothing into an AI, and then suggests the most suitable outfit based on the occasion, weather, and style. Furthermore, it also supports the suggestion and purchase of new fashion items.

[2198] System Configuration

[2199] This system includes the following components:

[2200] Means for receiving images of clothing

[2201] A method for analyzing received images and extracting clothing attribute information.

[2202] Means for saving extracted attribute information

[2203] A means for users to input TPO (Time, Place, Occasion), weather, and style information.

[2204] A method for suggesting the most suitable clothing based on input information and stored attribute information.

[2205] A means of displaying suggested clothing to the user and allowing them to select from it.

[2206] Means of acquiring data from partner retailers in order to propose new products.

[2207] A means of displaying proposed new products and providing purchase links.

[2208] A method for generating the optimal outfit using a generative AI model based on user-inputted information regarding time, place, occasion, weather, and style.

[2209] A method for suggesting new fashion items based on the user's past choices and style.

[2210] Program processing flow

[2211] The system program operates in the following sequence:

[2212] 1. System startup and login

[2213] Terminal:

[2214] The user launches the app, enters their username and password on the login screen, and presses the login button.

[2215] server:

[2216] The server receives the username and password, queries the authentication server, and performs authentication. If authentication is successful, it generates a session ID and retrieves user information.

[2217] 2. Upload images of clothing

[2218] Terminal:

[2219] The user selects the "Upload Clothing" option from the menu, activates the camera, takes a picture of the clothing, and taps the "Upload" button.

[2220] server:

[2221] The server receives the image data and sends it to the AI ​​image analysis module.

[2222] 3. Data analysis of clothing

[2223] server:

[2224] The AI ​​image analysis module processes image data and analyzes attributes such as the color, shape, material, brand, and style of the clothing.

[2225] server:

[2226] The analyzed attribute information is saved to the database.

[2227] 4. Entering user information

[2228] Terminal:

[2229] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and taps the "Submit" button.

[2230] server:

[2231] Receive information entered by the user and save it to the database.

[2232] 5. Generating Recommended Clothing

[2233] server:

[2234] The server retrieves data on the user's clothing from the database. The AI ​​styling module generates the optimal outfit combination based on the inputted TPO (Time, Place, Occasion), weather, and style information.

[2235] server:

[2236] The generated clothing data is sent to the terminal.

[2237] 6. Display and selection of recommended clothing.

[2238] Terminal:

[2239] The suggested outfits are displayed to the user in a list, and the user can view the details of each item. The user taps the selected outfit to complete the confirmation.

[2240] 7. Suggestions from the shop

[2241] server:

[2242] Based on the user's chosen style and past selection data, the system generates suggestions for new fashion items. It retrieves the latest product data from partner retailers, selects products that suit the user, and sends them to their device.

[2243] 8. Viewing and purchasing shop suggestions

[2244] Terminal:

[2245] The system displays a list of suggested products, allowing users to view detailed information about each item. When a user selects a product they wish to purchase and clicks the "Buy" button, they are redirected to the partner retailer's website or application.

[2246] Specific example

[2247] Example 1: Uploading images of clothing

[2248] Terminal:

[2249] The user launches the app and logs in. They select "Upload clothing," take a photo of a blue shirt, and click the "Upload" button.

[2250] server:

[2251] The server receives the image and sends it to an AI image analysis module. It identifies the color as blue, the shape as long-sleeved, and the material as cotton, and stores this information in a database.

[2252] Example 2: Generating Recommended Clothing

[2253] Terminal:

[2254] The user enters that they are planning a picnic, the weather will be sunny, and they will be dressed in casual attire.

[2255] server:

[2256] The server retrieves information about a blue shirt, black pants, and white sneakers from the database. The AI ​​styling module then suggests the optimal combination of these items based on the input data. The overall outfit information is then sent to the app.

[2257] Example 3: Shop proposal

[2258] server:

[2259] Based on the user's past choices and casual style, the app suggests new fashion items (e.g., hats, sunglasses). It also retrieves the latest product information from partner retailers and sends it to the app.

