System

Abstract

A system is provided.SOLUTION: A system comprising: means for preparing information on an actual place to be a stage of electronic content by using a generative model; means for receiving the prepared information on the place and plotting the information on a map by a terminal; and means for notifying related scene information when a user reaches within a predetermined range.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The present invention aims to solve the problem that there is a lack of specific information provided to tourists who want to visit the actual locations that are the settings for digital content, which results in difficult access, congestion, etiquette issues, etc. In particular, there is a need to create an environment that allows foreign tourists visiting Japan to visit the settings of anime and manga efficiently and with a sense of realism. [Means for solving the problem]

[0005] The present invention provides a system including means for preparing information about actual locations that are the setting for digital content using a generative model, means for receiving the prepared location information by a terminal and plotting it on a map, and means for notifying the user of related scene information when the user arrives within a predetermined range. The system also includes means for randomly simulating congestion situations and providing the simulation results to the terminal, and means for creating a travel plan for planned visits and proposing efficient sightseeing routes, thereby providing the user with a fulfilling sightseeing experience.

[0006] A "generative model" refers to an algorithm or program that automatically generates new information or content from data.

[0007] "Electronic Content" refers to visual media such as anime and manga and related data provided in digital form.

[0008] "Real-world location" refers to a specific real-world geographic location depicted within the Digital Content.

[0009] A "terminal" is a device that allows a user to receive, display, and interact with information, and includes smartphones, tablets, and the like.

[0010] "Plotting on a map" refers to visually displaying location-specific information on a geographic map.

[0011] "Within a specified range" refers to a predetermined distance or area centered on a specific location.

[0012] "Related scene information" refers to episode or scene details related to a particular location within electronic content.

[0013] "Randomly simulating crowding" refers to the virtual generation of the current number of people in a particular location using a probabilistic model or algorithm.

[0014] "Creating a trip plan" refers to planning a schedule and route for visitors to efficiently visit specific areas or locations.

[0015] "Suggesting a tourist route" means showing the user the best route or path to the destination. [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 system of the present invention guides users to the actual locations where digital content is set, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[0038] Server Roles

[0039] The server manages information about the actual locations where the digital content is set in a database. Using a generative model, it generates new locations and related scene information as needed. The server receives the user's current location information (latitude and longitude), filters information about anime settings near that location, and returns it to the user.

[0040] Receive the user's current location information.

[0041] Filter locations within 10km of the database.

[0042] Randomly generate crowd conditions and add them to each location.

[0043] The filtered anime setting information is returned to the terminal.

[0044] Device Role

[0045] The device plots the information about the anime's setting received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when they arrive within a specified range. It also creates a travel plan for the planned visit locations and suggests efficient sightseeing routes.

[0046] Get the user's current location.

[0047] Current location information is sent to the server and anime setting information is received.

[0048] The received information is displayed on a map.

[0049] When it reaches within a predetermined range, it notifies the relevant scene information.

[0050] Create a travel plan and suggest the best sightseeing route.

[0051] User operations

[0052] Users can receive information about nearby anime locations by launching the app and allowing location information acquisition. They can then select a location to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related scenes from the anime. The app also suggests efficient travel plans for the locations they plan to visit and allows them to check the congestion situation.

[0053] Specific examples

[0054] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of anime settings around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the congestion level is returned to the device as "high." The device then plots the Shinjuku park on a map and displays it visually to the user. As the user approaches the location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests efficient sightseeing routes.

[0055] In this way, the present invention is a system that provides users with real-time information about the locations where electronic content is set, enabling an efficient and smooth sightseeing experience.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] The user launches the app and allows location information to be acquired. The device retrieves the user's current location using navigator.geolocation.getCurrentPosition. This data is stored in the form of latitude and longitude.

[0059] Step 2:

[0060] The device sends the acquired latitude and longitude data to the server using an HTTP GET request, with the location information passed to the server as a query parameter.

[0061] Step 3:

[0062] The server receives the request, retrieves all the locations in the anime from its database, and then determines the user's current location based on the latitude and longitude provided.

[0063] Step 4:

[0064] The server uses geopy.distance to calculate the distance between the user's current location and each anime setting. It filters out locations within 10 km and randomly simulates congestion at each location before adding it to the list. This organizes the location information.

[0065] Step 5:

[0066] The server generates a list of filtered anime locations in JSON format and returns it to the device. The list includes the name, description, distance, and congestion status of each location.

[0067] Step 6:

[0068] The device analyzes the information about the anime's settings received from the server and plots it on a map. It also displays a list of the settings to the user. For example, it can visually display the information by placing pins on a map.

[0069] Step 7:

[0070] The device monitors the distance between the user's current location and each setting in real time. When the user reaches a predetermined distance (for example, within 1 km), scene information related to that setting is notified to the device. This allows the user to enjoy anime scene information in real time.

[0071] Step 8:

[0072] The device automatically creates a travel plan based on the planned visit locations and presents it to the user, suggesting an efficient sightseeing route and allowing the user to smoothly visit multiple locations.

[0073] Step 9:

[0074] The user travels based on recommended travel plans and sightseeing routes, and the device notifies users of congestion conditions in real time, providing reference information when choosing destinations to visit.

[0075] In this way, this system provides information about the anime's setting locations based on the user's current location information, making it possible to provide an efficient and immersive sightseeing experience.

[0076] Example 1

[0077] 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."

[0078] It is difficult to effectively guide users to the actual locations where digital content is set and provide relevant scene information and crowding status in real time. Furthermore, there is a lack of means to automatically generate and propose efficient travel plans to users. This can lead to confusion in the tourist experience and reduce its appeal.

[0079] 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.

[0080] In this invention, the server includes means for using a generative model to prepare information about the actual locations that are the setting for the digital content, means for filtering the location information for the digital content based on the user's current location information, generating a congestion status and sending it back to the terminal, and means for receiving and analyzing the user's current location information (latitude and longitude) by the server. This allows the user to obtain the location information for the digital content in real time, enabling an efficient and attractive sightseeing experience.

[0081] A "generative model" is an algorithm or program that generates new data or information based on existing data.

[0082] "Electronic Content" means information or media in digital form that can be displayed or played through an electronic device.

[0083] A "real-world location" is a real-world geographic location where a story or scene is actually set.

[0084] A "terminal" is a portable electronic device or computer device that is directly operated by a user.

[0085] "Plotting on a map" means visually displaying a specific location or information on a map app or software.

[0086] "When the user reaches within a predetermined range" means when the user enters a specific geographical range (for example, within 500 m).

[0087] "Related scene information" refers to detailed information or explanations about a particular scene or episode of electronic content.

[0088] "User's current location information" refers to latitude and longitude data that indicates the user's current geographical location.

[0089] "Crowd situation" refers to information that indicates the degree of crowding or bustle in a particular location or area.

[0090] A "travel plan" is a plan of travel routes and schedules that includes planned visits and tourist spots.

[0091] A "tourist route" is a recommended route for efficiently touring tourist spots and visiting places.

[0092] A "server" is a remote computer or system that stores, processes, and distributes data.

[0093] "Filtering" means selecting and extracting data or information based on specific criteria.

[0094] The system of the present invention guides users to the actual locations where digital content is set, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[0095] (Server role)

[0096] The server uses a generative model to prepare information about the actual locations where digital content is set. For example, OpenAI GPT-3 is used for this generative model. The server also receives the user's current location information (latitude and longitude) and filters information about locations within 10 km of the database based on that location. From the filtered information, the server randomly generates a congestion status and sends the result back to the terminal.

[0097] Specific examples of server side operations:

[0098] 1. Receive the user's current location information (latitude and longitude).

[0099] 2. Search and filter location information within 10km from a database management system (e.g., MySQL).

[0100] 3. Randomly generate congestion levels (using indicators such as "low," "medium," and "high").

[0101] 4. The filtered venue information and congestion status are returned to the terminal.

[0102] (Terminal role)

[0103] The device first uses its GPS function to obtain the user's current location information. It then sends the obtained location information to the server and receives information about the anime's setting and crowding situation returned from the server. The received information is then plotted on a map and presented visually to the user. Furthermore, when the user arrives near a specific setting, it notifies the user of related scene information. The device also creates a travel plan for the planned visit locations and suggests efficient sightseeing routes.

[0104] Specific operation examples on the terminal side:

[0105] 1. Obtain the user's current location using GPS.

[0106] 2. Send your current location to the server (example prompt: "What are the locations of anime films near me?").

[0107] 3. Receive the venue information and congestion status sent from the server.

[0108] 4. Display location information on the map using icons, etc., and visually indicate congestion levels using color coding.

[0109] 5. When the user arrives near the location, relevant scene information is notified.

[0110] 6. If the user wants to visit other destinations, we suggest efficient tourist routes and detailed travel plans.

[0111] (User operation)

[0112] Users can access information about nearby anime settings by launching the app and allowing location information acquisition. They can then select the location they want to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related scenes from the anime. They can also use the app to check efficient travel plans and congestion status for the locations they plan to visit.

[0113] Examples:

[0114] When a tourist in Tokyo launches the app, the device first obtains the current latitude and longitude of their location and sends them to the server. The server then searches a database of anime locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the congestion status is sent to the device as "high." The device can then plot the Shinjuku park on a map and display it visually to the user. When the user approaches the park, the device notifies them of related scene information. If the user is interested in places other than Shinjuku, the app suggests efficient sightseeing routes.

