system

Abstract

Provide a system. [Solution] A means for acquiring user location information; means for recommending fashion items based on a user's preferences; means for generating advertisements under certain conditions; means for integrating the generated advertisements into fashion items; means for distributing the integrated fashion items to users; A means for measuring the effectiveness of advertisements based on user behavior; and means for rewarding the user based on the measured effectiveness.

Description

[Technical Field]

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

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

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

[0004] Conventional street advertising, once installed, remains in a fixed location, meaning that the visibility and effectiveness of the advertisement depend on the location and time, and that it can only reach a specific group of people. Furthermore, the high rental and installation costs place a significant financial burden on advertisers. To overcome these challenges, a dynamic advertising display method is needed. Furthermore, since users have limited means of earning advertising revenue, providing them with easy opportunities to earn income in their daily lives is a challenge. [Means for solving the problem]

[0005] The present invention provides a system including a means for acquiring user location information, a means for recommending fashion items based on the user's preferences, a means for generating advertisements under specific conditions, a means for integrating the generated advertisements into fashion items, a means for distributing the integrated fashion items to users, a means for measuring the effectiveness of the advertisements based on the user's behavior, and a means for rewarding the user based on the measured effectiveness. This system allows advertisements to be displayed dynamically, ensuring visibility that is not dependent on a specific group or location. Furthermore, users can easily earn advertising revenue through their daily activities.

[0006] "Location information" is data that indicates the geographic coordinates of the user's current location.

[0007] "Taste" is preference information that reflects a user's personal fashion style and interests.

[0008] "Fashion items" refer to clothing, accessories, and other decorative items worn on the body.

[0009] "Advertising" is any message or visual content that promotes a particular product, service, or brand.

[0010] "Document generation AI" is artificial intelligence that automatically generates text using natural language processing technology.

[0011] "Image generation AI" is artificial intelligence that generates visual content based on given data and parameters.

[0012] "Behavioral data" refers to data that indicates a series of user behaviors, such as the user's travel route, place of stay, and activity history.

[0013] "Visibility" refers to the likelihood that a user can visually recognize an advertisement.

[0014] A "reward" is a value such as money or points that is given to a user based on the visibility and effectiveness of an advertisement. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The system of the present invention integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and provides rewards to users. The main elements of this system are a server, a terminal, and a user.

[0037] Overall system overview

[0038] 1. User registration and apparel selection

[0039] First, a user downloads the Fashion Ads app and creates an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends this information to the server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended apparel items based on the user's profile.

[0040] 2. Generating ad creatives

[0041] The server uses document generation AI to generate customized ad text based on the user's behavioral and location data. It also uses image generation AI to generate corresponding visual ads. These generated texts and images are combined to create customized ad creatives. The device displays a preview of this ad creative to the user and accepts approval or revision requests from the user. If necessary, the server modifies the ad creative and presents the final version to the user.

[0042] 3. Apparel distribution and advertising

[0043] When a user rents or purchases a selected apparel item, the device sends that information to the server. The server processes the shipment of the apparel item and delivers it to the user. When the user receives the apparel item, they confirm receipt within the app. The device then sends the receipt confirmation information to the server, which starts the ad display counter.

[0044] 4. Collecting location information and measuring advertising effectiveness

[0045] The user wears an apparel item and goes out. The device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. This allows the effectiveness of the advertisement to be evaluated.

[0046] 5. Calculation and Payment of Rewards

[0047] The server calculates rewards based on advertising effectiveness and adds points to the user's account. The terminal notifies the user of the points and displays a rewards statement. The user can check and use the rewards in the in-app wallet.

[0048] Specific examples

[0049] User A downloads the app and creates an account. The device sends the basic information entered by User A to the server, which stores it in a database. User A selects a shopping center that he or she frequently visits. Based on User A's profile, the server suggests a T-shirt with an advertisement printed on it that is suitable for that shopping center.

[0050] The server then uses document generation AI and image generation AI to generate text and visual ads targeted to specific stores in the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[0051] When User A receives the T-shirt and goes to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of the advertising at the shopping center. Finally, the server calculates the reward and adds points to User A's account, and the device displays the reward details.

[0052] This enables the Fashion Ads System to efficiently deliver advertisements through users' daily activities and provide advertising revenue to users.

[0053] The processing flow will be explained below.

[0054] Program processing steps

[0055] User registration and apparel selection

[0056] Step 1:

[0057] A user downloads the Fashion Ads app and creates a new account.

[0058] Step 2:

[0059] The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to the server.

[0060] Step 3:

[0061] The server stores the received basic information in a database.

[0062] Step 4:

[0063] Users select their fashion style and frequently visited places on the app's settings screen.

[0064] Step 5:

[0065] The terminal transmits the user's selection information to the server.

[0066] Step 6:

[0067] The server creates a list of recommended apparel items based on the user's profile and sends it to the terminal.

[0068] Step 7:

[0069] The device displays a list of recommended apparel items to the user.

[0070] Ad creative generation

[0071] Step 1:

[0072] The server uses document generation AI to generate customized ad text based on user behavioral and location data.

[0073] Step 2:

[0074] The server uses image generation AI to generate the corresponding visual advertisement.

[0075] Step 3:

[0076] The server combines the generated text and images to create customized ad creative.

[0077] Step 4:

[0078] The server sends the ad creative to the device.

[0079] Step 5:

[0080] The device displays a preview of the ad creative to the user and asks for approval.

[0081] Step 6:

[0082] The user reviews the ad creative and approves or requests revisions.

[0083] Step 7:

[0084] The terminal sends the user's feedback to the server.

[0085] Step 8:

[0086] The server modifies the ad creative as needed and sends the final version to the device.

[0087] Apparel distribution and advertising

[0088] Step 1:

[0089] The user rents or purchases the selected apparel item.

[0090] Step 2:

[0091] The terminal transmits the user's rental / purchase information to the server.

[0092] Step 3:

[0093] The server processes the shipping of the apparel item and delivers it to the user.

[0094] Step 4:

[0095] The user receives the apparel item and confirms receipt within the app.

[0096] Step 5:

[0097] The terminal sends a receipt confirmation to the server.

[0098] Step 6:

[0099] The server starts an ad display counter and begins tracking the user's location.

[0100] Collecting location information and measuring advertising effectiveness

[0101] Step 1:

[0102] The user goes out wearing the apparel item.

[0103] Step 2:

[0104] The device periodically acquires the user's GPS location information and sends it to the server.

[0105] Step 3:

[0106] The server analyzes the location information sent and measures the time spent in a particular location and the visibility of the advertisement.

[0107] Step 4:

[0108] The server evaluates the effectiveness of the advertisement based on the analysis results.

[0109] Reward calculation and payment

[0110] Step 1:

[0111] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[0112] Step 2:

[0113] The terminal displays a notification of the points awarded and a reward statement to the user.

[0114] Step 3:

[0115] The user can check and spend rewards in the in-app wallet.

[0116] Specific examples

[0117] After downloading the app, User A creates an account and enters basic information. The device sends this information to the server, which stores it in a database. User A then selects a shopping center that he or she frequently visits, and the device sends this information to the server. Based on User A's profile, the server recommends a T-shirt with an advertisement printed on it that is appropriate for that shopping center.

[0118] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific stores in the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[0119] When User A receives the T-shirt and heads to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and calculates the effectiveness of the shopping center's advertising. Finally, the server calculates rewards and adds points to User A's account, and the device displays a reward statement. In this way, the Fashion Ads system can efficiently deliver advertisements through the user's daily activities and provide advertising revenue to the user.

[0120] Example 1

[0121] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0122] Conventional advertising systems have difficulty effectively utilizing users' daily behavior and location information to increase the visibility and effectiveness of ads, and have been unable to provide appropriate rewards to users. Furthermore, customizing ads and providing apparel items tailored to users' preferences have been limited. For these reasons, there has been a demand for a system that provides high satisfaction for both advertisers and users.

[0123] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0124] In this invention, the server includes a means for acquiring user location information, a means for recommending clothing items based on the user's preferences, and a means for analyzing the user's behavioral data and location data, which makes it possible to effectively deliver advertisements based on the user's daily behavior and location information, measure advertisement visibility and dwell time, and provide appropriate rewards to the user.

[0125] The "means for acquiring user location information" refers to a device or system that has the function of collecting data indicating the user's current location.

[0126] A "means for recommending clothing items based on user preferences" is a device or system that has the function of suggesting optimal clothing items based on data related to the user's tastes and preferences.

[0127] The "means for analyzing user behavioral data and location data" refers to a device or system that has the function of analyzing a user's behavioral history and location information and extracting useful information based on this.

[0128] An "advertising generating means" is a device or system that has the functionality to create advertising content tailored to a specific purpose or target.

[0129] A "means for integrating generated advertising into apparel" is a device or system that has the functionality to incorporate generated advertising content into apparel, either physically or digitally.

[0130] The "means for distributing clothing items to users" refers to a device or system that has the function of providing selected clothing items to users.

[0131] The "means for measuring the visibility of advertisements and the length of stay" refers to a device or system that has the function of measuring the time a user views an advertisement or the time a user stays in a particular place.

[0132] The "means for rewarding users based on measured visibility and length of stay" refers to a device or system that has the function of providing appropriate rewards based on the user's behavior toward the advertisement and length of stay.

[0133] A "document generation algorithm" is a computational method or program for automatically generating text data.

[0134] An "image generation algorithm" is a computational method or program for automatically creating visual content.

[0135] The "means for previewing and approving advertising creatives" refers to a device or system that has the function of displaying generated advertising content in advance and obtaining approval from a user or administrator.

[0136] The present invention is a system that integrates advertisements into clothing worn by users in their daily lives and provides rewards to users by measuring the effectiveness of the advertisements. The system is composed of a server, terminals, and users.

[0137] System Configuration

[0138] The main components of the system are a means for acquiring user location information, a means for recommending clothing items based on user preferences, a means for analyzing behavioral and location data, a means for generating advertisements, a means for integrating the generated advertisements into clothing items, a means for distributing the clothing items to users, a means for measuring the visibility and dwell time of advertisements, and a means for rewarding users based on the measured visibility and dwell time.

[0139] 1. User registration and apparel selection

[0140] Users download the fashion advertising app, create an account, enter basic information (such as name, age, gender, and address), and select their preferred fashion style and frequently visited places (such as shopping centers) within the app.

[0141] The device sends the entered basic information to the server, which stores the received information in a database and presents recommended apparel items based on the user's profile.

[0142] 2. Generating ad creatives

[0143] The server analyzes the user's behavioral and location data and utilizes document and image generation algorithms to generate customized ad text and visual ads.

[0144] The terminal displays a preview of the generated ad creative to the user and accepts approval or a request for modification. If the user approves, the ad creative is finalized.

[0145] 3. Apparel distribution and advertising

[0146] The user selects the presented apparel item and purchases or rents it.

[0147] The terminal sends the purchase information to the server. The server processes the shipping of the apparel item and delivers it to the user. When the user receives the apparel item, the server confirms receipt and starts the advertisement display counter.

[0148] 4. Collecting location information and measuring advertising effectiveness

[0149] The device periodically acquires the user's GPS location information and sends it to the server, which then analyzes the location information to measure the time spent in a specific location and the visibility of advertisements.

[0150] 5. Calculation and Payment of Rewards

[0151] The server calculates rewards based on the advertising effectiveness and adds points to the user's account. The terminal displays a point-added notification and reward details to the user.

[0152] Specific examples

[0153] User A downloads the app and creates an account. The device sends the basic information entered by User A to the server, which stores it in a database. User A selects a shopping center that he or she frequently visits. Based on User A's profile, the server suggests a T-shirt with an advertisement printed on it that is suitable for that shopping center.

[0154] The server then uses document and image generation algorithms to generate text and visual ads targeted to specific stores within the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[0155] When User A receives the T-shirt and goes to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of the advertising at the shopping center. Finally, the server calculates the reward and adds points to User A's account, and the device displays the reward details.

[0156] Prompt Sentence Examples

[0157] "Regarding the user registration process for the Fashion Ads system, please tell me how the user enters basic information and how that information is sent to the server."

[0158] This prompt can be used to input questions into the generative AI model to obtain detailed information about specific parts of the system.

[0159] This enables the fashion advertising system to efficiently deliver advertisements through the user's daily activities and provide advertising revenue to the user.

[0160] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0161] Specific processing flow of the program

[0162] Step 1: User registration and app installation

[0163] Users download the fashion advertising app from the app store and begin creating an account.

[0164] Input: Install the app, enter basic information (name, age, gender, address)

[0165] Specific behavior: A user installs and launches the app, and fills in an in-app form with information such as their name, age, gender, and address.

[0166] Output: Basic information entered

[0167] Step 2: Submit and save basic information

[0168] The terminal transmits the basic information entered by the user to the server.

[0169] Input: Basic information

[0170] Specific operation: The terminal sends the encoded data to the server.

[0171] Output: Basic information sent to the server

[0172] Step 3: Create a profile

[0173] The server stores the received basic information in a database and creates a profile for the user.

[0174] Input: Basic information submitted

[0175] Specific operations: The server stores basic information in a database and creates a user profile.

[0176] Output: User profile in the database

[0177] Step 4: Enter and save your preferences

[0178] Users select their preferred fashion style and usual places within the app.

[0179] Input: Fashion style, range of activities

[0180] Specific behavior: The user selects their preferred style and range of activities from the app's selection menu.

[0181] Output: Selected preference data

[0182] Step 5: Submit your preferences and update your profile

[0183] The terminal sends the preference data to the server, which updates the profile.

[0184] Input: Your preferred data

[0185] Specific operation: The terminal sends the information and the server adds it to the database.

[0186] Output: Updated user profile

[0187] Step 6: Present recommended apparel items

[0188] The server selects recommended apparel items based on the profile and sends them to the device.

[0189] Input: User profile

[0190] Specific operation: The server analyzes the profile, selects the most suitable items, and sends the information to the device.

[0191] Output: A list of recommended apparel items

[0192] Step 7: Generate ad creative

[0193] The server analyzes user behavioral and location data and generates advertisements using document and image generation algorithms.

[0194] Input: behavioral data, location data

[0195] Specific operation: The server creates text ads using a document generation algorithm and visual ads using an image generation algorithm.

[0196] Output: Generated ad creative

[0197] Step 8: Ad preview and approval

[0198] The terminal displays the generated advertising creative to the user and accepts approval or modification requests.

[0199] Input: Ad creative

[0200] What happens: A preview of the ad is displayed on the device, and the user can choose to approve or request revisions.

[0201] Output: Approved ad creative or revision request

[0202] Step 9: Select and purchase apparel items

[0203] Users can select the best apparel items within the app and purchase or rent them.

[0204] Input: List of recommended apparel items

[0205] Specific behavior: The user selects an item from the list and checks out.

[0206] Output: Purchase information

[0207] Step 10: Submit your purchase and process your shipment

[0208] The terminal transmits the user's purchase information to the server, and the server starts the shipping process.

[0209] Input: Purchase information

[0210] Specific operation: The terminal sends purchase information, the server checks inventory and processes the shipment.

[0211] Output: Shipping confirmation information

[0212] Step 11: Confirm receipt and start the ad display counter

[0213] The user will confirm receipt after receiving the item.

[0214] Input: Receipt confirmation operation

[0215] Specific action: The user presses the confirmation button within the app.

[0216] Output: Receipt confirmation data

[0217] Step 12: Obtaining and sending GPS location information

[0218] The terminal periodically acquires the user's GPS location data and transmits it to the server.

[0219] Input: GPS location data

[0220] Specific operation: The device obtains and transmits location information in the background.

[0221] Output: Location data

[0222] Step 13: Analyze location data and measure advertising effectiveness

[0223] The server analyzes the location information and measures the length of stay and the visibility of the advertisement.

[0224] Input: Location data

[0225] Specific operation: The server analyzes the data and measures visibility and duration of visit.

[0226] Output: Advertising effectiveness data

[0227] Step 14: Calculating rewards and awarding points

[0228] The server calculates rewards for the users based on the measured advertising effectiveness and awards points to the users.

[0229] Input: Advertising effectiveness data

[0230] Specific operation: The server calculates rewards based on the effectiveness data and adds points to the user's account.

[0231] Output: Point award notification

[0232] Step 15: View your compensation statement

[0233] The terminal displays the reward details to the user within the app.

[0234] Input: Point award notification

[0235] Specific operation: The device will display a notification on the reward details screen.

[0236] Output: Remuneration details display

[0237] (Application example 1)

[0238] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0239] Conventional advertising systems have had difficulty integrating and measuring the effectiveness of advertisements that utilize fashion items worn by users in their daily lives. Furthermore, it is even more complicated to measure in real time how advertisements are viewed and their effectiveness through users' in-store behavior. This makes it difficult to optimize rewards to users.

[0240] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0241] In this invention, the server includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to the user, means for measuring the effectiveness of the advertisements based on the user's behavior, means for awarding rewards to the user based on the measured effectiveness, means for measuring the user's behavior while wearing the products in a physical store, and means for notifying the user of the status of the award of the reward. This makes it possible to measure the advertising effectiveness in real time as the user wears the fashion items and engages in daily activities, and to award appropriate rewards based on the effectiveness.

[0242] A "user" is an individual who uses the system to wear an advertised fashion item, and receives rewards based on the results of that wear.

[0243] "Location information" is data that indicates the user's current geographical location.

[0244] "Fashion items" are items such as clothing and accessories that users wear in their daily lives.

[0245] "Recommending" refers to the act of suggesting a particular fashion item based on the user's preferences and behavioral data.

[0246] An "advertisement" is a promotional text or image that offers a product or service to a user.

[0247] "Integration" is the process of incorporating advertising into fashion items.

[0248] "Distribution" refers to the act of providing integrated fashion items to users.

[0249] "Behavioral-based" means measuring the effectiveness of advertising based on user location and activity data.

[0250] "Measuring effectiveness" means quantitatively evaluating the extent of influence an advertisement has.

[0251] "Rewards" are benefits such as money or points that users receive based on the effectiveness of the advertisement.

[0252] A "physical store" is a physical store that a user visits.

[0253] "Notification" refers to informing the user of the status of the reward.

[0254] This invention is a system that integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and provides rewards to users. The system includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to users, means for measuring the effectiveness of the advertisements based on user behavior, means for rewarding users based on the measured effectiveness, means for measuring the behavior of users while wearing the products in physical stores, and means for notifying users of the status of reward awards. The details of this system are described below.

[0255] 1. User registration and apparel selection

[0256] First, users download a dedicated fashion ads application onto their smartphone and create an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to a server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended fashion items based on the user's profile.

[0257] 2. Generating ad creatives

[0258] The server uses document generation AI and image generation AI to generate customized ad text and visual ads based on the user's behavioral and location data. This ad creative is appropriate for the user's attributes and activities, and a preview is displayed to the user. Upon receiving approval or correction requests from the user, the server creates a final version of the ad creative and presents it to the user.

[0259] 3. Apparel distribution and advertising

[0260] When a user selects a fashion item for rent or purchase, the device sends that information to the server. The server processes and delivers the apparel item to the user. The user confirms receipt of the item within the app. This confirmation information is sent from the device to the server, which starts the ad display counter.

[0261] 4. Collecting location information and measuring advertising effectiveness

[0262] The user goes out wearing the relevant fashion item. The device periodically acquires the user's GPS location information and sends it to the server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. This data is used to evaluate the effectiveness of the advertisement.

[0263] 5. Calculation and Payment of Rewards

[0264] The server calculates the reward for the user based on the measured advertising effectiveness and adds points to the user's account. The device notifies the user of the points awarded and displays a reward statement. The user can check and use the reward in the in-app wallet.

[0265] As a concrete example, consider the case where a user visits a shopping mall wearing an "advertising T-shirt." The user sends location information to the server through the app, and the server measures the length of stay and visibility. As a result, points are awarded to the user's account.

[0266] An example of a prompt to input to a generative AI model is:

[0267] "Please send the location information of the user wearing the advertising T-shirt to the server every minute while they are in Shinjuku Shopping Mall."

[0268] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0269] Step 1: User registration and apparel selection

[0270] Here, users download a dedicated fashion ads app onto their smartphone and create an account. The device receives basic information entered by the user (name, age, gender, address, etc.) and sends this to a server. The server stores the entered data in a database as the user's profile. Next, the user selects their preferred fashion style and frequently visited places, and the device sends this information to the server. The server then uses this information to recommend fashion items to the user.

[0271] Step 2: Generate ad creative

[0272] The server uses document generation AI to generate customized ad text based on user behavior and location data, and image generation AI to generate corresponding visual ads. The generated ad creative is previewed by the user, who can approve or request revisions. After any necessary revisions are made, the server retains the final ad creative. The input is user behavior data, location data, and the prompt sentence from the generative AI model, and the output is the customized ad creative.

[0273] Step 3: Apparel distribution and advertising

[0274] When a user rents or purchases a selected fashion item, the device sends that information to the server. The server processes the apparel item and delivers it to the user. When the user confirms in the app that they have received the apparel item, the device sends that information to the server. The server receives this information and starts a counter for displaying advertisements. The input is the purchase information for the fashion item, and the output is the start of the counter for displaying advertisements.

