system

Abstract

Provide a system. A means for collecting tourist spot data based on information entered by a user; A method for calculating the optimal route that can be visited within specified conditions based on the collected tourist spot data; A means of generating detailed explanatory content for each tourist spot; means for integrating the generated route and explanatory content to create complete guide information; means for transmitting the created guide information to a user's terminal; a means for displaying the created guide information in a user terminal; A system including:

Description

[Technical Field]

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

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

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

[0004] In today's world, enjoying sightseeing requires gathering detailed information in advance and creating a plan that suits one's interests and time. However, when it comes to things like museums and castles, lack of knowledge often prevents a visitor from fully appreciating their attractions. Furthermore, time constraints and the need to listen to uninteresting stories make it difficult to achieve an efficient and satisfying sightseeing experience. There is a need for a system that can solve these problems and provide tourist guides that are optimized for the interests and time of individuals and groups. [Means for solving the problem]

[0005] The present invention is a system that collects tourist spot data based on information entered by a user and calculates the optimal route that can be visited within specified conditions. Specifically, the system includes: (1) a means for collecting tourist spot data based on information entered by a user; (2) a means for calculating the optimal route that can be visited within specified conditions based on the collected tourist spot data; (3) a means for generating detailed explanation content for each tourist spot; (4) a means for integrating the generated route and explanation content to create complete guide information; (5) a means for sending the created guide information to the user's device; and (6) a means for displaying the created guide information on the user's device. This allows the system to provide the user with the optimal tourist route and detailed guide information that suits their interests and schedule, thereby achieving a more satisfying tourist experience.

[0006] "User" refers to an individual or organization that uses the System to obtain tourist guide information.

[0007] "Terminal" refers to an electronic device that a user operates to input information and receive and display guide information.

[0008] "Server" refers to the central processing unit that receives information from users and works in conjunction with the database to collect data on tourist spots, calculate routes, and generate content.

[0009] "Tourist attractions" refer to places and facilities that are of interest to tourists, such as museums, castles, and historical buildings.

[0010] "Data" refers to all information used in each processing step of the system, such as information about tourist spots, information about users' interests and schedules, etc.

[0011] A "route" refers to a route that visits tourist spots that can be visited within specified conditions.

[0012] "Explanatory content" refers to information that provides detailed information about the history, characteristics, and highlights of tourist spots in the form of text, audio, images, etc.

[0013] "Guide information" refers to comprehensive tourist information provided to users that integrates optimal routes and explanatory content about each tourist spot.

[0014] "Input information" refers to information such as tourist category, time, and location that the user provides to the system.

[0015] "Database" refers to data storage within the system for storing and, when necessary, retrieving information about tourist attractions. [Brief explanation of the drawings]

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

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

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

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

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

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

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

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

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

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

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0037] The present invention is a system for individually providing users with information necessary for them to enjoy sightseeing more efficiently. Specific embodiments of the system will be described below.

[0038] Overall system configuration

[0039] The system consists of three main components: the user's terminal, the server, and the database. Each component works together to provide the user with the most suitable tourist guide information.

[0040] Entering user information

[0041] Device:

[0042] Users use the application to input their interests (e.g., museums, castles, historical buildings), the amount of time they have available (e.g., 3 hours, 1 day), and their current location or a place they want to visit (e.g., Tokyo, Kyoto).

[0043] Data collection

[0044] server:

[0045] The server receives user information sent from the device and uses this information to collect data on related tourist attractions from an internal database or external APIs. The tourist attractions covered include a wide range of categories, such as museums, castles, and historical buildings.

[0046] Route and Content Generation

[0047] server:

[0048] Based on the collected tourist spot data, the system calculates the optimal route that can be visited within a specified time. For example, if a user specifies "Tokyo," "Museums and Castles," and "within three hours," the system will collect information on Tokyo's major museums and castles and calculate an efficient route to visit these spots.

[0049] It also generates detailed commentary content for each tourist spot, including the historical background, highlights, and exhibits of the spot. For example, it provides specific information such as what exhibits are on display at the Tokyo National Museum and their historical significance.

[0050] Guide provided

[0051] Device:

[0052] The guide information created on the server is sent to the user's device and displayed through the application, allowing the user to see the optimal route and detailed explanations of each spot at a glance.

[0053] For example, along with the route "Tokyo National Museum → Hama Rikyu Gardens → Imperial Palace," information about each spot such as "Exhibition Room 7 contains ancient Japanese sculptures, and their historical background is..." is displayed.

[0054] Specific examples

[0055] Example 1:

[0056] If a user is interested in historical buildings and only plans to visit Kyoto for half a day, they can enter "historical buildings," "Kyoto," and "half day." The system will then collect Kyoto's major historical buildings from a database and generate a route that includes Nijo Castle, Kinkakuji Temple, and Kiyomizu-dera Temple. It will also generate detailed commentary about the history and highlights of each spot. This information is sent to the user's device and displayed through the application.

[0057] Example 2:

[0058] If a user wants to spend a day sightseeing in New York, they simply enter "museums," "New York," and "1 day." The system generates a route that includes the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art, providing detailed commentary on the characteristics and highlights of each museum. Users can enjoy sightseeing while checking this guide information through the app.

[0059] By using this system, users can obtain the optimal sightseeing route and detailed guide information based on their interests and time, resulting in an efficient and satisfying sightseeing experience.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] The user opens the application and enters the category of interest (e.g., museums, castles, historical buildings), the amount of time available (e.g., 3 hours, 1 day), and either their current location or a place they want to visit (e.g., Tokyo, Kyoto).

[0063] Step 2:

[0064] The device receives the information entered by the user and sends it to the server, specifically, data including tourist categories, available times, and location information.

[0065] Step 3:

[0066] The server receives user information sent from the device, then uses the received information to collect data on related tourist attractions using an internal database or external APIs. The tourist attractions covered include a wide range of categories, such as museums, castles, and historical buildings.

[0067] Step 4:

[0068] Based on the tourist spot data collected by the server, the optimal route that can be visited within a specified time is calculated, taking into account multiple factors such as transportation method, distance, and duration of stay.

[0069] Step 5:

[0070] The server generates detailed explanatory content for each tourist spot. The explanation includes the historical background, highlights, exhibits, etc. of the spot. Information is created to be easily understood by users using text, images, audio data, etc.

[0071] Step 6:

[0072] The server integrates the generated route and commentary content to create a complete guide, while providing more personalized guide information by setting priorities based on the user's interests.

[0073] Step 7:

[0074] The server then sends the created guide information to the user's device, which includes route guidance and detailed explanations of each tourist spot.

[0075] Step 8:

[0076] The guide information received by the device is displayed on the application, allowing users to enjoy sightseeing while viewing the optimal route guidance and detailed guide information for each spot through the app.

[0077] Example 1

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

[0079] Conventional tourist information systems can collect tourist spot data based on information entered by users, but they lack the functionality to generate optimal tourist routes based on the user's interests and available time, and to provide detailed explanatory information. This makes it difficult for users to efficiently enjoy sightseeing within their limited time. There is also a need for systems that can appropriately prioritize the collected tourist spot information and provide the most appropriate guide information to users.

[0080] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0081] In this invention, the server includes a means for collecting data on tourist attractions based on information entered by the user, a means for calculating the optimal route that can be visited within specified conditions based on the collected data on tourist attractions, and a means for using a generative AI model to generate detailed explanatory information for each tourist attraction. This makes it possible to generate optimal tourist routes according to the user's individual interests and conditions, and to provide comprehensive and detailed guide information.

[0082] "User" refers to an individual or organization that uses the tourist information system.

[0083] "Tourist destinations" refer to places that tourists visit, such as historical buildings, museums, and parks.

[0084] A "generative AI model" refers to an artificial intelligence model that generates information using natural language processing technology.

[0085] "Guide information" refers to comprehensive tourist information data including detailed explanations of tourist spots, optimal route guidance, and related information.

[0086] "Terminal" refers to a device such as a smartphone, tablet, or PC that a user uses to access the system.

[0087] "Data collection means" refers to a part of the system that collects data on related tourist destinations based on user input information.

[0088] "Means for calculating optimal route" refers to the system's algorithm that calculates a route for efficiently visiting tourist spots that can be visited within specified conditions.

[0089] "Explanatory information" refers to detailed explanations of the historical background, highlights, exhibit contents, etc. of tourist attractions.

[0090] "Transmission means" refers to a part of the system for transmitting the generated guide information to the user's terminal.

[0091] "Display means" refers to a part of the system for visually displaying guide information received on the user's terminal.

[0092] MODE FOR CARRYING OUT THE INVENTION

[0093] The present invention is a system that individually provides users with the information they need to enjoy sightseeing more efficiently. This system consists of three main components: a user terminal, a server, and a database. Specific embodiments of each component are described below.

[0094] Entering user information

[0095] Device:

[0096] Using a dedicated application, users input the tourist attractions they are interested in (e.g., museums, castles, historical buildings), the amount of time they have available for sightseeing (e.g., 3 hours, 1 day), and the places they want to visit (e.g., Tokyo, Kyoto). The device provides an input form and a submit button to receive this information.

[0097] Data collection

[0098] server:

[0099] The server receives user information sent from the device. Based on the received information, the server collects data on related tourist attractions using an internal database and external APIs (e.g., Google® Places API, TriPad® Visor API). The data includes the name, location, opening hours, and ratings of the tourist attractions.

[0100] Route and Content Generation

[0101] server:

[0102] The server analyzes the collected tourist destination data and uses an algorithm (e.g., Dijkstra's algorithm, A algorithm) to calculate the optimal tourist route that can be visited within a specified time. At the same time, a generative AI model (e.g., GPT-4 (registered trademark)) is used to generate detailed explanatory information for each tourist destination. The explanation includes the history, highlights, exhibits, etc. of the tourist destination.

[0103] Examples:

[0104] If a user inputs "art museum," "Tokyo," and "3 hours," the server uses this information to collect data on major art museums in Tokyo (e.g., Tokyo National Museum, Mori Art Museum, Ueno Royal Museum), calculates the optimal route to visit them efficiently within 3 hours, and then uses GPT-4 to generate detailed descriptions of each museum.

[0105] Example prompt sentence:

[0106] "Please tell me about the historical background of the Tokyo National Museum in Tokyo and what attractions it is worth visiting."

[0107] Guide provided

[0108] Device:

[0109] The guide information (optimal route and detailed commentary information) created on the server is sent to the user's device and displayed through the application. Users can check the optimal route and detailed commentary of each tourist spot within the application.

[0110] Specific behavior:

[0111] Users can check the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" within the app, and explanatory information for each spot will be displayed in a pop-up.

[0112] This system allows users to obtain the optimal sightseeing route and detailed guide information based on their individual interests and conditions, providing an efficient and satisfying sightseeing experience within a limited time frame.

[0113] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0114] Step 1:

[0115] Entering user information

[0116] Device:

[0117] The user opens the application and inputs their interests (e.g., museums, castles, historical buildings), available time (e.g., 3 hours, 1 day), and the places they want to visit (e.g., Tokyo, Kyoto). The input information is sent to the server by pressing the send button.

[0118] Input: The user enters "museum," "Tokyo," and "3 hours" into an input form within the app.

[0119] Output: The user's input data is sent to the server.

[0120] Specific operation: When the user presses the "Submit" button, the entered information is sent to the server.

[0121] Step 2:

[0122] Data collection

[0123] server:

[0124] The server receives the user information sent from the device and collects data on related tourist attractions by sending queries to an internal database and external APIs (e.g., Google Places API, TripAdvisor API) to obtain data on related tourist attractions.

[0125] Input: User input data (interests, location, time).

[0126] Output: Tourist attraction data (name, location, opening hours, rating, etc.).

[0127] Specific operation: The server obtains museum data via the Google Places API based on the information "Tokyo," "museum," and "3 hours," and stores it in an internal database.

[0128] Step 3:

[0129] Route and Content Generation

[0130] server:

[0131] Analyze the collected tourist destination data and calculate the optimal route that can be visited within a specified time. Use algorithms (e.g., Dijkstra algorithm, A algorithm) to find an efficient route. Next, use a generative AI model (e.g., GPT-4) to generate detailed descriptions of each tourist destination.

[0132] Input: tourist destination data.

[0133] Output: Optimal route, explanatory information.

[0134] Specific operation: Based on data on Tokyo's art museums, the server calculates the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" and uses a generative AI model to create detailed explanations of each museum.

[0135] Step 4:

[0136] Guide provided

[0137] Device:

[0138] The guide information (optimal route and detailed explanation) created on the server is sent to the user's device and displayed through the application. Users can check the optimal route and detailed explanation of each tourist spot within the app.

[0139] Input: Guide information received from the server.

[0140] Output: Display of guide information on the user's terminal.

[0141] Specific operation: The guide information sent by the server is received by the user's device, and the app displays the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" along with detailed explanations of each spot.

[0142] (Application example 1)

[0143] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0144] Today's consumers want to efficiently enjoy shopping in brick-and-mortar stores by obtaining the most appropriate information based on their interests, budget, and time. However, existing systems are specialized in tourist attractions and lack the functionality to collect extensive data applicable to brick-and-mortar shopping, provide appropriate route guidance, and provide product information for each store. Therefore, a system that can provide an efficient and satisfying shopping experience is needed.

[0145] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0146] In this invention, the server includes means for collecting store data based on information entered by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected store data, and means for generating detailed explanation content for each store, thereby enabling an efficient and satisfying shopping experience in a physical store.

[0147] "User-entered information" refers to data entered by a user specifying their interests, budget, and available time.

[0148] "Store data" refers to data that includes detailed information such as the location of each store, the products they carry, sales information, and store reputation.

[0149] An "optimal route" is a route that efficiently visits multiple stores that can be visited within specified conditions.

[0150] "Explanatory content" is a collection of text and images containing detailed information such as the characteristics of each store, product information, promotion information, and reputation.

[0151] "Guide information" is an information package provided to users that combines the optimal route with detailed explanations of each store.

[0152] A "user device" is a portable electronic device used by a user, such as a smartphone or tablet.

[0153] The present invention is a system that individually provides information to users to help them enjoy shopping at physical stores efficiently. This system provides the optimal shopping route and detailed store information based on the user's interests, budget, and available time, and includes the following components.

[0154] Overall system configuration

[0155] This system consists of three main components: the user's terminal, the server, and the database. Each component works together to provide the user with optimal shopping guide information.

[0156] Entering user information

[0157] Device:

[0158] Users use a smartphone application to input their interests (e.g., fashion, home appliances, food), budget (e.g., within 10,000 yen, within 20,000 yen), and available time (e.g., 1 hour, 2 hours). Current location information is also automatically obtained.

[0159] Data collection

[0160] server:

[0161] The server receives user information sent from the device. Based on this information, the server collects related store data from an internal database or external API (e.g., store information, product information, sale information).

[0162] Route and Content Generation

[0163] server:

[0164] Based on the collected store data, the system calculates the optimal route that can be visited within the specified conditions. For example, if a user specifies "fashion," "under 10,000 yen," and "two hours," the system calculates a route that efficiently visits nearby fashion-related stores. It also generates detailed explanatory content for each store. The explanation includes the store's features, product information, sales information, reputation, and more.

[0165] Guide provided

[0166] Device:

[0167] The guide information created on the server is sent to the user's device and displayed through the application, allowing the user to see the optimal route and detailed explanations of each store at a glance.

[0168] Specific examples

[0169] Example 1:

[0170] If a user is interested in home appliances and plans to spend two hours shopping for less than 20,000 yen, the user simply enters "home appliances," "less than 20,000 yen," and "2 hours." The system then collects nearby home appliance-related stores from a database and generates the optimal store route (e.g., major home appliance retailer A, home appliance specialty store B, discount store C). It also provides detailed information about featured products, sales, and reputations at each store. Users can use the app to enjoy a comfortable shopping experience.

[0171] Example 2:

[0172] If a user is interested in food and wishes to spend under 5,000 yen on shopping for one hour, they simply enter "food," "under 5,000 yen," and "one hour." The system then collects information on nearby supermarkets and specialty stores and generates the optimal route (e.g., high-end supermarket A, organic food store B, discount store C). It then provides detailed information on recommended products and promotions at each store.

[0173] Example prompts to input to the generative AI model

[0174] Prompt statement:

[0175] The user is interested in "home appliances" and plans to shop for "2 hours" for "less than 20,000 yen." Based on these conditions, generate the optimal route for efficient shopping and detailed information for each store.

[0176] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0177] Step 1:

[0178] Entering user information

[0179] Device: The user opens the application and enters their interests (e.g., fashion, home appliances, food), budget (e.g., under 10,000 yen, under 20,000 yen), and available time (e.g., 1 hour, 2 hours). The application also automatically obtains their current location information. This allows the device to prepare for sending the user's interests, budget, time, and location data to the server.

[0180] Step 2:

[0181] Data reception and processing

[0182] Server: Receives user information sent from the device. The technology used is API calls using the HTTP protocol. As input, it receives the user's interests, budget, available time, and current location data, and based on this, it collects related store data from a database or external API (e.g., store information API). The server temporarily stores the acquired store data and prepares it for the next step of processing.

[0183] Step 3:

[0184] Calculating the best route

[0185] Server: Based on the collected store data, calculates the optimal route that can be visited within the conditions specified by the user. The inputs are the user's interests, budget, time, location information, and store data. The server uses this data to execute an optimal route calculation method (e.g., Dijkstra's algorithm or A algorithm). As a result, it calculates the optimal store visit order and route and passes it to the next step.

[0186] Step 4:

[0187] Generating explanatory content

[0188] Server: Generates detailed explanatory content for each store. Store data and optimal route information are used as input. The server uses a generative AI model to generate explanatory content for each store (e.g., product information, sale information, reputation, etc.). Specifically, it uses OpenAI (registered trademark)'s GPT model and generates explanatory text by inputting a prompt. For example, it generates content such as, "This store has the latest home appliances, and we especially recommend the latest refrigerator."

[0189] Step 5:

[0190] Guide information integration

[0191] Server: Integrates the generated optimal route and explanatory content to create complete guide information. The optimal route information and explanatory content are used as input. The server formats this data and integrates it into a format that users can understand at a glance (e.g., a combination of maps and text). As a result, complete guide information is generated and passed to the next step.

[0192] Step 6:

[0193] Sending guide information

[0194] Server: Sends the created guide information to the user's device. A real-time communication protocol (e.g., WebSocket) is used to send data. The server uses the integrated guide information as input and prepares it for transmission to the user's device for display.

[0195] Step 7:

[0196] Display guide information

[0197] Terminal: The received guide information is displayed on the user's terminal. The guide information sent from the server is received as input and displayed through the application. The user can check the optimal route guidance and detailed explanations of each store on the application interface. A specific display method could be to draw the route on a map and present information about each store in text or images.

