system

Abstract

We provide the system. [Solution] Means of collecting local information, A means of generating engaging content from regional information collected using generative artificial intelligence, Means for collecting and analyzing user profile data, A means of suggesting customized travel plans based on user profiles, To promote monetization, a means of booking and managing travel plans, A service integration method that notifies users of local service activities and event information, A system that includes this.

Description

Technical Field

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

Background Art

[0002] [[ID=ll]] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In regional activation, although there is a need to effectively appeal the charm of a region and efficiently achieve customer attraction and monetization, many regions have not fully utilized their potential charm. In addition, there is a lack of means to appropriately collect regional information and effectively deliver it to users, so there is a problem that it is difficult to approach target users. Furthermore, since the optimization and monetization activities of advertising campaigns are not fully planned, the economic effect of the entire region cannot be enhanced. A new approach is needed to solve these problems.

Means for Solving the Problems

[0005] This invention provides a system that includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for proposing customized travel plans based on user profiles, means for booking and managing travel plans to promote monetization, and means for service integration to notify users of local service activities and event information. This enables a series of processes that effectively appeal to the region's attractions, attract user interest, and lead to monetization. Furthermore, by optimizing the effectiveness of advertising campaigns and promotions, it is possible to enhance the overall economic impact of the region.

[0006] "Local information" refers to various types of information about a particular region, such as tourist attractions, food culture, history, and weather.

[0007] "Generative artificial intelligence" refers to artificial intelligence that generates new content (e.g., text, images, videos) based on given data.

[0008] "User profile data" refers to data that shows the individual characteristics and preferences of a user, such as their interests, behavioral history, and location information.

[0009] A "customized travel plan" refers to a travel itinerary or plan that is individually proposed according to the user's specific interests and requests.

[0010] "Means for promoting monetization" refers to methods of generating revenue by creating pricing plans for travel packages, tours, accommodations, local restaurants, etc., and having users book them.

[0011] "Service integration methods" refer to methods for notifying users of local volunteer activities and event information, thereby promoting regional revitalization and user engagement. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a tagged processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, a tagged RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, a tagged storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0018] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] The present invention provides a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue. The specific embodiments described herein are configured as follows.

[0034] System Configuration

[0035] This system consists of the following main components:

[0036] 1. Server (Central Management System)

[0037] 2. Device (user's smartphone or computer)

[0038] 3. User

[0039] server

[0040] The server is a centralized management system with multiple functions. This server includes the following functions:

[0041] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0042] Content Generation: Based on collected local information, the server uses generative artificial intelligence to generate engaging content such as text, images, and videos. This content is automatically posted to social media and websites for widespread sharing.

[0043] User Profile Management: The server collects information such as each user's interests, behavioral history, and location, and uses this information to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[0044] terminal

[0045] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[0046] Data collection: The device records the user's search history, social media activity, etc., and sends it to the server.

[0047] Content display: The device displays content sent from the server, informing the user about the local attractions.

[0048] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[0049] user

[0050] Users are individuals or organizations that utilize the system and perform the following actions:

[0051] Providing interest information: Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0052] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[0053] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[0054] Specific usage examples

[0055] For example, suppose a user is interested in natural landscapes and hot springs. The user's device identifies these interests from their past search history and social media activity, and sends this data to the server. The server then gathers information on appropriate hot spring resorts in the user's region, tailored to their profile, and uses generative AI to create compelling descriptions and images. Next, the server posts this content to social media and notifies the user.

[0056] Users receive the notification and, if interested, check the suggested travel plan on their device. The plan includes information on how to access the hot spring resort, accommodations, and local activities. If the user is satisfied with the plan, they proceed with the booking process through their device. This booking data is aggregated on a server and automatically notified to the relevant service providers.

[0057] Furthermore, users can utilize a dashboard that visualizes their contribution to the local community during their activities, allowing them to truly understand how much their efforts are benefiting the region. This encourages users to develop a greater interest in and involvement with the local community.

[0058] The above describes a specific embodiment of the present invention. This system makes it possible to effectively promote the appeal of a region, attract user interest, and even generate revenue.

[0059] The following describes the processing flow.

[0060] Step 1:

[0061] The server collects local information. This local information includes tourist attractions, food culture, historical background, and weather information. Specifically, the server uses APIs to retrieve this information from the internet and databases, and stores the collected information in the database.

[0062] Step 2:

[0063] The server generates engaging content from local information collected using generative artificial intelligence. It uses text generation AI to create introductory articles about the region and image generation AI to create visuals of tourist attractions. The generated content is then posted to social media and websites.

[0064] Step 3:

[0065] The device collects user activity data. For example, the device records the user's search history, location information, and social media activity, and sends this data to a server. This data is used for subsequent analysis.

[0066] Step 4:

[0067] The server analyzes collected user activity data and generates user profiles. It uses clustering algorithms to classify user interests and create individual profiles. Based on these profiles, it is ready to suggest the most relevant local information to the user.

[0068] Step 5:

[0069] The server generates a customized travel plan based on the user's profile. The server selects tourist attractions, accommodations, and event information that match the user's interests, and uses generative artificial intelligence to create an attractive itinerary. The user is then notified of the created travel plan.

[0070] Step 6:

[0071] The device displays suggested travel plans to the user. The user can review the details of the travel plans through the device and select the plan that best suits their needs. If the user is satisfied with the travel plan, they can proceed with the booking process.

[0072] Step 7:

[0073] The user selects a suggested travel plan and proceeds with the booking process. This confirms the travel plan, and the user's booking data is sent to the server. The server then notifies the relevant service providers (e.g., accommodation, tour guides) of the booking information.

[0074] Step 8:

[0075] The server notifies users of local events and activities through SBG services. It updates a community contribution dashboard via API integration, visually showing users their level of community contribution. This provides users with motivation to participate in further activities and events.

[0076] The above outlines the specific processing flow of this system. Through these steps, it is possible to effectively communicate the appeal of the region, attract user interest, and ultimately contribute to increasing the region's revenue.

[0077] (Example 1)

[0078] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0079] Conventional regional information systems had limited information gathering and analysis capabilities, and did not adequately customize information based on user interests. As a result, it was difficult for users to fully understand and develop an interest in the region's attractions. Furthermore, efficient suggestions were not provided for travel plan generation and booking, making monetization a challenge.

[0080] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0081] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for proposing customized travel plans based on user profiles, means for booking and managing travel plans to promote monetization, means for notifying users of local service activities and event information, means for generating content based on prompt sentences using a generative artificial intelligence model, and means for classifying user interests using a clustering algorithm. This makes it possible to provide users with more personalized information and engaging travel plans.

[0082] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[0083] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates content such as text, images, and videos based on collected data.

[0084] "User profile data" refers to data such as a user's interests, behavioral history, and location information.

[0085] A "clustering algorithm" refers to a statistical method for grouping similar user data.

[0086] A "prompt message" refers to text input used to instruct a generative artificial intelligence system to generate specific information.

[0087] A "travel plan" refers to a detailed plan for a trip to a specific region.

[0088] "Monetization" refers to the process of generating profit from the services or information provided.

[0089] "Community service activities" refer to public services or volunteer activities carried out in a specific area.

[0090] "Event information" refers to detailed information about events held in a specific region.

[0091] This invention is a system that effectively promotes the appeal of a region, attracts user interest, and facilitates monetization. The specific form of implementing this system is configured as follows.

[0092] System Configuration

[0093] This system consists of the following main components:

[0094] 1. Server (Central Management System)

[0095] 2. Device (user's smartphone or computer)

[0096] 3. User

[0097] server

[0098] A server is a centralized management system with multiple functions. The server has the following functions:

[0099] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0100] Specific example: The server retrieves information about "AA Hot Spring Resort" from a tourism information API and saves it to a database.

[0101] Content generation using generative artificial intelligence (AI): Based on collected regional information, the server uses generative AI (e.g., OpenAI®, GPT-4®) to generate engaging content such as text, images, and videos. The generated content is automatically posted to social media and websites.

[0102] Example of a prompt: The server sends a prompt to the AI ​​generating the following: "Please introduce a region famous for its hot springs. Please include the region's history, the characteristics of the hot springs, and nearby tourist attractions." The AI ​​then generates a detailed introduction.

[0103] User Profile Management: The server collects each user's interests, behavioral history, location information, etc., and generates and analyzes user profiles based on this data. A clustering algorithm is used to classify user interests.

[0104] Specific example: The device sends search history such as "hot springs" and "hiking" to the server, and the server clusters user profiles as "users interested in nature and hot springs."

[0105] Travel plan suggestion: The server generates a customized travel plan based on the user profile and sends it to the device.

[0106] Specific example: The server generates a "travel plan to a hot spring resort" and sends it to the terminal.

[0107] Travel plan booking and management: The server books and manages the travel plans selected by the user. Booking data is automatically notified to the relevant service provider.

[0108] Specific example: Users use their devices to make reservations for accommodations and activities, and the server aggregates the reservation information and notifies the accommodations.

[0109] Notification function: The server notifies users of information about local service activities and events.

[0110] Specific example: A server collects information about local events and notifies users.

[0111] terminal

[0112] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. Its main functions are as follows:

[0113] Data collection: The device records the user's search history and social media activity and sends it to the server.

[0114] Specific example: The device monitors the user's past social media activity and sends topics of interest to the server.

[0115] Content display: The device displays content sent from the server, providing users with information about the local area.

[0116] Specific example: A message titled "Introduction to a new hot spring resort" appears on the user's smartphone, and the user views the details.

[0117] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[0118] Specific example: A user checks their travel plan on their smartphone and completes the booking process.

[0119] user

[0120] Users are individuals or organizations that utilize the system and perform the following actions:

[0121] Providing interest information: Users provide the system with their search history and preferences to receive more personalized suggestions.

[0122] Specific example: A user searches for terms like "hot springs" or "natural scenery," and their search history is saved on the server.

[0123] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[0124] Specific example: A user views a "hot spring resort introduction" on their smartphone.

[0125] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[0126] Specific example: A user uses their device to check travel plans and book accommodations.

[0127] The above describes a specific embodiment of the present invention. This system allows users to receive attractive local information and easily book customized travel plans. It also enables effective promotion of local attractions and facilitates monetization.

[0128] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0129] Step 1:

[0130] The server collects local information. Specifically, it periodically retrieves information such as tourist spots, food culture, history, and weather related to the region from the internet and dedicated databases using APIs, and stores it in the database.

[0131] Input: Request from the Tourism Information API

[0132] Output: Latest regional information from the database

[0133] Example of operation: The server requests information about "AA Hot Spring Resort" from the tourism information API and saves the retrieved data to the database.

[0134] Step 2:

[0135] The device records the user's search history and social media activity and sends it to the server. This allows the server to collect information about the user's interests, behavioral history, and location.

[0136] Input: User's search history, social media activity data

[0137] Output: Data stored in the user database on the server.

[0138] Example of operation: The device records the user's search history, such as "hot springs" and "natural scenery," and sends it to the server.

[0139] Step 3:

[0140] The server generates and analyzes user profiles using a clustering algorithm based on the collected user data.

[0141] Input: User's search history, social media activity data

[0142] Output: Classified user profile data

[0143] Example of operation: The server uses a clustering algorithm to classify users as "interested in nature and hot springs."

[0144] Step 4:

[0145] The server uses generative AI to generate engaging content based on collected local information and user profiles. Prompts are used to prompt the AI ​​to generate specific information.

[0146] Input: Regional information, user profile data, prompt text

[0147] Output: Generated content such as text, images, and videos.

[0148] Example of operation: The server generates content using the following prompt for the AI: "Please introduce a region famous for its hot springs. Please describe the region's history, the characteristics of the hot springs, and nearby tourist attractions."

[0149] Step 5:

[0150] The server automatically posts the generated content to social media and websites and notifies relevant users.

[0151] Input: Generated content

[0152] Output: Posts to social media and websites, notifications to users

[0153] Example of operation: The server posts "introductions to hot spring resorts" to Facebook and Twitter, and sends notifications to interested users.

[0154] Step 6:

[0155] The device receives notifications sent from the server and displays them to the user. The user views the content via a smartphone or computer.

[0156] Input: Notification from server

[0157] Output: Content displayed on the user's device

[0158] Example of operation: An advertisement for a new hot spring resort is displayed on the user's smartphone, and the user views the content in detail.

[0159] Step 7:

[0160] The server generates a customized travel plan based on the user's profile and sends it to the device. The user reviews the plan on the device and proceeds with the booking process if they like it.

[0161] Input: User profile data

[0162] Output: Generated customized travel plan

[0163] Example of operation: The server generates a "travel plan to a hot spring resort" and sends it to the terminal. The user checks the plan on the terminal and makes reservations for accommodations and activities.

[0164] Step 8:

[0165] The terminal sends the reservation data entered by the user to the server, and the server completes the reservation process. The server aggregates this data and notifies the relevant service providers.

[0166] Input: User's reservation data

[0167] Output: Booking completion data, notification to service provider

[0168] Example of operation: A user makes a reservation for accommodation using their device, that information is sent to the server, and the server notifies the accommodation.

[0169] The above outlines the specific processing steps and operation of this system. This system allows users to receive attractive local information, easily book customized travel plans, effectively promote the region's appeal, and facilitate monetization.

[0170] (Application Example 1)

[0171] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0172] In systems designed to effectively promote local attractions, attract user interest, and generate revenue, there is a lack of means to provide in-store promotions and special offers tailored to user interests. Furthermore, it is difficult to effectively classify user profiles in detail based on collected data and propose personalized travel plans and event information. There is also a need for a system to analyze and optimize the effectiveness of these promotions and suggestions.

[0173] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0174] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for proposing customized travel plans based on user profiles, means for booking and managing travel plans to promote monetization, means for service integration to notify users of local service activities and event information, and means for providing promotional information for physical stores and displaying special offers and coupons based on user interests. This enables effective promotion of the region's attractions, provides personalized information to users, promotes purchases at physical stores, and proposes travel plans based on user interests.

[0175] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[0176] "Generative artificial intelligence" refers to artificial intelligence that has algorithms to generate content such as text, images, and videos from input data.

[0177] "User profile data" refers to data that shows individual information about a user, such as their interests, behavioral history, and location information.

[0178] A "customized travel plan" is a travel schedule that is personalized and provided to the user based on their user profile data.

[0179] "Means for booking and managing travel plans" refers to system elements that allow users to book suggested travel plans and manage them afterward.

[0180] A "service linkage system" is a linkage system used to notify users of information about local community service activities and events.

[0181] "In-store promotional information" refers to information such as discounts, coupons, and special offers offered at physical stores.

[0182] Modes for carrying out the invention

[0183] This invention provides a system that effectively promotes the appeal of a region, attracts user interest, and leads to monetization. This system mainly consists of three components: a server, terminals, and users.

[0184] System Configuration

[0185] server

[0186] The server is a central management system with the following main functions. This server includes the following functions:

[0187] 1. Gathering local information

[0188] The server uses APIs (for example, travel data APIs) to periodically collect information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. This information is used as input data for generative artificial intelligence (AI), which will be discussed later.

[0189] 2. Content Generation

[0190] The server uses generative artificial intelligence (e.g., GPT-4) to generate engaging content such as text, images, and videos based on collected regional information. For example, it can generate content based on prompts such as, "Please create text and images to promote the charm of the region. Regional information: Ohori Park, a famous tourist spot in Fukuoka City, offers beautiful Japanese gardens and boating. The park also has many stylish cafes and attracts many tourists on weekends. Please also introduce mentaiko, a famous Fukuoka specialty."

[0191] 3. Database Management

[0192] The server uses relational databases such as MySQL (registered trademark) to manage generated content and user information.

[0193] 4. User Profile Management and Analysis

[0194] Using machine learning algorithms (for example, Scikit-learn's clustering algorithm), we generate and analyze user profiles based on their interests and behavioral history, and then provide personalized suggestions.

[0195] 5. Linked to physical stores

[0196] Based on user interests, the system displays promotional information, special offers, and coupons for physical stores (e.g., restaurants, souvenir shops, etc.).

[0197] terminal

[0198] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[0199] 1. Data Collection

[0200] The device records the user's search history, social media activity, etc., and sends it to the server.

[0201] 2. Content Display

[0202] The system displays content and promotional information sent from the server, informing users about the region's attractions. It also offers special offers and coupons.

[0203] 3. Reservation function

[0204] Make reservations for the proposed travel plans and events.

[0205] user

[0206] Users are individuals or organizations that utilize the system and perform the following actions:

[0207] 1. Providing information of interest

[0208] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0209] 2. Viewing content

[0210] Users view suggested content through their devices and deepen their interest in the local area.

[0211] 3. Deciding on and booking your travel plan.

[0212] Users review the suggested travel plans and book the one they like. They can also take advantage of local store information and special offers.

[0213] This system will effectively promote the attractions of the region, provide users with personalized information, and enable increased sales at physical stores as well as the suggestion of travel plans based on users' interests.

[0214] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0215] Step 1:

[0216] The server uses APIs to collect local information from the internet and dedicated databases. The input to this process is requests obtained from the API, and the output is information related to the region, such as tourist attractions, food culture, history, and weather. This data is then input into the generating AI in the next step.

[0217] Step 2:

[0218] The server generates content using generative artificial intelligence (e.g., GPT-4) based on collected regional information. The input to this process is regional information and prompt text, while the output is engaging content such as generated text, images, and videos. Specifically, prompt text is used to instruct the AI, which then generates the content.

[0219] Step 3:

[0220] The server saves the generated content to a relational database such as MySQL. The input to this process is the generated content, and the output is the content data stored in the database. Specifically, it creates an SQL query and inserts the content data into the database.

[0221] Step 4:

[0222] The device records the user's search history and social media activity and sends it to the server. The input to this process is the user's operation log, and the output is user data sent to the server. Specifically, it collects data locally and then makes an API request to send it to the server.

[0223] Step 5:

[0224] The server manages user profiles and analyzes user interests using machine learning algorithms (e.g., Scikit-learn). The input to this process is user data, and the output is clustered user profiles. Specifically, it applies a clustering algorithm to classify users according to their interests.

[0225] Step 6:

[0226] The server generates travel plans and event information based on user interests and sends them to the device. The input to this process is clustered user profiles and generated content, while the output is customized travel plans and event information. Specifically, it selects appropriate information based on the user profile and sends push notifications or displays them on the device.

[0227] Step 7:

[0228] The terminal displays customized travel plans and event information to the user, and provides promotional information, special offers, and coupons for physical stores. The input for this process is information sent from the server, and the output is the displayed travel plan and coupon information. Specifically, the system displays the information appropriately on the user interface, making it easily accessible to the user.

[0229] Step 8:

[0230] Users review the displayed customized travel plans and in-store promotional information, and make reservations or use coupons as needed. The input for this process is the information displayed on the terminal, and the output is reservation data and coupon usage history. Specific actions include reviewing travel plan details and entering coupon codes.

[0231] Step 9:

[0232] The server aggregates user reservation history and coupon usage data to optimize effective advertising campaigns and promotional strategies. The input to this process is reservation data and coupon usage history, while the output is optimized advertising campaign and promotional data. Specifically, it performs data analysis and selects the most suitable strategies.

