System

Abstract

A system is provided.SOLUTION: A system comprising: means for registering advertising material; means for collecting user data; means for analyzing the user data and generating optimal advertising content; means for delivering the generated advertising content to users; and means for tracking the performance of the advertising and sending reports to businesses.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional advertising systems typically statically change advertising content based on user interests. However, this method makes it difficult to flexibly respond to the diverse interests and emotions of users, resulting in limited advertising effectiveness. Furthermore, since advertising effectiveness is evaluated retroactively and real-time optimization of advertising content is not possible, there is also the problem of inability to deliver timely and effective advertising. Furthermore, for businesses, there is a lack of sufficient feedback needed to improve their advertising strategies, making it difficult to discover new advertising perspectives and viewpoints. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. First, a means for pre-registering advertising materials is provided, thereby registering images, text, and other advertising components prepared by companies into the system. Next, a means for collecting user data is provided, collecting anonymized user data such as web browsing history, search history, and selection history. Based on this data, a means for AI to analyze the user's interests and emotions and generate optimal advertising content in real time is provided. Next, a means for delivering the generated advertising content to the user's device and displaying it on a webpage or within an app is provided. Furthermore, a means for tracking the performance of an advertisement each time it is displayed and providing feedback to the company on the number of clicks and user behavior analysis data can be provided, allowing companies to gain new perspectives and insights for more flexible improvement of their advertising strategies. In this way, a system is provided that generates and displays advertisements optimized for each user in real time, maximizing advertising effectiveness.

[0006] "Advertising materials" are elements such as images, text, and parts that are prepared in advance by a company for use in advertising.

[0007] "User Data" is information that indicates a user's behavior and interests, such as their web browsing history, search history, and selection history.

[0008] "Analysis" is the process of analyzing user interests and emotions based on user data to generate optimal advertising content.

[0009] "Generating" means creating new advertising content by combining advertising materials based on the analysis results.

[0010] "Delivering" means sending the generated advertising content to the user's terminal and displaying it.

[0011] "Performance" refers to the effects, such as the number of clicks and engagement, after an ad is displayed to a user.

[0012] A "report" is a report that provides advertising performance data as feedback to a company.

[0013] "System" means a collection of devices or programs with a set of functions that executes the entire process of registering advertising materials, collecting, analyzing, generating, distributing, tracking performance, and generating reports. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The "evolving advertising system" of this invention is an integrated system consisting of multiple components, and is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user behavior data. Below, we will explain the specific implementation method of this system and the details of each process.

[0036] 1. Registration of advertising materials (server)

[0037] First, a company uploads advertising materials (images, text, parts, etc.) to a management portal on the server. This management portal provides an interface that allows companies to easily add, edit, and delete advertising materials. For example, if a company is creating an advertisement for a new smartphone, it can enter and save the smartphone's image, description, catchphrase, etc. into the portal.

[0038] 2. Collection of user data (terminals, users, servers)

[0039] Your device collects user data while you browse web pages, including your browsing history, search queries, and links you click. If you read a tech article or search for "latest smartphones," that behavioral data is anonymized and sent to a server.

[0040] The server receives this data and stores it in a database. The collected data is used to analyze user interests and behavior patterns.

[0041] 3. Data analysis and advertisement generation (server)

[0042] The server uses an AI model to analyze the collected user data, identifying the user's interests and generating optimal advertising content based on that information.

[0043] Specifically, if the AI ​​model identifies a user's technology interests, it will combine advertising materials (such as new technology specifications or detailed product information) that match those interests to create optimal content.

[0044] 4. Delivery and display of advertisements (servers and terminals)

[0045] The generated ad content is delivered to the user's device. The server determines in real time which ad to display and when based on the user's behavioral data. The generated ad is displayed when the user visits the web page again or when certain conditions are met.

[0046] For example, users who frequently read technical articles will be shown ads that provide more technical details.

[0047] 5. Performance Tracking and Reporting (Server)

[0048] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company in the form of a report.

[0049] Companies can use the reports they receive to review their advertising strategies and identify areas for improvement, allowing them to evolve their ads accordingly based on user interests and behavior, maximizing their effectiveness.

[0050] Specific examples

[0051] As a concrete example, imagine a company launching a new smartphone on the market. The company uploads images and text of the new product to a management portal. When users read tech articles or search for the latest smartphones, that data is anonymized and sent to a server.

[0052] Based on the data analyzed on the server, AI generates advertisements including technical details and delivers them to the user's device. When the user returns to the web, the advertisements highlighting the technical details are displayed. Performance data on the displayed advertisements is then collected and sent to the company as a report.

[0053] In this way, the present invention provides a series of processes for optimizing advertising content for each user and maximizing advertising effectiveness.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] A user views a web page.

[0057] A user opens a specific web page, enters a search query, clicks a link, etc. For example, a user browses a tech article and searches for a new smartphone.

[0058] Step 2:

[0059] The device collects user behavior data.

[0060] The device collects data such as your web browsing history, search queries, and links you click, all of which is collected in an anonymized and privacy-protecting manner.

[0061] Step 3:

[0062] The device sends the collected user data to the server.

[0063] The device then packets the collected user data and transmits it to the server using the appropriate communication protocol, such as the history of browsing technology articles or the search query "latest smartphones."

[0064] Step 4:

[0065] The server receives and stores the user data.

[0066] The server stores the received user data in a database, which stores each user's behavioral history in an anonymized form.

[0067] Step 5:

[0068] The server parses the user data.

[0069] The AI ​​analysis module on the server analyzes the stored user data. This analysis uses machine learning algorithms and natural language processing technology. For example, if a user has a lot of browsing history related to technology, it can determine that they are interested in technology.

[0070] Step 6:

[0071] The server generates the best ad.

[0072] The server generates ads by combining optimal advertising materials based on user data analyzed by AI. For example, for a user determined to be interested in technology, an ad emphasizing the technical details of the latest smartphones will be generated.

[0073] Step 7:

[0074] The server transmits the generated advertisement to the terminal.

[0075] The server then distributes the generated advertisement content to the user's device, appropriately packetizing it using a communication protocol and sending it to the device.

[0076] Step 8:

[0077] The device displays advertisements.

[0078] When the user visits the web page again, the device displays the advertisement received from the server, for example, an advertisement for a smartphone highlighting its technical details on the web page.

[0079] Step 9:

[0080] The device collects advertising performance data.

[0081] The device collects performance data, such as the clicks users make on ads they see and the amount of time they spend on them.

[0082] Step 10:

[0083] The terminal transmits the advertising performance data to the server.

[0084] The device sends the collected performance data to a server, which is also anonymized.

[0085] Step 11:

[0086] The server analyzes the ad performance data.

[0087] The server analyzes the received performance data and evaluates the effectiveness of the advertisement, such as the number of clicks and conversion rate.

[0088] Step 12:

[0089] The server generates the analysis results as a report and sends it to the company.

[0090] The server generates reports based on advertising performance data and provides feedback to businesses, giving them new perspectives to review and optimize their advertising strategies.

[0091] As described above, the specific processing flow from step 1 to step 12 makes it possible to realize a system that generates advertisements optimized for each user and measures and optimizes their effectiveness.

[0092] Example 1

[0093] 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."

[0094] In conventional advertising systems, the collection of user data, ad delivery, and performance tracking are all separated, making it difficult to efficiently optimize and measure advertising effectiveness.In addition, it is difficult to generate advertising content that reflects user interests in real time, making it difficult to maximize advertising effectiveness.

[0095] 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.

[0096] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for anonymizing the user data and transmitting it to the server, means for analyzing the user data collected by the server using an AI model and generating optimal advertising content, means for delivering the generated advertising content to the user's terminal, means for tracking performance data when the advertisement is displayed and storing it in a database, and means for analyzing the collected performance data and transmitting reports to the company. This makes it possible to centrally optimize advertising and measure its effectiveness, and to provide advertising content that evolves in real time based on user behavior data.

[0097] "Advertising materials" are data such as images, text, and parts that companies register in order to create advertisements.

[0098] "User data" is information collected when a user browses a web page, such as browsing history, search queries, and links clicked.

[0099] "Anonymization" is the process of removing personally identifiable information from user data, rendering it anonymous.

[0100] "Server" means the central device of the advertising system, which collects and analyzes user data, generates and delivers advertisements, tracks performance data, and sends reports.

[0101] An "AI model" is a machine learning algorithm used to analyze collected user data, identify user interests, and generate optimal advertising content.

[0102] "Performance data" refers to data that indicates the effectiveness of an advertisement, such as the number of clicks, duration of visit, and engagement rate.

[0103] A "report" is a document that summarizes the results of performance data analyzed by the server and provides it to a company.

[0104] "Device" means the device a user uses to view web pages, collect user data, and display advertisements.

[0105] "Advertising content" refers to the optimal advertising content generated by the AI ​​model based on user data.

[0106] "Database" means a storage device for storing collected user and performance data.

[0107] The "evolving advertising system" of this invention is an integrated system consisting of multiple components that allows companies to register advertising materials and generate and distribute optimal advertisements based on user data. This system functions primarily around a server, terminals, and users.

[0108] Registration of advertising materials (server)

[0109] The server provides a management portal that allows companies to register their advertising materials. Through this management portal, companies can upload images, text, and other elements, and add, edit, or delete them as needed. For example, if a company is creating an advertisement for a new smartphone, it can enter and save an image of the smartphone, a description, a tagline, and other information into the portal.

[0110] Collection of user data (terminal, user, server)

[0111] When a user browses a web page, the device collects user data, including browsing history, search queries, and clicked links. The collected data is anonymized and sent to a server. For example, if a user searches for "latest smartphones" and reads a technology article, the behavioral data is anonymized on the device and sent to a server. The server stores this data in a database and uses it to analyze the user's interests and behavioral patterns.

[0112] Data analysis and advertisement generation (server)

[0113] The server analyzes the collected user data using an AI model to identify the user's interests. Specifically, if the AI ​​model identifies a user's interest in technology, it combines advertising materials that match that interest and generates optimal advertising content. For example, if the AI ​​model determines that the user is "highly interested in technology," it generates an advertisement that includes technical details of a new smartphone as the optimal advertisement for that user.

[0114] Delivery and display of advertisements (servers and terminals)

[0115] The generated advertisement content is delivered from the server to the user's device. Based on the user's behavioral data, the server determines in real time which advertisement to display and when. For example, when the user visits a web page again, a smartphone advertisement including technical details is displayed. The device displays the received advertisement, providing the user with the most appropriate advertising content.

[0116] Performance Tracking and Reporting (Server)

[0117] Each time an ad is displayed, its performance data is collected. The server collects and analyzes the number of clicks, duration, engagement rate, etc. These results are provided to companies as a report. Companies can use the reports they receive to review their advertising strategies and identify areas for improvement. This allows ads to evolve in response to user interests and behavior, maximizing their effectiveness.

[0118] Examples and prompts

[0119] As a concrete example, consider a company launching a new smartphone. The company uploads images and text about the new product to a management portal. When users read technical articles or search for "latest smartphone," the data is anonymized and sent to a server. The server analyzes the data using an AI model and generates an advertisement with technical details. The advertisement is delivered to the user's device and displayed when they return to the web. Performance data on the advertisement is collected and analyzed and sent to the company in a report.

[0120] Example prompt sentence:

[0121] "Analyze data from users' searches and articles about the latest smartphones, and generate ad content that includes technical details relevant to their interests."

[0122] Thus, the present invention is a system that provides a series of processes for optimizing advertising content for each user and maximizing advertising effectiveness.

[0123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0124] Program processing flow

[0125] Step 1: Registering advertising materials (server)

[0126] The server provides a management portal for companies to register their advertising materials. Companies access this portal and upload advertising materials such as images, text, and parts.

[0127] Input: Advertising materials provided by the company (images, text, parts)

[0128] Output: Advertising materials stored in a database

[0129] Specific operation: A company logs in to the management portal through a web browser, clicks the "Create new ad" button to upload and save advertising materials, and the server stores the uploaded materials in a database.

[0130] Step 2: Collecting user data (device, user, server)

[0131] As users browse web pages, their devices collect user data, including browsing history, search queries, and links clicked.

[0132] Input: User behavioral data on webpage browsing (browsing history, search queries, clicks, etc.)

[0133] Output: Anonymized user data

[0134] What it does: When a user searches for "latest smartphones" and clicks to read a tech article, the device hashes this data, associates it with an anonymous user ID, and sends it to a server, which stores it in a database.

[0135] Step 3: Data analysis and ad generation (server)

[0136] The server inputs the collected user data into an AI model to identify the user's interests and generate optimal advertising content based on the results.

[0137] Input: Anonymized user data

[0138] Output: Optimal ad content

[0139] How it works: The server inputs data that "the user read a technical article" into the AI ​​model, and the AI ​​model determines that "the user has a high interest in technology." The server then generates advertising content including technical details based on this determination.

[0140] Step 4: Delivery and display of advertisements (server / terminal)

[0141] The server delivers the generated advertisement content to the user's device, and displays the advertisement at the appropriate time when the user visits the web page again.

[0142] Input: Best Ad Content

[0143] Output: Ad displayed on user device

[0144] How it works: The server detects when the user returns and delivers a smartphone ad highlighting technical details at that time. The device then displays the received ad to the user.

[0145] Step 5: Performance Tracking and Reporting (Server)

[0146] The server collects performance data each time an ad is displayed, such as the number of clicks, time spent, and engagement rate, and analyzes this data to provide reports to the company.

[0147] Input: Performance data of displayed ads (number of clicks, time spent, engagement rate, etc.)

[0148] Output: A report containing the analysis results

[0149] How it works: When a user clicks on an ad, their device sends that information to a server. The server then stores this data in a database and analyzes it. The analysis results are compiled into a report and sent to the company.

[0150] In this way, the server, terminal, and user work together to enable the "evolving advertising system" to optimize the content of advertisements and maximize advertising effectiveness.

[0151] (Application example 1)

[0152] 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."

[0153] While conventional advertising systems have provided a means to optimize advertisements based on user behavior data, they have not adequately optimized advertisements for specific environments or situations. In particular, in autonomous vehicles, there is a lack of a mechanism for displaying optimized advertisements in real time using passenger behavior data and geographic information. A system that can maximize the effectiveness of advertisements in such environments is needed.

[0154] 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.

[0155] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for analyzing the user data and generating optimal advertising content, means for delivering the generated advertising content to users, means for tracking the performance of the advertising and sending reports to companies, an information collection device in the vehicle for collecting passenger behavior data, and means for generating and delivering advertisements based on the behavior data and geographic information, thereby making it possible to display optimized advertisements in real time by utilizing passenger behavior data and geographic information in the vehicle.

[0156] The "means for registering advertising materials" is a part of the system that provides an interface for companies to upload advertising materials (images, text, parts, etc.) to a management portal on a server.

[0157] "Means for collecting user data" refers to the part of the system that collects behavioral data (browsing history, search queries, clicked links, etc.) from the user's device while browsing web pages and sends it to the server.

[0158] The "means for analyzing the user data and generating optimal advertising content" refers to part of a system that analyzes collected user data using an AI model and generates optimal advertising content based on the user's interests and concerns.

[0159] The "means for delivering the generated advertisement content to the user" is a part of the system that delivers the generated advertisement content to the user's terminal and displays it at an appropriate time.

[0160] The "means for tracking the performance of the advertisement and sending reports to the company" is part of a system that tracks performance data such as the number of clicks on the advertisement, the length of time spent on the advertisement, and the engagement rate, and sends the analysis results to the company as a report.

[0161] "In-vehicle information collection device for collecting passenger behavior data" refers to a device for collecting passenger behavior data inside an autonomous vehicle, and includes devices such as smartphones and displays.

[0162] The "means for generating and delivering advertisements based on the behavioral data and geographic information" refers to part of a system that generates optimal advertisements based on collected passenger behavioral data and vehicle geographic information, and delivers them in real time to displays inside autonomous vehicles.

[0163] The present invention consists of several important components for implementing an "evolving advertising system" in an autonomous vehicle. Specific implementation methods and details of each process are described below.

[0164] 1. Registration of advertising materials (server)

[0165] The server provides a means for companies to register their advertising materials. Companies access the management portal and upload advertising materials such as images, text, and parts. This management portal provides an interface that makes it easy to add, edit, and delete advertising materials.

[0166] 2. Collection of user data (terminals, users, servers)

[0167] A dedicated app installed on a user's smartphone collects behavioral data while browsing web pages. This data is anonymized and sent to a server via passenger smartphones or information collection devices in autonomous vehicles. This allows companies to obtain information such as browsing history, search queries, and links clicked.

[0168] 3. Data analysis and advertisement generation (server)

[0169] The server analyzes the collected user data and uses an AI model to identify the user's interests and generate optimal ads based on them. For example, if an interest in technology is identified, the server creates optimal content by combining advertising materials that match those interests.

[0170] 4. Delivery and display of advertisements (servers and terminals)

[0171] The generated advertising content is delivered to the user's device, particularly to the information display in the autonomous vehicle. The server determines in real time which advertisement to display and when based on the user's behavioral data. This allows the system to display optimized advertisements in real time by utilizing passenger behavioral data and geographical information.

[0172] 5. Performance Tracking and Reporting (Server)

[0173] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of ad clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company as a report. Based on the report, the company can review its advertising strategy and identify areas for improvement.

[0174] Specific examples

[0175] For example, if a passenger browses a specific shopping site on their smartphone, the application will collect that data. The collected data will be anonymized and analyzed by an advertising server. Advertisements for products and services tailored to the passenger's interests will be displayed in real time on the display inside the self-driving vehicle.

[0176] Prompt Sentence Examples

[0177] "Generate ads that may be of interest to you based on the following data:

[0178] Browsing history: Electronics, latest gadgets

[0179] Search Query: smartphone reviews

[0180] Link clicked: New smartphone feature article

[0181] As a result, the present invention makes it possible to utilize passenger behavior data and geographic information in autonomous vehicles to display optimal advertisements in real time.

[0182] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0183] Step 1:

[0184] The device (user's smartphone) collects behavioral data when the user browses web pages, including browsing history, search queries, clicked links, etc. This behavioral data is collected in real time and temporarily stored on the device.

[0185] Input: User behavior data (browsing history, search queries, clicked links)

[0186] Output: Behavioral data temporarily stored on the device

[0187] Step 2:

[0188] The device anonymizes the collected behavioral data. Specifically, it removes personal identification information such as user ID and location information. This anonymization process protects privacy.

[0189] Input: Collected behavioral data

[0190] Output: Anonymized behavioral data

[0191] Step 3:

[0192] The device sends anonymized behavioral data to a server, where it is stored and used for subsequent analysis.

[0193] Input: Anonymized behavioral data

[0194] Output: Behavioral data stored on the server

[0195] Step 4:

[0196] The server analyzes the stored behavioral data and uses a generative AI model to identify the user's interests. Specifically, it uses the collected data to analyze which areas the user is particularly interested in. Based on this analysis, it generates optimal advertising content.

[0197] Input: Behavioral data stored on the server

[0198] Output: Optimal ad content

[0199] Step 5:

[0200] The server then transmits the generated advertising content to the information display inside the autonomous vehicle, which then displays the advertisement in real time according to specific timing and conditions.

[0201] Input: Optimal ad content

[0202] Output: Advertisement displayed on the screen

[0203] Step 6:

[0204] The server tracks the performance of the ad after it has been displayed, using display sensors and device feedback to collect data such as ad clicks, dwell time, and engagement rate.

[0205] Input: Performance data of ads displayed on the screen

[0206] Output: Collected performance data

[0207] Step 7:

[0208] The server analyzes the collected performance data and sends it to the company as a report, which details the effectiveness of the advertisement and areas for improvement, providing important information for the company to review its advertising strategy.