[0198] This processing step allows customers to have an efficient and satisfying shopping experience in a physical store.

[0199] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0200] The present invention is a system for providing tourist guide information based on the user's interests and emotions. A specific embodiment of the system will be described below.

[0201] Overall system configuration

[0202] The system consists of four main components: the user's device, the server, the database, and the emotion engine. These components work together to provide optimal tourist guide information to users.

[0203] Inputting user information and emotions

[0204] Device:

[0205] Users use the application to input categories of interest (museums, castles, historical buildings, etc.), available time (e.g., 3 hours, 1 day), and current location or place they want to visit (e.g., Tokyo, Kyoto).The emotion engine then recognizes the user's emotional state in real time.

[0206] Data collection

[0207] server:

[0208] The server receives user information sent from the device and emotion data from the emotion engine. Based on this information, the server collects data on related tourist spots from an internal database or external API. The tourist spot data covers a wide range of categories, including museums, castles, and historical buildings.

[0209] Route and Content Generation

[0210] server:

[0211] Based on the collected tourist spot data, the system calculates the optimal route for visiting within a specified time frame, taking into account factors such as transportation mode, distance, and duration of stay. It also sets priorities based on the user's emotional state and selects a route optimized for their interests and emotions.

[0212] Furthermore, detailed explanatory content is generated for each tourist spot, including the historical background, highlights, and exhibits of the spot. Information is provided to users in an easy-to-understand format using text, images, and audio data.

[0213] Guide provided

[0214] Device:

[0215] The guide information created on the server is sent to the user's device and displayed through the application, allowing users to see the optimal route and detailed explanations of each spot at a glance.

[0216] Emotion monitoring and dynamic regulation

[0217] server:

[0218] The emotion engine continuously monitors the user's emotional state in real time. If the user's emotions change during sightseeing, that information is also sent to the server. Based on these emotional changes, the server regenerates the optimal route and explanatory content in real time and sends new guide information to the user's device.

[0219] Specific examples

[0220] Example 1:

[0221] If a user is interested in historical buildings and only plans to visit Kyoto for half a day, they can enter "historical buildings," "Kyoto," and "half a day" and have the emotion engine recognize their current emotion (e.g., excited, curious). The system then collects Kyoto's major historical buildings from a database and generates a route that includes Nijo Castle, Kinkaku-ji Temple, and Kiyomizu-dera Temple. It also generates detailed commentary about the history and highlights of each spot. If the user's emotion changes during sightseeing (e.g., tired, needing a break), the route and commentary content are adjusted in real time. This information is sent to the user's device and displayed through the application.

[0222] Example 2:

[0223] If a user wants to spend a day sightseeing in New York, they can input "museum," "New York," and "one day," and the emotion engine will recognize emotions (e.g., excitement, anticipation). The system will generate a route that includes the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art. Detailed commentary will be provided on the characteristics and highlights of each museum. If the user's emotional state changes during the tour (e.g., surprise, excitement), the system will use that information to readjust the optimal route and commentary content and provide new guide information.

[0224] This system allows users to obtain the optimal sightseeing route and detailed guide information based on their interests and emotions, resulting in an efficient and satisfying sightseeing experience.

[0225] The processing flow will be explained below.

[0226] Step 1:

[0227] The user opens the application and inputs the category of interest (museums, castles, historical buildings, etc.), the time available (e.g., 3 hours, 1 day), and the current location or place they want to visit (e.g., Tokyo, Kyoto).The emotion engine then recognizes the user's emotional state in real time.

[0228] Step 2:

[0229] The device sends the user's input information and emotion data recognized by the emotion engine to the server, including interest categories, time, location, and emotional state.

[0230] Step 3:

[0231] The server receives user information and emotion data sent from the device, and then collects related tourist spot data from an internal database or external APIs based on predefined categories such as museums, castles, and historical buildings.

[0232] Step 4:

[0233] The server calculates the optimal route for visiting tourist spots within a specified time frame based on the tourist spot data collected by the server. This calculation takes into account factors such as transportation mode, distance, duration of stay, and the user's emotional state. The system also dynamically changes the priority of tourist spots based on the user's emotional state.

[0234] Step 5:

[0235] The server generates detailed explanatory content for each tourist spot, including the historical background, highlights, and exhibits of the spot. The information is provided in the form of text, images, audio data, and more.

[0236] Step 6:

[0237] The server integrates the generated route and explanatory content to create a complete guide information, and at the same time, provides personalized guide information by setting priorities according to the user's emotional state.

[0238] Step 7:

[0239] The server then sends the created guide information to the user's device, which includes route guidance and detailed explanations of each tourist spot.

[0240] Step 8:

[0241] The device receives the guide information and displays it on the application, allowing users to view the optimal route and detailed guide information for each spot through the app.

[0242] Step 9:

[0243] The emotion engine monitors the user's emotional state in real time. If the emotion changes, the information is sent to the server. For example, it can detect when the user changes from tired to excited.

[0244] Step 10:

[0245] Based on the new emotion data received by the server, the optimal route and explanatory content are regenerated in real time, and the guide information is updated based on the new priorities and emotional state.

[0246] Step 11:

[0247] The server retransmits the updated guide information to the user's device, including the modified route guidance and newly generated spot descriptions.

[0248] Step 12:

[0249] The device receives the retransmitted guide information and displays it on the application, allowing users to continue sightseeing by viewing the newly optimized route guidance and commentary in real time.

[0250] Example 2

[0251] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0252] Conventional tourist guide systems have had difficulty dynamically providing optimal routes and explanatory content based on users' interests and emotions. Furthermore, fixed information alone makes it difficult to increase user satisfaction, and they are unable to respond flexibly to situations where real-time adjustments are essential. Therefore, there is a need for systems that can dynamically provide optimal tourist routes and detailed guide information based on users' interests and emotions.

[0253] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0254] In this invention, the server includes means for collecting tourist destination data based on information entered by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected tourist destination data, and means for generating detailed commentary content for each tourist destination, which makes it possible to dynamically provide optimal tourist routes and detailed guide information according to the user's interests and emotions.

[0255] "User" refers to an individual or organization that uses the system to obtain tourist guide information.

[0256] "Tourist destinations" refer to places or facilities that are considered worth visiting, such as historical buildings, museums, and castles.

[0257] "Data" refers to general information about tourist destinations, such as their location, opening hours, prices, reviews, and attractions.

[0258] "Server" refers to a computer system that collects, analyzes, stores, and provides data.

[0259] "Terminal" refers to electronic devices such as smartphones and tablets operated by users.

[0260] "Emotional state" refers to the user's psychological state, such as excitement, interest, fatigue, expectation, and emotion.

[0261] "Emotion engine" refers to a system that detects a user's emotional state in real time through facial recognition and voice analysis.

[0262] The "optimal route" refers to a route that is calculated to ensure efficient and satisfying sightseeing based on the conditions and emotional state entered by the user.

[0263] "Explanatory content" refers to detailed information about each tourist destination, such as its historical background, highlights, and exhibits, provided in text, images, and audio.

[0264] "Guide information" refers to a comprehensive tourist guide provided to users that integrates optimal routes and explanatory content.

[0265] The present invention relates to a system for providing tourist guide information based on the interests and emotions of users. Specifically, the system is configured as follows.

[0266] The system consists of four main components: the user's terminal, the server, the database, and the emotion engine. Each component works together using the following hardware and software to provide tourist guide information.

[0267] Inputting user information and emotions

[0268] User:

[0269] Users launch the application on their smartphone or tablet and input their category of interest (e.g., museums, castles, historical buildings), the amount of time they have available (e.g., 3 hours, 1 day), and their current location or a place they want to visit (e.g., Tokyo, Kyoto). The emotion engine uses facial recognition and voice analysis to detect the user's emotional state in real time.

[0270] Data collection

[0271] server:

[0272] The system receives information and sentiment data sent from users' devices and uses external APIs such as the Google Places API and Yelp API to collect relevant tourist destination data, including details such as location, opening hours, prices, reviews, and attractions.

[0273] Route and Content Generation

[0274] server:

[0275] Based on the collected data on tourist attractions, the system calculates the optimal route for visiting within a specified time frame, taking into account factors such as transportation mode (e.g., walking, public transportation), distance, and duration of stay. It prioritizes spots based on the user's emotional state and selects a route optimized for their interests and emotions. It also generates detailed explanatory content for each tourist attraction. The explanation includes the historical background, highlights, and exhibits of the spot, and is provided using text, images, and audio data.

[0276] Guide provided

[0277] Device:

[0278] The guide information created on the server is sent to the user's device and displayed through the application. Users can check the optimal route guidance and detailed explanations of each spot to continue their sightseeing.

[0279] Emotion monitoring and dynamic regulation

[0280] server:

[0281] The emotion engine continuously monitors the user's emotional state in real time. Emotional data is sent to the server in response to changes in emotion while sightseeing. The server uses this data to regenerate the optimal route and explanatory content in real time. The new guide information is then sent back to the user's device and displayed.

[0282] Specific examples

[0283] Example 1: Half-day tour of Kyoto's historical buildings

[0284] User input:

[0285] "Historical Buildings" "Kyoto" "Half Day" "Current Emotion: Excitement"

[0286] Server Action:

[0287] The system collects Kyoto's major historical buildings (Nijo Castle, Kinkakuji Temple, and Kiyomizu-dera Temple) from a database and generates an optimal route. If the user's emotion changes to "fatigue" during sightseeing, a new route and explanation will be generated and sent to the user's device.

[0288] Example 2: One day tour of New York art museums

[0289] User input:

[0290] "Museum," "New York," "One Day," "Current Emotions: Expectations"

[0291] Server Action:

[0292] The system collects data from the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art, and generates commentary about the characteristics and highlights of each museum. If the user's emotion changes to "emotion" during sightseeing, the system will adjust the route and commentary and provide it to the user's device.

[0293] Hardware and software used

[0294] 1. Devices: smartphones, tablets

[0295] 2. Servers: Database servers, web servers

[0296] 3. External APIs: Google Places API, Yelp API

[0297] 4. Emotion engine: facial recognition software, voice analysis software

[0298] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0299] Step 1: Enter user information and emotions

[0300] User:

[0301] The user starts the application and inputs the category of interest (e.g., museums, castles, historical buildings), the amount of time available (e.g., 3 hours, 1 day), and the current location or the place they want to visit (e.g., Tokyo, Kyoto). This becomes the input data.

[0302] Device:

[0303] The device receives the user's input data and uses an emotion engine to perform real-time facial recognition and voice analysis to detect the user's current emotional state (e.g., excited, curious). The detected emotional data is then added to the input data.

[0304] output:

[0305] The output of this step is a data package containing category, availability, location information, and emotion data.

[0306] ---

[0307] Step 2: Data collection

[0308] server:

[0309] The server receives the data package sent from the device. Based on this data, it collects relevant tourist destination data from an internal database and external APIs (e.g., Google Places API, Yelp API). Specifically, the server makes API requests based on category, location, and availability.

[0310] output:

[0311] The output of this step is a dataset containing detailed data about tourist destinations (e.g., location, opening hours, prices, reviews, attractions).

[0312] ---

[0313] Step 3: Generate Routes and Content

[0314] server:

[0315] The server uses the tourist destination dataset to calculate the optimal route that can be visited within a specified time frame. It uses an algorithm to calculate the shortest route, taking into account transportation mode (e.g., walking, public transportation), distance, and duration of stay. It also takes into account emotion data and sets priorities according to the user's interests and emotions. It then generates detailed explanatory content for each tourist destination, including text, images, and audio data that includes historical background, highlights, and exhibits about each location.

[0316] output:

[0317] The output of this step is guide information that integrates the optimal route with detailed explanatory content.

[0318] ---

[0319] Step 4: Provide guidance

[0320] Device:

[0321] The device receives the guide information sent from the server and displays it on the application screen. Specifically, the device displays a map of the optimal route, lists detailed information about each tourist spot, and plays audio guides.

[0322] output:

[0323] The output of this step is guide information that is visually and audibly accessible to the user.

[0324] ---

[0325] Step 5: Emotion monitoring and dynamic regulation

[0326] server:

[0327] The emotion engine continues to monitor the user's emotional state in real time while sightseeing. If the user's emotion changes (e.g., from excitement to fatigue), the device sends that data to the server. The server then regenerates the optimal route and commentary content based on this new emotional data.

[0328] Device:

[0329] The device receives the regenerated guide information and displays it again, and the user continues sightseeing using the new optimal route and commentary information.

[0330] output:

[0331] The output of this step is new guide information with a re-adjusted optimal route and detailed explanatory content.

[0332] (Application example 2)

[0333] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0334] The purpose of this invention is to improve user satisfaction by recognizing users' interests and emotions in real time in a tourist guide system and providing detailed information on tourist spots and optimal routes based on that information. In particular, conventional tourist guide systems lack a flexible approach that responds to changes in users' emotions, and have the problem that the tourist experience for users is uniform and it is difficult to respond to individual needs.

[0335] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting tourist spot data based on information input by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected tourist spot data, means for acquiring emotion data using an emotion engine that recognizes the user's emotions in real time, means for setting priorities based on the user's emotional state, means for generating detailed explanation content for each tourist spot, means for integrating the generated route and explanation content to create complete guide information, means for sending the created guide information to the user's terminal, and means for regenerating the route and explanation content in real time based on changes in the user's emotions. This makes it possible to provide flexible and sophisticated tourist guide information that suits the user's interests and emotional state.

[0336] "Information entered by the user" refers to information such as tourist spot conditions, categories of interest, available times, current location, or places you wish to visit.

[0337] "Tourist attraction data" refers to tourist locations such as museums, historical buildings, and natural landscapes, as well as detailed information about them.

[0338] "Specified Conditions" refers to specific conditions specified by the User, such as categories of interest, available times, or desired locations to visit.

[0339] An "optimal route" refers to the route that most efficiently visits all the tourist spots that can be visited within the specified conditions.

[0340] An "emotion engine" refers to technology or a system that recognizes a user's emotional state in real time.

[0341] "Emotion Data" refers to information about the user's emotional state as recognized by the Emotion Engine.

[0342] "Priority" refers to the order in which the importance of tourist attractions and information is determined based on the user's interests and emotional state.

[0343] "Detailed explanatory content" refers to detailed explanations of tourist spots, including their historical background, highlights, and exhibit contents.

[0344] "Guide information" refers to information that integrates the generated optimal route with detailed explanatory content for each tourist spot.

[0345] "User's device" refers to an information display device held by the user, such as a smartphone, tablet, or smart glasses.

[0346] "Regeneration in real time" refers to instantly recreating new routes and explanatory content based on changes in users' emotions.

[0347] Overall system configuration

[0348] This invention is a system that provides tourist guide information based on the user's interests and emotions. The system consists of four main components: the user's terminal, a server, a database, and an emotion engine. These components work together to provide the user with the most appropriate tourist guide information.

[0349] Inputting user information and emotions

[0350] Device:

[0351] Users use devices such as smartphones or smart glasses to input categories of interest (fashion, historical landmarks, etc.), available time (e.g., 2 hours), and their current location or a place they want to visit. An emotion engine (e.g., Affectiva SDK) then recognizes the user's emotional state in real time.

[0352] Data collection

[0353] server:

[0354] The server receives user information sent from the device and emotion data from the emotion engine. Based on this information, the server collects data on related tourist spots from a database or external API. The tourist spot data includes stores in the shopping mall and neighboring tourist spots.

[0355] Route and Content Generation

[0356] server:

[0357] Based on the collected tourist spot data, the system calculates the optimal route that can be visited within the specified conditions. The calculation takes into account factors such as transportation method, distance, stay time, and the user's emotional state. It also sets priorities based on emotional data obtained by an emotion engine, and selects a route optimized for interests and emotions. It also generates detailed explanatory content for each tourist spot (e.g., historical background, highlights, exhibits).

[0358] Guide provided

[0359] Device:

[0360] The guide information created on the server is sent to the user's device and displayed through the application, allowing users to see the optimal route and detailed explanations of each spot at a glance.

[0361] Emotion monitoring and dynamic regulation

[0362] server:

[0363] The emotion engine continuously monitors the user's emotional state in real time. If the user's emotions change during sightseeing, that information is also sent to the server. Based on these emotional changes, the server regenerates the optimal route and explanatory content in real time and sends new guide information to the user's device.

[0364] Specific use cases

[0365] For example, if a user is interested in the "fashion" category in a shopping mall and plans to spend two hours shopping, they put on the smart glasses and input "fashion" and "two hours." The emotion engine recognizes this as "excitement." The system then collects stores in the mall that sell fashion items from a database and generates an optimal route. As detailed information about products and stores that interest them during shopping is provided, the system will suggest a new route if their emotions change.

[0366] Prompt Sentence Examples

[0367] "I want to create a guide app that provides real-time information on the best route and products for users to enjoy a two-hour shopping trip in the 'fashion' category at a shopping mall. I want to dynamically adjust the information based on the user's emotions. What approach can you think of?"

[0368] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0369] Step 1:

[0370] The server receives user information (interest categories, available time, current location) and emotional data (real-time emotional state) from the user's device. This allows the system to obtain the basic data necessary to provide tourist guide information. This input includes data such as "fashion," "2 hours," and "excitement."

[0371] Step 2:

[0372] The server collects tourist attraction data from databases and external APIs. This data includes, for example, the stores in a shopping mall, the products they sell, their opening hours, etc. Based on the tourist attraction requirements entered, the server executes database queries to collect relevant data.

[0373] Step 3:

[0374] The server calculates the optimal route based on the acquired tourist attraction data within the specified conditions. The calculation takes into account factors such as transportation mode, distance, duration of stay, and the user's emotional state. For example, if the user is "excited," the server will suggest a route that involves active movement. The output is a prioritized list of stores and tourist attractions.

[0375] Step 4:

[0376] The server prioritizes tourist spots and shops based on emotion data acquired using an emotion engine. For example, if a user feels "tired," it prioritizes relaxation spots in the route. This process is based on data analysis performed by an emotion recognition engine (e.g., Affectiva SDK).

[0377] Step 5:

[0378] The server generates detailed explanatory content for each tourist spot, including the tourist spot's historical background, highlights, exhibits, etc. The explanatory content is generated using detailed information obtained from the database and a text generation model (e.g., a generative AI model).

[0379] Step 6:

[0380] The server integrates the generated route and commentary content to create complete guide information. The server combines the route information and detailed commentary to create guide information in a format that is easy for users to view. The output result is generated as a comprehensive guide data set.