[0275] Step 4: Collecting location information and measuring advertising effectiveness

[0276] When a user goes out wearing a fashion item, the device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the received location information and measures the amount of time spent in a specific location and the visibility of advertisements. The input is the user's GPS location information, and the output is the measurement results of the amount of time spent and visibility. Specifically, location information is acquired at regular intervals (for example, every minute).

[0277] Step 5: Calculating and paying rewards

[0278] The server calculates the reward for the user based on the measured advertising effectiveness and grants points to the user's account. The terminal notifies the user of the points awarded and displays a reward statement. The input is the measurement result of the advertising effectiveness, and the output is the points awarded to the user's account and a notification regarding this. In concrete terms, the reward is calculated based on the effectiveness measurement data, and points are added to the user's wallet.

[0279] Examples of applicable prompts include:

[0280] "Please send the location information of the user wearing the advertising T-shirt to the server every minute while in the shopping mall."

[0281] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0282] The system of the present invention integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and further maximizes the effectiveness of the advertisements by recognizing the user's emotions and adjusting the advertisement creatives accordingly. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[0283] Overall system overview

[0284] 1. User registration and apparel selection

[0285] First, a user downloads the Fashion Ads app and creates an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends this information to the server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended apparel items based on the user's profile.

[0286] 2. Generating ad creatives

[0287] The server uses document generation AI to generate customized ad text based on the user's behavioral and location data, as well as emotional data from the emotion engine. It also uses image generation AI to generate corresponding visual ads. These generated texts and images are combined to create customized ad creatives. The device displays a preview of this ad creative to the user and accepts approval or revision requests from the user. If necessary, the server modifies the ad creative and presents the final version to the user.

[0288] 3. Emotion Recognition by Emotion Engine

[0289] While a user is using the app or wearing an apparel item, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize their emotions. This emotion data is then sent to a server along with the user's behavioral and location data.

[0290] 4. Apparel distribution and advertising

[0291] When a user rents or purchases a selected apparel item, the device sends that information to the server. The server processes the shipment of the apparel item and delivers it to the user. When the user receives the apparel item, they confirm receipt within the app. The device then sends the receipt confirmation information to the server, which starts the ad display counter.

[0292] 5. Collecting location information and measuring advertising effectiveness

[0293] The user goes out wearing the apparel item. The device periodically acquires the user's GPS location information and sends it to the server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. Emotional data is also analyzed to evaluate the effectiveness of the advertisement.

[0294] 6. Calculation and Payment of Rewards

[0295] The server calculates rewards based on advertising effectiveness and adds points to the user's account. The terminal notifies the user of the points and displays a rewards statement. The user can check and use the rewards in the in-app wallet.

[0296] Specific examples

[0297] User B downloads the app and creates an account. The device sends the basic information entered by User B to the server, which stores it in a database. User B then selects a park he or she frequently visits, and the device sends that information to the server. Based on User B's profile, the server recommends sportswear with advertisements printed on it that are suitable for the park.

[0298] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific sports equipment available at the park. User B's recent emotional data (e.g., enjoyment or excitement) is recognized by the emotion engine and reflected in the ad content. The device then displays a preview of the ad design to User B, who approves it. When User B purchases sportswear, the device sends the information to the server, which then ships the apparel item.

[0299] When User B receives the sportswear and heads to the park, the device collects GPS location information and sends it to the server. The server analyzes this data to measure the effectiveness of the advertisement in the park. The analysis also includes emotional data recognized by the emotion engine to evaluate how User B's emotions affect the effectiveness of the advertisement. Finally, the server calculates the reward and adds points to User B's account, and the device displays the reward details.

[0300] This allows the Fashion Ads system to integrate users' daily behavior and emotions to efficiently deliver advertisements and provide advertising revenue to users.

[0301] The processing flow will be explained below.

[0302] Program processing steps

[0303] User registration and apparel selection

[0304] Step 1:

[0305] A user downloads the Fashion Ads app and creates a new account.

[0306] Step 2:

[0307] The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to the server.

[0308] Step 3:

[0309] The server stores the received basic information in a database.

[0310] Step 4:

[0311] Users select their fashion style and frequently visited places on the app's settings screen.

[0312] Step 5:

[0313] The terminal transmits the user's selection information to the server.

[0314] Step 6:

[0315] The server creates a list of recommended fashion items based on the user's profile and sends it to the device.

[0316] Step 7:

[0317] The device displays a list of recommended fashion items to the user.

[0318] Ad creative generation

[0319] Step 1:

[0320] The server uses document generation AI to generate customized ad text based on user behavioral and location data, as well as emotional data provided by the emotion engine.

[0321] Step 2:

[0322] The server uses image generation AI to generate the corresponding visual advertisement.

[0323] Step 3:

[0324] The server combines the generated text and images to create customized ad creative.

[0325] Step 4:

[0326] The server sends the ad creative to the device.

[0327] Step 5:

[0328] The device displays a preview of the ad creative to the user and asks for approval.

[0329] Step 6:

[0330] The user reviews the ad creative and approves or requests revisions.

[0331] Step 7:

[0332] The terminal sends the user's feedback to the server.

[0333] Step 8:

[0334] The server modifies the ad creative as needed and sends the final version to the device.

[0335] Emotion recognition by emotion engine

[0336] Step 1:

[0337] While a user is using the app or wearing an apparel item, the emotion engine collects facial expressions, voice and other biometric information to analyze the user's emotions.

[0338] Step 2:

[0339] The device transmits the collected emotional data to a server in real time.

[0340] Step 3:

[0341] The server stores the received emotion data and uses it to generate advertising creatives and measure effectiveness.

[0342] Apparel distribution and advertising

[0343] Step 1:

[0344] The user rents or purchases the selected apparel item.

[0345] Step 2:

[0346] The terminal transmits the user's rental / purchase information to the server.

[0347] Step 3:

[0348] The server processes the shipping of the apparel item and delivers it to the user.

[0349] Step 4:

[0350] The user receives the apparel item and confirms receipt within the app.

[0351] Step 5:

[0352] The terminal sends a receipt confirmation to the server.

[0353] Step 6:

[0354] The server starts an ad display counter and begins tracking the user's location.

[0355] Collecting location information and measuring advertising effectiveness

[0356] Step 1:

[0357] The user goes out wearing the apparel item.

[0358] Step 2:

[0359] The device periodically acquires the user's GPS location information and sends it to the server.

[0360] Step 3:

[0361] The server analyzes the location information sent and measures the time spent in a particular location and the visibility of the advertisement.

[0362] Step 4:

[0363] The server also analyzes emotional data to evaluate the effectiveness of the advertisement.

[0364] Reward calculation and payment

[0365] Step 1:

[0366] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[0367] Step 2:

[0368] The terminal displays a notification of the points awarded and a reward statement to the user.

[0369] Step 3:

[0370] The user can check and spend rewards in the in-app wallet.

[0371] Specific examples

[0372] User B downloads the app and creates an account. The device sends the basic information entered by User B to the server, which stores it in a database. User B then selects a park he or she frequently visits, and the device sends that information to the server. Based on User B's profile, the server recommends sportswear with advertisements printed on it that are suitable for the park.

[0373] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific sports equipment available in the park. User B's recent emotional data is recognized by the emotion engine and reflected in the ad content. The device displays a preview of the ad design to User B, who approves it. When User B purchases sportswear, the device sends the information to the server, which then ships the apparel item.

[0374] When User B receives the sportswear and heads to the park, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of advertising in the park. The analysis also includes emotional data recognized by the emotion engine to evaluate how User B's emotions affect the effectiveness of the advertising. Finally, the server calculates the reward and awards points to User B's account, and the device displays a reward statement. In this way, the fashion ads system integrates the user's daily behavior and emotions to efficiently deliver advertisements and provide advertising revenue to the user.

[0375] Example 2

[0376] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0377] Conventional advertising delivery systems were unable to fully utilize user behavioral and emotional data, making it difficult to maximize the effectiveness of advertising. Furthermore, there was a lack of a way to provide personalized advertisements to individual users, making it difficult to attract their interest. Furthermore, there were also issues with the inability to efficiently measure advertising effectiveness and award user rewards.

[0378] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0379] In this invention, the server includes means for acquiring user location information, means for recommending clothing based on the user's preferences, means for analyzing and collecting emotion data in real time, means for generating advertisements under specific conditions, means for integrating the generated advertisements into clothing, means for distributing the integrated clothing to the user, means for measuring the effectiveness of the advertisements based on the user's behavior, and means for providing rewards to the user based on the measured effectiveness. This enables the provision of efficient personalized advertisements that integrate user behavior data and emotion data, accurate measurement of advertising effectiveness, and appropriate provision of rewards.

[0380] "User location information" refers to information about the user's current location and movement history.

[0381] "Clothing" refers to clothing and other fashion items worn by a user.

[0382] "Emotional data" refers to data relating to the user's emotional state obtained by analyzing the user's facial expressions, voice, and other biometric information.

[0383] "Generating an advertisement" refers to using document generation AI or image generation AI to create the content of an advertisement to be presented to a user under specific conditions.

[0384] "Integrating advertising" refers to incorporating generated advertising into clothing or other media in a particular way.

[0385] "Measuring the effectiveness of advertising" refers to evaluating the impact of advertising based on user behavior and location information.

[0386] "Providing a reward" refers to providing points or other forms of reward to a user based on the effectiveness of an advertisement.

[0387] An embodiment of the present invention is a system that integrates advertisements into clothing worn by users in their daily lives, measures the effectiveness of the advertisements, and further maximizes the effectiveness of the advertisements by recognizing the user's emotions and adjusting the advertisement creatives. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[0388] First, the user downloads and installs the "Fashion Ads" app and registers an account. The device receives the user's basic information (name, age, gender, address, etc.) and sends it to the server. The server stores the received information in a database. Next, the user enters their preferred fashion style and places they usually visit (e.g., shopping centers, parks, etc.) in the app. The device sends this information to the server, which then presents recommended clothing based on the user's profile.

[0389] The server then uses document generation AI and image generation AI to generate customized ad text and visual ads based on the user's behavioral, location, and emotional data. The device then previews the generated ad creative for the user to evaluate and approve. The server then modifies the ad as needed and presents the final version to the user.

[0390] Furthermore, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize emotional data. The device then transmits this emotional data to the server, which then stores and analyzes it along with behavioral and location data.

[0391] When a user rents or purchases the selected clothing, the device sends the information to the server, which then processes the shipping of the clothing. When the user receives the item and confirms receipt within the app, the device sends the information to the server, which then starts the ad display counter.

[0392] When a user puts on clothing and goes out, the device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the collected location information to measure the length of stay and ad visibility. It also analyzes emotional data and ultimately evaluates the effectiveness of the ad.

[0393] The server calculates rewards for users based on advertising effectiveness and adds points to the user's account. The terminal displays a point-award notification and reward details to the user, who can then check and use the points in the in-app wallet.

[0394] For example, when User B downloads the app and enters his / her basic information, his / her device sends that information to the server, which stores it in a database. When User B selects a park as a place he / she often visits and his / her device sends that information to the server, the server suggests to User B sportswear with advertisements suitable for the park. The server uses document generation AI and image generation AI to generate advertisements targeted at specific sports equipment used in the park. For example, the server uses a prompt sentence such as, "Please create an advertisement based on a scenario in which User B is having fun in the park wearing sportswear."

[0395] In this way, the system of the present invention can maximize the effectiveness of advertising and provide rewards to users by integrating user behavioral data and emotional data to provide efficiently personalized advertisements.

[0396] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0397] Step 1: User registration and apparel selection

[0398] User Registration

[0399] A user downloads and installs the "Fashion Ads" app. They enter basic information (name, age, gender, address, etc.) on the account registration screen.

[0400] Input data: Name, age, gender, address

[0401] The device sends this input information to the server, which stores the received information in a database.

[0402] Output: User profile is saved in the database.

[0403] 1.2. Apparel selection

[0404] Within the app, users select their preferred fashion style and places they usually visit (e.g., shopping centers, parks, etc.).

[0405] Input data: fashion style, places visited

[0406] The device sends this information to a server, which then presents clothing recommendations based on the user's profile.

[0407] Output data: Recommended clothing list

[0408] Step 2: Generate ad creative

[0409] 2.1. Ad Generation

[0410] The server uses document generation AI and image generation AI to generate customized ad text and visual ads based on user behavioral data, location data, and emotional data.

[0411] Input data: user behavior data, location data, emotion data

[0412] The server uses document generation AI to generate advertising text and image generation AI to create visual advertisements.

[0413] Output data: Ad text, visual ad

[0414] 2.2. Ad Preview and Approval

[0415] The device displays a preview of the generated ad creative to the user, who can then review the ad and approve or request modifications.

[0416] Input data: Ad creative, user approval or modification request

[0417] The terminal sends the user's approval or request for correction to the server, which makes any necessary corrections and presents the final version to the user.

[0418] Output data: Final ad creative

[0419] Step 3: Collect and analyze emotion data

[0420] 3.1. Emotion Data Collection

[0421] While the user is using the app, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize emotional data.

[0422] Input data: User's facial expressions, voice, biometric information

[0423] The device sends emotion data to the server, which stores it and uses it for analysis.

[0424] Output data: Emotion data

[0425] Step 4: Apparel distribution and advertising

[0426] 4.1. Purchasing / Renting and Distribution of Apparel Items

[0427] The user rents or purchases the selected clothing, and the device sends the information to the server.

[0428] Input data: Purchase / rental information

[0429] The server processes the shipping of the clothing and delivers it to the user, who then receives the item and confirms receipt within the app.

[0430] Output data: Receipt confirmation information

[0431] 4.2. Starting the ad display counter

[0432] After the user receives and confirms the item, the device sends the information to the server.

[0433] Input data: Receipt confirmation information

[0434] The server starts an ad display counter.

[0435] Output data: Start of ad display counter

[0436] Step 5: Collecting location information and measuring advertising effectiveness

[0437] 5.1. Periodic collection of user location information

[0438] When a user goes out, the device periodically acquires the user's GPS location information and sends it to the server.

[0439] Input data: GPS location information

[0440] The server analyzes the location information collected and measures the length of stay and ad visibility.

[0441] Output data: Ad viewability data

[0442] 5.2. Evaluating advertising effectiveness using emotional data

[0443] The server analyzes the location information and emotional data together to evaluate the effectiveness of the advertisement.

[0444] Input data: location information, emotion data

[0445] The server comprehensively evaluates the effectiveness of the advertisement and stores the results.

[0446] Output data: Advertising effectiveness evaluation data

[0447] Step 6: Calculating and paying rewards

[0448] 6.1. Reward Calculation and Points Awarding

[0449] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[0450] Input data: Advertising effectiveness evaluation data

[0451] The device will notify the user of the points awarded and display a rewards statement, which the user can then use to check and redeem the rewards in the in-app wallet.

[0452] Output data: points, reward details

[0453] (Application example 2)

[0454] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0455] While traditional advertising systems can generate ads based on user location and behavioral data, they lack the ability to recognize user emotions in real time and dynamically adjust ad creatives. As a result, ads are often not as effective as they could be, and the user experience is not optimized. Furthermore, users are not rewarded systematically, which means users lack the motivation to actively engage with ads.

[0456] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to the user, means for measuring the effectiveness of advertisements based on user behavior, means for rewarding the user based on the measured effectiveness, means for recognizing the user's emotions using a smart device and dynamically adjusting advertisement creatives, means for analyzing the visibility and effectiveness of advertisements based on the location information and emotion data, and means for rewarding the user based on the analysis results. This enables advertisements to be displayed optimally based on the user's emotion information, maximizing the effectiveness of advertisements, and the user reward system can motivate users to actively engage with advertisements.

[0457] "Means for obtaining user location information" refers to equipment or software that obtains the user's current location using technology such as GPS.

[0458] A "means for recommending fashion items based on user preferences" refers to a system or algorithm that suggests optimal fashion items based on a user's pre-selected preferences and behavioral data.

[0459] "Means for generating advertisements under specific conditions" refers to an algorithm or system that creates advertisements based on conditions such as location information, user behavior data, or emotional data.

[0460] "Means for integrating generated advertisements into fashion items" refers to techniques or methods for incorporating generated advertising content into fashion items worn by users.

[0461] "Means for distributing integrated fashion items to users" refers to a delivery or distribution system for providing users with fashion items with integrated advertisements.

[0462] "Means for measuring the effectiveness of advertising based on user behavior" refers to a system or method that analyzes user behavior patterns and location data to evaluate the visibility and effectiveness of advertising.

[0463] "Means for rewarding users based on measured effectiveness" refers to a system or algorithm that evaluates the effectiveness of an advertisement and rewards users based on the results.

[0464] "Means for recognizing user emotions using smart devices and dynamically adjusting advertising creatives" refers to technologies and methods for analyzing user emotions in real time using smart gadgets and changing and optimizing advertising content based on the results.

[0465] "Means for analyzing the visibility and effectiveness of advertisements based on location information and emotional data" refers to a system or algorithm that uses user location information and emotional data to perform a detailed analysis of the effectiveness of advertisements.

[0466] The "means for providing a reward to a user based on the analysis results" refers to a system or program that provides a reward to a user based on the analysis results of the advertising effectiveness.

[0467] The present invention provides a system for allowing users to experience advertisements integrated into fashion items and maximizing the effectiveness of the advertisements. The specific configuration and operation procedure of the system will be described below.

[0468] (System Configuration)

[0469] The system consists of a server, a terminal (smart device), a user, and an emotion engine. The specific hardware and software used include the following:

[0470] Smart device: smart glasses, smartphone, or head-mounted display

[0471] Emotion engine: Emotion API

[0472] Generative AI models: Document generation AI (GPT-4 (registered trademark)), Image generation AI (DALL-E)

[0473] Cloud services: AWS (registered trademark), Google (registered trademark) Cloud Platform

[0474] (System operation procedure)

[0475] 1. User registration and apparel selection

[0476] A user uses a smart device app to create an account. The device receives basic information (such as name, age, gender, and address) and sends it to the server, which stores it in a database. The user then selects their preferred fashion style and favorite places, and the device sends the information to the server. The server then presents recommended fashion items based on the user's profile.

[0477] 2. Generating ad creatives

[0478] The server uses a generative AI model to create ad text and visual ads based on the user's behavioral, location, and emotional data, using the following prompt:

[0479] {"When a user is enjoying a run in the park, if the emotion engine detects the emotion of enjoyment, it will generate and display an advertisement for a specific sporting goods in real time."}

[0480] The resulting ad creative can be previewed by the user for approval or revision requests.

[0481] 3. Emotion Recognition by Emotion Engine

[0482] While the user is using the app, the smart device's built-in camera and microphone collect the user's facial expressions and voice, which are then analyzed in real time by the emotion engine. The analysis results are sent to the server and used to dynamically adjust the advertising creative.

[0483] 4. Apparel distribution and advertising

[0484] When a user purchases a selected apparel item, the device sends the information to the server, which handles the shipping process. Once the item is received, the integrated advertisement is displayed and the user can use it.

[0485] 5. Location information and advertising effectiveness measurement

[0486] When a user wears the item and goes out, the device periodically acquires GPS location information and sends it to the server. The server analyzes the location information and emotion data to evaluate the effectiveness of the advertisement. The following prompt sentence is used:

[0487] {"When a user visits a shopping mall, if the emotion engine detects that the user is smiling, it will generate and display ads tailored to positive emotions in real time."}

[0488] 6. Calculation and Payment of Rewards

[0489] The server calculates rewards based on the visibility and effectiveness of the advertisement and awards points to the user's account. The terminal displays a notification to the user that points have been awarded.

[0490] By implementing this system, it becomes possible to display advertisements that are optimized based on the user's emotional information, maximizing the effectiveness of advertisements, and the system for providing rewards to users can motivate them to actively participate in advertisements.

[0491] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0492] Step 1:

[0493] A user registers with the app using a smart device (smart glasses or smartphone). The user enters basic information (name, age, gender, address), which the device then sends to the server. The server stores the received information in a database. The input is basic information from the user, and the output is storing the information in the database.

[0494] Step 2:

[0495] Within the app, users select their preferred fashion style and frequently visited locations. The device sends this information to the server, which then presents recommended fashion items based on the user's profile. The input is the user's fashion style and behavioral pattern information, and the output is a list of recommended fashion items.

[0496] Step 3:

[0497] The server uses document generation AI (GPT-4) and image generation AI (DALL-E) to create ad text and visual ads based on user behavioral data, location data, and emotional data. Prompt text is used for this. The generated ad creative is previewed to the user via their device, and they can approve or request revisions. The input is the user's behavioral data and emotional data, and the output is the generated ad creative.

[0498] Step 4:

[0499] While a user is using the app, the smart device's built-in camera and microphone collect the user's facial expressions and voice, which are then analyzed in real time by the emotion engine (Emotion API). The analysis results are sent to the server and used to dynamically adjust advertising creatives. The input is the user's facial and voice data, and the output is analyzed emotional data.