[2260] Terminal:

[2261] View the suggested product list and check the details. Click on a product you like to go to the purchase page.

[2262] Example of a prompt

[2263] "What's the perfect outfit for a picnic? Something casual for a sunny day."

[2264] "Based on styles you've chosen in the past, please suggest new items that are suitable for today's weather."

[2265] In summary, this system is designed to efficiently support users' busy lifestyles, encourage them to make the most of their existing clothing, and provide suggestions for new fashion items.

[2266] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2267] Step 1: System startup and login

[2268] Terminal:

[2269] The user taps the app on their smartphone to launch it. The launch screen appears, followed by the login screen. The user enters their username and password on the login screen and taps the login button.

[2270] Input: Username, Password

[2271] Output: Sending authentication information

[2272] server:

[2273] The server receives the username and password. It queries the authentication server and compares the received authentication information with the database information. If authentication is successful, it generates a session ID and retrieves user information (name, profile picture, etc.). If authentication fails, it generates an error message and sends it to the terminal.

[2274] Input: Username, Password

[2275] Data processing: Verify authentication information in the database.

[2276] Output: Session ID, User information (if authentication is successful), Error message (if authentication fails)

[2277] Step 2: Upload images of clothing

[2278] Terminal:

[2279] The user selects the "Upload Clothing" option from the menu and taps the "Launch Camera" button. The camera launches, and the user takes a picture of their clothing. After taking the picture, tap the "Upload" button.

[2280] Input: Image of clothing

[2281] Output: Sending image data

[2282] server:

[2283] The server receives the image data and sends it to the AI ​​image analysis module.

[2284] Input: Image data of clothing

[2285] Data processing: Preparing for AI analysis of image data

[2286] Output: Retrieval of analysis results

[2287] Step 3: Analyzing clothing data

[2288] server:

[2289] The AI ​​image analysis module processes the received image data and analyzes attributes such as the color, shape, material, brand, and style of the clothing.

[2290] Input: Image data of clothing

[2291] Data processing: Attribute extraction using AI image analysis module

[2292] Output: Clothing attribute information

[2293] server:

[2294] The analyzed attribute information is saved to a database. The saved information includes clothing identification IDs, attribute information, and user IDs.

[2295] Input: Clothing attribute information

[2296] Data processing: Attribute information stored in a database.

[2297] Output: Save complete flag

[2298] Step 4: Enter user information

[2299] Terminal:

[2300] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then taps the "Submit" button.

[2301] Input: Information such as TPO (Time, Place, Occasion), destination, weather, and style.

[2302] Output: Send input information

[2303] server:

[2304] Receive information entered by the user and save it to the database.

[2305] Input: Information such as TPO (Time, Place, Occasion), destination, weather, and style.

[2306] Data processing: Storing input information in a database.

[2307] Output: Save complete flag

[2308] Step 5: Generating Recommended Clothing

[2309] server:

[2310] The server retrieves data on the user's clothing from the database. The AI ​​styling module generates the optimal outfit combination based on the user's input regarding time, place, occasion, weather, and style.

[2311] Input: TPO (Time, Place, Occasion), weather, style, attribute information of user-owned clothing

[2312] Data processing: Optimal clothing generation using AI styling module

[2313] Output: Recommended clothing data

[2314] server:

[2315] The generated recommended clothing data is sent to the device.

[2316] Input: Recommended clothing data

[2317] Output: Send recommended clothing

[2318] Step 6: Recommended clothing display and selection

[2319] Terminal:

[2320] A list of recommended outfit combinations is displayed to the user. The user can review the details of each item and tap their chosen outfit to complete the confirmation.

[2321] Input: Recommended clothing data

[2322] Output: Data for the selected clothing

[2323] Step 7: Proposal from the shop

[2324] server:

[2325] Based on past choices and styles, it generates suggestions for new fashion items. It retrieves the latest product data from partner retailers and selects products that suit the user. This product information is then sent to the user's device.