[0233] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0234] This invention combines a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue with an emotion engine that recognizes user emotions. The specific embodiments described herein are configured as follows.

[0235] System Configuration

[0236] This system consists of the following main components:

[0237] 1. Server (Central Management System)

[0238] 2. Device (user's smartphone or computer)

[0239] 3. User

[0240] 4. Emotional Engine

[0241] server

[0242] The server is a centralized management system with multiple functions. This server includes the following functions:

[0243] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0244] Content Generation: Based on collected local information, the server uses generative artificial intelligence to generate engaging content such as text, images, and videos. This content is then posted to social media and websites.

[0245] User Profile Management: The server collects information such as each user's interests, behavioral history, and location, and uses this information to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[0246] terminal

[0247] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[0248] Data collection: The device records the user's search history, social media activity, etc., and sends it to the server.

[0249] Content display: The device displays content sent from the server, informing the user about the local attractions.

[0250] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[0251] user

[0252] Users are individuals or organizations that utilize the system and perform the following actions:

[0253] Providing interest information: Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0254] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[0255] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[0256] Emotional Engine

[0257] The emotion engine is a system component that recognizes user emotions and adjusts content and suggestions based on those emotions. This emotion engine includes the following features:

[0258] Emotion Recognition: The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions and reflects the results in the user profile.

[0259] Real-time adjustment: The emotion engine monitors user emotions in real time and dynamically changes content to improve the user's customer experience.

[0260] Specific usage examples

[0261] For example, suppose a user is interested in natural landscapes and hot springs. The user's device identifies these interests from their past search history and social media activity, and sends this data to the server. The server then gathers information on appropriate hot spring resorts in the user's region, tailored to their profile, and uses generative AI to create compelling descriptions and images. Next, the server posts this content to social media and notifies the user.

[0262] Users receive the notification and, if interested, check the suggested travel plan on their device. The plan includes information on how to access the hot spring resort, accommodations, and local activities. If the user is satisfied with the plan, they proceed with the booking process through their device. This booking data is aggregated on a server and automatically notified to the relevant service providers.

[0263] In this process, the emotion engine recognizes the user's emotions from their facial expressions and voice, and adjusts the suggestions according to the user's emotional state. For example, if the user is excited about a particular plan, additional information is provided to emphasize that plan. On the other hand, if the user looks dissatisfied, a different suggestion is presented to increase their satisfaction.

[0264] Furthermore, users can utilize a dashboard that visualizes their contribution to the local community during their activities, allowing them to truly understand how much their efforts are benefiting the region. This encourages users to develop a greater interest in and involvement with the local community.

[0265] The above describes specific embodiments of the present invention. This system makes it possible to effectively promote the appeal of a region, attract user interest, and even generate revenue. Furthermore, by combining it with an emotion engine, it is possible to further personalize the user experience and improve customer satisfaction.

[0266] The following describes the processing flow.

[0267] Step 1:

[0268] The server collects local information. It uses APIs to retrieve information on tourist attractions, food culture, historical background, weather, etc., and stores it in a database. Specifically, it utilizes databases from local tourism bureaus and public data resources.

[0269] Step 2:

[0270] The server generates engaging content from collected local information using generative artificial intelligence. It uses text generation AI to create articles introducing tourist destinations and image generation AI to generate visuals of tourist spots. The generated content is automatically posted to social media and official local websites.

[0271] Step 3:

[0272] The device collects user activity data. It records the user's search history, location information, social media activity, etc., and sends this data to a server. For example, if a user searches for travel-related keywords, that data will be collected.

[0273] Step 4:

[0274] The server analyzes collected user activity data and generates user profiles. Using clustering algorithms, it classifies users' interests and creates individual profiles. For example, it might separate users into those who enjoy natural landscapes and those who enjoy urban tourism.

[0275] Step 5:

[0276] The server generates a customized travel plan based on the user's profile. Using generative artificial intelligence, it creates an itinerary combining suitable tourist spots, accommodations, and event information for the user. The created travel plan is then notified to the user's device.

[0277] Step 6:

[0278] The device displays suggested travel plans to the user. The user can view detailed information and customize the plan as needed. For example, if the user wants to travel on specific dates, a plan tailored to those dates will be displayed.

[0279] Step 7:

[0280] The user selects a suggested travel plan and proceeds with the booking process. After entering the required information into the booking form via their device, the booking information is sent to the server. Based on this information, the server notifies relevant service providers such as accommodations and tour guides.

[0281] Step 8:

[0282] The server notifies users of local events and activity information through the emotion engine. Through API linkage, the dashboard indicating the local contribution degree is updated. According to the emotions of users, the recommended events and activities are adjusted.

[0283] Step 9:

[0284] The emotion engine uses the user's face recognition technology and voice analysis technology to judge emotions. When the user operates the terminal, the emotion state is analyzed in real time through the camera and microphone and reflected in the user profile.

[0285] Step 10:

[0286] The server dynamically adjusts the content and travel plans based on the emotion data collected by the emotion engine. For example, when the user is happy looking at the travel plan, relevant additional information is provided. Conversely, when the user looks dissatisfied, another option is proposed.

[0287] The above is the specific processing flow of this system. Through these steps, the charm of the region can be effectively transmitted, attracting the interest of users, and ultimately contributing to the increase in the region's revenue. Also, by adding the emotion engine, it is possible to personalize the user experience and improve satisfaction.

[0288] (Example 2)

[0289] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0290] Traditional local information systems only provide basic information and lack personalized suggestions tailored to individual user interests and emotions. Furthermore, they are unable to recognize user emotions and adjust services in real time, making it difficult to increase customer satisfaction. In addition, they are insufficient in visualizing contributions to the local community and promoting monetization.

[0291] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting local information, means for generating attractive content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for recognizing emotions and dynamically adjusting the suggested content using the results, means for suggesting, booking, and managing travel plans, and means for service linkage. This enables personalized suggestions based on the user's individual interests and emotions, improving customer satisfaction, promoting monetization, and visualizing contributions to the local community.

[0292] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[0293] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates content such as text, images, and videos based on provided data.

[0294] "User profile data" refers to information about a user, including data such as their interests, behavioral history, and location information.

[0295] "Means of recognizing emotions" refers to technology that analyzes a user's facial expressions, voice, etc., to determine their emotional state.

[0296] "Personalized suggestions" refer to suggestions that are customized based on the user's individual interests, concerns, and emotional state.

[0297] "Service linkage means" refers to the function of notifying users of external services and event information or linking with other systems.

[0298] "Promotion of monetization" refers to activities that directly or indirectly generate revenue based on user usage.

[0299] The present invention relates to a system for effectively appealing the charm of a region, attracting user interest, and achieving monetization. This system is characterized by the collection of regional information, content generation by generative artificial intelligence, management of user profiles, emotional recognition of users by an emotion engine, and dynamic proposal adjustment based on the results. The specific embodiments described in this specification are configured as follows. <​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​ The server collects user interests, behavioral history, location information, etc., and generates user profiles using clustering algorithms (e.g., K-means).

[0309] Recognize emotions and adjust the proposal accordingly:

[0310] The server uses an emotion engine to analyze the user's facial expressions and voice, and dynamically adjusts content and suggestions based on the results.

[0311] 2. Device functions

[0312] A device is a smartphone or computer that serves as the user interface. It has the following functions:

[0313] Data collection:

[0314] The device records data such as the user's search history and social media activity, and periodically sends it to the server.

[0315] Content display:

[0316] The device displays content sent from the server, informing the user about the region's attractions. For example, it might display recommended tourist spots or travel plans.

[0317] Travel plan suggestions and bookings:

[0318] The terminal displays customized travel plans suggested by the server to the user and allows them to proceed with the booking process.

[0319] 3. User actions

[0320] Users are individuals or organizations that utilize the system. They perform the following actions:

[0321] Providing information of interest:

[0322] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0323] Viewing content:

[0324] Users view recommended content through their devices and deepen their interest in the local area.

[0325] Planning and booking your trip:

[0326] Users review the suggested travel plans and book the one they like.

[0327] Feedback based on emotion recognition:

[0328] The emotion engine recognizes the user's facial expressions and voice, and adjusts the suggested content in real time.

[0329] Specific example

[0330] For example, suppose user A is interested in "natural scenery" and "hot springs." User A's device recognizes these interests and sends data to the server. Based on this profile, the server collects information on hot spring resorts in appropriate regions and uses a generative AI to generate attractive descriptions and images. The server posts the generated content to social media and notifies user A. User A uses their device to review the travel plan, and if satisfied, proceeds with the booking process.

[0331] This system allows users to receive highly personalized information and suggestions, enabling them to fully experience the charm of their local area. Furthermore, by utilizing an emotion engine, user satisfaction can be improved in real time.

[0332] The specific embodiments of the present invention are as described above, and a specific platform is used for the hardware and software to realize them.

[0333] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0334] Step 1: Gathering local information

[0335] The server collects local information such as tourist attractions, food culture, history, and weather from the internet and dedicated databases. It sends queries to the Google Places API and OpenWeatherMap API as input, and stores the returned local information data in the database as output.

[0336] Specific actions:

[0337] The server sends a request to the Google Places API regarding "tourist spots in Tokyo."

[0338] The data returned from the API (tourist spot name, location, description, etc.) is stored in the server's database.

[0339] Step 2: User Data Collection

[0340] The device collects data such as the user's search history, social media activity, and location information, and sends it to the server. It collects user behavioral data as input and sends it to the server as output.

[0341] Specific actions:

[0342] When a user searches for "Tokyo hot springs" on their smartphone, that search history is recorded on the device.

[0343] The device periodically sends this information to the server.

[0344] Step 3: Generate User Profile

[0345] The server generates user profiles using a clustering algorithm based on user interests, behavioral history, location information, etc. It takes user data as input and generates profile data as output.

[0346] Specific actions:

[0347] The server analyzes user A's past search history and social media activity data.

[0348] Using a clustering algorithm (e.g., K-means), user A is tagged as being interested in "natural scenery" and "hot springs."

[0349] Step 4: Content Generation

[0350] Based on regional information and user profiles collected by the server, engaging content such as text, images, and videos is generated using a generative AI model (e.g., GPT-4, DALL-E). Regional information, prompt text, and user profiles are provided as input, and the generated content is obtained as output.

[0351] Specific actions:

[0352] The server inputs the prompt message "Generate a description of a hot spring tourist spot in Tokyo" into the AI ​​model.

[0353] The generative AI model generates an engaging description and associated images, and saves them.

[0354] Step 5: Content Distribution

[0355] The server distributes the generated content to social media and user devices. It takes generated content data as input and outputs it to social media or sends it to user devices.

[0356] Specific actions:

[0357] The server uses the generated introductory text and images to create data for social media posts.

[0358] The system uses the SNS API to automatically post and notify user A.

[0359] Step 6: Adjusting the proposal

[0360] The emotion engine recognizes the user's facial expressions and voice, and sends that data to the server. Based on this data, the server adjusts the suggestions in real time to provide the most suitable suggestions for the user. It receives the user's emotion data as input and provides adjusted suggestions as output.

[0361] Specific actions:

[0362] When user A is viewing a travel plan, the emotion engine recognizes user A's facial expressions.

[0363] If user A is excited, the server will display additional tourist attractions and special offers.

[0364] Step 7: Travel plan proposal and booking

[0365] The terminal displays travel plans suggested by the server to the user and allows them to make a reservation. It receives travel plan data from the server as input, presents it to the user as output, and performs the reservation operation.

[0366] Specific actions:

[0367] User A uses their device to review the suggested travel plan.

[0368] Select the suggested accommodations and sightseeing tours and proceed with the booking process.

[0369] Step 8: Visualizing the degree of contribution to the local community

[0370] The device collects user activity data in the local area and displays the level of contribution to the community on a visualized dashboard. It aggregates user consumption activity data as input and displays a dashboard that visualizes the level of contribution as output.

[0371] Specific actions:

[0372] When user A makes a purchase or engages in consumption activities locally, that data is recorded on the device.

[0373] The device visualizes the level of contribution to the local community (such as an economic activity index) and displays it to user A on a dashboard.

[0374] (Application Example 2)

[0375] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0376] Traditional local information systems could provide customized content and travel plans based on users' interests, but they could not recognize users' emotions in real time and dynamically adjust content and suggestions on the spot. Furthermore, in physical stores, it was difficult to personalize in-store recommendations and promotions based on users' emotions. As a result, they failed to improve the user experience and adequately enhance monetization and customer satisfaction.

[0377] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0378] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for dynamically adjusting content and suggestions using an emotion engine that recognizes user emotions, and means for recognizing user emotions in real time within a physical store and adjusting recommended products and promotions within the store. This makes it possible to adjust suggestions in real time based on user emotions and provide a more personalized experience.

[0379] 1. "Local information" refers to information about tourist attractions, food culture, history, weather, etc., related to a specific geographical area.

[0380] 2. "Generative artificial intelligence" refers to artificial intelligence technology used to generate engaging content such as text, images, and videos from collected data.

[0381] 3. "User profile data" refers to data that includes each user's interests, behavioral history, location information, etc.

[0382] 4. An "emotion engine" is a system component that uses facial recognition and voice analysis technologies to recognize a user's emotions and adjusts content and suggestions based on those emotions.

[0383] 5. "Content" refers to digital media such as text, images, and videos that include information and entertainment elements presented to the user.

[0384] 6. "Suggestions" refer to travel plans and product information recommended to the user based on their profile data and sentiment recognition results.

[0385] 7. A "physical store" is a shop located in a physical place where users can directly view and purchase products.

[0386] 8. "Real-time" refers to instantaneous processing that responds immediately to user actions and behaviors.

[0387] 9. "Recommended products" are products that have been deemed appropriate based on the user's profile and sentiment data.

[0388] 10. "Promotion" refers to incentives and advertising activities conducted to boost sales or increase brand awareness of a product.

[0389] System Configuration

[0390] The system of the present invention consists of the following main components:

[0391] 1. Server (Central Management System)

[0392] 2. Device (user's smartphone or computer)

[0393] 3. User

[0394] 4. Emotional Engine

[0395] server

[0396] The server is a centralized management system with multiple functions. This server includes the following functions:

[0397] Gathering local information:

[0398] The server periodically collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0399] Content generation:

[0400] Based on the collected regional information, the server uses generative artificial intelligence (such as GPT-3®) to generate engaging content such as text, images, and videos. This content is then posted to social media and websites.

[0401] User profile management:

[0402] The server collects each user's interests, behavioral history, location information, etc., and uses this data to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[0403] Processing emotion recognition data:

[0404] The server receives emotional data sent from the emotion engine and reflects it in the user's profile. Based on this data, it adjusts content and suggestions in real time.

[0405] terminal

[0406] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[0407] Data collection:

[0408] The device records the user's search history, social media activity, etc., and sends it to the server.

[0409] Content display:

[0410] The terminal displays content sent from the server, informing users about the attractions of the region.

[0411] Travel plan suggestions and bookings:

[0412] The terminal displays customized travel plans suggested by the server to the user and allows them to proceed with the booking process.

[0413] Real-time emotion recognition:

[0414] In physical stores, smart glasses or head-mounted displays are used as terminals to recognize the user's emotions in real time. This emotion data is then sent to a server, and recommended products and promotional information are displayed as appropriate.

[0415] user

[0416] Users are individuals or organizations that utilize the system and perform the following actions:

[0417] Providing information of interest:

[0418] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0419] Viewing content:

[0420] Users view recommended content through their devices and deepen their interest in the local area.

[0421] Planning and booking your trip:

[0422] Users review the suggested travel plans and book the one they like.

[0423] Emotional Engine

[0424] The emotion engine is a system component that recognizes user emotions and adjusts content and suggestions based on those emotions. This emotion engine includes the following features:

[0425] Emotion recognition:

[0426] The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions and reflects the results in the user profile. For example, it could use a facial recognition library such as DeepFace.

[0427] Real-time adjustment:

[0428] The emotion engine monitors user emotions in real time and dynamically changes content to improve the user's customer experience.

[0429] Specific usage examples

[0430] For example, imagine a user in a physical store wearing smart glasses and browsing the merchandise. When the emotion engine recognizes the user's facial expression and detects "joy," the server receives this emotion data and displays suitable product recommendations and promotional information on the smart glasses' display. This allows the user to have a more enjoyable shopping experience. Furthermore, the emotion engine can adjust its suggestions in real time based on the user's emotional changes, leading to improved customer satisfaction.

[0431] Example of a prompt

[0432] For example, it is possible to input prompt statements like the following into the generation AI model:

[0433] We want to offer the best possible promotion when our users are happy. Please tell us the specific product name and offer details.

[0434] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0435] Step 1:

[0436] The server collects local information from the internet and dedicated databases. Specifically, it uses APIs to retrieve information such as tourist attractions, food culture, history, and weather, and stores this data in the database.

[0437] Input: Local information such as tourist attractions, food culture, history, and weather.

[0438] Output: Regional information stored in the database.

[0439] Step 2:

[0440] The server uses generative artificial intelligence to generate content such as text, images, and videos based on collected regional information. Specifically, it uses GPT-3 and image generation models to create engaging content and posts it to social media and websites.

[0441] Input: Local information.

[0442] Output: Generated content such as text, images, and videos.

[0443] Step 3:

[0444] The server collects and analyzes user profile data, such as interests, behavioral history, and location information. It uses clustering algorithms to classify user preferences.

[0445] Input: User profile data such as interests, behavioral history, and location information.

[0446] Output: Classified user profiles.

[0447] Step 4:

[0448] The device recognizes the user's emotions in real time and sends that data to a server. Specifically, it uses cameras built into smart glasses or head-mounted displays to perform facial recognition and voice analysis technologies.

[0449] Input: User's facial expressions and voice data.

[0450] Output: Recognized emotion data.

[0451] Step 5:

[0452] The server receives sentiment data sent from the sentiment engine and reflects it in the user profile. Based on the sentiment data, content and suggestions are adjusted in real time.

[0453] Input: Sentiment data.

[0454] Output: Edited content and suggestions.

[0455] Step 6:

[0456] The terminal displays customized travel plans sent from the server to the user and allows them to make a reservation. In physical stores, it also displays recommended products and promotional information based on the user profile and sentiment data.

[0457] Input: Customized travel plans and content tailored in real time.

[0458] Output: Travel plans and promotional information displayed to the user.

[0459] Step 7:

[0460] Users review the suggested travel plans and, if they like them, proceed with the booking process. In physical stores, they purchase products based on the displayed recommended items and promotional information.

[0461] Input: Customized travel plans and promotional information.

[0462] Output: Booked travel plans and purchased items.

[0463] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0464] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0465] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0466] [Second Embodiment]

[0467] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0468] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0469] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0470] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0471] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0472] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0473] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0474] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0475] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0476] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0477] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0478] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0479] The present invention provides a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue. The specific embodiments described herein are configured as follows.

[0480] System Configuration

[0481] This system consists of the following main components:

[0482] 1. Server (Central Management System)

[0483] 2. Device (user's smartphone or computer)

[0484] 3. User

[0485] server

[0486] The server is a centralized management system with multiple functions. This server includes the following functions:

[0487] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0488] Content Generation: Based on collected local information, the server uses generative artificial intelligence to generate engaging content such as text, images, and videos. This content is automatically posted to social media and websites for widespread sharing.