[0115] Thus, the present invention is a system that provides users with real-time information about the locations where electronic content is set, thereby enabling an efficient and attractive tourist experience.

[0116] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0117] Step 1:

[0118] The user launches the app and allows location information to be acquired. Specifically, the user operates the app's location information acquisition permission dialog. The input is the user's permission to acquire location information, and the output is the device obtaining permission to acquire location information.

[0119] Step 2:

[0120] The device uses its GPS function to obtain the user's current location. The input is data from the GPS sensor, and the output is the latitude and longitude of the current location. Specifically, the device receives signals from GPS satellites and calculates the latitude and longitude.

[0121] Step 3:

[0122] The device sends the user's current location information to the server. Example prompt: "Tell me where nearby anime is set." The input is the latitude and longitude of the current location, and the output is the location data sent to the server. Specifically, the device generates an HTTP request and sends it to the server.

[0123] Step 4:

[0124] The server filters the location information of digital content based on the user's current location. The input is the current location information submitted, and the output is a list of locations within 10 km. Specifically, the server executes a database query and extracts nearby locations using a distance calculation algorithm.

[0125] Step 5:

[0126] The server generates congestion status for the filtered locations. The input is the filtered location information, and the output is the location information with congestion status added. Specifically, it uses a random number generation algorithm to assign a congestion status of "low," "medium," or "high" to each location.

[0127] Step 6:

[0128] The server sends the filtered information and congestion status to the terminal. The input is the venue information with congestion status added, and the output is the data sent to the terminal. The specific operation is to send the data via an HTTP response.

[0129] Step 7:

[0130] The device plots the received location information and congestion status on a map. The input is data received from the server, and the output is the location icon and congestion status displayed on the map app. Specifically, it calls the map API and visually displays the information using icons and colors.

[0131] Step 8:

[0132] When a user arrives near a specific location, the device notifies them of related scene information. The input is the device's location information and the set notification range, and the output is the notified scene information. Specifically, the device calculates the distance between the user's location and the setting, and activates the notification function if the user is within the specified range.

[0133] Step 9:

[0134] The user selects the places they plan to visit, and the device generates an efficient travel plan and sightseeing route. The input is a list of places selected by the user, and the output is an optimized sightseeing route. Specifically, the device applies a route optimization algorithm to generate and display the travel plan.

[0135] (Application example 1)

[0136] 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."

[0137] Conventional tourist information systems for digital content and anime locations lacked the ability to provide real-time information based on the user's current location. They also lacked the ability to grasp congestion levels or suggest efficient sightseeing routes, making it difficult for users to enjoy comfortable and efficient sightseeing. This led to a decline in user satisfaction and hindered the development of the tourism industry.

[0138] 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.

[0139] In this invention, the server includes means for using a generative model to prepare information about the actual location that will be the setting for the digital content, means for filtering information about nearby tourist spots based on the user's current location information, and means for randomly simulating and providing congestion conditions, allowing the user to receive information about nearby tourist spots in real time, understand congestion conditions, and receive suggestions for efficient tourist routes.

[0140] A "generative model" is a general term for algorithms and methods that learn specific patterns and features from data and generate new ones.

[0141] "Electronic content" refers to information and media provided in digital form, especially location information such as anime and manga.

[0142] "Tourist destination information" refers to information about specific places that tourists want to visit, including their location, characteristics, history, and crowding status.

[0143] "Nearby" refers to a location within a certain distance from the user's current location.

[0144] "Crowding situation" is information that shows the density and concentration of people and vehicles in a specific location in real time.

[0145] "Filtering" refers to the process or method of selecting data based on specific conditions.

[0146] "Tourist route" refers to a route or sequence set up to efficiently visit multiple tourist spots.

[0147] "User's current location" refers to information about the latitude and longitude of the user's current physical location.

[0148] "Scene information" refers to explanatory and image information related to a specific scene in electronic content such as an anime or manga.

[0149] The present invention is a system that guides users to actual locations that are the setting for digital content based on their current location information, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[0150] Server Roles

[0151] The server performs the following main roles:

[0152] 1. Location Management:

[0153] Using the generative model, we create a database of real-world locations where digital content is set, including location information (latitude and longitude) and related scene information.

[0154] 2. Filtering:

[0155] Receives the user's current location information and filters tourist spot information within a certain distance (e.g., 10 km) from that location.

[0156] 3. Congestion generation:

[0157] The system randomly simulates the congestion situation for each tourist spot and provides it to the user.

[0158] Device Role

[0159] The terminal performs the following main roles:

[0160] 1. Obtaining current location information:

[0161] Use the smartphone's GPS function to obtain the user's current location.

[0162] 2. Receiving and Displaying Information:

[0163] The system receives the organized location information and filtered tourist spot information from the server and plots and displays it on a map.

[0164] 3. Scene information notification:

[0165] When the user reaches a predetermined range, relevant scene information is notified.

[0166] 4. Create your travel plan:

[0167] Create a travel plan for the places you plan to visit and suggest efficient sightseeing routes.

[0168] Hardware and software used

[0169] Hardware:

[0170] Smartphone: A typical smartphone with GPS functionality and internet connectivity.

[0171] software:

[0172] Server-side software:

[0173] Database management systems (e.g. MySQL, PostgreSQL)

[0174] Generative models (e.g., TensorFlow, OpenAI GPT)

[0175] Terminal software:

[0176] GPS data acquisition function

[0177] Map display applications (e.g., Google Maps API)

[0178] Notifications (e.g. FCM, APNs)

[0179] Example of operation

[0180] For example, if a user is in Tokyo, when the application is launched, the latitude and longitude of the user's current location are first obtained and sent to the server. The server then searches a database of anime settings around Tokyo and filters locations within 10 km. For example, if a park in Shinjuku is nearby and the location is crowded, the congestion level is returned to the device as "high." The device plots the park on a map and displays it visually to the user. As the user approaches the location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests efficient sightseeing routes.

[0181] Prompt Sentence Examples

[0182] "Please explain about an app that guides users to nearby anime pilgrimage sites based on their current location."

[0183] "Write a prototype for an app called Anime Sacred Site Navigation. The app's function is to get the user's current location, plot nearby anime sacred sites, and display their congestion status."

[0184] As described above, the present invention is a system that provides users with real-time information about the locations where electronic content is set, enabling an efficient and smooth sightseeing experience.

[0185] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0186] Step 1:

[0187] Obtaining the user's current location

[0188] Description: When a user launches the application, the device (smartphone) uses the GPS function to obtain the user's current location information.

[0189] Input: The user's current latitude and longitude.

[0190] Output: Latitude and longitude of current location.

[0191] Specific operation: Uses the smartphone's GPS sensor to obtain location information and generate latitude and longitude data.

[0192] Step 2:

[0193] Sending location information to the server

[0194] Description: Sends the latitude and longitude information of the current location acquired by the device to the server.

[0195] Input: Latitude and longitude information of your current location.

[0196] Output: Send location information to server.

[0197] Specific operation: The device sends the acquired location information to the server as an API request using the HTTP protocol.

[0198] Step 3:

[0199] Location filtering

[0200] Description: The server filters tourist destination information within 10km from the database based on the received current location information.

[0201] Input: Latitude and longitude information of your current location.

[0202] Output: Nearby tourist attractions information.

[0203] Specific operation: The server executes a database query to extract tourist information within a certain range of the user's current location.

[0204] Step 4:

[0205] Generating congestion status

[0206] Description: The server randomly simulates the crowding of each tourist spot and adds it to each location.

[0207] Input: Nearby tourist attractions information.

[0208] Output: Tourist attraction information with crowd status added.

[0209] Specific operation: The server uses a random number generation algorithm to quantify the congestion level of each tourist spot and add it to the tourist spot information.

[0210] Step 5:

[0211] Sending tourist information to devices

[0212] Description: The server sends tourist spot information including congestion status to the terminal.

[0213] Input: Tourist attraction information with added crowd status.

[0214] Output: Send tourist information to the device.

[0215] Specific operation: The server converts the processed tourist attraction information into JSON format and returns it to the terminal as an HTTP response.

[0216] Step 6:

[0217] Plotting tourist destination information

[0218] Description: The tourist destination information received by the device is plotted on a map and presented visually to the user.

[0219] Input: Tourist attraction information with added crowd status.

[0220] Output: Tourist attractions plotted on a map.

[0221] Specific operation: The device uses Google Maps API or similar to display tourist spot information as markers on a map.

[0222] Step 7:

[0223] Scene information notification

[0224] Description: When the user approaches a specific tourist spot, the device notifies them of related scene information.

[0225] Input: User location and tourist destination information.

[0226] Output: Notification of relevant scene information.

[0227] Specific operation: The device compares the user's current location with the location of the tourist attraction and sends a push notification when the user enters within a specified range.

[0228] Step 8:

[0229] Travel plan creation and proposal

[0230] Description: The device creates and suggests efficient travel plans to the user based on the places the user plans to visit.

[0231] Input: The user's planned visit location.

[0232] Output: Efficient sightseeing route suggestions.

[0233] Specific operation: The device calculates a route using an algorithm that takes into account multiple planned destinations and optimizes distance and time, and presents a visual suggestion to the user.