[0209] Input: Collected performance data

[0210] Output: Report sent to company

[0211] Specific behavior:

[0212] 1. When a user browses a specific shopping site, the device records this activity.

[0213] 2. The device removes the user ID from the recorded data and anonymizes it.

[0214] 3. The anonymized data is sent to a server via Wi-Fi or 4G / 5G networks.

[0215] 4. The server uses a generative AI model to analyze the data and determine that the user is interested in the latest gadgets.

[0216] 5. The server generates the most suitable advertisement (e.g., an advertisement for the latest gadget) and sends it to a display inside the autonomous vehicle.

[0217] 6. If a passenger clicks on an ad, their data is collected again.

[0218] 7. The server sends the collected data in the form of a report to the company to evaluate the effectiveness of the advertisement.

[0219] 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.

[0220] The "evolving advertising system" of this invention is an integrated system consisting of multiple components, and is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user behavior data and emotions. Below, we will explain the specific implementation method of this system and the details of each process.

[0221] 1. Registration of advertising materials (server)

[0222] First, a company uploads advertising materials (images, text, parts, etc.) to a management portal on the server. This management portal provides an interface that allows companies to easily add, edit, and delete advertising materials. For example, if a company is creating an advertisement for a new smartphone, it can enter and save the smartphone's image, description, catchphrase, etc. into the portal.

[0223] 2. Collection of user data (terminals, users, servers)

[0224] Your device collects user data while you browse web pages, including your browsing history, search queries, and links you click. If you read a tech article or search for "latest smartphones," that behavioral data is anonymized and sent to a server.

[0225] The server receives this data and stores it in a database. The collected data is used to analyze user interests and behavior patterns.

[0226] 3. Emotion data collection (emotion engine, device, user)

[0227] The user's device is equipped with a camera device. This camera is used to analyze the user's facial expressions in real time, and an emotion engine is activated to collect emotional data. For example, emotions such as interest, enthusiasm, and dissatisfaction can be recognized from the user's facial expressions while browsing a web page.

[0228] 4. Data analysis and advertisement generation (server)

[0229] The server uses an AI analysis module to analyze the collected user data and emotional data. Based on the analysis results, the AI ​​generates ads by combining optimal advertising materials. For example, if a user shows interest while reading a technology article, an ad highlighting the technical specifications of a new smartphone will be generated.

[0230] 5. Delivery and display of advertisements (servers and terminals)

[0231] The generated ad content is delivered to the user's device. The server determines in real time which ad to display and when based on the user's behavioral and emotional data. The generated ad is displayed when the user visits the web page again or when certain conditions are met.

[0232] For example, if a user frequently reads technology articles and shows an expression of interest, they will be shown a smartphone ad that highlights the technical details.

[0233] 6. Performance Tracking and Reporting (Server)

[0234] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company in the form of a report.

[0235] Companies can use the reports they receive to refine their advertising strategies and identify areas for improvement, allowing their ads to evolve accordingly based on user interests, behaviors, and emotions, maximizing their effectiveness.

[0236] Specific examples

[0237] As a concrete example, consider a company launching a new smartphone on the market. The company uploads images and text of the new product to a management portal. When users read technical articles or perform searches about the latest smartphones, the data is anonymized and sent to a server. In addition, the camera device captures the user's facial expressions as they read the articles, and emotional data is also collected.

[0238] Based on the data analyzed on the server and the emotional data, AI generates advertisements including technical details and delivers them to the user's device. When the user visits the web again, the advertisements emphasizing the technical details are displayed. Performance data on the displayed advertisements is then collected and sent to the company as a report.

[0239] In this way, the present invention provides a series of processes for optimizing advertising content for each user and taking into account their emotional responses, thereby maximizing advertising effectiveness.

[0240] The processing flow will be explained below.

[0241] Step 1:

[0242] A user views a web page.

[0243] A user opens a specific web page, enters a search query, clicks a link, etc. For example, a user browses a tech article and searches for a new smartphone.

[0244] Step 2:

[0245] The device collects user behavior data.

[0246] The device collects data such as your web browsing history, search queries, and links you click, all of which is collected in an anonymized and privacy-protecting manner.

[0247] Step 3:

[0248] The device sends the collected user data to the server.

[0249] The device then packets the collected user data and transmits it to the server using the appropriate communication protocol, such as the history of browsing technology articles or the search query "latest smartphones."

[0250] Step 4:

[0251] The server receives and stores the user data.

[0252] The server stores the received user data in a database, which stores each user's behavioral history in an anonymized form.

[0253] Step 5:

[0254] The device's built-in emotion engine analyzes the user's facial expressions.

[0255] Using the camera built into the user's device, the emotion engine captures and analyzes the user's facial expressions in real time, for example, recognizing whether the user is smiling or looking interested while reading an article.

[0256] Step 6:

[0257] The device transmits the collected emotion data to a server.

[0258] The device anonymizes the collected emotional data and transmits it to a server using an appropriate communication protocol.

[0259] Step 7:

[0260] The server receives and stores the emotion data.

[0261] The server stores the received emotion data in a database, where it is associated with behavioral data and used for analysis.

[0262] Step 8:

[0263] The server analyzes user data and emotional data.

[0264] The AI ​​analysis module on the server analyzes the stored user data and emotional data. The analysis uses machine learning algorithms and natural language processing technology. For example, if a user has a history of browsing technical content and looks interested, it can determine that they are interested in technology.

[0265] Step 9:

[0266] The server generates the best ad.

[0267] The server generates ads by combining optimal advertising materials based on user data and emotional data analyzed by AI, such as a smartphone ad that emphasizes technical details.

[0268] Step 10:

[0269] The server transmits the generated advertisement to the terminal.

[0270] The server then distributes the generated advertisement content to the user's device, appropriately packetizing it using a communication protocol and sending it to the device.

[0271] Step 11:

[0272] The device displays advertisements.

[0273] When the user visits the web page again, the device displays the advertisement received from the server, for example, an advertisement for a smartphone highlighting its technical details on the web page.

[0274] Step 12:

[0275] The device collects advertising performance data.

[0276] The device collects performance data, such as the clicks users make on ads they see and the amount of time they spend on them.

[0277] Step 13:

[0278] The terminal transmits the advertising performance data to the server.

[0279] The device sends the collected performance data to a server, which is also anonymized.

[0280] Step 14:

[0281] The server analyzes the ad performance data.

[0282] The server analyzes the received performance data and evaluates the effectiveness of the advertisement, such as the number of clicks and conversion rate.

[0283] Step 15:

[0284] The server generates the analysis results as a report and sends it to the company.

[0285] The server generates reports based on advertising performance data and provides feedback to businesses, giving them new perspectives to review and optimize their advertising strategies.

[0286] As described above, by following the specific processing flow from step 1 to step 15, it is possible to realize a system that generates advertisements optimized for each user and measures and optimizes their effectiveness.

[0287] Example 2

[0288] 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."

[0289] Conventional ad delivery systems generate and deliver ads based solely on user behavior data, but they are insufficient in adapting to the emotional responses of individual users. This results in ads not being optimized based on user emotions, and the effectiveness of ads is not maximized. Furthermore, the lack of analysis and feedback on advertising effectiveness makes it difficult for companies to quickly revise their advertising strategies.

[0290] 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.

[0291] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for collecting user emotion data using a camera device, means for analyzing the user data and emotion data and generating optimal advertising content using a generative AI model, means for delivering the generated advertising content to user devices, and means for tracking the performance of the advertising and sending reports to companies. This makes it possible to optimize advertising based on user behavioral data and emotion data, and further evolve advertising content in real time, thereby maximizing advertising effectiveness.

[0292] "Advertising materials" are digital content such as images, text, and parts that companies use to create advertisements.

[0293] "User Data" refers to behavioral data such as a user's web page browsing history, search queries, and links clicked.

[0294] A "camera device" is a hardware device used to capture a user's facial expressions.

[0295] "Emotion data" refers to data relating to emotions such as interest, concern, enjoyment, and dissatisfaction recognized from the user's facial expression.

[0296] A "generative AI model" is an artificial intelligence algorithm used to generate optimal advertising content based on collected data.

[0297] "Advertising Content" refers to the combination of text, images, and parts of a specific advertisement delivered to a user.

[0298] "Advertising performance" refers to effectiveness measurement data such as the number of clicks, length of stay, and engagement rate when an ad is displayed.

[0299] A "report" is a document or digital file that is sent to a company and is the result of analyzing advertising performance data.

[0300] This invention is an integrated advertising system consisting of multiple components, which is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user data and emotional data. Below, we will explain the specific implementation method of this system and the details of each process.

[0301] Registration of advertising materials (server)

[0302] The server provides a management portal where companies can upload advertising materials (images, text, parts, etc.). This portal has an interface that allows companies to easily add, edit, and delete advertising materials. When a company creates an advertisement for a new smartphone, it enters and saves an image of the smartphone, a description, a tagline, etc. into the portal. The hardware used is a web server (e.g., Apache, NGINX), and the software used is a CMS (content management system) such as WordPress or Joomla.

[0303] Collection of user data (terminal, user, server)

[0304] The device collects behavioral data (browsing history, search queries, clicked links, etc.) when the user browses web pages. For example, if a user reads a technology article or searches for "latest smartphones," this behavioral data is anonymized and sent to a server. The sent data is stored in the server's database (e.g., MySQL, PostgreSQL) and used to analyze user interests and behavioral patterns. Software used includes Google Analytics and Mixpanel.

[0305] Emotion data collection (emotion engine, device, user)

[0306] A camera installed on the user's device analyzes the user's facial expressions in real time, and an emotion engine is activated to collect emotional data. For example, emotions such as interest, enthusiasm, and dissatisfaction can be recognized from the user's facial expressions while browsing a web page. This is achieved using software such as TensorFlow and OpenCV. The collected emotional data is sent from the device to a server and stored in a database.

[0307] Data analysis and advertisement generation (server)

[0308] The server uses an AI analysis module to analyze the collected user data and sentiment data. Based on the analysis results, the AI ​​generates ads by combining optimal advertising materials. For example, for a user who shows interest while reading a technical article, an ad highlighting the technical specifications of a new smartphone will be generated. The AI ​​analysis module used is a proprietary model using PyTorch and TensorFlow.

[0309] Delivery and display of advertisements (servers and terminals)

[0310] The server delivers the generated advertising content to the user's device. Based on the user's behavioral and emotional data, the server determines in real time which advertisement to display and when. For example, if a user frequently reads technical articles and shows an expression that indicates interest, a smartphone advertisement emphasizing technical details will be displayed. Advertisements are delivered using an AdServer platform (e.g., Google AdServer).

[0311] Performance Tracking and Reporting (Server)

[0312] The server tracks the performance of each ad displayed. The server collects and analyzes data such as the number of ad clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company as a report. Based on the reports, the company can review its advertising strategy and identify areas for improvement. Software such as Tableau and Google Data Studio are used for analysis and report generation.

[0313] Specific examples

[0314] As a specific example, when a company launches a new smartphone, it uploads images and text of the new product to a management portal. When a user reads a technical article or searches for "latest smartphone," the data is anonymized and sent to a server. A camera captures the user's facial expressions as they read the article, and emotional data is also collected. Based on the data analyzed on the server and the emotional data, AI generates an advertisement that includes technical details and delivers it to the user's device. When the user visits the web again, an advertisement emphasizing the technical details is displayed. Performance data on the displayed advertisement is then collected and sent to the company as a report. This allows the content of the advertisement to be optimized for each user, maximizing its effectiveness.

[0315] Prompt Sentence Examples

[0316] Below are some example prompts to input to a generative AI model:

[0317] "Upload new smartphone ad materials to the management portal and generate optimal ads based on user browsing and sentiment data."

[0318] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0319] System program processing flow

[0320] Step 1: Registering advertising materials (server)

[0321] Input: Advertising materials provided by companies (images, text, parts)

[0322] Specific operation: A company accesses the server's management portal and uploads new advertising materials, which inputs the images, text, and parts of the advertisement into the portal and sends them to the server.

[0323] Data processing: The server receives the uploaded advertising material and converts it into the required format.

[0324] Output: Save the converted advertising material in the database.

[0325] Step 2: Collecting user data (device, user, server)

[0326] Input: User's webpage browsing history, search queries, and clicked links

[0327] Specific operations: The device collects behavioral data when the user browses web pages.

[0328] Data processing: The device anonymizes the collected data and sends it to a server using a secure protocol.

[0329] Output: The server stores the received data in a database.

[0330] Step 3: Collecting emotion data (emotion engine, device, user)

[0331] Input: User's facial expression data

[0332] Specific operation: The camera on the user's device captures facial expressions, which are then analyzed in real time by an emotion engine (e.g., TensorFlow).

[0333] Data processing: The analyzed emotion data is sent from the device to the server.

[0334] Output: The server stores the emotion data in a database.

[0335] Step 4: Data analysis and ad generation (server)

[0336] Input: User data and emotion data

[0337] Specific operation: The server's AI analysis module performs analysis based on collected user data and emotional data.

[0338] Data processing: An AI analysis module (e.g., PyTorch) analyzes the data and combines the optimal advertising materials based on the results.

[0339] Output: The generated advertisement content is saved in the database.

[0340] Step 5: Delivery and display of advertisements (server / terminal)

[0341] Input: Generated ad content

[0342] Specific operation: The server delivers advertisements to the user's device at the appropriate time.

[0343] Data processing: Delivering advertisements using an advertising platform (e.g., Google AdServer).

[0344] Output: The user's device displays the delivered ad.

[0345] Step 6: Performance Tracking and Reporting (Server)

[0346] Input: Performance data such as ad clicks, visit duration, and engagement rate

[0347] What it does: The server tracks the performance of the ads in real time.

[0348] Data processing: Analyze performance data and generate reports based on the results.

[0349] Output: Send the generated report to the company.

[0350] (Application example 2)

[0351] 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."

[0352] Conventional advertising systems personalize ads based on user behavior data, but they face the challenge of being unable to take into account user emotions and instantaneous reactions. This often results in insufficient advertising effectiveness. Another issue is that even if advertising performance data is collected, there is a lack of adequate means to properly analyze it and reflect it in advertising strategies.

[0353] 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 registering advertising materials, means for collecting user data and emotion data, means for analyzing the user data and emotion data and generating optimal advertising content, means for evolving the advertising content based on prompt text using a generative AI model, means for delivering the generated advertising content to users, means for collecting emotion data, and means for tracking the performance of the advertising and sending reports to companies. This makes it possible to optimize advertising in real time based on user behavioral data and emotion data, maximizing advertising effectiveness.

[0354] "Advertising materials" are elements such as images, text, video, and audio that make up an advertisement.

[0355] "User Data" refers to your web page browsing history, search queries, links you click, and other online behavior data.

[0356] "Emotional data" refers to data related to emotions such as interest, concern, enjoyment, and dissatisfaction that can be read from the user's facial expressions and voice.

[0357] The "AI analysis module" is an artificial intelligence-based analysis system that analyzes user data and emotional data to generate optimal advertising content.

[0358] A "generative AI model" is an artificial intelligence-based generation system that evolves advertising content based on a given prompt.

[0359] A "prompt" is an instruction given to a generative AI model to evolve advertising content.

[0360] "Performance data" refers to data used to evaluate the effectiveness of advertising, such as the number of clicks, duration, and engagement rate after an advertisement is displayed.

[0361] A "report" is a report that analyzes advertising performance data and summarizes the results.

[0362] "Delivery" means displaying the generated advertising content to the user.

[0363] The "evolving advertising system" of the present invention is an integrated system that includes a management portal for registering advertising materials, an AI analysis module for collecting and analyzing user data and emotional data, a generative AI model, an advertising distribution system, a performance data tracking system, and a report generation system.

[0364] 1. Registration of advertising materials

[0365] Companies use the management portal to register advertising materials. Specifically, this includes images, text, videos, etc. to be used in advertisements. These materials are stored on the server and used in later steps. The management portal is designed so that companies can easily add, edit, and delete advertising materials.

[0366] 2. Collection of User Data

[0367] While a user is browsing a web page, their device collects user data, including browsing history, search queries, clicked links, etc. This data is anonymized and sent to a server.

[0368] 3. Collecting Emotional Data

[0369] The user's device is equipped with a camera device that captures the user's facial expressions. The emotion engine analyzes the facial expressions in real time and collects emotional data such as interest, concern, enjoyment, and dissatisfaction. This data is also anonymized and sent to the server.

[0370] 4. Data analysis and ad generation

[0371] The AI ​​analysis module on the server analyzes user data and emotional data. Based on the analysis results, the generative AI model generates ads by combining optimal advertising materials. This creates personalized ads that match the user's interests and emotions.

[0372] 5. Delivery and display of advertisements

[0373] The generated ad content is delivered to the user's device. The server displays the ad at the optimal time based on the user's behavioral and emotional data, thereby maximizing the effectiveness of the ad.

[0374] 6. Performance Tracking and Reporting

[0375] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks on the ad, the time spent on the ad, and the engagement rate. The results of this analysis are sent to the company as a report, which the company can use to revise its advertising strategy.

[0376] Hardware and software used

[0377] Smartphone: The device on which the application is installed

[0378] Camera device: Captures the user's facial expressions

[0379] Server: Analyzes data, generates and delivers ads

[0380] AI analysis module: Artificial intelligence for analyzing collected data

[0381] Generative AI model: Artificial intelligence for evolving ad content based on prompts

[0382] Database: Stores user data and emotion data

[0383] Specific examples

[0384] For example, if a user is browsing a movie-related webpage and their facial expressions indicate interest, they can be shown a trailer ad for a new movie. Furthermore, the performance data of the ad can be analyzed and feedback on advertising strategies can be provided based on the results.

[0385] Prompt Sentence Examples

[0386] "When a user is searching for movie-related information, generate new movie trailer ads. Capture the user's facial expressions that express interest, and use that emotional data to display the most appropriate ad."

[0387] In this way, the present invention provides a system that uses user behavioral data and emotional data to optimize advertisements in real time and maximize advertising effectiveness.

[0388] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0389] Step 1:

[0390] The device collects user data, including browsing history, search queries, and clicked links. This data is used to understand user behavior patterns. Input data is user data, and output data is user data sent to a server for analysis.

[0391] Step 2:

[0392] The device uses a camera device to collect user emotional data. The collected emotional data is used to analyze emotions such as interest, concern, enjoyment, and dissatisfaction from the user's facial expressions. The input is facial expression data captured in real time, and the output is emotional data analyzed by the emotion engine.

[0393] Step 3:

[0394] The server receives the user data and emotion data collected in step 1 and step 2 and stores them in a database, thereby forming a consistent dataset of user behavior and emotion. The input data are the user data and emotion data, and the output data is the dataset stored in the database.

[0395] Step 4:

[0396] The server's AI analysis module analyzes the user data and emotional data stored in the database. The analysis reveals the user's behavioral patterns and emotional characteristics. The input data is the data stored in the database, and the output data is the analysis results.

[0397] Step 5:

[0398] The server's generative AI model selects the optimal advertising materials based on the analysis results and generates the advertisement. Specifically, it automatically generates relevant advertising content based on prompts that are likely to interest the user. The input data are the analysis results and prompts, and the output data is the generated advertisement.

[0399] Step 6:

[0400] The server delivers the generated advertisement to the user's device. The timing of the advertisement delivery is optimized based on real-time user data and emotion data. The input data is the generated advertisement, and the output data is the advertisement displayed on the device.

[0401] Step 7:

[0402] The device collects performance data as a result of the advertisement being displayed to the user, including the number of clicks on the advertisement, the duration of the visit, the engagement rate, etc. The input data is the user's response to the advertisement, and the output data is the performance data.

[0403] Step 8:

[0404] The server analyzes the performance data collected in step 7 and generates a report for the company. The report is used to evaluate the effectiveness of the advertisement and to suggest improvements to the advertisement strategy. The input data is the performance data and the output data is the report sent to the company.