[0489] User Profile Management: The server collects information such as each user's interests, behavioral history, and location, and uses this information to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[0490] terminal

[0491] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[0492] Data collection: The device records the user's search history, social media activity, etc., and sends it to the server.

[0493] Content display: The device displays content sent from the server, informing the user about the local attractions.

[0494] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[0495] user

[0496] Users are individuals or organizations that utilize the system and perform the following actions:

[0497] Providing interest information: Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0498] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[0499] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[0500] Specific usage examples

[0501] For example, suppose a user is interested in natural landscapes and hot springs. The user's device identifies these interests from their past search history and social media activity, and sends this data to the server. The server then gathers information on appropriate hot spring resorts in the user's region, tailored to their profile, and uses generative AI to create compelling descriptions and images. Next, the server posts this content to social media and notifies the user.

[0502] Users receive the notification and, if interested, check the suggested travel plan on their device. The plan includes information on how to access the hot spring resort, accommodations, and local activities. If the user is satisfied with the plan, they proceed with the booking process through their device. This booking data is aggregated on a server and automatically notified to the relevant service providers.

[0503] Furthermore, users can utilize a dashboard that visualizes their contribution to the local community during their activities, allowing them to truly understand how much their efforts are benefiting the region. This encourages users to develop a greater interest in and involvement with the local community.

[0504] The above describes a specific embodiment of the present invention. This system makes it possible to effectively promote the appeal of a region, attract user interest, and even generate revenue.

[0505] The following describes the processing flow.

[0506] Step 1:

[0507] The server collects local information. This local information includes tourist attractions, food culture, historical background, and weather information. Specifically, the server uses APIs to retrieve this information from the internet and databases, and stores the collected information in the database.

[0508] Step 2:

[0509] The server generates engaging content from local information collected using generative artificial intelligence. It uses text generation AI to create introductory articles about the region and image generation AI to create visuals of tourist attractions. The generated content is then posted to social media and websites.

[0510] Step 3:

[0511] The device collects user activity data. For example, the device records the user's search history, location information, and social media activity, and sends this data to a server. This data is used for subsequent analysis.

[0512] Step 4:

[0513] The server analyzes collected user activity data and generates user profiles. It uses clustering algorithms to classify user interests and create individual profiles. Based on these profiles, it is ready to suggest the most relevant local information to the user.

[0514] Step 5:

[0515] The server generates a customized travel plan based on the user's profile. The server selects tourist attractions, accommodations, and event information that match the user's interests, and uses generative artificial intelligence to create an attractive itinerary. The user is then notified of the created travel plan.

[0516] Step 6:

[0517] The device displays suggested travel plans to the user. The user can review the details of the travel plans through the device and select the plan that best suits their needs. If the user is satisfied with the travel plan, they can proceed with the booking process.

[0518] Step 7:

[0519] The user selects a suggested travel plan and proceeds with the booking process. This confirms the travel plan, and the user's booking data is sent to the server. The server then notifies the relevant service providers (e.g., accommodation, tour guides) of the booking information.

[0520] Step 8:

[0521] The server notifies users of local events and activities through SBG services. It updates a community contribution dashboard via API integration, visually showing users their level of community contribution. This provides users with motivation to participate in further activities and events.

[0522] The above outlines the specific processing flow of this system. Through these steps, it is possible to effectively communicate the appeal of the region, attract user interest, and ultimately contribute to increasing the region's revenue.

[0523] (Example 1)

[0524] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0525] Conventional regional information systems had limited information gathering and analysis capabilities, and did not adequately customize information based on user interests. As a result, it was difficult for users to fully understand and develop an interest in the region's attractions. Furthermore, efficient suggestions were not provided for travel plan generation and booking, making monetization a challenge.

[0526] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0527] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for proposing customized travel plans based on user profiles, means for booking and managing travel plans to promote monetization, means for notifying users of local service activities and event information, means for generating content based on prompt sentences using a generative artificial intelligence model, and means for classifying user interests using a clustering algorithm. This makes it possible to provide users with more personalized information and engaging travel plans.

[0528] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[0529] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates content such as text, images, and videos based on collected data.

[0530] "User profile data" refers to data such as a user's interests, behavioral history, and location information.

[0531] A "clustering algorithm" refers to a statistical method for grouping similar user data.

[0532] A "prompt message" refers to text input used to instruct a generative artificial intelligence system to generate specific information.

[0533] A "travel plan" refers to a detailed plan for a trip to a specific region.

[0534] "Monetization" refers to the process of generating profit from the services or information provided.

[0535] "Community service activities" refer to public services or volunteer activities carried out in a specific area.

[0536] "Event information" refers to detailed information about events held in a specific region.

[0537] This invention is a system that effectively promotes the appeal of a region, attracts user interest, and facilitates monetization. The specific form of implementing this system is configured as follows.

[0538] System Configuration

[0539] This system consists of the following main components:

[0540] 1. Server (Central Management System)

[0541] 2. Device (user's smartphone or computer)

[0542] 3. User

[0543] server

[0544] A server is a centralized management system with multiple functions. The server has the following functions:

[0545] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0546] Specific example: The server retrieves information about "AA Hot Spring Resort" from a tourism information API and saves it to a database.

[0547] Content generation using generative artificial intelligence (AI): Based on collected regional information, the server uses generative AI (e.g., OpenAI GPT-4) to generate engaging content such as text, images, and videos. The generated content is automatically posted to social media and websites.

[0548] Example of a prompt: The server sends a prompt to the AI ​​generating the following: "Please introduce a region famous for its hot springs. Please include the region's history, the characteristics of the hot springs, and nearby tourist attractions." The AI ​​then generates a detailed introduction.

[0549] User Profile Management: The server collects each user's interests, behavioral history, location information, etc., and generates and analyzes user profiles based on this data. A clustering algorithm is used to classify user interests.

[0550] Specific example: The device sends search history such as "hot springs" and "hiking" to the server, and the server clusters user profiles as "users interested in nature and hot springs."

[0551] Travel plan suggestion: The server generates a customized travel plan based on the user profile and sends it to the device.

[0552] Specific example: The server generates a "travel plan to a hot spring resort" and sends it to the terminal.

[0553] Travel plan booking and management: The server books and manages the travel plans selected by the user. Booking data is automatically notified to the relevant service provider.

[0554] Specific example: Users use their devices to make reservations for accommodations and activities, and the server aggregates the reservation information and notifies the accommodations.

[0555] Notification function: The server notifies users of information about local service activities and events.

[0556] Specific example: A server collects information about local events and notifies users.

[0557] terminal

[0558] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. Its main functions are as follows:

[0559] Data collection: The device records the user's search history and social media activity and sends it to the server.

[0560] Specific example: The device monitors the user's past social media activity and sends topics of interest to the server.

[0561] Content display: The device displays content sent from the server, providing users with information about the local area.

[0562] Specific example: A message titled "Introduction to a new hot spring resort" appears on the user's smartphone, and the user views the details.

[0563] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[0564] Specific example: A user checks their travel plan on their smartphone and completes the booking process.

[0565] user

[0566] Users are individuals or organizations that utilize the system and perform the following actions:

[0567] Providing interest information: Users provide the system with their search history and preferences to receive more personalized suggestions.

[0568] Specific example: A user searches for terms like "hot springs" or "natural scenery," and their search history is saved on the server.

[0569] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[0570] Specific example: A user views a "hot spring resort introduction" on their smartphone.

[0571] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[0572] Specific example: A user uses their device to check travel plans and book accommodations.

[0573] The above describes a specific embodiment of the present invention. This system allows users to receive attractive local information and easily book customized travel plans. It also enables effective promotion of local attractions and facilitates monetization.

[0574] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0575] Step 1:

[0576] The server collects local information. Specifically, it periodically retrieves information such as tourist spots, food culture, history, and weather related to the region from the internet and dedicated databases using APIs, and stores it in the database.

[0577] Input: Request from the Tourism Information API

[0578] Output: Latest regional information from the database

[0579] Example of operation: The server requests information about "AA Hot Spring Resort" from the tourism information API and saves the retrieved data to the database.

[0580] Step 2:

[0581] The device records the user's search history and social media activity and sends it to the server. This allows the server to collect information about the user's interests, behavioral history, and location.

[0582] Input: User's search history, social media activity data

[0583] Output: Data stored in the user database on the server.

[0584] Example of operation: The device records the user's search history, such as "hot springs" and "natural scenery," and sends it to the server.

[0585] Step 3:

[0586] The server generates and analyzes user profiles using a clustering algorithm based on the collected user data.

[0587] Input: User's search history, social media activity data

[0588] Output: Classified user profile data

[0589] Example of operation: The server uses a clustering algorithm to classify users as "interested in nature and hot springs."

[0590] Step 4:

[0591] The server uses generative AI to generate engaging content based on collected local information and user profiles. Prompts are used to prompt the AI ​​to generate specific information.

[0592] Input: Regional information, user profile data, prompt text

[0593] Output: Generated content such as text, images, and videos.

[0594] Example of operation: The server generates content using the following prompt for the AI: "Please introduce a region famous for its hot springs. Please describe the region's history, the characteristics of the hot springs, and nearby tourist attractions."

[0595] Step 5:

[0596] The server automatically posts the generated content to social media and websites and notifies relevant users.

[0597] Input: Generated content

[0598] Output: Posts to social media and websites, notifications to users

[0599] Example of operation: The server posts "introductions to hot spring resorts" to Facebook and Twitter, and sends notifications to interested users.

[0600] Step 6:

[0601] The device receives notifications sent from the server and displays them to the user. The user views the content via a smartphone or computer.

[0602] Input: Notification from server

[0603] Output: Content displayed on the user's device

[0604] Example of operation: An advertisement for a new hot spring resort is displayed on the user's smartphone, and the user views the content in detail.

[0605] Step 7:

[0606] The server generates a customized travel plan based on the user's profile and sends it to the device. The user reviews the plan on the device and proceeds with the booking process if they like it.

[0607] Input: User profile data

[0608] Output: Generated customized travel plan

[0609] Example of operation: The server generates a "travel plan to a hot spring resort" and sends it to the terminal. The user checks the plan on the terminal and makes reservations for accommodations and activities.

[0610] Step 8:

[0611] The terminal sends the reservation data entered by the user to the server, and the server completes the reservation process. The server aggregates this data and notifies the relevant service providers.

[0612] Input: User's reservation data

[0613] Output: Booking completion data, notification to service provider

[0614] Example of operation: A user makes a reservation for accommodation using their device, that information is sent to the server, and the server notifies the accommodation.

[0615] The above outlines the specific processing steps and operation of this system. This system allows users to receive attractive local information, easily book customized travel plans, effectively promote the region's appeal, and facilitate monetization.

[0616] (Application Example 1)

[0617] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0618] In systems designed to effectively promote local attractions, attract user interest, and generate revenue, there is a lack of means to provide in-store promotions and special offers tailored to user interests. Furthermore, it is difficult to effectively classify user profiles in detail based on collected data and propose personalized travel plans and event information. There is also a need for a system to analyze and optimize the effectiveness of these promotions and suggestions.

[0619] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0620] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for proposing customized travel plans based on user profiles, means for booking and managing travel plans to promote monetization, means for service integration to notify users of local service activities and event information, and means for providing promotional information for physical stores and displaying special offers and coupons based on user interests. This enables effective promotion of the region's attractions, provides personalized information to users, promotes purchases at physical stores, and proposes travel plans based on user interests.

[0621] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[0622] "Generative artificial intelligence" refers to artificial intelligence that has algorithms to generate content such as text, images, and videos from input data.

[0623] "User profile data" refers to data that shows individual information about a user, such as their interests, behavioral history, and location information.

[0624] A "customized travel plan" is a travel schedule that is personalized and provided to the user based on their user profile data.

[0625] "Means for booking and managing travel plans" refers to system elements that allow users to book suggested travel plans and manage them afterward.

[0626] A "service linkage system" is a linkage system used to notify users of information about local community service activities and events.

[0627] "In-store promotional information" refers to information such as discounts, coupons, and special offers offered at physical stores.

[0628] Modes for carrying out the invention

[0629] This invention provides a system that effectively promotes the appeal of a region, attracts user interest, and leads to monetization. This system mainly consists of three components: a server, terminals, and users.

[0630] System Configuration

[0631] server

[0632] The server is a central management system with the following main functions. This server includes the following functions:

[0633] 1. Gathering local information

[0634] The server uses APIs (for example, travel data APIs) to periodically collect information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. This information is used as input data for generative artificial intelligence (AI), which will be discussed later.

[0635] 2. Content Generation

[0636] The server uses generative artificial intelligence (e.g., GPT-4) to generate engaging content such as text, images, and videos based on collected regional information. For example, it can generate content based on prompts such as, "Please create text and images to promote the charm of the region. Regional information: Ohori Park, a famous tourist spot in Fukuoka City, offers beautiful Japanese gardens and boating. The park also has many stylish cafes and attracts many tourists on weekends. Please also introduce mentaiko, a famous Fukuoka specialty."

[0637] 3. Database Management

[0638] The server uses relational databases such as MySQL to manage generated content and user information.

[0639] 4. User Profile Management and Analysis

[0640] Using machine learning algorithms (for example, Scikit-learn's clustering algorithm), we generate and analyze user profiles based on their interests and behavioral history, and then provide personalized suggestions.

[0641] 5. Linked to physical stores

[0642] Based on user interests, the system displays promotional information, special offers, and coupons for physical stores (e.g., restaurants, souvenir shops, etc.).

[0643] terminal

[0644] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[0645] 1. Data Collection

[0646] The device records the user's search history, social media activity, etc., and sends it to the server.

[0647] 2. Content Display

[0648] The system displays content and promotional information sent from the server, informing users about the region's attractions. It also offers special offers and coupons.

[0649] 3. Reservation function

[0650] Make reservations for the proposed travel plans and events.

[0651] user

[0652] Users are individuals or organizations that utilize the system and perform the following actions:

[0653] 1. Providing information of interest

[0654] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0655] 2. Viewing content

[0656] Users view suggested content through their devices and deepen their interest in the local area.

[0657] 3. Deciding on and booking your travel plan.

[0658] Users review the suggested travel plans and book the one they like. They can also take advantage of local store information and special offers.

[0659] This system will effectively promote the attractions of the region, provide users with personalized information, and enable increased sales at physical stores as well as the suggestion of travel plans based on users' interests.

[0660] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0661] Step 1:

[0662] The server uses APIs to collect local information from the internet and dedicated databases. The input to this process is requests obtained from the API, and the output is information related to the region, such as tourist attractions, food culture, history, and weather. This data is then input into the generating AI in the next step.

[0663] Step 2:

[0664] The server generates content using generative artificial intelligence (e.g., GPT-4) based on collected regional information. The input to this process is regional information and prompt text, while the output is engaging content such as generated text, images, and videos. Specifically, prompt text is used to instruct the AI, which then generates the content.

[0665] Step 3:

[0666] The server saves the generated content to a relational database such as MySQL. The input to this process is the generated content, and the output is the content data stored in the database. Specifically, it creates an SQL query and inserts the content data into the database.

[0667] Step 4:

[0668] The device records the user's search history and social media activity and sends it to the server. The input to this process is the user's operation log, and the output is user data sent to the server. Specifically, it collects data locally and then makes an API request to send it to the server.

[0669] Step 5:

[0670] The server manages user profiles and analyzes user interests using machine learning algorithms (e.g., Scikit-learn). The input to this process is user data, and the output is clustered user profiles. Specifically, it applies a clustering algorithm to classify users according to their interests.

[0671] Step 6:

[0672] The server generates travel plans and event information based on user interests and sends them to the device. The input to this process is clustered user profiles and generated content, while the output is customized travel plans and event information. Specifically, it selects appropriate information based on the user profile and sends push notifications or displays them on the device.

[0673] Step 7:

[0674] The terminal displays customized travel plans and event information to the user, and provides promotional information, special offers, and coupons for physical stores. The input for this process is information sent from the server, and the output is the displayed travel plan and coupon information. Specifically, the system displays the information appropriately on the user interface, making it easily accessible to the user.

[0675] Step 8:

[0676] Users review the displayed customized travel plans and in-store promotional information, and make reservations or use coupons as needed. The input for this process is the information displayed on the terminal, and the output is reservation data and coupon usage history. Specific actions include reviewing travel plan details and entering coupon codes.

[0677] Step 9:

[0678] The server aggregates user reservation history and coupon usage data to optimize effective advertising campaigns and promotional strategies. The input to this process is reservation data and coupon usage history, while the output is optimized advertising campaign and promotional data. Specifically, it performs data analysis and selects the most suitable strategies.

[0679] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0680] This invention combines a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue with an emotion engine that recognizes user emotions. The specific embodiments described herein are configured as follows.

[0681] System Configuration

[0682] This system consists of the following main components:

[0683] 1. Server (Central Management System)

[0684] 2. Device (user's smartphone or computer)

[0685] 3. User

[0686] 4. Emotional Engine

[0687] server

[0688] The server is a centralized management system with multiple functions. This server includes the following functions:

[0689] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0690] Content Generation: Based on collected local information, the server uses generative artificial intelligence to generate engaging content such as text, images, and videos. This content is then posted to social media and websites.

[0691] User Profile Management: The server collects information such as each user's interests, behavioral history, and location, and uses this information to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[0692] terminal

[0693] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[0694] Data collection: The device records the user's search history, social media activity, etc., and sends it to the server.

[0695] Content display: The device displays content sent from the server, informing the user about the local attractions.

[0696] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[0697] user

[0698] Users are individuals or organizations that utilize the system and perform the following actions:

[0699] Providing interest information: Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0700] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[0701] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[0702] Emotional Engine

[0703] The emotion engine is a system component that recognizes user emotions and adjusts content and suggestions based on those emotions. This emotion engine includes the following features:

[0704] Emotion Recognition: The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions and reflects the results in the user profile.

[0705] Real-time adjustment: The emotion engine monitors user emotions in real time and dynamically changes content to improve the user's customer experience.

[0706] Specific usage examples

[0707] For example, suppose a user is interested in natural landscapes and hot springs. The user's device identifies these interests from their past search history and social media activity, and sends this data to the server. The server then gathers information on appropriate hot spring resorts in the user's region, tailored to their profile, and uses generative AI to create compelling descriptions and images. Next, the server posts this content to social media and notifies the user.

[0708] Users receive the notification and, if interested, check the suggested travel plan on their device. The plan includes information on how to access the hot spring resort, accommodations, and local activities. If the user is satisfied with the plan, they proceed with the booking process through their device. This booking data is aggregated on a server and automatically notified to the relevant service providers.

[0709] In this process, the emotion engine recognizes the user's emotions from their facial expressions and voice, and adjusts the suggestions according to the user's emotional state. For example, if the user is excited about a particular plan, additional information is provided to emphasize that plan. On the other hand, if the user looks dissatisfied, a different suggestion is presented to increase their satisfaction.

[0710] Furthermore, users can utilize a dashboard that visualizes their contribution to the local community during their activities, allowing them to truly understand how much their efforts are benefiting the region. This encourages users to develop a greater interest in and involvement with the local community.