[0234] The above are the specific processing steps of the present invention.

[0235] 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.

[0236] This system guides users to the actual locations where digital content is set, provides relevant scene information and congestion status based on the user's current location information, creates travel plans and suggests efficient sightseeing routes, and recognizes the user's emotions and optimizes the information provided and route suggestions based on those emotions.

[0237] Server Roles

[0238] The server uses the generative model to organize information about the actual locations where the digital content is set in the database. It receives the user's current location information (latitude and longitude), filters information about anime settings near that location, and receives the user's emotional information through an emotion engine to provide the user with optimized information.

[0239] Receive the user's current location information.

[0240] Filter locations within 10km of the database.

[0241] Randomly generate crowd conditions and add them to each location.

[0242] The emotional information of the user is received, and the location information to be presented is optimized based on the information.

[0243] The filtered anime setting information is returned to the terminal.

[0244] Device Role

[0245] The device receives information about the anime's setting from the server, plots it on a map, and presents it visually to the user. It also notifies the user of related scene information when they arrive within a specified range. It also has the function of creating a travel plan for planned visits and proposing efficient sightseeing routes. It recognizes the user's emotions and dynamically changes the information display and route suggestions based on that.

[0246] Get the user's current location.

[0247] Current location information is sent to the server and anime setting information is received.

[0248] The received information is displayed on a map.

[0249] When it reaches within a predetermined range, it notifies the relevant scene information.

[0250] Create a travel plan and suggest the best sightseeing route.

[0251] An emotion engine is used to recognize the user's emotions and dynamically change the display content and route based on those emotions.

[0252] User operations

[0253] Users can receive information about nearby anime locations by launching the app and allowing location information acquisition. They can then select locations to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related anime scenes. The app can also suggest efficient travel plans for the locations they plan to visit, and provide feedback based on crowding and sentiment.

[0254] Specific examples

[0255] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of anime locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the server will return "Crowded: High" to the device. Furthermore, if the user's emotion is recognized as "tired," the server will suggest more relaxing places and shorter routes to the user.

[0256] The device plots Shinjuku parks on a map and visually displays them to the user. When the user approaches a location, the app notifies them of related scene information. If the user wants to visit places outside of Shinjuku, the app can suggest efficient sightseeing routes and include appropriate rest stops along the way based on their emotions.

[0257] In this way, the present invention is a system that provides users with the most optimal sightseeing experience by providing them with information about anime settings based on their current location information and further combining this with emotion recognition.

[0258] The processing flow will be explained below.

[0259] Step 1:

[0260] When the user launches the app and grants permission to acquire location information and recognize emotions, the device acquires the user's current location using navigator.geolocation.getCurrentPosition and recognizes the user's emotions using sensors such as the camera and microphone.

[0261] Step 2:

[0262] The device sends the acquired latitude and longitude data and emotion data to the server using an HTTP GET request, with the location information and emotion information passed to the server as query parameters.

[0263] Step 3:

[0264] The server receives the request, retrieves all the locations in the anime from its database, and then determines the user's current location based on the latitude and longitude provided.

[0265] Step 4:

[0266] The server uses geopy.distance to calculate the distance between the user's current location and each anime setting. It filters out locations within 10 km and randomly simulates congestion at each location before adding it to the list. This organizes the location information.

[0267] Step 5:

[0268] The server analyzes the user's emotional information and optimizes the content and order of the location information based on that emotional state. For example, if the server detects that the user is "tired," it will prioritize suggesting less crowded or relaxing locations.

[0269] Step 6:

[0270] The server generates a filtered and optimized list of anime locations in JSON format and returns it to the device, including special suggestions based on each location's name, description, distance, crowding status, and emotion.

[0271] Step 7:

[0272] The device analyzes the information about the anime's settings received from the server and plots it on a map. It also displays a list of the settings to the user. For example, it can visually display the information by placing pins on a map.

[0273] Step 8:

[0274] The device monitors the distance between the user's current location and each setting in real time. When the user reaches a predetermined distance (for example, within 1 km), scene information related to that setting is notified to the device. This allows the user to enjoy anime scene information in real time.

[0275] Step 9:

[0276] The device automatically creates a travel plan based on the planned destinations and presents it to the user. This suggests an efficient sightseeing route, allowing the user to smoothly visit multiple locations. Furthermore, the travel plan is dynamically changed based on the user's emotional information. For example, if the user is "having fun," a new location may be added to the sightseeing route.

[0277] Step 10:

[0278] The user travels based on recommended travel plans and sightseeing routes. The device notifies the user of congestion status and emotion information in real time, providing reference information for the user when choosing destinations. The device also recommends appropriate rest areas along the way based on the user's emotions.

[0279] In this way, this system provides information about anime settings based on the user's current location and emotional information, providing an efficient and immersive sightseeing experience. Furthermore, by optimizing information and routes according to the user's emotions, it is possible to provide a more fulfilling experience.

[0280] Example 2

[0281] 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."

[0282] Conventional tourist information systems lack guidance based on the user's current location information and provide limited information on the locations where digital content is set. Furthermore, they do not provide information or suggest routes that take into account congestion or the user's emotions, making it difficult to provide an optimal tourist experience for each individual user. Therefore, there is a need for information to avoid congestion at the site and for the creation of travel plans that suit the user's emotions.

[0283] 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.

[0284] In this invention, the server includes means for preparing information on actual locations that serve as the setting for the digital content using a generative AI model, means for receiving the prepared location information and plotting it on a map using a terminal, means for notifying the user of related scene information when the user arrives within a predetermined range, means for acquiring the user's current location information and sending it to the server, means for the server to filter locations within the predetermined range from a database, means for the server to receive the user's emotional information using an emotion engine and generate optimized information, and means for the terminal to recognize the user's emotions and dynamically change the information display and route suggestions based on the emotions. This makes it possible to provide optimal tourist routes and information according to the user's current location and emotional state, as well as information on the setting for the digital content.

[0285] A "generative AI model" is a model that uses artificial intelligence techniques to generate optimal results for a specific task.

[0286] "Electronic content" refers to information and data that is stored, transmitted, and played in digital form, including, for example, animation and games.

[0287] "Real-life locations" refers to real-life locations that are depicted as the backdrop for scenes or stories in the digital content.

[0288] A "terminal" is a device used by a user for operation, and includes a smartphone, tablet, etc.

[0289] A "server" is a computer system that receives and processes requests from users.

[0290] "Processing" refers to the process of organizing and structuring data to make it usable.

[0291] "Means for receiving and plotting on a map" refers to the process of receiving the transmitted information at the terminal and displaying the information in a map application.

[0292] The "means for notifying scene information" refers to a mechanism for notifying the user of content information related to a specific location when the user reaches that location.

[0293] "Current location information" refers to latitude and longitude data that indicates the user's location.

[0294] "Means for filtering locations within a predetermined range from a database" refers to a process that searches for information in a database based on the user's current location and extracts only results within a pre-defined range.

[0295] An "emotion engine" is a system that identifies a user's emotional state and provides appropriate answers or responses based on that.

[0296] "Means for dynamically changing information display and route suggestions" refers to a mechanism that instantly changes the information presented and the recommended route according to the user's real-time information and emotions.

[0297] This system guides users to actual locations that are the setting for digital content based on their current location information, and provides related scene information and congestion status. It also creates travel plans and suggests efficient sightseeing routes, and can recognize users' emotions and optimize the information provided and route suggestions based on those emotions.

[0298] Server Roles

[0299] The server uses a generative AI model to organize information about the actual locations in the database where digital content is set. It also receives the user's current location information (latitude and longitude) and filters information about locations near that location. The server also receives the user's emotional information using an emotion engine and provides optimized information to the user. The specific process is as follows:

[0300] Receive the user's current location information.

[0301] Filter locations within 10km of the database.

[0302] Randomly generate crowd conditions and add them to each location.

[0303] The emotional information of the user is received, and the location information to be presented is optimized based on the information.

[0304] The filtered location information is returned to the terminal.

[0305] Device Role

[0306] The device plots the location information received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when the user arrives within a specified range. It also has the function of creating a travel plan for planned visits and proposing efficient sightseeing routes. The device uses an emotion engine to recognize the user's emotions and dynamically changes the information display and route suggestions based on those emotions. The specific process is as follows:

[0307] Get the user's current location.

[0308] Current location information is sent to the server, and location information is received.

[0309] The received information is displayed on a map.

[0310] When it reaches within a predetermined range, it notifies the relevant scene information.

[0311] Create a travel plan and suggest the best sightseeing route.

[0312] An emotion engine is used to recognize the user's emotions and dynamically change the display content and route based on those emotions.

[0313] User operations

[0314] Users can launch the app and allow location information acquisition to receive information about nearby locations. They can select locations to visit from the displayed list or map, and when they arrive at the location, they receive related scene information in real time. The app can also suggest efficient travel plans for the locations they plan to visit and provide feedback based on crowd levels and emotions.

[0315] Specific examples

[0316] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the app will return "Crowded: high" to the device.

[0317] Furthermore, if the user's emotion is recognized as "tired," the server suggests more relaxing places and shorter routes to the user. The device plots Shinjuku parks on a map and visually displays them to the user. When the user approaches a location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests an efficient sightseeing route, including appropriate rest stops along the way based on the user's emotion.