[0500] Step 5:

[0501] When a user purchases or rents a selected apparel item, the terminal sends the information to the server, which then handles the shipping process. When the user receives the item, a receipt confirmation is sent from the terminal to the server. The input is the purchase or rental information, and the output is the receipt confirmation information and the delivery of the apparel item.

[0502] Step 6:

[0503] When a user wears an item and goes out, the device periodically acquires GPS location information and sends it to the server. The server analyzes this information and measures the visibility and dwell time of the advertisement in a specific location. The input is the GPS location information, and the output is the evaluation results of visibility and effectiveness.

[0504] Step 7:

[0505] The server evaluates the effectiveness of the advertisement and calculates the reward based on the emotion data and location data. The calculated reward is awarded as points to the user's account, and the device displays a reward notification. The input is the evaluation result of the advertisement effectiveness, and the output is the points awarded to the user's account and the reward notification.

[0506] This system optimizes ad display based on user emotions and location information, maximizing advertising effectiveness. In addition, users are rewarded systematically, encouraging active user engagement with ads.

[0507] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0508] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0509] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0510] [Second embodiment]

[0511] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0512] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0513] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0514] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0515] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0516] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0517] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0518] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0519] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0520] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0521] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0522] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0523] The system of the present invention integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and provides rewards to users. The main elements of this system are a server, a terminal, and a user.

[0524] Overall system overview

[0525] 1. User registration and apparel selection

[0526] First, a user downloads the Fashion Ads app and creates an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends this information to the server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended apparel items based on the user's profile.

[0527] 2. Generating ad creatives

[0528] The server uses document generation AI to generate customized ad text based on the user's behavioral and location data. It also uses image generation AI to generate corresponding visual ads. These generated texts and images are combined to create customized ad creatives. The device displays a preview of this ad creative to the user and accepts approval or revision requests from the user. If necessary, the server modifies the ad creative and presents the final version to the user.

[0529] 3. Apparel distribution and advertising

[0530] When a user rents or purchases a selected apparel item, the device sends that information to the server. The server processes the shipment of the apparel item and delivers it to the user. When the user receives the apparel item, they confirm receipt within the app. The device then sends the receipt confirmation information to the server, which starts the ad display counter.

[0531] 4. Collecting location information and measuring advertising effectiveness

[0532] The user wears an apparel item and goes out. The device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. This allows the effectiveness of the advertisement to be evaluated.

[0533] 5. Calculation and Payment of Rewards

[0534] The server calculates rewards based on advertising effectiveness and adds points to the user's account. The terminal notifies the user of the points and displays a rewards statement. The user can check and use the rewards in the in-app wallet.

[0535] Specific examples

[0536] User A downloads the app and creates an account. The device sends the basic information entered by User A to the server, which stores it in a database. User A selects a shopping center that he or she frequently visits. Based on User A's profile, the server suggests a T-shirt with an advertisement printed on it that is suitable for that shopping center.

[0537] The server then uses document generation AI and image generation AI to generate text and visual ads targeted to specific stores in the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[0538] When User A receives the T-shirt and goes to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of the advertising at the shopping center. Finally, the server calculates the reward and adds points to User A's account, and the device displays the reward details.

[0539] This enables the Fashion Ads System to efficiently deliver advertisements through users' daily activities and provide advertising revenue to users.

[0540] The processing flow will be explained below.

[0541] Program processing steps

[0542] User registration and apparel selection

[0543] Step 1:

[0544] A user downloads the Fashion Ads app and creates a new account.

[0545] Step 2:

[0546] The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to the server.

[0547] Step 3:

[0548] The server stores the received basic information in a database.

[0549] Step 4:

[0550] Users select their fashion style and frequently visited places on the app's settings screen.

[0551] Step 5:

[0552] The terminal transmits the user's selection information to the server.

[0553] Step 6:

[0554] The server creates a list of recommended apparel items based on the user's profile and sends it to the terminal.

[0555] Step 7:

[0556] The device displays a list of recommended apparel items to the user.

[0557] Ad creative generation

[0558] Step 1:

[0559] The server uses document generation AI to generate customized ad text based on user behavioral and location data.

[0560] Step 2:

[0561] The server uses image generation AI to generate the corresponding visual advertisement.

[0562] Step 3:

[0563] The server combines the generated text and images to create customized ad creative.

[0564] Step 4:

[0565] The server sends the ad creative to the device.

[0566] Step 5:

[0567] The device displays a preview of the ad creative to the user and asks for approval.

[0568] Step 6:

[0569] The user reviews the ad creative and approves or requests revisions.

[0570] Step 7:

[0571] The terminal sends the user's feedback to the server.

[0572] Step 8:

[0573] The server modifies the ad creative as needed and sends the final version to the device.

[0574] Apparel distribution and advertising

[0575] Step 1:

[0576] The user rents or purchases the selected apparel item.

[0577] Step 2:

[0578] The terminal transmits the user's rental / purchase information to the server.

[0579] Step 3:

[0580] The server processes the shipping of the apparel item and delivers it to the user.

[0581] Step 4:

[0582] The user receives the apparel item and confirms receipt within the app.

[0583] Step 5:

[0584] The terminal sends a receipt confirmation to the server.

[0585] Step 6:

[0586] The server starts an ad display counter and begins tracking the user's location.

[0587] Collecting location information and measuring advertising effectiveness

[0588] Step 1:

[0589] The user goes out wearing the apparel item.

[0590] Step 2:

[0591] The device periodically acquires the user's GPS location information and sends it to the server.

[0592] Step 3:

[0593] The server analyzes the location information sent and measures the time spent in a particular location and the visibility of the advertisement.

[0594] Step 4:

[0595] The server evaluates the effectiveness of the advertisement based on the analysis results.

[0596] Reward calculation and payment

[0597] Step 1:

[0598] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[0599] Step 2:

[0600] The terminal displays a notification of the points awarded and a reward statement to the user.

[0601] Step 3:

[0602] The user can check and spend rewards in the in-app wallet.

[0603] Specific examples

[0604] After downloading the app, User A creates an account and enters basic information. The device sends this information to the server, which stores it in a database. User A then selects a shopping center that he or she frequently visits, and the device sends this information to the server. Based on User A's profile, the server recommends a T-shirt with an advertisement printed on it that is appropriate for that shopping center.

[0605] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific stores in the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[0606] When User A receives the T-shirt and heads to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and calculates the effectiveness of the shopping center's advertising. Finally, the server calculates rewards and adds points to User A's account, and the device displays a reward statement. In this way, the Fashion Ads system can efficiently deliver advertisements through the user's daily activities and provide advertising revenue to the user.

[0607] Example 1

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

[0609] Conventional advertising systems have difficulty effectively utilizing users' daily behavior and location information to increase the visibility and effectiveness of ads, and have been unable to provide appropriate rewards to users. Furthermore, customizing ads and providing apparel items tailored to users' preferences have been limited. For these reasons, there has been a demand for a system that provides high satisfaction for both advertisers and users.

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

[0611] In this invention, the server includes a means for acquiring user location information, a means for recommending clothing based on the user's preferences, and a means for analyzing the user's behavioral data and location data, which makes it possible to effectively deliver advertisements based on the user's daily behavior and location information, measure advertisement visibility and dwell time, and provide appropriate rewards to the user.

[0612] The "means for acquiring user location information" refers to a device or system that has the function of collecting data indicating the user's current location.

[0613] A "means for recommending clothing items based on user preferences" is a device or system that has the function of suggesting optimal clothing items based on data related to the user's tastes and preferences.

[0614] The "means for analyzing user behavioral data and location data" refers to a device or system that has the function of analyzing a user's behavioral history and location information and extracting useful information based on this.

[0615] An "advertising generating means" is a device or system that has the functionality to create advertising content tailored to a specific purpose or target.

[0616] A "means for integrating generated advertising into apparel" is a device or system that has the functionality to incorporate generated advertising content into apparel, either physically or digitally.

[0617] The "means for distributing clothing items to users" refers to a device or system that has the function of providing selected clothing items to users.

[0618] The "means for measuring the visibility of advertisements and the length of stay" refers to a device or system that has the function of measuring the time a user views an advertisement or the time a user stays in a particular place.

[0619] The "means for rewarding users based on measured visibility and length of stay" refers to a device or system that has the function of providing appropriate rewards based on the user's behavior toward the advertisement and length of stay.

[0620] A "document generation algorithm" is a computational method or program for automatically generating text data.

[0621] An "image generation algorithm" is a computational method or program for automatically creating visual content.

[0622] The "means for previewing and approving advertising creatives" refers to a device or system that has the function of displaying generated advertising content in advance and obtaining approval from a user or administrator.

[0623] The present invention is a system that integrates advertisements into clothing worn by users in their daily lives and provides rewards to users by measuring the effectiveness of the advertisements. The system is composed of a server, terminals, and users.

[0624] System Configuration

[0625] The main components of the system are a means for acquiring user location information, a means for recommending clothing items based on user preferences, a means for analyzing behavioral and location data, a means for generating advertisements, a means for integrating the generated advertisements into clothing items, a means for distributing the clothing items to users, a means for measuring the visibility and dwell time of advertisements, and a means for rewarding users based on the measured visibility and dwell time.

[0626] 1. User registration and apparel selection

[0627] Users download the fashion advertising app, create an account, enter basic information (such as name, age, gender, and address), and select their preferred fashion style and frequently visited places (such as shopping centers) within the app.

[0628] The device sends the entered basic information to the server, which stores the received information in a database and presents recommended apparel items based on the user's profile.

[0629] 2. Generating ad creatives

[0630] The server analyzes the user's behavioral and location data and utilizes document and image generation algorithms to generate customized ad text and visual ads.

[0631] The terminal displays a preview of the generated ad creative to the user and accepts approval or a request for modification. If the user approves, the ad creative is finalized.

[0632] 3. Apparel distribution and advertising

[0633] The user selects the presented apparel item and purchases or rents it.

[0634] The terminal sends the purchase information to the server. The server processes the shipping of the apparel item and delivers it to the user. When the user receives the apparel item, the server confirms receipt and starts the advertisement display counter.

[0635] 4. Collecting location information and measuring advertising effectiveness

[0636] The device periodically acquires the user's GPS location information and sends it to the server, which then analyzes the location information to measure the time spent in a specific location and the visibility of advertisements.

[0637] 5. Calculation and Payment of Rewards

[0638] The server calculates rewards based on the advertising effectiveness and adds points to the user's account. The terminal displays a point-added notification and reward details to the user.

[0639] Specific examples

[0640] User A downloads the app and creates an account. The device sends the basic information entered by User A to the server, which stores it in a database. User A selects a shopping center that he or she frequently visits. Based on User A's profile, the server suggests a T-shirt with an advertisement printed on it that is suitable for that shopping center.

[0641] The server then uses document and image generation algorithms to generate text and visual ads targeted to specific stores within the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[0642] When User A receives the T-shirt and goes to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of the advertising at the shopping center. Finally, the server calculates the reward and adds points to User A's account, and the device displays the reward details.

[0643] Prompt Sentence Examples

[0644] "Regarding the user registration process for the Fashion Ads system, please tell me how the user enters basic information and how that information is sent to the server."

[0645] This prompt can be used to input questions into the generative AI model to obtain detailed information about specific parts of the system.

[0646] This enables the fashion advertising system to efficiently deliver advertisements through the user's daily activities and provide advertising revenue to the user.

[0647] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0648] Specific processing flow of the program

[0649] Step 1: User registration and app installation

[0650] Users download the fashion advertising app from the app store and begin creating an account.

[0651] Input: Install the app, enter basic information (name, age, gender, address)

[0652] Specific behavior: A user installs and launches the app, and fills in an in-app form with information such as their name, age, gender, and address.

[0653] Output: Basic information entered

[0654] Step 2: Submit and save basic information

[0655] The terminal transmits the basic information entered by the user to the server.

[0656] Input: Basic information

[0657] Specific operation: The terminal sends the encoded data to the server.

[0658] Output: Basic information sent to the server

[0659] Step 3: Create a profile

[0660] The server stores the received basic information in a database and creates a profile for the user.

[0661] Input: Basic information submitted

[0662] Specific operations: The server stores basic information in a database and creates a user profile.

[0663] Output: User profile in the database

[0664] Step 4: Enter and save your preferences

[0665] Users select their preferred fashion style and usual places within the app.

[0666] Input: Fashion style, range of activities

[0667] Specific behavior: The user selects their preferred style and range of activities from the app's selection menu.

[0668] Output: Selected preference data

[0669] Step 5: Submit your preferences and update your profile

[0670] The terminal sends the preference data to the server, which updates the profile.

[0671] Input: Your preferred data

[0672] Specific operation: The terminal sends the information and the server adds it to the database.

[0673] Output: Updated user profile

[0674] Step 6: Present recommended apparel items

[0675] The server selects recommended apparel items based on the profile and sends them to the device.

[0676] Input: User profile

[0677] Specific operation: The server analyzes the profile, selects the most suitable items, and sends the information to the device.

[0678] Output: A list of recommended apparel items

[0679] Step 7: Generate ad creative

[0680] The server analyzes user behavioral and location data and generates advertisements using document and image generation algorithms.

[0681] Input: behavioral data, location data

[0682] Specific operation: The server creates text ads using a document generation algorithm and visual ads using an image generation algorithm.

[0683] Output: Generated ad creative

[0684] Step 8: Ad preview and approval

[0685] The terminal displays the generated advertising creative to the user and accepts approval or modification requests.

[0686] Input: Ad creative

[0687] What happens: A preview of the ad is displayed on the device, and the user can choose to approve or request revisions.

[0688] Output: Approved ad creative or revision request

[0689] Step 9: Select and purchase apparel items

[0690] Users can select the best apparel items within the app and purchase or rent them.

[0691] Input: List of recommended apparel items

[0692] Specific behavior: The user selects an item from the list and checks out.

[0693] Output: Purchase information

[0694] Step 10: Submit your purchase and process your shipment

[0695] The terminal transmits the user's purchase information to the server, and the server starts the shipping process.

[0696] Input: Purchase information

[0697] Specific operation: The terminal sends purchase information, the server checks inventory and processes the shipment.

[0698] Output: Shipping confirmation information

[0699] Step 11: Confirm receipt and start the ad display counter

[0700] The user will confirm receipt after receiving the item.

[0701] Input: Receipt confirmation operation

[0702] Specific action: The user presses the confirmation button within the app.

[0703] Output: Receipt confirmation data

[0704] Step 12: Obtaining and sending GPS location information

[0705] The terminal periodically acquires the user's GPS location data and transmits it to the server.

[0706] Input: GPS location data

[0707] Specific operation: The device obtains and transmits location information in the background.

[0708] Output: Location data

[0709] Step 13: Analyze location data and measure advertising effectiveness

[0710] The server analyzes the location information and measures the length of stay and the visibility of the advertisement.

[0711] Input: Location data

[0712] Specific operation: The server analyzes the data and measures visibility and duration of visit.

[0713] Output: Advertising effectiveness data

[0714] Step 14: Calculating rewards and awarding points

[0715] The server calculates rewards for the users based on the measured advertising effectiveness and awards points to the users.

[0716] Input: Advertising effectiveness data

[0717] Specific operation: The server calculates rewards based on the effectiveness data and adds points to the user's account.

[0718] Output: Point award notification

[0719] Step 15: View your compensation statement

[0720] The terminal displays the reward details to the user within the app.

[0721] Input: Point award notification

[0722] Specific operation: The device will display a notification on the reward details screen.

[0723] Output: Remuneration details display

[0724] (Application example 1)

[0725] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0726] Conventional advertising systems have had difficulty integrating and measuring the effectiveness of advertisements that utilize fashion items worn by users in their daily lives. Furthermore, it is even more complicated to measure in real time how advertisements are viewed and their effectiveness through users' in-store behavior. This makes it difficult to optimize rewards to users.

[0727] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0728] In this invention, the server includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to the user, means for measuring the effectiveness of the advertisements based on the user's behavior, means for awarding rewards to the user based on the measured effectiveness, means for measuring the user's behavior while wearing the products in a physical store, and means for notifying the user of the status of the award of the reward. This makes it possible to measure the advertising effectiveness in real time as the user wears the fashion items and engages in daily activities, and to award appropriate rewards based on the effectiveness.

[0729] A "user" is an individual who uses the system to wear an advertised fashion item, and receives rewards based on the results of that wear.

[0730] "Location information" is data that indicates the user's current geographical location.

[0731] "Fashion items" are items such as clothing and accessories that users wear in their daily lives.

[0732] "Recommending" refers to the act of suggesting a particular fashion item based on the user's preferences and behavioral data.

[0733] An "advertisement" is a promotional text or image that offers a product or service to a user.

[0734] "Integration" is the process of incorporating advertising into fashion items.

[0735] "Distribution" refers to the act of providing integrated fashion items to users.

[0736] "Behavioral-based" means measuring the effectiveness of advertising based on user location and activity data.

[0737] "Measuring effectiveness" means quantitatively evaluating the extent of influence an advertisement has.

[0738] "Rewards" are benefits such as money or points that users receive based on the effectiveness of the advertisement.

[0739] A "physical store" is a physical store that a user visits.

[0740] "Notification" refers to informing the user of the status of the reward.

[0741] This invention is a system that integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and provides rewards to users. The system includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to users, means for measuring the effectiveness of the advertisements based on user behavior, means for rewarding users based on the measured effectiveness, means for measuring the behavior of users while wearing the products in physical stores, and means for notifying users of the status of reward awards. The details of this system are described below.

[0742] 1. User registration and apparel selection

[0743] First, users download a dedicated fashion ads application onto their smartphone and create an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to a server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended fashion items based on the user's profile.

[0744] 2. Generating ad creatives

[0745] The server uses document generation AI and image generation AI to generate customized ad text and visual ads based on the user's behavioral and location data. This ad creative is appropriate for the user's attributes and activities, and a preview is displayed to the user. Upon receiving approval or correction requests from the user, the server creates a final version of the ad creative and presents it to the user.

[0746] 3. Apparel distribution and advertising

[0747] When a user selects a fashion item for rent or purchase, the device sends that information to the server. The server processes and delivers the apparel item to the user. The user confirms receipt of the item within the app. This confirmation information is sent from the device to the server, which starts the ad display counter.

[0748] 4. Collecting location information and measuring advertising effectiveness

[0749] The user goes out wearing the relevant fashion item. The device periodically acquires the user's GPS location information and sends it to the server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. This data is used to evaluate the effectiveness of the advertisement.

[0750] 5. Calculation and Payment of Rewards

[0751] The server calculates the reward for the user based on the measured advertising effectiveness and adds points to the user's account. The device notifies the user of the points awarded and displays a reward statement. The user can check and use the reward in the in-app wallet.

[0752] As a concrete example, consider the case where a user visits a shopping mall wearing an "advertising T-shirt." The user sends location information to the server through the app, and the server measures the length of stay and visibility. As a result, points are awarded to the user's account.

[0753] An example of a prompt to input to a generative AI model is:

[0754] "Please send the location information of the user wearing the advertising T-shirt to the server every minute while they are in Shinjuku Shopping Mall."

[0755] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0756] Step 1: User registration and apparel selection

[0757] Here, users download a dedicated fashion ads app onto their smartphone and create an account. The device receives basic information entered by the user (name, age, gender, address, etc.) and sends this to a server. The server stores the entered data in a database as the user's profile. Next, the user selects their preferred fashion style and frequently visited places, and the device sends this information to the server. The server then uses this information to recommend fashion items to the user.

[0758] Step 2: Generate ad creative

[0759] The server uses document generation AI to generate customized ad text based on user behavior and location data, and image generation AI to generate corresponding visual ads. The generated ad creative is previewed by the user, who can approve or request revisions. After any necessary revisions are made, the server retains the final ad creative. The input is user behavior data, location data, and the prompt sentence from the generative AI model, and the output is the customized ad creative.

[0760] Step 3: Apparel distribution and advertising

[0761] When a user rents or purchases a selected fashion item, the device sends that information to the server. The server processes the apparel item and delivers it to the user. When the user confirms in the app that they have received the apparel item, the device sends that information to the server. The server receives this information and starts a counter for displaying advertisements. The input is the purchase information for the fashion item, and the output is the start of the counter for displaying advertisements.

[0762] Step 4: Collecting location information and measuring advertising effectiveness

[0763] When a user goes out wearing a fashion item, the device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the received location information and measures the amount of time spent in a specific location and the visibility of advertisements. The input is the user's GPS location information, and the output is the measurement results of the amount of time spent and visibility. Specifically, location information is acquired at regular intervals (for example, every minute).

[0764] Step 5: Calculating and paying rewards

[0765] The server calculates the reward for the user based on the measured advertising effectiveness and grants points to the user's account. The terminal notifies the user of the points awarded and displays a reward statement. The input is the measurement result of the advertising effectiveness, and the output is the points awarded to the user's account and a notification regarding this. In concrete terms, the reward is calculated based on the effectiveness measurement data, and points are added to the user's wallet.