[0381] Step 7:

[0382] The server sends the created guide information to the user's device, which then uses an application to display the received guide information, providing the information in the most optimal format for the user. The guide content, updated in real time, is displayed on the display of the smart glasses or smartphone.

[0383] Step 8:

[0384] If the user's emotions change in real time, the emotion engine reacquires that information and sends it to the server. The server then regenerates the optimal route and explanatory content based on this new emotion data, updating the guide information in real time. For example, if the user's emotions change from "excited" to "tired," a relaxing spot will be added to the route.

[0385] This allows users to always receive the latest information and tourist guides that best suit their circumstances.

[0386] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0387] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0388] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0389] [Second embodiment]

[0390] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0391] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0392] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0393] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0394] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0395] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0396] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0397] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0398] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0399] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0400] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0401] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0402] The present invention is a system for individually providing users with information necessary for them to enjoy sightseeing more efficiently. Specific embodiments of the system will be described below.

[0403] Overall system configuration

[0404] The system consists of three main components: the user's terminal, the server, and the database. Each component works together to provide the user with the most suitable tourist guide information.

[0405] Entering user information

[0406] Device:

[0407] Users use the application to input their interests (e.g., museums, castles, historical buildings), the amount of time they have available (e.g., 3 hours, 1 day), and their current location or a place they want to visit (e.g., Tokyo, Kyoto).

[0408] Data collection

[0409] server:

[0410] The server receives user information sent from the device and uses this information to collect data on related tourist attractions from an internal database or external APIs. The tourist attractions covered include a wide range of categories, such as museums, castles, and historical buildings.

[0411] Route and Content Generation

[0412] server:

[0413] Based on the collected tourist spot data, the system calculates the optimal route that can be visited within a specified time. For example, if a user specifies "Tokyo," "Museums and Castles," and "within three hours," the system will collect information on Tokyo's major museums and castles and calculate an efficient route to visit these spots.

[0414] It also generates detailed commentary content for each tourist spot, including the historical background, highlights, and exhibits of the spot. For example, it provides specific information such as what exhibits are on display at the Tokyo National Museum and their historical significance.

[0415] Guide provided

[0416] Device:

[0417] The guide information created on the server is sent to the user's device and displayed through the application, allowing the user to see the optimal route and detailed explanations of each spot at a glance.

[0418] For example, along with the route "Tokyo National Museum → Hama Rikyu Gardens → Imperial Palace," information about each spot such as "Exhibition Room 7 contains ancient Japanese sculptures, and their historical background is..." is displayed.

[0419] Specific examples

[0420] Example 1:

[0421] If a user is interested in historical buildings and only plans to visit Kyoto for half a day, they can enter "historical buildings," "Kyoto," and "half day." The system will then collect Kyoto's major historical buildings from a database and generate a route that includes Nijo Castle, Kinkakuji Temple, and Kiyomizu-dera Temple. It will also generate detailed commentary about the history and highlights of each spot. This information is sent to the user's device and displayed through the application.

[0422] Example 2:

[0423] If a user wants to spend a day sightseeing in New York, they simply enter "museums," "New York," and "1 day." The system generates a route that includes the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art, providing detailed commentary on the characteristics and highlights of each museum. Users can enjoy sightseeing while checking this guide information through the app.

[0424] By using this system, users can obtain the optimal sightseeing route and detailed guide information based on their interests and time, resulting in an efficient and satisfying sightseeing experience.

[0425] The processing flow will be explained below.

[0426] Step 1:

[0427] The user opens the application and enters the category of interest (e.g., museums, castles, historical buildings), the amount of time available (e.g., 3 hours, 1 day), and either their current location or a place they want to visit (e.g., Tokyo, Kyoto).

[0428] Step 2:

[0429] The device receives the information entered by the user and sends it to the server, specifically, data including tourist categories, available times, and location information.

[0430] Step 3:

[0431] The server receives user information sent from the device, then uses the received information to collect data on related tourist attractions using an internal database or external APIs. The tourist attractions covered include a wide range of categories, such as museums, castles, and historical buildings.

[0432] Step 4:

[0433] Based on the tourist spot data collected by the server, the optimal route that can be visited within a specified time is calculated, taking into account multiple factors such as transportation method, distance, and duration of stay.

[0434] Step 5:

[0435] The server generates detailed explanatory content for each tourist spot. The explanation includes the historical background, highlights, exhibits, etc. of the spot. Information is created to be easily understood by users using text, images, audio data, etc.

[0436] Step 6:

[0437] The server integrates the generated route and commentary content to create a complete guide, while providing more personalized guide information by setting priorities based on the user's interests.

[0438] Step 7:

[0439] The server then sends the created guide information to the user's device, which includes route guidance and detailed explanations of each tourist spot.

[0440] Step 8:

[0441] The guide information received by the device is displayed on the application, allowing users to enjoy sightseeing while viewing the optimal route guidance and detailed guide information for each spot through the app.

[0442] Example 1

[0443] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0444] Conventional tourist information systems can collect tourist spot data based on information entered by users, but they lack the functionality to generate optimal tourist routes based on the user's interests and available time, and to provide detailed explanatory information. This makes it difficult for users to efficiently enjoy sightseeing within their limited time. There is also a need for systems that can appropriately prioritize the collected tourist spot information and provide the most appropriate guide information to users.

[0445] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0446] In this invention, the server includes a means for collecting data on tourist attractions based on information entered by the user, a means for calculating the optimal route that can be visited within specified conditions based on the collected data on tourist attractions, and a means for using a generative AI model to generate detailed explanatory information for each tourist attraction. This makes it possible to generate optimal tourist routes according to the user's individual interests and conditions, and to provide comprehensive and detailed guide information.

[0447] "User" refers to an individual or organization that uses the tourist information system.

[0448] "Tourist destinations" refer to places that tourists visit, such as historical buildings, museums, and parks.

[0449] A "generative AI model" refers to an artificial intelligence model that generates information using natural language processing technology.

[0450] "Guide information" refers to comprehensive tourist information data including detailed explanations of tourist spots, optimal route guidance, and related information.

[0451] "Terminal" refers to a device such as a smartphone, tablet, or PC that a user uses to access the system.

[0452] "Data collection means" refers to a part of the system that collects data on related tourist destinations based on user input information.

[0453] "Means for calculating optimal route" refers to the system's algorithm that calculates a route for efficiently visiting tourist spots that can be visited within specified conditions.

[0454] "Explanatory information" refers to detailed explanations of the historical background, highlights, exhibit contents, etc. of tourist attractions.

[0455] "Transmission means" refers to a part of the system for transmitting the generated guide information to the user's terminal.

[0456] "Display means" refers to a part of the system for visually displaying guide information received on the user's terminal.

[0457] MODE FOR CARRYING OUT THE INVENTION

[0458] The present invention is a system that individually provides users with the information they need to enjoy sightseeing more efficiently. This system consists of three main components: a user terminal, a server, and a database. Specific embodiments of each component are described below.

[0459] Entering user information

[0460] Device:

[0461] Using a dedicated application, users input the tourist attractions they are interested in (e.g., museums, castles, historical buildings), the amount of time they have available for sightseeing (e.g., 3 hours, 1 day), and the places they want to visit (e.g., Tokyo, Kyoto). The device provides an input form and a submit button to receive this information.

[0462] Data collection

[0463] server:

[0464] The server receives user information sent from the device. Based on the received information, the server collects data on related tourist attractions using an internal database and external APIs (e.g., Google Places API, TripAdvisor API). This data includes the name, location, opening hours, and ratings of the tourist attractions.

[0465] Route and Content Generation

[0466] server:

[0467] The server analyzes the collected tourist destination data and uses an algorithm (e.g., Dijkstra's algorithm, A algorithm) to calculate the optimal tourist route that can be visited within a specified time. At the same time, it uses a generative AI model (e.g., GPT-4) to generate detailed explanatory information for each tourist destination. The explanation includes the history, highlights, and exhibits of the destination.

[0468] Examples:

[0469] If a user inputs "art museum," "Tokyo," and "3 hours," the server uses this information to collect data on major art museums in Tokyo (e.g., Tokyo National Museum, Mori Art Museum, Ueno Royal Museum), calculates the optimal route to visit them efficiently within 3 hours, and then uses GPT-4 to generate detailed descriptions of each museum.

[0470] Example prompt sentence:

[0471] "Please tell me about the historical background of the Tokyo National Museum in Tokyo and what attractions it is worth visiting."

[0472] Guide provided

[0473] Device:

[0474] The guide information (optimal route and detailed commentary information) created on the server is sent to the user's device and displayed through the application. Users can check the optimal route and detailed commentary of each tourist spot within the application.

[0475] Specific behavior:

[0476] Users can check the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" within the app, and explanatory information for each spot will be displayed in a pop-up.

[0477] This system allows users to obtain the optimal sightseeing route and detailed guide information based on their individual interests and conditions, providing an efficient and satisfying sightseeing experience within a limited time frame.

[0478] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0479] Step 1:

[0480] Entering user information

[0481] Device:

[0482] The user opens the application and inputs their interests (e.g., museums, castles, historical buildings), available time (e.g., 3 hours, 1 day), and the places they want to visit (e.g., Tokyo, Kyoto). The input information is sent to the server by pressing the send button.

[0483] Input: The user enters "museum," "Tokyo," and "3 hours" into an input form within the app.

[0484] Output: The user's input data is sent to the server.

[0485] Specific operation: When the user presses the "Submit" button, the entered information is sent to the server.

[0486] Step 2:

[0487] Data collection

[0488] server:

[0489] The server receives the user information sent from the device and collects data on related tourist attractions by sending queries to an internal database and external APIs (e.g., Google Places API, TripAdvisor API) to obtain data on related tourist attractions.

[0490] Input: User input data (interests, location, time).

[0491] Output: Tourist attraction data (name, location, opening hours, rating, etc.).

[0492] Specific operation: The server obtains museum data via the Google Places API based on the information "Tokyo," "museum," and "3 hours," and stores it in an internal database.

[0493] Step 3:

[0494] Route and Content Generation

[0495] server:

[0496] Analyze the collected tourist destination data and calculate the optimal route that can be visited within a specified time. Use algorithms (e.g., Dijkstra algorithm, A algorithm) to find an efficient route. Next, use a generative AI model (e.g., GPT-4) to generate detailed descriptions of each tourist destination.

[0497] Input: tourist destination data.

[0498] Output: Optimal route, explanatory information.

[0499] Specific operation: Based on data on Tokyo's art museums, the server calculates the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" and uses a generative AI model to create detailed explanations of each museum.

[0500] Step 4:

[0501] Guide provided

[0502] Device:

[0503] The guide information (optimal route and detailed explanation) created on the server is sent to the user's device and displayed through the application. Users can check the optimal route and detailed explanation of each tourist spot within the app.

[0504] Input: Guide information received from the server.

[0505] Output: Display of guide information on the user's terminal.

[0506] Specific operation: The guide information sent by the server is received by the user's device, and the app displays the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" along with detailed explanations of each spot.

[0507] (Application example 1)

[0508] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0509] Today's consumers want to efficiently enjoy shopping in brick-and-mortar stores by obtaining the most appropriate information based on their interests, budget, and time. However, existing systems are specialized in tourist attractions and lack the functionality to collect extensive data applicable to brick-and-mortar shopping, provide appropriate route guidance, and provide product information for each store. Therefore, a system that can provide an efficient and satisfying shopping experience is needed.

[0510] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0511] In this invention, the server includes means for collecting store data based on information entered by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected store data, and means for generating detailed explanation content for each store, thereby enabling an efficient and satisfying shopping experience in a physical store.

[0512] "User-entered information" refers to data entered by a user specifying their interests, budget, and available time.

[0513] "Store data" refers to data that includes detailed information such as the location of each store, the products they carry, sales information, and store reputation.

[0514] An "optimal route" is a route that efficiently visits multiple stores that can be visited within specified conditions.

[0515] "Explanatory content" is a collection of text and images containing detailed information such as the characteristics of each store, product information, promotion information, and reputation.

[0516] "Guide information" is an information package provided to users that combines the optimal route with detailed explanations of each store.

[0517] A "user device" is a portable electronic device used by a user, such as a smartphone or tablet.

[0518] The present invention is a system that individually provides information to users to help them enjoy shopping at physical stores efficiently. This system provides the optimal shopping route and detailed store information based on the user's interests, budget, and available time, and includes the following components.

[0519] Overall system configuration

[0520] This system consists of three main components: the user's terminal, the server, and the database. Each component works together to provide the user with optimal shopping guide information.

[0521] Entering user information

[0522] Device:

[0523] Users use a smartphone application to input their interests (e.g., fashion, home appliances, food), budget (e.g., within 10,000 yen, within 20,000 yen), and available time (e.g., 1 hour, 2 hours). Current location information is also automatically obtained.

[0524] Data collection

[0525] server:

[0526] The server receives user information sent from the device. Based on this information, the server collects related store data from an internal database or external API (e.g., store information, product information, sale information).

[0527] Route and Content Generation

[0528] server:

[0529] Based on the collected store data, the system calculates the optimal route that can be visited within the specified conditions. For example, if a user specifies "fashion," "under 10,000 yen," and "two hours," the system calculates a route that efficiently visits nearby fashion-related stores. It also generates detailed explanatory content for each store. The explanation includes the store's features, product information, sales information, reputation, and more.

[0530] Guide provided

[0531] Device:

[0532] The guide information created on the server is sent to the user's device and displayed through the application, allowing the user to see the optimal route and detailed explanations of each store at a glance.

[0533] Specific examples

[0534] Example 1:

[0535] If a user is interested in home appliances and plans to spend two hours shopping for less than 20,000 yen, the user simply enters "home appliances," "less than 20,000 yen," and "2 hours." The system then collects nearby home appliance-related stores from a database and generates the optimal store route (e.g., major home appliance retailer A, home appliance specialty store B, discount store C). It also provides detailed information about featured products, sales, and reputations at each store. Users can use the app to enjoy a comfortable shopping experience.

[0536] Example 2:

[0537] If a user is interested in food and wishes to spend under 5,000 yen on shopping for one hour, they simply enter "food," "under 5,000 yen," and "one hour." The system then collects information on nearby supermarkets and specialty stores and generates the optimal route (e.g., high-end supermarket A, organic food store B, discount store C). It then provides detailed information on recommended products and promotions at each store.

[0538] Example prompts to input to the generative AI model

[0539] Prompt statement:

[0540] The user is interested in "home appliances" and plans to shop for "2 hours" for "less than 20,000 yen." Based on these conditions, generate the optimal route for efficient shopping and detailed information for each store.

[0541] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0542] Step 1:

[0543] Entering user information

[0544] Device: The user opens the application and enters their interests (e.g., fashion, home appliances, food), budget (e.g., under 10,000 yen, under 20,000 yen), and available time (e.g., 1 hour, 2 hours). The application also automatically obtains their current location information. This allows the device to prepare for sending the user's interests, budget, time, and location data to the server.

[0545] Step 2:

[0546] Data reception and processing

[0547] Server: Receives user information sent from the device. The technology used is API calls using the HTTP protocol. As input, it receives the user's interests, budget, available time, and current location data, and based on this, it collects related store data from a database or external API (e.g., store information API). The server temporarily stores the acquired store data and prepares it for the next step of processing.

[0548] Step 3:

[0549] Calculating the best route

[0550] Server: Based on the collected store data, calculates the optimal route that can be visited within the conditions specified by the user. The inputs are the user's interests, budget, time, location information, and store data. The server uses this data to execute an optimal route calculation method (e.g., Dijkstra's algorithm or A algorithm). As a result, it calculates the optimal store visit order and route and passes it to the next step.

[0551] Step 4:

[0552] Generating explanatory content

[0553] Server: Generates detailed explanatory content for each store. Store data and optimal route information are used as input. The server utilizes a generative AI model to generate explanatory content for each store (e.g., product information, sale information, reputation, etc.). Specifically, it uses OpenAI's GPT model and generates explanatory text by inputting a prompt text. For example, it generates content such as, "This store has the latest home appliances, and we especially recommend the latest refrigerator."

[0554] Step 5:

[0555] Guide information integration

[0556] Server: Integrates the generated optimal route and explanatory content to create complete guide information. The optimal route information and explanatory content are used as input. The server formats this data and integrates it into a format that users can understand at a glance (e.g., a combination of maps and text). As a result, complete guide information is generated and passed to the next step.

[0557] Step 6:

[0558] Sending guide information

[0559] Server: Sends the created guide information to the user's device. A real-time communication protocol (e.g., WebSocket) is used to send data. The server uses the integrated guide information as input and prepares it for transmission to the user's device for display.

[0560] Step 7:

[0561] Display guide information

[0562] Terminal: The received guide information is displayed on the user's terminal. The guide information sent from the server is received as input and displayed through the application. The user can check the optimal route guidance and detailed explanations of each store on the application interface. A specific display method could be to draw the route on a map and present information about each store in text or images.

[0563] This processing step allows customers to have an efficient and satisfying shopping experience in a physical store.

[0564] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0565] The present invention is a system for providing tourist guide information based on the user's interests and emotions. A specific embodiment of the system will be described below.

[0566] Overall system configuration

[0567] The system consists of four main components: the user's device, the server, the database, and the emotion engine. These components work together to provide optimal tourist guide information to users.

[0568] Inputting user information and emotions

[0569] Device:

[0570] Users use the application to input categories of interest (museums, castles, historical buildings, etc.), available time (e.g., 3 hours, 1 day), and current location or place they want to visit (e.g., Tokyo, Kyoto).The emotion engine then recognizes the user's emotional state in real time.

[0571] Data collection

[0572] server:

[0573] The server receives user information sent from the device and emotion data from the emotion engine. Based on this information, the server collects data on related tourist spots from an internal database or external API. The tourist spot data covers a wide range of categories, including museums, castles, and historical buildings.

[0574] Route and Content Generation

[0575] server:

[0576] Based on the collected tourist spot data, the system calculates the optimal route for visiting within a specified time frame, taking into account factors such as transportation mode, distance, and duration of stay. It also sets priorities based on the user's emotional state and selects a route optimized for their interests and emotions.

[0577] Furthermore, detailed explanatory content is generated for each tourist spot, including the historical background, highlights, and exhibits of the spot. Information is provided to users in an easy-to-understand format using text, images, and audio data.

[0578] Guide provided

[0579] Device:

[0580] The guide information created on the server is sent to the user's device and displayed through the application, allowing users to see the optimal route and detailed explanations of each spot at a glance.

[0581] Emotion monitoring and dynamic regulation

[0582] server:

[0583] The emotion engine continuously monitors the user's emotional state in real time. If the user's emotions change during sightseeing, that information is also sent to the server. Based on these emotional changes, the server regenerates the optimal route and explanatory content in real time and sends new guide information to the user's device.