[0318] Prompt Sentence Examples

[0319] An example of an input prompt when a user wants to get a specific sightseeing plan is, "Please tell me some recommended locations around Tokyo. I'm currently in Shinjuku. Also, I'm a little tired, so please suggest some places where I can relax." This makes it possible to provide a sightseeing experience optimized for the user's situation and emotions.

[0320] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0321] Step 1:

[0322] The user launches the app

[0323] A user taps an app on their smartphone to launch it. When the app is launched for the first time, it asks for permission to obtain location information. The inputs are user interaction and permission to obtain location information, and the outputs are confirmation that the app has been launched and the setting for permission to obtain location information.

[0324] Step 2:

[0325] The device obtains location information

[0326] The device uses the smartphone's GPS sensor to obtain the user's current location information (latitude and longitude). For example, if the user is near Shinjuku Station, the latitude will be 35.6895 degrees and the longitude will be 139.6917 degrees. The input required is data from the GPS sensor, and the output is the latitude and longitude data of the current location.

[0327] Step 3:

[0328] The device sends its current location information to the server.

[0329] The device sends the acquired latitude and longitude data to the server in real time. The data is sent in a standard format such as JSON. The input requires the latitude and longitude data of the current location, and the output is the current location data sent to the server.

[0330] Step 4:

[0331] The server filters locations within 10km of the database

[0332] The server executes a database query to filter location information within 10km of the user's current location. It uses SQL SELECT statements to extract records that match the criteria. The input requires the received latitude and longitude data and the database, and the output is the filtered location information within 10km.

[0333] Step 5:

[0334] The server receives the user's emotional information using an emotion engine and generates optimized information.

[0335] The server receives the user's emotional information through the emotion recognition API and generates optimized location information based on that information. For example, if the user is recognized as "tired," the information is saved as internal data and reflected in the filtering results. The input requires the user's emotional information and filtered location information, and the output is optimized location information.

[0336] Step 6:

[0337] The server sends optimized location information to the device.

[0338] The server returns the optimized location information to the device. The information is in JSON format and includes latitude, longitude, congestion status, recommended comments, etc. The input requires the optimized location information, and the output is the optimized information sent to the device.

[0339] Step 7:

[0340] The device plots the information on a map

[0341] The device plots the received location information on a map application. The user can visually check the location and information of each location on the map. The received location information is required as input, and the output is the information plotted on the map.

[0342] Step 8:

[0343] The device detects the user's arrival and notifies them of the scene information.

[0344] The device notifies the user of related scene information when the user arrives within a specified range of the setting. For example, when the user arrives at Shinjuku Park, a description and image of a specific scene from the anime are displayed. GPS data and scene information are required as input, and the output is a scene information notification to the user.

[0345] Step 9:

[0346] The device creates a travel plan for the places you plan to visit.

[0347] The device generates an efficient travel plan based on the user's selected locations. For example, it proposes a route that goes around Takadanobaba, Shinjuku, and Ikebukuro. The input requires the user's selected locations, and the output is a travel plan.

[0348] Step 10:

[0349] The device suggests the best sightseeing route for the user

[0350] The device then proposes an optimal sightseeing route to the user based on the generated travel plan. The route is presented with a map, and the points to be visited are marked. The travel plan data is required as input, and the output is the proposed sightseeing route to the user.

[0351] Step 11:

[0352] The device dynamically updates the information

[0353] The device dynamically updates the display and route based on the user's real-time location and emotions, suggesting additional rest stops and new routes. The input requires current location information and emotion information, and the output is the updated display and route.

[0354] (Application example 2)

[0355] 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."

[0356] Conventional information provision systems related to digital content have difficulty providing optimal information that takes into account the user's current location and emotions. Furthermore, functions for providing detailed information about store congestion and in-store product information are limited, leaving a lack of means to maximize the user experience. Furthermore, it has been difficult to provide efficient guidance and information in physical stores. For these reasons, a system that can provide flexible information according to the user's situation and optimal in-store navigation is needed.

[0357] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0358] In this invention, the server includes means for using a generative model to prepare information about the actual location where the digital content is set, means for providing guidance to nearby stores based on the user's current location information, and means for providing information about the congestion status and products in the stores. This makes it possible to provide optimal store guidance, congestion information, and product information based on the user's current location information and emotions.

[0359] A "generative model" refers to an algorithm or machine learning model that generates new information based on given data. Examples include natural language generation and image generation.

[0360] "Electronic content" is a general term for information and media content provided in digital form, including, for example, e-books, videos, music, and web pages.

[0361] A "real-world location" refers to a specific geographic location in the real world where electronic content is set and that a user can visit.

[0362] "Current location information" refers to data that indicates the user's location, and typically refers to latitude and longitude information obtained using location measurement technology such as GPS.

[0363] "Plot on a map" means visually displaying the user's location or a particular location on a geographic map.

[0364] "Scene information" refers to information relating to a particular scene or situation in electronic content, and includes, for example, a particular scene in an anime or a particular episode in a story.

[0365] "Crowding status" is information indicating the degree of crowding of people in a particular location, and is usually expressed as levels such as "high," "medium," and "low."

[0366] "Product information" refers to detailed information about products sold in physical stores, including price, features, and stock status.

[0367] "Emotion recognition" refers to technology that grasps a user's emotional state from their facial expressions, voice, etc., and categorizes emotions such as "joy," "surprise," "sadness," and "fatigue."

[0368] "Navigation" means providing directions or guidance information to help a user reach a particular destination.

[0369] "Event information" refers to information about events and campaigns held at physical stores or specific facilities, including sales, tasting sessions, autograph sessions, etc.

[0370] This system guides users to nearby stores based on their current location and provides information on store congestion and product information. It also recognizes the user's emotions and optimizes route guidance and suggests recommended products based on those emotions. It also has the ability to create a travel plan for planned visits, suggest efficient sightseeing routes, and notify users of events being held in stores.

[0371] Server Roles

[0372] The server uses the generative model to organize information about the actual locations in the database where the digital content is set. To do this, it performs the following processes: First, it receives the user's current location information (latitude and longitude) and filters out store information near that location. It also randomly generates congestion information and adds it to each location. It then receives the user's emotional information using an emotion engine and optimizes store guides and product suggestions based on that information. Finally, it returns the filtered store information to the terminal. This allows the user to receive optimized store information in real time.

[0373] Device Role

[0374] The device plots the store information received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when the user arrives within a specified range. It also has the function of creating a travel plan for planned visits and suggesting efficient sightseeing routes. The device recognizes the user's emotions and dynamically changes the information display and route suggestions based on that. For example, if it recognizes that the user is tired, it will prioritize displaying routes to stores that are less crowded.

[0375] User operations

[0376] Users can receive information about nearby stores by launching the smartphone app and allowing location information acquisition. They can select the store they want to visit from the displayed list or map, and when they actually arrive at the location, they can receive real-time information about the store's products and events. The app can also suggest efficient travel plans for the places they plan to visit and provide feedback based on crowding levels and emotions.

[0377] Specific examples

[0378] For example, suppose the user is in Shinjuku, Tokyo. If the server recognizes that the user is tired, it will prioritize providing information on less crowded stores. Specifically, if the user's current location is "latitude 35.6895, longitude 139.6917" and the user's emotion is recognized as "tired," the server will filter store information around Shinjuku and return information on "ABC Store (low crowding)" to the terminal.

[0379] Example prompts to be input to the generative AI model

[0380] plaintext

[0381] Current location: 35.6895, 139.6917

[0382] Emotion: Tired

[0383] In this way, the system combines emotion recognition and location information to provide optimal information to maximize the user experience.

[0384] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0385] Step 1:

[0386] The user launches the smartphone app and allows location information to be obtained.

[0387] Input: Permission to obtain location information from the user, GPS data from the smartphone

[0388] Output: User's current location (latitude and longitude)

[0389] How it works: Uses the smartphone's GPS module to obtain current location information and its latitude and longitude.

[0390] Step 2:

[0391] The terminal transmits the acquired current location information to the server.

[0392] Input: User's current location information (latitude and longitude)

[0393] Output: Location information sent to the server

[0394] What it does: Sends your current location to the server as an HTTP request.

[0395] Step 3:

[0396] The server filters store information within 10 km of the database based on the received current location information.

[0397] Input: Current location information (latitude and longitude), store database

[0398] Output: A filtered list of stores

[0399] What it does: Uses a database query to find stores within 10km of the current location and lists their information.

[0400] Step 4:

[0401] The server randomly generates congestion status for the filtered store information and adds it to each store information.

[0402] Input: A filtered list of store locations

[0403] Output: List of store information with added crowd status

[0404] How it works: A random algorithm is used to generate three levels of congestion status: high, medium, and low, and this is added to the store information.

[0405] Step 5:

[0406] The server receives the user's emotional information using an emotion engine and optimizes store guides and product suggestions based on that information.

[0407] Input: A list of store information with user emotion information and crowding status added

[0408] Output: A list of store information optimized based on user sentiment

[0409] How it works: The emotion engine analyzes the user's emotional data and generates optimal store guide information based on that data, taking into account the level of congestion and the products offered.

[0410] Step 6:

[0411] The server returns the optimized store information to the terminal.

[0412] Input: List of optimized store locations

[0413] Output: Optimized store information sent back to the device

[0414] Operation: Sends optimized store information to the terminal as an HTTP response.