[0766] Examples of applicable prompts include:

[0767] "Please send the location information of the user wearing the advertising T-shirt to the server every minute while in the shopping mall."

[0768] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0769] The system of the present invention integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and further maximizes the effectiveness of the advertisements by recognizing the user's emotions and adjusting the advertisement creatives accordingly. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[0770] Overall system overview

[0771] 1. User registration and apparel selection

[0772] First, a user downloads the Fashion Ads app and creates an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends this information to the server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended apparel items based on the user's profile.

[0773] 2. Generating ad creatives

[0774] The server uses document generation AI to generate customized ad text based on the user's behavioral and location data, as well as emotional data from the emotion engine. It also uses image generation AI to generate corresponding visual ads. These generated texts and images are combined to create customized ad creatives. The device displays a preview of this ad creative to the user and accepts approval or revision requests from the user. If necessary, the server modifies the ad creative and presents the final version to the user.

[0775] 3. Emotion Recognition by Emotion Engine

[0776] While a user is using the app or wearing an apparel item, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize their emotions. This emotion data is then sent to a server along with the user's behavioral and location data.

[0777] 4. Apparel distribution and advertising

[0778] When a user rents or purchases a selected apparel item, the device sends that information to the server. The server processes the shipment of the apparel item and delivers it to the user. When the user receives the apparel item, they confirm receipt within the app. The device then sends the receipt confirmation information to the server, which starts the ad display counter.

[0779] 5. Collecting location information and measuring advertising effectiveness

[0780] The user goes out wearing the apparel item. The device periodically acquires the user's GPS location information and sends it to the server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. Emotional data is also analyzed to evaluate the effectiveness of the advertisement.

[0781] 6. Calculation and Payment of Rewards

[0782] The server calculates rewards based on advertising effectiveness and adds points to the user's account. The terminal notifies the user of the points and displays a rewards statement. The user can check and use the rewards in the in-app wallet.

[0783] Specific examples

[0784] User B downloads the app and creates an account. The device sends the basic information entered by User B to the server, which stores it in a database. User B then selects a park he or she frequently visits, and the device sends that information to the server. Based on User B's profile, the server recommends sportswear with advertisements printed on it that are suitable for the park.

[0785] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific sports equipment available at the park. User B's recent emotional data (e.g., enjoyment or excitement) is recognized by the emotion engine and reflected in the ad content. The device then displays a preview of the ad design to User B, who approves it. When User B purchases sportswear, the device sends the information to the server, which then ships the apparel item.

[0786] When User B receives the sportswear and heads to the park, the device collects GPS location information and sends it to the server. The server analyzes this data to measure the effectiveness of the advertisement in the park. The analysis also includes emotional data recognized by the emotion engine to evaluate how User B's emotions affect the effectiveness of the advertisement. Finally, the server calculates the reward and adds points to User B's account, and the device displays the reward details.

[0787] This allows the Fashion Ads system to integrate users' daily behavior and emotions to efficiently deliver advertisements and provide advertising revenue to users.

[0788] The processing flow will be explained below.

[0789] Program processing steps

[0790] User registration and apparel selection

[0791] Step 1:

[0792] A user downloads the Fashion Ads app and creates a new account.

[0793] Step 2:

[0794] The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to the server.

[0795] Step 3:

[0796] The server stores the received basic information in a database.

[0797] Step 4:

[0798] Users select their fashion style and frequently visited places on the app's settings screen.

[0799] Step 5:

[0800] The terminal transmits the user's selection information to the server.

[0801] Step 6:

[0802] The server creates a list of recommended fashion items based on the user's profile and sends it to the device.

[0803] Step 7:

[0804] The device displays a list of recommended fashion items to the user.

[0805] Ad creative generation

[0806] Step 1:

[0807] The server uses document generation AI to generate customized ad text based on user behavioral and location data, as well as emotional data provided by the emotion engine.

[0808] Step 2:

[0809] The server uses image generation AI to generate the corresponding visual advertisement.

[0810] Step 3:

[0811] The server combines the generated text and images to create customized ad creative.

[0812] Step 4:

[0813] The server sends the ad creative to the device.

[0814] Step 5:

[0815] The device displays a preview of the ad creative to the user and asks for approval.

[0816] Step 6:

[0817] The user reviews the ad creative and approves or requests revisions.

[0818] Step 7:

[0819] The terminal sends the user's feedback to the server.

[0820] Step 8:

[0821] The server modifies the ad creative as needed and sends the final version to the device.

[0822] Emotion recognition by emotion engine

[0823] Step 1:

[0824] While a user is using the app or wearing an apparel item, the emotion engine collects facial expressions, voice and other biometric information to analyze the user's emotions.

[0825] Step 2:

[0826] The device transmits the collected emotional data to a server in real time.

[0827] Step 3:

[0828] The server stores the received emotion data and uses it to generate advertising creatives and measure effectiveness.

[0829] Apparel distribution and advertising

[0830] Step 1:

[0831] The user rents or purchases the selected apparel item.

[0832] Step 2:

[0833] The terminal transmits the user's rental / purchase information to the server.

[0834] Step 3:

[0835] The server processes the shipping of the apparel item and delivers it to the user.

[0836] Step 4:

[0837] The user receives the apparel item and confirms receipt within the app.

[0838] Step 5:

[0839] The terminal sends a receipt confirmation to the server.

[0840] Step 6:

[0841] The server starts an ad display counter and begins tracking the user's location.

[0842] Collecting location information and measuring advertising effectiveness

[0843] Step 1:

[0844] The user goes out wearing the apparel item.

[0845] Step 2:

[0846] The device periodically acquires the user's GPS location information and sends it to the server.

[0847] Step 3:

[0848] The server analyzes the location information sent and measures the time spent in a particular location and the visibility of the advertisement.

[0849] Step 4:

[0850] The server also analyzes emotional data to evaluate the effectiveness of the advertisement.

[0851] Reward calculation and payment

[0852] Step 1:

[0853] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[0854] Step 2:

[0855] The terminal displays a notification of the points awarded and a reward statement to the user.

[0856] Step 3:

[0857] The user can check and spend rewards in the in-app wallet.

[0858] Specific examples

[0859] User B downloads the app and creates an account. The device sends the basic information entered by User B to the server, which stores it in a database. User B then selects a park he or she frequently visits, and the device sends that information to the server. Based on User B's profile, the server recommends sportswear with advertisements printed on it that are suitable for the park.

[0860] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific sports equipment available in the park. User B's recent emotional data is recognized by the emotion engine and reflected in the ad content. The device displays a preview of the ad design to User B, who approves it. When User B purchases sportswear, the device sends the information to the server, which then ships the apparel item.

[0861] When User B receives the sportswear and heads to the park, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of advertising in the park. The analysis also includes emotional data recognized by the emotion engine to evaluate how User B's emotions affect the effectiveness of the advertising. Finally, the server calculates the reward and awards points to User B's account, and the device displays a reward statement. In this way, the fashion ads system integrates the user's daily behavior and emotions to efficiently deliver advertisements and provide advertising revenue to the user.

[0862] Example 2

[0863] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0864] Conventional advertising delivery systems were unable to fully utilize user behavioral and emotional data, making it difficult to maximize the effectiveness of advertising. Furthermore, there was a lack of a way to provide personalized advertisements to individual users, making it difficult to attract their interest. Furthermore, there were also issues with the inability to efficiently measure advertising effectiveness and award user rewards.

[0865] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0866] In this invention, the server includes means for acquiring user location information, means for recommending clothing based on the user's preferences, means for analyzing and collecting emotion data in real time, means for generating advertisements under specific conditions, means for integrating the generated advertisements into clothing, means for distributing the integrated clothing to the user, means for measuring the effectiveness of the advertisements based on the user's behavior, and means for providing rewards to the user based on the measured effectiveness. This enables the provision of efficient personalized advertisements that integrate user behavior data and emotion data, accurate measurement of advertising effectiveness, and appropriate provision of rewards.

[0867] "User location information" refers to information about the user's current location and movement history.

[0868] "Clothing" refers to clothing and other fashion items worn by a user.

[0869] "Emotional data" refers to data relating to the user's emotional state obtained by analyzing the user's facial expressions, voice, and other biometric information.

[0870] "Generating an advertisement" refers to using document generation AI or image generation AI to create the content of an advertisement to be presented to a user under specific conditions.

[0871] "Integrating advertising" refers to incorporating generated advertising into clothing or other media in a particular way.

[0872] "Measuring the effectiveness of advertising" refers to evaluating the impact of advertising based on user behavior and location information.

[0873] "Providing a reward" refers to providing points or other forms of reward to a user based on the effectiveness of an advertisement.

[0874] An embodiment of the present invention is a system that integrates advertisements into clothing worn by users in their daily lives, measures the effectiveness of the advertisements, and further maximizes the effectiveness of the advertisements by recognizing the user's emotions and adjusting the advertisement creatives. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[0875] First, the user downloads and installs the "Fashion Ads" app and registers an account. The device receives the user's basic information (name, age, gender, address, etc.) and sends it to the server. The server stores the received information in a database. Next, the user enters their preferred fashion style and places they usually visit (e.g., shopping centers, parks, etc.) in the app. The device sends this information to the server, which then presents recommended clothing based on the user's profile.

[0876] The server then uses document generation AI and image generation AI to generate customized ad text and visual ads based on the user's behavioral, location, and emotional data. The device then previews the generated ad creative for the user to evaluate and approve. The server then modifies the ad as needed and presents the final version to the user.

[0877] Furthermore, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize emotional data. The device then transmits this emotional data to the server, which then stores and analyzes it along with behavioral and location data.

[0878] When a user rents or purchases the selected clothing, the device sends the information to the server, which then processes the shipping of the clothing. When the user receives the item and confirms receipt within the app, the device sends the information to the server, which then starts the ad display counter.

[0879] When a user puts on clothing and goes out, the device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the collected location information to measure the length of stay and ad visibility. It also analyzes emotional data and ultimately evaluates the effectiveness of the ad.

[0880] The server calculates rewards for users based on advertising effectiveness and adds points to the user's account. The terminal displays a point-award notification and reward details to the user, who can then check and use the points in the in-app wallet.

[0881] For example, when User B downloads the app and enters his / her basic information, his / her device sends that information to the server, which stores it in a database. When User B selects a park as a place he / she often visits and his / her device sends that information to the server, the server suggests to User B sportswear with advertisements suitable for the park. The server uses document generation AI and image generation AI to generate advertisements targeted at specific sports equipment used in the park. For example, the server uses a prompt sentence such as, "Please create an advertisement based on a scenario in which User B is having fun in the park wearing sportswear."

[0882] In this way, the system of the present invention can maximize the effectiveness of advertising and provide rewards to users by integrating user behavioral data and emotional data to provide efficiently personalized advertisements.

[0883] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0884] Step 1: User registration and apparel selection

[0885] User Registration

[0886] A user downloads and installs the "Fashion Ads" app. They enter basic information (name, age, gender, address, etc.) on the account registration screen.

[0887] Input data: Name, age, gender, address

[0888] The device sends this input information to the server, which stores the received information in a database.

[0889] Output: User profile is saved in the database.

[0890] 1.2. Apparel selection

[0891] Within the app, users select their preferred fashion style and places they usually visit (e.g., shopping centers, parks, etc.).

[0892] Input data: fashion style, places visited

[0893] The device sends this information to a server, which then presents clothing recommendations based on the user's profile.

[0894] Output data: Recommended clothing list

[0895] Step 2: Generate ad creative

[0896] 2.1. Ad Generation

[0897] The server uses document generation AI and image generation AI to generate customized ad text and visual ads based on user behavioral data, location data, and emotional data.

[0898] Input data: user behavior data, location data, emotion data

[0899] The server uses document generation AI to generate advertising text and image generation AI to create visual advertisements.

[0900] Output data: Ad text, visual ad

[0901] 2.2. Ad Preview and Approval

[0902] The device displays a preview of the generated ad creative to the user, who can then review the ad and approve or request modifications.

[0903] Input data: Ad creative, user approval or modification request

[0904] The terminal sends the user's approval or request for correction to the server, which makes any necessary corrections and presents the final version to the user.

[0905] Output data: Final ad creative

[0906] Step 3: Collect and analyze emotion data

[0907] 3.1. Emotion Data Collection

[0908] While the user is using the app, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize emotional data.

[0909] Input data: User's facial expressions, voice, biometric information

[0910] The device sends emotion data to the server, which stores it and uses it for analysis.

[0911] Output data: Emotion data

[0912] Step 4: Apparel distribution and advertising

[0913] 4.1. Purchasing / Renting and Distribution of Apparel Items

[0914] The user rents or purchases the selected clothing, and the device sends the information to the server.

[0915] Input data: Purchase / rental information

[0916] The server processes the shipping of the clothing and delivers it to the user, who then receives the item and confirms receipt within the app.

[0917] Output data: Receipt confirmation information

[0918] 4.2. Starting the ad display counter

[0919] After the user receives and confirms the item, the device sends the information to the server.

[0920] Input data: Receipt confirmation information

[0921] The server starts an ad display counter.

[0922] Output data: Start of ad display counter

[0923] Step 5: Collecting location information and measuring advertising effectiveness

[0924] 5.1. Periodic collection of user location information

[0925] When a user goes out, the device periodically acquires the user's GPS location information and sends it to the server.

[0926] Input data: GPS location information

[0927] The server analyzes the location information collected and measures the length of stay and ad visibility.

[0928] Output data: Ad viewability data

[0929] 5.2. Evaluating advertising effectiveness using emotional data

[0930] The server analyzes the location information and emotional data together to evaluate the effectiveness of the advertisement.

[0931] Input data: location information, emotion data

[0932] The server comprehensively evaluates the effectiveness of the advertisement and stores the results.

[0933] Output data: Advertising effectiveness evaluation data

[0934] Step 6: Calculating and paying rewards

[0935] 6.1. Reward Calculation and Points Awarding

[0936] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[0937] Input data: Advertising effectiveness evaluation data

[0938] The device will notify the user of the points awarded and display a rewards statement, which the user can then use to check and redeem the rewards in the in-app wallet.

[0939] Output data: points, reward details

[0940] (Application example 2)

[0941] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0942] While traditional advertising systems can generate ads based on user location and behavioral data, they lack the ability to recognize user emotions in real time and dynamically adjust ad creatives. As a result, ads are often not as effective as they could be, and the user experience is not optimized. Furthermore, users are not rewarded systematically, which means users lack the motivation to actively engage with ads.

[0943] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to the user, means for measuring the effectiveness of advertisements based on user behavior, means for rewarding the user based on the measured effectiveness, means for recognizing the user's emotions using a smart device and dynamically adjusting advertisement creatives, means for analyzing the visibility and effectiveness of advertisements based on the location information and emotion data, and means for rewarding the user based on the analysis results. This enables advertisements to be displayed optimally based on the user's emotion information, maximizing the effectiveness of advertisements, and the user reward system can motivate users to actively engage with advertisements.

[0944] "Means for obtaining user location information" refers to equipment or software that obtains the user's current location using technology such as GPS.

[0945] A "means for recommending fashion items based on user preferences" refers to a system or algorithm that suggests optimal fashion items based on a user's pre-selected preferences and behavioral data.

[0946] "Means for generating advertisements under specific conditions" refers to an algorithm or system that creates advertisements based on conditions such as location information, user behavior data, or emotional data.

[0947] "Means for integrating generated advertisements into fashion items" refers to techniques or methods for incorporating generated advertising content into fashion items worn by users.

[0948] "Means for distributing integrated fashion items to users" refers to a delivery or distribution system for providing users with fashion items with integrated advertisements.

[0949] "Means for measuring the effectiveness of advertising based on user behavior" refers to a system or method that analyzes user behavior patterns and location data to evaluate the visibility and effectiveness of advertising.

[0950] "Means for rewarding users based on measured effectiveness" refers to a system or algorithm that evaluates the effectiveness of an advertisement and rewards users based on the results.

[0951] "Means for recognizing user emotions using smart devices and dynamically adjusting advertising creatives" refers to technologies and methods for analyzing user emotions in real time using smart gadgets and changing and optimizing advertising content based on the results.

[0952] "Means for analyzing the visibility and effectiveness of advertisements based on location information and emotional data" refers to a system or algorithm that uses user location information and emotional data to perform a detailed analysis of the effectiveness of advertisements.

[0953] The "means for providing a reward to a user based on the analysis results" refers to a system or program that provides a reward to a user based on the analysis results of the advertising effectiveness.

[0954] The present invention provides a system for allowing users to experience advertisements integrated into fashion items and maximizing the effectiveness of the advertisements. The specific configuration and operation procedure of the system will be described below.

[0955] (System Configuration)

[0956] The system consists of a server, a terminal (smart device), a user, and an emotion engine. The specific hardware and software used include the following:

[0957] Smart device: smart glasses, smartphone, or head-mounted display

[0958] Emotion engine: Emotion API

[0959] Generative AI models: Document generation AI (GPT-4), Image generation AI (DALL-E)

[0960] Cloud services: AWS, Google Cloud Platform

[0961] (System operation procedure)

[0962] 1. User registration and apparel selection

[0963] A user uses a smart device app to create an account. The device receives basic information (such as name, age, gender, and address) and sends it to the server, which stores it in a database. The user then selects their preferred fashion style and favorite places, and the device sends the information to the server. The server then presents recommended fashion items based on the user's profile.

[0964] 2. Generating ad creatives

[0965] The server uses a generative AI model to create ad text and visual ads based on the user's behavioral, location, and emotional data, using the following prompt:

[0966] {"When a user is enjoying a run in the park, if the emotion engine detects the emotion of enjoyment, it will generate and display an advertisement for a specific sporting goods in real time."}

[0967] The resulting ad creative can be previewed by the user for approval or revision requests.

[0968] 3. Emotion Recognition by Emotion Engine

[0969] While the user is using the app, the smart device's built-in camera and microphone collect the user's facial expressions and voice, which are then analyzed in real time by the emotion engine. The analysis results are sent to the server and used to dynamically adjust the advertising creative.

[0970] 4. Apparel distribution and advertising

[0971] When a user purchases a selected apparel item, the device sends the information to the server, which handles the shipping process. Once the item is received, the integrated advertisement is displayed and the user can use it.

[0972] 5. Location information and advertising effectiveness measurement

[0973] When a user wears the item and goes out, the device periodically acquires GPS location information and sends it to the server. The server analyzes the location information and emotion data to evaluate the effectiveness of the advertisement. The following prompt sentence is used:

[0974] {"When a user visits a shopping mall, if the emotion engine detects that the user is smiling, it will generate and display ads tailored to positive emotions in real time."}

[0975] 6. Calculation and Payment of Rewards

[0976] The server calculates rewards based on the visibility and effectiveness of the advertisement and awards points to the user's account. The terminal displays a notification to the user that points have been awarded.

[0977] By implementing this system, it becomes possible to display advertisements that are optimized based on the user's emotional information, maximizing the effectiveness of advertisements, and the system for providing rewards to users can motivate them to actively participate in advertisements.

[0978] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0979] Step 1:

[0980] A user registers with the app using a smart device (smart glasses or smartphone). The user enters basic information (name, age, gender, address), which the device then sends to the server. The server stores the received information in a database. The input is basic information from the user, and the output is storing the information in the database.

[0981] Step 2:

[0982] Within the app, users select their preferred fashion style and frequently visited locations. The device sends this information to the server, which then presents recommended fashion items based on the user's profile. The input is the user's fashion style and behavioral pattern information, and the output is a list of recommended fashion items.

[0983] Step 3:

[0984] The server uses document generation AI (GPT-4) and image generation AI (DALL-E) to create ad text and visual ads based on user behavioral data, location data, and emotional data. Prompt text is used for this. The generated ad creative is previewed to the user via their device, and they can approve or request revisions. The input is the user's behavioral data and emotional data, and the output is the generated ad creative.

[0985] Step 4:

[0986] While a user is using the app, the smart device's built-in camera and microphone collect the user's facial expressions and voice, which are then analyzed in real time by the emotion engine (Emotion API). The analysis results are sent to the server and used to dynamically adjust advertising creatives. The input is the user's facial and voice data, and the output is analyzed emotional data.

[0987] Step 5:

[0988] When a user purchases or rents a selected apparel item, the terminal sends the information to the server, which then handles the shipping process. When the user receives the item, a receipt confirmation is sent from the terminal to the server. The input is the purchase or rental information, and the output is the receipt confirmation information and the delivery of the apparel item.

[0989] Step 6:

[0990] When a user wears an item and goes out, the device periodically acquires GPS location information and sends it to the server. The server analyzes this information and measures the visibility and dwell time of the advertisement in a specific location. The input is the GPS location information, and the output is the evaluation results of visibility and effectiveness.

[0991] Step 7:

[0992] The server evaluates the effectiveness of the advertisement and calculates the reward based on the emotion data and location data. The calculated reward is awarded as points to the user's account, and the device displays a reward notification. The input is the evaluation result of the advertisement effectiveness, and the output is the points awarded to the user's account and the reward notification.