[0584] Specific examples

[0585] Example 1:

[0586] If a user is interested in historical buildings and only plans to visit Kyoto for half a day, they can enter "historical buildings," "Kyoto," and "half a day" and have the emotion engine recognize their current emotion (e.g., excited, curious). The system then collects Kyoto's major historical buildings from a database and generates a route that includes Nijo Castle, Kinkaku-ji Temple, and Kiyomizu-dera Temple. It also generates detailed commentary about the history and highlights of each spot. If the user's emotion changes during sightseeing (e.g., tired, needing a break), the route and commentary content are adjusted in real time. This information is sent to the user's device and displayed through the application.

[0587] Example 2:

[0588] If a user wants to spend a day sightseeing in New York, they can input "museum," "New York," and "one day," and the emotion engine will recognize emotions (e.g., excitement, anticipation). The system will generate a route that includes the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art. Detailed commentary will be provided on the characteristics and highlights of each museum. If the user's emotional state changes during the tour (e.g., surprise, excitement), the system will use that information to readjust the optimal route and commentary content and provide new guide information.

[0589] This system allows users to obtain the optimal sightseeing route and detailed guide information based on their interests and emotions, resulting in an efficient and satisfying sightseeing experience.

[0590] The processing flow will be explained below.

[0591] Step 1:

[0592] The user opens the application and inputs the category of interest (museums, castles, historical buildings, etc.), the time available (e.g., 3 hours, 1 day), and the current location or place they want to visit (e.g., Tokyo, Kyoto).The emotion engine then recognizes the user's emotional state in real time.

[0593] Step 2:

[0594] The device sends the user's input information and emotion data recognized by the emotion engine to the server, including interest categories, time, location, and emotional state.

[0595] Step 3:

[0596] The server receives user information and emotion data sent from the device, and then collects related tourist spot data from an internal database or external APIs based on predefined categories such as museums, castles, and historical buildings.

[0597] Step 4:

[0598] The server calculates the optimal route for visiting tourist spots within a specified time frame based on the tourist spot data collected by the server. This calculation takes into account factors such as transportation mode, distance, duration of stay, and the user's emotional state. The system also dynamically changes the priority of tourist spots based on the user's emotional state.

[0599] Step 5:

[0600] The server generates detailed explanatory content for each tourist spot, including the historical background, highlights, and exhibits of the spot. The information is provided in the form of text, images, audio data, and more.

[0601] Step 6:

[0602] The server integrates the generated route and explanatory content to create a complete guide information, and at the same time, provides personalized guide information by setting priorities according to the user's emotional state.

[0603] Step 7:

[0604] The server then sends the created guide information to the user's device, which includes route guidance and detailed explanations of each tourist spot.

[0605] Step 8:

[0606] The device receives the guide information and displays it on the application, allowing users to view the optimal route and detailed guide information for each spot through the app.

[0607] Step 9:

[0608] The emotion engine monitors the user's emotional state in real time. If the emotion changes, the information is sent to the server. For example, it can detect when the user changes from tired to excited.

[0609] Step 10:

[0610] Based on the new emotion data received by the server, the optimal route and explanatory content are regenerated in real time, and the guide information is updated based on the new priorities and emotional state.

[0611] Step 11:

[0612] The server retransmits the updated guide information to the user's device, including the modified route guidance and newly generated spot descriptions.

[0613] Step 12:

[0614] The device receives the retransmitted guide information and displays it on the application, allowing users to continue sightseeing by viewing the newly optimized route guidance and commentary in real time.

[0615] Example 2

[0616] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0617] Conventional tourist guide systems have had difficulty dynamically providing optimal routes and explanatory content based on users' interests and emotions. Furthermore, fixed information alone makes it difficult to increase user satisfaction, and they are unable to respond flexibly to situations where real-time adjustments are essential. Therefore, there is a need for systems that can dynamically provide optimal tourist routes and detailed guide information based on users' interests and emotions.

[0618] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0619] In this invention, the server includes means for collecting tourist destination data based on information entered by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected tourist destination data, and means for generating detailed commentary content for each tourist destination, which makes it possible to dynamically provide optimal tourist routes and detailed guide information according to the user's interests and emotions.

[0620] "User" refers to an individual or organization that uses the system to obtain tourist guide information.

[0621] "Tourist destinations" refer to places or facilities that are considered worth visiting, such as historical buildings, museums, and castles.

[0622] "Data" refers to general information about tourist destinations, such as their location, opening hours, prices, reviews, and attractions.

[0623] "Server" refers to a computer system that collects, analyzes, stores, and provides data.

[0624] "Terminal" refers to electronic devices such as smartphones and tablets operated by users.

[0625] "Emotional state" refers to the user's psychological state, such as excitement, interest, fatigue, expectation, and emotion.

[0626] "Emotion engine" refers to a system that detects a user's emotional state in real time through facial recognition and voice analysis.

[0627] The "optimal route" refers to a route that is calculated to ensure efficient and satisfying sightseeing based on the conditions and emotional state entered by the user.

[0628] "Explanatory content" refers to detailed information about each tourist destination, such as its historical background, highlights, and exhibits, provided in text, images, and audio.

[0629] "Guide information" refers to a comprehensive tourist guide provided to users that integrates optimal routes and explanatory content.

[0630] The present invention relates to a system for providing tourist guide information based on the interests and emotions of users. Specifically, the system is configured as follows.

[0631] The system consists of four main components: the user's terminal, the server, the database, and the emotion engine. Each component works together using the following hardware and software to provide tourist guide information.

[0632] Inputting user information and emotions

[0633] User:

[0634] Users launch the application on their smartphone or tablet and input their category of interest (e.g., museums, castles, historical buildings), the amount of time they have available (e.g., 3 hours, 1 day), and their current location or a place they want to visit (e.g., Tokyo, Kyoto). The emotion engine uses facial recognition and voice analysis to detect the user's emotional state in real time.

[0635] Data collection

[0636] server:

[0637] The system receives information and sentiment data sent from users' devices and uses external APIs such as the Google Places API and Yelp API to collect relevant tourist destination data, including details such as location, opening hours, prices, reviews, and attractions.

[0638] Route and Content Generation

[0639] server:

[0640] Based on the collected data on tourist attractions, the system calculates the optimal route for visiting within a specified time frame, taking into account factors such as transportation mode (e.g., walking, public transportation), distance, and duration of stay. It prioritizes spots based on the user's emotional state and selects a route optimized for their interests and emotions. It also generates detailed explanatory content for each tourist attraction. The explanation includes the historical background, highlights, and exhibits of the spot, and is provided using text, images, and audio data.

[0641] Guide provided

[0642] Device:

[0643] The guide information created on the server is sent to the user's device and displayed through the application. Users can check the optimal route guidance and detailed explanations of each spot to continue their sightseeing.

[0644] Emotion monitoring and dynamic regulation

[0645] server:

[0646] The emotion engine continuously monitors the user's emotional state in real time. Emotional data is sent to the server in response to changes in emotion while sightseeing. The server uses this data to regenerate the optimal route and explanatory content in real time. The new guide information is then sent back to the user's device and displayed.

[0647] Specific examples

[0648] Example 1: Half-day tour of Kyoto's historical buildings

[0649] User input:

[0650] "Historical Buildings" "Kyoto" "Half Day" "Current Emotion: Excitement"

[0651] Server Action:

[0652] The system collects Kyoto's major historical buildings (Nijo Castle, Kinkakuji Temple, and Kiyomizu-dera Temple) from a database and generates an optimal route. If the user's emotion changes to "fatigue" during sightseeing, a new route and explanation will be generated and sent to the user's device.

[0653] Example 2: One day tour of New York art museums

[0654] User input:

[0655] "Museum," "New York," "One Day," "Current Emotions: Expectations"

[0656] Server Action:

[0657] The system collects data from the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art, and generates commentary about the characteristics and highlights of each museum. If the user's emotion changes to "emotion" during sightseeing, the system will adjust the route and commentary and provide it to the user's device.

[0658] Hardware and software used

[0659] 1. Devices: smartphones, tablets

[0660] 2. Servers: Database servers, web servers

[0661] 3. External APIs: Google Places API, Yelp API

[0662] 4. Emotion engine: facial recognition software, voice analysis software

[0663] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0664] Step 1: Enter user information and emotions

[0665] User:

[0666] The user starts the application and inputs the category of interest (e.g., museums, castles, historical buildings), the amount of time available (e.g., 3 hours, 1 day), and the current location or the place they want to visit (e.g., Tokyo, Kyoto). This becomes the input data.

[0667] Device:

[0668] The device receives the user's input data and uses an emotion engine to perform real-time facial recognition and voice analysis to detect the user's current emotional state (e.g., excited, curious). The detected emotional data is then added to the input data.

[0669] output:

[0670] The output of this step is a data package containing category, availability, location information, and emotion data.

[0671] ---

[0672] Step 2: Data collection

[0673] server:

[0674] The server receives the data package sent from the device. Based on this data, it collects relevant tourist destination data from an internal database and external APIs (e.g., Google Places API, Yelp API). Specifically, the server makes API requests based on category, location, and availability.

[0675] output:

[0676] The output of this step is a dataset containing detailed data about tourist destinations (e.g., location, opening hours, prices, reviews, attractions).

[0677] ---

[0678] Step 3: Generate Routes and Content

[0679] server:

[0680] The server uses the tourist destination dataset to calculate the optimal route that can be visited within a specified time frame. It uses an algorithm to calculate the shortest route, taking into account transportation mode (e.g., walking, public transportation), distance, and duration of stay. It also takes into account emotion data and sets priorities according to the user's interests and emotions. It then generates detailed explanatory content for each tourist destination, including text, images, and audio data that includes historical background, highlights, and exhibits about each location.

[0681] output:

[0682] The output of this step is guide information that integrates the optimal route with detailed explanatory content.

[0683] ---

[0684] Step 4: Provide guidance

[0685] Device:

[0686] The device receives the guide information sent from the server and displays it on the application screen. Specifically, the device displays a map of the optimal route, lists detailed information about each tourist spot, and plays audio guides.

[0687] output:

[0688] The output of this step is guide information that is visually and audibly accessible to the user.

[0689] ---

[0690] Step 5: Emotion monitoring and dynamic regulation

[0691] server:

[0692] The emotion engine continues to monitor the user's emotional state in real time while sightseeing. If the user's emotion changes (e.g., from excitement to fatigue), the device sends that data to the server. The server then regenerates the optimal route and commentary content based on this new emotional data.

[0693] Device:

[0694] The device receives the regenerated guide information and displays it again, and the user continues sightseeing using the new optimal route and commentary information.

[0695] output:

[0696] The output of this step is new guide information with a re-adjusted optimal route and detailed explanatory content.

[0697] (Application example 2)

[0698] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0699] The purpose of this invention is to improve user satisfaction by recognizing users' interests and emotions in real time in a tourist guide system and providing detailed information on tourist spots and optimal routes based on that information. In particular, conventional tourist guide systems lack a flexible approach that responds to changes in users' emotions, and have the problem that the tourist experience for users is uniform and it is difficult to respond to individual needs.

[0700] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting tourist spot data based on information input by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected tourist spot data, means for acquiring emotion data using an emotion engine that recognizes the user's emotions in real time, means for setting priorities based on the user's emotional state, means for generating detailed explanation content for each tourist spot, means for integrating the generated route and explanation content to create complete guide information, means for sending the created guide information to the user's terminal, and means for regenerating the route and explanation content in real time based on changes in the user's emotions. This makes it possible to provide flexible and sophisticated tourist guide information that suits the user's interests and emotional state.

[0701] "Information entered by the user" refers to information such as tourist spot conditions, categories of interest, available times, current location, or places you wish to visit.

[0702] "Tourist attraction data" refers to tourist locations such as museums, historical buildings, and natural landscapes, as well as detailed information about them.

[0703] "Specified Conditions" refers to specific conditions specified by the User, such as categories of interest, available times, or desired locations to visit.

[0704] An "optimal route" refers to the route that most efficiently visits all the tourist spots that can be visited within the specified conditions.

[0705] An "emotion engine" refers to technology or a system that recognizes a user's emotional state in real time.

[0706] "Emotion Data" refers to information about the user's emotional state as recognized by the Emotion Engine.

[0707] "Priority" refers to the order in which the importance of tourist attractions and information is determined based on the user's interests and emotional state.

[0708] "Detailed explanatory content" refers to detailed explanations of tourist spots, including their historical background, highlights, and exhibit contents.

[0709] "Guide information" refers to information that integrates the generated optimal route with detailed explanatory content for each tourist spot.

[0710] "User's device" refers to an information display device held by the user, such as a smartphone, tablet, or smart glasses.

[0711] "Regeneration in real time" refers to instantly recreating new routes and explanatory content based on changes in users' emotions.

[0712] Overall system configuration

[0713] This invention is a system that provides tourist guide information based on the user's interests and emotions. The system consists of four main components: the user's terminal, a server, a database, and an emotion engine. These components work together to provide the user with the most appropriate tourist guide information.

[0714] Inputting user information and emotions

[0715] Device:

[0716] Users use devices such as smartphones or smart glasses to input categories of interest (fashion, historical landmarks, etc.), available time (e.g., 2 hours), and their current location or a place they want to visit. An emotion engine (e.g., Affectiva SDK) then recognizes the user's emotional state in real time.

[0717] Data collection

[0718] server:

[0719] The server receives user information sent from the device and emotion data from the emotion engine. Based on this information, the server collects data on related tourist spots from a database or external API. The tourist spot data includes stores in the shopping mall and neighboring tourist spots.

[0720] Route and Content Generation

[0721] server:

[0722] Based on the collected tourist spot data, the system calculates the optimal route that can be visited within the specified conditions. The calculation takes into account factors such as transportation method, distance, stay time, and the user's emotional state. It also sets priorities based on emotional data obtained by an emotion engine, and selects a route optimized for interests and emotions. It also generates detailed explanatory content for each tourist spot (e.g., historical background, highlights, exhibits).

[0723] Guide provided

[0724] Device:

[0725] The guide information created on the server is sent to the user's device and displayed through the application, allowing users to see the optimal route and detailed explanations of each spot at a glance.

[0726] Emotion monitoring and dynamic regulation

[0727] server:

[0728] The emotion engine continuously monitors the user's emotional state in real time. If the user's emotions change during sightseeing, that information is also sent to the server. Based on these emotional changes, the server regenerates the optimal route and explanatory content in real time and sends new guide information to the user's device.

[0729] Specific use cases

[0730] For example, if a user is interested in the "fashion" category in a shopping mall and plans to spend two hours shopping, they put on the smart glasses and input "fashion" and "two hours." The emotion engine recognizes this as "excitement." The system then collects stores in the mall that sell fashion items from a database and generates an optimal route. As detailed information about products and stores that interest them during shopping is provided, the system will suggest a new route if their emotions change.

[0731] Prompt Sentence Examples

[0732] "I want to create a guide app that provides real-time information on the best route and products for users to enjoy a two-hour shopping trip in the 'fashion' category at a shopping mall. I want to dynamically adjust the information based on the user's emotions. What approach can you think of?"

[0733] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0734] Step 1:

[0735] The server receives user information (interest categories, available time, current location) and emotional data (real-time emotional state) from the user's device. This allows the system to obtain the basic data necessary to provide tourist guide information. This input includes data such as "fashion," "2 hours," and "excitement."

[0736] Step 2:

[0737] The server collects tourist attraction data from databases and external APIs. This data includes, for example, the stores in a shopping mall, the products they sell, their opening hours, etc. Based on the tourist attraction requirements entered, the server executes database queries to collect relevant data.

[0738] Step 3:

[0739] The server calculates the optimal route based on the acquired tourist attraction data within the specified conditions. The calculation takes into account factors such as transportation mode, distance, duration of stay, and the user's emotional state. For example, if the user is "excited," the server will suggest a route that involves active movement. The output is a prioritized list of stores and tourist attractions.

[0740] Step 4:

[0741] The server prioritizes tourist spots and shops based on emotion data acquired using an emotion engine. For example, if a user feels "tired," it prioritizes relaxation spots in the route. This process is based on data analysis performed by an emotion recognition engine (e.g., Affectiva SDK).

[0742] Step 5:

[0743] The server generates detailed explanatory content for each tourist spot, including the tourist spot's historical background, highlights, exhibits, etc. The explanatory content is generated using detailed information obtained from the database and a text generation model (e.g., a generative AI model).

[0744] Step 6:

[0745] The server integrates the generated route and commentary content to create complete guide information. The server combines the route information and detailed commentary to create guide information in a format that is easy for users to view. The output result is generated as a comprehensive guide data set.

[0746] Step 7:

[0747] The server sends the created guide information to the user's device, which then uses an application to display the received guide information, providing the information in the most optimal format for the user. The guide content, updated in real time, is displayed on the display of the smart glasses or smartphone.

[0748] Step 8:

[0749] If the user's emotions change in real time, the emotion engine reacquires that information and sends it to the server. The server then regenerates the optimal route and explanatory content based on this new emotion data, updating the guide information in real time. For example, if the user's emotions change from "excited" to "tired," a relaxing spot will be added to the route.

[0750] This allows users to always receive the latest information and tourist guides that best suit their circumstances.

[0751] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0752] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0753] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0754] [Third embodiment]

[0755] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0756] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0757] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0758] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0759] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0760] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0761] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0762] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0763] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0764] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0765] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0766] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0767] The present invention is a system for individually providing users with information necessary for them to enjoy sightseeing more efficiently. Specific embodiments of the system will be described below.

[0768] Overall system configuration

[0769] The system consists of three main components: the user's terminal, the server, and the database. Each component works together to provide the user with the most suitable tourist guide information.

[0770] Entering user information

[0771] Device:

[0772] Users use the application to input their interests (e.g., museums, castles, historical buildings), the amount of time they have available (e.g., 3 hours, 1 day), and their current location or a place they want to visit (e.g., Tokyo, Kyoto).

[0773] Data collection

[0774] server:

[0775] The server receives user information sent from the device and uses this information to collect data on related tourist attractions from an internal database or external APIs. The tourist attractions covered include a wide range of categories, such as museums, castles, and historical buildings.

[0776] Route and Content Generation

[0777] server:

[0778] Based on the collected tourist spot data, the system calculates the optimal route that can be visited within a specified time. For example, if a user specifies "Tokyo," "Museums and Castles," and "within three hours," the system will collect information on Tokyo's major museums and castles and calculate an efficient route to visit these spots.

[0779] It also generates detailed commentary content for each tourist spot, including the historical background, highlights, and exhibits of the spot. For example, it provides specific information such as what exhibits are on display at the Tokyo National Museum and their historical significance.