[0415] Step 7:

[0416] The terminal plots the received store information on a map and presents it visually to the user.

[0417] Input: Optimized store information

[0418] Output: Store information displayed on the map

[0419] How it works: Using the map API, the received store information is plotted on the corresponding geographic coordinates and displayed visually.

[0420] Step 8:

[0421] When the user arrives at the store, the terminal notifies the user of related scene information and detailed information.

[0422] Input: User's current location information, optimized store information

[0423] Output: Notified related scene information and detailed information

[0424] How it works: Using geofencing technology, the app provides scene information and detailed information via pop-up notifications when a user approaches a specific store.

[0425] Step 9:

[0426] The device creates a travel plan for the places you plan to visit and suggests efficient sightseeing routes.

[0427] Input: User's planned visit information, optimized store information, event information

[0428] Output: Suggested itinerary and sightseeing route information

[0429] How it works: It uses a travel plan generation algorithm to create a list of places to visit and calculate and present the optimal route.

[0430] Example prompts to be input to the generative AI model

[0431] plaintext

[0432] Current location: 35.6895, 139.6917

[0433] Emotion: Tired

[0434] 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.

[0435] 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.

[0436] 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.

[0437] [Second embodiment]

[0438] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0439] 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.

[0440] 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).

[0441] 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.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] 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."

[0450] The system of the present invention guides users to the actual locations where digital content is set, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[0451] Server Roles

[0452] The server manages information about the actual locations where the digital content is set in a database. Using a generative model, it generates new locations and related scene information as needed. The server receives the user's current location information (latitude and longitude), filters information about anime settings near that location, and returns it to the user.

[0453] Receive the user's current location information.

[0454] Filter locations within 10km of the database.

[0455] Randomly generate crowd conditions and add them to each location.

[0456] The filtered anime setting information is returned to the terminal.

[0457] Device Role

[0458] The device plots the information about the anime's setting received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when they arrive within a specified range. It also creates a travel plan for the planned visit locations and suggests efficient sightseeing routes.

[0459] Get the user's current location.

[0460] Current location information is sent to the server and anime setting information is received.

[0461] The received information is displayed on a map.

[0462] When it reaches within a predetermined range, it notifies the relevant scene information.

[0463] Create a travel plan and suggest the best sightseeing route.

[0464] User operations

[0465] Users can receive information about nearby anime locations by launching the app and allowing location information acquisition. They can then select a location to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related scenes from the anime. The app also suggests efficient travel plans for the locations they plan to visit and allows them to check the congestion situation.

[0466] Specific examples

[0467] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of anime settings around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the congestion level is returned to the device as "high." The device then plots the Shinjuku park on a map and displays it visually to the user. As the user approaches the location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests efficient sightseeing routes.

[0468] In this way, the present invention is a system that provides users with real-time information about the locations where electronic content is set, enabling an efficient and smooth sightseeing experience.

[0469] The processing flow will be explained below.

[0470] Step 1:

[0471] The user launches the app and allows location information to be acquired. The device retrieves the user's current location using navigator.geolocation.getCurrentPosition. This data is stored in the form of latitude and longitude.

[0472] Step 2:

[0473] The device sends the acquired latitude and longitude data to the server using an HTTP GET request, with the location information passed to the server as a query parameter.

[0474] Step 3:

[0475] The server receives the request, retrieves all the locations in the anime from its database, and then determines the user's current location based on the latitude and longitude provided.

[0476] Step 4:

[0477] The server uses geopy.distance to calculate the distance between the user's current location and each anime setting. It filters out locations within 10 km and randomly simulates congestion at each location before adding it to the list. This organizes the location information.

[0478] Step 5:

[0479] The server generates a list of filtered anime locations in JSON format and returns it to the device. The list includes the name, description, distance, and congestion status of each location.

[0480] Step 6:

[0481] The device analyzes the information about the anime's settings received from the server and plots it on a map. It also displays a list of the settings to the user. For example, it can visually display the information by placing pins on a map.

[0482] Step 7:

[0483] The device monitors the distance between the user's current location and each setting in real time. When the user reaches a predetermined distance (for example, within 1 km), scene information related to that setting is notified to the device. This allows the user to enjoy anime scene information in real time.

[0484] Step 8:

[0485] The device automatically creates a travel plan based on the planned visit locations and presents it to the user, suggesting an efficient sightseeing route and allowing the user to smoothly visit multiple locations.

[0486] Step 9:

[0487] The user travels based on recommended travel plans and sightseeing routes, and the device notifies users of congestion conditions in real time, providing reference information when choosing destinations to visit.

[0488] In this way, this system provides information about the anime's setting locations based on the user's current location information, making it possible to provide an efficient and immersive sightseeing experience.

[0489] Example 1

[0490] 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."

[0491] It is difficult to effectively guide users to the actual locations where digital content is set and provide relevant scene information and crowding status in real time. Furthermore, there is a lack of means to automatically generate and propose efficient travel plans to users. This can lead to confusion in the tourist experience and reduce its appeal.

[0492] 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.

[0493] In this invention, the server includes means for using a generative model to prepare information about the actual locations that are the setting for the digital content, means for filtering the location information for the digital content based on the user's current location information, generating a congestion status and sending it back to the terminal, and means for receiving and analyzing the user's current location information (latitude and longitude) by the server. This allows the user to obtain the location information for the digital content in real time, enabling an efficient and attractive sightseeing experience.

[0494] A "generative model" is an algorithm or program that generates new data or information based on existing data.

[0495] "Electronic Content" means information or media in digital form that can be displayed or played through an electronic device.

[0496] A "real-world location" is a real-world geographic location where a story or scene is actually set.

[0497] A "terminal" is a portable electronic device or computer device that is directly operated by a user.

[0498] "Plotting on a map" means visually displaying a specific location or information on a map app or software.

[0499] "When the user reaches within a predetermined range" means when the user enters a specific geographical range (for example, within 500 m).

[0500] "Related scene information" refers to detailed information or explanations about a particular scene or episode of electronic content.

[0501] "User's current location information" refers to latitude and longitude data that indicates the user's current geographical location.

[0502] "Crowd situation" refers to information that indicates the degree of crowding or bustle in a particular location or area.

[0503] A "travel plan" is a plan of travel routes and schedules that includes planned visits and tourist spots.

[0504] A "tourist route" is a recommended route for efficiently touring tourist spots and visiting places.

[0505] A "server" is a remote computer or system that stores, processes, and distributes data.

[0506] "Filtering" means selecting and extracting data or information based on specific criteria.

[0507] The system of the present invention guides users to the actual locations where digital content is set, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[0508] (Server role)

[0509] The server uses a generative model to prepare information about the actual locations where digital content is set. For example, OpenAI GPT-3 is used for this generative model. The server also receives the user's current location information (latitude and longitude) and filters information about locations within 10 km of the database based on that location. From the filtered information, the server randomly generates a congestion status and sends the result back to the terminal.

[0510] Specific examples of server side operations:

[0511] 1. Receive the user's current location information (latitude and longitude).

[0512] 2. Search and filter location information within 10km from a database management system (e.g., MySQL).

[0513] 3. Randomly generate congestion levels (using indicators such as "low," "medium," and "high").

[0514] 4. The filtered venue information and congestion status are returned to the terminal.

[0515] (Terminal role)

[0516] The device first uses its GPS function to obtain the user's current location information. It then sends the obtained location information to the server and receives information about the anime's setting and crowding situation returned from the server. The received information is then plotted on a map and presented visually to the user. Furthermore, when the user arrives near a specific setting, it notifies the user of related scene information. The device also creates a travel plan for the planned visit locations and suggests efficient sightseeing routes.

[0517] Specific operation examples on the terminal side:

[0518] 1. Obtain the user's current location using GPS.

[0519] 2. Send your current location to the server (example prompt: "What are the locations of anime films near me?").

[0520] 3. Receive the venue information and congestion status sent from the server.

[0521] 4. Display location information on the map using icons, etc., and visually indicate congestion levels using color coding.

[0522] 5. When the user arrives near the location, relevant scene information is notified.

[0523] 6. If the user wants to visit other destinations, we suggest efficient tourist routes and detailed travel plans.

[0524] (User operation)

[0525] Users can access information about nearby anime settings by launching the app and allowing location information acquisition. They can then select the location they want to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related scenes from the anime. They can also use the app to check efficient travel plans and congestion status for the locations they plan to visit.

[0526] Examples:

[0527] When a tourist in Tokyo launches the app, the device first obtains the current latitude and longitude of their location and sends them to the server. The server then searches a database of anime locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the congestion status is sent to the device as "high." The device can then plot the Shinjuku park on a map and display it visually to the user. When the user approaches the park, the device notifies them of related scene information. If the user is interested in places other than Shinjuku, the app suggests efficient sightseeing routes.

[0528] Thus, the present invention is a system that provides users with real-time information about the locations where electronic content is set, thereby enabling an efficient and attractive tourist experience.

[0529] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0530] Step 1:

[0531] The user launches the app and allows location information to be acquired. Specifically, the user operates the app's location information acquisition permission dialog. The input is the user's permission to acquire location information, and the output is the device obtaining permission to acquire location information.