[0711] The above describes specific embodiments of the present invention. This system makes it possible to effectively promote the appeal of a region, attract user interest, and even generate revenue. Furthermore, by combining it with an emotion engine, it is possible to further personalize the user experience and improve customer satisfaction.

[0712] The following describes the processing flow.

[0713] Step 1:

[0714] The server collects local information. It uses APIs to retrieve information on tourist attractions, food culture, historical background, weather, etc., and stores it in a database. Specifically, it utilizes databases from local tourism bureaus and public data resources.

[0715] Step 2:

[0716] The server generates engaging content from collected local information using generative artificial intelligence. It uses text generation AI to create articles introducing tourist destinations and image generation AI to generate visuals of tourist spots. The generated content is automatically posted to social media and official local websites.

[0717] Step 3:

[0718] The device collects user activity data. It records the user's search history, location information, social media activity, etc., and sends this data to a server. For example, if a user searches for travel-related keywords, that data will be collected.

[0719] Step 4:

[0720] The server analyzes collected user activity data and generates user profiles. Using clustering algorithms, it classifies users' interests and creates individual profiles. For example, it might separate users into those who enjoy natural landscapes and those who enjoy urban tourism.

[0721] Step 5:

[0722] The server generates a customized travel plan based on the user's profile. Using generative artificial intelligence, it creates an itinerary combining suitable tourist spots, accommodations, and event information for the user. The created travel plan is then notified to the user's device.

[0723] Step 6:

[0724] The device displays suggested travel plans to the user. The user can view detailed information and customize the plan as needed. For example, if the user wants to travel on specific dates, a plan tailored to those dates will be displayed.

[0725] Step 7:

[0726] The user selects a suggested travel plan and proceeds with the booking process. After entering the required information into the booking form via their device, the booking information is sent to the server. Based on this information, the server notifies relevant service providers such as accommodations and tour guides.

[0727] Step 8:

[0728] The server notifies users of local events and activities through an emotion engine. A dashboard showing local contributions is updated via API integration. Recommended events and activities are adjusted based on the user's emotions.

[0729] Step 9:

[0730] The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions. As the user operates the device, it analyzes their emotional state in real time through the camera and microphone and reflects this in the user profile.

[0731] Step 10:

[0732] The server dynamically adjusts content and travel plans based on emotional data collected by the emotion engine. For example, if a user is pleased with a travel plan, it provides additional relevant information. Conversely, if the user looks dissatisfied, it suggests alternative options.

[0733] The above outlines the specific processing flow of this system. Through these steps, it is possible to effectively communicate the appeal of a region, attract user interest, and ultimately contribute to increased regional revenue. Furthermore, by adding an emotion engine, it is possible to further personalize the user experience and improve satisfaction.

[0734] (Example 2)

[0735] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0736] Traditional local information systems only provide basic information and lack personalized suggestions tailored to individual user interests and emotions. Furthermore, they are unable to recognize user emotions and adjust services in real time, making it difficult to increase customer satisfaction. In addition, they are insufficient in visualizing contributions to the local community and promoting monetization.

[0737] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting local information, means for generating attractive content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for recognizing emotions and dynamically adjusting the suggested content using the results, means for suggesting, booking, and managing travel plans, and means for service linkage. This enables personalized suggestions based on the user's individual interests and emotions, improving customer satisfaction, promoting monetization, and visualizing contributions to the local community.

[0738] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[0739] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates content such as text, images, and videos based on provided data.

[0740] "User profile data" refers to information about a user, including data such as their interests, behavioral history, and location information.

[0741] "Means of recognizing emotions" refers to technology that analyzes a user's facial expressions, voice, etc., to determine their emotional state.

[0742] "Personalized suggestions" refer to suggestions that are customized based on the user's individual interests, concerns, and emotional state.

[0743] "Service integration means" refers to functions that notify users of external services or event information, or that integrate with other systems.

[0744] "Promoting monetization" refers to activities that generate revenue directly or indirectly based on user usage.

[0745] This invention relates to a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue. This system features the collection of regional information, content generation using generative artificial intelligence, user profile management, and user emotion recognition by an emotion engine, along with dynamic suggestion adjustments based on the results. Specific embodiments described herein are configured as follows:

[0746] 1. Server Functions

[0747] The server is responsible for the central management of the system. It has the following functions:

[0748] Gathering local information:

[0749] The server collects local information such as tourist attractions, food culture, history, and weather from the internet and dedicated databases. For example, it uses the Google Places API and OpenWeatherMap API to retrieve information and store it in the database.

[0750] Content generation:

[0751] The server uses generative artificial intelligence (e.g., GPT-4, DALL-E) based on the collected regional information to generate engaging content such as text, images, and videos.

[0752] Example prompt: "Generate a detailed description of five must-see tourist spots in Tokyo and their highlights."

[0753] User profile management:

[0754] The server collects user interests, behavioral history, location information, etc., and generates user profiles using clustering algorithms (e.g., K-means).

[0755] Recognize emotions and adjust the proposal accordingly:

[0756] The server uses an emotion engine to analyze the user's facial expressions and voice, and dynamically adjusts content and suggestions based on the results.

[0757] 2. Device functions

[0758] A device is a smartphone or computer that serves as the user interface. It has the following functions:

[0759] Data collection:

[0760] The device records data such as the user's search history and social media activity, and periodically sends it to the server.

[0761] Content display:

[0762] The device displays content sent from the server, informing the user about the region's attractions. For example, it might display recommended tourist spots or travel plans.

[0763] Travel plan suggestions and bookings:

[0764] The terminal displays customized travel plans suggested by the server to the user and allows them to proceed with the booking process.

[0765] 3. User actions

[0766] Users are individuals or organizations that utilize the system. They perform the following actions:

[0767] Providing information of interest:

[0768] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0769] Viewing content:

[0770] Users view recommended content through their devices and deepen their interest in the local area.

[0771] Planning and booking your trip:

[0772] Users review the suggested travel plans and book the one they like.

[0773] Feedback based on emotion recognition:

[0774] The emotion engine recognizes the user's facial expressions and voice, and adjusts the suggested content in real time.

[0775] Specific example

[0776] For example, suppose user A is interested in "natural scenery" and "hot springs." User A's device recognizes these interests and sends data to the server. Based on this profile, the server collects information on hot spring resorts in appropriate regions and uses a generative AI to generate attractive descriptions and images. The server posts the generated content to social media and notifies user A. User A uses their device to review the travel plan, and if satisfied, proceeds with the booking process.

[0777] This system allows users to receive highly personalized information and suggestions, enabling them to fully experience the charm of their local area. Furthermore, by utilizing an emotion engine, user satisfaction can be improved in real time.

[0778] The specific embodiments of the present invention are as described above, and a specific platform is used for the hardware and software to realize them.

[0779] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0780] Step 1: Gathering local information

[0781] The server collects local information such as tourist attractions, food culture, history, and weather from the internet and dedicated databases. It sends queries to the Google Places API and OpenWeatherMap API as input, and stores the returned local information data in the database as output.

[0782] Specific actions:

[0783] The server sends a request to the Google Places API regarding "tourist spots in Tokyo."

[0784] The data returned from the API (tourist spot name, location, description, etc.) is stored in the server's database.

[0785] Step 2: User Data Collection

[0786] The device collects data such as the user's search history, social media activity, and location information, and sends it to the server. It collects user behavioral data as input and sends it to the server as output.

[0787] Specific actions:

[0788] When a user searches for "Tokyo hot springs" on their smartphone, that search history is recorded on the device.

[0789] The device periodically sends this information to the server.

[0790] Step 3: Generate User Profile

[0791] The server generates user profiles using a clustering algorithm based on user interests, behavioral history, location information, etc. It takes user data as input and generates profile data as output.

[0792] Specific actions:

[0793] The server analyzes user A's past search history and social media activity data.

[0794] Using a clustering algorithm (e.g., K-means), user A is tagged as being interested in "natural scenery" and "hot springs."

[0795] Step 4: Content Generation

[0796] Based on regional information and user profiles collected by the server, engaging content such as text, images, and videos is generated using a generative AI model (e.g., GPT-4, DALL-E). Regional information, prompt text, and user profiles are provided as input, and the generated content is obtained as output.

[0797] Specific actions:

[0798] The server inputs the prompt message "Generate a description of a hot spring tourist spot in Tokyo" into the AI ​​model.

[0799] The generative AI model generates an engaging description and associated images, and saves them.

[0800] Step 5: Content Distribution

[0801] The server distributes the generated content to social media and user devices. It takes generated content data as input and outputs it to social media or sends it to user devices.

[0802] Specific actions:

[0803] The server uses the generated introductory text and images to create data for social media posts.

[0804] The system uses the SNS API to automatically post and notify user A.

[0805] Step 6: Adjusting the proposal

[0806] The emotion engine recognizes the user's facial expressions and voice, and sends that data to the server. Based on this data, the server adjusts the suggestions in real time to provide the most suitable suggestions for the user. It receives the user's emotion data as input and provides adjusted suggestions as output.

[0807] Specific actions:

[0808] When user A is viewing a travel plan, the emotion engine recognizes user A's facial expressions.

[0809] If user A is excited, the server will display additional tourist attractions and special offers.

[0810] Step 7: Travel plan proposal and booking

[0811] The terminal displays travel plans suggested by the server to the user and allows them to make a reservation. It receives travel plan data from the server as input, presents it to the user as output, and performs the reservation operation.

[0812] Specific actions:

[0813] User A uses their device to review the suggested travel plan.

[0814] Select the suggested accommodations and sightseeing tours and proceed with the booking process.

[0815] Step 8: Visualizing the degree of contribution to the local community

[0816] The device collects user activity data in the local area and displays the level of contribution to the community on a visualized dashboard. It aggregates user consumption activity data as input and displays a dashboard that visualizes the level of contribution as output.

[0817] Specific actions:

[0818] When user A makes a purchase or engages in consumption activities locally, that data is recorded on the device.

[0819] The device visualizes the level of contribution to the local community (such as an economic activity index) and displays it to user A on a dashboard.

[0820] (Application Example 2)

[0821] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0822] Traditional local information systems could provide customized content and travel plans based on users' interests, but they could not recognize users' emotions in real time and dynamically adjust content and suggestions on the spot. Furthermore, in physical stores, it was difficult to personalize in-store recommendations and promotions based on users' emotions. As a result, they failed to improve the user experience and adequately enhance monetization and customer satisfaction.

[0823] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0824] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for dynamically adjusting content and suggestions using an emotion engine that recognizes user emotions, and means for recognizing user emotions in real time within a physical store and adjusting recommended products and promotions within the store. This makes it possible to adjust suggestions in real time based on user emotions and provide a more personalized experience.

[0825] 1. "Local information" refers to information about tourist attractions, food culture, history, weather, etc., related to a specific geographical area.

[0826] 2. "Generative artificial intelligence" refers to artificial intelligence technology used to generate engaging content such as text, images, and videos from collected data.

[0827] 3. "User profile data" refers to data that includes each user's interests, behavioral history, location information, etc.

[0828] 4. An "emotion engine" is a system component that uses facial recognition and voice analysis technologies to recognize a user's emotions and adjusts content and suggestions based on those emotions.

[0829] 5. "Content" refers to digital media such as text, images, and videos that include information and entertainment elements presented to the user.

[0830] 6. "Suggestions" refer to travel plans and product information recommended to the user based on their profile data and sentiment recognition results.

[0831] 7. A "physical store" is a shop located in a physical place where users can directly view and purchase products.

[0832] 8. "Real-time" refers to instantaneous processing that responds immediately to user actions and behaviors.

[0833] 9. "Recommended products" are products that have been deemed appropriate based on the user's profile and sentiment data.

[0834] 10. "Promotion" refers to incentives and advertising activities conducted to boost sales or increase brand awareness of a product.

[0835] System Configuration

[0836] The system of the present invention consists of the following main components:

[0837] 1. Server (Central Management System)

[0838] 2. Device (user's smartphone or computer)

[0839] 3. User

[0840] 4. Emotional Engine

[0841] server

[0842] The server is a centralized management system with multiple functions. This server includes the following functions:

[0843] Gathering local information:

[0844] The server periodically collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0845] Content generation:

[0846] Based on the collected regional information, the server uses generative artificial intelligence (such as GPT-3) to generate engaging content such as text, images, and videos. This content is then posted to social media and websites.

[0847] User profile management:

[0848] The server collects each user's interests, behavioral history, location information, etc., and uses this data to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[0849] Processing emotion recognition data:

[0850] The server receives emotional data sent from the emotion engine and reflects it in the user's profile. Based on this data, it adjusts content and suggestions in real time.

[0851] terminal

[0852] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[0853] Data collection:

[0854] The device records the user's search history, social media activity, etc., and sends it to the server.

[0855] Content display:

[0856] The terminal displays content sent from the server, informing users about the attractions of the region.

[0857] Travel plan suggestions and bookings:

[0858] The terminal displays customized travel plans suggested by the server to the user and allows them to proceed with the booking process.

[0859] Real-time emotion recognition:

[0860] In physical stores, smart glasses or head-mounted displays are used as terminals to recognize the user's emotions in real time. This emotion data is then sent to a server, and recommended products and promotional information are displayed as appropriate.

[0861] user

[0862] Users are individuals or organizations that utilize the system and perform the following actions:

[0863] Providing information of interest:

[0864] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0865] Viewing content:

[0866] Users view recommended content through their devices and deepen their interest in the local area.

[0867] Planning and booking your trip:

[0868] Users review the suggested travel plans and book the one they like.

[0869] Emotional Engine

[0870] The emotion engine is a system component that recognizes user emotions and adjusts content and suggestions based on those emotions. This emotion engine includes the following features:

[0871] Emotion recognition:

[0872] The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions and reflects the results in the user profile. For example, it could use a facial recognition library such as DeepFace.

[0873] Real-time adjustment:

[0874] The emotion engine monitors user emotions in real time and dynamically changes content to improve the user's customer experience.

[0875] Specific usage examples

[0876] For example, imagine a user in a physical store wearing smart glasses and browsing the merchandise. When the emotion engine recognizes the user's facial expression and detects "joy," the server receives this emotion data and displays suitable product recommendations and promotional information on the smart glasses' display. This allows the user to have a more enjoyable shopping experience. Furthermore, the emotion engine can adjust its suggestions in real time based on the user's emotional changes, leading to improved customer satisfaction.

[0877] Example of a prompt

[0878] For example, it is possible to input prompt statements like the following into the generation AI model:

[0879] We want to offer the best possible promotion when our users are happy. Please tell us the specific product name and offer details.

[0880] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0881] Step 1:

[0882] The server collects local information from the internet and dedicated databases. Specifically, it uses APIs to retrieve information such as tourist attractions, food culture, history, and weather, and stores this data in the database.

[0883] Input: Local information such as tourist attractions, food culture, history, and weather.

[0884] Output: Regional information stored in the database.

[0885] Step 2:

[0886] The server uses generative artificial intelligence to generate content such as text, images, and videos based on collected regional information. Specifically, it uses GPT-3 and image generation models to create engaging content and posts it to social media and websites.

[0887] Input: Local information.

[0888] Output: Generated content such as text, images, and videos.

[0889] Step 3:

[0890] The server collects and analyzes user profile data, such as interests, behavioral history, and location information. It uses clustering algorithms to classify user preferences.

[0891] Input: User profile data such as interests, behavioral history, and location information.

[0892] Output: Classified user profiles.

[0893] Step 4:

[0894] The device recognizes the user's emotions in real time and sends that data to a server. Specifically, it uses cameras built into smart glasses or head-mounted displays to perform facial recognition and voice analysis technologies.

[0895] Input: User's facial expressions and voice data.

[0896] Output: Recognized emotion data.

[0897] Step 5:

[0898] The server receives sentiment data sent from the sentiment engine and reflects it in the user profile. Based on the sentiment data, content and suggestions are adjusted in real time.

[0899] Input: Sentiment data.

[0900] Output: Edited content and suggestions.

[0901] Step 6:

[0902] The terminal displays customized travel plans sent from the server to the user and allows them to make a reservation. In physical stores, it also displays recommended products and promotional information based on the user profile and sentiment data.

[0903] Input: Customized travel plans and content tailored in real time.

[0904] Output: Travel plans and promotional information displayed to the user.

[0905] Step 7:

[0906] Users review the suggested travel plans and, if they like them, proceed with the booking process. In physical stores, they purchase products based on the displayed recommended items and promotional information.

[0907] Input: Customized travel plans and promotional information.

[0908] Output: Booked travel plans and purchased items.

[0909] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0910] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0911] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0912] [Third Embodiment]

[0913] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0914] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0915] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0916] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0917] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0918] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0919] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0920] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0921] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0922] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0923] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0924] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0925] The present invention provides a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue. The specific embodiments described herein are configured as follows.

[0926] System Configuration

[0927] This system consists of the following main components:

[0928] 1. Server (Central Management System)

[0929] 2. Device (user's smartphone or computer)

[0930] 3. User

[0931] server

[0932] The server is a centralized management system with multiple functions. This server includes the following functions:

[0933] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0934] Content Generation: Based on collected local information, the server uses generative artificial intelligence to generate engaging content such as text, images, and videos. This content is automatically posted to social media and websites for widespread sharing.

[0935] User Profile Management: The server collects information such as each user's interests, behavioral history, and location, and uses this information to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[0936] terminal

[0937] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[0938] Data collection: The device records the user's search history, social media activity, etc., and sends it to the server.

[0939] Content display: The device displays content sent from the server, informing the user about the local attractions.

[0940] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[0941] user

[0942] Users are individuals or organizations that utilize the system and perform the following actions:

[0943] Providing interest information: Users can provide the system with their search history and preferences to receive more personalized suggestions.

[0944] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[0945] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[0946] Specific usage examples

[0947] For example, suppose a user is interested in natural landscapes and hot springs. The user's device identifies these interests from their past search history and social media activity, and sends this data to the server. The server then gathers information on appropriate hot spring resorts in the user's region, tailored to their profile, and uses generative AI to create compelling descriptions and images. Next, the server posts this content to social media and notifies the user.

[0948] Users receive the notification and, if interested, check the suggested travel plan on their device. The plan includes information on how to access the hot spring resort, accommodations, and local activities. If the user is satisfied with the plan, they proceed with the booking process through their device. This booking data is aggregated on a server and automatically notified to the relevant service providers.

[0949] Furthermore, users can utilize a dashboard that visualizes their contribution to the local community during their activities, allowing them to truly understand how much their efforts are benefiting the region. This encourages users to develop a greater interest in and involvement with the local community.

[0950] The above describes a specific embodiment of the present invention. This system makes it possible to effectively promote the appeal of a region, attract user interest, and even generate revenue.

[0951] The following describes the processing flow.

[0952] Step 1:

[0953] The server collects local information. This local information includes tourist attractions, food culture, historical background, and weather information. Specifically, the server uses APIs to retrieve this information from the internet and databases, and stores the collected information in the database.

[0954] Step 2:

[0955] The server generates engaging content from local information collected using generative artificial intelligence. It uses text generation AI to create introductory articles about the region and image generation AI to create visuals of tourist attractions. The generated content is then posted to social media and websites.