[0993] This system optimizes ad display based on user emotions and location information, maximizing advertising effectiveness. In addition, users are rewarded systematically, encouraging active user engagement with ads.

[0994] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0995] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0996] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0997] [Third embodiment]

[0998] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0999] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1000] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1001] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1002] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1003] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1004] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1005] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1006] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1007] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1008] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1009] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1010] The system of the present invention integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and provides rewards to users. The main elements of this system are a server, a terminal, and a user.

[1011] Overall system overview

[1012] 1. User registration and apparel selection

[1013] First, a user downloads the Fashion Ads app and creates an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends this information to the server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended apparel items based on the user's profile.

[1014] 2. Generating ad creatives

[1015] The server uses document generation AI to generate customized ad text based on the user's behavioral and location data. It also uses image generation AI to generate corresponding visual ads. These generated texts and images are combined to create customized ad creatives. The device displays a preview of this ad creative to the user and accepts approval or revision requests from the user. If necessary, the server modifies the ad creative and presents the final version to the user.

[1016] 3. Apparel distribution and advertising

[1017] When a user rents or purchases a selected apparel item, the device sends that information to the server. The server processes the shipment of the apparel item and delivers it to the user. When the user receives the apparel item, they confirm receipt within the app. The device then sends the receipt confirmation information to the server, which starts the ad display counter.

[1018] 4. Collecting location information and measuring advertising effectiveness

[1019] The user wears an apparel item and goes out. The device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. This allows the effectiveness of the advertisement to be evaluated.

[1020] 5. Calculation and Payment of Rewards

[1021] The server calculates rewards based on advertising effectiveness and adds points to the user's account. The terminal notifies the user of the points and displays a rewards statement. The user can check and use the rewards in the in-app wallet.

[1022] Specific examples

[1023] User A downloads the app and creates an account. The device sends the basic information entered by User A to the server, which stores it in a database. User A selects a shopping center that he or she frequently visits. Based on User A's profile, the server suggests a T-shirt with an advertisement printed on it that is suitable for that shopping center.

[1024] The server then uses document generation AI and image generation AI to generate text and visual ads targeted to specific stores in the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[1025] When User A receives the T-shirt and goes to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of the advertising at the shopping center. Finally, the server calculates the reward and adds points to User A's account, and the device displays the reward details.

[1026] This enables the Fashion Ads System to efficiently deliver advertisements through users' daily activities and provide advertising revenue to users.

[1027] The processing flow will be explained below.

[1028] Program processing steps

[1029] User registration and apparel selection

[1030] Step 1:

[1031] A user downloads the Fashion Ads app and creates a new account.

[1032] Step 2:

[1033] The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to the server.

[1034] Step 3:

[1035] The server stores the received basic information in a database.

[1036] Step 4:

[1037] Users select their fashion style and frequently visited places on the app's settings screen.

[1038] Step 5:

[1039] The terminal transmits the user's selection information to the server.

[1040] Step 6:

[1041] The server creates a list of recommended apparel items based on the user's profile and sends it to the terminal.

[1042] Step 7:

[1043] The device displays a list of recommended apparel items to the user.

[1044] Ad creative generation

[1045] Step 1:

[1046] The server uses document generation AI to generate customized ad text based on user behavioral and location data.

[1047] Step 2:

[1048] The server uses image generation AI to generate the corresponding visual advertisement.

[1049] Step 3:

[1050] The server combines the generated text and images to create customized ad creative.

[1051] Step 4:

[1052] The server sends the ad creative to the device.

[1053] Step 5:

[1054] The device displays a preview of the ad creative to the user and asks for approval.

[1055] Step 6:

[1056] The user reviews the ad creative and approves or requests revisions.

[1057] Step 7:

[1058] The terminal sends the user's feedback to the server.

[1059] Step 8:

[1060] The server modifies the ad creative as needed and sends the final version to the device.

[1061] Apparel distribution and advertising

[1062] Step 1:

[1063] The user rents or purchases the selected apparel item.

[1064] Step 2:

[1065] The terminal transmits the user's rental / purchase information to the server.

[1066] Step 3:

[1067] The server processes the shipping of the apparel item and delivers it to the user.

[1068] Step 4:

[1069] The user receives the apparel item and confirms receipt within the app.

[1070] Step 5:

[1071] The terminal sends a receipt confirmation to the server.

[1072] Step 6:

[1073] The server starts an ad display counter and begins tracking the user's location.

[1074] Collecting location information and measuring advertising effectiveness

[1075] Step 1:

[1076] The user goes out wearing the apparel item.

[1077] Step 2:

[1078] The device periodically acquires the user's GPS location information and sends it to the server.

[1079] Step 3:

[1080] The server analyzes the location information sent and measures the time spent in a particular location and the visibility of the advertisement.

[1081] Step 4:

[1082] The server evaluates the effectiveness of the advertisement based on the analysis results.

[1083] Reward calculation and payment

[1084] Step 1:

[1085] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[1086] Step 2:

[1087] The terminal displays a notification of the points awarded and a reward statement to the user.

[1088] Step 3:

[1089] The user can check and spend rewards in the in-app wallet.

[1090] Specific examples

[1091] After downloading the app, User A creates an account and enters basic information. The device sends this information to the server, which stores it in a database. User A then selects a shopping center that he or she frequently visits, and the device sends this information to the server. Based on User A's profile, the server recommends a T-shirt with an advertisement printed on it that is appropriate for that shopping center.

[1092] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific stores in the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[1093] When User A receives the T-shirt and heads to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and calculates the effectiveness of the shopping center's advertising. Finally, the server calculates rewards and adds points to User A's account, and the device displays a reward statement. In this way, the Fashion Ads system can efficiently deliver advertisements through the user's daily activities and provide advertising revenue to the user.

[1094] Example 1

[1095] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1096] Conventional advertising systems have difficulty effectively utilizing users' daily behavior and location information to increase the visibility and effectiveness of ads, and have been unable to provide appropriate rewards to users. Furthermore, customizing ads and providing apparel items tailored to users' preferences have been limited. For these reasons, there has been a demand for a system that provides high satisfaction for both advertisers and users.

[1097] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1098] In this invention, the server includes a means for acquiring user location information, a means for recommending clothing items based on the user's preferences, and a means for analyzing the user's behavioral data and location data, which makes it possible to effectively deliver advertisements based on the user's daily behavior and location information, measure advertisement visibility and dwell time, and provide appropriate rewards to the user.

[1099] The "means for acquiring user location information" refers to a device or system that has the function of collecting data indicating the user's current location.

[1100] A "means for recommending clothing items based on user preferences" is a device or system that has the function of suggesting optimal clothing items based on data related to the user's tastes and preferences.

[1101] The "means for analyzing user behavioral data and location data" refers to a device or system that has the function of analyzing a user's behavioral history and location information and extracting useful information based on this.

[1102] An "advertising generating means" is a device or system that has the functionality to create advertising content tailored to a specific purpose or target.

[1103] A "means for integrating generated advertising into apparel" is a device or system that has the functionality to incorporate generated advertising content into apparel, either physically or digitally.

[1104] The "means for distributing clothing items to users" refers to a device or system that has the function of providing selected clothing items to users.

[1105] The "means for measuring the visibility of advertisements and the length of stay" refers to a device or system that has the function of measuring the time a user views an advertisement or the time a user stays in a particular place.

[1106] The "means for rewarding users based on measured visibility and length of stay" refers to a device or system that has the function of providing appropriate rewards based on the user's behavior toward the advertisement and length of stay.

[1107] A "document generation algorithm" is a computational method or program for automatically generating text data.

[1108] An "image generation algorithm" is a computational method or program for automatically creating visual content.

[1109] The "means for previewing and approving advertising creatives" refers to a device or system that has the function of displaying generated advertising content in advance and obtaining approval from a user or administrator.

[1110] The present invention is a system that integrates advertisements into clothing worn by users in their daily lives and provides rewards to users by measuring the effectiveness of the advertisements. The system is composed of a server, terminals, and users.

[1111] System Configuration

[1112] The main components of the system are a means for acquiring user location information, a means for recommending clothing items based on user preferences, a means for analyzing behavioral and location data, a means for generating advertisements, a means for integrating the generated advertisements into clothing items, a means for distributing the clothing items to users, a means for measuring the visibility and dwell time of advertisements, and a means for rewarding users based on the measured visibility and dwell time.

[1113] 1. User registration and apparel selection

[1114] Users download the fashion advertising app, create an account, enter basic information (such as name, age, gender, and address), and select their preferred fashion style and frequently visited places (such as shopping centers) within the app.

[1115] The device sends the entered basic information to the server, which stores the received information in a database and presents recommended apparel items based on the user's profile.

[1116] 2. Generating ad creatives

[1117] The server analyzes the user's behavioral and location data and utilizes document and image generation algorithms to generate customized ad text and visual ads.

[1118] The terminal displays a preview of the generated ad creative to the user and accepts approval or a request for modification. If the user approves, the ad creative is finalized.

[1119] 3. Apparel distribution and advertising

[1120] The user selects the presented apparel item and purchases or rents it.

[1121] The terminal sends the purchase information to the server. The server processes the shipping of the apparel item and delivers it to the user. When the user receives the apparel item, the server confirms receipt and starts the advertisement display counter.

[1122] 4. Collecting location information and measuring advertising effectiveness

[1123] The device periodically acquires the user's GPS location information and sends it to the server, which then analyzes the location information to measure the time spent in a specific location and the visibility of advertisements.

[1124] 5. Calculation and Payment of Rewards

[1125] The server calculates rewards based on the advertising effectiveness and adds points to the user's account. The terminal displays a point-added notification and reward details to the user.

[1126] Specific examples

[1127] User A downloads the app and creates an account. The device sends the basic information entered by User A to the server, which stores it in a database. User A selects a shopping center that he or she frequently visits. Based on User A's profile, the server suggests a T-shirt with an advertisement printed on it that is suitable for that shopping center.

[1128] The server then uses document and image generation algorithms to generate text and visual ads targeted to specific stores within the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[1129] When User A receives the T-shirt and goes to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of the advertising at the shopping center. Finally, the server calculates the reward and adds points to User A's account, and the device displays the reward details.

[1130] Prompt Sentence Examples

[1131] "Regarding the user registration process for the Fashion Ads system, please tell me how the user enters basic information and how that information is sent to the server."

[1132] This prompt can be used to input questions into the generative AI model to obtain detailed information about specific parts of the system.

[1133] This enables the fashion advertising system to efficiently deliver advertisements through the user's daily activities and provide advertising revenue to the user.

[1134] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1135] Specific processing flow of the program

[1136] Step 1: User registration and app installation

[1137] Users download the fashion advertising app from the app store and begin creating an account.

[1138] Input: Install the app, enter basic information (name, age, gender, address)

[1139] Specific behavior: A user installs and launches the app, and fills in an in-app form with information such as their name, age, gender, and address.

[1140] Output: Basic information entered

[1141] Step 2: Submit and save basic information

[1142] The terminal transmits the basic information entered by the user to the server.

[1143] Input: Basic information

[1144] Specific operation: The terminal sends the encoded data to the server.

[1145] Output: Basic information sent to the server

[1146] Step 3: Create a profile

[1147] The server stores the received basic information in a database and creates a profile for the user.

[1148] Input: Basic information submitted

[1149] Specific operations: The server stores basic information in a database and creates a user profile.

[1150] Output: User profile in the database

[1151] Step 4: Enter and save your preferences

[1152] Users select their preferred fashion style and usual places within the app.

[1153] Input: Fashion style, range of activities

[1154] Specific behavior: The user selects their preferred style and range of activities from the app's selection menu.

[1155] Output: Selected preference data

[1156] Step 5: Submit your preferences and update your profile

[1157] The terminal sends the preference data to the server, which updates the profile.

[1158] Input: Your preferred data

[1159] Specific operation: The terminal sends the information and the server adds it to the database.

[1160] Output: Updated user profile

[1161] Step 6: Present recommended apparel items

[1162] The server selects recommended apparel items based on the profile and sends them to the device.

[1163] Input: User profile

[1164] Specific operation: The server analyzes the profile, selects the most suitable items, and sends the information to the device.

[1165] Output: A list of recommended apparel items

[1166] Step 7: Generate ad creative

[1167] The server analyzes user behavioral and location data and generates advertisements using document and image generation algorithms.

[1168] Input: behavioral data, location data

[1169] Specific operation: The server creates text ads using a document generation algorithm and visual ads using an image generation algorithm.

[1170] Output: Generated ad creative

[1171] Step 8: Ad preview and approval

[1172] The terminal displays the generated advertising creative to the user and accepts approval or modification requests.

[1173] Input: Ad creative

[1174] What happens: A preview of the ad is displayed on the device, and the user can choose to approve or request revisions.

[1175] Output: Approved ad creative or revision request

[1176] Step 9: Select and purchase apparel items

[1177] Users can select the best apparel items within the app and purchase or rent them.

[1178] Input: List of recommended apparel items

[1179] Specific behavior: The user selects an item from the list and checks out.

[1180] Output: Purchase information

[1181] Step 10: Submit your purchase and process your shipment

[1182] The terminal transmits the user's purchase information to the server, and the server starts the shipping process.

[1183] Input: Purchase information

[1184] Specific operation: The terminal sends purchase information, the server checks inventory and processes the shipment.

[1185] Output: Shipping confirmation information

[1186] Step 11: Confirm receipt and start the ad display counter

[1187] The user will confirm receipt after receiving the item.

[1188] Input: Receipt confirmation operation

[1189] Specific action: The user presses the confirmation button within the app.

[1190] Output: Receipt confirmation data

[1191] Step 12: Obtaining and sending GPS location information

[1192] The terminal periodically acquires the user's GPS location data and transmits it to the server.

[1193] Input: GPS location data

[1194] Specific operation: The device obtains and transmits location information in the background.

[1195] Output: Location data

[1196] Step 13: Analyze location data and measure advertising effectiveness

[1197] The server analyzes the location information and measures the length of stay and the visibility of the advertisement.

[1198] Input: Location data

[1199] Specific operation: The server analyzes the data and measures visibility and duration of visit.

[1200] Output: Advertising effectiveness data

[1201] Step 14: Calculating rewards and awarding points

[1202] The server calculates rewards for the users based on the measured advertising effectiveness and awards points to the users.

[1203] Input: Advertising effectiveness data

[1204] Specific operation: The server calculates rewards based on the effectiveness data and adds points to the user's account.

[1205] Output: Point award notification

[1206] Step 15: View your compensation statement

[1207] The terminal displays the reward details to the user within the app.

[1208] Input: Point award notification

[1209] Specific operation: The device will display a notification on the reward details screen.

[1210] Output: Remuneration details display

[1211] (Application example 1)

[1212] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1213] Conventional advertising systems have had difficulty integrating and measuring the effectiveness of advertisements that utilize fashion items worn by users in their daily lives. Furthermore, it is even more complicated to measure in real time how advertisements are viewed and their effectiveness through users' in-store behavior. This makes it difficult to optimize rewards to users.

[1214] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1215] In this invention, the server includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to the user, means for measuring the effectiveness of the advertisements based on the user's behavior, means for awarding rewards to the user based on the measured effectiveness, means for measuring the user's behavior while wearing the products in a physical store, and means for notifying the user of the status of the award of the reward. This makes it possible to measure the advertising effectiveness in real time as the user wears the fashion items and engages in daily activities, and to award appropriate rewards based on the effectiveness.

[1216] A "user" is an individual who uses the system to wear an advertised fashion item, and receives rewards based on the results of that wear.

[1217] "Location information" is data that indicates the user's current geographical location.

[1218] "Fashion items" are items such as clothing and accessories that users wear in their daily lives.

[1219] "Recommending" refers to the act of suggesting a particular fashion item based on the user's preferences and behavioral data.

[1220] An "advertisement" is a promotional text or image that offers a product or service to a user.

[1221] "Integration" is the process of incorporating advertising into fashion items.

[1222] "Distribution" refers to the act of providing integrated fashion items to users.

[1223] "Behavioral-based" means measuring the effectiveness of advertising based on user location and activity data.

[1224] "Measuring effectiveness" means quantitatively evaluating the extent of influence an advertisement has.

[1225] "Rewards" are benefits such as money or points that users receive based on the effectiveness of the advertisement.

[1226] A "physical store" is a physical store that a user visits.

[1227] "Notification" refers to informing the user of the status of the reward.

[1228] This invention is a system that integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and provides rewards to users. The system includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to users, means for measuring the effectiveness of the advertisements based on user behavior, means for rewarding users based on the measured effectiveness, means for measuring the behavior of users while wearing the products in physical stores, and means for notifying users of the status of reward awards. The details of this system are described below.

[1229] 1. User registration and apparel selection

[1230] First, users download a dedicated fashion ads application onto their smartphone and create an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to a server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended fashion items based on the user's profile.

[1231] 2. Generating ad creatives

[1232] The server uses document generation AI and image generation AI to generate customized ad text and visual ads based on the user's behavioral and location data. This ad creative is appropriate for the user's attributes and activities, and a preview is displayed to the user. Upon receiving approval or correction requests from the user, the server creates a final version of the ad creative and presents it to the user.

[1233] 3. Apparel distribution and advertising

[1234] When a user selects a fashion item for rent or purchase, the device sends that information to the server. The server processes and delivers the apparel item to the user. The user confirms receipt of the item within the app. This confirmation information is sent from the device to the server, which starts the ad display counter.

[1235] 4. Collecting location information and measuring advertising effectiveness

[1236] The user goes out wearing the relevant fashion item. The device periodically acquires the user's GPS location information and sends it to the server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. This data is used to evaluate the effectiveness of the advertisement.

[1237] 5. Calculation and Payment of Rewards

[1238] The server calculates the reward for the user based on the measured advertising effectiveness and adds points to the user's account. The device notifies the user of the points awarded and displays a reward statement. The user can check and use the reward in the in-app wallet.

[1239] As a concrete example, consider the case where a user visits a shopping mall wearing an "advertising T-shirt." The user sends location information to the server through the app, and the server measures the length of stay and visibility. As a result, points are awarded to the user's account.

[1240] An example of a prompt to input to a generative AI model is:

[1241] "Please send the location information of the user wearing the advertising T-shirt to the server every minute while they are in Shinjuku Shopping Mall."

[1242] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1243] Step 1: User registration and apparel selection

[1244] Here, users download a dedicated fashion ads app onto their smartphone and create an account. The device receives basic information entered by the user (name, age, gender, address, etc.) and sends this to a server. The server stores the entered data in a database as the user's profile. Next, the user selects their preferred fashion style and frequently visited places, and the device sends this information to the server. The server then uses this information to recommend fashion items to the user.

[1245] Step 2: Generate ad creative

[1246] The server uses document generation AI to generate customized ad text based on user behavior and location data, and image generation AI to generate corresponding visual ads. The generated ad creative is previewed by the user, who can approve or request revisions. After any necessary revisions are made, the server retains the final ad creative. The input is user behavior data, location data, and the prompt sentence from the generative AI model, and the output is the customized ad creative.

[1247] Step 3: Apparel distribution and advertising

[1248] When a user rents or purchases a selected fashion item, the device sends that information to the server. The server processes the apparel item and delivers it to the user. When the user confirms in the app that they have received the apparel item, the device sends that information to the server. The server receives this information and starts a counter for displaying advertisements. The input is the purchase information for the fashion item, and the output is the start of the counter for displaying advertisements.

[1249] Step 4: Collecting location information and measuring advertising effectiveness

[1250] When a user goes out wearing a fashion item, the device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the received location information and measures the amount of time spent in a specific location and the visibility of advertisements. The input is the user's GPS location information, and the output is the measurement results of the amount of time spent and visibility. Specifically, location information is acquired at regular intervals (for example, every minute).

[1251] Step 5: Calculating and paying rewards

[1252] The server calculates the reward for the user based on the measured advertising effectiveness and grants points to the user's account. The terminal notifies the user of the points awarded and displays a reward statement. The input is the measurement result of the advertising effectiveness, and the output is the points awarded to the user's account and a notification regarding this. In concrete terms, the reward is calculated based on the effectiveness measurement data, and points are added to the user's wallet.

[1253] Examples of applicable prompts include:

[1254] "Please send the location information of the user wearing the advertising T-shirt to the server every minute while in the shopping mall."

[1255] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1256] The system of the present invention integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and further maximizes the effectiveness of the advertisements by recognizing the user's emotions and adjusting the advertisement creatives accordingly. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[1257] Overall system overview

[1258] 1. User registration and apparel selection

[1259] First, a user downloads the Fashion Ads app and creates an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends this information to the server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended apparel items based on the user's profile.

[1260] 2. Generating ad creatives

[1261] The server uses document generation AI to generate customized ad text based on the user's behavioral and location data, as well as emotional data from the emotion engine. It also uses image generation AI to generate corresponding visual ads. These generated texts and images are combined to create customized ad creatives. The device displays a preview of this ad creative to the user and accepts approval or revision requests from the user. If necessary, the server modifies the ad creative and presents the final version to the user.

[1262] 3. Emotion Recognition by Emotion Engine

[1263] While a user is using the app or wearing an apparel item, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize their emotions. This emotion data is then sent to a server along with the user's behavioral and location data.