[0532] Step 2:

[0533] The device uses its GPS function to obtain the user's current location. The input is data from the GPS sensor, and the output is the latitude and longitude of the current location. Specifically, the device receives signals from GPS satellites and calculates the latitude and longitude.

[0534] Step 3:

[0535] The device sends the user's current location information to the server. Example prompt: "Tell me where nearby anime is set." The input is the latitude and longitude of the current location, and the output is the location data sent to the server. Specifically, the device generates an HTTP request and sends it to the server.

[0536] Step 4:

[0537] The server filters the location information of digital content based on the user's current location. The input is the current location information submitted, and the output is a list of locations within 10 km. Specifically, the server executes a database query and extracts nearby locations using a distance calculation algorithm.

[0538] Step 5:

[0539] The server generates congestion status for the filtered locations. The input is the filtered location information, and the output is the location information with congestion status added. Specifically, it uses a random number generation algorithm to assign a congestion status of "low," "medium," or "high" to each location.

[0540] Step 6:

[0541] The server sends the filtered information and congestion status to the terminal. The input is the venue information with congestion status added, and the output is the data sent to the terminal. The specific operation is to send the data via an HTTP response.

[0542] Step 7:

[0543] The device plots the received location information and congestion status on a map. The input is data received from the server, and the output is the location icon and congestion status displayed on the map app. Specifically, it calls the map API and visually displays the information using icons and colors.

[0544] Step 8:

[0545] When a user arrives near a specific location, the device notifies them of related scene information. The input is the device's location information and the set notification range, and the output is the notified scene information. Specifically, the device calculates the distance between the user's location and the setting, and activates the notification function if the user is within the specified range.

[0546] Step 9:

[0547] The user selects the places they plan to visit, and the device generates an efficient travel plan and sightseeing route. The input is a list of places selected by the user, and the output is an optimized sightseeing route. Specifically, the device applies a route optimization algorithm to generate and display the travel plan.

[0548] (Application example 1)

[0549] 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."

[0550] Conventional tourist information systems for digital content and anime locations lacked the ability to provide real-time information based on the user's current location. They also lacked the ability to grasp congestion levels or suggest efficient sightseeing routes, making it difficult for users to enjoy comfortable and efficient sightseeing. This led to a decline in user satisfaction and hindered the development of the tourism industry.

[0551] 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.

[0552] In this invention, the server includes means for using a generative model to prepare information about the actual location that will be the setting for the digital content, means for filtering information about nearby tourist spots based on the user's current location information, and means for randomly simulating and providing congestion conditions, allowing the user to receive information about nearby tourist spots in real time, understand congestion conditions, and receive suggestions for efficient tourist routes.

[0553] A "generative model" is a general term for algorithms and methods that learn specific patterns and features from data and generate new ones.

[0554] "Electronic content" refers to information and media provided in digital form, especially location information such as anime and manga.

[0555] "Tourist destination information" refers to information about specific places that tourists want to visit, including their location, characteristics, history, and crowding status.

[0556] "Nearby" refers to a location within a certain distance from the user's current location.

[0557] "Crowding situation" is information that shows the density and concentration of people and vehicles in a specific location in real time.

[0558] "Filtering" refers to the process or method of selecting data based on specific conditions.

[0559] "Tourist route" refers to a route or sequence set up to efficiently visit multiple tourist spots.

[0560] "User's current location" refers to information about the latitude and longitude of the user's current physical location.

[0561] "Scene information" refers to explanatory and image information related to a specific scene in electronic content such as an anime or manga.

[0562] The present invention is a system that guides users to actual locations that are the setting for digital content based on their current location information, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[0563] Server Roles

[0564] The server performs the following main roles:

[0565] 1. Location Management:

[0566] Using the generative model, we create a database of real-world locations where digital content is set, including location information (latitude and longitude) and related scene information.

[0567] 2. Filtering:

[0568] Receives the user's current location information and filters tourist spot information within a certain distance (e.g., 10 km) from that location.

[0569] 3. Congestion generation:

[0570] The system randomly simulates the congestion situation for each tourist spot and provides it to the user.

[0571] Device Role

[0572] The terminal performs the following main roles:

[0573] 1. Obtaining current location information:

[0574] Use the smartphone's GPS function to obtain the user's current location.

[0575] 2. Receiving and Displaying Information:

[0576] The system receives the organized location information and filtered tourist spot information from the server and plots and displays it on a map.

[0577] 3. Scene information notification:

[0578] When the user reaches a predetermined range, relevant scene information is notified.

[0579] 4. Create your travel plan:

[0580] Create a travel plan for the places you plan to visit and suggest efficient sightseeing routes.

[0581] Hardware and software used

[0582] Hardware:

[0583] Smartphone: A typical smartphone with GPS functionality and internet connectivity.

[0584] software:

[0585] Server-side software:

[0586] Database management systems (e.g. MySQL, PostgreSQL)

[0587] Generative models (e.g., TensorFlow, OpenAI GPT)

[0588] Terminal software:

[0589] GPS data acquisition function

[0590] Map display applications (e.g., Google Maps API)

[0591] Notifications (e.g. FCM, APNs)

[0592] Example of operation

[0593] For example, if a user is in Tokyo, when the application is launched, the latitude and longitude of the user's current location are first obtained and sent to the server. The server then searches a database of anime settings around Tokyo and filters locations within 10 km. For example, if a park in Shinjuku is nearby and the location is crowded, the congestion level is returned to the device as "high." The device plots the park on a map and displays it visually to the user. As the user approaches the location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests efficient sightseeing routes.

[0594] Prompt Sentence Examples

[0595] "Please explain about an app that guides users to nearby anime pilgrimage sites based on their current location."

[0596] "Write a prototype for an app called Anime Sacred Site Navigation. The app's function is to get the user's current location, plot nearby anime sacred sites, and display their congestion status."

[0597] As described above, the present invention is a system that provides users with real-time information about the locations where electronic content is set, enabling an efficient and smooth sightseeing experience.

[0598] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0599] Step 1:

[0600] Obtaining the user's current location

[0601] Description: When a user launches the application, the device (smartphone) uses the GPS function to obtain the user's current location information.

[0602] Input: The user's current latitude and longitude.

[0603] Output: Latitude and longitude of current location.

[0604] Specific operation: Uses the smartphone's GPS sensor to obtain location information and generate latitude and longitude data.

[0605] Step 2:

[0606] Sending location information to the server

[0607] Description: Sends the latitude and longitude information of the current location acquired by the device to the server.

[0608] Input: Latitude and longitude information of your current location.

[0609] Output: Send location information to server.

[0610] Specific operation: The device sends the acquired location information to the server as an API request using the HTTP protocol.

[0611] Step 3:

[0612] Location filtering

[0613] Description: The server filters tourist destination information within 10km from the database based on the received current location information.

[0614] Input: Latitude and longitude information of your current location.

[0615] Output: Nearby tourist attractions information.

[0616] Specific operation: The server executes a database query to extract tourist information within a certain range of the user's current location.

[0617] Step 4:

[0618] Generating congestion status

[0619] Description: The server randomly simulates the crowding of each tourist spot and adds it to each location.

[0620] Input: Nearby tourist attractions information.

[0621] Output: Tourist attraction information with crowd status added.

[0622] Specific operation: The server uses a random number generation algorithm to quantify the congestion level of each tourist spot and add it to the tourist spot information.

[0623] Step 5:

[0624] Sending tourist information to devices

[0625] Description: The server sends tourist spot information including congestion status to the terminal.

[0626] Input: Tourist attraction information with added crowd status.

[0627] Output: Send tourist information to the device.

[0628] Specific operation: The server converts the processed tourist attraction information into JSON format and returns it to the terminal as an HTTP response.

[0629] Step 6:

[0630] Plotting tourist destination information

[0631] Description: The tourist destination information received by the device is plotted on a map and presented visually to the user.

[0632] Input: Tourist attraction information with added crowd status.

[0633] Output: Tourist attractions plotted on a map.

[0634] Specific operation: The device uses Google Maps API or similar to display tourist spot information as markers on a map.

[0635] Step 7:

[0636] Scene information notification

[0637] Description: When the user approaches a specific tourist spot, the device notifies them of related scene information.

[0638] Input: User location and tourist destination information.

[0639] Output: Notification of relevant scene information.

[0640] Specific operation: The device compares the user's current location with the location of the tourist attraction and sends a push notification when the user enters within a specified range.

[0641] Step 8:

[0642] Travel plan creation and proposal

[0643] Description: The device creates and suggests efficient travel plans to the user based on the places the user plans to visit.

[0644] Input: The user's planned visit location.

[0645] Output: Efficient sightseeing route suggestions.

[0646] Specific operation: The device calculates a route using an algorithm that takes into account multiple planned destinations and optimizes distance and time, and presents a visual suggestion to the user.

[0647] The above are the specific processing steps of the present invention.

[0648] 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.

[0649] This system guides users to the actual locations where digital content is set, provides relevant scene information and congestion status based on the user's current location information, creates travel plans and suggests efficient sightseeing routes, and recognizes the user's emotions and optimizes the information provided and route suggestions based on those emotions.

[0650] Server Roles

[0651] The server uses the generative model to organize information about the actual locations where the digital content is set in the database. It receives the user's current location information (latitude and longitude), filters information about anime settings near that location, and receives the user's emotional information through an emotion engine to provide the user with optimized information.

[0652] Receive the user's current location information.