[0956] Step 3:

[0957] The device collects user activity data. For example, the device records the user's search history, location information, and social media activity, and sends this data to a server. This data is used for subsequent analysis.

[0958] Step 4:

[0959] The server analyzes collected user activity data and generates user profiles. It uses clustering algorithms to classify user interests and create individual profiles. Based on these profiles, it is ready to suggest the most relevant local information to the user.

[0960] Step 5:

[0961] The server generates a customized travel plan based on the user's profile. The server selects tourist attractions, accommodations, and event information that match the user's interests, and uses generative artificial intelligence to create an attractive itinerary. The user is then notified of the created travel plan.

[0962] Step 6:

[0963] The device displays suggested travel plans to the user. The user can review the details of the travel plans through the device and select the plan that best suits their needs. If the user is satisfied with the travel plan, they can proceed with the booking process.

[0964] Step 7:

[0965] The user selects a suggested travel plan and proceeds with the booking process. This confirms the travel plan, and the user's booking data is sent to the server. The server then notifies the relevant service providers (e.g., accommodation, tour guides) of the booking information.

[0966] Step 8:

[0967] The server notifies users of local events and activities through SBG services. It updates a community contribution dashboard via API integration, visually showing users their level of community contribution. This provides users with motivation to participate in further activities and events.

[0968] The above outlines the specific processing flow of this system. Through these steps, it is possible to effectively communicate the appeal of the region, attract user interest, and ultimately contribute to increasing the region's revenue.

[0969] (Example 1)

[0970] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0971] Conventional regional information systems had limited information gathering and analysis capabilities, and did not adequately customize information based on user interests. As a result, it was difficult for users to fully understand and develop an interest in the region's attractions. Furthermore, efficient suggestions were not provided for travel plan generation and booking, making monetization a challenge.

[0972] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0973] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for proposing customized travel plans based on user profiles, means for booking and managing travel plans to promote monetization, means for notifying users of local service activities and event information, means for generating content based on prompt sentences using a generative artificial intelligence model, and means for classifying user interests using a clustering algorithm. This makes it possible to provide users with more personalized information and engaging travel plans.

[0974] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[0975] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates content such as text, images, and videos based on collected data.

[0976] "User profile data" refers to data such as a user's interests, behavioral history, and location information.

[0977] A "clustering algorithm" refers to a statistical method for grouping similar user data.

[0978] A "prompt message" refers to text input used to instruct a generative artificial intelligence system to generate specific information.

[0979] A "travel plan" refers to a detailed plan for a trip to a specific region.

[0980] "Monetization" refers to the process of generating profit from the services or information provided.

[0981] "Community service activities" refer to public services or volunteer activities carried out in a specific area.

[0982] "Event information" refers to detailed information about events held in a specific region.

[0983] This invention is a system that effectively promotes the appeal of a region, attracts user interest, and facilitates monetization. The specific form of implementing this system is configured as follows.

[0984] System Configuration

[0985] This system consists of the following main components:

[0986] 1. Server (Central Management System)

[0987] 2. Device (user's smartphone or computer)

[0988] 3. User

[0989] server

[0990] A server is a centralized management system with multiple functions. The server has the following functions:

[0991] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[0992] Specific example: The server retrieves information about "AA Hot Spring Resort" from a tourism information API and saves it to a database.

[0993] Content generation using generative artificial intelligence (AI): Based on collected regional information, the server uses generative AI (e.g., OpenAI GPT-4) to generate engaging content such as text, images, and videos. The generated content is automatically posted to social media and websites.

[0994] Example of a prompt: The server sends a prompt to the AI ​​generating the following: "Please introduce a region famous for its hot springs. Please include the region's history, the characteristics of the hot springs, and nearby tourist attractions." The AI ​​then generates a detailed introduction.

[0995] User Profile Management: The server collects each user's interests, behavioral history, location information, etc., and generates and analyzes user profiles based on this data. A clustering algorithm is used to classify user interests.

[0996] Specific example: The device sends search history such as "hot springs" and "hiking" to the server, and the server clusters user profiles as "users interested in nature and hot springs."

[0997] Travel plan suggestion: The server generates a customized travel plan based on the user profile and sends it to the device.

[0998] Specific example: The server generates a "travel plan to a hot spring resort" and sends it to the terminal.

[0999] Travel plan booking and management: The server books and manages the travel plans selected by the user. Booking data is automatically notified to the relevant service provider.

[1000] Specific example: Users use their devices to make reservations for accommodations and activities, and the server aggregates the reservation information and notifies the accommodations.

[1001] Notification function: The server notifies users of information about local service activities and events.

[1002] Specific example: A server collects information about local events and notifies users.

[1003] terminal

[1004] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. Its main functions are as follows:

[1005] Data collection: The device records the user's search history and social media activity and sends it to the server.

[1006] Specific example: The device monitors the user's past social media activity and sends topics of interest to the server.

[1007] Content display: The device displays content sent from the server, providing users with information about the local area.

[1008] Specific example: A message titled "Introduction to a new hot spring resort" appears on the user's smartphone, and the user views the details.

[1009] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[1010] Specific example: A user checks their travel plan on their smartphone and completes the booking process.

[1011] user

[1012] Users are individuals or organizations that utilize the system and perform the following actions:

[1013] Providing interest information: Users provide the system with their search history and preferences to receive more personalized suggestions.

[1014] Specific example: A user searches for terms like "hot springs" or "natural scenery," and their search history is saved on the server.

[1015] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[1016] Specific example: A user views a "hot spring resort introduction" on their smartphone.

[1017] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[1018] Specific example: A user uses their device to check travel plans and book accommodations.

[1019] The above describes a specific embodiment of the present invention. This system allows users to receive attractive local information and easily book customized travel plans. It also enables effective promotion of local attractions and facilitates monetization.

[1020] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1021] Step 1:

[1022] The server collects local information. Specifically, it periodically retrieves information such as tourist spots, food culture, history, and weather related to the region from the internet and dedicated databases using APIs, and stores it in the database.

[1023] Input: Request from the Tourism Information API

[1024] Output: Latest regional information from the database

[1025] Example of operation: The server requests information about "AA Hot Spring Resort" from the tourism information API and saves the retrieved data to the database.

[1026] Step 2:

[1027] The device records the user's search history and social media activity and sends it to the server. This allows the server to collect information about the user's interests, behavioral history, and location.

[1028] Input: User's search history, social media activity data

[1029] Output: Data stored in the user database on the server.

[1030] Example of operation: The device records the user's search history, such as "hot springs" and "natural scenery," and sends it to the server.

[1031] Step 3:

[1032] The server generates and analyzes user profiles using a clustering algorithm based on the collected user data.

[1033] Input: User's search history, social media activity data

[1034] Output: Classified user profile data

[1035] Example of operation: The server uses a clustering algorithm to classify users as "interested in nature and hot springs."

[1036] Step 4:

[1037] The server uses generative AI to generate engaging content based on collected local information and user profiles. Prompts are used to prompt the AI ​​to generate specific information.

[1038] Input: Regional information, user profile data, prompt text

[1039] Output: Generated content such as text, images, and videos.

[1040] Example of operation: The server generates content using the following prompt for the AI: "Please introduce a region famous for its hot springs. Please describe the region's history, the characteristics of the hot springs, and nearby tourist attractions."

[1041] Step 5:

[1042] The server automatically posts the generated content to social media and websites and notifies relevant users.

[1043] Input: Generated content

[1044] Output: Posts to social media and websites, notifications to users

[1045] Example of operation: The server posts "introductions to hot spring resorts" to Facebook and Twitter, and sends notifications to interested users.

[1046] Step 6:

[1047] The device receives notifications sent from the server and displays them to the user. The user views the content via a smartphone or computer.

[1048] Input: Notification from server

[1049] Output: Content displayed on the user's device

[1050] Example of operation: An advertisement for a new hot spring resort is displayed on the user's smartphone, and the user views the content in detail.

[1051] Step 7:

[1052] The server generates a customized travel plan based on the user's profile and sends it to the device. The user reviews the plan on the device and proceeds with the booking process if they like it.

[1053] Input: User profile data

[1054] Output: Generated customized travel plan

[1055] Example of operation: The server generates a "travel plan to a hot spring resort" and sends it to the terminal. The user checks the plan on the terminal and makes reservations for accommodations and activities.

[1056] Step 8:

[1057] The terminal sends the reservation data entered by the user to the server, and the server completes the reservation process. The server aggregates this data and notifies the relevant service providers.

[1058] Input: User's reservation data

[1059] Output: Booking completion data, notification to service provider

[1060] Example of operation: A user makes a reservation for accommodation using their device, that information is sent to the server, and the server notifies the accommodation.

[1061] The above outlines the specific processing steps and operation of this system. This system allows users to receive attractive local information, easily book customized travel plans, effectively promote the region's appeal, and facilitate monetization.

[1062] (Application Example 1)

[1063] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1064] In systems designed to effectively promote local attractions, attract user interest, and generate revenue, there is a lack of means to provide in-store promotions and special offers tailored to user interests. Furthermore, it is difficult to effectively classify user profiles in detail based on collected data and propose personalized travel plans and event information. There is also a need for a system to analyze and optimize the effectiveness of these promotions and suggestions.

[1065] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1066] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for proposing customized travel plans based on user profiles, means for booking and managing travel plans to promote monetization, means for service integration to notify users of local service activities and event information, and means for providing promotional information for physical stores and displaying special offers and coupons based on user interests. This enables effective promotion of the region's attractions, provides personalized information to users, promotes purchases at physical stores, and proposes travel plans based on user interests.

[1067] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[1068] "Generative artificial intelligence" refers to artificial intelligence that has algorithms to generate content such as text, images, and videos from input data.

[1069] "User profile data" refers to data that shows individual information about a user, such as their interests, behavioral history, and location information.

[1070] A "customized travel plan" is a travel schedule that is personalized and provided to the user based on their user profile data.

[1071] "Means for booking and managing travel plans" refers to system elements that allow users to book suggested travel plans and manage them afterward.

[1072] A "service linkage system" is a linkage system used to notify users of information about local community service activities and events.

[1073] "In-store promotional information" refers to information such as discounts, coupons, and special offers offered at physical stores.

[1074] Modes for carrying out the invention

[1075] This invention provides a system that effectively promotes the appeal of a region, attracts user interest, and leads to monetization. This system mainly consists of three components: a server, terminals, and users.

[1076] System Configuration

[1077] server

[1078] The server is a central management system with the following main functions. This server includes the following functions:

[1079] 1. Gathering local information

[1080] The server uses APIs (for example, travel data APIs) to periodically collect information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. This information is used as input data for generative artificial intelligence (AI), which will be discussed later.

[1081] 2. Content Generation

[1082] The server uses generative artificial intelligence (e.g., GPT-4) to generate engaging content such as text, images, and videos based on collected regional information. For example, it can generate content based on prompts such as, "Please create text and images to promote the charm of the region. Regional information: Ohori Park, a famous tourist spot in Fukuoka City, offers beautiful Japanese gardens and boating. The park also has many stylish cafes and attracts many tourists on weekends. Please also introduce mentaiko, a famous Fukuoka specialty."

[1083] 3. Database Management

[1084] The server uses relational databases such as MySQL to manage generated content and user information.

[1085] 4. User Profile Management and Analysis

[1086] Using machine learning algorithms (for example, Scikit-learn's clustering algorithm), we generate and analyze user profiles based on their interests and behavioral history, and then provide personalized suggestions.

[1087] 5. Linked to physical stores

[1088] Based on user interests, the system displays promotional information, special offers, and coupons for physical stores (e.g., restaurants, souvenir shops, etc.).

[1089] terminal

[1090] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[1091] 1. Data Collection

[1092] The device records the user's search history, social media activity, etc., and sends it to the server.

[1093] 2. Content Display

[1094] The system displays content and promotional information sent from the server, informing users about the region's attractions. It also offers special offers and coupons.

[1095] 3. Reservation function

[1096] Make reservations for the proposed travel plans and events.

[1097] user

[1098] Users are individuals or organizations that utilize the system and perform the following actions:

[1099] 1. Providing information of interest

[1100] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[1101] 2. Viewing content

[1102] Users view suggested content through their devices and deepen their interest in the local area.

[1103] 3. Deciding on and booking your travel plan.

[1104] Users review the suggested travel plans and book the one they like. They can also take advantage of local store information and special offers.

[1105] This system will effectively promote the attractions of the region, provide users with personalized information, and enable increased sales at physical stores as well as the suggestion of travel plans based on users' interests.

[1106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1107] Step 1:

[1108] The server uses APIs to collect local information from the internet and dedicated databases. The input to this process is requests obtained from the API, and the output is information related to the region, such as tourist attractions, food culture, history, and weather. This data is then input into the generating AI in the next step.

[1109] Step 2:

[1110] The server generates content using generative artificial intelligence (e.g., GPT-4) based on collected regional information. The input to this process is regional information and prompt text, while the output is engaging content such as generated text, images, and videos. Specifically, prompt text is used to instruct the AI, which then generates the content.

[1111] Step 3:

[1112] The server saves the generated content to a relational database such as MySQL. The input to this process is the generated content, and the output is the content data stored in the database. Specifically, it creates an SQL query and inserts the content data into the database.

[1113] Step 4:

[1114] The device records the user's search history and social media activity and sends it to the server. The input to this process is the user's operation log, and the output is user data sent to the server. Specifically, it collects data locally and then makes an API request to send it to the server.

[1115] Step 5:

[1116] The server manages user profiles and analyzes user interests using machine learning algorithms (e.g., Scikit-learn). The input to this process is user data, and the output is clustered user profiles. Specifically, it applies a clustering algorithm to classify users according to their interests.

[1117] Step 6:

[1118] The server generates travel plans and event information based on user interests and sends them to the device. The input to this process is clustered user profiles and generated content, while the output is customized travel plans and event information. Specifically, it selects appropriate information based on the user profile and sends push notifications or displays them on the device.

[1119] Step 7:

[1120] The terminal displays customized travel plans and event information to the user, and provides promotional information, special offers, and coupons for physical stores. The input for this process is information sent from the server, and the output is the displayed travel plan and coupon information. Specifically, the system displays the information appropriately on the user interface, making it easily accessible to the user.

[1121] Step 8:

[1122] Users review the displayed customized travel plans and in-store promotional information, and make reservations or use coupons as needed. The input for this process is the information displayed on the terminal, and the output is reservation data and coupon usage history. Specific actions include reviewing travel plan details and entering coupon codes.

[1123] Step 9:

[1124] The server aggregates user reservation history and coupon usage data to optimize effective advertising campaigns and promotional strategies. The input to this process is reservation data and coupon usage history, while the output is optimized advertising campaign and promotional data. Specifically, it performs data analysis and selects the most suitable strategies.

[1125] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1126] This invention combines a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue with an emotion engine that recognizes user emotions. The specific embodiments described herein are configured as follows.

[1127] System Configuration

[1128] This system consists of the following main components:

[1129] 1. Server (Central Management System)

[1130] 2. Device (user's smartphone or computer)

[1131] 3. User

[1132] 4. Emotional Engine

[1133] server

[1134] The server is a centralized management system with multiple functions. This server includes the following functions:

[1135] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[1136] Content Generation: Based on collected local information, the server uses generative artificial intelligence to generate engaging content such as text, images, and videos. This content is then posted to social media and websites.

[1137] User Profile Management: The server collects information such as each user's interests, behavioral history, and location, and uses this information to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[1138] terminal

[1139] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[1140] Data collection: The device records the user's search history, social media activity, etc., and sends it to the server.

[1141] Content display: The device displays content sent from the server, informing the user about the local attractions.

[1142] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[1143] user

[1144] Users are individuals or organizations that utilize the system and perform the following actions:

[1145] Providing interest information: Users can provide the system with their search history and preferences to receive more personalized suggestions.

[1146] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[1147] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[1148] Emotional Engine

[1149] The emotion engine is a system component that recognizes user emotions and adjusts content and suggestions based on those emotions. This emotion engine includes the following features:

[1150] Emotion Recognition: The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions and reflects the results in the user profile.

[1151] Real-time adjustment: The emotion engine monitors user emotions in real time and dynamically changes content to improve the user's customer experience.

[1152] Specific usage examples

[1153] For example, suppose a user is interested in natural landscapes and hot springs. The user's device identifies these interests from their past search history and social media activity, and sends this data to the server. The server then gathers information on appropriate hot spring resorts in the user's region, tailored to their profile, and uses generative AI to create compelling descriptions and images. Next, the server posts this content to social media and notifies the user.

[1154] Users receive the notification and, if interested, check the suggested travel plan on their device. The plan includes information on how to access the hot spring resort, accommodations, and local activities. If the user is satisfied with the plan, they proceed with the booking process through their device. This booking data is aggregated on a server and automatically notified to the relevant service providers.

[1155] In this process, the emotion engine recognizes the user's emotions from their facial expressions and voice, and adjusts the suggestions according to the user's emotional state. For example, if the user is excited about a particular plan, additional information is provided to emphasize that plan. On the other hand, if the user looks dissatisfied, a different suggestion is presented to increase their satisfaction.

[1156] Furthermore, users can utilize a dashboard that visualizes their contribution to the local community during their activities, allowing them to truly understand how much their efforts are benefiting the region. This encourages users to develop a greater interest in and involvement with the local community.

[1157] The above describes specific embodiments of the present invention. This system makes it possible to effectively promote the appeal of a region, attract user interest, and even generate revenue. Furthermore, by combining it with an emotion engine, it is possible to further personalize the user experience and improve customer satisfaction.

[1158] The following describes the processing flow.

[1159] Step 1:

[1160] The server collects local information. It uses APIs to retrieve information on tourist attractions, food culture, historical background, weather, etc., and stores it in a database. Specifically, it utilizes databases from local tourism bureaus and public data resources.

[1161] Step 2:

[1162] The server generates engaging content from collected local information using generative artificial intelligence. It uses text generation AI to create articles introducing tourist destinations and image generation AI to generate visuals of tourist spots. The generated content is automatically posted to social media and official local websites.

[1163] Step 3:

[1164] The device collects user activity data. It records the user's search history, location information, social media activity, etc., and sends this data to a server. For example, if a user searches for travel-related keywords, that data will be collected.

[1165] Step 4:

[1166] The server analyzes collected user activity data and generates user profiles. Using clustering algorithms, it classifies users' interests and creates individual profiles. For example, it might separate users into those who enjoy natural landscapes and those who enjoy urban tourism.

[1167] Step 5:

[1168] The server generates a customized travel plan based on the user's profile. Using generative artificial intelligence, it creates an itinerary combining suitable tourist spots, accommodations, and event information for the user. The created travel plan is then notified to the user's device.

[1169] Step 6:

[1170] The device displays suggested travel plans to the user. The user can view detailed information and customize the plan as needed. For example, if the user wants to travel on specific dates, a plan tailored to those dates will be displayed.

[1171] Step 7:

[1172] The user selects a suggested travel plan and proceeds with the booking process. After entering the required information into the booking form via their device, the booking information is sent to the server. Based on this information, the server notifies relevant service providers such as accommodations and tour guides.