[0780] Guide provided

[0781] Device:

[0782] The guide information created on the server is sent to the user's device and displayed through the application, allowing the user to see the optimal route and detailed explanations of each spot at a glance.

[0783] For example, along with the route "Tokyo National Museum → Hama Rikyu Gardens → Imperial Palace," information about each spot such as "Exhibition Room 7 contains ancient Japanese sculptures, and their historical background is..." is displayed.

[0784] Specific examples

[0785] Example 1:

[0786] If a user is interested in historical buildings and only plans to visit Kyoto for half a day, they can enter "historical buildings," "Kyoto," and "half day." The system will then collect Kyoto's major historical buildings from a database and generate a route that includes Nijo Castle, Kinkakuji Temple, and Kiyomizu-dera Temple. It will also generate detailed commentary about the history and highlights of each spot. This information is sent to the user's device and displayed through the application.

[0787] Example 2:

[0788] If a user wants to spend a day sightseeing in New York, they simply enter "museums," "New York," and "1 day." The system generates a route that includes the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art, providing detailed commentary on the characteristics and highlights of each museum. Users can enjoy sightseeing while checking this guide information through the app.

[0789] By using this system, users can obtain the optimal sightseeing route and detailed guide information based on their interests and time, resulting in an efficient and satisfying sightseeing experience.

[0790] The processing flow will be explained below.

[0791] Step 1:

[0792] The user opens the application and enters the category of interest (e.g., museums, castles, historical buildings), the amount of time available (e.g., 3 hours, 1 day), and either their current location or a place they want to visit (e.g., Tokyo, Kyoto).

[0793] Step 2:

[0794] The device receives the information entered by the user and sends it to the server, specifically, data including tourist categories, available times, and location information.

[0795] Step 3:

[0796] The server receives user information sent from the device, then uses the received information to collect data on related tourist attractions using an internal database or external APIs. The tourist attractions covered include a wide range of categories, such as museums, castles, and historical buildings.

[0797] Step 4:

[0798] Based on the tourist spot data collected by the server, the optimal route that can be visited within a specified time is calculated, taking into account multiple factors such as transportation method, distance, and duration of stay.

[0799] Step 5:

[0800] The server generates detailed explanatory content for each tourist spot. The explanation includes the historical background, highlights, exhibits, etc. of the spot. Information is created to be easily understood by users using text, images, audio data, etc.

[0801] Step 6:

[0802] The server integrates the generated route and commentary content to create a complete guide, while providing more personalized guide information by setting priorities based on the user's interests.

[0803] Step 7:

[0804] The server then sends the created guide information to the user's device, which includes route guidance and detailed explanations of each tourist spot.

[0805] Step 8:

[0806] The guide information received by the device is displayed on the application, allowing users to enjoy sightseeing while viewing the optimal route guidance and detailed guide information for each spot through the app.

[0807] Example 1

[0808] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0809] Conventional tourist information systems can collect tourist spot data based on information entered by users, but they lack the functionality to generate optimal tourist routes based on the user's interests and available time, and to provide detailed explanatory information. This makes it difficult for users to efficiently enjoy sightseeing within their limited time. There is also a need for systems that can appropriately prioritize the collected tourist spot information and provide the most appropriate guide information to users.

[0810] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0811] In this invention, the server includes a means for collecting data on tourist attractions based on information entered by the user, a means for calculating the optimal route that can be visited within specified conditions based on the collected data on tourist attractions, and a means for using a generative AI model to generate detailed explanatory information for each tourist attraction. This makes it possible to generate optimal tourist routes according to the user's individual interests and conditions, and to provide comprehensive and detailed guide information.

[0812] "User" refers to an individual or organization that uses the tourist information system.

[0813] "Tourist destinations" refer to places that tourists visit, such as historical buildings, museums, and parks.

[0814] A "generative AI model" refers to an artificial intelligence model that generates information using natural language processing technology.

[0815] "Guide information" refers to comprehensive tourist information data including detailed explanations of tourist spots, optimal route guidance, and related information.

[0816] "Terminal" refers to a device such as a smartphone, tablet, or PC that a user uses to access the system.

[0817] "Data collection means" refers to a part of the system that collects data on related tourist destinations based on user input information.

[0818] "Means for calculating optimal route" refers to the system's algorithm that calculates a route for efficiently visiting tourist spots that can be visited within specified conditions.

[0819] "Explanatory information" refers to detailed explanations of the historical background, highlights, exhibit contents, etc. of tourist attractions.

[0820] "Transmission means" refers to a part of the system for transmitting the generated guide information to the user's terminal.

[0821] "Display means" refers to a part of the system for visually displaying guide information received on the user's terminal.

[0822] MODE FOR CARRYING OUT THE INVENTION

[0823] The present invention is a system that individually provides users with the information they need to enjoy sightseeing more efficiently. This system consists of three main components: a user terminal, a server, and a database. Specific embodiments of each component are described below.

[0824] Entering user information

[0825] Device:

[0826] Using a dedicated application, users input the tourist attractions they are interested in (e.g., museums, castles, historical buildings), the amount of time they have available for sightseeing (e.g., 3 hours, 1 day), and the places they want to visit (e.g., Tokyo, Kyoto). The device provides an input form and a submit button to receive this information.

[0827] Data collection

[0828] server:

[0829] The server receives user information sent from the device. Based on the received information, the server collects data on related tourist attractions using an internal database and external APIs (e.g., Google Places API, TripAdvisor API). This data includes the name, location, opening hours, and ratings of the tourist attractions.

[0830] Route and Content Generation

[0831] server:

[0832] The server analyzes the collected tourist destination data and uses an algorithm (e.g., Dijkstra's algorithm, A algorithm) to calculate the optimal tourist route that can be visited within a specified time. At the same time, it uses a generative AI model (e.g., GPT-4) to generate detailed explanatory information for each tourist destination. The explanation includes the history, highlights, and exhibits of the destination.

[0833] Examples:

[0834] If a user inputs "art museum," "Tokyo," and "3 hours," the server uses this information to collect data on major art museums in Tokyo (e.g., Tokyo National Museum, Mori Art Museum, Ueno Royal Museum), calculates the optimal route to visit them efficiently within 3 hours, and then uses GPT-4 to generate detailed descriptions of each museum.

[0835] Example prompt sentence:

[0836] "Please tell me about the historical background of the Tokyo National Museum in Tokyo and what attractions it is worth visiting."

[0837] Guide provided

[0838] Device:

[0839] The guide information (optimal route and detailed commentary information) created on the server is sent to the user's device and displayed through the application. Users can check the optimal route and detailed commentary of each tourist spot within the application.

[0840] Specific behavior:

[0841] Users can check the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" within the app, and explanatory information for each spot will be displayed in a pop-up.

[0842] This system allows users to obtain the optimal sightseeing route and detailed guide information based on their individual interests and conditions, providing an efficient and satisfying sightseeing experience within a limited time frame.

[0843] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0844] Step 1:

[0845] Entering user information

[0846] Device:

[0847] The user opens the application and inputs their interests (e.g., museums, castles, historical buildings), available time (e.g., 3 hours, 1 day), and the places they want to visit (e.g., Tokyo, Kyoto). The input information is sent to the server by pressing the send button.

[0848] Input: The user enters "museum," "Tokyo," and "3 hours" into an input form within the app.

[0849] Output: The user's input data is sent to the server.

[0850] Specific operation: When the user presses the "Submit" button, the entered information is sent to the server.

[0851] Step 2:

[0852] Data collection

[0853] server:

[0854] The server receives the user information sent from the device and collects data on related tourist attractions by sending queries to an internal database and external APIs (e.g., Google Places API, TripAdvisor API) to obtain data on related tourist attractions.

[0855] Input: User input data (interests, location, time).

[0856] Output: Tourist attraction data (name, location, opening hours, rating, etc.).

[0857] Specific operation: The server obtains museum data via the Google Places API based on the information "Tokyo," "museum," and "3 hours," and stores it in an internal database.

[0858] Step 3:

[0859] Route and Content Generation

[0860] server:

[0861] Analyze the collected tourist destination data and calculate the optimal route that can be visited within a specified time. Use algorithms (e.g., Dijkstra algorithm, A algorithm) to find an efficient route. Next, use a generative AI model (e.g., GPT-4) to generate detailed descriptions of each tourist destination.

[0862] Input: tourist destination data.

[0863] Output: Optimal route, explanatory information.

[0864] Specific operation: Based on data on Tokyo's art museums, the server calculates the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" and uses a generative AI model to create detailed explanations of each museum.

[0865] Step 4:

[0866] Guide provided

[0867] Device:

[0868] The guide information (optimal route and detailed explanation) created on the server is sent to the user's device and displayed through the application. Users can check the optimal route and detailed explanation of each tourist spot within the app.

[0869] Input: Guide information received from the server.

[0870] Output: Display of guide information on the user's terminal.

[0871] Specific operation: The guide information sent by the server is received by the user's device, and the app displays the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" along with detailed explanations of each spot.

[0872] (Application example 1)

[0873] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0874] Today's consumers want to efficiently enjoy shopping in brick-and-mortar stores by obtaining the most appropriate information based on their interests, budget, and time. However, existing systems are specialized in tourist attractions and lack the functionality to collect extensive data applicable to brick-and-mortar shopping, provide appropriate route guidance, and provide product information for each store. Therefore, a system that can provide an efficient and satisfying shopping experience is needed.

[0875] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0876] In this invention, the server includes means for collecting store data based on information entered by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected store data, and means for generating detailed explanation content for each store, thereby enabling an efficient and satisfying shopping experience in a physical store.

[0877] "User-entered information" refers to data entered by a user specifying their interests, budget, and available time.

[0878] "Store data" refers to data that includes detailed information such as the location of each store, the products they carry, sales information, and store reputation.

[0879] An "optimal route" is a route that efficiently visits multiple stores that can be visited within specified conditions.

[0880] "Explanatory content" is a collection of text and images containing detailed information such as the characteristics of each store, product information, promotion information, and reputation.

[0881] "Guide information" is an information package provided to users that combines the optimal route with detailed explanations of each store.

[0882] A "user device" is a portable electronic device used by a user, such as a smartphone or tablet.

[0883] The present invention is a system that individually provides information to users to help them enjoy shopping at physical stores efficiently. This system provides the optimal shopping route and detailed store information based on the user's interests, budget, and available time, and includes the following components.

[0884] Overall system configuration

[0885] This system consists of three main components: the user's terminal, the server, and the database. Each component works together to provide the user with optimal shopping guide information.

[0886] Entering user information

[0887] Device:

[0888] Users use a smartphone application to input their interests (e.g., fashion, home appliances, food), budget (e.g., within 10,000 yen, within 20,000 yen), and available time (e.g., 1 hour, 2 hours). Current location information is also automatically obtained.

[0889] Data collection

[0890] server:

[0891] The server receives user information sent from the device. Based on this information, the server collects related store data from an internal database or external API (e.g., store information, product information, sale information).

[0892] Route and Content Generation

[0893] server:

[0894] Based on the collected store data, the system calculates the optimal route that can be visited within the specified conditions. For example, if a user specifies "fashion," "under 10,000 yen," and "two hours," the system calculates a route that efficiently visits nearby fashion-related stores. It also generates detailed explanatory content for each store. The explanation includes the store's features, product information, sales information, reputation, and more.

[0895] Guide provided

[0896] Device:

[0897] The guide information created on the server is sent to the user's device and displayed through the application, allowing the user to see the optimal route and detailed explanations of each store at a glance.

[0898] Specific examples

[0899] Example 1:

[0900] If a user is interested in home appliances and plans to spend two hours shopping for less than 20,000 yen, the user simply enters "home appliances," "less than 20,000 yen," and "2 hours." The system then collects nearby home appliance-related stores from a database and generates the optimal store route (e.g., major home appliance retailer A, home appliance specialty store B, discount store C). It also provides detailed information about featured products, sales, and reputations at each store. Users can use the app to enjoy a comfortable shopping experience.

[0901] Example 2:

[0902] If a user is interested in food and wishes to spend under 5,000 yen on shopping for one hour, they simply enter "food," "under 5,000 yen," and "one hour." The system then collects information on nearby supermarkets and specialty stores and generates the optimal route (e.g., high-end supermarket A, organic food store B, discount store C). It then provides detailed information on recommended products and promotions at each store.

[0903] Example prompts to input to the generative AI model

[0904] Prompt statement:

[0905] The user is interested in "home appliances" and plans to shop for "2 hours" for "less than 20,000 yen." Based on these conditions, generate the optimal route for efficient shopping and detailed information for each store.

[0906] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0907] Step 1:

[0908] Entering user information

[0909] Device: The user opens the application and enters their interests (e.g., fashion, home appliances, food), budget (e.g., under 10,000 yen, under 20,000 yen), and available time (e.g., 1 hour, 2 hours). The application also automatically obtains their current location information. This allows the device to prepare for sending the user's interests, budget, time, and location data to the server.

[0910] Step 2:

[0911] Data reception and processing

[0912] Server: Receives user information sent from the device. The technology used is API calls using the HTTP protocol. As input, it receives the user's interests, budget, available time, and current location data, and based on this, it collects related store data from a database or external API (e.g., store information API). The server temporarily stores the acquired store data and prepares it for the next step of processing.

[0913] Step 3:

[0914] Calculating the best route

[0915] Server: Based on the collected store data, calculates the optimal route that can be visited within the conditions specified by the user. The inputs are the user's interests, budget, time, location information, and store data. The server uses this data to execute an optimal route calculation method (e.g., Dijkstra's algorithm or A algorithm). As a result, it calculates the optimal store visit order and route and passes it to the next step.

[0916] Step 4:

[0917] Generating explanatory content

[0918] Server: Generates detailed explanatory content for each store. Store data and optimal route information are used as input. The server utilizes a generative AI model to generate explanatory content for each store (e.g., product information, sale information, reputation, etc.). Specifically, it uses OpenAI's GPT model and generates explanatory text by inputting a prompt text. For example, it generates content such as, "This store has the latest home appliances, and we especially recommend the latest refrigerator."

[0919] Step 5:

[0920] Guide information integration

[0921] Server: Integrates the generated optimal route and explanatory content to create complete guide information. The optimal route information and explanatory content are used as input. The server formats this data and integrates it into a format that users can understand at a glance (e.g., a combination of maps and text). As a result, complete guide information is generated and passed to the next step.

[0922] Step 6:

[0923] Sending guide information

[0924] Server: Sends the created guide information to the user's device. A real-time communication protocol (e.g., WebSocket) is used to send data. The server uses the integrated guide information as input and prepares it for transmission to the user's device for display.

[0925] Step 7:

[0926] Display guide information

[0927] Terminal: The received guide information is displayed on the user's terminal. The guide information sent from the server is received as input and displayed through the application. The user can check the optimal route guidance and detailed explanations of each store on the application interface. A specific display method could be to draw the route on a map and present information about each store in text or images.

[0928] This processing step allows customers to have an efficient and satisfying shopping experience in a physical store.

[0929] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0930] The present invention is a system for providing tourist guide information based on the user's interests and emotions. A specific embodiment of the system will be described below.

[0931] Overall system configuration

[0932] The system consists of four main components: the user's device, the server, the database, and the emotion engine. These components work together to provide optimal tourist guide information to users.

[0933] Inputting user information and emotions

[0934] Device:

[0935] Users use the application to input categories of interest (museums, castles, historical buildings, etc.), available time (e.g., 3 hours, 1 day), and current location or place they want to visit (e.g., Tokyo, Kyoto).The emotion engine then recognizes the user's emotional state in real time.

[0936] Data collection

[0937] server:

[0938] The server receives user information sent from the device and emotion data from the emotion engine. Based on this information, the server collects data on related tourist spots from an internal database or external API. The tourist spot data covers a wide range of categories, including museums, castles, and historical buildings.

[0939] Route and Content Generation

[0940] server:

[0941] Based on the collected tourist spot data, the system calculates the optimal route for visiting within a specified time frame, taking into account factors such as transportation mode, distance, and duration of stay. It also sets priorities based on the user's emotional state and selects a route optimized for their interests and emotions.

[0942] Furthermore, detailed explanatory content is generated for each tourist spot, including the historical background, highlights, and exhibits of the spot. Information is provided to users in an easy-to-understand format using text, images, and audio data.

[0943] Guide provided

[0944] Device:

[0945] The guide information created on the server is sent to the user's device and displayed through the application, allowing users to see the optimal route and detailed explanations of each spot at a glance.

[0946] Emotion monitoring and dynamic regulation

[0947] server:

[0948] The emotion engine continuously monitors the user's emotional state in real time. If the user's emotions change during sightseeing, that information is also sent to the server. Based on these emotional changes, the server regenerates the optimal route and explanatory content in real time and sends new guide information to the user's device.

[0949] Specific examples

[0950] Example 1:

[0951] If a user is interested in historical buildings and only plans to visit Kyoto for half a day, they can enter "historical buildings," "Kyoto," and "half a day" and have the emotion engine recognize their current emotion (e.g., excited, curious). The system then collects Kyoto's major historical buildings from a database and generates a route that includes Nijo Castle, Kinkaku-ji Temple, and Kiyomizu-dera Temple. It also generates detailed commentary about the history and highlights of each spot. If the user's emotion changes during sightseeing (e.g., tired, needing a break), the route and commentary content are adjusted in real time. This information is sent to the user's device and displayed through the application.

[0952] Example 2:

[0953] If a user wants to spend a day sightseeing in New York, they can input "museum," "New York," and "one day," and the emotion engine will recognize emotions (e.g., excitement, anticipation). The system will generate a route that includes the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art. Detailed commentary will be provided on the characteristics and highlights of each museum. If the user's emotional state changes during the tour (e.g., surprise, excitement), the system will use that information to readjust the optimal route and commentary content and provide new guide information.

[0954] This system allows users to obtain the optimal sightseeing route and detailed guide information based on their interests and emotions, resulting in an efficient and satisfying sightseeing experience.

[0955] The processing flow will be explained below.

[0956] Step 1:

[0957] The user opens the application and inputs the category of interest (museums, castles, historical buildings, etc.), the time available (e.g., 3 hours, 1 day), and the current location or place they want to visit (e.g., Tokyo, Kyoto).The emotion engine then recognizes the user's emotional state in real time.

[0958] Step 2:

[0959] The device sends the user's input information and emotion data recognized by the emotion engine to the server, including interest categories, time, location, and emotional state.

[0960] Step 3:

[0961] The server receives user information and emotion data sent from the device, and then collects related tourist spot data from an internal database or external APIs based on predefined categories such as museums, castles, and historical buildings.