[2326] Input: Past selection data, latest product data

[2327] Data processing: New item suggestion generation, product data acquisition.

[2328] Output: Send the proposed product list.

[2329] Step 8: View and purchase shop suggestions

[2330] Terminal:

[2331] The user is shown a list of suggested products, and can view detailed information about each product. When they select a product they wish to purchase and tap the "Purchase" button, they are redirected to the partner retailer's website or application.

[2332] Input: Proposed product list

[2333] Output: Redirect to the purchase page

[2334] Through the steps described above, this system can efficiently support users in receiving clothing suggestions and purchasing new fashion items.

[2335] (Application Example 1)

[2336] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2337] Traditional clothing suggestion systems can suggest the best outfits based on images taken by the user at home and other input information, but they lack the real-time information needed when choosing new clothes in a physical store. Therefore, users find it difficult to effectively coordinate their existing wardrobe with new purchases, resulting in a less-than-ideal shopping experience. Furthermore, the lack of support for immediate purchases in physical stores makes smooth purchasing difficult.

[2338] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2339] In this invention, the server includes means for receiving images taken by the user, means for analyzing the received images to extract clothing attribute information, and means for storing the extracted attribute information. This allows the user to receive suggestions for new clothing items in a physical store based on their existing clothing data, and to see coordinated outfits displayed on the spot. Furthermore, by including means for acquiring data from partner companies to suggest new products, and including payment means for purchasing suggested products in-store, the user can receive coordinated outfit suggestions and make immediate purchases in real time, enjoying a comfortable and efficient shopping experience.

[2340] "Means for receiving images taken by users" refers to a function that allows users to send images taken using their smartphones or cameras to the system, and for the system to receive those images.

[2341] "Means for analyzing received images and extracting clothing attribute information" refers to a function in which the system analyzes received image data using AI or image recognition technology to extract information such as the color, shape, material, brand, and style of the clothing.

[2342] "Means for saving extracted attribute information" refers to a function for recording the attribute information of clothing obtained through analysis into a storage device such as a database.

[2343] "A means for users to input TPO, weather, and style information" refers to a function that allows users to input information about specific situations, weather conditions, and preferred fashion styles into the system.

[2344] The "means of suggesting the optimal outfit" refers to a function that suggests the most suitable outfit combination based on the user's inputted TPO (Time, Place, Occasion), weather, and style information, as well as saved clothing attribute information.

[2345] "A means of displaying and allowing users to select clothing" refers to a function that visually presents the system with suggested clothing combinations to the user, allowing the user to select from among them.

[2346] "Means of acquiring data from partner companies" refers to a function that allows the system to acquire the latest product data from partner shops and companies in order to propose new products and fashion items.

[2347] "Means of providing purchase links" refers to functions that provide users with links or interfaces to purchase suggested new products, thereby supporting online shopping and in-store purchases.

[2348] "Methods implemented in physical stores" refers to a function that allows users to receive new clothing suggestions and check outfit combinations in real time while they are in a physical store.

[2349] "Payment methods" refers to the function that allows users to instantly purchase products offered within a store by completing the payment process. This function supports various payment methods such as credit cards, mobile payments, and digital wallets.

[2350] The system for implementing this invention comprises a series of means for receiving images taken by a user, analyzing those images to extract clothing attribute information, and storing this information. It also includes means for the user to input TPO (Time, Place, Occasion), weather, and style information, for which the most suitable clothing is suggested, and for the user to see and select the suggested clothing. Furthermore, it includes means for acquiring data from partner companies to suggest new products, for displaying the suggested new products, and for providing purchase links. As an important element, it also includes means for suggesting new clothing in a physical store based on the user's clothing data, for displaying coordinated outfits on the spot, and for payment methods for purchasing the suggested products in the store.