[0653] Filter locations within 10km of the database.

[0654] Randomly generate crowd conditions and add them to each location.

[0655] The emotional information of the user is received, and the location information to be presented is optimized based on the information.

[0656] The filtered anime setting information is returned to the terminal.

[0657] Device Role

[0658] The device receives information about the anime's setting from the server, plots it on a map, and presents it visually to the user. It also notifies the user of related scene information when they arrive within a specified range. It also has the function of creating a travel plan for planned visits and proposing efficient sightseeing routes. It recognizes the user's emotions and dynamically changes the information display and route suggestions based on that.

[0659] Get the user's current location.

[0660] Current location information is sent to the server and anime setting information is received.

[0661] The received information is displayed on a map.

[0662] When it reaches within a predetermined range, it notifies the relevant scene information.

[0663] Create a travel plan and suggest the best sightseeing route.

[0664] An emotion engine is used to recognize the user's emotions and dynamically change the display content and route based on those emotions.

[0665] User operations

[0666] Users can receive information about nearby anime locations by launching the app and allowing location information acquisition. They can then select locations to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related anime scenes. The app can also suggest efficient travel plans for the locations they plan to visit, and provide feedback based on crowding and sentiment.

[0667] Specific examples

[0668] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of anime locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the server will return "Crowded: High" to the device. Furthermore, if the user's emotion is recognized as "tired," the server will suggest more relaxing places and shorter routes to the user.

[0669] The device plots Shinjuku parks on a map and visually displays them to the user. When the user approaches a location, the app notifies them of related scene information. If the user wants to visit places outside of Shinjuku, the app can suggest efficient sightseeing routes and include appropriate rest stops along the way based on their emotions.

[0670] In this way, the present invention is a system that provides users with the most optimal sightseeing experience by providing them with information about anime settings based on their current location information and further combining this with emotion recognition.

[0671] The processing flow will be explained below.

[0672] Step 1:

[0673] When the user launches the app and grants permission to acquire location information and recognize emotions, the device acquires the user's current location using navigator.geolocation.getCurrentPosition and recognizes the user's emotions using sensors such as the camera and microphone.

[0674] Step 2:

[0675] The device sends the acquired latitude and longitude data and emotion data to the server using an HTTP GET request, with the location information and emotion information passed to the server as query parameters.

[0676] Step 3:

[0677] The server receives the request, retrieves all the locations in the anime from its database, and then determines the user's current location based on the latitude and longitude provided.

[0678] Step 4:

[0679] The server uses geopy.distance to calculate the distance between the user's current location and each anime setting. It filters out locations within 10 km and randomly simulates congestion at each location before adding it to the list. This organizes the location information.

[0680] Step 5:

[0681] The server analyzes the user's emotional information and optimizes the content and order of the location information based on that emotional state. For example, if the server detects that the user is "tired," it will prioritize suggesting less crowded or relaxing locations.

[0682] Step 6:

[0683] The server generates a filtered and optimized list of anime locations in JSON format and returns it to the device, including special suggestions based on each location's name, description, distance, crowding status, and emotion.

[0684] Step 7:

[0685] The device analyzes the information about the anime's settings received from the server and plots it on a map. It also displays a list of the settings to the user. For example, it can visually display the information by placing pins on a map.

[0686] Step 8:

[0687] The device monitors the distance between the user's current location and each setting in real time. When the user reaches a predetermined distance (for example, within 1 km), scene information related to that setting is notified to the device. This allows the user to enjoy anime scene information in real time.

[0688] Step 9:

[0689] The device automatically creates a travel plan based on the planned destinations and presents it to the user. This suggests an efficient sightseeing route, allowing the user to smoothly visit multiple locations. Furthermore, the travel plan is dynamically changed based on the user's emotional information. For example, if the user is "having fun," a new location may be added to the sightseeing route.

[0690] Step 10:

[0691] The user travels based on recommended travel plans and sightseeing routes. The device notifies the user of congestion status and emotion information in real time, providing reference information for the user when choosing destinations. The device also recommends appropriate rest areas along the way based on the user's emotions.

[0692] In this way, this system provides information about anime settings based on the user's current location and emotional information, providing an efficient and immersive sightseeing experience. Furthermore, by optimizing information and routes according to the user's emotions, it is possible to provide a more fulfilling experience.

[0693] Example 2

[0694] 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."

[0695] Conventional tourist information systems lack guidance based on the user's current location information and provide limited information on the locations where digital content is set. Furthermore, they do not provide information or suggest routes that take into account congestion or the user's emotions, making it difficult to provide an optimal tourist experience for each individual user. Therefore, there is a need for information to avoid congestion at the site and for the creation of travel plans that suit the user's emotions.

[0696] 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.

[0697] In this invention, the server includes means for preparing information on actual locations that serve as the setting for the digital content using a generative AI model, means for receiving the prepared location information and plotting it on a map using a terminal, means for notifying the user of related scene information when the user arrives within a predetermined range, means for acquiring the user's current location information and sending it to the server, means for the server to filter locations within the predetermined range from a database, means for the server to receive the user's emotional information using an emotion engine and generate optimized information, and means for the terminal to recognize the user's emotions and dynamically change the information display and route suggestions based on the emotions. This makes it possible to provide optimal tourist routes and information according to the user's current location and emotional state, as well as information on the setting for the digital content.

[0698] A "generative AI model" is a model that uses artificial intelligence techniques to generate optimal results for a specific task.

[0699] "Electronic content" refers to information and data that is stored, transmitted, and played in digital form, including, for example, animation and games.

[0700] "Real-life locations" refers to real-life locations that are depicted as the backdrop for scenes or stories in the digital content.

[0701] A "terminal" is a device used by a user for operation, and includes a smartphone, tablet, etc.

[0702] A "server" is a computer system that receives and processes requests from users.

[0703] "Processing" refers to the process of organizing and structuring data to make it usable.

[0704] "Means for receiving and plotting on a map" refers to the process of receiving the transmitted information at the terminal and displaying the information in a map application.

[0705] The "means for notifying scene information" refers to a mechanism for notifying the user of content information related to a specific location when the user reaches that location.

[0706] "Current location information" refers to latitude and longitude data that indicates the user's location.

[0707] "Means for filtering locations within a predetermined range from a database" refers to a process that searches for information in a database based on the user's current location and extracts only results within a pre-defined range.

[0708] An "emotion engine" is a system that identifies a user's emotional state and provides appropriate answers or responses based on that.

[0709] "Means for dynamically changing information display and route suggestions" refers to a mechanism that instantly changes the information presented and the recommended route according to the user's real-time information and emotions.

[0710] This system guides users to actual locations that are the setting for digital content based on their current location information, and provides related scene information and congestion status. It also creates travel plans and suggests efficient sightseeing routes, and can recognize users' emotions and optimize the information provided and route suggestions based on those emotions.

[0711] Server Roles

[0712] The server uses a generative AI model to organize information about the actual locations in the database where digital content is set. It also receives the user's current location information (latitude and longitude) and filters information about locations near that location. The server also receives the user's emotional information using an emotion engine and provides optimized information to the user. The specific process is as follows:

[0713] Receive the user's current location information.

[0714] Filter locations within 10km of the database.

[0715] Randomly generate crowd conditions and add them to each location.

[0716] The emotional information of the user is received, and the location information to be presented is optimized based on the information.

[0717] The filtered location information is returned to the terminal.

[0718] Device Role

[0719] The device plots the location information received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when the user arrives within a specified range. It also has the function of creating a travel plan for planned visits and proposing efficient sightseeing routes. The device uses an emotion engine to recognize the user's emotions and dynamically changes the information display and route suggestions based on those emotions. The specific process is as follows:

[0720] Get the user's current location.

[0721] Current location information is sent to the server, and location information is received.

[0722] The received information is displayed on a map.

[0723] When it reaches within a predetermined range, it notifies the relevant scene information.

[0724] Create a travel plan and suggest the best sightseeing route.

[0725] An emotion engine is used to recognize the user's emotions and dynamically change the display content and route based on those emotions.

[0726] User operations

[0727] Users can launch the app and allow location information acquisition to receive information about nearby locations. They can select locations to visit from the displayed list or map, and when they arrive at the location, they receive related scene information in real time. The app can also suggest efficient travel plans for the locations they plan to visit and provide feedback based on crowd levels and emotions.

[0728] Specific examples

[0729] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the app will return "Crowded: high" to the device.

[0730] Furthermore, if the user's emotion is recognized as "tired," the server suggests more relaxing places and shorter routes to the user. The device plots Shinjuku parks on a map and visually displays them to the user. When the user approaches a location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests an efficient sightseeing route, including appropriate rest stops along the way based on the user's emotion.

[0731] Prompt Sentence Examples

[0732] An example of an input prompt when a user wants to get a specific sightseeing plan is, "Please tell me some recommended locations around Tokyo. I'm currently in Shinjuku. Also, I'm a little tired, so please suggest some places where I can relax." This makes it possible to provide a sightseeing experience optimized for the user's situation and emotions.

[0733] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0734] Step 1:

[0735] The user launches the app

[0736] A user taps an app on their smartphone to launch it. When the app is launched for the first time, it asks for permission to obtain location information. The inputs are user interaction and permission to obtain location information, and the outputs are confirmation that the app has been launched and the setting for permission to obtain location information.