[1264] 4. Apparel distribution and advertising

[1265] When a user rents or purchases a selected apparel item, the device sends that information to the server. The server processes the shipment of the apparel item and delivers it to the user. When the user receives the apparel item, they confirm receipt within the app. The device then sends the receipt confirmation information to the server, which starts the ad display counter.

[1266] 5. Collecting location information and measuring advertising effectiveness

[1267] The user goes out wearing the apparel item. The device periodically acquires the user's GPS location information and sends it to the server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. Emotional data is also analyzed to evaluate the effectiveness of the advertisement.

[1268] 6. Calculation and Payment of Rewards

[1269] The server calculates rewards based on advertising effectiveness and adds points to the user's account. The terminal notifies the user of the points and displays a rewards statement. The user can check and use the rewards in the in-app wallet.

[1270] Specific examples

[1271] User B downloads the app and creates an account. The device sends the basic information entered by User B to the server, which stores it in a database. User B then selects a park he or she frequently visits, and the device sends that information to the server. Based on User B's profile, the server recommends sportswear with advertisements printed on it that are suitable for the park.

[1272] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific sports equipment available at the park. User B's recent emotional data (e.g., enjoyment or excitement) is recognized by the emotion engine and reflected in the ad content. The device then displays a preview of the ad design to User B, who approves it. When User B purchases sportswear, the device sends the information to the server, which then ships the apparel item.

[1273] When User B receives the sportswear and heads to the park, the device collects GPS location information and sends it to the server. The server analyzes this data to measure the effectiveness of the advertisement in the park. The analysis also includes emotional data recognized by the emotion engine to evaluate how User B's emotions affect the effectiveness of the advertisement. Finally, the server calculates the reward and adds points to User B's account, and the device displays the reward details.

[1274] This allows the Fashion Ads system to integrate users' daily behavior and emotions to efficiently deliver advertisements and provide advertising revenue to users.

[1275] The processing flow will be explained below.

[1276] Program processing steps

[1277] User registration and apparel selection

[1278] Step 1:

[1279] A user downloads the Fashion Ads app and creates a new account.

[1280] Step 2:

[1281] The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to the server.

[1282] Step 3:

[1283] The server stores the received basic information in a database.

[1284] Step 4:

[1285] Users select their fashion style and frequently visited places on the app's settings screen.

[1286] Step 5:

[1287] The terminal transmits the user's selection information to the server.

[1288] Step 6:

[1289] The server creates a list of recommended fashion items based on the user's profile and sends it to the device.

[1290] Step 7:

[1291] The device displays a list of recommended fashion items to the user.

[1292] Ad creative generation

[1293] Step 1:

[1294] The server uses document generation AI to generate customized ad text based on user behavioral and location data, as well as emotional data provided by the emotion engine.

[1295] Step 2:

[1296] The server uses image generation AI to generate the corresponding visual advertisement.

[1297] Step 3:

[1298] The server combines the generated text and images to create customized ad creative.

[1299] Step 4:

[1300] The server sends the ad creative to the device.

[1301] Step 5:

[1302] The device displays a preview of the ad creative to the user and asks for approval.

[1303] Step 6:

[1304] The user reviews the ad creative and approves or requests revisions.

[1305] Step 7:

[1306] The terminal sends the user's feedback to the server.

[1307] Step 8:

[1308] The server modifies the ad creative as needed and sends the final version to the device.

[1309] Emotion recognition by emotion engine

[1310] Step 1:

[1311] While a user is using the app or wearing an apparel item, the emotion engine collects facial expressions, voice and other biometric information to analyze the user's emotions.

[1312] Step 2:

[1313] The device transmits the collected emotional data to a server in real time.

[1314] Step 3:

[1315] The server stores the received emotion data and uses it to generate advertising creatives and measure effectiveness.

[1316] Apparel distribution and advertising

[1317] Step 1:

[1318] The user rents or purchases the selected apparel item.

[1319] Step 2:

[1320] The terminal transmits the user's rental / purchase information to the server.

[1321] Step 3:

[1322] The server processes the shipping of the apparel item and delivers it to the user.

[1323] Step 4:

[1324] The user receives the apparel item and confirms receipt within the app.

[1325] Step 5:

[1326] The terminal sends a receipt confirmation to the server.

[1327] Step 6:

[1328] The server starts an ad display counter and begins tracking the user's location.

[1329] Collecting location information and measuring advertising effectiveness

[1330] Step 1:

[1331] The user goes out wearing the apparel item.

[1332] Step 2:

[1333] The device periodically acquires the user's GPS location information and sends it to the server.

[1334] Step 3:

[1335] The server analyzes the location information sent and measures the time spent in a particular location and the visibility of the advertisement.

[1336] Step 4:

[1337] The server also analyzes emotional data to evaluate the effectiveness of the advertisement.

[1338] Reward calculation and payment

[1339] Step 1:

[1340] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[1341] Step 2:

[1342] The terminal displays a notification of the points awarded and a reward statement to the user.

[1343] Step 3:

[1344] The user can check and spend rewards in the in-app wallet.

[1345] Specific examples

[1346] User B downloads the app and creates an account. The device sends the basic information entered by User B to the server, which stores it in a database. User B then selects a park he or she frequently visits, and the device sends that information to the server. Based on User B's profile, the server recommends sportswear with advertisements printed on it that are suitable for the park.

[1347] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific sports equipment available in the park. User B's recent emotional data is recognized by the emotion engine and reflected in the ad content. The device displays a preview of the ad design to User B, who approves it. When User B purchases sportswear, the device sends the information to the server, which then ships the apparel item.

[1348] When User B receives the sportswear and heads to the park, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of advertising in the park. The analysis also includes emotional data recognized by the emotion engine to evaluate how User B's emotions affect the effectiveness of the advertising. Finally, the server calculates the reward and awards points to User B's account, and the device displays a reward statement. In this way, the fashion ads system integrates the user's daily behavior and emotions to efficiently deliver advertisements and provide advertising revenue to the user.

[1349] Example 2

[1350] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1351] Conventional advertising delivery systems were unable to fully utilize user behavioral and emotional data, making it difficult to maximize the effectiveness of advertising. Furthermore, there was a lack of a way to provide personalized advertisements to individual users, making it difficult to attract their interest. Furthermore, there were also issues with the inability to efficiently measure advertising effectiveness and award user rewards.

[1352] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1353] In this invention, the server includes means for acquiring user location information, means for recommending clothing based on the user's preferences, means for analyzing and collecting emotion data in real time, means for generating advertisements under specific conditions, means for integrating the generated advertisements into clothing, means for distributing the integrated clothing to the user, means for measuring the effectiveness of the advertisements based on the user's behavior, and means for providing rewards to the user based on the measured effectiveness. This enables the provision of efficient personalized advertisements that integrate user behavior data and emotion data, accurate measurement of advertising effectiveness, and appropriate provision of rewards.

[1354] "User location information" refers to information about the user's current location and movement history.

[1355] "Clothing" refers to clothing and other fashion items worn by a user.

[1356] "Emotional data" refers to data relating to the user's emotional state obtained by analyzing the user's facial expressions, voice, and other biometric information.

[1357] "Generating an advertisement" refers to using document generation AI or image generation AI to create the content of an advertisement to be presented to a user under specific conditions.

[1358] "Integrating advertising" refers to incorporating generated advertising into clothing or other media in a particular way.

[1359] "Measuring the effectiveness of advertising" refers to evaluating the impact of advertising based on user behavior and location information.

[1360] "Providing a reward" refers to providing points or other forms of reward to a user based on the effectiveness of an advertisement.

[1361] An embodiment of the present invention is a system that integrates advertisements into clothing worn by users in their daily lives, measures the effectiveness of the advertisements, and further maximizes the effectiveness of the advertisements by recognizing the user's emotions and adjusting the advertisement creatives. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[1362] First, the user downloads and installs the "Fashion Ads" app and registers an account. The device receives the user's basic information (name, age, gender, address, etc.) and sends it to the server. The server stores the received information in a database. Next, the user enters their preferred fashion style and places they usually visit (e.g., shopping centers, parks, etc.) in the app. The device sends this information to the server, which then presents recommended clothing based on the user's profile.

[1363] The server then uses document generation AI and image generation AI to generate customized ad text and visual ads based on the user's behavioral, location, and emotional data. The device then previews the generated ad creative for the user to evaluate and approve. The server then modifies the ad as needed and presents the final version to the user.

[1364] Furthermore, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize emotional data. The device then transmits this emotional data to the server, which then stores and analyzes it along with behavioral and location data.

[1365] When a user rents or purchases the selected clothing, the device sends the information to the server, which then processes the shipping of the clothing. When the user receives the item and confirms receipt within the app, the device sends the information to the server, which then starts the ad display counter.

[1366] When a user puts on clothing and goes out, the device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the collected location information to measure the length of stay and ad visibility. It also analyzes emotional data and ultimately evaluates the effectiveness of the ad.

[1367] The server calculates rewards for users based on advertising effectiveness and adds points to the user's account. The terminal displays a point-award notification and reward details to the user, who can then check and use the points in the in-app wallet.

[1368] For example, when User B downloads the app and enters his / her basic information, his / her device sends that information to the server, which stores it in a database. When User B selects a park as a place he / she often visits and his / her device sends that information to the server, the server suggests to User B sportswear with advertisements suitable for the park. The server uses document generation AI and image generation AI to generate advertisements targeted at specific sports equipment used in the park. For example, the server uses a prompt sentence such as, "Please create an advertisement based on a scenario in which User B is having fun in the park wearing sportswear."

[1369] In this way, the system of the present invention can maximize the effectiveness of advertising and provide rewards to users by integrating user behavioral data and emotional data to provide efficiently personalized advertisements.

[1370] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1371] Step 1: User registration and apparel selection

[1372] User Registration

[1373] A user downloads and installs the "Fashion Ads" app. They enter basic information (name, age, gender, address, etc.) on the account registration screen.

[1374] Input data: Name, age, gender, address

[1375] The device sends this input information to the server, which stores the received information in a database.

[1376] Output: User profile is saved in the database.

[1377] 1.2. Apparel selection

[1378] Within the app, users select their preferred fashion style and places they usually visit (e.g., shopping centers, parks, etc.).

[1379] Input data: fashion style, places visited

[1380] The device sends this information to a server, which then presents clothing recommendations based on the user's profile.

[1381] Output data: Recommended clothing list

[1382] Step 2: Generate ad creative

[1383] 2.1. Ad Generation

[1384] The server uses document generation AI and image generation AI to generate customized ad text and visual ads based on user behavioral data, location data, and emotional data.

[1385] Input data: user behavior data, location data, emotion data

[1386] The server uses document generation AI to generate advertising text and image generation AI to create visual advertisements.

[1387] Output data: Ad text, visual ad

[1388] 2.2. Ad Preview and Approval

[1389] The device displays a preview of the generated ad creative to the user, who can then review the ad and approve or request modifications.

[1390] Input data: Ad creative, user approval or modification request

[1391] The terminal sends the user's approval or request for correction to the server, which makes any necessary corrections and presents the final version to the user.

[1392] Output data: Final ad creative

[1393] Step 3: Collect and analyze emotion data

[1394] 3.1. Emotion Data Collection

[1395] While the user is using the app, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize emotional data.

[1396] Input data: User's facial expressions, voice, biometric information

[1397] The device sends emotion data to the server, which stores it and uses it for analysis.

[1398] Output data: Emotion data

[1399] Step 4: Apparel distribution and advertising

[1400] 4.1. Purchasing / Renting and Distribution of Apparel Items

[1401] The user rents or purchases the selected clothing, and the device sends the information to the server.

[1402] Input data: Purchase / rental information

[1403] The server processes the shipping of the clothing and delivers it to the user, who then receives the item and confirms receipt within the app.

[1404] Output data: Receipt confirmation information

[1405] 4.2. Starting the ad display counter

[1406] After the user receives and confirms the item, the device sends the information to the server.

[1407] Input data: Receipt confirmation information

[1408] The server starts an ad display counter.

[1409] Output data: Start of ad display counter

[1410] Step 5: Collecting location information and measuring advertising effectiveness

[1411] 5.1. Periodic collection of user location information

[1412] When a user goes out, the device periodically acquires the user's GPS location information and sends it to the server.

[1413] Input data: GPS location information

[1414] The server analyzes the location information collected and measures the length of stay and ad visibility.

[1415] Output data: Ad viewability data

[1416] 5.2. Evaluating advertising effectiveness using emotional data

[1417] The server analyzes the location information and emotional data together to evaluate the effectiveness of the advertisement.

[1418] Input data: location information, emotion data

[1419] The server comprehensively evaluates the effectiveness of the advertisement and stores the results.

[1420] Output data: Advertising effectiveness evaluation data

[1421] Step 6: Calculating and paying rewards

[1422] 6.1. Reward Calculation and Points Awarding

[1423] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[1424] Input data: Advertising effectiveness evaluation data

[1425] The device will notify the user of the points awarded and display a rewards statement, which the user can then use to check and redeem the rewards in the in-app wallet.

[1426] Output data: points, reward details

[1427] (Application example 2)

[1428] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1429] While traditional advertising systems can generate ads based on user location and behavioral data, they lack the ability to recognize user emotions in real time and dynamically adjust ad creatives. As a result, ads are often not as effective as they could be, and the user experience is not optimized. Furthermore, users are not rewarded systematically, which means users lack the motivation to actively engage with ads.

[1430] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to the user, means for measuring the effectiveness of advertisements based on user behavior, means for rewarding the user based on the measured effectiveness, means for recognizing the user's emotions using a smart device and dynamically adjusting advertisement creatives, means for analyzing the visibility and effectiveness of advertisements based on the location information and emotion data, and means for rewarding the user based on the analysis results. This enables advertisements to be displayed optimally based on the user's emotion information, maximizing the effectiveness of advertisements, and the user reward system can motivate users to actively engage with advertisements.

[1431] "Means for obtaining user location information" refers to equipment or software that obtains the user's current location using technology such as GPS.

[1432] A "means for recommending fashion items based on user preferences" refers to a system or algorithm that suggests optimal fashion items based on a user's pre-selected preferences and behavioral data.

[1433] "Means for generating advertisements under specific conditions" refers to an algorithm or system that creates advertisements based on conditions such as location information, user behavior data, or emotional data.

[1434] "Means for integrating generated advertisements into fashion items" refers to techniques or methods for incorporating generated advertising content into fashion items worn by users.

[1435] "Means for distributing integrated fashion items to users" refers to a delivery or distribution system for providing users with fashion items with integrated advertisements.

[1436] "Means for measuring the effectiveness of advertising based on user behavior" refers to a system or method that analyzes user behavior patterns and location data to evaluate the visibility and effectiveness of advertising.

[1437] "Means for rewarding users based on measured effectiveness" refers to a system or algorithm that evaluates the effectiveness of an advertisement and rewards users based on the results.

[1438] "Means for recognizing user emotions using smart devices and dynamically adjusting advertising creatives" refers to technologies and methods for analyzing user emotions in real time using smart gadgets and changing and optimizing advertising content based on the results.

[1439] "Means for analyzing the visibility and effectiveness of advertisements based on location information and emotional data" refers to a system or algorithm that uses user location information and emotional data to perform a detailed analysis of the effectiveness of advertisements.

[1440] The "means for providing a reward to a user based on the analysis results" refers to a system or program that provides a reward to a user based on the analysis results of the advertising effectiveness.

[1441] The present invention provides a system for allowing users to experience advertisements integrated into fashion items and maximizing the effectiveness of the advertisements. The specific configuration and operation procedure of the system will be described below.

[1442] (System Configuration)

[1443] The system consists of a server, a terminal (smart device), a user, and an emotion engine. The specific hardware and software used include the following:

[1444] Smart device: smart glasses, smartphone, or head-mounted display

[1445] Emotion engine: Emotion API

[1446] Generative AI models: Document generation AI (GPT-4), Image generation AI (DALL-E)

[1447] Cloud services: AWS, Google Cloud Platform

[1448] (System operation procedure)

[1449] 1. User registration and apparel selection

[1450] A user uses a smart device app to create an account. The device receives basic information (such as name, age, gender, and address) and sends it to the server, which stores it in a database. The user then selects their preferred fashion style and favorite places, and the device sends the information to the server. The server then presents recommended fashion items based on the user's profile.

[1451] 2. Generating ad creatives

[1452] The server uses a generative AI model to create ad text and visual ads based on the user's behavioral, location, and emotional data, using the following prompt:

[1453] {"When a user is enjoying a run in the park, if the emotion engine detects the emotion of enjoyment, it will generate and display an advertisement for a specific sporting goods in real time."}

[1454] The resulting ad creative can be previewed by the user for approval or revision requests.

[1455] 3. Emotion Recognition by Emotion Engine

[1456] While the user is using the app, the smart device's built-in camera and microphone collect the user's facial expressions and voice, which are then analyzed in real time by the emotion engine. The analysis results are sent to the server and used to dynamically adjust the advertising creative.

[1457] 4. Apparel distribution and advertising

[1458] When a user purchases a selected apparel item, the device sends the information to the server, which handles the shipping process. Once the item is received, the integrated advertisement is displayed and the user can use it.

[1459] 5. Location information and advertising effectiveness measurement

[1460] When a user wears the item and goes out, the device periodically acquires GPS location information and sends it to the server. The server analyzes the location information and emotion data to evaluate the effectiveness of the advertisement. The following prompt sentence is used:

[1461] {"When a user visits a shopping mall, if the emotion engine detects that the user is smiling, it will generate and display ads tailored to positive emotions in real time."}

[1462] 6. Calculation and Payment of Rewards

[1463] The server calculates rewards based on the visibility and effectiveness of the advertisement and awards points to the user's account. The terminal displays a notification to the user that points have been awarded.

[1464] By implementing this system, it becomes possible to display advertisements that are optimized based on the user's emotional information, maximizing the effectiveness of advertisements, and the system for providing rewards to users can motivate them to actively participate in advertisements.

[1465] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1466] Step 1:

[1467] A user registers with the app using a smart device (smart glasses or smartphone). The user enters basic information (name, age, gender, address), which the device then sends to the server. The server stores the received information in a database. The input is basic information from the user, and the output is storing the information in the database.

[1468] Step 2:

[1469] Within the app, users select their preferred fashion style and frequently visited locations. The device sends this information to the server, which then presents recommended fashion items based on the user's profile. The input is the user's fashion style and behavioral pattern information, and the output is a list of recommended fashion items.

[1470] Step 3:

[1471] The server uses document generation AI (GPT-4) and image generation AI (DALL-E) to create ad text and visual ads based on user behavioral data, location data, and emotional data. Prompt text is used for this. The generated ad creative is previewed to the user via their device, and they can approve or request revisions. The input is the user's behavioral data and emotional data, and the output is the generated ad creative.

[1472] Step 4:

[1473] While a user is using the app, the smart device's built-in camera and microphone collect the user's facial expressions and voice, which are then analyzed in real time by the emotion engine (Emotion API). The analysis results are sent to the server and used to dynamically adjust advertising creatives. The input is the user's facial and voice data, and the output is analyzed emotional data.

[1474] Step 5:

[1475] When a user purchases or rents a selected apparel item, the terminal sends the information to the server, which then handles the shipping process. When the user receives the item, a receipt confirmation is sent from the terminal to the server. The input is the purchase or rental information, and the output is the receipt confirmation information and the delivery of the apparel item.

[1476] Step 6:

[1477] When a user wears an item and goes out, the device periodically acquires GPS location information and sends it to the server. The server analyzes this information and measures the visibility and dwell time of the advertisement in a specific location. The input is the GPS location information, and the output is the evaluation results of visibility and effectiveness.

[1478] Step 7:

[1479] The server evaluates the effectiveness of the advertisement and calculates the reward based on the emotion data and location data. The calculated reward is awarded as points to the user's account, and the device displays a reward notification. The input is the evaluation result of the advertisement effectiveness, and the output is the points awarded to the user's account and the reward notification.

[1480] This system optimizes ad display based on user emotions and location information, maximizing advertising effectiveness. In addition, users are rewarded systematically, encouraging active user engagement with ads.

[1481] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1482] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1483] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1484] [Fourth embodiment]

[1485] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1486] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1487] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1488] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1489] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1490] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1491] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1492] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1493] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1494] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1495] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1496] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1497] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1498] The system of the present invention integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and provides rewards to users. The main elements of this system are a server, a terminal, and a user.

[1499] Overall system overview

[1500] 1. User registration and apparel selection

[1501] First, a user downloads the Fashion Ads app and creates an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends this information to the server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended apparel items based on the user's profile.

[1502] 2. Generating ad creatives

[1503] The server uses document generation AI to generate customized ad text based on the user's behavioral and location data. It also uses image generation AI to generate corresponding visual ads. These generated texts and images are combined to create customized ad creatives. The device displays a preview of this ad creative to the user and accepts approval or revision requests from the user. If necessary, the server modifies the ad creative and presents the final version to the user.