[0405] Through each step, ads are created that are optimized in real time based on user behavior and emotions, maximizing their effectiveness.

[0406] 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.

[0407] 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.

[0408] 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.

[0409] [Second embodiment]

[0410] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0411] 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.

[0412] 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).

[0413] 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.

[0414] 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.

[0415] 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).

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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."

[0422] The "evolving advertising system" of this invention is an integrated system consisting of multiple components, and is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user behavior data. Below, we will explain the specific implementation method of this system and the details of each process.

[0423] 1. Registration of advertising materials (server)

[0424] First, a company uploads advertising materials (images, text, parts, etc.) to a management portal on the server. This management portal provides an interface that allows companies to easily add, edit, and delete advertising materials. For example, if a company is creating an advertisement for a new smartphone, it can enter and save the smartphone's image, description, catchphrase, etc. into the portal.

[0425] 2. Collection of user data (terminals, users, servers)

[0426] Your device collects user data while you browse web pages, including your browsing history, search queries, and links you click. If you read a tech article or search for "latest smartphones," that behavioral data is anonymized and sent to a server.

[0427] The server receives this data and stores it in a database. The collected data is used to analyze user interests and behavior patterns.

[0428] 3. Data analysis and advertisement generation (server)

[0429] The server uses an AI model to analyze the collected user data, identifying the user's interests and generating optimal advertising content based on that information.

[0430] Specifically, if the AI ​​model identifies a user's technology interests, it will combine advertising materials (such as new technology specifications or detailed product information) that match those interests to create optimal content.

[0431] 4. Delivery and display of advertisements (servers and terminals)

[0432] The generated ad content is delivered to the user's device. The server determines in real time which ad to display and when based on the user's behavioral data. The generated ad is displayed when the user visits the web page again or when certain conditions are met.

[0433] For example, users who frequently read technical articles will be shown ads that provide more technical details.

[0434] 5. Performance Tracking and Reporting (Server)

[0435] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company in the form of a report.

[0436] Companies can use the reports they receive to review their advertising strategies and identify areas for improvement, allowing them to evolve their ads accordingly based on user interests and behavior, maximizing their effectiveness.

[0437] Specific examples

[0438] As a concrete example, imagine a company launching a new smartphone on the market. The company uploads images and text of the new product to a management portal. When users read tech articles or search for the latest smartphones, that data is anonymized and sent to a server.

[0439] Based on the data analyzed on the server, AI generates advertisements including technical details and delivers them to the user's device. When the user returns to the web, the advertisements highlighting the technical details are displayed. Performance data on the displayed advertisements is then collected and sent to the company as a report.

[0440] In this way, the present invention provides a series of processes for optimizing advertising content for each user and maximizing advertising effectiveness.

[0441] The processing flow will be explained below.

[0442] Step 1:

[0443] A user views a web page.

[0444] A user opens a specific web page, enters a search query, clicks a link, etc. For example, a user browses a tech article and searches for a new smartphone.

[0445] Step 2:

[0446] The device collects user behavior data.

[0447] The device collects data such as your web browsing history, search queries, and links you click, all of which is collected in an anonymized and privacy-protecting manner.

[0448] Step 3:

[0449] The device sends the collected user data to the server.

[0450] The device then packets the collected user data and transmits it to the server using the appropriate communication protocol, such as the history of browsing technology articles or the search query "latest smartphones."

[0451] Step 4:

[0452] The server receives and stores the user data.

[0453] The server stores the received user data in a database, which stores each user's behavioral history in an anonymized form.

[0454] Step 5:

[0455] The server parses the user data.

[0456] The AI ​​analysis module on the server analyzes the stored user data. This analysis uses machine learning algorithms and natural language processing technology. For example, if a user has a lot of browsing history related to technology, it can determine that they are interested in technology.

[0457] Step 6:

[0458] The server generates the best ad.

[0459] The server generates ads by combining optimal advertising materials based on user data analyzed by AI. For example, for a user determined to be interested in technology, an ad emphasizing the technical details of the latest smartphones will be generated.

[0460] Step 7:

[0461] The server transmits the generated advertisement to the terminal.

[0462] The server then distributes the generated advertisement content to the user's device, appropriately packetizing it using a communication protocol and sending it to the device.

[0463] Step 8:

[0464] The device displays advertisements.

[0465] When the user visits the web page again, the device displays the advertisement received from the server, for example, an advertisement for a smartphone highlighting its technical details on the web page.

[0466] Step 9:

[0467] The device collects advertising performance data.

[0468] The device collects performance data, such as the clicks users make on ads they see and the amount of time they spend on them.

[0469] Step 10:

[0470] The terminal transmits the advertising performance data to the server.

[0471] The device sends the collected performance data to a server, which is also anonymized.

[0472] Step 11:

[0473] The server analyzes the ad performance data.

[0474] The server analyzes the received performance data and evaluates the effectiveness of the advertisement, such as the number of clicks and conversion rate.

[0475] Step 12:

[0476] The server generates the analysis results as a report and sends it to the company.

[0477] The server generates reports based on advertising performance data and provides feedback to businesses, giving them new perspectives to review and optimize their advertising strategies.

[0478] As described above, the specific processing flow from step 1 to step 12 makes it possible to realize a system that generates advertisements optimized for each user and measures and optimizes their effectiveness.

[0479] Example 1

[0480] 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."

[0481] In conventional advertising systems, the collection of user data, ad delivery, and performance tracking are all separated, making it difficult to efficiently optimize and measure advertising effectiveness.In addition, it is difficult to generate advertising content that reflects user interests in real time, making it difficult to maximize advertising effectiveness.

[0482] 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.

[0483] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for anonymizing the user data and transmitting it to the server, means for analyzing the user data collected by the server using an AI model and generating optimal advertising content, means for delivering the generated advertising content to the user's terminal, means for tracking performance data when the advertisement is displayed and storing it in a database, and means for analyzing the collected performance data and transmitting reports to the company. This makes it possible to centrally optimize advertising and measure its effectiveness, and to provide advertising content that evolves in real time based on user behavior data.

[0484] "Advertising materials" are data such as images, text, and parts that companies register in order to create advertisements.

[0485] "User data" is information collected when a user browses a web page, such as browsing history, search queries, and links clicked.

[0486] "Anonymization" is the process of removing personally identifiable information from user data, rendering it anonymous.

[0487] "Server" means the central device of the advertising system, which collects and analyzes user data, generates and delivers advertisements, tracks performance data, and sends reports.

[0488] An "AI model" is a machine learning algorithm used to analyze collected user data, identify user interests, and generate optimal advertising content.

[0489] "Performance data" refers to data that indicates the effectiveness of an advertisement, such as the number of clicks, duration of visit, and engagement rate.

[0490] A "report" is a document that summarizes the results of performance data analyzed by the server and provides it to a company.

[0491] "Device" means the device a user uses to view web pages, collect user data, and display advertisements.

[0492] "Advertising content" refers to the optimal advertising content generated by the AI ​​model based on user data.

[0493] "Database" means a storage device for storing collected user and performance data.

[0494] The "evolving advertising system" of this invention is an integrated system consisting of multiple components that allows companies to register advertising materials and generate and distribute optimal advertisements based on user data. This system functions primarily around a server, terminals, and users.

[0495] Registration of advertising materials (server)

[0496] The server provides a management portal that allows companies to register their advertising materials. Through this management portal, companies can upload images, text, and other elements, and add, edit, or delete them as needed. For example, if a company is creating an advertisement for a new smartphone, it can enter and save an image of the smartphone, a description, a tagline, and other information into the portal.

[0497] Collection of user data (terminal, user, server)

[0498] When a user browses a web page, the device collects user data, including browsing history, search queries, and clicked links. The collected data is anonymized and sent to a server. For example, if a user searches for "latest smartphones" and reads a technology article, the behavioral data is anonymized on the device and sent to a server. The server stores this data in a database and uses it to analyze the user's interests and behavioral patterns.

[0499] Data analysis and advertisement generation (server)

[0500] The server analyzes the collected user data using an AI model to identify the user's interests. Specifically, if the AI ​​model identifies a user's interest in technology, it combines advertising materials that match that interest and generates optimal advertising content. For example, if the AI ​​model determines that the user is "highly interested in technology," it generates an advertisement that includes technical details of a new smartphone as the optimal advertisement for that user.

[0501] Delivery and display of advertisements (servers and terminals)

[0502] The generated advertisement content is delivered from the server to the user's device. Based on the user's behavioral data, the server determines in real time which advertisement to display and when. For example, when the user visits a web page again, a smartphone advertisement including technical details is displayed. The device displays the received advertisement, providing the user with the most appropriate advertising content.

[0503] Performance Tracking and Reporting (Server)

[0504] Each time an ad is displayed, its performance data is collected. The server collects and analyzes the number of clicks, duration, engagement rate, etc. These results are provided to companies as a report. Companies can use the reports they receive to review their advertising strategies and identify areas for improvement. This allows ads to evolve in response to user interests and behavior, maximizing their effectiveness.

[0505] Examples and prompts

[0506] As a concrete example, consider a company launching a new smartphone. The company uploads images and text about the new product to a management portal. When users read technical articles or search for "latest smartphone," the data is anonymized and sent to a server. The server analyzes the data using an AI model and generates an advertisement with technical details. The advertisement is delivered to the user's device and displayed when they return to the web. Performance data on the advertisement is collected and analyzed and sent to the company in a report.

[0507] Example prompt sentence:

[0508] "Analyze data from users' searches and articles about the latest smartphones, and generate ad content that includes technical details relevant to their interests."

[0509] Thus, the present invention is a system that provides a series of processes for optimizing advertising content for each user and maximizing advertising effectiveness.

[0510] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0511] Program processing flow

[0512] Step 1: Registering advertising materials (server)

[0513] The server provides a management portal for companies to register their advertising materials. Companies access this portal and upload advertising materials such as images, text, and parts.

[0514] Input: Advertising materials provided by the company (images, text, parts)

[0515] Output: Advertising materials stored in a database

[0516] Specific operation: A company logs in to the management portal through a web browser, clicks the "Create new ad" button to upload and save advertising materials, and the server stores the uploaded materials in a database.

[0517] Step 2: Collecting user data (device, user, server)

[0518] As users browse web pages, their devices collect user data, including browsing history, search queries, and links clicked.

[0519] Input: User behavioral data on webpage browsing (browsing history, search queries, clicks, etc.)

[0520] Output: Anonymized user data

[0521] What it does: When a user searches for "latest smartphones" and clicks to read a tech article, the device hashes this data, associates it with an anonymous user ID, and sends it to a server, which stores it in a database.

[0522] Step 3: Data analysis and ad generation (server)

[0523] The server inputs the collected user data into an AI model to identify the user's interests and generate optimal advertising content based on the results.

[0524] Input: Anonymized user data

[0525] Output: Optimal ad content

[0526] How it works: The server inputs data that "the user read a technical article" into the AI ​​model, and the AI ​​model determines that "the user has a high interest in technology." The server then generates advertising content including technical details based on this determination.

[0527] Step 4: Delivery and display of advertisements (server / terminal)

[0528] The server delivers the generated advertisement content to the user's device, and displays the advertisement at the appropriate time when the user visits the web page again.

[0529] Input: Best Ad Content

[0530] Output: Ad displayed on user device

[0531] How it works: The server detects when the user returns and delivers a smartphone ad highlighting technical details at that time. The device then displays the received ad to the user.

[0532] Step 5: Performance Tracking and Reporting (Server)

[0533] The server collects performance data each time an ad is displayed, such as the number of clicks, time spent, and engagement rate, and analyzes this data to provide reports to the company.

[0534] Input: Performance data of displayed ads (number of clicks, time spent, engagement rate, etc.)

[0535] Output: A report containing the analysis results

[0536] How it works: When a user clicks on an ad, their device sends that information to a server. The server then stores this data in a database and analyzes it. The analysis results are compiled into a report and sent to the company.

[0537] In this way, the server, terminal, and user work together to enable the "evolving advertising system" to optimize the content of advertisements and maximize advertising effectiveness.

[0538] (Application example 1)

[0539] 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."

[0540] While conventional advertising systems have provided a means to optimize advertisements based on user behavior data, they have not adequately optimized advertisements for specific environments or situations. In particular, in autonomous vehicles, there is a lack of a mechanism for displaying optimized advertisements in real time using passenger behavior data and geographic information. A system that can maximize the effectiveness of advertisements in such environments is needed.

[0541] 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.

[0542] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for analyzing the user data and generating optimal advertising content, means for delivering the generated advertising content to users, means for tracking the performance of the advertising and sending reports to companies, an information collection device in the vehicle for collecting passenger behavior data, and means for generating and delivering advertisements based on the behavior data and geographic information, thereby making it possible to display optimized advertisements in real time by utilizing passenger behavior data and geographic information in the vehicle.

[0543] The "means for registering advertising materials" is a part of the system that provides an interface for companies to upload advertising materials (images, text, parts, etc.) to a management portal on a server.

[0544] "Means for collecting user data" refers to the part of the system that collects behavioral data (browsing history, search queries, clicked links, etc.) from the user's device while browsing web pages and sends it to the server.

[0545] The "means for analyzing the user data and generating optimal advertising content" refers to part of a system that analyzes collected user data using an AI model and generates optimal advertising content based on the user's interests and concerns.

[0546] The "means for delivering the generated advertisement content to the user" is a part of the system that delivers the generated advertisement content to the user's terminal and displays it at an appropriate time.

[0547] The "means for tracking the performance of the advertisement and sending reports to the company" is part of a system that tracks performance data such as the number of clicks on the advertisement, the length of time spent on the advertisement, and the engagement rate, and sends the analysis results to the company as a report.

[0548] "In-vehicle information collection device for collecting passenger behavior data" refers to a device for collecting passenger behavior data inside an autonomous vehicle, and includes devices such as smartphones and displays.

[0549] The "means for generating and delivering advertisements based on the behavioral data and geographic information" refers to part of a system that generates optimal advertisements based on collected passenger behavioral data and vehicle geographic information, and delivers them in real time to displays inside autonomous vehicles.

[0550] The present invention consists of several important components for implementing an "evolving advertising system" in an autonomous vehicle. Specific implementation methods and details of each process are described below.

[0551] 1. Registration of advertising materials (server)

[0552] The server provides a means for companies to register their advertising materials. Companies access the management portal and upload advertising materials such as images, text, and parts. This management portal provides an interface that makes it easy to add, edit, and delete advertising materials.

[0553] 2. Collection of user data (terminals, users, servers)

[0554] A dedicated app installed on a user's smartphone collects behavioral data while browsing web pages. This data is anonymized and sent to a server via passenger smartphones or information collection devices in autonomous vehicles. This allows companies to obtain information such as browsing history, search queries, and links clicked.

[0555] 3. Data analysis and advertisement generation (server)

[0556] The server analyzes the collected user data and uses an AI model to identify the user's interests and generate optimal ads based on them. For example, if an interest in technology is identified, the server creates optimal content by combining advertising materials that match those interests.

[0557] 4. Delivery and display of advertisements (servers and terminals)

[0558] The generated advertising content is delivered to the user's device, particularly to the information display in the autonomous vehicle. The server determines in real time which advertisement to display and when based on the user's behavioral data. This allows the system to display optimized advertisements in real time by utilizing passenger behavioral data and geographical information.

[0559] 5. Performance Tracking and Reporting (Server)

[0560] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of ad clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company as a report. Based on the report, the company can review its advertising strategy and identify areas for improvement.

[0561] Specific examples

[0562] For example, if a passenger browses a specific shopping site on their smartphone, the application will collect that data. The collected data will be anonymized and analyzed by an advertising server. Advertisements for products and services tailored to the passenger's interests will be displayed in real time on the display inside the self-driving vehicle.

[0563] Prompt Sentence Examples

[0564] "Generate ads that may be of interest to you based on the following data:

[0565] Browsing history: Electronics, latest gadgets

[0566] Search Query: smartphone reviews

[0567] Link clicked: New smartphone feature article

[0568] As a result, the present invention makes it possible to utilize passenger behavior data and geographic information in autonomous vehicles to display optimal advertisements in real time.

[0569] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0570] Step 1:

[0571] The device (user's smartphone) collects behavioral data when the user browses web pages, including browsing history, search queries, clicked links, etc. This behavioral data is collected in real time and temporarily stored on the device.

[0572] Input: User behavior data (browsing history, search queries, clicked links)

[0573] Output: Behavioral data temporarily stored on the device

[0574] Step 2:

[0575] The device anonymizes the collected behavioral data. Specifically, it removes personal identification information such as user ID and location information. This anonymization process protects privacy.

[0576] Input: Collected behavioral data

[0577] Output: Anonymized behavioral data

[0578] Step 3:

[0579] The device sends anonymized behavioral data to a server, where it is stored and used for subsequent analysis.

[0580] Input: Anonymized behavioral data

[0581] Output: Behavioral data stored on the server

[0582] Step 4:

[0583] The server analyzes the stored behavioral data and uses a generative AI model to identify the user's interests. Specifically, it uses the collected data to analyze which areas the user is particularly interested in. Based on this analysis, it generates optimal advertising content.

[0584] Input: Behavioral data stored on the server

[0585] Output: Optimal ad content

[0586] Step 5:

[0587] The server then transmits the generated advertising content to the information display inside the autonomous vehicle, which then displays the advertisement in real time according to specific timing and conditions.

[0588] Input: Optimal ad content

[0589] Output: Advertisement displayed on the screen

[0590] Step 6:

[0591] The server tracks the performance of the ad after it has been displayed, using display sensors and device feedback to collect data such as ad clicks, dwell time, and engagement rate.

[0592] Input: Performance data of ads displayed on the screen

[0593] Output: Collected performance data

[0594] Step 7:

[0595] The server analyzes the collected performance data and sends it to the company as a report, which details the effectiveness of the advertisement and areas for improvement, providing important information for the company to review its advertising strategy.

[0596] Input: Collected performance data

[0597] Output: Report sent to company

[0598] Specific behavior:

[0599] 1. When a user browses a specific shopping site, the device records this activity.

[0600] 2. The device removes the user ID from the recorded data and anonymizes it.

[0601] 3. The anonymized data is sent to a server via Wi-Fi or 4G / 5G networks.

[0602] 4. The server uses a generative AI model to analyze the data and determine that the user is interested in the latest gadgets.

[0603] 5. The server generates the most suitable advertisement (e.g., an advertisement for the latest gadget) and sends it to a display inside the autonomous vehicle.

[0604] 6. If a passenger clicks on an ad, their data is collected again.

[0605] 7. The server sends the collected data in the form of a report to the company to evaluate the effectiveness of the advertisement.

[0606] 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.

[0607] The "evolving advertising system" of this invention is an integrated system consisting of multiple components, and is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user behavior data and emotions. Below, we will explain the specific implementation method of this system and the details of each process.

[0608] 1. Registration of advertising materials (server)

[0609] First, a company uploads advertising materials (images, text, parts, etc.) to a management portal on the server. This management portal provides an interface that allows companies to easily add, edit, and delete advertising materials. For example, if a company is creating an advertisement for a new smartphone, it can enter and save the smartphone's image, description, catchphrase, etc. into the portal.

[0610] 2. Collection of user data (terminals, users, servers)

[0611] Your device collects user data while you browse web pages, including your browsing history, search queries, and links you click. If you read a tech article or search for "latest smartphones," that behavioral data is anonymized and sent to a server.

[0612] The server receives this data and stores it in a database. The collected data is used to analyze user interests and behavior patterns.