[1173] Step 8:

[1174] The server notifies users of local events and activities through an emotion engine. A dashboard showing local contributions is updated via API integration. Recommended events and activities are adjusted based on the user's emotions.

[1175] Step 9:

[1176] The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions. As the user operates the device, it analyzes their emotional state in real time through the camera and microphone and reflects this in the user profile.

[1177] Step 10:

[1178] The server dynamically adjusts content and travel plans based on emotional data collected by the emotion engine. For example, if a user is pleased with a travel plan, it provides additional relevant information. Conversely, if the user looks dissatisfied, it suggests alternative options.

[1179] The above outlines the specific processing flow of this system. Through these steps, it is possible to effectively communicate the appeal of a region, attract user interest, and ultimately contribute to increased regional revenue. Furthermore, by adding an emotion engine, it is possible to further personalize the user experience and improve satisfaction.

[1180] (Example 2)

[1181] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1182] Traditional local information systems only provide basic information and lack personalized suggestions tailored to individual user interests and emotions. Furthermore, they are unable to recognize user emotions and adjust services in real time, making it difficult to increase customer satisfaction. In addition, they are insufficient in visualizing contributions to the local community and promoting monetization.

[1183] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting local information, means for generating attractive content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for recognizing emotions and dynamically adjusting the suggested content using the results, means for suggesting, booking, and managing travel plans, and means for service linkage. This enables personalized suggestions based on the user's individual interests and emotions, improving customer satisfaction, promoting monetization, and visualizing contributions to the local community.

[1184] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[1185] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates content such as text, images, and videos based on provided data.

[1186] "User profile data" refers to information about a user, including data such as their interests, behavioral history, and location information.

[1187] "Means of recognizing emotions" refers to technology that analyzes a user's facial expressions, voice, etc., to determine their emotional state.

[1188] "Personalized suggestions" refer to suggestions that are customized based on the user's individual interests, concerns, and emotional state.

[1189] "Service integration means" refers to functions that notify users of external services or event information, or that integrate with other systems.

[1190] "Promoting monetization" refers to activities that generate revenue directly or indirectly based on user usage.

[1191] This invention relates to a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue. This system features the collection of regional information, content generation using generative artificial intelligence, user profile management, and user emotion recognition by an emotion engine, along with dynamic suggestion adjustments based on the results. Specific embodiments described herein are configured as follows:

[1192] 1. Server Functions

[1193] The server is responsible for the central management of the system. It has the following functions:

[1194] Gathering local information:

[1195] The server collects local information such as tourist attractions, food culture, history, and weather from the internet and dedicated databases. For example, it uses the Google Places API and OpenWeatherMap API to retrieve information and store it in the database.

[1196] Content generation:

[1197] The server uses generative artificial intelligence (e.g., GPT-4, DALL-E) based on the collected regional information to generate engaging content such as text, images, and videos.

[1198] Example prompt: "Generate a detailed description of five must-see tourist spots in Tokyo and their highlights."

[1199] User profile management:

[1200] The server collects user interests, behavioral history, location information, etc., and generates user profiles using clustering algorithms (e.g., K-means).

[1201] Recognize emotions and adjust the proposal accordingly:

[1202] The server uses an emotion engine to analyze the user's facial expressions and voice, and dynamically adjusts content and suggestions based on the results.

[1203] 2. Device functions

[1204] A device is a smartphone or computer that serves as the user interface. It has the following functions:

[1205] Data collection:

[1206] The device records data such as the user's search history and social media activity, and periodically sends it to the server.

[1207] Content display:

[1208] The device displays content sent from the server, informing the user about the region's attractions. For example, it might display recommended tourist spots or travel plans.

[1209] Travel plan suggestions and bookings:

[1210] The terminal displays customized travel plans suggested by the server to the user and allows them to proceed with the booking process.

[1211] 3. User actions

[1212] Users are individuals or organizations that utilize the system. They perform the following actions:

[1213] Providing information of interest:

[1214] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[1215] Viewing content:

[1216] Users view recommended content through their devices and deepen their interest in the local area.

[1217] Planning and booking your trip:

[1218] Users review the suggested travel plans and book the one they like.

[1219] Feedback based on emotion recognition:

[1220] The emotion engine recognizes the user's facial expressions and voice, and adjusts the suggested content in real time.

[1221] Specific example

[1222] For example, suppose user A is interested in "natural scenery" and "hot springs." User A's device recognizes these interests and sends data to the server. Based on this profile, the server collects information on hot spring resorts in appropriate regions and uses a generative AI to generate attractive descriptions and images. The server posts the generated content to social media and notifies user A. User A uses their device to review the travel plan, and if satisfied, proceeds with the booking process.

[1223] This system allows users to receive highly personalized information and suggestions, enabling them to fully experience the charm of their local area. Furthermore, by utilizing an emotion engine, user satisfaction can be improved in real time.

[1224] The specific embodiments of the present invention are as described above, and a specific platform is used for the hardware and software to realize them.

[1225] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1226] Step 1: Gathering local information

[1227] The server collects local information such as tourist attractions, food culture, history, and weather from the internet and dedicated databases. It sends queries to the Google Places API and OpenWeatherMap API as input, and stores the returned local information data in the database as output.

[1228] Specific actions:

[1229] The server sends a request to the Google Places API regarding "tourist spots in Tokyo."

[1230] The data returned from the API (tourist spot name, location, description, etc.) is stored in the server's database.

[1231] Step 2: User Data Collection

[1232] The device collects data such as the user's search history, social media activity, and location information, and sends it to the server. It collects user behavioral data as input and sends it to the server as output.

[1233] Specific actions:

[1234] When a user searches for "Tokyo hot springs" on their smartphone, that search history is recorded on the device.

[1235] The device periodically sends this information to the server.

[1236] Step 3: Generate User Profile

[1237] The server generates user profiles using a clustering algorithm based on user interests, behavioral history, location information, etc. It takes user data as input and generates profile data as output.

[1238] Specific actions:

[1239] The server analyzes user A's past search history and social media activity data.

[1240] Using a clustering algorithm (e.g., K-means), user A is tagged as being interested in "natural scenery" and "hot springs."

[1241] Step 4: Content Generation

[1242] Based on regional information and user profiles collected by the server, engaging content such as text, images, and videos is generated using a generative AI model (e.g., GPT-4, DALL-E). Regional information, prompt text, and user profiles are provided as input, and the generated content is obtained as output.

[1243] Specific actions:

[1244] The server inputs the prompt message "Generate a description of a hot spring tourist spot in Tokyo" into the AI ​​model.

[1245] The generative AI model generates an engaging description and associated images, and saves them.

[1246] Step 5: Content Distribution

[1247] The server distributes the generated content to social media and user devices. It takes generated content data as input and outputs it to social media or sends it to user devices.

[1248] Specific actions:

[1249] The server uses the generated introductory text and images to create data for social media posts.

[1250] The system uses the SNS API to automatically post and notify user A.

[1251] Step 6: Adjusting the proposal

[1252] The emotion engine recognizes the user's facial expressions and voice, and sends that data to the server. Based on this data, the server adjusts the suggestions in real time to provide the most suitable suggestions for the user. It receives the user's emotion data as input and provides adjusted suggestions as output.

[1253] Specific actions:

[1254] When user A is viewing a travel plan, the emotion engine recognizes user A's facial expressions.

[1255] If user A is excited, the server will display additional tourist attractions and special offers.

[1256] Step 7: Travel plan proposal and booking

[1257] The terminal displays travel plans suggested by the server to the user and allows them to make a reservation. It receives travel plan data from the server as input, presents it to the user as output, and performs the reservation operation.

[1258] Specific actions:

[1259] User A uses their device to review the suggested travel plan.

[1260] Select the suggested accommodations and sightseeing tours and proceed with the booking process.

[1261] Step 8: Visualizing the degree of contribution to the local community

[1262] The device collects user activity data in the local area and displays the level of contribution to the community on a visualized dashboard. It aggregates user consumption activity data as input and displays a dashboard that visualizes the level of contribution as output.

[1263] Specific actions:

[1264] When user A makes a purchase or engages in consumption activities locally, that data is recorded on the device.

[1265] The device visualizes the level of contribution to the local community (such as an economic activity index) and displays it to user A on a dashboard.

[1266] (Application Example 2)

[1267] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1268] Traditional local information systems could provide customized content and travel plans based on users' interests, but they could not recognize users' emotions in real time and dynamically adjust content and suggestions on the spot. Furthermore, in physical stores, it was difficult to personalize in-store recommendations and promotions based on users' emotions. As a result, they failed to improve the user experience and adequately enhance monetization and customer satisfaction.

[1269] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1270] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for dynamically adjusting content and suggestions using an emotion engine that recognizes user emotions, and means for recognizing user emotions in real time within a physical store and adjusting recommended products and promotions within the store. This makes it possible to adjust suggestions in real time based on user emotions and provide a more personalized experience.

[1271] 1. "Local information" refers to information about tourist attractions, food culture, history, weather, etc., related to a specific geographical area.

[1272] 2. "Generative artificial intelligence" refers to artificial intelligence technology used to generate engaging content such as text, images, and videos from collected data.

[1273] 3. "User profile data" refers to data that includes each user's interests, behavioral history, location information, etc.

[1274] 4. An "emotion engine" is a system component that uses facial recognition and voice analysis technologies to recognize a user's emotions and adjusts content and suggestions based on those emotions.

[1275] 5. "Content" refers to digital media such as text, images, and videos that include information and entertainment elements presented to the user.

[1276] 6. "Suggestions" refer to travel plans and product information recommended to the user based on their profile data and sentiment recognition results.

[1277] 7. A "physical store" is a shop located in a physical place where users can directly view and purchase products.

[1278] 8. "Real-time" refers to instantaneous processing that responds immediately to user actions and behaviors.

[1279] 9. "Recommended products" are products that have been deemed appropriate based on the user's profile and sentiment data.

[1280] 10. "Promotion" refers to incentives and advertising activities conducted to boost sales or increase brand awareness of a product.

[1281] System Configuration

[1282] The system of the present invention consists of the following main components:

[1283] 1. Server (Central Management System)

[1284] 2. Device (user's smartphone or computer)

[1285] 3. User

[1286] 4. Emotional Engine

[1287] server

[1288] The server is a centralized management system with multiple functions. This server includes the following functions:

[1289] Gathering local information:

[1290] The server periodically collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[1291] Content generation:

[1292] Based on the collected regional information, the server uses generative artificial intelligence (such as GPT-3) to generate engaging content such as text, images, and videos. This content is then posted to social media and websites.

[1293] User profile management:

[1294] The server collects each user's interests, behavioral history, location information, etc., and uses this data to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[1295] Processing emotion recognition data:

[1296] The server receives emotional data sent from the emotion engine and reflects it in the user's profile. Based on this data, it adjusts content and suggestions in real time.

[1297] terminal

[1298] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[1299] Data collection:

[1300] The device records the user's search history, social media activity, etc., and sends it to the server.

[1301] Content display:

[1302] The terminal displays content sent from the server, informing users about the attractions of the region.

[1303] Travel plan suggestions and bookings:

[1304] The terminal displays customized travel plans suggested by the server to the user and allows them to proceed with the booking process.

[1305] Real-time emotion recognition:

[1306] In physical stores, smart glasses or head-mounted displays are used as terminals to recognize the user's emotions in real time. This emotion data is then sent to a server, and recommended products and promotional information are displayed as appropriate.

[1307] user

[1308] Users are individuals or organizations that utilize the system and perform the following actions:

[1309] Providing information of interest:

[1310] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[1311] Viewing content:

[1312] Users view recommended content through their devices and deepen their interest in the local area.

[1313] Planning and booking your trip:

[1314] Users review the suggested travel plans and book the one they like.

[1315] Emotional Engine

[1316] The emotion engine is a system component that recognizes user emotions and adjusts content and suggestions based on those emotions. This emotion engine includes the following features:

[1317] Emotion recognition:

[1318] The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions and reflects the results in the user profile. For example, it could use a facial recognition library such as DeepFace.

[1319] Real-time adjustment:

[1320] The emotion engine monitors user emotions in real time and dynamically changes content to improve the user's customer experience.

[1321] Specific usage examples

[1322] For example, imagine a user in a physical store wearing smart glasses and browsing the merchandise. When the emotion engine recognizes the user's facial expression and detects "joy," the server receives this emotion data and displays suitable product recommendations and promotional information on the smart glasses' display. This allows the user to have a more enjoyable shopping experience. Furthermore, the emotion engine can adjust its suggestions in real time based on the user's emotional changes, leading to improved customer satisfaction.

[1323] Example of a prompt

[1324] For example, it is possible to input prompt statements like the following into the generation AI model:

[1325] We want to offer the best possible promotion when our users are happy. Please tell us the specific product name and offer details.

[1326] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1327] Step 1:

[1328] The server collects local information from the internet and dedicated databases. Specifically, it uses APIs to retrieve information such as tourist attractions, food culture, history, and weather, and stores this data in the database.

[1329] Input: Local information such as tourist attractions, food culture, history, and weather.

[1330] Output: Regional information stored in the database.

[1331] Step 2:

[1332] The server uses generative artificial intelligence to generate content such as text, images, and videos based on collected regional information. Specifically, it uses GPT-3 and image generation models to create engaging content and posts it to social media and websites.

[1333] Input: Local information.

[1334] Output: Generated content such as text, images, and videos.

[1335] Step 3:

[1336] The server collects and analyzes user profile data, such as interests, behavioral history, and location information. It uses clustering algorithms to classify user preferences.

[1337] Input: User profile data such as interests, behavioral history, and location information.

[1338] Output: Classified user profiles.

[1339] Step 4:

[1340] The device recognizes the user's emotions in real time and sends that data to a server. Specifically, it uses cameras built into smart glasses or head-mounted displays to perform facial recognition and voice analysis technologies.

[1341] Input: User's facial expressions and voice data.

[1342] Output: Recognized emotion data.

[1343] Step 5:

[1344] The server receives sentiment data sent from the sentiment engine and reflects it in the user profile. Based on the sentiment data, content and suggestions are adjusted in real time.

[1345] Input: Sentiment data.

[1346] Output: Edited content and suggestions.

[1347] Step 6:

[1348] The terminal displays customized travel plans sent from the server to the user and allows them to make a reservation. In physical stores, it also displays recommended products and promotional information based on the user profile and sentiment data.

[1349] Input: Customized travel plans and content tailored in real time.

[1350] Output: Travel plans and promotional information displayed to the user.

[1351] Step 7:

[1352] Users review the suggested travel plans and, if they like them, proceed with the booking process. In physical stores, they purchase products based on the displayed recommended items and promotional information.

[1353] Input: Customized travel plans and promotional information.

[1354] Output: Booked travel plans and purchased items.

[1355] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1356] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1357] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1358] [Fourth Embodiment]

[1359] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1360] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1361] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1362] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1363] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1364] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1365] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1366] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1367] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1368] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1369] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1370] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1371] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1372] The present invention provides a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue. The specific embodiments described herein are configured as follows.

[1373] System Configuration

[1374] This system consists of the following main components:

[1375] 1. Server (Central Management System)

[1376] 2. Device (user's smartphone or computer)

[1377] 3. User

[1378] server

[1379] The server is a centralized management system with multiple functions. This server includes the following functions:

[1380] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[1381] Content Generation: Based on collected local information, the server uses generative artificial intelligence to generate engaging content such as text, images, and videos. This content is automatically posted to social media and websites for widespread sharing.

[1382] User Profile Management: The server collects information such as each user's interests, behavioral history, and location, and uses this information to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[1383] terminal

[1384] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[1385] Data collection: The device records the user's search history, social media activity, etc., and sends it to the server.

[1386] Content display: The device displays content sent from the server, informing the user about the local attractions.

[1387] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[1388] user

[1389] Users are individuals or organizations that utilize the system and perform the following actions:

[1390] Providing interest information: Users can provide the system with their search history and preferences to receive more personalized suggestions.

[1391] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[1392] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[1393] Specific usage examples

[1394] For example, suppose a user is interested in natural landscapes and hot springs. The user's device identifies these interests from their past search history and social media activity, and sends this data to the server. The server then gathers information on appropriate hot spring resorts in the user's region, tailored to their profile, and uses generative AI to create compelling descriptions and images. Next, the server posts this content to social media and notifies the user.

[1395] Users receive the notification and, if interested, check the suggested travel plan on their device. The plan includes information on how to access the hot spring resort, accommodations, and local activities. If the user is satisfied with the plan, they proceed with the booking process through their device. This booking data is aggregated on a server and automatically notified to the relevant service providers.

[1396] Furthermore, users can utilize a dashboard that visualizes their contribution to the local community during their activities, allowing them to truly understand how much their efforts are benefiting the region. This encourages users to develop a greater interest in and involvement with the local community.

[1397] The above describes a specific embodiment of the present invention. This system makes it possible to effectively promote the appeal of a region, attract user interest, and even generate revenue.

[1398] The following describes the processing flow.

[1399] Step 1:

[1400] The server collects local information. This local information includes tourist attractions, food culture, historical background, and weather information. Specifically, the server uses APIs to retrieve this information from the internet and databases, and stores the collected information in the database.

[1401] Step 2:

[1402] The server generates engaging content from local information collected using generative artificial intelligence. It uses text generation AI to create introductory articles about the region and image generation AI to create visuals of tourist attractions. The generated content is then posted to social media and websites.

[1403] Step 3:

[1404] The device collects user activity data. For example, the device records the user's search history, location information, and social media activity, and sends this data to a server. This data is used for subsequent analysis.

[1405] Step 4:

[1406] The server analyzes collected user activity data and generates user profiles. It uses clustering algorithms to classify user interests and create individual profiles. Based on these profiles, it is ready to suggest the most relevant local information to the user.

[1407] Step 5:

[1408] The server generates a customized travel plan based on the user's profile. The server selects tourist attractions, accommodations, and event information that match the user's interests, and uses generative artificial intelligence to create an attractive itinerary. The user is then notified of the created travel plan.

[1409] Step 6:

[1410] The device displays suggested travel plans to the user. The user can review the details of the travel plans through the device and select the plan that best suits their needs. If the user is satisfied with the travel plan, they can proceed with the booking process.

[1411] Step 7:

[1412] The user selects a suggested travel plan and proceeds with the booking process. This confirms the travel plan, and the user's booking data is sent to the server. The server then notifies the relevant service providers (e.g., accommodation, tour guides) of the booking information.

[1413] Step 8:

[1414] The server notifies users of local events and activities through SBG services. It updates a community contribution dashboard via API integration, visually showing users their level of community contribution. This provides users with motivation to participate in further activities and events.

[1415] The above outlines the specific processing flow of this system. Through these steps, it is possible to effectively communicate the appeal of the region, attract user interest, and ultimately contribute to increasing the region's revenue.

[1416] (Example 1)

[1417] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1418] Conventional regional information systems had limited information gathering and analysis capabilities, and did not adequately customize information based on user interests. As a result, it was difficult for users to fully understand and develop an interest in the region's attractions. Furthermore, efficient suggestions were not provided for travel plan generation and booking, making monetization a challenge.