[1504] 3. Apparel distribution and advertising

[1505] When a user rents or purchases a selected apparel item, the device sends that information to the server. The server processes the shipment of the apparel item and delivers it to the user. When the user receives the apparel item, they confirm receipt within the app. The device then sends the receipt confirmation information to the server, which starts the ad display counter.

[1506] 4. Collecting location information and measuring advertising effectiveness

[1507] The user wears an apparel item and goes out. The device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. This allows the effectiveness of the advertisement to be evaluated.

[1508] 5. Calculation and Payment of Rewards

[1509] The server calculates rewards based on advertising effectiveness and adds points to the user's account. The terminal notifies the user of the points and displays a rewards statement. The user can check and use the rewards in the in-app wallet.

[1510] Specific examples

[1511] User A downloads the app and creates an account. The device sends the basic information entered by User A to the server, which stores it in a database. User A selects a shopping center that he or she frequently visits. Based on User A's profile, the server suggests a T-shirt with an advertisement printed on it that is suitable for that shopping center.

[1512] The server then uses document generation AI and image generation AI to generate text and visual ads targeted to specific stores in the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[1513] When User A receives the T-shirt and goes to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of the advertising at the shopping center. Finally, the server calculates the reward and adds points to User A's account, and the device displays the reward details.

[1514] This enables the Fashion Ads System to efficiently deliver advertisements through users' daily activities and provide advertising revenue to users.

[1515] The processing flow will be explained below.

[1516] Program processing steps

[1517] User registration and apparel selection

[1518] Step 1:

[1519] A user downloads the Fashion Ads app and creates a new account.

[1520] Step 2:

[1521] The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to the server.

[1522] Step 3:

[1523] The server stores the received basic information in a database.

[1524] Step 4:

[1525] Users select their fashion style and frequently visited places on the app's settings screen.

[1526] Step 5:

[1527] The terminal transmits the user's selection information to the server.

[1528] Step 6:

[1529] The server creates a list of recommended apparel items based on the user's profile and sends it to the terminal.

[1530] Step 7:

[1531] The device displays a list of recommended apparel items to the user.

[1532] Ad creative generation

[1533] Step 1:

[1534] The server uses document generation AI to generate customized ad text based on user behavioral and location data.

[1535] Step 2:

[1536] The server uses image generation AI to generate the corresponding visual advertisement.

[1537] Step 3:

[1538] The server combines the generated text and images to create customized ad creative.

[1539] Step 4:

[1540] The server sends the ad creative to the device.

[1541] Step 5:

[1542] The device displays a preview of the ad creative to the user and asks for approval.

[1543] Step 6:

[1544] The user reviews the ad creative and approves or requests revisions.

[1545] Step 7:

[1546] The terminal sends the user's feedback to the server.

[1547] Step 8:

[1548] The server modifies the ad creative as needed and sends the final version to the device.

[1549] Apparel distribution and advertising

[1550] Step 1:

[1551] The user rents or purchases the selected apparel item.

[1552] Step 2:

[1553] The terminal transmits the user's rental / purchase information to the server.

[1554] Step 3:

[1555] The server processes the shipping of the apparel item and delivers it to the user.

[1556] Step 4:

[1557] The user receives the apparel item and confirms receipt within the app.

[1558] Step 5:

[1559] The terminal sends a receipt confirmation to the server.

[1560] Step 6:

[1561] The server starts an ad display counter and begins tracking the user's location.

[1562] Collecting location information and measuring advertising effectiveness

[1563] Step 1:

[1564] The user goes out wearing the apparel item.

[1565] Step 2:

[1566] The device periodically acquires the user's GPS location information and sends it to the server.

[1567] Step 3:

[1568] The server analyzes the location information sent and measures the time spent in a particular location and the visibility of the advertisement.

[1569] Step 4:

[1570] The server evaluates the effectiveness of the advertisement based on the analysis results.

[1571] Reward calculation and payment

[1572] Step 1:

[1573] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[1574] Step 2:

[1575] The terminal displays a notification of the points awarded and a reward statement to the user.

[1576] Step 3:

[1577] The user can check and spend rewards in the in-app wallet.

[1578] Specific examples

[1579] After downloading the app, User A creates an account and enters basic information. The device sends this information to the server, which stores it in a database. User A then selects a shopping center that he or she frequently visits, and the device sends this information to the server. Based on User A's profile, the server recommends a T-shirt with an advertisement printed on it that is appropriate for that shopping center.

[1580] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific stores in the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[1581] When User A receives the T-shirt and heads to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and calculates the effectiveness of the shopping center's advertising. Finally, the server calculates rewards and adds points to User A's account, and the device displays a reward statement. In this way, the Fashion Ads system can efficiently deliver advertisements through the user's daily activities and provide advertising revenue to the user.

[1582] Example 1

[1583] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1584] Conventional advertising systems have difficulty effectively utilizing users' daily behavior and location information to increase the visibility and effectiveness of ads, and have been unable to provide appropriate rewards to users. Furthermore, customizing ads and providing apparel items tailored to users' preferences have been limited. For these reasons, there has been a demand for a system that provides high satisfaction for both advertisers and users.

[1585] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1586] In this invention, the server includes a means for acquiring user location information, a means for recommending clothing items based on the user's preferences, and a means for analyzing the user's behavioral data and location data, which makes it possible to effectively deliver advertisements based on the user's daily behavior and location information, measure advertisement visibility and dwell time, and provide appropriate rewards to the user.

[1587] The "means for acquiring user location information" refers to a device or system that has the function of collecting data indicating the user's current location.

[1588] A "means for recommending clothing items based on user preferences" is a device or system that has the function of suggesting optimal clothing items based on data related to the user's tastes and preferences.

[1589] The "means for analyzing user behavioral data and location data" refers to a device or system that has the function of analyzing a user's behavioral history and location information and extracting useful information based on this.

[1590] An "advertising generating means" is a device or system that has the functionality to create advertising content tailored to a specific purpose or target.

[1591] A "means for integrating generated advertising into apparel" is a device or system that has the functionality to incorporate generated advertising content into apparel, either physically or digitally.

[1592] The "means for distributing clothing items to users" refers to a device or system that has the function of providing selected clothing items to users.

[1593] The "means for measuring the visibility of advertisements and the length of stay" refers to a device or system that has the function of measuring the time a user views an advertisement or the time a user stays in a particular place.

[1594] The "means for rewarding users based on measured visibility and length of stay" refers to a device or system that has the function of providing appropriate rewards based on the user's behavior toward the advertisement and length of stay.

[1595] A "document generation algorithm" is a computational method or program for automatically generating text data.

[1596] An "image generation algorithm" is a computational method or program for automatically creating visual content.

[1597] The "means for previewing and approving advertising creatives" refers to a device or system that has the function of displaying generated advertising content in advance and obtaining approval from a user or administrator.

[1598] The present invention is a system that integrates advertisements into clothing worn by users in their daily lives and provides rewards to users by measuring the effectiveness of the advertisements. The system is composed of a server, terminals, and users.

[1599] System Configuration

[1600] The main components of the system are a means for acquiring user location information, a means for recommending clothing items based on user preferences, a means for analyzing behavioral and location data, a means for generating advertisements, a means for integrating the generated advertisements into clothing items, a means for distributing the clothing items to users, a means for measuring the visibility and dwell time of advertisements, and a means for rewarding users based on the measured visibility and dwell time.

[1601] 1. User registration and apparel selection

[1602] Users download the fashion advertising app, create an account, enter basic information (such as name, age, gender, and address), and select their preferred fashion style and frequently visited places (such as shopping centers) within the app.

[1603] The device sends the entered basic information to the server, which stores the received information in a database and presents recommended apparel items based on the user's profile.

[1604] 2. Generating ad creatives

[1605] The server analyzes the user's behavioral and location data and utilizes document and image generation algorithms to generate customized ad text and visual ads.

[1606] The terminal displays a preview of the generated ad creative to the user and accepts approval or a request for modification. If the user approves, the ad creative is finalized.

[1607] 3. Apparel distribution and advertising

[1608] The user selects the presented apparel item and purchases or rents it.

[1609] The terminal sends the purchase information to the server. The server processes the shipping of the apparel item and delivers it to the user. When the user receives the apparel item, the server confirms receipt and starts the advertisement display counter.

[1610] 4. Collecting location information and measuring advertising effectiveness

[1611] The device periodically acquires the user's GPS location information and sends it to the server, which then analyzes the location information to measure the time spent in a specific location and the visibility of advertisements.

[1612] 5. Calculation and Payment of Rewards

[1613] The server calculates rewards based on the advertising effectiveness and adds points to the user's account. The terminal displays a point-added notification and reward details to the user.

[1614] Specific examples

[1615] User A downloads the app and creates an account. The device sends the basic information entered by User A to the server, which stores it in a database. User A selects a shopping center that he or she frequently visits. Based on User A's profile, the server suggests a T-shirt with an advertisement printed on it that is suitable for that shopping center.

[1616] The server then uses document and image generation algorithms to generate text and visual ads targeted to specific stores within the shopping center. The device displays a preview of the ad design to User A, who approves it. When User A purchases a T-shirt, the device sends the information to the server, which then ships the apparel item.

[1617] When User A receives the T-shirt and goes to the shopping center, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of the advertising at the shopping center. Finally, the server calculates the reward and adds points to User A's account, and the device displays the reward details.

[1618] Prompt Sentence Examples

[1619] "Regarding the user registration process for the Fashion Ads system, please tell me how the user enters basic information and how that information is sent to the server."

[1620] This prompt can be used to input questions into the generative AI model to obtain detailed information about specific parts of the system.

[1621] This enables the fashion advertising system to efficiently deliver advertisements through the user's daily activities and provide advertising revenue to the user.

[1622] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1623] Specific processing flow of the program

[1624] Step 1: User registration and app installation

[1625] Users download the fashion advertising app from the app store and begin creating an account.

[1626] Input: Install the app, enter basic information (name, age, gender, address)

[1627] Specific behavior: A user installs and launches the app, and fills in an in-app form with information such as their name, age, gender, and address.

[1628] Output: Basic information entered

[1629] Step 2: Submit and save basic information

[1630] The terminal transmits the basic information entered by the user to the server.

[1631] Input: Basic information

[1632] Specific operation: The terminal sends the encoded data to the server.

[1633] Output: Basic information sent to the server

[1634] Step 3: Create a profile

[1635] The server stores the received basic information in a database and creates a profile for the user.

[1636] Input: Basic information submitted

[1637] Specific operations: The server stores basic information in a database and creates a user profile.

[1638] Output: User profile in the database

[1639] Step 4: Enter and save your preferences

[1640] Users select their preferred fashion style and usual places within the app.

[1641] Input: Fashion style, range of activities

[1642] Specific behavior: The user selects their preferred style and range of activities from the app's selection menu.

[1643] Output: Selected preference data

[1644] Step 5: Submit your preferences and update your profile

[1645] The terminal sends the preference data to the server, which updates the profile.

[1646] Input: Your preferred data

[1647] Specific operation: The terminal sends the information and the server adds it to the database.

[1648] Output: Updated user profile

[1649] Step 6: Present recommended apparel items

[1650] The server selects recommended apparel items based on the profile and sends them to the device.

[1651] Input: User profile

[1652] Specific operation: The server analyzes the profile, selects the most suitable items, and sends the information to the device.

[1653] Output: A list of recommended apparel items

[1654] Step 7: Generate ad creative

[1655] The server analyzes user behavioral and location data and generates advertisements using document and image generation algorithms.

[1656] Input: behavioral data, location data

[1657] Specific operation: The server creates text ads using a document generation algorithm and visual ads using an image generation algorithm.

[1658] Output: Generated ad creative

[1659] Step 8: Ad preview and approval

[1660] The terminal displays the generated advertising creative to the user and accepts approval or modification requests.

[1661] Input: Ad creative

[1662] What happens: A preview of the ad is displayed on the device, and the user can choose to approve or request revisions.

[1663] Output: Approved ad creative or revision request

[1664] Step 9: Select and purchase apparel items

[1665] Users can select the best apparel items within the app and purchase or rent them.

[1666] Input: List of recommended apparel items

[1667] Specific behavior: The user selects an item from the list and checks out.

[1668] Output: Purchase information

[1669] Step 10: Submit your purchase and process your shipment

[1670] The terminal transmits the user's purchase information to the server, and the server starts the shipping process.

[1671] Input: Purchase information

[1672] Specific operation: The terminal sends purchase information, the server checks inventory and processes the shipment.

[1673] Output: Shipping confirmation information

[1674] Step 11: Confirm receipt and start the ad display counter

[1675] The user will confirm receipt after receiving the item.

[1676] Input: Receipt confirmation operation

[1677] Specific action: The user presses the confirmation button within the app.

[1678] Output: Receipt confirmation data

[1679] Step 12: Obtaining and sending GPS location information

[1680] The terminal periodically acquires the user's GPS location data and transmits it to the server.

[1681] Input: GPS location data

[1682] Specific operation: The device obtains and transmits location information in the background.

[1683] Output: Location data

[1684] Step 13: Analyze location data and measure advertising effectiveness

[1685] The server analyzes the location information and measures the length of stay and the visibility of the advertisement.

[1686] Input: Location data

[1687] Specific operation: The server analyzes the data and measures visibility and duration of visit.

[1688] Output: Advertising effectiveness data

[1689] Step 14: Calculating rewards and awarding points

[1690] The server calculates rewards for the users based on the measured advertising effectiveness and awards points to the users.

[1691] Input: Advertising effectiveness data

[1692] Specific operation: The server calculates rewards based on the effectiveness data and adds points to the user's account.

[1693] Output: Point award notification

[1694] Step 15: View your compensation statement

[1695] The terminal displays the reward details to the user within the app.

[1696] Input: Point award notification

[1697] Specific operation: The device will display a notification on the reward details screen.

[1698] Output: Remuneration details display

[1699] (Application example 1)

[1700] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1701] Conventional advertising systems have had difficulty integrating and measuring the effectiveness of advertisements that utilize fashion items worn by users in their daily lives. Furthermore, it is even more complicated to measure in real time how advertisements are viewed and their effectiveness through users' in-store behavior. This makes it difficult to optimize rewards to users.

[1702] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1703] In this invention, the server includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to the user, means for measuring the effectiveness of the advertisements based on the user's behavior, means for awarding rewards to the user based on the measured effectiveness, means for measuring the user's behavior while wearing the products in a physical store, and means for notifying the user of the status of the award of the reward. This makes it possible to measure the advertising effectiveness in real time as the user wears the fashion items and engages in daily activities, and to award appropriate rewards based on the effectiveness.

[1704] A "user" is an individual who uses the system to wear an advertised fashion item, and receives rewards based on the results of that wear.

[1705] "Location information" is data that indicates the user's current geographical location.

[1706] "Fashion items" are items such as clothing and accessories that users wear in their daily lives.

[1707] "Recommending" refers to the act of suggesting a particular fashion item based on the user's preferences and behavioral data.

[1708] An "advertisement" is a promotional text or image that offers a product or service to a user.

[1709] "Integration" is the process of incorporating advertising into fashion items.

[1710] "Distribution" refers to the act of providing integrated fashion items to users.

[1711] "Behavioral-based" means measuring the effectiveness of advertising based on user location and activity data.

[1712] "Measuring effectiveness" means quantitatively evaluating the extent of influence an advertisement has.

[1713] "Rewards" are benefits such as money or points that users receive based on the effectiveness of the advertisement.

[1714] A "physical store" is a physical store that a user visits.

[1715] "Notification" refers to informing the user of the status of the reward.

[1716] This invention is a system that integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and provides rewards to users. The system includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to users, means for measuring the effectiveness of the advertisements based on user behavior, means for rewarding users based on the measured effectiveness, means for measuring the behavior of users while wearing the products in physical stores, and means for notifying users of the status of reward awards. The details of this system are described below.

[1717] 1. User registration and apparel selection

[1718] First, users download a dedicated fashion ads application onto their smartphone and create an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to a server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended fashion items based on the user's profile.

[1719] 2. Generating ad creatives

[1720] The server uses document generation AI and image generation AI to generate customized ad text and visual ads based on the user's behavioral and location data. This ad creative is appropriate for the user's attributes and activities, and a preview is displayed to the user. Upon receiving approval or correction requests from the user, the server creates a final version of the ad creative and presents it to the user.

[1721] 3. Apparel distribution and advertising

[1722] When a user selects a fashion item for rent or purchase, the device sends that information to the server. The server processes and delivers the apparel item to the user. The user confirms receipt of the item within the app. This confirmation information is sent from the device to the server, which starts the ad display counter.

[1723] 4. Collecting location information and measuring advertising effectiveness

[1724] The user goes out wearing the relevant fashion item. The device periodically acquires the user's GPS location information and sends it to the server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. This data is used to evaluate the effectiveness of the advertisement.

[1725] 5. Calculation and Payment of Rewards

[1726] The server calculates the reward for the user based on the measured advertising effectiveness and adds points to the user's account. The device notifies the user of the points awarded and displays a reward statement. The user can check and use the reward in the in-app wallet.

[1727] As a concrete example, consider the case where a user visits a shopping mall wearing an "advertising T-shirt." The user sends location information to the server through the app, and the server measures the length of stay and visibility. As a result, points are awarded to the user's account.

[1728] An example of a prompt to input to a generative AI model is:

[1729] "Please send the location information of the user wearing the advertising T-shirt to the server every minute while they are in Shinjuku Shopping Mall."

[1730] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1731] Step 1: User registration and apparel selection

[1732] Here, users download a dedicated fashion ads app onto their smartphone and create an account. The device receives basic information entered by the user (name, age, gender, address, etc.) and sends this to a server. The server stores the entered data in a database as the user's profile. Next, the user selects their preferred fashion style and frequently visited places, and the device sends this information to the server. The server then uses this information to recommend fashion items to the user.

[1733] Step 2: Generate ad creative

[1734] The server uses document generation AI to generate customized ad text based on user behavior and location data, and image generation AI to generate corresponding visual ads. The generated ad creative is previewed by the user, who can approve or request revisions. After any necessary revisions are made, the server retains the final ad creative. The input is user behavior data, location data, and the prompt sentence from the generative AI model, and the output is the customized ad creative.

[1735] Step 3: Apparel distribution and advertising

[1736] When a user rents or purchases a selected fashion item, the device sends that information to the server. The server processes the apparel item and delivers it to the user. When the user confirms in the app that they have received the apparel item, the device sends that information to the server. The server receives this information and starts a counter for displaying advertisements. The input is the purchase information for the fashion item, and the output is the start of the counter for displaying advertisements.

[1737] Step 4: Collecting location information and measuring advertising effectiveness

[1738] When a user goes out wearing a fashion item, the device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the received location information and measures the amount of time spent in a specific location and the visibility of advertisements. The input is the user's GPS location information, and the output is the measurement results of the amount of time spent and visibility. Specifically, location information is acquired at regular intervals (for example, every minute).

[1739] Step 5: Calculating and paying rewards

[1740] The server calculates the reward for the user based on the measured advertising effectiveness and grants points to the user's account. The terminal notifies the user of the points awarded and displays a reward statement. The input is the measurement result of the advertising effectiveness, and the output is the points awarded to the user's account and a notification regarding this. In concrete terms, the reward is calculated based on the effectiveness measurement data, and points are added to the user's wallet.

[1741] Examples of applicable prompts include:

[1742] "Please send the location information of the user wearing the advertising T-shirt to the server every minute while in the shopping mall."

[1743] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1744] The system of the present invention integrates advertisements into fashion items worn by users in their daily lives, measures the effectiveness of the advertisements, and further maximizes the effectiveness of the advertisements by recognizing the user's emotions and adjusting the advertisement creatives accordingly. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[1745] Overall system overview

[1746] 1. User registration and apparel selection

[1747] First, a user downloads the Fashion Ads app and creates an account. The device receives basic information entered by the user (such as name, age, gender, and address) and sends this information to the server. The server stores the received information in a database. Next, the user selects their preferred fashion style and frequently visited locations (e.g., shopping centers) on the app. The device sends this information to the server, which then presents recommended apparel items based on the user's profile.

[1748] 2. Generating ad creatives

[1749] The server uses document generation AI to generate customized ad text based on the user's behavioral and location data, as well as emotional data from the emotion engine. It also uses image generation AI to generate corresponding visual ads. These generated texts and images are combined to create customized ad creatives. The device displays a preview of this ad creative to the user and accepts approval or revision requests from the user. If necessary, the server modifies the ad creative and presents the final version to the user.

[1750] 3. Emotion Recognition by Emotion Engine

[1751] While a user is using the app or wearing an apparel item, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize their emotions. This emotion data is then sent to a server along with the user's behavioral and location data.

[1752] 4. Apparel distribution and advertising

[1753] When a user rents or purchases a selected apparel item, the device sends that information to the server. The server processes the shipment of the apparel item and delivers it to the user. When the user receives the apparel item, they confirm receipt within the app. The device then sends the receipt confirmation information to the server, which starts the ad display counter.