[0613] 3. Emotion data collection (emotion engine, device, user)

[0614] The user's device is equipped with a camera device. This camera is used to analyze the user's facial expressions in real time, and an emotion engine is activated to collect emotional data. For example, emotions such as interest, enthusiasm, and dissatisfaction can be recognized from the user's facial expressions while browsing a web page.

[0615] 4. Data analysis and advertisement generation (server)

[0616] The server uses an AI analysis module to analyze the collected user data and emotional data. Based on the analysis results, the AI ​​generates ads by combining optimal advertising materials. For example, if a user shows interest while reading a technology article, an ad highlighting the technical specifications of a new smartphone will be generated.

[0617] 5. Delivery and display of advertisements (servers and terminals)

[0618] The generated ad content is delivered to the user's device. The server determines in real time which ad to display and when based on the user's behavioral and emotional data. The generated ad is displayed when the user visits the web page again or when certain conditions are met.

[0619] For example, if a user frequently reads technology articles and shows an expression of interest, they will be shown a smartphone ad that highlights the technical details.

[0620] 6. Performance Tracking and Reporting (Server)

[0621] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company in the form of a report.

[0622] Companies can use the reports they receive to refine their advertising strategies and identify areas for improvement, allowing their ads to evolve accordingly based on user interests, behaviors, and emotions, maximizing their effectiveness.

[0623] Specific examples

[0624] As a concrete example, consider a company launching a new smartphone on the market. The company uploads images and text of the new product to a management portal. When users read technical articles or perform searches about the latest smartphones, the data is anonymized and sent to a server. In addition, the camera device captures the user's facial expressions as they read the articles, and emotional data is also collected.

[0625] Based on the data analyzed on the server and the emotional data, AI generates advertisements including technical details and delivers them to the user's device. When the user visits the web again, the advertisements emphasizing the technical details are displayed. Performance data on the displayed advertisements is then collected and sent to the company as a report.

[0626] In this way, the present invention provides a series of processes for optimizing advertising content for each user and taking into account their emotional responses, thereby maximizing advertising effectiveness.

[0627] The processing flow will be explained below.

[0628] Step 1:

[0629] A user views a web page.

[0630] A user opens a specific web page, enters a search query, clicks a link, etc. For example, a user browses a tech article and searches for a new smartphone.

[0631] Step 2:

[0632] The device collects user behavior data.

[0633] The device collects data such as your web browsing history, search queries, and links you click, all of which is collected in an anonymized and privacy-protecting manner.

[0634] Step 3:

[0635] The device sends the collected user data to the server.

[0636] The device then packets the collected user data and transmits it to the server using the appropriate communication protocol, such as the history of browsing technology articles or the search query "latest smartphones."

[0637] Step 4:

[0638] The server receives and stores the user data.

[0639] The server stores the received user data in a database, which stores each user's behavioral history in an anonymized form.

[0640] Step 5:

[0641] The device's built-in emotion engine analyzes the user's facial expressions.

[0642] Using the camera built into the user's device, the emotion engine captures and analyzes the user's facial expressions in real time, for example, recognizing whether the user is smiling or looking interested while reading an article.

[0643] Step 6:

[0644] The device transmits the collected emotion data to a server.

[0645] The device anonymizes the collected emotional data and transmits it to a server using an appropriate communication protocol.

[0646] Step 7:

[0647] The server receives and stores the emotion data.

[0648] The server stores the received emotion data in a database, where it is associated with behavioral data and used for analysis.

[0649] Step 8:

[0650] The server analyzes user data and emotional data.

[0651] The AI ​​analysis module on the server analyzes the stored user data and emotional data. The analysis uses machine learning algorithms and natural language processing technology. For example, if a user has a history of browsing technical content and looks interested, it can determine that they are interested in technology.

[0652] Step 9:

[0653] The server generates the best ad.

[0654] The server generates ads by combining optimal advertising materials based on user data and emotional data analyzed by AI, such as a smartphone ad that emphasizes technical details.

[0655] Step 10:

[0656] The server transmits the generated advertisement to the terminal.

[0657] The server then distributes the generated advertisement content to the user's device, appropriately packetizing it using a communication protocol and sending it to the device.

[0658] Step 11:

[0659] The device displays advertisements.

[0660] When the user visits the web page again, the device displays the advertisement received from the server, for example, an advertisement for a smartphone highlighting its technical details on the web page.

[0661] Step 12:

[0662] The device collects advertising performance data.

[0663] The device collects performance data, such as the clicks users make on ads they see and the amount of time they spend on them.

[0664] Step 13:

[0665] The terminal transmits the advertising performance data to the server.

[0666] The device sends the collected performance data to a server, which is also anonymized.

[0667] Step 14:

[0668] The server analyzes the ad performance data.

[0669] The server analyzes the received performance data and evaluates the effectiveness of the advertisement, such as the number of clicks and conversion rate.

[0670] Step 15:

[0671] The server generates the analysis results as a report and sends it to the company.

[0672] The server generates reports based on advertising performance data and provides feedback to businesses, giving them new perspectives to review and optimize their advertising strategies.

[0673] As described above, by following the specific processing flow from step 1 to step 15, it is possible to realize a system that generates advertisements optimized for each user and measures and optimizes their effectiveness.

[0674] Example 2

[0675] 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."

[0676] Conventional ad delivery systems generate and deliver ads based solely on user behavior data, but they are insufficient in adapting to the emotional responses of individual users. This results in ads not being optimized based on user emotions, and the effectiveness of ads is not maximized. Furthermore, the lack of analysis and feedback on advertising effectiveness makes it difficult for companies to quickly revise their advertising strategies.

[0677] 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.

[0678] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for collecting user emotion data using a camera device, means for analyzing the user data and emotion data and generating optimal advertising content using a generative AI model, means for delivering the generated advertising content to user devices, and means for tracking the performance of the advertising and sending reports to companies. This makes it possible to optimize advertising based on user behavioral data and emotion data, and further evolve advertising content in real time, thereby maximizing advertising effectiveness.

[0679] "Advertising materials" are digital content such as images, text, and parts that companies use to create advertisements.

[0680] "User Data" refers to behavioral data such as a user's web page browsing history, search queries, and links clicked.

[0681] A "camera device" is a hardware device used to capture a user's facial expressions.

[0682] "Emotion data" refers to data relating to emotions such as interest, concern, enjoyment, and dissatisfaction recognized from the user's facial expression.

[0683] A "generative AI model" is an artificial intelligence algorithm used to generate optimal advertising content based on collected data.

[0684] "Advertising Content" refers to the combination of text, images, and parts of a specific advertisement delivered to a user.

[0685] "Advertising performance" refers to effectiveness measurement data such as the number of clicks, length of stay, and engagement rate when an ad is displayed.

[0686] A "report" is a document or digital file that is sent to a company and is the result of analyzing advertising performance data.

[0687] This invention is an integrated advertising system consisting of multiple components, which is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user data and emotional data. Below, we will explain the specific implementation method of this system and the details of each process.

[0688] Registration of advertising materials (server)

[0689] The server provides a management portal where companies can upload advertising materials (images, text, parts, etc.). This portal has an interface that allows companies to easily add, edit, and delete advertising materials. When a company creates an advertisement for a new smartphone, it enters and saves an image of the smartphone, a description, a tagline, etc. into the portal. The hardware used is a web server (e.g., Apache, NGINX), and the software used is a CMS (content management system) such as WordPress or Joomla.

[0690] Collection of user data (terminal, user, server)

[0691] The device collects behavioral data (browsing history, search queries, clicked links, etc.) when the user browses web pages. For example, if a user reads a technology article or searches for "latest smartphones," this behavioral data is anonymized and sent to a server. The sent data is stored in the server's database (e.g., MySQL, PostgreSQL) and used to analyze user interests and behavioral patterns. Software used includes Google Analytics and Mixpanel.

[0692] Emotion data collection (emotion engine, device, user)

[0693] A camera installed on the user's device analyzes the user's facial expressions in real time, and an emotion engine is activated to collect emotional data. For example, emotions such as interest, enthusiasm, and dissatisfaction can be recognized from the user's facial expressions while browsing a web page. This is achieved using software such as TensorFlow and OpenCV. The collected emotional data is sent from the device to a server and stored in a database.

[0694] Data analysis and advertisement generation (server)

[0695] The server uses an AI analysis module to analyze the collected user data and sentiment data. Based on the analysis results, the AI ​​generates ads by combining optimal advertising materials. For example, for a user who shows interest while reading a technical article, an ad highlighting the technical specifications of a new smartphone will be generated. The AI ​​analysis module used is a proprietary model using PyTorch and TensorFlow.

[0696] Delivery and display of advertisements (servers and terminals)

[0697] The server delivers the generated advertising content to the user's device. Based on the user's behavioral and emotional data, the server determines in real time which advertisement to display and when. For example, if a user frequently reads technical articles and shows an expression that indicates interest, a smartphone advertisement emphasizing technical details will be displayed. Advertisements are delivered using an AdServer platform (e.g., Google AdServer).

[0698] Performance Tracking and Reporting (Server)

[0699] The server tracks the performance of each ad displayed. The server collects and analyzes data such as the number of ad clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company as a report. Based on the reports, the company can review its advertising strategy and identify areas for improvement. Software such as Tableau and Google Data Studio are used for analysis and report generation.

[0700] Specific examples

[0701] As a specific example, when a company launches a new smartphone, it uploads images and text of the new product to a management portal. When a user reads a technical article or searches for "latest smartphone," the data is anonymized and sent to a server. A camera captures the user's facial expressions as they read the article, and emotional data is also collected. Based on the data analyzed on the server and the emotional data, AI generates an advertisement that includes technical details and delivers it to the user's device. When the user visits the web again, an advertisement emphasizing the technical details is displayed. Performance data on the displayed advertisement is then collected and sent to the company as a report. This allows the content of the advertisement to be optimized for each user, maximizing its effectiveness.

[0702] Prompt Sentence Examples

[0703] Below are some example prompts to input to a generative AI model:

[0704] "Upload new smartphone ad materials to the management portal and generate optimal ads based on user browsing and sentiment data."

[0705] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0706] System program processing flow

[0707] Step 1: Registering advertising materials (server)

[0708] Input: Advertising materials provided by companies (images, text, parts)

[0709] Specific operation: A company accesses the server's management portal and uploads new advertising materials, which inputs the images, text, and parts of the advertisement into the portal and sends them to the server.

[0710] Data processing: The server receives the uploaded advertising material and converts it into the required format.

[0711] Output: Save the converted advertising material in the database.

[0712] Step 2: Collecting user data (device, user, server)

[0713] Input: User's webpage browsing history, search queries, and clicked links

[0714] Specific operations: The device collects behavioral data when the user browses web pages.

[0715] Data processing: The device anonymizes the collected data and sends it to a server using a secure protocol.

[0716] Output: The server stores the received data in a database.

[0717] Step 3: Collecting emotion data (emotion engine, device, user)

[0718] Input: User's facial expression data

[0719] Specific operation: The camera on the user's device captures facial expressions, which are then analyzed in real time by an emotion engine (e.g., TensorFlow).

[0720] Data processing: The analyzed emotion data is sent from the device to the server.

[0721] Output: The server stores the emotion data in a database.

[0722] Step 4: Data analysis and ad generation (server)

[0723] Input: User data and emotion data

[0724] Specific operation: The server's AI analysis module performs analysis based on collected user data and emotional data.

[0725] Data processing: An AI analysis module (e.g., PyTorch) analyzes the data and combines the optimal advertising materials based on the results.

[0726] Output: The generated advertisement content is saved in the database.

[0727] Step 5: Delivery and display of advertisements (server / terminal)

[0728] Input: Generated ad content

[0729] Specific operation: The server delivers advertisements to the user's device at the appropriate time.

[0730] Data processing: Delivering advertisements using an advertising platform (e.g., Google AdServer).

[0731] Output: The user's device displays the delivered ad.

[0732] Step 6: Performance Tracking and Reporting (Server)

[0733] Input: Performance data such as ad clicks, visit duration, and engagement rate

[0734] What it does: The server tracks the performance of the ads in real time.

[0735] Data processing: Analyze performance data and generate reports based on the results.

[0736] Output: Send the generated report to the company.

[0737] (Application example 2)

[0738] 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."

[0739] Conventional advertising systems personalize ads based on user behavior data, but they face the challenge of being unable to take into account user emotions and instantaneous reactions. This often results in insufficient advertising effectiveness. Another issue is that even if advertising performance data is collected, there is a lack of adequate means to properly analyze it and reflect it in advertising strategies.

[0740] 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 registering advertising materials, means for collecting user data and emotion data, means for analyzing the user data and emotion data and generating optimal advertising content, means for evolving the advertising content based on prompt text using a generative AI model, means for delivering the generated advertising content to users, means for collecting emotion data, and means for tracking the performance of the advertising and sending reports to companies. This makes it possible to optimize advertising in real time based on user behavioral data and emotion data, maximizing advertising effectiveness.

[0741] "Advertising materials" are elements such as images, text, video, and audio that make up an advertisement.

[0742] "User Data" refers to your web page browsing history, search queries, links you click, and other online behavior data.

[0743] "Emotional data" refers to data related to emotions such as interest, concern, enjoyment, and dissatisfaction that can be read from the user's facial expressions and voice.

[0744] The "AI analysis module" is an artificial intelligence-based analysis system that analyzes user data and emotional data to generate optimal advertising content.

[0745] A "generative AI model" is an artificial intelligence-based generation system that evolves advertising content based on a given prompt.

[0746] A "prompt" is an instruction given to a generative AI model to evolve advertising content.

[0747] "Performance data" refers to data used to evaluate the effectiveness of advertising, such as the number of clicks, duration, and engagement rate after an advertisement is displayed.

[0748] A "report" is a report that analyzes advertising performance data and summarizes the results.

[0749] "Delivery" means displaying the generated advertising content to the user.

[0750] The "evolving advertising system" of the present invention is an integrated system that includes a management portal for registering advertising materials, an AI analysis module for collecting and analyzing user data and emotional data, a generative AI model, an advertising distribution system, a performance data tracking system, and a report generation system.

[0751] 1. Registration of advertising materials

[0752] Companies use the management portal to register advertising materials. Specifically, this includes images, text, videos, etc. to be used in advertisements. These materials are stored on the server and used in later steps. The management portal is designed so that companies can easily add, edit, and delete advertising materials.

[0753] 2. Collection of User Data

[0754] While a user is browsing a web page, their device collects user data, including browsing history, search queries, clicked links, etc. This data is anonymized and sent to a server.

[0755] 3. Collecting Emotional Data

[0756] The user's device is equipped with a camera device that captures the user's facial expressions. The emotion engine analyzes the facial expressions in real time and collects emotional data such as interest, concern, enjoyment, and dissatisfaction. This data is also anonymized and sent to the server.

[0757] 4. Data analysis and ad generation

[0758] The AI ​​analysis module on the server analyzes user data and emotional data. Based on the analysis results, the generative AI model generates ads by combining optimal advertising materials. This creates personalized ads that match the user's interests and emotions.

[0759] 5. Delivery and display of advertisements

[0760] The generated ad content is delivered to the user's device. The server displays the ad at the optimal time based on the user's behavioral and emotional data, thereby maximizing the effectiveness of the ad.

[0761] 6. Performance Tracking and Reporting

[0762] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks on the ad, the time spent on the ad, and the engagement rate. The results of this analysis are sent to the company as a report, which the company can use to revise its advertising strategy.

[0763] Hardware and software used

[0764] Smartphone: The device on which the application is installed

[0765] Camera device: Captures the user's facial expressions

[0766] Server: Analyzes data, generates and delivers ads

[0767] AI analysis module: Artificial intelligence for analyzing collected data

[0768] Generative AI model: Artificial intelligence for evolving ad content based on prompts

[0769] Database: Stores user data and emotion data

[0770] Specific examples

[0771] For example, if a user is browsing a movie-related webpage and their facial expressions indicate interest, they can be shown a trailer ad for a new movie. Furthermore, the performance data of the ad can be analyzed and feedback on advertising strategies can be provided based on the results.

[0772] Prompt Sentence Examples

[0773] "When a user is searching for movie-related information, generate new movie trailer ads. Capture the user's facial expressions that express interest, and use that emotional data to display the most appropriate ad."

[0774] In this way, the present invention provides a system that uses user behavioral data and emotional data to optimize advertisements in real time and maximize advertising effectiveness.

[0775] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0776] Step 1:

[0777] The device collects user data, including browsing history, search queries, and clicked links. This data is used to understand user behavior patterns. Input data is user data, and output data is user data sent to a server for analysis.

[0778] Step 2:

[0779] The device uses a camera device to collect user emotional data. The collected emotional data is used to analyze emotions such as interest, concern, enjoyment, and dissatisfaction from the user's facial expressions. The input is facial expression data captured in real time, and the output is emotional data analyzed by the emotion engine.

[0780] Step 3:

[0781] The server receives the user data and emotion data collected in step 1 and step 2 and stores them in a database, thereby forming a consistent dataset of user behavior and emotion. The input data are the user data and emotion data, and the output data is the dataset stored in the database.

[0782] Step 4:

[0783] The server's AI analysis module analyzes the user data and emotional data stored in the database. The analysis reveals the user's behavioral patterns and emotional characteristics. The input data is the data stored in the database, and the output data is the analysis results.

[0784] Step 5:

[0785] The server's generative AI model selects the optimal advertising materials based on the analysis results and generates the advertisement. Specifically, it automatically generates relevant advertising content based on prompts that are likely to interest the user. The input data are the analysis results and prompts, and the output data is the generated advertisement.

[0786] Step 6:

[0787] The server delivers the generated advertisement to the user's device. The timing of the advertisement delivery is optimized based on real-time user data and emotion data. The input data is the generated advertisement, and the output data is the advertisement displayed on the device.

[0788] Step 7:

[0789] The device collects performance data as a result of the advertisement being displayed to the user, including the number of clicks on the advertisement, the duration of the visit, the engagement rate, etc. The input data is the user's response to the advertisement, and the output data is the performance data.

[0790] Step 8:

[0791] The server analyzes the performance data collected in step 7 and generates a report for the company. The report is used to evaluate the effectiveness of the advertisement and to suggest improvements to the advertisement strategy. The input data is the performance data and the output data is the report sent to the company.

[0792] Through each step, ads are created that are optimized in real time based on user behavior and emotions, maximizing their effectiveness.

[0793] 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.

[0794] 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.

[0795] 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.

[0796] [Third embodiment]

[0797] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0798] 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.

[0799] 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).

[0800] 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.

[0801] 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.

[0802] 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).

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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."

[0809] The "evolving advertising system" of this invention is an integrated system consisting of multiple components, and is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user behavior data. Below, we will explain the specific implementation method of this system and the details of each process.

[0810] 1. Registration of advertising materials (server)

[0811] First, a company uploads advertising materials (images, text, parts, etc.) to a management portal on the server. This management portal provides an interface that allows companies to easily add, edit, and delete advertising materials. For example, if a company is creating an advertisement for a new smartphone, it can enter and save the smartphone's image, description, catchphrase, etc. into the portal.

[0812] 2. Collection of user data (terminals, users, servers)

[0813] Your device collects user data while you browse web pages, including your browsing history, search queries, and links you click. If you read a tech article or search for "latest smartphones," that behavioral data is anonymized and sent to a server.

[0814] The server receives this data and stores it in a database. The collected data is used to analyze user interests and behavior patterns.

[0815] 3. Data analysis and advertisement generation (server)

[0816] The server uses an AI model to analyze the collected user data, identifying the user's interests and generating optimal advertising content based on that information.

[0817] Specifically, if the AI ​​model identifies a user's technology interests, it will combine advertising materials (such as new technology specifications or detailed product information) that match those interests to create optimal content.

[0818] 4. Delivery and display of advertisements (servers and terminals)

[0819] The generated ad content is delivered to the user's device. The server determines in real time which ad to display and when based on the user's behavioral data. The generated ad is displayed when the user visits the web page again or when certain conditions are met.