[2351] Processing details

[2352] 1. Device startup and user authentication:

[2353] The terminal uses a mobile device such as a smartphone or smart glasses, and the user logs in to the launched application. The username and password are sent to the authentication server. If authentication is successful, the server starts a session and retrieves user information. Specifically, authentication technologies such as OAuth 2.0 and JWT (JSON Web Token) are used.

[2354] 2. Image upload and analysis:

[2355] Users take pictures of new clothing items in a physical store using the camera on their smartphone or smart glasses. The device sends the image data to a server, which processes the images using an AI image analysis module to extract clothing attribute information (color, shape, material, brand, style). Deep learning technologies such as Convolutional Neural Networks (CNNs) are used.

[2356] 3. Storing attribute data and user information:

[2357] The extracted clothing attribute information is stored in a database. Relational databases or NoSQL databases are often used. The user then enters information such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual) into a form, which the server receives and stores.

[2358] 4. Outfit suggestions:

[2359] The server compares the stored user clothing data with newly entered information and uses an AI styling module to generate the optimal clothing combination. At this stage, the generative AI model and inference module previously used as training data are utilized.

[2360] 5. Displaying coordinated outfits and payment within physical stores:

[2361] The user's device displays suggested outfits. The user reviews the suggested outfits and, if they like them, proceeds with the purchase. Mobile payments utilize NFC (Near Field Communication) technology or QR code payments.

[2362] Specific example

[2363] Example 1: In-store image scanning and analysis

[2364] 1. Device: The user launches the app and logs in.

[2365] 2. Terminal: Take a picture of the red dress inside the store and send it to the server.

[2366] 3. Server: Sends the image to an AI image analysis module for analysis, determining that the color is red, the shape is a dress, and the material is silk.

[2367] Example 2: Outfit suggestions and purchase

[2368] 1. Terminal: The user enters TPO (formal dinner), weather (sunny), and preferred style (elegant).

[2369] 2. Server: Based on the analysis data and user information, it generates suggestions for white high heels and a gold clutch bag and sends them to the terminal.

[2370] 3. Device: Recommended outfits are displayed, and the user proceeds with mobile payment.

[2371] Examples of prompts for generative AI models

[2372] The prompt text for an application that recommends new items and outfit combinations in a physical store based on the user's clothing data:

[2373] 1. User Information:

[2374] Clothing owned: Blue shirt, black pants, white sneakers

[2375] 2. New items:

[2376] red dress

[2377] 3. Event Information:

[2378] TPO: Formal dinner

[2379] Weather: Sunny

[2380] Preferred style: Elegant

[2381] 4. Proposed outfit:

[2382] A blue shirt, black pants, white sneakers, and a clutch bag and jewelry to match the red dress.

[2383] Based on the above information, we will suggest the most suitable outfit and encourage users to purchase it at a physical store.

[2384] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2385] Step 1:

[2386] System startup and user authentication

[2387] Input: The user activates their smartphone or smart glasses and enters their username and password into the application.

[2388] Specific operation: The terminal sends user authentication information to the server. The server queries the authentication server to verify that the username and password match.

[2389] Output: If authentication is successful, a session is started and user information is sent from the server to the terminal. If it fails, an authentication error message is displayed on the terminal.

[2390] Step 2:

[2391] Upload image

[2392] Input: The user takes pictures of new clothing items in a physical store using the camera on their smartphone or smart glasses.

[2393] Specific operation: The device sends the captured image data to the server.

[2394] Output: Image data is received by the server and sent to the next analysis step.

[2395] Step 3:

[2396] Image analysis and attribute extraction

[2397] Input: Image data received by the server.

[2398] Specific operation: The server uses an AI image analysis module to process image data and extract attributes such as the color, shape, material, brand, and style of the clothing.

[2399] Output: The attribute information of the extracted clothing items is saved to the database.

[2400] Step 4:

[2401] Entering user information

[2402] Input: The user enters information into the application such as TPO (e.g., casual picnic), weather (e.g., sunny), and preferred style (e.g., casual).

[2403] Specific operation: The terminal sends the information entered by the user to the server.