[1419] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1420] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for proposing customized travel plans based on user profiles, means for booking and managing travel plans to promote monetization, means for notifying users of local service activities and event information, means for generating content based on prompt sentences using a generative artificial intelligence model, and means for classifying user interests using a clustering algorithm. This makes it possible to provide users with more personalized information and engaging travel plans.

[1421] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[1422] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates content such as text, images, and videos based on collected data.

[1423] "User profile data" refers to data such as a user's interests, behavioral history, and location information.

[1424] A "clustering algorithm" refers to a statistical method for grouping similar user data.

[1425] A "prompt message" refers to text input used to instruct a generative artificial intelligence system to generate specific information.

[1426] A "travel plan" refers to a detailed plan for a trip to a specific region.

[1427] "Monetization" refers to the process of generating profit from the services or information provided.

[1428] "Community service activities" refer to public services or volunteer activities carried out in a specific area.

[1429] "Event information" refers to detailed information about events held in a specific region.

[1430] This invention is a system that effectively promotes the appeal of a region, attracts user interest, and facilitates monetization. The specific form of implementing this system is configured as follows.

[1431] System Configuration

[1432] This system consists of the following main components:

[1433] 1. Server (Central Management System)

[1434] 2. Device (user's smartphone or computer)

[1435] 3. User

[1436] server

[1437] A server is a centralized management system with multiple functions. The server has the following functions:

[1438] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[1439] Specific example: The server retrieves information about "AA Hot Spring Resort" from a tourism information API and saves it to a database.

[1440] Content generation using generative artificial intelligence (AI): Based on collected regional information, the server uses generative AI (e.g., OpenAI GPT-4) to generate engaging content such as text, images, and videos. The generated content is automatically posted to social media and websites.

[1441] Example of a prompt: The server sends a prompt to the AI ​​generating the following: "Please introduce a region famous for its hot springs. Please include the region's history, the characteristics of the hot springs, and nearby tourist attractions." The AI ​​then generates a detailed introduction.

[1442] User Profile Management: The server collects each user's interests, behavioral history, location information, etc., and generates and analyzes user profiles based on this data. A clustering algorithm is used to classify user interests.

[1443] Specific example: The device sends search history such as "hot springs" and "hiking" to the server, and the server clusters user profiles as "users interested in nature and hot springs."

[1444] Travel plan suggestion: The server generates a customized travel plan based on the user profile and sends it to the device.

[1445] Specific example: The server generates a "travel plan to a hot spring resort" and sends it to the terminal.

[1446] Travel plan booking and management: The server books and manages the travel plans selected by the user. Booking data is automatically notified to the relevant service provider.

[1447] Specific example: Users use their devices to make reservations for accommodations and activities, and the server aggregates the reservation information and notifies the accommodations.

[1448] Notification function: The server notifies users of information about local service activities and events.

[1449] Specific example: A server collects information about local events and notifies users.

[1450] terminal

[1451] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. Its main functions are as follows:

[1452] Data collection: The device records the user's search history and social media activity and sends it to the server.

[1453] Specific example: The device monitors the user's past social media activity and sends topics of interest to the server.

[1454] Content display: The device displays content sent from the server, providing users with information about the local area.

[1455] Specific example: A message titled "Introduction to a new hot spring resort" appears on the user's smartphone, and the user views the details.

[1456] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[1457] Specific example: A user checks their travel plan on their smartphone and completes the booking process.

[1458] user

[1459] Users are individuals or organizations that utilize the system and perform the following actions:

[1460] Providing interest information: Users provide the system with their search history and preferences to receive more personalized suggestions.

[1461] Specific example: A user searches for terms like "hot springs" or "natural scenery," and their search history is saved on the server.

[1462] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[1463] Specific example: A user views a "hot spring resort introduction" on their smartphone.

[1464] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[1465] Specific example: A user uses their device to check travel plans and book accommodations.

[1466] The above describes a specific embodiment of the present invention. This system allows users to receive attractive local information and easily book customized travel plans. It also enables effective promotion of local attractions and facilitates monetization.

[1467] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1468] Step 1:

[1469] The server collects local information. Specifically, it periodically retrieves information such as tourist spots, food culture, history, and weather related to the region from the internet and dedicated databases using APIs, and stores it in the database.

[1470] Input: Request from the Tourism Information API

[1471] Output: Latest regional information from the database

[1472] Example of operation: The server requests information about "AA Hot Spring Resort" from the tourism information API and saves the retrieved data to the database.

[1473] Step 2:

[1474] The device records the user's search history and social media activity and sends it to the server. This allows the server to collect information about the user's interests, behavioral history, and location.

[1475] Input: User's search history, social media activity data

[1476] Output: Data stored in the user database on the server.

[1477] Example of operation: The device records the user's search history, such as "hot springs" and "natural scenery," and sends it to the server.

[1478] Step 3:

[1479] The server generates and analyzes user profiles using a clustering algorithm based on the collected user data.

[1480] Input: User's search history, social media activity data

[1481] Output: Classified user profile data

[1482] Example of operation: The server uses a clustering algorithm to classify users as "interested in nature and hot springs."

[1483] Step 4:

[1484] The server uses generative AI to generate engaging content based on collected local information and user profiles. Prompts are used to prompt the AI ​​to generate specific information.

[1485] Input: Regional information, user profile data, prompt text

[1486] Output: Generated content such as text, images, and videos.

[1487] Example of operation: The server generates content using the following prompt for the AI: "Please introduce a region famous for its hot springs. Please describe the region's history, the characteristics of the hot springs, and nearby tourist attractions."

[1488] Step 5:

[1489] The server automatically posts the generated content to social media and websites and notifies relevant users.

[1490] Input: Generated content

[1491] Output: Posts to social media and websites, notifications to users

[1492] Example of operation: The server posts "introductions to hot spring resorts" to Facebook and Twitter, and sends notifications to interested users.

[1493] Step 6:

[1494] The device receives notifications sent from the server and displays them to the user. The user views the content via a smartphone or computer.

[1495] Input: Notification from server

[1496] Output: Content displayed on the user's device

[1497] Example of operation: An advertisement for a new hot spring resort is displayed on the user's smartphone, and the user views the content in detail.

[1498] Step 7:

[1499] The server generates a customized travel plan based on the user's profile and sends it to the device. The user reviews the plan on the device and proceeds with the booking process if they like it.

[1500] Input: User profile data

[1501] Output: Generated customized travel plan

[1502] Example of operation: The server generates a "travel plan to a hot spring resort" and sends it to the terminal. The user checks the plan on the terminal and makes reservations for accommodations and activities.

[1503] Step 8:

[1504] The terminal sends the reservation data entered by the user to the server, and the server completes the reservation process. The server aggregates this data and notifies the relevant service providers.

[1505] Input: User's reservation data

[1506] Output: Booking completion data, notification to service provider

[1507] Example of operation: A user makes a reservation for accommodation using their device, that information is sent to the server, and the server notifies the accommodation.

[1508] The above outlines the specific processing steps and operation of this system. This system allows users to receive attractive local information, easily book customized travel plans, effectively promote the region's appeal, and facilitate monetization.

[1509] (Application Example 1)

[1510] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1511] In systems designed to effectively promote local attractions, attract user interest, and generate revenue, there is a lack of means to provide in-store promotions and special offers tailored to user interests. Furthermore, it is difficult to effectively classify user profiles in detail based on collected data and propose personalized travel plans and event information. There is also a need for a system to analyze and optimize the effectiveness of these promotions and suggestions.

[1512] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1513] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for proposing customized travel plans based on user profiles, means for booking and managing travel plans to promote monetization, means for service integration to notify users of local service activities and event information, and means for providing promotional information for physical stores and displaying special offers and coupons based on user interests. This enables effective promotion of the region's attractions, provides personalized information to users, promotes purchases at physical stores, and proposes travel plans based on user interests.

[1514] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[1515] "Generative artificial intelligence" refers to artificial intelligence that has algorithms to generate content such as text, images, and videos from input data.

[1516] "User profile data" refers to data that shows individual information about a user, such as their interests, behavioral history, and location information.

[1517] A "customized travel plan" is a travel schedule that is personalized and provided to the user based on their user profile data.

[1518] "Means for booking and managing travel plans" refers to system elements that allow users to book suggested travel plans and manage them afterward.

[1519] A "service linkage system" is a linkage system used to notify users of information about local community service activities and events.

[1520] "In-store promotional information" refers to information such as discounts, coupons, and special offers offered at physical stores.

[1521] Modes for carrying out the invention

[1522] This invention provides a system that effectively promotes the appeal of a region, attracts user interest, and leads to monetization. This system mainly consists of three components: a server, terminals, and users.

[1523] System Configuration

[1524] server

[1525] The server is a central management system with the following main functions. This server includes the following functions:

[1526] 1. Gathering local information

[1527] The server uses APIs (for example, travel data APIs) to periodically collect information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. This information is used as input data for generative artificial intelligence (AI), which will be discussed later.

[1528] 2. Content Generation

[1529] The server uses generative artificial intelligence (e.g., GPT-4) to generate engaging content such as text, images, and videos based on collected regional information. For example, it can generate content based on prompts such as, "Please create text and images to promote the charm of the region. Regional information: Ohori Park, a famous tourist spot in Fukuoka City, offers beautiful Japanese gardens and boating. The park also has many stylish cafes and attracts many tourists on weekends. Please also introduce mentaiko, a famous Fukuoka specialty."

[1530] 3. Database Management

[1531] The server uses relational databases such as MySQL to manage generated content and user information.

[1532] 4. User Profile Management and Analysis

[1533] Using machine learning algorithms (for example, Scikit-learn's clustering algorithm), we generate and analyze user profiles based on their interests and behavioral history, and then provide personalized suggestions.

[1534] 5. Linked to physical stores

[1535] Based on user interests, the system displays promotional information, special offers, and coupons for physical stores (e.g., restaurants, souvenir shops, etc.).

[1536] terminal

[1537] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[1538] 1. Data Collection

[1539] The device records the user's search history, social media activity, etc., and sends it to the server.

[1540] 2. Content Display

[1541] The system displays content and promotional information sent from the server, informing users about the region's attractions. It also offers special offers and coupons.

[1542] 3. Reservation function

[1543] Make reservations for the proposed travel plans and events.

[1544] user

[1545] Users are individuals or organizations that utilize the system and perform the following actions:

[1546] 1. Providing information of interest

[1547] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[1548] 2. Viewing content

[1549] Users view suggested content through their devices and deepen their interest in the local area.

[1550] 3. Deciding on and booking your travel plan.

[1551] Users review the suggested travel plans and book the one they like. They can also take advantage of local store information and special offers.

[1552] This system will effectively promote the attractions of the region, provide users with personalized information, and enable increased sales at physical stores as well as the suggestion of travel plans based on users' interests.

[1553] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1554] Step 1:

[1555] The server uses APIs to collect local information from the internet and dedicated databases. The input to this process is requests obtained from the API, and the output is information related to the region, such as tourist attractions, food culture, history, and weather. This data is then input into the generating AI in the next step.

[1556] Step 2:

[1557] The server generates content using generative artificial intelligence (e.g., GPT-4) based on collected regional information. The input to this process is regional information and prompt text, while the output is engaging content such as generated text, images, and videos. Specifically, prompt text is used to instruct the AI, which then generates the content.

[1558] Step 3:

[1559] The server saves the generated content to a relational database such as MySQL. The input to this process is the generated content, and the output is the content data stored in the database. Specifically, it creates an SQL query and inserts the content data into the database.

[1560] Step 4:

[1561] The device records the user's search history and social media activity and sends it to the server. The input to this process is the user's operation log, and the output is user data sent to the server. Specifically, it collects data locally and then makes an API request to send it to the server.

[1562] Step 5:

[1563] The server manages user profiles and analyzes user interests using machine learning algorithms (e.g., Scikit-learn). The input to this process is user data, and the output is clustered user profiles. Specifically, it applies a clustering algorithm to classify users according to their interests.

[1564] Step 6:

[1565] The server generates travel plans and event information based on user interests and sends them to the device. The input to this process is clustered user profiles and generated content, while the output is customized travel plans and event information. Specifically, it selects appropriate information based on the user profile and sends push notifications or displays them on the device.

[1566] Step 7:

[1567] The terminal displays customized travel plans and event information to the user, and provides promotional information, special offers, and coupons for physical stores. The input for this process is information sent from the server, and the output is the displayed travel plan and coupon information. Specifically, the system displays the information appropriately on the user interface, making it easily accessible to the user.

[1568] Step 8:

[1569] Users review the displayed customized travel plans and in-store promotional information, and make reservations or use coupons as needed. The input for this process is the information displayed on the terminal, and the output is reservation data and coupon usage history. Specific actions include reviewing travel plan details and entering coupon codes.

[1570] Step 9:

[1571] The server aggregates user reservation history and coupon usage data to optimize effective advertising campaigns and promotional strategies. The input to this process is reservation data and coupon usage history, while the output is optimized advertising campaign and promotional data. Specifically, it performs data analysis and selects the most suitable strategies.

[1572] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1573] This invention combines a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue with an emotion engine that recognizes user emotions. The specific embodiments described herein are configured as follows.

[1574] System Configuration

[1575] This system consists of the following main components:

[1576] 1. Server (Central Management System)

[1577] 2. Device (user's smartphone or computer)

[1578] 3. User

[1579] 4. Emotional Engine

[1580] server

[1581] The server is a centralized management system with multiple functions. This server includes the following functions:

[1582] Local Information Collection: The server regularly collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[1583] Content Generation: Based on collected local information, the server uses generative artificial intelligence to generate engaging content such as text, images, and videos. This content is then posted to social media and websites.

[1584] User Profile Management: The server collects information such as each user's interests, behavioral history, and location, and uses this information to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[1585] terminal

[1586] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[1587] Data collection: The device records the user's search history, social media activity, etc., and sends it to the server.

[1588] Content display: The device displays content sent from the server, informing the user about the local attractions.

[1589] Travel plan suggestion and booking: The terminal displays customized travel plans suggested by the server to the user, and allows them to proceed with the booking process.

[1590] user

[1591] Users are individuals or organizations that utilize the system and perform the following actions:

[1592] Providing interest information: Users can provide the system with their search history and preferences to receive more personalized suggestions.

[1593] Content Viewing: Users view recommended content through their devices, deepening their interest in the local area.

[1594] Travel plan selection and booking: Users review the suggested travel plans and book the one they like.

[1595] Emotional Engine

[1596] The emotion engine is a system component that recognizes user emotions and adjusts content and suggestions based on those emotions. This emotion engine includes the following features:

[1597] Emotion Recognition: The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions and reflects the results in the user profile.

[1598] Real-time adjustment: The emotion engine monitors user emotions in real time and dynamically changes content to improve the user's customer experience.

[1599] Specific usage examples

[1600] For example, suppose a user is interested in natural landscapes and hot springs. The user's device identifies these interests from their past search history and social media activity, and sends this data to the server. The server then gathers information on appropriate hot spring resorts in the user's region, tailored to their profile, and uses generative AI to create compelling descriptions and images. Next, the server posts this content to social media and notifies the user.

[1601] Users receive the notification and, if interested, check the suggested travel plan on their device. The plan includes information on how to access the hot spring resort, accommodations, and local activities. If the user is satisfied with the plan, they proceed with the booking process through their device. This booking data is aggregated on a server and automatically notified to the relevant service providers.

[1602] In this process, the emotion engine recognizes the user's emotions from their facial expressions and voice, and adjusts the suggestions according to the user's emotional state. For example, if the user is excited about a particular plan, additional information is provided to emphasize that plan. On the other hand, if the user looks dissatisfied, a different suggestion is presented to increase their satisfaction.

[1603] Furthermore, users can utilize a dashboard that visualizes their contribution to the local community during their activities, allowing them to truly understand how much their efforts are benefiting the region. This encourages users to develop a greater interest in and involvement with the local community.

[1604] The above describes specific embodiments of the present invention. This system makes it possible to effectively promote the appeal of a region, attract user interest, and even generate revenue. Furthermore, by combining it with an emotion engine, it is possible to further personalize the user experience and improve customer satisfaction.

[1605] The following describes the processing flow.

[1606] Step 1:

[1607] The server collects local information. It uses APIs to retrieve information on tourist attractions, food culture, historical background, weather, etc., and stores it in a database. Specifically, it utilizes databases from local tourism bureaus and public data resources.

[1608] Step 2:

[1609] The server generates engaging content from collected local information using generative artificial intelligence. It uses text generation AI to create articles introducing tourist destinations and image generation AI to generate visuals of tourist spots. The generated content is automatically posted to social media and official local websites.

[1610] Step 3:

[1611] The device collects user activity data. It records the user's search history, location information, social media activity, etc., and sends this data to a server. For example, if a user searches for travel-related keywords, that data will be collected.

[1612] Step 4:

[1613] The server analyzes collected user activity data and generates user profiles. Using clustering algorithms, it classifies users' interests and creates individual profiles. For example, it might separate users into those who enjoy natural landscapes and those who enjoy urban tourism.

[1614] Step 5:

[1615] The server generates a customized travel plan based on the user's profile. Using generative artificial intelligence, it creates an itinerary combining suitable tourist spots, accommodations, and event information for the user. The created travel plan is then notified to the user's device.

[1616] Step 6:

[1617] The device displays suggested travel plans to the user. The user can view detailed information and customize the plan as needed. For example, if the user wants to travel on specific dates, a plan tailored to those dates will be displayed.

[1618] Step 7:

[1619] The user selects a suggested travel plan and proceeds with the booking process. After entering the required information into the booking form via their device, the booking information is sent to the server. Based on this information, the server notifies relevant service providers such as accommodations and tour guides.

[1620] Step 8:

[1621] The server notifies users of local events and activities through an emotion engine. A dashboard showing local contributions is updated via API integration. Recommended events and activities are adjusted based on the user's emotions.

[1622] Step 9:

[1623] The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions. As the user operates the device, it analyzes their emotional state in real time through the camera and microphone and reflects this in the user profile.

[1624] Step 10:

[1625] The server dynamically adjusts content and travel plans based on emotional data collected by the emotion engine. For example, if a user is pleased with a travel plan, it provides additional relevant information. Conversely, if the user looks dissatisfied, it suggests alternative options.

[1626] The above outlines the specific processing flow of this system. Through these steps, it is possible to effectively communicate the appeal of a region, attract user interest, and ultimately contribute to increased regional revenue. Furthermore, by adding an emotion engine, it is possible to further personalize the user experience and improve satisfaction.

[1627] (Example 2)

[1628] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1629] Traditional local information systems only provide basic information and lack personalized suggestions tailored to individual user interests and emotions. Furthermore, they are unable to recognize user emotions and adjust services in real time, making it difficult to increase customer satisfaction. In addition, they are insufficient in visualizing contributions to the local community and promoting monetization.

[1630] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting local information, means for generating attractive content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for recognizing emotions and dynamically adjusting the suggested content using the results, means for suggesting, booking, and managing travel plans, and means for service linkage. This enables personalized suggestions based on the user's individual interests and emotions, improving customer satisfaction, promoting monetization, and visualizing contributions to the local community.