[0820] For example, users who frequently read technical articles will be shown ads that provide more technical details.

[0821] 5. Performance Tracking and Reporting (Server)

[0822] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company in the form of a report.

[0823] Companies can use the reports they receive to review their advertising strategies and identify areas for improvement, allowing them to evolve their ads accordingly based on user interests and behavior, maximizing their effectiveness.

[0824] Specific examples

[0825] As a concrete example, imagine a company launching a new smartphone on the market. The company uploads images and text of the new product to a management portal. When users read tech articles or search for the latest smartphones, that data is anonymized and sent to a server.

[0826] Based on the data analyzed on the server, AI generates advertisements including technical details and delivers them to the user's device. When the user returns to the web, the advertisements highlighting the technical details are displayed. Performance data on the displayed advertisements is then collected and sent to the company as a report.

[0827] In this way, the present invention provides a series of processes for optimizing advertising content for each user and maximizing advertising effectiveness.

[0828] The processing flow will be explained below.

[0829] Step 1:

[0830] A user views a web page.

[0831] A user opens a specific web page, enters a search query, clicks a link, etc. For example, a user browses a tech article and searches for a new smartphone.

[0832] Step 2:

[0833] The device collects user behavior data.

[0834] The device collects data such as your web browsing history, search queries, and links you click, all of which is collected in an anonymized and privacy-protecting manner.

[0835] Step 3:

[0836] The device sends the collected user data to the server.

[0837] The device then packets the collected user data and transmits it to the server using the appropriate communication protocol, such as the history of browsing technology articles or the search query "latest smartphones."

[0838] Step 4:

[0839] The server receives and stores the user data.

[0840] The server stores the received user data in a database, which stores each user's behavioral history in an anonymized form.

[0841] Step 5:

[0842] The server parses the user data.

[0843] The AI ​​analysis module on the server analyzes the stored user data. This analysis uses machine learning algorithms and natural language processing technology. For example, if a user has a lot of browsing history related to technology, it can determine that they are interested in technology.

[0844] Step 6:

[0845] The server generates the best ad.

[0846] The server generates ads by combining optimal advertising materials based on user data analyzed by AI. For example, for a user determined to be interested in technology, an ad emphasizing the technical details of the latest smartphones will be generated.

[0847] Step 7:

[0848] The server transmits the generated advertisement to the terminal.

[0849] The server then distributes the generated advertisement content to the user's device, appropriately packetizing it using a communication protocol and sending it to the device.

[0850] Step 8:

[0851] The device displays advertisements.

[0852] When the user visits the web page again, the device displays the advertisement received from the server, for example, an advertisement for a smartphone highlighting its technical details on the web page.

[0853] Step 9:

[0854] The device collects advertising performance data.

[0855] The device collects performance data, such as the clicks users make on ads they see and the amount of time they spend on them.

[0856] Step 10:

[0857] The terminal transmits the advertising performance data to the server.

[0858] The device sends the collected performance data to a server, which is also anonymized.

[0859] Step 11:

[0860] The server analyzes the ad performance data.

[0861] The server analyzes the received performance data and evaluates the effectiveness of the advertisement, such as the number of clicks and conversion rate.

[0862] Step 12:

[0863] The server generates the analysis results as a report and sends it to the company.

[0864] The server generates reports based on advertising performance data and provides feedback to businesses, giving them new perspectives to review and optimize their advertising strategies.

[0865] As described above, the specific processing flow from step 1 to step 12 makes it possible to realize a system that generates advertisements optimized for each user and measures and optimizes their effectiveness.

[0866] Example 1

[0867] 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."

[0868] In conventional advertising systems, the collection of user data, ad delivery, and performance tracking are all separated, making it difficult to efficiently optimize and measure advertising effectiveness.In addition, it is difficult to generate advertising content that reflects user interests in real time, making it difficult to maximize advertising effectiveness.

[0869] 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.

[0870] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for anonymizing the user data and transmitting it to the server, means for analyzing the user data collected by the server using an AI model and generating optimal advertising content, means for delivering the generated advertising content to the user's terminal, means for tracking performance data when the advertisement is displayed and storing it in a database, and means for analyzing the collected performance data and transmitting reports to the company. This makes it possible to centrally optimize advertising and measure its effectiveness, and to provide advertising content that evolves in real time based on user behavior data.

[0871] "Advertising materials" are data such as images, text, and parts that companies register in order to create advertisements.

[0872] "User data" is information collected when a user browses a web page, such as browsing history, search queries, and links clicked.

[0873] "Anonymization" is the process of removing personally identifiable information from user data, rendering it anonymous.

[0874] "Server" means the central device of the advertising system, which collects and analyzes user data, generates and delivers advertisements, tracks performance data, and sends reports.

[0875] An "AI model" is a machine learning algorithm used to analyze collected user data, identify user interests, and generate optimal advertising content.

[0876] "Performance data" refers to data that indicates the effectiveness of an advertisement, such as the number of clicks, duration of visit, and engagement rate.

[0877] A "report" is a document that summarizes the results of performance data analyzed by the server and provides it to a company.

[0878] "Device" means the device a user uses to view web pages, collect user data, and display advertisements.

[0879] "Advertising content" refers to the optimal advertising content generated by the AI ​​model based on user data.

[0880] "Database" means a storage device for storing collected user and performance data.

[0881] The "evolving advertising system" of this invention is an integrated system consisting of multiple components that allows companies to register advertising materials and generate and distribute optimal advertisements based on user data. This system functions primarily around a server, terminals, and users.

[0882] Registration of advertising materials (server)

[0883] The server provides a management portal that allows companies to register their advertising materials. Through this management portal, companies can upload images, text, and other elements, and add, edit, or delete them as needed. For example, if a company is creating an advertisement for a new smartphone, it can enter and save an image of the smartphone, a description, a tagline, and other information into the portal.

[0884] Collection of user data (terminal, user, server)

[0885] When a user browses a web page, the device collects user data, including browsing history, search queries, and clicked links. The collected data is anonymized and sent to a server. For example, if a user searches for "latest smartphones" and reads a technology article, the behavioral data is anonymized on the device and sent to a server. The server stores this data in a database and uses it to analyze the user's interests and behavioral patterns.

[0886] Data analysis and advertisement generation (server)

[0887] The server analyzes the collected user data using an AI model to identify the user's interests. Specifically, if the AI ​​model identifies a user's interest in technology, it combines advertising materials that match that interest and generates optimal advertising content. For example, if the AI ​​model determines that the user is "highly interested in technology," it generates an advertisement that includes technical details of a new smartphone as the optimal advertisement for that user.

[0888] Delivery and display of advertisements (servers and terminals)

[0889] The generated advertisement content is delivered from the server to the user's device. Based on the user's behavioral data, the server determines in real time which advertisement to display and when. For example, when the user visits a web page again, a smartphone advertisement including technical details is displayed. The device displays the received advertisement, providing the user with the most appropriate advertising content.

[0890] Performance Tracking and Reporting (Server)

[0891] Each time an ad is displayed, its performance data is collected. The server collects and analyzes the number of clicks, duration, engagement rate, etc. These results are provided to companies as a report. Companies can use the reports they receive to review their advertising strategies and identify areas for improvement. This allows ads to evolve in response to user interests and behavior, maximizing their effectiveness.

[0892] Examples and prompts

[0893] As a concrete example, consider a company launching a new smartphone. The company uploads images and text about the new product to a management portal. When users read technical articles or search for "latest smartphone," the data is anonymized and sent to a server. The server analyzes the data using an AI model and generates an advertisement with technical details. The advertisement is delivered to the user's device and displayed when they return to the web. Performance data on the advertisement is collected and analyzed and sent to the company in a report.

[0894] Example prompt sentence:

[0895] "Analyze data from users' searches and articles about the latest smartphones, and generate ad content that includes technical details relevant to their interests."

[0896] Thus, the present invention is a system that provides a series of processes for optimizing advertising content for each user and maximizing advertising effectiveness.

[0897] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0898] Program processing flow

[0899] Step 1: Registering advertising materials (server)

[0900] The server provides a management portal for companies to register their advertising materials. Companies access this portal and upload advertising materials such as images, text, and parts.

[0901] Input: Advertising materials provided by the company (images, text, parts)

[0902] Output: Advertising materials stored in a database

[0903] Specific operation: A company logs in to the management portal through a web browser, clicks the "Create new ad" button to upload and save advertising materials, and the server stores the uploaded materials in a database.

[0904] Step 2: Collecting user data (device, user, server)

[0905] As users browse web pages, their devices collect user data, including browsing history, search queries, and links clicked.

[0906] Input: User behavioral data on webpage browsing (browsing history, search queries, clicks, etc.)

[0907] Output: Anonymized user data

[0908] What it does: When a user searches for "latest smartphones" and clicks to read a tech article, the device hashes this data, associates it with an anonymous user ID, and sends it to a server, which stores it in a database.

[0909] Step 3: Data analysis and ad generation (server)

[0910] The server inputs the collected user data into an AI model to identify the user's interests and generate optimal advertising content based on the results.

[0911] Input: Anonymized user data

[0912] Output: Optimal ad content

[0913] How it works: The server inputs data that "the user read a technical article" into the AI ​​model, and the AI ​​model determines that "the user has a high interest in technology." The server then generates advertising content including technical details based on this determination.

[0914] Step 4: Delivery and display of advertisements (server / terminal)

[0915] The server delivers the generated advertisement content to the user's device, and displays the advertisement at the appropriate time when the user visits the web page again.

[0916] Input: Best Ad Content

[0917] Output: Ad displayed on user device

[0918] How it works: The server detects when the user returns and delivers a smartphone ad highlighting technical details at that time. The device then displays the received ad to the user.

[0919] Step 5: Performance Tracking and Reporting (Server)

[0920] The server collects performance data each time an ad is displayed, such as the number of clicks, time spent, and engagement rate, and analyzes this data to provide reports to the company.

[0921] Input: Performance data of displayed ads (number of clicks, time spent, engagement rate, etc.)

[0922] Output: A report containing the analysis results

[0923] How it works: When a user clicks on an ad, their device sends that information to a server. The server then stores this data in a database and analyzes it. The analysis results are compiled into a report and sent to the company.

[0924] In this way, the server, terminal, and user work together to enable the "evolving advertising system" to optimize the content of advertisements and maximize advertising effectiveness.

[0925] (Application example 1)

[0926] 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."

[0927] While conventional advertising systems have provided a means to optimize advertisements based on user behavior data, they have not adequately optimized advertisements for specific environments or situations. In particular, in autonomous vehicles, there is a lack of a mechanism for displaying optimized advertisements in real time using passenger behavior data and geographic information. A system that can maximize the effectiveness of advertisements in such environments is needed.

[0928] 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.

[0929] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for analyzing the user data and generating optimal advertising content, means for delivering the generated advertising content to users, means for tracking the performance of the advertising and sending reports to companies, an information collection device in the vehicle for collecting passenger behavior data, and means for generating and delivering advertisements based on the behavior data and geographic information, thereby making it possible to display optimized advertisements in real time by utilizing passenger behavior data and geographic information in the vehicle.

[0930] The "means for registering advertising materials" is a part of the system that provides an interface for companies to upload advertising materials (images, text, parts, etc.) to a management portal on a server.

[0931] "Means for collecting user data" refers to the part of the system that collects behavioral data (browsing history, search queries, clicked links, etc.) from the user's device while browsing web pages and sends it to the server.

[0932] The "means for analyzing the user data and generating optimal advertising content" refers to part of a system that analyzes collected user data using an AI model and generates optimal advertising content based on the user's interests and concerns.

[0933] The "means for delivering the generated advertisement content to the user" is a part of the system that delivers the generated advertisement content to the user's terminal and displays it at an appropriate time.

[0934] The "means for tracking the performance of the advertisement and sending reports to the company" is part of a system that tracks performance data such as the number of clicks on the advertisement, the length of time spent on the advertisement, and the engagement rate, and sends the analysis results to the company as a report.

[0935] "In-vehicle information collection device for collecting passenger behavior data" refers to a device for collecting passenger behavior data inside an autonomous vehicle, and includes devices such as smartphones and displays.

[0936] The "means for generating and delivering advertisements based on the behavioral data and geographic information" refers to part of a system that generates optimal advertisements based on collected passenger behavioral data and vehicle geographic information, and delivers them in real time to displays inside autonomous vehicles.

[0937] The present invention consists of several important components for implementing an "evolving advertising system" in an autonomous vehicle. Specific implementation methods and details of each process are described below.

[0938] 1. Registration of advertising materials (server)

[0939] The server provides a means for companies to register their advertising materials. Companies access the management portal and upload advertising materials such as images, text, and parts. This management portal provides an interface that makes it easy to add, edit, and delete advertising materials.

[0940] 2. Collection of user data (terminals, users, servers)

[0941] A dedicated app installed on a user's smartphone collects behavioral data while browsing web pages. This data is anonymized and sent to a server via passenger smartphones or information collection devices in autonomous vehicles. This allows companies to obtain information such as browsing history, search queries, and links clicked.

[0942] 3. Data analysis and advertisement generation (server)

[0943] The server analyzes the collected user data and uses an AI model to identify the user's interests and generate optimal ads based on them. For example, if an interest in technology is identified, the server creates optimal content by combining advertising materials that match those interests.

[0944] 4. Delivery and display of advertisements (servers and terminals)

[0945] The generated advertising content is delivered to the user's device, particularly to the information display in the autonomous vehicle. The server determines in real time which advertisement to display and when based on the user's behavioral data. This allows the system to display optimized advertisements in real time by utilizing passenger behavioral data and geographical information.

[0946] 5. Performance Tracking and Reporting (Server)

[0947] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of ad clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company as a report. Based on the report, the company can review its advertising strategy and identify areas for improvement.

[0948] Specific examples

[0949] For example, if a passenger browses a specific shopping site on their smartphone, the application will collect that data. The collected data will be anonymized and analyzed by an advertising server. Advertisements for products and services tailored to the passenger's interests will be displayed in real time on the display inside the self-driving vehicle.

[0950] Prompt Sentence Examples

[0951] "Generate ads that may be of interest to you based on the following data:

[0952] Browsing history: Electronics, latest gadgets

[0953] Search Query: smartphone reviews

[0954] Link clicked: New smartphone feature article

[0955] As a result, the present invention makes it possible to utilize passenger behavior data and geographic information in autonomous vehicles to display optimal advertisements in real time.

[0956] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0957] Step 1:

[0958] The device (user's smartphone) collects behavioral data when the user browses web pages, including browsing history, search queries, clicked links, etc. This behavioral data is collected in real time and temporarily stored on the device.

[0959] Input: User behavior data (browsing history, search queries, clicked links)

[0960] Output: Behavioral data temporarily stored on the device

[0961] Step 2:

[0962] The device anonymizes the collected behavioral data. Specifically, it removes personal identification information such as user ID and location information. This anonymization process protects privacy.

[0963] Input: Collected behavioral data

[0964] Output: Anonymized behavioral data

[0965] Step 3:

[0966] The device sends anonymized behavioral data to a server, where it is stored and used for subsequent analysis.

[0967] Input: Anonymized behavioral data

[0968] Output: Behavioral data stored on the server

[0969] Step 4:

[0970] The server analyzes the stored behavioral data and uses a generative AI model to identify the user's interests. Specifically, it uses the collected data to analyze which areas the user is particularly interested in. Based on this analysis, it generates optimal advertising content.

[0971] Input: Behavioral data stored on the server

[0972] Output: Optimal ad content

[0973] Step 5:

[0974] The server then transmits the generated advertising content to the information display inside the autonomous vehicle, which then displays the advertisement in real time according to specific timing and conditions.

[0975] Input: Optimal ad content

[0976] Output: Advertisement displayed on the screen

[0977] Step 6:

[0978] The server tracks the performance of the ad after it has been displayed, using display sensors and device feedback to collect data such as ad clicks, dwell time, and engagement rate.

[0979] Input: Performance data of ads displayed on the screen

[0980] Output: Collected performance data

[0981] Step 7:

[0982] The server analyzes the collected performance data and sends it to the company as a report, which details the effectiveness of the advertisement and areas for improvement, providing important information for the company to review its advertising strategy.

[0983] Input: Collected performance data

[0984] Output: Report sent to company

[0985] Specific behavior:

[0986] 1. When a user browses a specific shopping site, the device records this activity.

[0987] 2. The device removes the user ID from the recorded data and anonymizes it.

[0988] 3. The anonymized data is sent to a server via Wi-Fi or 4G / 5G networks.

[0989] 4. The server uses a generative AI model to analyze the data and determine that the user is interested in the latest gadgets.

[0990] 5. The server generates the most suitable advertisement (e.g., an advertisement for the latest gadget) and sends it to a display inside the autonomous vehicle.

[0991] 6. If a passenger clicks on an ad, their data is collected again.

[0992] 7. The server sends the collected data in the form of a report to the company to evaluate the effectiveness of the advertisement.

[0993] 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.

[0994] The "evolving advertising system" of this invention is an integrated system consisting of multiple components, and is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user behavior data and emotions. Below, we will explain the specific implementation method of this system and the details of each process.

[0995] 1. Registration of advertising materials (server)

[0996] First, a company uploads advertising materials (images, text, parts, etc.) to a management portal on the server. This management portal provides an interface that allows companies to easily add, edit, and delete advertising materials. For example, if a company is creating an advertisement for a new smartphone, it can enter and save the smartphone's image, description, catchphrase, etc. into the portal.

[0997] 2. Collection of user data (terminals, users, servers)

[0998] Your device collects user data while you browse web pages, including your browsing history, search queries, and links you click. If you read a tech article or search for "latest smartphones," that behavioral data is anonymized and sent to a server.

[0999] The server receives this data and stores it in a database. The collected data is used to analyze user interests and behavior patterns.

[1000] 3. Emotion data collection (emotion engine, device, user)

[1001] The user's device is equipped with a camera device. This camera is used to analyze the user's facial expressions in real time, and an emotion engine is activated to collect emotional data. For example, emotions such as interest, enthusiasm, and dissatisfaction can be recognized from the user's facial expressions while browsing a web page.

[1002] 4. Data analysis and advertisement generation (server)

[1003] The server uses an AI analysis module to analyze the collected user data and emotional data. Based on the analysis results, the AI ​​generates ads by combining optimal advertising materials. For example, if a user shows interest while reading a technology article, an ad highlighting the technical specifications of a new smartphone will be generated.

[1004] 5. Delivery and display of advertisements (servers and terminals)

[1005] The generated ad content is delivered to the user's device. The server determines in real time which ad to display and when based on the user's behavioral and emotional data. The generated ad is displayed when the user visits the web page again or when certain conditions are met.

[1006] For example, if a user frequently reads technology articles and shows an expression of interest, they will be shown a smartphone ad that highlights the technical details.

[1007] 6. Performance Tracking and Reporting (Server)

[1008] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company in the form of a report.

[1009] Companies can use the reports they receive to refine their advertising strategies and identify areas for improvement, allowing their ads to evolve accordingly based on user interests, behaviors, and emotions, maximizing their effectiveness.

[1010] Specific examples

[1011] As a concrete example, consider a company launching a new smartphone on the market. The company uploads images and text of the new product to a management portal. When users read technical articles or perform searches about the latest smartphones, the data is anonymized and sent to a server. In addition, the camera device captures the user's facial expressions as they read the articles, and emotional data is also collected.

[1012] Based on the data analyzed on the server and the emotional data, AI generates advertisements including technical details and delivers them to the user's device. When the user visits the web again, the advertisements emphasizing the technical details are displayed. Performance data on the displayed advertisements is then collected and sent to the company as a report.