[2404] Output: The server saves the received user's TPO, weather, and style information to the database.

[2405] Step 5:

[2406] Coordination generation

[2407] Input: Saved user clothing data and newly entered TPO, weather, and style information.

[2408] Specific operation: The server uses an AI styling module to match input information with stored data and generate the optimal clothing combination.

[2409] Output: The optimal clothing combination is sent to the device.

[2410] Step 6:

[2411] Display and select outfits

[2412] Input: Information on the optimal clothing combination sent from the server.

[2413] Specific operation: The device displays clothing suggestions to the user. The user makes a selection from these suggestions.

[2414] Output: Details of the clothing selected by the user are saved on the device.

[2415] Step 7:

[2416] Proposal for a new product

[2417] Input: User selection information, past selections, and style information.

[2418] Specific operation: The server retrieves new product data from partner vendors and suggests the most suitable new products based on the user's style and past choices.

[2419] Output: New product suggestion information is sent to the terminal.

[2420] Step 8:

[2421] Display and purchase of product suggestions.

[2422] Input: New product suggestion information sent from the server.

[2423] Specific operation: The terminal displays a list of new products and provides detailed information about each product. The user selects the product they wish to purchase and proceeds with the payment process.

[2424] Output: The selected items are displayed in the store, and the user completes the payment process. If a mobile payment system is used, the purchase record is saved on the server.

[2425] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2426] This invention is a system that uses a webcam or smartphone app to input images of the user's clothing into an AI, and then suggests the most suitable outfit based on the occasion, weather, style, and the user's emotions. Furthermore, it also supports the suggestion and purchase of new fashion items.

[2427] The basic configuration of this system includes means for receiving images taken by the user, means for analyzing the received images and extracting clothing attribute information, means for storing the extracted attribute information, means for the user to input TPO, weather, and style information, an emotion engine that recognizes the user's emotions, means for suggesting the most suitable outfit based on the input information, stored attribute information, and emotion information, means for displaying the suggested outfits to the user and allowing them to select one, means for acquiring data from partner shops to suggest new products, and means for displaying the suggested new products and providing purchase links.

[2428] Program Processing Description

[2429] 1. System startup and login

[2430] Terminal:

[2431] The user launches the app, enters their username and password on the login screen, and presses the login button.

[2432] server:

[2433] The server receives the username and password, queries the authentication server for authentication, and if authentication is successful, starts a session and retrieves user information.

[2434] 2. Upload images of clothing

[2435] Terminal:

[2436] The user selects the "Upload Clothing" option from the menu, activates the camera to take a picture of the clothing, and clicks the "Upload" button.

[2437] server:

[2438] The server receives the image data and sends it to the AI ​​image analysis module.

[2439] 3. Data analysis of clothing

[2440] server:

[2441] The AI ​​image analysis module processes image data and extracts attributes such as clothing color, shape, material, brand, and style. The extracted attribute information is then stored in a database.

[2442] 4. Entering user information

[2443] Terminal:

[2444] The user selects "Enter Styling Information" from the menu, enters information such as TPO (e.g., casual picnic), destination (e.g., park), weather (e.g., sunny), and preferred style (e.g., casual) into the form, and then presses the "Submit" button.

[2445] server:

[2446] Th...

Claims

1. A means of receiving images taken by the user, A means for analyzing received images and extracting clothing attribute information, A means of storing the extracted attribute information, A means for users to input TPO, weather, and style information, A method for suggesting the most suitable clothing based on the input information and stored attribute information, A means of displaying suggested clothing to the user and allowing them to select it, A means of acquiring data from partner shops in order to propose new products, A means of displaying proposed new products and providing purchase links, A system that includes this.

2. The system according to claim 1, comprising means of using a pull-down menu or checkboxes when a user inputs TPO, weather, and preferred style.

3. The system according to claim 1, wherein the means for storing clothing attribute information is a means for storing information on color, shape, material, brand, and style in a database.

Images