[1631] "Local information" refers to information about a specific region, such as tourist attractions, food culture, history, and weather.

[1632] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates content such as text, images, and videos based on provided data.

[1633] "User profile data" refers to information about a user, including data such as their interests, behavioral history, and location information.

[1634] "Means of recognizing emotions" refers to technology that analyzes a user's facial expressions, voice, etc., to determine their emotional state.

[1635] "Personalized suggestions" refer to suggestions that are customized based on the user's individual interests, concerns, and emotional state.

[1636] "Service integration means" refers to functions that notify users of external services or event information, or that integrate with other systems.

[1637] "Promoting monetization" refers to activities that generate revenue directly or indirectly based on user usage.

[1638] This invention relates to a system for effectively promoting the appeal of a region, attracting user interest, and generating revenue. This system features the collection of regional information, content generation using generative artificial intelligence, user profile management, and user emotion recognition by an emotion engine, along with dynamic suggestion adjustments based on the results. Specific embodiments described herein are configured as follows:

[1639] 1. Server Functions

[1640] The server is responsible for the central management of the system. It has the following functions:

[1641] Gathering local information:

[1642] The server collects local information such as tourist attractions, food culture, history, and weather from the internet and dedicated databases. For example, it uses the Google Places API and OpenWeatherMap API to retrieve information and store it in the database.

[1643] Content generation:

[1644] The server uses generative artificial intelligence (e.g., GPT-4, DALL-E) based on the collected regional information to generate engaging content such as text, images, and videos.

[1645] Example prompt: "Generate a detailed description of five must-see tourist spots in Tokyo and their highlights."

[1646] User profile management:

[1647] The server collects user interests, behavioral history, location information, etc., and generates user profiles using clustering algorithms (e.g., K-means).

[1648] Recognize emotions and adjust the proposal accordingly:

[1649] The server uses an emotion engine to analyze the user's facial expressions and voice, and dynamically adjusts content and suggestions based on the results.

[1650] 2. Device functions

[1651] A device is a smartphone or computer that serves as the user interface. It has the following functions:

[1652] Data collection:

[1653] The device records data such as the user's search history and social media activity, and periodically sends it to the server.

[1654] Content display:

[1655] The device displays content sent from the server, informing the user about the region's attractions. For example, it might display recommended tourist spots or travel plans.

[1656] Travel plan suggestions and bookings:

[1657] The terminal displays customized travel plans suggested by the server to the user and allows them to proceed with the booking process.

[1658] 3. User actions

[1659] Users are individuals or organizations that utilize the system. They perform the following actions:

[1660] Providing information of interest:

[1661] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[1662] Viewing content:

[1663] Users view recommended content through their devices and deepen their interest in the local area.

[1664] Planning and booking your trip:

[1665] Users review the suggested travel plans and book the one they like.

[1666] Feedback based on emotion recognition:

[1667] The emotion engine recognizes the user's facial expressions and voice, and adjusts the suggested content in real time.

[1668] Specific example

[1669] For example, suppose user A is interested in "natural scenery" and "hot springs." User A's device recognizes these interests and sends data to the server. Based on this profile, the server collects information on hot spring resorts in appropriate regions and uses a generative AI to generate attractive descriptions and images. The server posts the generated content to social media and notifies user A. User A uses their device to review the travel plan, and if satisfied, proceeds with the booking process.

[1670] This system allows users to receive highly personalized information and suggestions, enabling them to fully experience the charm of their local area. Furthermore, by utilizing an emotion engine, user satisfaction can be improved in real time.

[1671] The specific embodiments of the present invention are as described above, and a specific platform is used for the hardware and software to realize them.

[1672] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1673] Step 1: Gathering local information

[1674] The server collects local information such as tourist attractions, food culture, history, and weather from the internet and dedicated databases. It sends queries to the Google Places API and OpenWeatherMap API as input, and stores the returned local information data in the database as output.

[1675] Specific actions:

[1676] The server sends a request to the Google Places API regarding "tourist spots in Tokyo."

[1677] The data returned from the API (tourist spot name, location, description, etc.) is stored in the server's database.

[1678] Step 2: User Data Collection

[1679] The device collects data such as the user's search history, social media activity, and location information, and sends it to the server. It collects user behavioral data as input and sends it to the server as output.

[1680] Specific actions:

[1681] When a user searches for "Tokyo hot springs" on their smartphone, that search history is recorded on the device.

[1682] The device periodically sends this information to the server.

[1683] Step 3: Generate User Profile

[1684] The server generates user profiles using a clustering algorithm based on user interests, behavioral history, location information, etc. It takes user data as input and generates profile data as output.

[1685] Specific actions:

[1686] The server analyzes user A's past search history and social media activity data.

[1687] Using a clustering algorithm (e.g., K-means), user A is tagged as being interested in "natural scenery" and "hot springs."

[1688] Step 4: Content Generation

[1689] Based on regional information and user profiles collected by the server, engaging content such as text, images, and videos is generated using a generative AI model (e.g., GPT-4, DALL-E). Regional information, prompt text, and user profiles are provided as input, and the generated content is obtained as output.

[1690] Specific actions:

[1691] The server inputs the prompt message "Generate a description of a hot spring tourist spot in Tokyo" into the AI ​​model.

[1692] The generative AI model generates an engaging description and associated images, and saves them.

[1693] Step 5: Content Distribution

[1694] The server distributes the generated content to social media and user devices. It takes generated content data as input and outputs it to social media or sends it to user devices.

[1695] Specific actions:

[1696] The server uses the generated introductory text and images to create data for social media posts.

[1697] The system uses the SNS API to automatically post and notify user A.

[1698] Step 6: Adjusting the proposal

[1699] The emotion engine recognizes the user's facial expressions and voice, and sends that data to the server. Based on this data, the server adjusts the suggestions in real time to provide the most suitable suggestions for the user. It receives the user's emotion data as input and provides adjusted suggestions as output.

[1700] Specific actions:

[1701] When user A is viewing a travel plan, the emotion engine recognizes user A's facial expressions.

[1702] If user A is excited, the server will display additional tourist attractions and special offers.

[1703] Step 7: Travel plan proposal and booking

[1704] The terminal displays travel plans suggested by the server to the user and allows them to make a reservation. It receives travel plan data from the server as input, presents it to the user as output, and performs the reservation operation.

[1705] Specific actions:

[1706] User A uses their device to review the suggested travel plan.

[1707] Select the suggested accommodations and sightseeing tours and proceed with the booking process.

[1708] Step 8: Visualizing the degree of contribution to the local community

[1709] The device collects user activity data in the local area and displays the level of contribution to the community on a visualized dashboard. It aggregates user consumption activity data as input and displays a dashboard that visualizes the level of contribution as output.

[1710] Specific actions:

[1711] When user A makes a purchase or engages in consumption activities locally, that data is recorded on the device.

[1712] The device visualizes the level of contribution to the local community (such as an economic activity index) and displays it to user A on a dashboard.

[1713] (Application Example 2)

[1714] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1715] Traditional local information systems could provide customized content and travel plans based on users' interests, but they could not recognize users' emotions in real time and dynamically adjust content and suggestions on the spot. Furthermore, in physical stores, it was difficult to personalize in-store recommendations and promotions based on users' emotions. As a result, they failed to improve the user experience and adequately enhance monetization and customer satisfaction.

[1716] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1717] In this invention, the server includes means for collecting local information, means for generating engaging content from the collected local information using generative artificial intelligence, means for collecting and analyzing user profile data, means for dynamically adjusting content and suggestions using an emotion engine that recognizes user emotions, and means for recognizing user emotions in real time within a physical store and adjusting recommended products and promotions within the store. This makes it possible to adjust suggestions in real time based on user emotions and provide a more personalized experience.

[1718] 1. "Local information" refers to information about tourist attractions, food culture, history, weather, etc., related to a specific geographical area.

[1719] 2. "Generative artificial intelligence" refers to artificial intelligence technology used to generate engaging content such as text, images, and videos from collected data.

[1720] 3. "User profile data" refers to data that includes each user's interests, behavioral history, location information, etc.

[1721] 4. An "emotion engine" is a system component that uses facial recognition and voice analysis technologies to recognize a user's emotions and adjusts content and suggestions based on those emotions.

[1722] 5. "Content" refers to digital media such as text, images, and videos that include information and entertainment elements presented to the user.

[1723] 6. "Suggestions" refer to travel plans and product information recommended to the user based on their profile data and sentiment recognition results.

[1724] 7. A "physical store" is a shop located in a physical place where users can directly view and purchase products.

[1725] 8. "Real-time" refers to instantaneous processing that responds immediately to user actions and behaviors.

[1726] 9. "Recommended products" are products that have been deemed appropriate based on the user's profile and sentiment data.

[1727] 10. "Promotion" refers to incentives and advertising activities conducted to boost sales or increase brand awareness of a product.

[1728] System Configuration

[1729] The system of the present invention consists of the following main components:

[1730] 1. Server (Central Management System)

[1731] 2. Device (user's smartphone or computer)

[1732] 3. User

[1733] 4. Emotional Engine

[1734] server

[1735] The server is a centralized management system with multiple functions. This server includes the following functions:

[1736] Gathering local information:

[1737] The server periodically collects information related to the region, such as tourist attractions, food culture, history, and weather, from the internet and dedicated databases. For example, it might use an API to retrieve tourist information and store it in the database.

[1738] Content generation:

[1739] Based on the collected regional information, the server uses generative artificial intelligence (such as GPT-3) to generate engaging content such as text, images, and videos. This content is then posted to social media and websites.

[1740] User profile management:

[1741] The server collects each user's interests, behavioral history, location information, etc., and uses this data to generate and analyze user profiles. For example, it uses clustering algorithms to classify user preferences.

[1742] Processing emotion recognition data:

[1743] The server receives emotional data sent from the emotion engine and reflects it in the user's profile. Based on this data, it adjusts content and suggestions in real time.

[1744] terminal

[1745] A device is the interface that a user accesses, and includes smartphones, computers, and other devices. The main functions of a device are as follows:

[1746] Data collection:

[1747] The device records the user's search history, social media activity, etc., and sends it to the server.

[1748] Content display:

[1749] The terminal displays content sent from the server, informing users about the attractions of the region.

[1750] Travel plan suggestions and bookings:

[1751] The terminal displays customized travel plans suggested by the server to the user and allows them to proceed with the booking process.

[1752] Real-time emotion recognition:

[1753] In physical stores, smart glasses or head-mounted displays are used as terminals to recognize the user's emotions in real time. This emotion data is then sent to a server, and recommended products and promotional information are displayed as appropriate.

[1754] user

[1755] Users are individuals or organizations that utilize the system and perform the following actions:

[1756] Providing information of interest:

[1757] Users can provide the system with their search history and preferences to receive more personalized suggestions.

[1758] Viewing content:

[1759] Users view recommended content through their devices and deepen their interest in the local area.

[1760] Planning and booking your trip:

[1761] Users review the suggested travel plans and book the one they like.

[1762] Emotional Engine

[1763] The emotion engine is a system component that recognizes user emotions and adjusts content and suggestions based on those emotions. This emotion engine includes the following features:

[1764] Emotion recognition:

[1765] The emotion engine uses facial recognition and voice analysis technologies to determine the user's emotions and reflects the results in the user profile. For example, it could use a facial recognition library such as DeepFace.

[1766] Real-time adjustment:

[1767] The emotion engine monitors user emotions in real time and dynamically changes content to improve the user's customer experience.

[1768] Specific usage examples

[1769] For example, imagine a user in a physical store wearing smart glasses and browsing the merchandise. When the emotion engine recognizes the user's facial expression and detects "joy," the server receives this emotion data and displays suitable product recommendations and promotional information on the smart glasses' display. This allows the user to have a more enjoyable shopping experience. Furthermore, the emotion engine can adjust its suggestions in real time based on the user's emotional changes, leading to improved customer satisfaction.

[1770] Example of a prompt

[1771] For example, it is possible to input prompt statements like the following into the generation AI model:

[1772] We want to offer the best possible promotion when our users are happy. Please tell us the specific product name and offer details.

[1773] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1774] Step 1:

[1775] The server collects local information from the internet and dedicated databases. Specifically, it uses APIs to retrieve information such as tourist attractions, food culture, history, and weather, and stores this data in the database.

[1776] Input: Local information such as tourist attractions, food culture, history, and weather.

[1777] Output: Regional information stored in the database.

[1778] Step 2:

[1779] The server uses generative artificial intelligence to generate content such as text, images, and videos based on collected regional information. Specifically, it uses GPT-3 and image generation models to create engaging content and posts it to social media and websites.

[1780] Input: Local information.

[1781] Output: Generated content such as text, images, and videos.

[1782] Step 3:

[1783] The server collects and analyzes user profile data, such as interests, behavioral history, and location information. It uses clustering algorithms to classify user preferences.

[1784] Input: User profile data such as interests, behavioral history, and location information.

[1785] Output: Classified user profiles.

[1786] Step 4:

[1787] The device recognizes the user's emotions in real time and sends that data to a server. Specifically, it uses cameras built into smart glasses or head-mounted displays to perform facial recognition and voice analysis technologies.

[1788] Input: User's facial expressions and voice data.

[1789] Output: Recognized emotion data.

[1790] Step 5:

[1791] The server receives sentiment data sent from the sentiment engine and reflects it in the user profile. Based on the sentiment data, content and suggestions are adjusted in real time.

[1792] Input: Sentiment data.

[1793] Output: Edited content and suggestions.

[1794] Step 6:

[1795] The terminal displays customized travel plans sent from the server to the user and allows them to make a reservation. In physical stores, it also displays recommended products and promotional information based on the user profile and sentiment data.

[1796] Input: Customized travel plans and content tailored in real time.

[1797] Output: Travel plans and promotional information displayed to the user.

[1798] Step 7:

[1799] Users review the suggested travel plans and, if they like them, proceed with the booking process. In physical stores, they purchase products based on the displayed recommended items and promotional information.

[1800] Input: Customized travel plans and promotional information.

[1801] Output: Booked travel plans and purchased items.

[1802] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1803] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1804] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1805] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1806] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1807] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1808] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1809] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1810] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1811] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1812] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1813] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1814] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1815] 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.

[1816] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1817] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1818] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1819] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1820] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1821] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1822] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1823] The following is further disclosed regarding the embodiments described above.

[1824] (Claim 1)

[1825] Means of collecting local information,

[1826] A means of generating engaging content from regional information collected using generative artificial intelligence,

[1827] Means for collecting and analyzing user profile data,

[1828] A means of suggesting customized travel plans based on user profiles,

[1829] To promote monetization, a means of booking and managing travel plans,

[1830] A service integration method that notifies users of local service activities and event information,

[1831] A system that includes this.

[1832] (Claim 2)

[1833] It has a classification mechanism that categorizes users' interests based on user profile data.

[1834] The system according to claim 1.

[1835] (Claim 3)

[1836] We have the means to optimize measures for delivering advertising campaigns and promotions and analyzing their effectiveness.

[1837] The system according to claim 1.

[1838]

[1839] "Example 1"

[1840] (Claim 1)

[1841] Means of collecting local information,

[1842] A means of generating engaging content from regional information collected using generative artificial intelligence,

[1843] Means for collecting and analyzing user profile data,

[1844] A means of suggesting customized travel plans based on user profiles,

[1845] To promote monetization, a means of booking and managing travel plans,

[1846] A means of notifying users of local service activities and event information,

[1847] A means of generating content based on a prompt sentence using a generative artificial intelligence model,

[1848] A means of classifying users' interests using clustering algorithms,

[1849] A system that includes this.

[1850] (Claim 2)

[1851] It has a means of classifying users' interests using a clustering algorithm based on user profile data.

[1852] The system according to claim 1.

[1853] (Claim 3)

[1854] It has a means of generating content from local information based on a specified prompt sentence using a generative artificial intelligence model.

[1855] The system according to claim 1.

[1856] "Application Example 1"

[1857] (Claim 1)

[1858] Means of collecting local information,

[1859] A means of generating engaging content from regional information collected using generative artificial intelligence,

[1860] Means for collecting and analyzing user profile data,

[1861] A means of suggesting customized travel plans based on user profiles,

[1862] To promote monetization, a means of booking and managing travel plans,

[1863] A service integration method that notifies users of local service activities and event information,

[1864] A means of providing in-store promotional information and displaying special offers and coupons based on user interests,

[1865] A system that includes this.

[1866] (Claim 2)

[1867] It has a classification mechanism that categorizes users' interests based on user profile data.

[1868] The system according to claim 1.

[1869] (Claim 3)

[1870] We have the means to optimize measures for delivering advertising campaigns and promotions and analyzing their effectiveness.

[1871] The system according to claim 1.

[1872] "Example 2 of combining an emotion engine"

[1873] (Claim 1)

[1874] Means of collecting local information,

[1875] A means of generating engaging content from regional information collected using generative artificial intelligence,

[1876] Means for collecting and analyzing user profile data,

[1877] A means of suggesting customized travel plans based on user profiles,

[1878] To promote monetization, a means of booking and managing travel plans,

[1879] A means of recognizing the user's emotions and dynamically adjusting the suggested content based on those results,

[1880] A service integration method that notifies users of local service activities and event information,

[1881] A system that includes this.

[1882] (Claim 2)

[1883] A classification method that categorizes users' interests based on user profile data,

[1884] It has means of generating content such as text, images, and videos using generative artificial intelligence.

[1885] The system according to claim 1.

[1886] (Claim 3)

[1887] A means of optimizing strategies for delivering advertising campaigns and promotions and analyzing their effectiveness,

[1888] It has a means of collecting data from users' search history and social media activity and sending it to a server.

[1889] The system according to claim 1.

[1890] "Application example 2 when combining with an emotional engine"

[1891] (Claim 1)

[1892] Means of collecting local information,

[1893] A means of generating engaging content from regional information collected using generative artificial intelligence,

[1894] Means for collecting and analyzing user profile data,

[1895] A means of suggesting customized travel plans based on user profiles,

[1896] To promote monetization, a means of booking and managing travel plans,

[1897] A service integration method that notifies users of local service activities and event information,

[1898] A means of dynamically adjusting content and suggestions using an emotion engine that recognizes user emotions,

[1899] A means of recognizing user emotions in real time within a physical store and adjusting recommended products and promotions within the store,

[1900] A system that includes this.

[1901] (Claim 2)

[1902] It has a classification mechanism that categorizes users' interests based on user profile data.

[1903] The system according to claim 1.

[1904] (Claim 3)

[1905] We have the means to optimize measures for delivering advertising campaigns and promotions and analyzing their effectiveness.

[1906] The system according to claim 1. [Explanation of Symbols]

[1907] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of collecting local information, A means of generating engaging content from regional information collected using generative artificial intelligence, Means for collecting and analyzing user profile data, A means of suggesting customized travel plans based on user profiles, To promote monetization, a means of booking and managing travel plans, A service integration method that notifies users of local service activities and event information, A system that includes this.

2. It has a classification mechanism that categorizes users' interests based on user profile data. The system according to claim 1.

3. We have the means to optimize measures for delivering advertising campaigns and promotions and analyzing their effectiveness. The system according to claim 1.

Images