[0962] Step 4:

[0963] The server calculates the optimal route for visiting tourist spots within a specified time frame based on the tourist spot data collected by the server. This calculation takes into account factors such as transportation mode, distance, duration of stay, and the user's emotional state. The system also dynamically changes the priority of tourist spots based on the user's emotional state.

[0964] Step 5:

[0965] The server generates detailed explanatory content for each tourist spot, including the historical background, highlights, and exhibits of the spot. The information is provided in the form of text, images, audio data, and more.

[0966] Step 6:

[0967] The server integrates the generated route and explanatory content to create a complete guide information, and at the same time, provides personalized guide information by setting priorities according to the user's emotional state.

[0968] Step 7:

[0969] The server then sends the created guide information to the user's device, which includes route guidance and detailed explanations of each tourist spot.

[0970] Step 8:

[0971] The device receives the guide information and displays it on the application, allowing users to view the optimal route and detailed guide information for each spot through the app.

[0972] Step 9:

[0973] The emotion engine monitors the user's emotional state in real time. If the emotion changes, the information is sent to the server. For example, it can detect when the user changes from tired to excited.

[0974] Step 10:

[0975] Based on the new emotion data received by the server, the optimal route and explanatory content are regenerated in real time, and the guide information is updated based on the new priorities and emotional state.

[0976] Step 11:

[0977] The server retransmits the updated guide information to the user's device, including the modified route guidance and newly generated spot descriptions.

[0978] Step 12:

[0979] The device receives the retransmitted guide information and displays it on the application, allowing users to continue sightseeing by viewing the newly optimized route guidance and commentary in real time.

[0980] Example 2

[0981] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0982] Conventional tourist guide systems have had difficulty dynamically providing optimal routes and explanatory content based on users' interests and emotions. Furthermore, fixed information alone makes it difficult to increase user satisfaction, and they are unable to respond flexibly to situations where real-time adjustments are essential. Therefore, there is a need for systems that can dynamically provide optimal tourist routes and detailed guide information based on users' interests and emotions.

[0983] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0984] In this invention, the server includes means for collecting tourist destination data based on information entered by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected tourist destination data, and means for generating detailed commentary content for each tourist destination, which makes it possible to dynamically provide optimal tourist routes and detailed guide information according to the user's interests and emotions.

[0985] "User" refers to an individual or organization that uses the system to obtain tourist guide information.

[0986] "Tourist destinations" refer to places or facilities that are considered worth visiting, such as historical buildings, museums, and castles.

[0987] "Data" refers to general information about tourist destinations, such as their location, opening hours, prices, reviews, and attractions.

[0988] "Server" refers to a computer system that collects, analyzes, stores, and provides data.

[0989] "Terminal" refers to electronic devices such as smartphones and tablets operated by users.

[0990] "Emotional state" refers to the user's psychological state, such as excitement, interest, fatigue, expectation, and emotion.

[0991] "Emotion engine" refers to a system that detects a user's emotional state in real time through facial recognition and voice analysis.

[0992] The "optimal route" refers to a route that is calculated to ensure efficient and satisfying sightseeing based on the conditions and emotional state entered by the user.

[0993] "Explanatory content" refers to detailed information about each tourist destination, such as its historical background, highlights, and exhibits, provided in text, images, and audio.

[0994] "Guide information" refers to a comprehensive tourist guide provided to users that integrates optimal routes and explanatory content.

[0995] The present invention relates to a system for providing tourist guide information based on the interests and emotions of users. Specifically, the system is configured as follows.

[0996] The system consists of four main components: the user's terminal, the server, the database, and the emotion engine. Each component works together using the following hardware and software to provide tourist guide information.

[0997] Inputting user information and emotions

[0998] User:

[0999] Users launch the application on their smartphone or tablet and input their category of interest (e.g., museums, castles, historical buildings), the amount of time they have available (e.g., 3 hours, 1 day), and their current location or a place they want to visit (e.g., Tokyo, Kyoto). The emotion engine uses facial recognition and voice analysis to detect the user's emotional state in real time.

[1000] Data collection

[1001] server:

[1002] The system receives information and sentiment data sent from users' devices and uses external APIs such as the Google Places API and Yelp API to collect relevant tourist destination data, including details such as location, opening hours, prices, reviews, and attractions.

[1003] Route and Content Generation

[1004] server:

[1005] Based on the collected data on tourist attractions, the system calculates the optimal route for visiting within a specified time frame, taking into account factors such as transportation mode (e.g., walking, public transportation), distance, and duration of stay. It prioritizes spots based on the user's emotional state and selects a route optimized for their interests and emotions. It also generates detailed explanatory content for each tourist attraction. The explanation includes the historical background, highlights, and exhibits of the spot, and is provided using text, images, and audio data.

[1006] Guide provided

[1007] Device:

[1008] The guide information created on the server is sent to the user's device and displayed through the application. Users can check the optimal route guidance and detailed explanations of each spot to continue their sightseeing.

[1009] Emotion monitoring and dynamic regulation

[1010] server:

[1011] The emotion engine continuously monitors the user's emotional state in real time. Emotional data is sent to the server in response to changes in emotion while sightseeing. The server uses this data to regenerate the optimal route and explanatory content in real time. The new guide information is then sent back to the user's device and displayed.

[1012] Specific examples

[1013] Example 1: Half-day tour of Kyoto's historical buildings

[1014] User input:

[1015] "Historical Buildings" "Kyoto" "Half Day" "Current Emotion: Excitement"

[1016] Server Action:

[1017] The system collects Kyoto's major historical buildings (Nijo Castle, Kinkakuji Temple, and Kiyomizu-dera Temple) from a database and generates an optimal route. If the user's emotion changes to "fatigue" during sightseeing, a new route and explanation will be generated and sent to the user's device.

[1018] Example 2: One day tour of New York art museums

[1019] User input:

[1020] "Museum," "New York," "One Day," "Current Emotions: Expectations"

[1021] Server Action:

[1022] The system collects data from the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art, and generates commentary about the characteristics and highlights of each museum. If the user's emotion changes to "emotion" during sightseeing, the system will adjust the route and commentary and provide it to the user's device.

[1023] Hardware and software used

[1024] 1. Devices: smartphones, tablets

[1025] 2. Servers: Database servers, web servers

[1026] 3. External APIs: Google Places API, Yelp API

[1027] 4. Emotion engine: facial recognition software, voice analysis software

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

[1029] Step 1: Enter user information and emotions

[1030] User:

[1031] The user starts the application and inputs the category of interest (e.g., museums, castles, historical buildings), the amount of time available (e.g., 3 hours, 1 day), and the current location or the place they want to visit (e.g., Tokyo, Kyoto). This becomes the input data.

[1032] Device:

[1033] The device receives the user's input data and uses an emotion engine to perform real-time facial recognition and voice analysis to detect the user's current emotional state (e.g., excited, curious). The detected emotional data is then added to the input data.

[1034] output:

[1035] The output of this step is a data package containing category, availability, location information, and emotion data.

[1036] ---

[1037] Step 2: Data collection

[1038] server:

[1039] The server receives the data package sent from the device. Based on this data, it collects relevant tourist destination data from an internal database and external APIs (e.g., Google Places API, Yelp API). Specifically, the server makes API requests based on category, location, and availability.

[1040] output:

[1041] The output of this step is a dataset containing detailed data about tourist destinations (e.g., location, opening hours, prices, reviews, attractions).

[1042] ---

[1043] Step 3: Generate Routes and Content

[1044] server:

[1045] The server uses the tourist destination dataset to calculate the optimal route that can be visited within a specified time frame. It uses an algorithm to calculate the shortest route, taking into account transportation mode (e.g., walking, public transportation), distance, and duration of stay. It also takes into account emotion data and sets priorities according to the user's interests and emotions. It then generates detailed explanatory content for each tourist destination, including text, images, and audio data that includes historical background, highlights, and exhibits about each location.

[1046] output:

[1047] The output of this step is guide information that integrates the optimal route with detailed explanatory content.

[1048] ---

[1049] Step 4: Provide guidance

[1050] Device:

[1051] The device receives the guide information sent from the server and displays it on the application screen. Specifically, the device displays a map of the optimal route, lists detailed information about each tourist spot, and plays audio guides.

[1052] output:

[1053] The output of this step is guide information that is visually and audibly accessible to the user.

[1054] ---

[1055] Step 5: Emotion monitoring and dynamic regulation

[1056] server:

[1057] The emotion engine continues to monitor the user's emotional state in real time while sightseeing. If the user's emotion changes (e.g., from excitement to fatigue), the device sends that data to the server. The server then regenerates the optimal route and commentary content based on this new emotional data.

[1058] Device:

[1059] The device receives the regenerated guide information and displays it again, and the user continues sightseeing using the new optimal route and commentary information.

[1060] output:

[1061] The output of this step is new guide information with a re-adjusted optimal route and detailed explanatory content.

[1062] (Application example 2)

[1063] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1064] The purpose of this invention is to improve user satisfaction by recognizing users' interests and emotions in real time in a tourist guide system and providing detailed information on tourist spots and optimal routes based on that information. In particular, conventional tourist guide systems lack a flexible approach that responds to changes in users' emotions, and have the problem that the tourist experience for users is uniform and it is difficult to respond to individual needs.

[1065] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting tourist spot data based on information input by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected tourist spot data, means for acquiring emotion data using an emotion engine that recognizes the user's emotions in real time, means for setting priorities based on the user's emotional state, means for generating detailed explanation content for each tourist spot, means for integrating the generated route and explanation content to create complete guide information, means for sending the created guide information to the user's terminal, and means for regenerating the route and explanation content in real time based on changes in the user's emotions. This makes it possible to provide flexible and sophisticated tourist guide information that suits the user's interests and emotional state.

[1066] "Information entered by the user" refers to information such as tourist spot conditions, categories of interest, available times, current location, or places you wish to visit.

[1067] "Tourist attraction data" refers to tourist locations such as museums, historical buildings, and natural landscapes, as well as detailed information about them.

[1068] "Specified Conditions" refers to specific conditions specified by the User, such as categories of interest, available times, or desired locations to visit.

[1069] An "optimal route" refers to the route that most efficiently visits all the tourist spots that can be visited within the specified conditions.

[1070] An "emotion engine" refers to technology or a system that recognizes a user's emotional state in real time.

[1071] "Emotion Data" refers to information about the user's emotional state as recognized by the Emotion Engine.

[1072] "Priority" refers to the order in which the importance of tourist attractions and information is determined based on the user's interests and emotional state.

[1073] "Detailed explanatory content" refers to detailed explanations of tourist spots, including their historical background, highlights, and exhibit contents.

[1074] "Guide information" refers to information that integrates the generated optimal route with detailed explanatory content for each tourist spot.

[1075] "User's device" refers to an information display device held by the user, such as a smartphone, tablet, or smart glasses.

[1076] "Regeneration in real time" refers to instantly recreating new routes and explanatory content based on changes in users' emotions.

[1077] Overall system configuration

[1078] This invention is a system that provides tourist guide information based on the user's interests and emotions. The system consists of four main components: the user's terminal, a server, a database, and an emotion engine. These components work together to provide the user with the most appropriate tourist guide information.

[1079] Inputting user information and emotions

[1080] Device:

[1081] Users use devices such as smartphones or smart glasses to input categories of interest (fashion, historical landmarks, etc.), available time (e.g., 2 hours), and their current location or a place they want to visit. An emotion engine (e.g., Affectiva SDK) then recognizes the user's emotional state in real time.

[1082] Data collection

[1083] server:

[1084] The server receives user information sent from the device and emotion data from the emotion engine. Based on this information, the server collects data on related tourist spots from a database or external API. The tourist spot data includes stores in the shopping mall and neighboring tourist spots.

[1085] Route and Content Generation

[1086] server:

[1087] Based on the collected tourist spot data, the system calculates the optimal route that can be visited within the specified conditions. The calculation takes into account factors such as transportation method, distance, stay time, and the user's emotional state. It also sets priorities based on emotional data obtained by an emotion engine, and selects a route optimized for interests and emotions. It also generates detailed explanatory content for each tourist spot (e.g., historical background, highlights, exhibits).

[1088] Guide provided

[1089] Device:

[1090] The guide information created on the server is sent to the user's device and displayed through the application, allowing users to see the optimal route and detailed explanations of each spot at a glance.

[1091] Emotion monitoring and dynamic regulation

[1092] server:

[1093] The emotion engine continuously monitors the user's emotional state in real time. If the user's emotions change during sightseeing, that information is also sent to the server. Based on these emotional changes, the server regenerates the optimal route and explanatory content in real time and sends new guide information to the user's device.

[1094] Specific use cases

[1095] For example, if a user is interested in the "fashion" category in a shopping mall and plans to spend two hours shopping, they put on the smart glasses and input "fashion" and "two hours." The emotion engine recognizes this as "excitement." The system then collects stores in the mall that sell fashion items from a database and generates an optimal route. As detailed information about products and stores that interest them during shopping is provided, the system will suggest a new route if their emotions change.

[1096] Prompt Sentence Examples

[1097] "I want to create a guide app that provides real-time information on the best route and products for users to enjoy a two-hour shopping trip in the 'fashion' category at a shopping mall. I want to dynamically adjust the information based on the user's emotions. What approach can you think of?"

[1098] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1099] Step 1:

[1100] The server receives user information (interest categories, available time, current location) and emotional data (real-time emotional state) from the user's device. This allows the system to obtain the basic data necessary to provide tourist guide information. This input includes data such as "fashion," "2 hours," and "excitement."

[1101] Step 2:

[1102] The server collects tourist attraction data from databases and external APIs. This data includes, for example, the stores in a shopping mall, the products they sell, their opening hours, etc. Based on the tourist attraction requirements entered, the server executes database queries to collect relevant data.

[1103] Step 3:

[1104] The server calculates the optimal route based on the acquired tourist attraction data within the specified conditions. The calculation takes into account factors such as transportation mode, distance, duration of stay, and the user's emotional state. For example, if the user is "excited," the server will suggest a route that involves active movement. The output is a prioritized list of stores and tourist attractions.

[1105] Step 4:

[1106] The server prioritizes tourist spots and shops based on emotion data acquired using an emotion engine. For example, if a user feels "tired," it prioritizes relaxation spots in the route. This process is based on data analysis performed by an emotion recognition engine (e.g., Affectiva SDK).

[1107] Step 5:

[1108] The server generates detailed explanatory content for each tourist spot, including the tourist spot's historical background, highlights, exhibits, etc. The explanatory content is generated using detailed information obtained from the database and a text generation model (e.g., a generative AI model).

[1109] Step 6:

[1110] The server integrates the generated route and commentary content to create complete guide information. The server combines the route information and detailed commentary to create guide information in a format that is easy for users to view. The output result is generated as a comprehensive guide data set.

[1111] Step 7:

[1112] The server sends the created guide information to the user's device, which then uses an application to display the received guide information, providing the information in the most optimal format for the user. The guide content, updated in real time, is displayed on the display of the smart glasses or smartphone.

[1113] Step 8:

[1114] If the user's emotions change in real time, the emotion engine reacquires that information and sends it to the server. The server then regenerates the optimal route and explanatory content based on this new emotion data, updating the guide information in real time. For example, if the user's emotions change from "excited" to "tired," a relaxing spot will be added to the route.

[1115] This allows users to always receive the latest information and tourist guides that best suit their circumstances.

[1116] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1117] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1118] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1119] [Fourth embodiment]

[1120] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1121] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1122] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1123] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1124] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1125] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1126] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1127] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1128] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1129] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1130] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1131] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1132] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1133] The present invention is a system for individually providing users with information necessary for them to enjoy sightseeing more efficiently. Specific embodiments of the system will be described below.

[1134] Overall system configuration

[1135] The system consists of three main components: the user's terminal, the server, and the database. Each component works together to provide the user with the most suitable tourist guide information.

[1136] Entering user information

[1137] Device:

[1138] Users use the application to input their interests (e.g., museums, castles, historical buildings), the amount of time they have available (e.g., 3 hours, 1 day), and their current location or a place they want to visit (e.g., Tokyo, Kyoto).

[1139] Data collection

[1140] server:

[1141] The server receives user information sent from the device and uses this information to collect data on related tourist attractions from an internal database or external APIs. The tourist attractions covered include a wide range of categories, such as museums, castles, and historical buildings.

[1142] Route and Content Generation

[1143] server:

[1144] Based on the collected tourist spot data, the system calculates the optimal route that can be visited within a specified time. For example, if a user specifies "Tokyo," "Museums and Castles," and "within three hours," the system will collect information on Tokyo's major museums and castles and calculate an efficient route to visit these spots.

[1145] It also generates detailed commentary content for each tourist spot, including the historical background, highlights, and exhibits of the spot. For example, it provides specific information such as what exhibits are on display at the Tokyo National Museum and their historical significance.

[1146] Guide provided

[1147] Device:

[1148] The guide information created on the server is sent to the user's device and displayed through the application, allowing the user to see the optimal route and detailed explanations of each spot at a glance.

[1149] For example, along with the route "Tokyo National Museum → Hama Rikyu Gardens → Imperial Palace," information about each spot such as "Exhibition Room 7 contains ancient Japanese sculptures, and their historical background is..." is displayed.

[1150] Specific examples

[1151] Example 1:

[1152] If a user is interested in historical buildings and only plans to visit Kyoto for half a day, they can enter "historical buildings," "Kyoto," and "half day." The system will then collect Kyoto's major historical buildings from a database and generate a route that includes Nijo Castle, Kinkakuji Temple, and Kiyomizu-dera Temple. It will also generate detailed commentary about the history and highlights of each spot. This information is sent to the user's device and displayed through the application.

[1153] Example 2:

[1154] If a user wants to spend a day sightseeing in New York, they simply enter "museums," "New York," and "1 day." The system generates a route that includes the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art, providing detailed commentary on the characteristics and highlights of each museum. Users can enjoy sightseeing while checking this guide information through the app.

[1155] By using this system, users can obtain the optimal sightseeing route and detailed guide information based on their interests and time, resulting in an efficient and satisfying sightseeing experience.

[1156] The processing flow will be explained below.

[1157] Step 1:

[1158] The user opens the application and enters the category of interest (e.g., museums, castles, historical buildings), the amount of time available (e.g., 3 hours, 1 day), and either their current location or a place they want to visit (e.g., Tokyo, Kyoto).

[1159] Step 2:

[1160] The device receives the information entered by the user and sends it to the server, specifically, data including tourist categories, available times, and location information.

[1161] Step 3:

[1162] The server receives user information sent from the device, then uses the received information to collect data on related tourist attractions using an internal database or external APIs. The tourist attractions covered include a wide range of categories, such as museums, castles, and historical buildings.