[1013] In this way, the present invention provides a series of processes for optimizing advertising content for each user and taking into account their emotional responses, thereby maximizing advertising effectiveness.

[1014] The processing flow will be explained below.

[1015] Step 1:

[1016] A user views a web page.

[1017] A user opens a specific web page, enters a search query, clicks a link, etc. For example, a user browses a tech article and searches for a new smartphone.

[1018] Step 2:

[1019] The device collects user behavior data.

[1020] The device collects data such as your web browsing history, search queries, and links you click, all of which is collected in an anonymized and privacy-protecting manner.

[1021] Step 3:

[1022] The device sends the collected user data to the server.

[1023] The device then packets the collected user data and transmits it to the server using the appropriate communication protocol, such as the history of browsing technology articles or the search query "latest smartphones."

[1024] Step 4:

[1025] The server receives and stores the user data.

[1026] The server stores the received user data in a database, which stores each user's behavioral history in an anonymized form.

[1027] Step 5:

[1028] The device's built-in emotion engine analyzes the user's facial expressions.

[1029] Using the camera built into the user's device, the emotion engine captures and analyzes the user's facial expressions in real time, for example, recognizing whether the user is smiling or looking interested while reading an article.

[1030] Step 6:

[1031] The device transmits the collected emotion data to a server.

[1032] The device anonymizes the collected emotional data and transmits it to a server using an appropriate communication protocol.

[1033] Step 7:

[1034] The server receives and stores the emotion data.

[1035] The server stores the received emotion data in a database, where it is associated with behavioral data and used for analysis.

[1036] Step 8:

[1037] The server analyzes user data and emotional data.

[1038] The AI ​​analysis module on the server analyzes the stored user data and emotional data. The analysis uses machine learning algorithms and natural language processing technology. For example, if a user has a history of browsing technical content and looks interested, it can determine that they are interested in technology.

[1039] Step 9:

[1040] The server generates the best ad.

[1041] The server generates ads by combining optimal advertising materials based on user data and emotional data analyzed by AI, such as a smartphone ad that emphasizes technical details.

[1042] Step 10:

[1043] The server transmits the generated advertisement to the terminal.

[1044] The server then distributes the generated advertisement content to the user's device, appropriately packetizing it using a communication protocol and sending it to the device.

[1045] Step 11:

[1046] The device displays advertisements.

[1047] When the user visits the web page again, the device displays the advertisement received from the server, for example, an advertisement for a smartphone highlighting its technical details on the web page.

[1048] Step 12:

[1049] The device collects advertising performance data.

[1050] The device collects performance data, such as the clicks users make on ads they see and the amount of time they spend on them.

[1051] Step 13:

[1052] The terminal transmits the advertising performance data to the server.

[1053] The device sends the collected performance data to a server, which is also anonymized.

[1054] Step 14:

[1055] The server analyzes the ad performance data.

[1056] The server analyzes the received performance data and evaluates the effectiveness of the advertisement, such as the number of clicks and conversion rate.

[1057] Step 15:

[1058] The server generates the analysis results as a report and sends it to the company.

[1059] The server generates reports based on advertising performance data and provides feedback to businesses, giving them new perspectives to review and optimize their advertising strategies.

[1060] As described above, by following the specific processing flow from step 1 to step 15, it is possible to realize a system that generates advertisements optimized for each user and measures and optimizes their effectiveness.

[1061] Example 2

[1062] 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."

[1063] Conventional ad delivery systems generate and deliver ads based solely on user behavior data, but they are insufficient in adapting to the emotional responses of individual users. This results in ads not being optimized based on user emotions, and the effectiveness of ads is not maximized. Furthermore, the lack of analysis and feedback on advertising effectiveness makes it difficult for companies to quickly revise their advertising strategies.

[1064] 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.

[1065] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for collecting user emotion data using a camera device, means for analyzing the user data and emotion data and generating optimal advertising content using a generative AI model, means for delivering the generated advertising content to user devices, and means for tracking the performance of the advertising and sending reports to companies. This makes it possible to optimize advertising based on user behavioral data and emotion data, and further evolve advertising content in real time, thereby maximizing advertising effectiveness.

[1066] "Advertising materials" are digital content such as images, text, and parts that companies use to create advertisements.

[1067] "User Data" refers to behavioral data such as a user's web page browsing history, search queries, and links clicked.

[1068] A "camera device" is a hardware device used to capture a user's facial expressions.

[1069] "Emotion data" refers to data relating to emotions such as interest, concern, enjoyment, and dissatisfaction recognized from the user's facial expression.

[1070] A "generative AI model" is an artificial intelligence algorithm used to generate optimal advertising content based on collected data.

[1071] "Advertising Content" refers to the combination of text, images, and parts of a specific advertisement delivered to a user.

[1072] "Advertising performance" refers to effectiveness measurement data such as the number of clicks, length of stay, and engagement rate when an ad is displayed.

[1073] A "report" is a document or digital file that is sent to a company and is the result of analyzing advertising performance data.

[1074] This invention is an integrated advertising system consisting of multiple components, which is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user data and emotional data. Below, we will explain the specific implementation method of this system and the details of each process.

[1075] Registration of advertising materials (server)

[1076] The server provides a management portal where companies can upload advertising materials (images, text, parts, etc.). This portal has an interface that allows companies to easily add, edit, and delete advertising materials. When a company creates an advertisement for a new smartphone, it enters and saves an image of the smartphone, a description, a tagline, etc. into the portal. The hardware used is a web server (e.g., Apache, NGINX), and the software used is a CMS (content management system) such as WordPress or Joomla.

[1077] Collection of user data (terminal, user, server)

[1078] The device collects behavioral data (browsing history, search queries, clicked links, etc.) when the user browses web pages. For example, if a user reads a technology article or searches for "latest smartphones," this behavioral data is anonymized and sent to a server. The sent data is stored in the server's database (e.g., MySQL, PostgreSQL) and used to analyze user interests and behavioral patterns. Software used includes Google Analytics and Mixpanel.

[1079] Emotion data collection (emotion engine, device, user)

[1080] A camera installed on the user's device analyzes the user's facial expressions in real time, and an emotion engine is activated to collect emotional data. For example, emotions such as interest, enthusiasm, and dissatisfaction can be recognized from the user's facial expressions while browsing a web page. This is achieved using software such as TensorFlow and OpenCV. The collected emotional data is sent from the device to a server and stored in a database.

[1081] Data analysis and advertisement generation (server)

[1082] The server uses an AI analysis module to analyze the collected user data and sentiment data. Based on the analysis results, the AI ​​generates ads by combining optimal advertising materials. For example, for a user who shows interest while reading a technical article, an ad highlighting the technical specifications of a new smartphone will be generated. The AI ​​analysis module used is a proprietary model using PyTorch and TensorFlow.

[1083] Delivery and display of advertisements (servers and terminals)

[1084] The server delivers the generated advertising content to the user's device. Based on the user's behavioral and emotional data, the server determines in real time which advertisement to display and when. For example, if a user frequently reads technical articles and shows an expression that indicates interest, a smartphone advertisement emphasizing technical details will be displayed. Advertisements are delivered using an AdServer platform (e.g., Google AdServer).

[1085] Performance Tracking and Reporting (Server)

[1086] The server tracks the performance of each ad displayed. The server collects and analyzes data such as the number of ad clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company as a report. Based on the reports, the company can review its advertising strategy and identify areas for improvement. Software such as Tableau and Google Data Studio are used for analysis and report generation.

[1087] Specific examples

[1088] As a specific example, when a company launches a new smartphone, it uploads images and text of the new product to a management portal. When a user reads a technical article or searches for "latest smartphone," the data is anonymized and sent to a server. A camera captures the user's facial expressions as they read the article, and emotional data is also collected. Based on the data analyzed on the server and the emotional data, AI generates an advertisement that includes technical details and delivers it to the user's device. When the user visits the web again, an advertisement emphasizing the technical details is displayed. Performance data on the displayed advertisement is then collected and sent to the company as a report. This allows the content of the advertisement to be optimized for each user, maximizing its effectiveness.

[1089] Prompt Sentence Examples

[1090] Below are some example prompts to input to a generative AI model:

[1091] "Upload new smartphone ad materials to the management portal and generate optimal ads based on user browsing and sentiment data."

[1092] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1093] System program processing flow

[1094] Step 1: Registering advertising materials (server)

[1095] Input: Advertising materials provided by companies (images, text, parts)

[1096] Specific operation: A company accesses the server's management portal and uploads new advertising materials, which inputs the images, text, and parts of the advertisement into the portal and sends them to the server.

[1097] Data processing: The server receives the uploaded advertising material and converts it into the required format.

[1098] Output: Save the converted advertising material in the database.

[1099] Step 2: Collecting user data (device, user, server)

[1100] Input: User's webpage browsing history, search queries, and clicked links

[1101] Specific operations: The device collects behavioral data when the user browses web pages.

[1102] Data processing: The device anonymizes the collected data and sends it to a server using a secure protocol.

[1103] Output: The server stores the received data in a database.

[1104] Step 3: Collecting emotion data (emotion engine, device, user)

[1105] Input: User's facial expression data

[1106] Specific operation: The camera on the user's device captures facial expressions, which are then analyzed in real time by an emotion engine (e.g., TensorFlow).

[1107] Data processing: The analyzed emotion data is sent from the device to the server.

[1108] Output: The server stores the emotion data in a database.

[1109] Step 4: Data analysis and ad generation (server)

[1110] Input: User data and emotion data

[1111] Specific operation: The server's AI analysis module performs analysis based on collected user data and emotional data.

[1112] Data processing: An AI analysis module (e.g., PyTorch) analyzes the data and combines the optimal advertising materials based on the results.

[1113] Output: The generated advertisement content is saved in the database.

[1114] Step 5: Delivery and display of advertisements (server / terminal)

[1115] Input: Generated ad content

[1116] Specific operation: The server delivers advertisements to the user's device at the appropriate time.

[1117] Data processing: Delivering advertisements using an advertising platform (e.g., Google AdServer).

[1118] Output: The user's device displays the delivered ad.

[1119] Step 6: Performance Tracking and Reporting (Server)

[1120] Input: Performance data such as ad clicks, visit duration, and engagement rate

[1121] What it does: The server tracks the performance of the ads in real time.

[1122] Data processing: Analyze performance data and generate reports based on the results.

[1123] Output: Send the generated report to the company.

[1124] (Application example 2)

[1125] 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."

[1126] Conventional advertising systems personalize ads based on user behavior data, but they face the challenge of being unable to take into account user emotions and instantaneous reactions. This often results in insufficient advertising effectiveness. Another issue is that even if advertising performance data is collected, there is a lack of adequate means to properly analyze it and reflect it in advertising strategies.

[1127] 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 registering advertising materials, means for collecting user data and emotion data, means for analyzing the user data and emotion data and generating optimal advertising content, means for evolving the advertising content based on prompt text using a generative AI model, means for delivering the generated advertising content to users, means for collecting emotion data, and means for tracking the performance of the advertising and sending reports to companies. This makes it possible to optimize advertising in real time based on user behavioral data and emotion data, maximizing advertising effectiveness.

[1128] "Advertising materials" are elements such as images, text, video, and audio that make up an advertisement.

[1129] "User Data" refers to your web page browsing history, search queries, links you click, and other online behavior data.

[1130] "Emotional data" refers to data related to emotions such as interest, concern, enjoyment, and dissatisfaction that can be read from the user's facial expressions and voice.

[1131] The "AI analysis module" is an artificial intelligence-based analysis system that analyzes user data and emotional data to generate optimal advertising content.

[1132] A "generative AI model" is an artificial intelligence-based generation system that evolves advertising content based on a given prompt.

[1133] A "prompt" is an instruction given to a generative AI model to evolve advertising content.

[1134] "Performance data" refers to data used to evaluate the effectiveness of advertising, such as the number of clicks, duration, and engagement rate after an advertisement is displayed.

[1135] A "report" is a report that analyzes advertising performance data and summarizes the results.

[1136] "Delivery" means displaying the generated advertising content to the user.

[1137] The "evolving advertising system" of the present invention is an integrated system that includes a management portal for registering advertising materials, an AI analysis module for collecting and analyzing user data and emotional data, a generative AI model, an advertising distribution system, a performance data tracking system, and a report generation system.

[1138] 1. Registration of advertising materials

[1139] Companies use the management portal to register advertising materials. Specifically, this includes images, text, videos, etc. to be used in advertisements. These materials are stored on the server and used in later steps. The management portal is designed so that companies can easily add, edit, and delete advertising materials.

[1140] 2. Collection of User Data

[1141] While a user is browsing a web page, their device collects user data, including browsing history, search queries, clicked links, etc. This data is anonymized and sent to a server.

[1142] 3. Collecting Emotional Data

[1143] The user's device is equipped with a camera device that captures the user's facial expressions. The emotion engine analyzes the facial expressions in real time and collects emotional data such as interest, concern, enjoyment, and dissatisfaction. This data is also anonymized and sent to the server.

[1144] 4. Data analysis and ad generation

[1145] The AI ​​analysis module on the server analyzes user data and emotional data. Based on the analysis results, the generative AI model generates ads by combining optimal advertising materials. This creates personalized ads that match the user's interests and emotions.

[1146] 5. Delivery and display of advertisements

[1147] The generated ad content is delivered to the user's device. The server displays the ad at the optimal time based on the user's behavioral and emotional data, thereby maximizing the effectiveness of the ad.

[1148] 6. Performance Tracking and Reporting

[1149] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks on the ad, the time spent on the ad, and the engagement rate. The results of this analysis are sent to the company as a report, which the company can use to revise its advertising strategy.

[1150] Hardware and software used

[1151] Smartphone: The device on which the application is installed

[1152] Camera device: Captures the user's facial expressions

[1153] Server: Analyzes data, generates and delivers ads

[1154] AI analysis module: Artificial intelligence for analyzing collected data

[1155] Generative AI model: Artificial intelligence for evolving ad content based on prompts

[1156] Database: Stores user data and emotion data

[1157] Specific examples

[1158] For example, if a user is browsing a movie-related webpage and their facial expressions indicate interest, they can be shown a trailer ad for a new movie. Furthermore, the performance data of the ad can be analyzed and feedback on advertising strategies can be provided based on the results.

[1159] Prompt Sentence Examples

[1160] "When a user is searching for movie-related information, generate new movie trailer ads. Capture the user's facial expressions that express interest, and use that emotional data to display the most appropriate ad."

[1161] In this way, the present invention provides a system that uses user behavioral data and emotional data to optimize advertisements in real time and maximize advertising effectiveness.

[1162] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1163] Step 1:

[1164] The device collects user data, including browsing history, search queries, and clicked links. This data is used to understand user behavior patterns. Input data is user data, and output data is user data sent to a server for analysis.

[1165] Step 2:

[1166] The device uses a camera device to collect user emotional data. The collected emotional data is used to analyze emotions such as interest, concern, enjoyment, and dissatisfaction from the user's facial expressions. The input is facial expression data captured in real time, and the output is emotional data analyzed by the emotion engine.

[1167] Step 3:

[1168] The server receives the user data and emotion data collected in step 1 and step 2 and stores them in a database, thereby forming a consistent dataset of user behavior and emotion. The input data are the user data and emotion data, and the output data is the dataset stored in the database.

[1169] Step 4:

[1170] The server's AI analysis module analyzes the user data and emotional data stored in the database. The analysis reveals the user's behavioral patterns and emotional characteristics. The input data is the data stored in the database, and the output data is the analysis results.

[1171] Step 5:

[1172] The server's generative AI model selects the optimal advertising materials based on the analysis results and generates the advertisement. Specifically, it automatically generates relevant advertising content based on prompts that are likely to interest the user. The input data are the analysis results and prompts, and the output data is the generated advertisement.

[1173] Step 6:

[1174] The server delivers the generated advertisement to the user's device. The timing of the advertisement delivery is optimized based on real-time user data and emotion data. The input data is the generated advertisement, and the output data is the advertisement displayed on the device.

[1175] Step 7:

[1176] The device collects performance data as a result of the advertisement being displayed to the user, including the number of clicks on the advertisement, the duration of the visit, the engagement rate, etc. The input data is the user's response to the advertisement, and the output data is the performance data.

[1177] Step 8:

[1178] The server analyzes the performance data collected in step 7 and generates a report for the company. The report is used to evaluate the effectiveness of the advertisement and to suggest improvements to the advertisement strategy. The input data is the performance data and the output data is the report sent to the company.

[1179] Through each step, ads are created that are optimized in real time based on user behavior and emotions, maximizing their effectiveness.

[1180] 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.

[1181] 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.

[1182] 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.

[1183] [Fourth embodiment]

[1184] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1185] 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.

[1186] 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).

[1187] 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.

[1188] 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.

[1189] 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).

[1190] 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.

[1191] 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.

[1192] 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.

[1193] 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.

[1194] 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.

[1195] 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.

[1196] 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."

[1197] The "evolving advertising system" of this invention is an integrated system consisting of multiple components, and is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user behavior data. Below, we will explain the specific implementation method of this system and the details of each process.

[1198] 1. Registration of advertising materials (server)

[1199] First, a company uploads advertising materials (images, text, parts, etc.) to a management portal on the server. This management portal provides an interface that allows companies to easily add, edit, and delete advertising materials. For example, if a company is creating an advertisement for a new smartphone, it can enter and save the smartphone's image, description, catchphrase, etc. into the portal.

[1200] 2. Collection of user data (terminals, users, servers)

[1201] Your device collects user data while you browse web pages, including your browsing history, search queries, and links you click. If you read a tech article or search for "latest smartphones," that behavioral data is anonymized and sent to a server.

[1202] The server receives this data and stores it in a database. The collected data is used to analyze user interests and behavior patterns.

[1203] 3. Data analysis and advertisement generation (server)

[1204] The server uses an AI model to analyze the collected user data, identifying the user's interests and generating optimal advertising content based on that information.

[1205] Specifically, if the AI ​​model identifies a user's technology interests, it will combine advertising materials (such as new technology specifications or detailed product information) that match those interests to create optimal content.

[1206] 4. Delivery and display of advertisements (servers and terminals)

[1207] The generated ad content is delivered to the user's device. The server determines in real time which ad to display and when based on the user's behavioral data. The generated ad is displayed when the user visits the web page again or when certain conditions are met.

[1208] For example, users who frequently read technical articles will be shown ads that provide more technical details.

[1209] 5. Performance Tracking and Reporting (Server)

[1210] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company in the form of a report.

[1211] Companies can use the reports they receive to review their advertising strategies and identify areas for improvement, allowing them to evolve their ads accordingly based on user interests and behavior, maximizing their effectiveness.

[1212] Specific examples

[1213] As a concrete example, imagine a company launching a new smartphone on the market. The company uploads images and text of the new product to a management portal. When users read tech articles or search for the latest smartphones, that data is anonymized and sent to a server.

[1214] Based on the data analyzed on the server, AI generates advertisements including technical details and delivers them to the user's device. When the user returns to the web, the advertisements highlighting the technical details are displayed. Performance data on the displayed advertisements is then collected and sent to the company as a report.

[1215] In this way, the present invention provides a series of processes for optimizing advertising content for each user and maximizing advertising effectiveness.

[1216] The processing flow will be explained below.

[1217] Step 1:

[1218] A user views a web page.

[1219] A user opens a specific web page, enters a search query, clicks a link, etc. For example, a user browses a tech article and searches for a new smartphone.

[1220] Step 2:

[1221] The device collects user behavior data.

[1222] The device collects data such as your web browsing history, search queries, and links you click, all of which is collected in an anonymized and privacy-protecting manner.

[1223] Step 3:

[1224] The device sends the collected user data to the server.

[1225] The device then packets the collected user data and transmits it to the server using the appropriate communication protocol, such as the history of browsing technology articles or the search query "latest smartphones."