[1754] 5. Collecting location information and measuring advertising effectiveness

[1755] The user goes out wearing the apparel item. The device periodically acquires the user's GPS location information and sends it to the server. The server analyzes the location information and measures the time spent in a specific location and the visibility of the advertisement. Emotional data is also analyzed to evaluate the effectiveness of the advertisement.

[1756] 6. Calculation and Payment of Rewards

[1757] The server calculates rewards based on advertising effectiveness and adds points to the user's account. The terminal notifies the user of the points and displays a rewards statement. The user can check and use the rewards in the in-app wallet.

[1758] Specific examples

[1759] User B downloads the app and creates an account. The device sends the basic information entered by User B to the server, which stores it in a database. User B then selects a park he or she frequently visits, and the device sends that information to the server. Based on User B's profile, the server recommends sportswear with advertisements printed on it that are suitable for the park.

[1760] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific sports equipment available at the park. User B's recent emotional data (e.g., enjoyment or excitement) is recognized by the emotion engine and reflected in the ad content. The device then displays a preview of the ad design to User B, who approves it. When User B purchases sportswear, the device sends the information to the server, which then ships the apparel item.

[1761] When User B receives the sportswear and heads to the park, the device collects GPS location information and sends it to the server. The server analyzes this data to measure the effectiveness of the advertisement in the park. The analysis also includes emotional data recognized by the emotion engine to evaluate how User B's emotions affect the effectiveness of the advertisement. Finally, the server calculates the reward and adds points to User B's account, and the device displays the reward details.

[1762] This allows the Fashion Ads system to integrate users' daily behavior and emotions to efficiently deliver advertisements and provide advertising revenue to users.

[1763] The processing flow will be explained below.

[1764] Program processing steps

[1765] User registration and apparel selection

[1766] Step 1:

[1767] A user downloads the Fashion Ads app and creates a new account.

[1768] Step 2:

[1769] The device receives basic information entered by the user (such as name, age, gender, and address) and sends it to the server.

[1770] Step 3:

[1771] The server stores the received basic information in a database.

[1772] Step 4:

[1773] Users select their fashion style and frequently visited places on the app's settings screen.

[1774] Step 5:

[1775] The terminal transmits the user's selection information to the server.

[1776] Step 6:

[1777] The server creates a list of recommended fashion items based on the user's profile and sends it to the device.

[1778] Step 7:

[1779] The device displays a list of recommended fashion items to the user.

[1780] Ad creative generation

[1781] Step 1:

[1782] The server uses document generation AI to generate customized ad text based on user behavioral and location data, as well as emotional data provided by the emotion engine.

[1783] Step 2:

[1784] The server uses image generation AI to generate the corresponding visual advertisement.

[1785] Step 3:

[1786] The server combines the generated text and images to create customized ad creative.

[1787] Step 4:

[1788] The server sends the ad creative to the device.

[1789] Step 5:

[1790] The device displays a preview of the ad creative to the user and asks for approval.

[1791] Step 6:

[1792] The user reviews the ad creative and approves or requests revisions.

[1793] Step 7:

[1794] The terminal sends the user's feedback to the server.

[1795] Step 8:

[1796] The server modifies the ad creative as needed and sends the final version to the device.

[1797] Emotion recognition by emotion engine

[1798] Step 1:

[1799] While a user is using the app or wearing an apparel item, the emotion engine collects facial expressions, voice and other biometric information to analyze the user's emotions.

[1800] Step 2:

[1801] The device transmits the collected emotional data to a server in real time.

[1802] Step 3:

[1803] The server stores the received emotion data and uses it to generate advertising creatives and measure effectiveness.

[1804] Apparel distribution and advertising

[1805] Step 1:

[1806] The user rents or purchases the selected apparel item.

[1807] Step 2:

[1808] The terminal transmits the user's rental / purchase information to the server.

[1809] Step 3:

[1810] The server processes the shipping of the apparel item and delivers it to the user.

[1811] Step 4:

[1812] The user receives the apparel item and confirms receipt within the app.

[1813] Step 5:

[1814] The terminal sends a receipt confirmation to the server.

[1815] Step 6:

[1816] The server starts an ad display counter and begins tracking the user's location.

[1817] Collecting location information and measuring advertising effectiveness

[1818] Step 1:

[1819] The user goes out wearing the apparel item.

[1820] Step 2:

[1821] The device periodically acquires the user's GPS location information and sends it to the server.

[1822] Step 3:

[1823] The server analyzes the location information sent and measures the time spent in a particular location and the visibility of the advertisement.

[1824] Step 4:

[1825] The server also analyzes emotional data to evaluate the effectiveness of the advertisement.

[1826] Reward calculation and payment

[1827] Step 1:

[1828] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[1829] Step 2:

[1830] The terminal displays a notification of the points awarded and a reward statement to the user.

[1831] Step 3:

[1832] The user can check and spend rewards in the in-app wallet.

[1833] Specific examples

[1834] User B downloads the app and creates an account. The device sends the basic information entered by User B to the server, which stores it in a database. User B then selects a park he or she frequently visits, and the device sends that information to the server. Based on User B's profile, the server recommends sportswear with advertisements printed on it that are suitable for the park.

[1835] The server then uses document generation AI and image generation AI to generate text and visual ads targeted at specific sports equipment available in the park. User B's recent emotional data is recognized by the emotion engine and reflected in the ad content. The device displays a preview of the ad design to User B, who approves it. When User B purchases sportswear, the device sends the information to the server, which then ships the apparel item.

[1836] When User B receives the sportswear and heads to the park, the device collects GPS location information and sends it to the server. The server analyzes this data and measures the effectiveness of advertising in the park. The analysis also includes emotional data recognized by the emotion engine to evaluate how User B's emotions affect the effectiveness of the advertising. Finally, the server calculates the reward and awards points to User B's account, and the device displays a reward statement. In this way, the fashion ads system integrates the user's daily behavior and emotions to efficiently deliver advertisements and provide advertising revenue to the user.

[1837] Example 2

[1838] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1839] Conventional advertising delivery systems were unable to fully utilize user behavioral and emotional data, making it difficult to maximize the effectiveness of advertising. Furthermore, there was a lack of a way to provide personalized advertisements to individual users, making it difficult to attract their interest. Furthermore, there were also issues with the inability to efficiently measure advertising effectiveness and award user rewards.

[1840] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1841] In this invention, the server includes means for acquiring user location information, means for recommending clothing based on the user's preferences, means for analyzing and collecting emotion data in real time, means for generating advertisements under specific conditions, means for integrating the generated advertisements into clothing, means for distributing the integrated clothing to the user, means for measuring the effectiveness of the advertisements based on the user's behavior, and means for providing rewards to the user based on the measured effectiveness. This enables the provision of efficient personalized advertisements that integrate user behavior data and emotion data, accurate measurement of advertising effectiveness, and appropriate provision of rewards.

[1842] "User location information" refers to information about the user's current location and movement history.

[1843] "Clothing" refers to clothing and other fashion items worn by a user.

[1844] "Emotional data" refers to data relating to the user's emotional state obtained by analyzing the user's facial expressions, voice, and other biometric information.

[1845] "Generating an advertisement" refers to using document generation AI or image generation AI to create the content of an advertisement to be presented to a user under specific conditions.

[1846] "Integrating advertising" refers to incorporating generated advertising into clothing or other media in a particular way.

[1847] "Measuring the effectiveness of advertising" refers to evaluating the impact of advertising based on user behavior and location information.

[1848] "Providing a reward" refers to providing points or other forms of reward to a user based on the effectiveness of an advertisement.

[1849] An embodiment of the present invention is a system that integrates advertisements into clothing worn by users in their daily lives, measures the effectiveness of the advertisements, and further maximizes the effectiveness of the advertisements by recognizing the user's emotions and adjusting the advertisement creatives. The main elements of this system are a server, a terminal, a user, and an emotion engine.

[1850] First, the user downloads and installs the "Fashion Ads" app and registers an account. The device receives the user's basic information (name, age, gender, address, etc.) and sends it to the server. The server stores the received information in a database. Next, the user enters their preferred fashion style and places they usually visit (e.g., shopping centers, parks, etc.) in the app. The device sends this information to the server, which then presents recommended clothing based on the user's profile.

[1851] The server then uses document generation AI and image generation AI to generate customized ad text and visual ads based on the user's behavioral, location, and emotional data. The device then previews the generated ad creative for the user to evaluate and approve. The server then modifies the ad as needed and presents the final version to the user.

[1852] Furthermore, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize emotional data. The device then transmits this emotional data to the server, which then stores and analyzes it along with behavioral and location data.

[1853] When a user rents or purchases the selected clothing, the device sends the information to the server, which then processes the shipping of the clothing. When the user receives the item and confirms receipt within the app, the device sends the information to the server, which then starts the ad display counter.

[1854] When a user puts on clothing and goes out, the device periodically acquires the user's GPS location information and sends it to a server. The server analyzes the collected location information to measure the length of stay and ad visibility. It also analyzes emotional data and ultimately evaluates the effectiveness of the ad.

[1855] The server calculates rewards for users based on advertising effectiveness and adds points to the user's account. The terminal displays a point-award notification and reward details to the user, who can then check and use the points in the in-app wallet.

[1856] For example, when User B downloads the app and enters his / her basic information, his / her device sends that information to the server, which stores it in a database. When User B selects a park as a place he / she often visits and his / her device sends that information to the server, the server suggests to User B sportswear with advertisements suitable for the park. The server uses document generation AI and image generation AI to generate advertisements targeted at specific sports equipment used in the park. For example, the server uses a prompt sentence such as, "Please create an advertisement based on a scenario in which User B is having fun in the park wearing sportswear."

[1857] In this way, the system of the present invention can maximize the effectiveness of advertising and provide rewards to users by integrating user behavioral data and emotional data to provide efficiently personalized advertisements.

[1858] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1859] Step 1: User registration and apparel selection

[1860] User Registration

[1861] A user downloads and installs the "Fashion Ads" app. They enter basic information (name, age, gender, address, etc.) on the account registration screen.

[1862] Input data: Name, age, gender, address

[1863] The device sends this input information to the server, which stores the received information in a database.

[1864] Output: User profile is saved in the database.

[1865] 1.2. Apparel selection

[1866] Within the app, users select their preferred fashion style and places they usually visit (e.g., shopping centers, parks, etc.).

[1867] Input data: fashion style, places visited

[1868] The device sends this information to a server, which then presents clothing recommendations based on the user's profile.

[1869] Output data: Recommended clothing list

[1870] Step 2: Generate ad creative

[1871] 2.1. Ad Generation

[1872] The server uses document generation AI and image generation AI to generate customized ad text and visual ads based on user behavioral data, location data, and emotional data.

[1873] Input data: user behavior data, location data, emotion data

[1874] The server uses document generation AI to generate advertising text and image generation AI to create visual advertisements.

[1875] Output data: Ad text, visual ad

[1876] 2.2. Ad Preview and Approval

[1877] The device displays a preview of the generated ad creative to the user, who can then review the ad and approve or request modifications.

[1878] Input data: Ad creative, user approval or modification request

[1879] The terminal sends the user's approval or request for correction to the server, which makes any necessary corrections and presents the final version to the user.

[1880] Output data: Final ad creative

[1881] Step 3: Collect and analyze emotion data

[1882] 3.1. Emotion Data Collection

[1883] While the user is using the app, the emotion engine analyzes the user's facial expressions, voice, and other biometric information in real time to recognize emotional data.

[1884] Input data: User's facial expressions, voice, biometric information

[1885] The device sends emotion data to the server, which stores it and uses it for analysis.

[1886] Output data: Emotion data

[1887] Step 4: Apparel distribution and advertising

[1888] 4.1. Purchasing / Renting and Distribution of Apparel Items

[1889] The user rents or purchases the selected clothing, and the device sends the information to the server.

[1890] Input data: Purchase / rental information

[1891] The server processes the shipping of the clothing and delivers it to the user, who then receives the item and confirms receipt within the app.

[1892] Output data: Receipt confirmation information

[1893] 4.2. Starting the ad display counter

[1894] After the user receives and confirms the item, the device sends the information to the server.

[1895] Input data: Receipt confirmation information

[1896] The server starts an ad display counter.

[1897] Output data: Start of ad display counter

[1898] Step 5: Collecting location information and measuring advertising effectiveness

[1899] 5.1. Periodic collection of user location information

[1900] When a user goes out, the device periodically acquires the user's GPS location information and sends it to the server.

[1901] Input data: GPS location information

[1902] The server analyzes the location information collected and measures the length of stay and ad visibility.

[1903] Output data: Ad viewability data

[1904] 5.2. Evaluating advertising effectiveness using emotional data

[1905] The server analyzes the location information and emotional data together to evaluate the effectiveness of the advertisement.

[1906] Input data: location information, emotion data

[1907] The server comprehensively evaluates the effectiveness of the advertisement and stores the results.

[1908] Output data: Advertising effectiveness evaluation data

[1909] Step 6: Calculating and paying rewards

[1910] 6.1. Reward Calculation and Points Awarding

[1911] The server calculates rewards based on the advertising effectiveness and gives points to the user's account.

[1912] Input data: Advertising effectiveness evaluation data

[1913] The device will notify the user of the points awarded and display a rewards statement, which the user can then use to check and redeem the rewards in the in-app wallet.

[1914] Output data: points, reward details

[1915] (Application example 2)

[1916] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1917] While traditional advertising systems can generate ads based on user location and behavioral data, they lack the ability to recognize user emotions in real time and dynamically adjust ad creatives. As a result, ads are often not as effective as they could be, and the user experience is not optimized. Furthermore, users are not rewarded systematically, which means users lack the motivation to actively engage with ads.

[1918] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for recommending fashion items based on the user's preferences, means for generating advertisements under specific conditions, means for integrating the generated advertisements into fashion items, means for distributing the integrated fashion items to the user, means for measuring the effectiveness of advertisements based on user behavior, means for rewarding the user based on the measured effectiveness, means for recognizing the user's emotions using a smart device and dynamically adjusting advertisement creatives, means for analyzing the visibility and effectiveness of advertisements based on the location information and emotion data, and means for rewarding the user based on the analysis results. This enables advertisements to be displayed optimally based on the user's emotion information, maximizing the effectiveness of advertisements, and the user reward system can motivate users to actively engage with advertisements.

[1919] "Means for obtaining user location information" refers to equipment or software that obtains the user's current location using technology such as GPS.

[1920] A "means for recommending fashion items based on user preferences" refers to a system or algorithm that suggests optimal fashion items based on a user's pre-selected preferences and behavioral data.

[1921] "Means for generating advertisements under specific conditions" refers to an algorithm or system that creates advertisements based on conditions such as location information, user behavior data, or emotional data.

[1922] "Means for integrating generated advertisements into fashion items" refers to techniques or methods for incorporating generated advertising content into fashion items worn by users.

[1923] "Means for distributing integrated fashion items to users" refers to a delivery or distribution system for providing users with fashion items with integrated advertisements.

[1924] "Means for measuring the effectiveness of advertising based on user behavior" refers to a system or method that analyzes user behavior patterns and location data to evaluate the visibility and effectiveness of advertising.

[1925] "Means for rewarding users based on measured effectiveness" refers to a system or algorithm that evaluates the effectiveness of an advertisement and rewards users based on the results.

[1926] "Means for recognizing user emotions using smart devices and dynamically adjusting advertising creatives" refers to technologies and methods for analyzing user emotions in real time using smart gadgets and changing and optimizing advertising content based on the results.

[1927] "Means for analyzing the visibility and effectiveness of advertisements based on location information and emotional data" refers to a system or algorithm that uses user location information and emotional data to perform a detailed analysis of the effectiveness of advertisements.

[1928] The "means for providing a reward to a user based on the analysis results" refers to a system or program that provides a reward to a user based on the analysis results of the advertising effectiveness.

[1929] The present invention provides a system for allowing users to experience advertisements integrated into fashion items and maximizing the effectiveness of the advertisements. The specific configuration and operation procedure of the system will be described below.

[1930] (System Configuration)

[1931] The system consists of a server, a terminal (smart device), a user, and an emotion engine. The specific hardware and software used include the following:

[1932] Smart device: smart glasses, smartphone, or head-mounted display

[1933] Emotion engine: Emotion API

[1934] Generative AI models: Document generation AI (GPT-4), Image generation AI (DALL-E)

[1935] Cloud services: AWS, Google Cloud Platform

[1936] (System operation procedure)

[1937] 1. User registration and apparel selection

[1938] A user uses a smart device app to create an account. The device receives basic information (such as name, age, gender, and address) and sends it to the server, which stores it in a database. The user then selects their preferred fashion style and favorite places, and the device sends the information to the server. The server then presents recommended fashion items based on the user's profile.

[1939] 2. Generating ad creatives

[1940] The server uses a generative AI model to create ad text and visual ads based on the user's behavioral, location, and emotional data, using the following prompt:

[1941] {"When a user is enjoying a run in the park, if the emotion engine detects the emotion of enjoyment, it will generate and display an advertisement for a specific sporting goods in real time."}

[1942] The resulting ad creative can be previewed by the user for approval or revision requests.

[1943] 3. Emotion Recognition by Emotion Engine

[1944] While the user is using the app, the smart device's built-in camera and microphone collect the user's facial expressions and voice, which are then analyzed in real time by the emotion engine. The analysis results are sent to the server and used to dynamically adjust the advertising creative.

[1945] 4. Apparel distribution and advertising

[1946] When a user purchases a selected apparel item, the device sends the information to the server, which handles the shipping process. Once the item is received, the integrated advertisement is displayed and the user can use it.

[1947] 5. Location information and advertising effectiveness measurement

[1948] When a user wears the item and goes out, the device periodically acquires GPS location information and sends it to the server. The server analyzes the location information and emotion data to evaluate the effectiveness of the advertisement. The following prompt sentence is used:

[1949] {"When a user visits a shopping mall, if the emotion engine detects that the user is smiling, it will generate and display ads tailored to positive emotions in real time."}

[1950] 6. Calculation and Payment of Rewards

[1951] The server calculates rewards based on the visibility and effectiveness of the advertisement and awards points to the user's account. The terminal displays a notification to the user that points have been awarded.

[1952] By implementing this system, it becomes possible to display advertisements that are optimized based on the user's emotional information, maximizing the effectiveness of advertisements, and the system for providing rewards to users can motivate them to actively participate in advertisements.

[1953] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1954] Step 1:

[1955] A user registers with the app using a smart device (smart glasses or smartphone). The user enters basic information (name, age, gender, address), which the device then sends to the server. The server stores the received information in a database. The input is basic information from the user, and the output is storing the information in the database.

[1956] Step 2:

[1957] Within the app, users select their preferred fashion style and frequently visited locations. The device sends this information to the server, which then presents recommended fashion items based on the user's profile. The input is the user's fashion style and behavioral pattern information, and the output is a list of recommended fashion items.

[1958] Step 3:

[1959] The server uses document generation AI (GPT-4) and image generation AI (DALL-E) to create ad text and visual ads based on user behavioral data, location data, and emotional data. Prompt text is used for this. The generated ad creative is previewed to the user via their device, and they can approve or request revisions. The input is the user's behavioral data and emotional data, and the output is the generated ad creative.

[1960] Step 4:

[1961] While a user is using the app, the smart device's built-in camera and microphone collect the user's facial expressions and voice, which are then analyzed in real time by the emotion engine (Emotion API). The analysis results are sent to the server and used to dynamically adjust advertising creatives. The input is the user's facial and voice data, and the output is analyzed emotional data.

[1962] Step 5:

[1963] When a user purchases or rents a selected apparel item, the terminal sends the information to the server, which then handles the shipping process. When the user receives the item, a receipt confirmation is sent from the terminal to the server. The input is the purchase or rental information, and the output is the receipt confirmation information and the delivery of the apparel item.

[1964] Step 6:

[1965] When a user wears an item and goes out, the device periodically acquires GPS location information and sends it to the server. The server analyzes this information and measures the visibility and dwell time of the advertisement in a specific location. The input is the GPS location information, and the output is the evaluation results of visibility and effectiveness.

[1966] Step 7:

[1967] The server evaluates the effectiveness of the advertisement and calculates the reward based on the emotion data and location data. The calculated reward is awarded as points to the user's account, and the device displays a reward notification. The input is the evaluation result of the advertisement effectiveness, and the output is the points awarded to the user's account and the reward notification.

[1968] This system optimizes ad display based on user emotions and location information, maximizing advertising effectiveness. In addition, users are rewarded systematically, encouraging active user engagement with ads.

[1969] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1970] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1971] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1972] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1973] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1974] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1975] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1976] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emo...

Claims

1. A means for acquiring user location information; means for recommending fashion items based on a user's preferences; means for generating advertisements under certain conditions; means for integrating the generated advertisements into fashion items; means for distributing the integrated fashion items to users; A means for measuring the effectiveness of advertisements based on user behavior; and means for rewarding the user based on the measured effectiveness.

2. The system of claim 1 , wherein the preference-based fashion item recommendation is performed by using user behavioral data and location data.

3. 2. The system according to claim 1, wherein the advertisement is generated by using a document generation AI and an image generation AI.

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