[1163] Step 4:

[1164] Based on the tourist spot data collected by the server, the optimal route that can be visited within a specified time is calculated, taking into account multiple factors such as transportation method, distance, and duration of stay.

[1165] Step 5:

[1166] The server generates detailed explanatory content for each tourist spot. The explanation includes the historical background, highlights, exhibits, etc. of the spot. Information is created to be easily understood by users using text, images, audio data, etc.

[1167] Step 6:

[1168] The server integrates the generated route and commentary content to create a complete guide, while providing more personalized guide information by setting priorities based on the user's interests.

[1169] Step 7:

[1170] The server then sends the created guide information to the user's device, which includes route guidance and detailed explanations of each tourist spot.

[1171] Step 8:

[1172] The guide information received by the device is displayed on the application, allowing users to enjoy sightseeing while viewing the optimal route guidance and detailed guide information for each spot through the app.

[1173] Example 1

[1174] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1175] Conventional tourist information systems can collect tourist spot data based on information entered by users, but they lack the functionality to generate optimal tourist routes based on the user's interests and available time, and to provide detailed explanatory information. This makes it difficult for users to efficiently enjoy sightseeing within their limited time. There is also a need for systems that can appropriately prioritize the collected tourist spot information and provide the most appropriate guide information to users.

[1176] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1177] In this invention, the server includes a means for collecting data on tourist attractions based on information entered by the user, a means for calculating the optimal route that can be visited within specified conditions based on the collected data on tourist attractions, and a means for using a generative AI model to generate detailed explanatory information for each tourist attraction. This makes it possible to generate optimal tourist routes according to the user's individual interests and conditions, and to provide comprehensive and detailed guide information.

[1178] "User" refers to an individual or organization that uses the tourist information system.

[1179] "Tourist destinations" refer to places that tourists visit, such as historical buildings, museums, and parks.

[1180] A "generative AI model" refers to an artificial intelligence model that generates information using natural language processing technology.

[1181] "Guide information" refers to comprehensive tourist information data including detailed explanations of tourist spots, optimal route guidance, and related information.

[1182] "Terminal" refers to a device such as a smartphone, tablet, or PC that a user uses to access the system.

[1183] "Data collection means" refers to a part of the system that collects data on related tourist destinations based on user input information.

[1184] "Means for calculating optimal route" refers to the system's algorithm that calculates a route for efficiently visiting tourist spots that can be visited within specified conditions.

[1185] "Explanatory information" refers to detailed explanations of the historical background, highlights, exhibit contents, etc. of tourist attractions.

[1186] "Transmission means" refers to a part of the system for transmitting the generated guide information to the user's terminal.

[1187] "Display means" refers to a part of the system for visually displaying guide information received on the user's terminal.

[1188] MODE FOR CARRYING OUT THE INVENTION

[1189] The present invention is a system that individually provides users with the information they need to enjoy sightseeing more efficiently. This system consists of three main components: a user terminal, a server, and a database. Specific embodiments of each component are described below.

[1190] Entering user information

[1191] Device:

[1192] Using a dedicated application, users input the tourist attractions they are interested in (e.g., museums, castles, historical buildings), the amount of time they have available for sightseeing (e.g., 3 hours, 1 day), and the places they want to visit (e.g., Tokyo, Kyoto). The device provides an input form and a submit button to receive this information.

[1193] Data collection

[1194] server:

[1195] The server receives user information sent from the device. Based on the received information, the server collects data on related tourist attractions using an internal database and external APIs (e.g., Google Places API, TripAdvisor API). This data includes the name, location, opening hours, and ratings of the tourist attractions.

[1196] Route and Content Generation

[1197] server:

[1198] The server analyzes the collected tourist destination data and uses an algorithm (e.g., Dijkstra's algorithm, A algorithm) to calculate the optimal tourist route that can be visited within a specified time. At the same time, it uses a generative AI model (e.g., GPT-4) to generate detailed explanatory information for each tourist destination. The explanation includes the history, highlights, and exhibits of the destination.

[1199] Examples:

[1200] If a user inputs "art museum," "Tokyo," and "3 hours," the server uses this information to collect data on major art museums in Tokyo (e.g., Tokyo National Museum, Mori Art Museum, Ueno Royal Museum), calculates the optimal route to visit them efficiently within 3 hours, and then uses GPT-4 to generate detailed descriptions of each museum.

[1201] Example prompt sentence:

[1202] "Please tell me about the historical background of the Tokyo National Museum in Tokyo and what attractions it is worth visiting."

[1203] Guide provided

[1204] Device:

[1205] The guide information (optimal route and detailed commentary information) created on the server is sent to the user's device and displayed through the application. Users can check the optimal route and detailed commentary of each tourist spot within the application.

[1206] Specific behavior:

[1207] Users can check the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" within the app, and explanatory information for each spot will be displayed in a pop-up.

[1208] This system allows users to obtain the optimal sightseeing route and detailed guide information based on their individual interests and conditions, providing an efficient and satisfying sightseeing experience within a limited time frame.

[1209] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1210] Step 1:

[1211] Entering user information

[1212] Device:

[1213] The user opens the application and inputs their interests (e.g., museums, castles, historical buildings), available time (e.g., 3 hours, 1 day), and the places they want to visit (e.g., Tokyo, Kyoto). The input information is sent to the server by pressing the send button.

[1214] Input: The user enters "museum," "Tokyo," and "3 hours" into an input form within the app.

[1215] Output: The user's input data is sent to the server.

[1216] Specific operation: When the user presses the "Submit" button, the entered information is sent to the server.

[1217] Step 2:

[1218] Data collection

[1219] server:

[1220] The server receives the user information sent from the device and collects data on related tourist attractions by sending queries to an internal database and external APIs (e.g., Google Places API, TripAdvisor API) to obtain data on related tourist attractions.

[1221] Input: User input data (interests, location, time).

[1222] Output: Tourist attraction data (name, location, opening hours, rating, etc.).

[1223] Specific operation: The server obtains museum data via the Google Places API based on the information "Tokyo," "museum," and "3 hours," and stores it in an internal database.

[1224] Step 3:

[1225] Route and Content Generation

[1226] server:

[1227] Analyze the collected tourist destination data and calculate the optimal route that can be visited within a specified time. Use algorithms (e.g., Dijkstra algorithm, A algorithm) to find an efficient route. Next, use a generative AI model (e.g., GPT-4) to generate detailed descriptions of each tourist destination.

[1228] Input: tourist destination data.

[1229] Output: Optimal route, explanatory information.

[1230] Specific operation: Based on data on Tokyo's art museums, the server calculates the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" and uses a generative AI model to create detailed explanations of each museum.

[1231] Step 4:

[1232] Guide provided

[1233] Device:

[1234] The guide information (optimal route and detailed explanation) created on the server is sent to the user's device and displayed through the application. Users can check the optimal route and detailed explanation of each tourist spot within the app.

[1235] Input: Guide information received from the server.

[1236] Output: Display of guide information on the user's terminal.

[1237] Specific operation: The guide information sent by the server is received by the user's device, and the app displays the route "Tokyo National Museum → Mori Art Museum → Ueno Royal Museum" along with detailed explanations of each spot.

[1238] (Application example 1)

[1239] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1240] Today's consumers want to efficiently enjoy shopping in brick-and-mortar stores by obtaining the most appropriate information based on their interests, budget, and time. However, existing systems are specialized in tourist attractions and lack the functionality to collect extensive data applicable to brick-and-mortar shopping, provide appropriate route guidance, and provide product information for each store. Therefore, a system that can provide an efficient and satisfying shopping experience is needed.

[1241] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1242] In this invention, the server includes means for collecting store data based on information entered by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected store data, and means for generating detailed explanation content for each store, thereby enabling an efficient and satisfying shopping experience in a physical store.

[1243] "User-entered information" refers to data entered by a user specifying their interests, budget, and available time.

[1244] "Store data" refers to data that includes detailed information such as the location of each store, the products they carry, sales information, and store reputation.

[1245] An "optimal route" is a route that efficiently visits multiple stores that can be visited within specified conditions.

[1246] "Explanatory content" is a collection of text and images containing detailed information such as the characteristics of each store, product information, promotion information, and reputation.

[1247] "Guide information" is an information package provided to users that combines the optimal route with detailed explanations of each store.

[1248] A "user device" is a portable electronic device used by a user, such as a smartphone or tablet.

[1249] The present invention is a system that individually provides information to users to help them enjoy shopping at physical stores efficiently. This system provides the optimal shopping route and detailed store information based on the user's interests, budget, and available time, and includes the following components.

[1250] Overall system configuration

[1251] This system consists of three main components: the user's terminal, the server, and the database. Each component works together to provide the user with optimal shopping guide information.

[1252] Entering user information

[1253] Device:

[1254] Users use a smartphone application to input their interests (e.g., fashion, home appliances, food), budget (e.g., within 10,000 yen, within 20,000 yen), and available time (e.g., 1 hour, 2 hours). Current location information is also automatically obtained.

[1255] Data collection

[1256] server:

[1257] The server receives user information sent from the device. Based on this information, the server collects related store data from an internal database or external API (e.g., store information, product information, sale information).

[1258] Route and Content Generation

[1259] server:

[1260] Based on the collected store data, the system calculates the optimal route that can be visited within the specified conditions. For example, if a user specifies "fashion," "under 10,000 yen," and "two hours," the system calculates a route that efficiently visits nearby fashion-related stores. It also generates detailed explanatory content for each store. The explanation includes the store's features, product information, sales information, reputation, and more.

[1261] Guide provided

[1262] Device:

[1263] The guide information created on the server is sent to the user's device and displayed through the application, allowing the user to see the optimal route and detailed explanations of each store at a glance.

[1264] Specific examples

[1265] Example 1:

[1266] If a user is interested in home appliances and plans to spend two hours shopping for less than 20,000 yen, the user simply enters "home appliances," "less than 20,000 yen," and "2 hours." The system then collects nearby home appliance-related stores from a database and generates the optimal store route (e.g., major home appliance retailer A, home appliance specialty store B, discount store C). It also provides detailed information about featured products, sales, and reputations at each store. Users can use the app to enjoy a comfortable shopping experience.

[1267] Example 2:

[1268] If a user is interested in food and wishes to spend under 5,000 yen on shopping for one hour, they simply enter "food," "under 5,000 yen," and "one hour." The system then collects information on nearby supermarkets and specialty stores and generates the optimal route (e.g., high-end supermarket A, organic food store B, discount store C). It then provides detailed information on recommended products and promotions at each store.

[1269] Example prompts to input to the generative AI model

[1270] Prompt statement:

[1271] The user is interested in "home appliances" and plans to shop for "2 hours" for "less than 20,000 yen." Based on these conditions, generate the optimal route for efficient shopping and detailed information for each store.

[1272] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1273] Step 1:

[1274] Entering user information

[1275] Device: The user opens the application and enters their interests (e.g., fashion, home appliances, food), budget (e.g., under 10,000 yen, under 20,000 yen), and available time (e.g., 1 hour, 2 hours). The application also automatically obtains their current location information. This allows the device to prepare for sending the user's interests, budget, time, and location data to the server.

[1276] Step 2:

[1277] Data reception and processing

[1278] Server: Receives user information sent from the device. The technology used is API calls using the HTTP protocol. As input, it receives the user's interests, budget, available time, and current location data, and based on this, it collects related store data from a database or external API (e.g., store information API). The server temporarily stores the acquired store data and prepares it for the next step of processing.

[1279] Step 3:

[1280] Calculating the best route

[1281] Server: Based on the collected store data, calculates the optimal route that can be visited within the conditions specified by the user. The inputs are the user's interests, budget, time, location information, and store data. The server uses this data to execute an optimal route calculation method (e.g., Dijkstra's algorithm or A algorithm). As a result, it calculates the optimal store visit order and route and passes it to the next step.

[1282] Step 4:

[1283] Generating explanatory content

[1284] Server: Generates detailed explanatory content for each store. Store data and optimal route information are used as input. The server utilizes a generative AI model to generate explanatory content for each store (e.g., product information, sale information, reputation, etc.). Specifically, it uses OpenAI's GPT model and generates explanatory text by inputting a prompt text. For example, it generates content such as, "This store has the latest home appliances, and we especially recommend the latest refrigerator."

[1285] Step 5:

[1286] Guide information integration

[1287] Server: Integrates the generated optimal route and explanatory content to create complete guide information. The optimal route information and explanatory content are used as input. The server formats this data and integrates it into a format that users can understand at a glance (e.g., a combination of maps and text). As a result, complete guide information is generated and passed to the next step.

[1288] Step 6:

[1289] Sending guide information

[1290] Server: Sends the created guide information to the user's device. A real-time communication protocol (e.g., WebSocket) is used to send data. The server uses the integrated guide information as input and prepares it for transmission to the user's device for display.

[1291] Step 7:

[1292] Display guide information

[1293] Terminal: The received guide information is displayed on the user's terminal. The guide information sent from the server is received as input and displayed through the application. The user can check the optimal route guidance and detailed explanations of each store on the application interface. A specific display method could be to draw the route on a map and present information about each store in text or images.

[1294] This processing step allows customers to have an efficient and satisfying shopping experience in a physical store.

[1295] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1296] The present invention is a system for providing tourist guide information based on the user's interests and emotions. A specific embodiment of the system will be described below.

[1297] Overall system configuration

[1298] The system consists of four main components: the user's device, the server, the database, and the emotion engine. These components work together to provide optimal tourist guide information to users.

[1299] Inputting user information and emotions

[1300] Device:

[1301] Users use the application to input categories of interest (museums, castles, historical buildings, etc.), available time (e.g., 3 hours, 1 day), and current location or place they want to visit (e.g., Tokyo, Kyoto).The emotion engine then recognizes the user's emotional state in real time.

[1302] Data collection

[1303] server:

[1304] The server receives user information sent from the device and emotion data from the emotion engine. Based on this information, the server collects data on related tourist spots from an internal database or external API. The tourist spot data covers a wide range of categories, including museums, castles, and historical buildings.

[1305] Route and Content Generation

[1306] server:

[1307] Based on the collected tourist spot data, the system calculates the optimal route for visiting within a specified time frame, taking into account factors such as transportation mode, distance, and duration of stay. It also sets priorities based on the user's emotional state and selects a route optimized for their interests and emotions.

[1308] Furthermore, detailed explanatory content is generated for each tourist spot, including the historical background, highlights, and exhibits of the spot. Information is provided to users in an easy-to-understand format using text, images, and audio data.

[1309] Guide provided

[1310] Device:

[1311] The guide information created on the server is sent to the user's device and displayed through the application, allowing users to see the optimal route and detailed explanations of each spot at a glance.

[1312] Emotion monitoring and dynamic regulation

[1313] server:

[1314] The emotion engine continuously monitors the user's emotional state in real time. If the user's emotions change during sightseeing, that information is also sent to the server. Based on these emotional changes, the server regenerates the optimal route and explanatory content in real time and sends new guide information to the user's device.

[1315] Specific examples

[1316] Example 1:

[1317] If a user is interested in historical buildings and only plans to visit Kyoto for half a day, they can enter "historical buildings," "Kyoto," and "half a day" and have the emotion engine recognize their current emotion (e.g., excited, curious). The system then collects Kyoto's major historical buildings from a database and generates a route that includes Nijo Castle, Kinkaku-ji Temple, and Kiyomizu-dera Temple. It also generates detailed commentary about the history and highlights of each spot. If the user's emotion changes during sightseeing (e.g., tired, needing a break), the route and commentary content are adjusted in real time. This information is sent to the user's device and displayed through the application.

[1318] Example 2:

[1319] If a user wants to spend a day sightseeing in New York, they can input "museum," "New York," and "one day," and the emotion engine will recognize emotions (e.g., excitement, anticipation). The system will generate a route that includes the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art. Detailed commentary will be provided on the characteristics and highlights of each museum. If the user's emotional state changes during the tour (e.g., surprise, excitement), the system will use that information to readjust the optimal route and commentary content and provide new guide information.

[1320] This system allows users to obtain the optimal sightseeing route and detailed guide information based on their interests and emotions, resulting in an efficient and satisfying sightseeing experience.

[1321] The processing flow will be explained below.

[1322] Step 1:

[1323] The user opens the application and inputs the category of interest (museums, castles, historical buildings, etc.), the time available (e.g., 3 hours, 1 day), and the current location or place they want to visit (e.g., Tokyo, Kyoto).The emotion engine then recognizes the user's emotional state in real time.

[1324] Step 2:

[1325] The device sends the user's input information and emotion data recognized by the emotion engine to the server, including interest categories, time, location, and emotional state.

[1326] Step 3:

[1327] The server receives user information and emotion data sent from the device, and then collects related tourist spot data from an internal database or external APIs based on predefined categories such as museums, castles, and historical buildings.

[1328] Step 4:

[1329] The server calculates the optimal route for visiting tourist spots within a specified time frame based on the tourist spot data collected by the server. This calculation takes into account factors such as transportation mode, distance, duration of stay, and the user's emotional state. The system also dynamically changes the priority of tourist spots based on the user's emotional state.

[1330] Step 5:

[1331] The server generates detailed explanatory content for each tourist spot, including the historical background, highlights, and exhibits of the spot. The information is provided in the form of text, images, audio data, and more.

[1332] Step 6:

[1333] The server integrates the generated route and explanatory content to create a complete guide information, and at the same time, provides personalized guide information by setting priorities according to the user's emotional state.

[1334] Step 7:

[1335] The server then sends the created guide information to the user's device, which includes route guidance and detailed explanations of each tourist spot.

[1336] Step 8:

[1337] The device receives the guide information and displays it on the application, allowing users to view the optimal route and detailed guide information for each spot through the app.

[1338] Step 9:

[1339] The emotion engine monitors the user's emotional state in real time. If the emotion changes, the information is sent to the server. For example, it can detect when the user changes from tired to excited.

[1340] Step 10:

[1341] Based on the new emotion data received by the server, the optimal route and explanatory content are regenerated in real time, and the guide information is updated based on the new priorities and emotional state.

[1342] Step 11:

[1343] The server retransmits the updated guide information to the user's device, including the modified route guidance and newly generated spot descriptions.

[1344] Step 12:

[1345] The device receives the retransmitted guide information and displays it on the application, allowing users to continue sightseeing by viewing the newly optimized route guidance and commentary in real time.

[1346] Example 2

[1347] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1348] Conventional tourist guide systems have had difficulty dynamically providing optimal routes and explanatory content based on users' interests and emotions. Furthermore, fixed information alone makes it difficult to increase user satisfaction, and they are unable to respond flexibly to situations where real-time adjustments are essential. Therefore, there is a need for systems that can dynamically provide optimal tourist routes and detailed guide information based on users' interests and emotions.