[1226] Step 4:

[1227] The server receives and stores the user data.

[1228] The server stores the received user data in a database, which stores each user's behavioral history in an anonymized form.

[1229] Step 5:

[1230] The server parses the user data.

[1231] The AI ​​analysis module on the server analyzes the stored user data. This analysis uses machine learning algorithms and natural language processing technology. For example, if a user has a lot of browsing history related to technology, it can determine that they are interested in technology.

[1232] Step 6:

[1233] The server generates the best ad.

[1234] The server generates ads by combining optimal advertising materials based on user data analyzed by AI. For example, for a user determined to be interested in technology, an ad emphasizing the technical details of the latest smartphones will be generated.

[1235] Step 7:

[1236] The server transmits the generated advertisement to the terminal.

[1237] The server then distributes the generated advertisement content to the user's device, appropriately packetizing it using a communication protocol and sending it to the device.

[1238] Step 8:

[1239] The device displays advertisements.

[1240] When the user visits the web page again, the device displays the advertisement received from the server, for example, an advertisement for a smartphone highlighting its technical details on the web page.

[1241] Step 9:

[1242] The device collects advertising performance data.

[1243] The device collects performance data, such as the clicks users make on ads they see and the amount of time they spend on them.

[1244] Step 10:

[1245] The terminal transmits the advertising performance data to the server.

[1246] The device sends the collected performance data to a server, which is also anonymized.

[1247] Step 11:

[1248] The server analyzes the ad performance data.

[1249] The server analyzes the received performance data and evaluates the effectiveness of the advertisement, such as the number of clicks and conversion rate.

[1250] Step 12:

[1251] The server generates the analysis results as a report and sends it to the company.

[1252] The server generates reports based on advertising performance data and provides feedback to businesses, giving them new perspectives to review and optimize their advertising strategies.

[1253] As described above, the specific processing flow from step 1 to step 12 makes it possible to realize a system that generates advertisements optimized for each user and measures and optimizes their effectiveness.

[1254] Example 1

[1255] 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."

[1256] In conventional advertising systems, the collection of user data, ad delivery, and performance tracking are all separated, making it difficult to efficiently optimize and measure advertising effectiveness.In addition, it is difficult to generate advertising content that reflects user interests in real time, making it difficult to maximize advertising effectiveness.

[1257] 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.

[1258] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for anonymizing the user data and transmitting it to the server, means for analyzing the user data collected by the server using an AI model and generating optimal advertising content, means for delivering the generated advertising content to the user's terminal, means for tracking performance data when the advertisement is displayed and storing it in a database, and means for analyzing the collected performance data and transmitting reports to the company. This makes it possible to centrally optimize advertising and measure its effectiveness, and to provide advertising content that evolves in real time based on user behavior data.

[1259] "Advertising materials" are data such as images, text, and parts that companies register in order to create advertisements.

[1260] "User data" is information collected when a user browses a web page, such as browsing history, search queries, and links clicked.

[1261] "Anonymization" is the process of removing personally identifiable information from user data, rendering it anonymous.

[1262] "Server" means the central device of the advertising system, which collects and analyzes user data, generates and delivers advertisements, tracks performance data, and sends reports.

[1263] An "AI model" is a machine learning algorithm used to analyze collected user data, identify user interests, and generate optimal advertising content.

[1264] "Performance data" refers to data that indicates the effectiveness of an advertisement, such as the number of clicks, duration of visit, and engagement rate.

[1265] A "report" is a document that summarizes the results of performance data analyzed by the server and provides it to a company.

[1266] "Device" means the device a user uses to view web pages, collect user data, and display advertisements.

[1267] "Advertising content" refers to the optimal advertising content generated by the AI ​​model based on user data.

[1268] "Database" means a storage device for storing collected user and performance data.

[1269] The "evolving advertising system" of this invention is an integrated system consisting of multiple components that allows companies to register advertising materials and generate and distribute optimal advertisements based on user data. This system functions primarily around a server, terminals, and users.

[1270] Registration of advertising materials (server)

[1271] The server provides a management portal that allows companies to register their advertising materials. Through this management portal, companies can upload images, text, and other elements, and add, edit, or delete them as needed. For example, if a company is creating an advertisement for a new smartphone, it can enter and save an image of the smartphone, a description, a tagline, and other information into the portal.

[1272] Collection of user data (terminal, user, server)

[1273] When a user browses a web page, the device collects user data, including browsing history, search queries, and clicked links. The collected data is anonymized and sent to a server. For example, if a user searches for "latest smartphones" and reads a technology article, the behavioral data is anonymized on the device and sent to a server. The server stores this data in a database and uses it to analyze the user's interests and behavioral patterns.

[1274] Data analysis and advertisement generation (server)

[1275] The server analyzes the collected user data using an AI model to identify the user's interests. Specifically, if the AI ​​model identifies a user's interest in technology, it combines advertising materials that match that interest and generates optimal advertising content. For example, if the AI ​​model determines that the user is "highly interested in technology," it generates an advertisement that includes technical details of a new smartphone as the optimal advertisement for that user.

[1276] Delivery and display of advertisements (servers and terminals)

[1277] The generated advertisement content is delivered from the server to the user's device. Based on the user's behavioral data, the server determines in real time which advertisement to display and when. For example, when the user visits a web page again, a smartphone advertisement including technical details is displayed. The device displays the received advertisement, providing the user with the most appropriate advertising content.

[1278] Performance Tracking and Reporting (Server)

[1279] Each time an ad is displayed, its performance data is collected. The server collects and analyzes the number of clicks, duration, engagement rate, etc. These results are provided to companies as a report. Companies can use the reports they receive to review their advertising strategies and identify areas for improvement. This allows ads to evolve in response to user interests and behavior, maximizing their effectiveness.

[1280] Examples and prompts

[1281] As a concrete example, consider a company launching a new smartphone. The company uploads images and text about the new product to a management portal. When users read technical articles or search for "latest smartphone," the data is anonymized and sent to a server. The server analyzes the data using an AI model and generates an advertisement with technical details. The advertisement is delivered to the user's device and displayed when they return to the web. Performance data on the advertisement is collected and analyzed and sent to the company in a report.

[1282] Example prompt sentence:

[1283] "Analyze data from users' searches and articles about the latest smartphones, and generate ad content that includes technical details relevant to their interests."

[1284] Thus, the present invention is a system that provides a series of processes for optimizing advertising content for each user and maximizing advertising effectiveness.

[1285] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1286] Program processing flow

[1287] Step 1: Registering advertising materials (server)

[1288] The server provides a management portal for companies to register their advertising materials. Companies access this portal and upload advertising materials such as images, text, and parts.

[1289] Input: Advertising materials provided by the company (images, text, parts)

[1290] Output: Advertising materials stored in a database

[1291] Specific operation: A company logs in to the management portal through a web browser, clicks the "Create new ad" button to upload and save advertising materials, and the server stores the uploaded materials in a database.

[1292] Step 2: Collecting user data (device, user, server)

[1293] As users browse web pages, their devices collect user data, including browsing history, search queries, and links clicked.

[1294] Input: User behavioral data on webpage browsing (browsing history, search queries, clicks, etc.)

[1295] Output: Anonymized user data

[1296] What it does: When a user searches for "latest smartphones" and clicks to read a tech article, the device hashes this data, associates it with an anonymous user ID, and sends it to a server, which stores it in a database.

[1297] Step 3: Data analysis and ad generation (server)

[1298] The server inputs the collected user data into an AI model to identify the user's interests and generate optimal advertising content based on the results.

[1299] Input: Anonymized user data

[1300] Output: Optimal ad content

[1301] How it works: The server inputs data that "the user read a technical article" into the AI ​​model, and the AI ​​model determines that "the user has a high interest in technology." The server then generates advertising content including technical details based on this determination.

[1302] Step 4: Delivery and display of advertisements (server / terminal)

[1303] The server delivers the generated advertisement content to the user's device, and displays the advertisement at the appropriate time when the user visits the web page again.

[1304] Input: Best Ad Content

[1305] Output: Ad displayed on user device

[1306] How it works: The server detects when the user returns and delivers a smartphone ad highlighting technical details at that time. The device then displays the received ad to the user.

[1307] Step 5: Performance Tracking and Reporting (Server)

[1308] The server collects performance data each time an ad is displayed, such as the number of clicks, time spent, and engagement rate, and analyzes this data to provide reports to the company.

[1309] Input: Performance data of displayed ads (number of clicks, time spent, engagement rate, etc.)

[1310] Output: A report containing the analysis results

[1311] How it works: When a user clicks on an ad, their device sends that information to a server. The server then stores this data in a database and analyzes it. The analysis results are compiled into a report and sent to the company.

[1312] In this way, the server, terminal, and user work together to enable the "evolving advertising system" to optimize the content of advertisements and maximize advertising effectiveness.

[1313] (Application example 1)

[1314] 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."

[1315] While conventional advertising systems have provided a means to optimize advertisements based on user behavior data, they have not adequately optimized advertisements for specific environments or situations. In particular, in autonomous vehicles, there is a lack of a mechanism for displaying optimized advertisements in real time using passenger behavior data and geographic information. A system that can maximize the effectiveness of advertisements in such environments is needed.

[1316] 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.

[1317] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for analyzing the user data and generating optimal advertising content, means for delivering the generated advertising content to users, means for tracking the performance of the advertising and sending reports to companies, an information collection device in the vehicle for collecting passenger behavior data, and means for generating and delivering advertisements based on the behavior data and geographic information, thereby making it possible to display optimized advertisements in real time by utilizing passenger behavior data and geographic information in the vehicle.

[1318] The "means for registering advertising materials" is a part of the system that provides an interface for companies to upload advertising materials (images, text, parts, etc.) to a management portal on a server.

[1319] "Means for collecting user data" refers to the part of the system that collects behavioral data (browsing history, search queries, clicked links, etc.) from the user's device while browsing web pages and sends it to the server.

[1320] The "means for analyzing the user data and generating optimal advertising content" refers to part of a system that analyzes collected user data using an AI model and generates optimal advertising content based on the user's interests and concerns.

[1321] The "means for delivering the generated advertisement content to the user" is a part of the system that delivers the generated advertisement content to the user's terminal and displays it at an appropriate time.

[1322] The "means for tracking the performance of the advertisement and sending reports to the company" is part of a system that tracks performance data such as the number of clicks on the advertisement, the length of time spent on the advertisement, and the engagement rate, and sends the analysis results to the company as a report.

[1323] "In-vehicle information collection device for collecting passenger behavior data" refers to a device for collecting passenger behavior data inside an autonomous vehicle, and includes devices such as smartphones and displays.

[1324] The "means for generating and delivering advertisements based on the behavioral data and geographic information" refers to part of a system that generates optimal advertisements based on collected passenger behavioral data and vehicle geographic information, and delivers them in real time to displays inside autonomous vehicles.

[1325] The present invention consists of several important components for implementing an "evolving advertising system" in an autonomous vehicle. Specific implementation methods and details of each process are described below.

[1326] 1. Registration of advertising materials (server)

[1327] The server provides a means for companies to register their advertising materials. Companies access the management portal and upload advertising materials such as images, text, and parts. This management portal provides an interface that makes it easy to add, edit, and delete advertising materials.

[1328] 2. Collection of user data (terminals, users, servers)

[1329] A dedicated app installed on a user's smartphone collects behavioral data while browsing web pages. This data is anonymized and sent to a server via passenger smartphones or information collection devices in autonomous vehicles. This allows companies to obtain information such as browsing history, search queries, and links clicked.

[1330] 3. Data analysis and advertisement generation (server)

[1331] The server analyzes the collected user data and uses an AI model to identify the user's interests and generate optimal ads based on them. For example, if an interest in technology is identified, the server creates optimal content by combining advertising materials that match those interests.

[1332] 4. Delivery and display of advertisements (servers and terminals)

[1333] The generated advertising content is delivered to the user's device, particularly to the information display in the autonomous vehicle. The server determines in real time which advertisement to display and when based on the user's behavioral data. This allows the system to display optimized advertisements in real time by utilizing passenger behavioral data and geographical information.

[1334] 5. Performance Tracking and Reporting (Server)

[1335] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of ad clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company as a report. Based on the report, the company can review its advertising strategy and identify areas for improvement.

[1336] Specific examples

[1337] For example, if a passenger browses a specific shopping site on their smartphone, the application will collect that data. The collected data will be anonymized and analyzed by an advertising server. Advertisements for products and services tailored to the passenger's interests will be displayed in real time on the display inside the self-driving vehicle.

[1338] Prompt Sentence Examples

[1339] "Generate ads that may be of interest to you based on the following data:

[1340] Browsing history: Electronics, latest gadgets

[1341] Search Query: smartphone reviews

[1342] Link clicked: New smartphone feature article

[1343] As a result, the present invention makes it possible to utilize passenger behavior data and geographic information in autonomous vehicles to display optimal advertisements in real time.

[1344] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1345] Step 1:

[1346] The device (user's smartphone) collects behavioral data when the user browses web pages, including browsing history, search queries, clicked links, etc. This behavioral data is collected in real time and temporarily stored on the device.

[1347] Input: User behavior data (browsing history, search queries, clicked links)

[1348] Output: Behavioral data temporarily stored on the device

[1349] Step 2:

[1350] The device anonymizes the collected behavioral data. Specifically, it removes personal identification information such as user ID and location information. This anonymization process protects privacy.

[1351] Input: Collected behavioral data

[1352] Output: Anonymized behavioral data

[1353] Step 3:

[1354] The device sends anonymized behavioral data to a server, where it is stored and used for subsequent analysis.

[1355] Input: Anonymized behavioral data

[1356] Output: Behavioral data stored on the server

[1357] Step 4:

[1358] The server analyzes the stored behavioral data and uses a generative AI model to identify the user's interests. Specifically, it uses the collected data to analyze which areas the user is particularly interested in. Based on this analysis, it generates optimal advertising content.

[1359] Input: Behavioral data stored on the server

[1360] Output: Optimal ad content

[1361] Step 5:

[1362] The server then transmits the generated advertising content to the information display inside the autonomous vehicle, which then displays the advertisement in real time according to specific timing and conditions.

[1363] Input: Optimal ad content

[1364] Output: Advertisement displayed on the screen

[1365] Step 6:

[1366] The server tracks the performance of the ad after it has been displayed, using display sensors and device feedback to collect data such as ad clicks, dwell time, and engagement rate.

[1367] Input: Performance data of ads displayed on the screen

[1368] Output: Collected performance data

[1369] Step 7:

[1370] The server analyzes the collected performance data and sends it to the company as a report, which details the effectiveness of the advertisement and areas for improvement, providing important information for the company to review its advertising strategy.

[1371] Input: Collected performance data

[1372] Output: Report sent to company

[1373] Specific behavior:

[1374] 1. When a user browses a specific shopping site, the device records this activity.

[1375] 2. The device removes the user ID from the recorded data and anonymizes it.

[1376] 3. The anonymized data is sent to a server via Wi-Fi or 4G / 5G networks.

[1377] 4. The server uses a generative AI model to analyze the data and determine that the user is interested in the latest gadgets.

[1378] 5. The server generates the most suitable advertisement (e.g., an advertisement for the latest gadget) and sends it to a display inside the autonomous vehicle.

[1379] 6. If a passenger clicks on an ad, their data is collected again.

[1380] 7. The server sends the collected data in the form of a report to the company to evaluate the effectiveness of the advertisement.

[1381] 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.

[1382] The "evolving advertising system" of this invention is an integrated system consisting of multiple components, and is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user behavior data and emotions. Below, we will explain the specific implementation method of this system and the details of each process.

[1383] 1. Registration of advertising materials (server)

[1384] First, a company uploads advertising materials (images, text, parts, etc.) to a management portal on the server. This management portal provides an interface that allows companies to easily add, edit, and delete advertising materials. For example, if a company is creating an advertisement for a new smartphone, it can enter and save the smartphone's image, description, catchphrase, etc. into the portal.

[1385] 2. Collection of user data (terminals, users, servers)

[1386] Your device collects user data while you browse web pages, including your browsing history, search queries, and links you click. If you read a tech article or search for "latest smartphones," that behavioral data is anonymized and sent to a server.

[1387] The server receives this data and stores it in a database. The collected data is used to analyze user interests and behavior patterns.

[1388] 3. Emotion data collection (emotion engine, device, user)

[1389] The user's device is equipped with a camera device. This camera is used to analyze the user's facial expressions in real time, and an emotion engine is activated to collect emotional data. For example, emotions such as interest, enthusiasm, and dissatisfaction can be recognized from the user's facial expressions while browsing a web page.

[1390] 4. Data analysis and advertisement generation (server)

[1391] The server uses an AI analysis module to analyze the collected user data and emotional data. Based on the analysis results, the AI ​​generates ads by combining optimal advertising materials. For example, if a user shows interest while reading a technology article, an ad highlighting the technical specifications of a new smartphone will be generated.

[1392] 5. Delivery and display of advertisements (servers and terminals)

[1393] The generated ad content is delivered to the user's device. The server determines in real time which ad to display and when based on the user's behavioral and emotional data. The generated ad is displayed when the user visits the web page again or when certain conditions are met.

[1394] For example, if a user frequently reads technology articles and shows an expression of interest, they will be shown a smartphone ad that highlights the technical details.

[1395] 6. Performance Tracking and Reporting (Server)

[1396] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company in the form of a report.

[1397] Companies can use the reports they receive to refine their advertising strategies and identify areas for improvement, allowing their ads to evolve accordingly based on user interests, behaviors, and emotions, maximizing their effectiveness.

[1398] Specific examples

[1399] As a concrete example, consider a company launching a new smartphone on the market. The company uploads images and text of the new product to a management portal. When users read technical articles or perform searches about the latest smartphones, the data is anonymized and sent to a server. In addition, the camera device captures the user's facial expressions as they read the articles, and emotional data is also collected.

[1400] Based on the data analyzed on the server and the emotional data, AI generates advertisements including technical details and delivers them to the user's device. When the user visits the web again, the advertisements emphasizing the technical details are displayed. Performance data on the displayed advertisements is then collected and sent to the company as a report.

[1401] In this way, the present invention provides a series of processes for optimizing advertising content for each user and taking into account their emotional responses, thereby maximizing advertising effectiveness.

[1402] The processing flow will be explained below.

[1403] Step 1:

[1404] A user views a web page.

[1405] A user opens a specific web page, enters a search query, clicks a link, etc. For example, a user browses a tech article and searches for a new smartphone.

[1406] Step 2:

[1407] The device collects user behavior data.

[1408] The device collects data such as your web browsing history, search queries, and links you click, all of which is collected in an anonymized and privacy-protecting manner.

[1409] Step 3:

[1410] The device sends the collected user data to the server.

[1411] The device then packets the collected user data and transmits it to the server using the appropriate communication protocol, such as the history of browsing technology articles or the search query "latest smartphones."

[1412] Step 4:

[1413] The server receives and stores the user data.

[1414] The server stores the received user data in a database, which stores each user's behavioral history in an anonymized form.

[1415] Step 5:

[1416] The device's built-in emotion engine analyzes the user's facial expressions.

[1417] Using the camera built into the user's device, the emotion engine captures and analyzes the user's facial expressions in real time, for example, recognizing whether the user is smiling or looking interested while reading an article.

[1418] Step 6:

[1419] The device transmits the collected emotion data to a server.

[1420] The device anonymizes the collected emotional data and transmits it to a server using an appropriate communication protocol.

[1421] Step 7:

[1422] The server receives and stores the emotion data.

[1423] The server stores the received emotion data in a database, where it is associated with behavioral data and used for analysis.

[1424] Step 8:

[1425] The server analyzes user data and emotional data.