[1349] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1350] In this invention, the server includes means for collecting tourist destination data based on information entered by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected tourist destination data, and means for generating detailed commentary content for each tourist destination, which makes it possible to dynamically provide optimal tourist routes and detailed guide information according to the user's interests and emotions.

[1351] "User" refers to an individual or organization that uses the system to obtain tourist guide information.

[1352] "Tourist destinations" refer to places or facilities that are considered worth visiting, such as historical buildings, museums, and castles.

[1353] "Data" refers to general information about tourist destinations, such as their location, opening hours, prices, reviews, and attractions.

[1354] "Server" refers to a computer system that collects, analyzes, stores, and provides data.

[1355] "Terminal" refers to electronic devices such as smartphones and tablets operated by users.

[1356] "Emotional state" refers to the user's psychological state, such as excitement, interest, fatigue, expectation, and emotion.

[1357] "Emotion engine" refers to a system that detects a user's emotional state in real time through facial recognition and voice analysis.

[1358] The "optimal route" refers to a route that is calculated to ensure efficient and satisfying sightseeing based on the conditions and emotional state entered by the user.

[1359] "Explanatory content" refers to detailed information about each tourist destination, such as its historical background, highlights, and exhibits, provided in text, images, and audio.

[1360] "Guide information" refers to a comprehensive tourist guide provided to users that integrates optimal routes and explanatory content.

[1361] The present invention relates to a system for providing tourist guide information based on the interests and emotions of users. Specifically, the system is configured as follows.

[1362] The system consists of four main components: the user's terminal, the server, the database, and the emotion engine. Each component works together using the following hardware and software to provide tourist guide information.

[1363] Inputting user information and emotions

[1364] User:

[1365] Users launch the application on their smartphone or tablet and input their category of interest (e.g., museums, castles, historical buildings), the amount of time they have available (e.g., 3 hours, 1 day), and their current location or a place they want to visit (e.g., Tokyo, Kyoto). The emotion engine uses facial recognition and voice analysis to detect the user's emotional state in real time.

[1366] Data collection

[1367] server:

[1368] The system receives information and sentiment data sent from users' devices and uses external APIs such as the Google Places API and Yelp API to collect relevant tourist destination data, including details such as location, opening hours, prices, reviews, and attractions.

[1369] Route and Content Generation

[1370] server:

[1371] Based on the collected data on tourist attractions, the system calculates the optimal route for visiting within a specified time frame, taking into account factors such as transportation mode (e.g., walking, public transportation), distance, and duration of stay. It prioritizes spots based on the user's emotional state and selects a route optimized for their interests and emotions. It also generates detailed explanatory content for each tourist attraction. The explanation includes the historical background, highlights, and exhibits of the spot, and is provided using text, images, and audio data.

[1372] Guide provided

[1373] Device:

[1374] The guide information created on the server is sent to the user's device and displayed through the application. Users can check the optimal route guidance and detailed explanations of each spot to continue their sightseeing.

[1375] Emotion monitoring and dynamic regulation

[1376] server:

[1377] The emotion engine continuously monitors the user's emotional state in real time. Emotional data is sent to the server in response to changes in emotion while sightseeing. The server uses this data to regenerate the optimal route and explanatory content in real time. The new guide information is then sent back to the user's device and displayed.

[1378] Specific examples

[1379] Example 1: Half-day tour of Kyoto's historical buildings

[1380] User input:

[1381] "Historical Buildings" "Kyoto" "Half Day" "Current Emotion: Excitement"

[1382] Server Action:

[1383] The system collects Kyoto's major historical buildings (Nijo Castle, Kinkakuji Temple, and Kiyomizu-dera Temple) from a database and generates an optimal route. If the user's emotion changes to "fatigue" during sightseeing, a new route and explanation will be generated and sent to the user's device.

[1384] Example 2: One day tour of New York art museums

[1385] User input:

[1386] "Museum," "New York," "One Day," "Current Emotions: Expectations"

[1387] Server Action:

[1388] The system collects data from the Metropolitan Museum of Art, the Museum of Modern Art, and the Whitney Museum of American Art, and generates commentary about the characteristics and highlights of each museum. If the user's emotion changes to "emotion" during sightseeing, the system will adjust the route and commentary and provide it to the user's device.

[1389] Hardware and software used

[1390] 1. Devices: smartphones, tablets

[1391] 2. Servers: Database servers, web servers

[1392] 3. External APIs: Google Places API, Yelp API

[1393] 4. Emotion engine: facial recognition software, voice analysis software

[1394] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1395] Step 1: Enter user information and emotions

[1396] User:

[1397] The user starts the application and inputs the category of interest (e.g., museums, castles, historical buildings), the amount of time available (e.g., 3 hours, 1 day), and the current location or the place they want to visit (e.g., Tokyo, Kyoto). This becomes the input data.

[1398] Device:

[1399] The device receives the user's input data and uses an emotion engine to perform real-time facial recognition and voice analysis to detect the user's current emotional state (e.g., excited, curious). The detected emotional data is then added to the input data.

[1400] output:

[1401] The output of this step is a data package containing category, availability, location information, and emotion data.

[1402] ---

[1403] Step 2: Data collection

[1404] server:

[1405] The server receives the data package sent from the device. Based on this data, it collects relevant tourist destination data from an internal database and external APIs (e.g., Google Places API, Yelp API). Specifically, the server makes API requests based on category, location, and availability.

[1406] output:

[1407] The output of this step is a dataset containing detailed data about tourist destinations (e.g., location, opening hours, prices, reviews, attractions).

[1408] ---

[1409] Step 3: Generate Routes and Content

[1410] server:

[1411] The server uses the tourist destination dataset to calculate the optimal route that can be visited within a specified time frame. It uses an algorithm to calculate the shortest route, taking into account transportation mode (e.g., walking, public transportation), distance, and duration of stay. It also takes into account emotion data and sets priorities according to the user's interests and emotions. It then generates detailed explanatory content for each tourist destination, including text, images, and audio data that includes historical background, highlights, and exhibits about each location.

[1412] output:

[1413] The output of this step is guide information that integrates the optimal route with detailed explanatory content.

[1414] ---

[1415] Step 4: Provide guidance

[1416] Device:

[1417] The device receives the guide information sent from the server and displays it on the application screen. Specifically, the device displays a map of the optimal route, lists detailed information about each tourist spot, and plays audio guides.

[1418] output:

[1419] The output of this step is guide information that is visually and audibly accessible to the user.

[1420] ---

[1421] Step 5: Emotion monitoring and dynamic regulation

[1422] server:

[1423] The emotion engine continues to monitor the user's emotional state in real time while sightseeing. If the user's emotion changes (e.g., from excitement to fatigue), the device sends that data to the server. The server then regenerates the optimal route and commentary content based on this new emotional data.

[1424] Device:

[1425] The device receives the regenerated guide information and displays it again, and the user continues sightseeing using the new optimal route and commentary information.

[1426] output:

[1427] The output of this step is new guide information with a re-adjusted optimal route and detailed explanatory content.

[1428] (Application example 2)

[1429] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1430] The purpose of this invention is to improve user satisfaction by recognizing users' interests and emotions in real time in a tourist guide system and providing detailed information on tourist spots and optimal routes based on that information. In particular, conventional tourist guide systems lack a flexible approach that responds to changes in users' emotions, and have the problem that the tourist experience for users is uniform and it is difficult to respond to individual needs.

[1431] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting tourist spot data based on information input by the user, means for calculating the optimal route that can be visited within specified conditions based on the collected tourist spot data, means for acquiring emotion data using an emotion engine that recognizes the user's emotions in real time, means for setting priorities based on the user's emotional state, means for generating detailed explanation content for each tourist spot, means for integrating the generated route and explanation content to create complete guide information, means for sending the created guide information to the user's terminal, and means for regenerating the route and explanation content in real time based on changes in the user's emotions. This makes it possible to provide flexible and sophisticated tourist guide information that suits the user's interests and emotional state.

[1432] "Information entered by the user" refers to information such as tourist spot conditions, categories of interest, available times, current location, or places you wish to visit.

[1433] "Tourist attraction data" refers to tourist locations such as museums, historical buildings, and natural landscapes, as well as detailed information about them.

[1434] "Specified Conditions" refers to specific conditions specified by the User, such as categories of interest, available times, or desired locations to visit.

[1435] An "optimal route" refers to the route that most efficiently visits all the tourist spots that can be visited within the specified conditions.

[1436] An "emotion engine" refers to technology or a system that recognizes a user's emotional state in real time.

[1437] "Emotion Data" refers to information about the user's emotional state as recognized by the Emotion Engine.

[1438] "Priority" refers to the order in which the importance of tourist attractions and information is determined based on the user's interests and emotional state.

[1439] "Detailed explanatory content" refers to detailed explanations of tourist spots, including their historical background, highlights, and exhibit contents.

[1440] "Guide information" refers to information that integrates the generated optimal route with detailed explanatory content for each tourist spot.

[1441] "User's device" refers to an information display device held by the user, such as a smartphone, tablet, or smart glasses.

[1442] "Regeneration in real time" refers to instantly recreating new routes and explanatory content based on changes in users' emotions.

[1443] Overall system configuration

[1444] This invention is a system that provides tourist guide information based on the user's interests and emotions. The system consists of four main components: the user's terminal, a server, a database, and an emotion engine. These components work together to provide the user with the most appropriate tourist guide information.

[1445] Inputting user information and emotions

[1446] Device:

[1447] Users use devices such as smartphones or smart glasses to input categories of interest (fashion, historical landmarks, etc.), available time (e.g., 2 hours), and their current location or a place they want to visit. An emotion engine (e.g., Affectiva SDK) then recognizes the user's emotional state in real time.

[1448] Data collection

[1449] server:

[1450] The server receives user information sent from the device and emotion data from the emotion engine. Based on this information, the server collects data on related tourist spots from a database or external API. The tourist spot data includes stores in the shopping mall and neighboring tourist spots.

[1451] Route and Content Generation

[1452] server:

[1453] Based on the collected tourist spot data, the system calculates the optimal route that can be visited within the specified conditions. The calculation takes into account factors such as transportation method, distance, stay time, and the user's emotional state. It also sets priorities based on emotional data obtained by an emotion engine, and selects a route optimized for interests and emotions. It also generates detailed explanatory content for each tourist spot (e.g., historical background, highlights, exhibits).

[1454] Guide provided

[1455] Device:

[1456] The guide information created on the server is sent to the user's device and displayed through the application, allowing users to see the optimal route and detailed explanations of each spot at a glance.

[1457] Emotion monitoring and dynamic regulation

[1458] server:

[1459] The emotion engine continuously monitors the user's emotional state in real time. If the user's emotions change during sightseeing, that information is also sent to the server. Based on these emotional changes, the server regenerates the optimal route and explanatory content in real time and sends new guide information to the user's device.

[1460] Specific use cases

[1461] For example, if a user is interested in the "fashion" category in a shopping mall and plans to spend two hours shopping, they put on the smart glasses and input "fashion" and "two hours." The emotion engine recognizes this as "excitement." The system then collects stores in the mall that sell fashion items from a database and generates an optimal route. As detailed information about products and stores that interest them during shopping is provided, the system will suggest a new route if their emotions change.

[1462] Prompt Sentence Examples

[1463] "I want to create a guide app that provides real-time information on the best route and products for users to enjoy a two-hour shopping trip in the 'fashion' category at a shopping mall. I want to dynamically adjust the information based on the user's emotions. What approach can you think of?"

[1464] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1465] Step 1:

[1466] The server receives user information (interest categories, available time, current location) and emotional data (real-time emotional state) from the user's device. This allows the system to obtain the basic data necessary to provide tourist guide information. This input includes data such as "fashion," "2 hours," and "excitement."

[1467] Step 2:

[1468] The server collects tourist attraction data from databases and external APIs. This data includes, for example, the stores in a shopping mall, the products they sell, their opening hours, etc. Based on the tourist attraction requirements entered, the server executes database queries to collect relevant data.

[1469] Step 3:

[1470] The server calculates the optimal route based on the acquired tourist attraction data within the specified conditions. The calculation takes into account factors such as transportation mode, distance, duration of stay, and the user's emotional state. For example, if the user is "excited," the server will suggest a route that involves active movement. The output is a prioritized list of stores and tourist attractions.

[1471] Step 4:

[1472] The server prioritizes tourist spots and shops based on emotion data acquired using an emotion engine. For example, if a user feels "tired," it prioritizes relaxation spots in the route. This process is based on data analysis performed by an emotion recognition engine (e.g., Affectiva SDK).

[1473] Step 5:

[1474] The server generates detailed explanatory content for each tourist spot, including the tourist spot's historical background, highlights, exhibits, etc. The explanatory content is generated using detailed information obtained from the database and a text generation model (e.g., a generative AI model).

[1475] Step 6:

[1476] The server integrates the generated route and commentary content to create complete guide information. The server combines the route information and detailed commentary to create guide information in a format that is easy for users to view. The output result is generated as a comprehensive guide data set.

[1477] Step 7:

[1478] The server sends the created guide information to the user's device, which then uses an application to display the received guide information, providing the information in the most optimal format for the user. The guide content, updated in real time, is displayed on the display of the smart glasses or smartphone.

[1479] Step 8:

[1480] If the user's emotions change in real time, the emotion engine reacquires that information and sends it to the server. The server then regenerates the optimal route and explanatory content based on this new emotion data, updating the guide information in real time. For example, if the user's emotions change from "excited" to "tired," a relaxing spot will be added to the route.

[1481] This allows users to always receive the latest information and tourist guides that best suit their circumstances.

[1482] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1483] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1484] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1485] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1486] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1487] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1488] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1489] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1490] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1491] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1492] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1493] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1494] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1495] 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.

[1496] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1497] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1498] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1499] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1500] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1501] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1502] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1503] The following is further disclosed regarding the above embodiment.

[1504] (Claim 1)

[1505] A means for collecting tourist spot data based on information input by users;

[1506] A method for calculating the optimal route that can be visited within specified conditions based on the collected tourist spot data;

[1507] A means of generating detailed explanatory content for each tourist spot;

[1508] means for integrating the generated route and explanatory content to create complete guide information;

[1509] means for transmitting the created guide information to a user's terminal;

[1510] a means for displaying the created guide information in a user terminal;

[1511] A system including:

[1512] (Claim 2)

[1513] The system according to claim 1, wherein the guide information includes route guidance to tourist attractions and detailed information about the characteristics of each tourist attraction.

[1514] (Claim 3)

[1515] The system of claim 1, further comprising means for prioritizing presentation of the tourist attraction data based on user interests.

[1516] "Example 1"

[1517] (Claim 1)

[1518] A means for collecting tourist destination data based on information input by a user;

[1519] A means for calculating the optimal route that can be visited within specified conditions based on the collected tourist destination data;

[1520] a means for using the generative AI model to generate detailed narrative information for each tourist attraction;

[1521] A means for integrating the generated route and explanation information to create complete guide information;

[1522] means for transmitting the created guide information to a user's terminal;

[1523] a means for displaying the created guide information in a user terminal;

[1524] A system including:

[1525] (Claim 2)

[1526] The system according to claim 1, wherein the guide information includes route guidance to tourist attractions and detailed information about the characteristics of each tourist attraction.

[1527] (Claim 3)

[1528] The system of claim 1 , further comprising means for prioritizing presentation of the tourist destination data based on user interests.

[1529] "Application Example 1"

[1530] (Claim 1)

[1531] A means for collecting store data based on information input by a user;

[1532] A means for calculating the optimal route that can be visited within specified conditions based on the collected store data;

[1533] A means of generating detailed explanatory content for each store,

[1534] means for integrating the generated route and explanatory content to create complete guide information;

[1535] means for transmitting the created guide information to a user's terminal;

[1536] a means for displaying the created guide information in a user terminal;

[1537] A system including:

[1538] (Claim 2)

[1539] The system of claim 1 , wherein the guide information includes route guidance to the store and detailed information about the characteristics of each store.

[1540] (Claim 3)

[1541] The system according to claim 1, further comprising means for setting priorities based on user interests when presenting the store data.

[1542] "Example 2: Combining Emotion Engines"

[1543] (Claim 1)

[1544] A means for collecting tourist destination data based on information input by a user;

[1545] A method for calculating the optimal route that can be visited within specified conditions based on the collected tourist destination data;

[1546] A means for generating detailed explanatory content for each tourist spot;

[1547] means for integrating the generated route and explanatory content to create complete guide information;

[1548] means for transmitting the created guide information to a user's terminal;

[1549] a means for displaying the created guide information in a user terminal;

[1550] a means for monitoring the user's emotional state in real time;

[1551] means for regenerating an optimal route and explanatory content according to the emotional state of the user;

[1552] A system including:

[1553] (Claim 2)

[1554] The system according to claim 1, wherein the guide information includes route guidance to tourist attractions and detailed information about the characteristics of each tourist attraction.

[1555] (Claim 3)

[1556] The system according to claim 1 , further comprising means for setting priorities based on user interests and emotions when presenting data on tourist destinations.

[1557] "Application example 2 when combining emotion engines"

[1558] (Claim 1)

[1559] A means for collecting tourist spot data based on information input by users;

[1560] A method for calculating the optimal route that can be visited within specified conditions based on the collected tourist spot data;

[1561] A means for acquiring emotion data using an emotion engine that recognizes user emotions in real time;

[1562] a means for setting priorities based on the user's emotional state;

[1563] A means of generating detailed explanatory content for each tourist spot;

[1564] means for integrating the generated route and explanatory content to create complete guide information;

[1565] means for transmitting the created guide information to a user's terminal;

[1566] a means for displaying the created guide information in a user terminal;

[1567] means for regenerating route and commentary content in real time based on changes in user emotion;

[1568] A system including:

[1569] (Claim 2)

[1570] The system according to claim 1, wherein the guide information includes route guidance to tourist attractions and detailed information about the characteristics of each tourist attraction.

[1571] (Claim 3)

[1572] The system of claim 1, further comprising means for prioritizing presentation of the tourist attraction data based on the user's interests and emotional state. [Explanation of symbols]

[1573] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for collecting tourist spot data based on information input by users; A method for calculating the optimal route that can be visited within specified conditions based on the collected tourist spot data; A means of generating detailed explanatory content for each tourist spot; means for integrating the generated route and explanatory content to create complete guide information; means for transmitting the created guide information to a user's terminal; a means for displaying the created guide information in a user terminal; A system including:

2. The system according to claim 1 , wherein the guide information includes route guidance to tourist attractions and detailed information regarding the characteristics of each tourist attraction.

3. The system according to claim 1 , further comprising means for prioritizing presentation of the tourist attraction data based on user interests.

Images