[1426] The AI ​​analysis module on the server analyzes the stored user data and emotional data. The analysis uses machine learning algorithms and natural language processing technology. For example, if a user has a history of browsing technical content and looks interested, it can determine that they are interested in technology.

[1427] Step 9:

[1428] The server generates the best ad.

[1429] The server generates ads by combining optimal advertising materials based on user data and emotional data analyzed by AI, such as a smartphone ad that emphasizes technical details.

[1430] Step 10:

[1431] The server transmits the generated advertisement to the terminal.

[1432] The server then distributes the generated advertisement content to the user's device, appropriately packetizing it using a communication protocol and sending it to the device.

[1433] Step 11:

[1434] The device displays advertisements.

[1435] When the user visits the web page again, the device displays the advertisement received from the server, for example, an advertisement for a smartphone highlighting its technical details on the web page.

[1436] Step 12:

[1437] The device collects advertising performance data.

[1438] The device collects performance data, such as the clicks users make on ads they see and the amount of time they spend on them.

[1439] Step 13:

[1440] The terminal transmits the advertising performance data to the server.

[1441] The device sends the collected performance data to a server, which is also anonymized.

[1442] Step 14:

[1443] The server analyzes the ad performance data.

[1444] The server analyzes the received performance data and evaluates the effectiveness of the advertisement, such as the number of clicks and conversion rate.

[1445] Step 15:

[1446] The server generates the analysis results as a report and sends it to the company.

[1447] The server generates reports based on advertising performance data and provides feedback to businesses, giving them new perspectives to review and optimize their advertising strategies.

[1448] As described above, by following the specific processing flow from step 1 to step 15, it is possible to realize a system that generates advertisements optimized for each user and measures and optimizes their effectiveness.

[1449] Example 2

[1450] 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."

[1451] Conventional ad delivery systems generate and deliver ads based solely on user behavior data, but they are insufficient in adapting to the emotional responses of individual users. This results in ads not being optimized based on user emotions, and the effectiveness of ads is not maximized. Furthermore, the lack of analysis and feedback on advertising effectiveness makes it difficult for companies to quickly revise their advertising strategies.

[1452] 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.

[1453] In this invention, the server includes means for registering advertising materials, means for collecting user data, means for collecting user emotion data using a camera device, means for analyzing the user data and emotion data and generating optimal advertising content using a generative AI model, means for delivering the generated advertising content to user devices, and means for tracking the performance of the advertising and sending reports to companies. This makes it possible to optimize advertising based on user behavioral data and emotion data, and further evolve advertising content in real time, thereby maximizing advertising effectiveness.

[1454] "Advertising materials" are digital content such as images, text, and parts that companies use to create advertisements.

[1455] "User Data" refers to behavioral data such as a user's web page browsing history, search queries, and links clicked.

[1456] A "camera device" is a hardware device used to capture a user's facial expressions.

[1457] "Emotion data" refers to data relating to emotions such as interest, concern, enjoyment, and dissatisfaction recognized from the user's facial expression.

[1458] A "generative AI model" is an artificial intelligence algorithm used to generate optimal advertising content based on collected data.

[1459] "Advertising Content" refers to the combination of text, images, and parts of a specific advertisement delivered to a user.

[1460] "Advertising performance" refers to effectiveness measurement data such as the number of clicks, length of stay, and engagement rate when an ad is displayed.

[1461] A "report" is a document or digital file that is sent to a company and is the result of analyzing advertising performance data.

[1462] This invention is an integrated advertising system consisting of multiple components, which is primarily used by companies to register advertising materials and generate and deliver optimal advertisements based on user data and emotional data. Below, we will explain the specific implementation method of this system and the details of each process.

[1463] Registration of advertising materials (server)

[1464] The server provides a management portal where companies can upload advertising materials (images, text, parts, etc.). This portal has an interface that allows companies to easily add, edit, and delete advertising materials. When a company creates an advertisement for a new smartphone, it enters and saves an image of the smartphone, a description, a tagline, etc. into the portal. The hardware used is a web server (e.g., Apache, NGINX), and the software used is a CMS (content management system) such as WordPress or Joomla.

[1465] Collection of user data (terminal, user, server)

[1466] The device collects behavioral data (browsing history, search queries, clicked links, etc.) when the user browses web pages. For example, if a user reads a technology article or searches for "latest smartphones," this behavioral data is anonymized and sent to a server. The sent data is stored in the server's database (e.g., MySQL, PostgreSQL) and used to analyze user interests and behavioral patterns. Software used includes Google Analytics and Mixpanel.

[1467] Emotion data collection (emotion engine, device, user)

[1468] A camera installed on the user's device analyzes the user's facial expressions in real time, and an emotion engine is activated to collect emotional data. For example, emotions such as interest, enthusiasm, and dissatisfaction can be recognized from the user's facial expressions while browsing a web page. This is achieved using software such as TensorFlow and OpenCV. The collected emotional data is sent from the device to a server and stored in a database.

[1469] Data analysis and advertisement generation (server)

[1470] The server uses an AI analysis module to analyze the collected user data and sentiment data. Based on the analysis results, the AI ​​generates ads by combining optimal advertising materials. For example, for a user who shows interest while reading a technical article, an ad highlighting the technical specifications of a new smartphone will be generated. The AI ​​analysis module used is a proprietary model using PyTorch and TensorFlow.

[1471] Delivery and display of advertisements (servers and terminals)

[1472] The server delivers the generated advertising content to the user's device. Based on the user's behavioral and emotional data, the server determines in real time which advertisement to display and when. For example, if a user frequently reads technical articles and shows an expression that indicates interest, a smartphone advertisement emphasizing technical details will be displayed. Advertisements are delivered using an AdServer platform (e.g., Google AdServer).

[1473] Performance Tracking and Reporting (Server)

[1474] The server tracks the performance of each ad displayed. The server collects and analyzes data such as the number of ad clicks, time spent on the ad, and engagement rate. The results of this analysis are sent to the company as a report. Based on the reports, the company can review its advertising strategy and identify areas for improvement. Software such as Tableau and Google Data Studio are used for analysis and report generation.

[1475] Specific examples

[1476] As a specific example, when a company launches a new smartphone, it uploads images and text of the new product to a management portal. When a user reads a technical article or searches for "latest smartphone," the data is anonymized and sent to a server. A camera captures the user's facial expressions as they read the article, and emotional data is also collected. Based on the data analyzed on the server and the emotional data, AI generates an advertisement that includes technical details and delivers it to the user's device. When the user visits the web again, an advertisement emphasizing the technical details is displayed. Performance data on the displayed advertisement is then collected and sent to the company as a report. This allows the content of the advertisement to be optimized for each user, maximizing its effectiveness.

[1477] Prompt Sentence Examples

[1478] Below are some example prompts to input to a generative AI model:

[1479] "Upload new smartphone ad materials to the management portal and generate optimal ads based on user browsing and sentiment data."

[1480] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1481] System program processing flow

[1482] Step 1: Registering advertising materials (server)

[1483] Input: Advertising materials provided by companies (images, text, parts)

[1484] Specific operation: A company accesses the server's management portal and uploads new advertising materials, which inputs the images, text, and parts of the advertisement into the portal and sends them to the server.

[1485] Data processing: The server receives the uploaded advertising material and converts it into the required format.

[1486] Output: Save the converted advertising material in the database.

[1487] Step 2: Collecting user data (device, user, server)

[1488] Input: User's webpage browsing history, search queries, and clicked links

[1489] Specific operations: The device collects behavioral data when the user browses web pages.

[1490] Data processing: The device anonymizes the collected data and sends it to a server using a secure protocol.

[1491] Output: The server stores the received data in a database.

[1492] Step 3: Collecting emotion data (emotion engine, device, user)

[1493] Input: User's facial expression data

[1494] Specific operation: The camera on the user's device captures facial expressions, which are then analyzed in real time by an emotion engine (e.g., TensorFlow).

[1495] Data processing: The analyzed emotion data is sent from the device to the server.

[1496] Output: The server stores the emotion data in a database.

[1497] Step 4: Data analysis and ad generation (server)

[1498] Input: User data and emotion data

[1499] Specific operation: The server's AI analysis module performs analysis based on collected user data and emotional data.

[1500] Data processing: An AI analysis module (e.g., PyTorch) analyzes the data and combines the optimal advertising materials based on the results.

[1501] Output: The generated advertisement content is saved in the database.

[1502] Step 5: Delivery and display of advertisements (server / terminal)

[1503] Input: Generated ad content

[1504] Specific operation: The server delivers advertisements to the user's device at the appropriate time.

[1505] Data processing: Delivering advertisements using an advertising platform (e.g., Google AdServer).

[1506] Output: The user's device displays the delivered ad.

[1507] Step 6: Performance Tracking and Reporting (Server)

[1508] Input: Performance data such as ad clicks, visit duration, and engagement rate

[1509] What it does: The server tracks the performance of the ads in real time.

[1510] Data processing: Analyze performance data and generate reports based on the results.

[1511] Output: Send the generated report to the company.

[1512] (Application example 2)

[1513] 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."

[1514] Conventional advertising systems personalize ads based on user behavior data, but they face the challenge of being unable to take into account user emotions and instantaneous reactions. This often results in insufficient advertising effectiveness. Another issue is that even if advertising performance data is collected, there is a lack of adequate means to properly analyze it and reflect it in advertising strategies.

[1515] 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 registering advertising materials, means for collecting user data and emotion data, means for analyzing the user data and emotion data and generating optimal advertising content, means for evolving the advertising content based on prompt text using a generative AI model, means for delivering the generated advertising content to users, means for collecting emotion data, and means for tracking the performance of the advertising and sending reports to companies. This makes it possible to optimize advertising in real time based on user behavioral data and emotion data, maximizing advertising effectiveness.

[1516] "Advertising materials" are elements such as images, text, video, and audio that make up an advertisement.

[1517] "User Data" refers to your web page browsing history, search queries, links you click, and other online behavior data.

[1518] "Emotional data" refers to data related to emotions such as interest, concern, enjoyment, and dissatisfaction that can be read from the user's facial expressions and voice.

[1519] The "AI analysis module" is an artificial intelligence-based analysis system that analyzes user data and emotional data to generate optimal advertising content.

[1520] A "generative AI model" is an artificial intelligence-based generation system that evolves advertising content based on a given prompt.

[1521] A "prompt" is an instruction given to a generative AI model to evolve advertising content.

[1522] "Performance data" refers to data used to evaluate the effectiveness of advertising, such as the number of clicks, duration, and engagement rate after an advertisement is displayed.

[1523] A "report" is a report that analyzes advertising performance data and summarizes the results.

[1524] "Delivery" means displaying the generated advertising content to the user.

[1525] The "evolving advertising system" of the present invention is an integrated system that includes a management portal for registering advertising materials, an AI analysis module for collecting and analyzing user data and emotional data, a generative AI model, an advertising distribution system, a performance data tracking system, and a report generation system.

[1526] 1. Registration of advertising materials

[1527] Companies use the management portal to register advertising materials. Specifically, this includes images, text, videos, etc. to be used in advertisements. These materials are stored on the server and used in later steps. The management portal is designed so that companies can easily add, edit, and delete advertising materials.

[1528] 2. Collection of User Data

[1529] While a user is browsing a web page, their device collects user data, including browsing history, search queries, clicked links, etc. This data is anonymized and sent to a server.

[1530] 3. Collecting Emotional Data

[1531] The user's device is equipped with a camera device that captures the user's facial expressions. The emotion engine analyzes the facial expressions in real time and collects emotional data such as interest, concern, enjoyment, and dissatisfaction. This data is also anonymized and sent to the server.

[1532] 4. Data analysis and ad generation

[1533] The AI ​​analysis module on the server analyzes user data and emotional data. Based on the analysis results, the generative AI model generates ads by combining optimal advertising materials. This creates personalized ads that match the user's interests and emotions.

[1534] 5. Delivery and display of advertisements

[1535] The generated ad content is delivered to the user's device. The server displays the ad at the optimal time based on the user's behavioral and emotional data, thereby maximizing the effectiveness of the ad.

[1536] 6. Performance Tracking and Reporting

[1537] Each time an ad is displayed, its performance is tracked. The server collects and analyzes data such as the number of clicks on the ad, the time spent on the ad, and the engagement rate. The results of this analysis are sent to the company as a report, which the company can use to revise its advertising strategy.

[1538] Hardware and software used

[1539] Smartphone: The device on which the application is installed

[1540] Camera device: Captures the user's facial expressions

[1541] Server: Analyzes data, generates and delivers ads

[1542] AI analysis module: Artificial intelligence for analyzing collected data

[1543] Generative AI model: Artificial intelligence for evolving ad content based on prompts

[1544] Database: Stores user data and emotion data

[1545] Specific examples

[1546] For example, if a user is browsing a movie-related webpage and their facial expressions indicate interest, they can be shown a trailer ad for a new movie. Furthermore, the performance data of the ad can be analyzed and feedback on advertising strategies can be provided based on the results.

[1547] Prompt Sentence Examples

[1548] "When a user is searching for movie-related information, generate new movie trailer ads. Capture the user's facial expressions that express interest, and use that emotional data to display the most appropriate ad."

[1549] In this way, the present invention provides a system that uses user behavioral data and emotional data to optimize advertisements in real time and maximize advertising effectiveness.

[1550] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1551] Step 1:

[1552] The device collects user data, including browsing history, search queries, and clicked links. This data is used to understand user behavior patterns. Input data is user data, and output data is user data sent to a server for analysis.

[1553] Step 2:

[1554] The device uses a camera device to collect user emotional data. The collected emotional data is used to analyze emotions such as interest, concern, enjoyment, and dissatisfaction from the user's facial expressions. The input is facial expression data captured in real time, and the output is emotional data analyzed by the emotion engine.

[1555] Step 3:

[1556] The server receives the user data and emotion data collected in step 1 and step 2 and stores them in a database, thereby forming a consistent dataset of user behavior and emotion. The input data are the user data and emotion data, and the output data is the dataset stored in the database.

[1557] Step 4:

[1558] The server's AI analysis module analyzes the user data and emotional data stored in the database. The analysis reveals the user's behavioral patterns and emotional characteristics. The input data is the data stored in the database, and the output data is the analysis results.

[1559] Step 5:

[1560] The server's generative AI model selects the optimal advertising materials based on the analysis results and generates the advertisement. Specifically, it automatically generates relevant advertising content based on prompts that are likely to interest the user. The input data are the analysis results and prompts, and the output data is the generated advertisement.

[1561] Step 6:

[1562] The server delivers the generated advertisement to the user's device. The timing of the advertisement delivery is optimized based on real-time user data and emotion data. The input data is the generated advertisement, and the output data is the advertisement displayed on the device.

[1563] Step 7:

[1564] The device collects performance data as a result of the advertisement being displayed to the user, including the number of clicks on the advertisement, the duration of the visit, the engagement rate, etc. The input data is the user's response to the advertisement, and the output data is the performance data.

[1565] Step 8:

[1566] The server analyzes the performance data collected in step 7 and generates a report for the company. The report is used to evaluate the effectiveness of the advertisement and to suggest improvements to the advertisement strategy. The input data is the performance data and the output data is the report sent to the company.

[1567] Through each step, ads are created that are optimized in real time based on user behavior and emotions, maximizing their effectiveness.

[1568] 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.

[1569] 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.

[1570] 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.

[1571] 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.

[1572] 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.

[1573] 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.

[1574] 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).

[1575] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1576] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1577] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1578] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1579] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1580] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1581] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1582] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1583] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1584] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1585] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1586] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1587] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1588] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1589] The following is further disclosed regarding the above embodiment.

[1590] (Claim 1)

[1591] a means for registering advertising materials;

[1592] the means by which user data is collected;

[1593] A means for analyzing the user data and generating optimal advertising content;

[1594] means for delivering the generated advertising content to users;

[1595] means for tracking the performance of said advertisements and sending reports to the business;

[1596] A system including:

[1597] (Claim 2)

[1598] 10. The system of claim 1, further comprising means for evolving advertising content in real time based on user behavior data.

[1599] (Claim 3)

[1600] 10. The system of claim 1, further comprising means for analyzing advertising performance data and providing advertising strategy feedback to the business.

[1601] "Example 1"

[1602] (Claim 1)

[1603] a means for registering advertising materials;

[1604] the means by which user data is collected;

[1605] means for anonymizing the user data and transmitting it to a server;

[1606] A means for analyzing the user data collected by the server using an AI model to generate optimal advertising content;

[1607] means for delivering the generated advertising content to a user terminal;

[1608] means for tracking and storing performance data of said advertisements when they are displayed in a database;

[1609] A means of analyzing the collected performance data and sending reports to the company;

[1610] A system including:

[1611] (Claim 2)

[1612] 10. The system of claim 1, further comprising means for evolving advertising content in real time based on user behavior data.

[1613] (Claim 3)

[1614] 10. The system of claim 1, further comprising means for analyzing advertising performance data and providing advertising strategy feedback to the business.

[1615] "Application Example 1"

[1616] Claiming a new invention

[1617] (Claim 1)

[1618] a means for registering advertising materials;

[1619] the means by which user data is collected;

[1620] A means for analyzing the user data and generating optimal advertising content;

[1621] means for delivering the generated advertising content to users;

[1622] means for tracking the performance of said advertisements and sending reports to the business;

[1623] an in-vehicle information collection device for collecting passenger behavior data;

[1624] means for generating and delivering advertisements based on the behavioral data and geographic information;

[1625] A system including:

[1626] (Claim 2)

[1627] 10. The system of claim 1, further comprising means for displaying the advertisement in real time using an information display within the vehicle.

[1628] (Claim 3)

[1629] 10. The system of claim 1, further comprising means for analyzing performance data of advertising presentation using in-vehicle information displays and providing feedback on advertising strategies.

[1630] "Example 2: Combining Emotion Engines"

[1631] (Claim 1)

[1632] a means for registering advertising materials;

[1633] the means by which user data is collected;

[1634] means for anonymizing said user data and transmitting it to a server;

[1635] means for collecting user emotion data using a camera device;

[1636] means for collecting the emotion data and transmitting it to a server;

[1637] A means for analyzing the user data and emotion data and generating optimal advertising content using a generative AI model;

[1638] means for delivering the generated advertising content to a user terminal;

[1639] means for displaying the distributed advertisement;

[1640] means for tracking the performance of said advertisements and sending reports to the business;

[1641] A system including:

[1642] (Claim 2)

[1643] 10. The system of claim 1, further comprising means for evolving advertising content in real time based on user behavioral and emotional data.

[1644] (Claim 3)

[1645] 10. The system of claim 1, further comprising means for analyzing advertising performance data and providing advertising strategy feedback to the business.

[1646] "Application example 2 when combining emotion engines"

[1647] (Claim 1)

[1648] a means for registering advertising materials;

[1649] the means by which user data is collected;

[1650] means for analyzing the user data and emotion data and generating optimal advertising content;

[1651] means for delivering the generated advertising content to users;

[1652] means for tracking the performance of said advertisements and sending reports to the business;

[1653] a means for collecting emotion data;

[1654] A system including:

[1655] (Claim 2)

[1656] 10. The system of claim 1, further comprising means for evolving advertising content in real time based on user behavioral and emotional data.

[1657] (Claim 3)

[1658] 10. The system of claim 1, further comprising: means for analyzing advertising performance data to provide advertising strategy feedback to the business; and means for evolving advertising content based on prompts using a generative AI model. [Explanation of symbols]

[1659] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for registering advertising materials; the means by which user data is collected; A means for analyzing the user data and generating optimal advertising content; means for delivering the generated advertising content to users; means for tracking the performance of said advertisements and sending reports to the business; A system including:

2. The system of claim 1 , further comprising means for evolving advertising content in real time based on user behavior data.

3. 10. The system of claim 1, further comprising means for analyzing advertising performance data and providing advertising strategy feedback to businesses.

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