[0737] Step 2:

[0738] The device obtains location information

[0739] The device uses the smartphone's GPS sensor to obtain the user's current location information (latitude and longitude). For example, if the user is near Shinjuku Station, the latitude will be 35.6895 degrees and the longitude will be 139.6917 degrees. The input required is data from the GPS sensor, and the output is the latitude and longitude data of the current location.

[0740] Step 3:

[0741] The device sends its current location information to the server.

[0742] The device sends the acquired latitude and longitude data to the server in real time. The data is sent in a standard format such as JSON. The input requires the latitude and longitude data of the current location, and the output is the current location data sent to the server.

[0743] Step 4:

[0744] The server filters locations within 10km of the database

[0745] The server executes a database query to filter location information within 10km of the user's current location. It uses SQL SELECT statements to extract records that match the criteria. The input requires the received latitude and longitude data and the database, and the output is the filtered location information within 10km.

[0746] Step 5:

[0747] The server receives the user's emotional information using an emotion engine and generates optimized information.

[0748] The server receives the user's emotional information through the emotion recognition API and generates optimized location information based on that information. For example, if the user is recognized as "tired," the information is saved as internal data and reflected in the filtering results. The input requires the user's emotional information and filtered location information, and the output is optimized location information.

[0749] Step 6:

[0750] The server sends optimized location information to the device.

[0751] The server returns the optimized location information to the device. The information is in JSON format and includes latitude, longitude, congestion status, recommended comments, etc. The input requires the optimized location information, and the output is the optimized information sent to the device.

[0752] Step 7:

[0753] The device plots the information on a map

[0754] The device plots the received location information on a map application. The user can visually check the location and information of each location on the map. The received location information is required as input, and the output is the information plotted on the map.

[0755] Step 8:

[0756] The device detects the user's arrival and notifies them of the scene information.

[0757] The device notifies the user of related scene information when the user arrives within a specified range of the setting. For example, when the user arrives at Shinjuku Park, a description and image of a specific scene from the anime are displayed. GPS data and scene information are required as input, and the output is a scene information notification to the user.

[0758] Step 9:

[0759] The device creates a travel plan for the places you plan to visit.

[0760] The device generates an efficient travel plan based on the user's selected locations. For example, it proposes a route that goes around Takadanobaba, Shinjuku, and Ikebukuro. The input requires the user's selected locations, and the output is a travel plan.

[0761] Step 10:

[0762] The device suggests the best sightseeing route for the user

[0763] The device then proposes an optimal sightseeing route to the user based on the generated travel plan. The route is presented with a map, and the points to be visited are marked. The travel plan data is required as input, and the output is the proposed sightseeing route to the user.

[0764] Step 11:

[0765] The device dynamically updates the information

[0766] The device dynamically updates the display and route based on the user's real-time location and emotions, suggesting additional rest stops and new routes. The input requires current location information and emotion information, and the output is the updated display and route.

[0767] (Application example 2)

[0768] 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."

[0769] Conventional information provision systems related to digital content have difficulty providing optimal information that takes into account the user's current location and emotions. Furthermore, functions for providing detailed information about store congestion and in-store product information are limited, leaving a lack of means to maximize the user experience. Furthermore, it has been difficult to provide efficient guidance and information in physical stores. For these reasons, a system that can provide flexible information according to the user's situation and optimal in-store navigation is needed.

[0770] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0771] In this invention, the server includes means for using a generative model to prepare information about the actual location where the digital content is set, means for providing guidance to nearby stores based on the user's current location information, and means for providing information about the congestion status and products in the stores. This makes it possible to provide optimal store guidance, congestion information, and product information based on the user's current location information and emotions.

[0772] A "generative model" refers to an algorithm or machine learning model that generates new information based on given data. Examples include natural language generation and image generation.

[0773] "Electronic content" is a general term for information and media content provided in digital form, including, for example, e-books, videos, music, and web pages.

[0774] A "real-world location" refers to a specific geographic location in the real world where electronic content is set and that a user can visit.

[0775] "Current location information" refers to data that indicates the user's location, and typically refers to latitude and longitude information obtained using location measurement technology such as GPS.

[0776] "Plot on a map" means visually displaying the user's location or a particular location on a geographic map.

[0777] "Scene information" refers to information relating to a particular scene or situation in electronic content, and includes, for example, a particular scene in an anime or a particular episode in a story.

[0778] "Crowding status" is information indicating the degree of crowding of people in a particular location, and is usually expressed as levels such as "high," "medium," and "low."

[0779] "Product information" refers to detailed information about products sold in physical stores, including price, features, and stock status.

[0780] "Emotion recognition" refers to technology that grasps a user's emotional state from their facial expressions, voice, etc., and categorizes emotions such as "joy," "surprise," "sadness," and "fatigue."

[0781] "Navigation" means providing directions or guidance information to help a user reach a particular destination.

[0782] "Event information" refers to information about events and campaigns held at physical stores or specific facilities, including sales, tasting sessions, autograph sessions, etc.

[0783] This system guides users to nearby stores based on their current location and provides information on store congestion and product information. It also recognizes the user's emotions and optimizes route guidance and suggests recommended products based on those emotions. It also has the ability to create a travel plan for planned visits, suggest efficient sightseeing routes, and notify users of events being held in stores.

[0784] Server Roles

[0785] The server uses the generative model to organize information about the actual locations in the database where the digital content is set. To do this, it performs the following processes: First, it receives the user's current location information (latitude and longitude) and filters out store information near that location. It also randomly generates congestion information and adds it to each location. It then receives the user's emotional information using an emotion engine and optimizes store guides and product suggestions based on that information. Finally, it returns the filtered store information to the terminal. This allows the user to receive optimized store information in real time.

[0786] Device Role

[0787] The device plots the store information received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when the user arrives within a specified range. It also has the function of creating a travel plan for planned visits and suggesting efficient sightseeing routes. The device recognizes the user's emotions and dynamically changes the information display and route suggestions based on that. For example, if it recognizes that the user is tired, it will prioritize displaying routes to stores that are less crowded.

[0788] User operations

[0789] Users can receive information about nearby stores by launching the smartphone app and allowing location information acquisition. They can select the store they want to visit from the displayed list or map, and when they actually arrive at the location, they can receive real-time information about the store's products and events. The app can also suggest efficient travel plans for the places they plan to visit and provide feedback based on crowding levels and emotions.

[0790] Specific examples

[0791] For example, suppose the user is in Shinjuku, Tokyo. If the server recognizes that the user is tired, it will prioritize providing information on less crowded stores. Specifically, if the user's current location is "latitude 35.6895, longitude 139.6917" and the user's emotion is recognized as "tired," the server will filter store information around Shinjuku and return information on "ABC Store (low crowding)" to the terminal.

[0792] Example prompts to be input to the generative AI model

[0793] plaintext

[0794] Current location: 35.6895, 139.6917

[0795] Emotion: Tired

[0796] In this way, the system combines emotion recognition and location information to provide optimal information to maximize the user experience.

[0797] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0798] Step 1:

[0799] The user launches the smartphone app and allows location information to be obtained.

[0800] Input: Permission to obtain location information from the user, GPS data from the smartphone

[0801] Output: User's current location (latitude and longitude)

[0802] How it works: Uses the smartphone's GPS module to obtain current location information and its latitude and longitude.

[0803] Step 2:

[0804] The terminal transmits the acquired current location information to the server.

[0805] Input: User's current location information (latitude and longitude)

[0806] Output: Location information sent to the server

[0807] What it does: Sends your current location to the server as an HTTP request.

[0808] Step 3:

[0809] The server filters store information within 10 km of the database based on the received current location information.

[0810] Input: Current location information (latitude and longitude), store database

[0811] Output: A filtered list of stores

[0812] What it does: Uses a database query to find stores within 10km of the current location and lists their information.

[0813] Step 4:

[0814] The server randomly generates congestion status for the filtered store information and adds it to each store information.

[0815] Input: A filtered list of store locations

[0816] Output: List of store information with added crowd status

[0817] How it works: A random algorithm is used to generate three levels of congestion status: high, medium, and low, and this is added to the store information.

[0818] Step 5:

[0819] The server receives the user's emotional information using an emotion engine and optimizes store guides and product suggestions based on that information.

[0820] Input: A list of store information with user emotion information and crowding status added

[0821] Output: A list of store information optimized based on user sentiment

[0822] How it works: The emotion engine analyzes the user's emotional data and generates optimal store guide information based on that data, taking into account the level of congestion and the products offered.

[0823] Step 6:

[0824] The server returns the optimized store information to the terminal.

[0825] Input: List of optimized store locations

[0826] Output: Optimized store information sent back to the device

[0827] Operation: Sends optimized store information to the terminal as an HTTP response.

[0828] Step 7:

[0829] The terminal plots the received store information on a map and presents it visually to the user.

[0830] Input: Optimized store information

[0831] Output: Store information displayed on the map

[0832] How it works: Using the map API, the received store information is plotted on the corresponding geographic coordinates and displayed visually.

[0833] Step 8:

[0834] When the user arrives at the store, the terminal notifies the user of related scene information and detailed information.

[0835] Input: User's current location information, optimized store information

[0836] Output: Notified related scene information and detailed information

[0837] How it works: Using geofencing technology, the app provides scene information and detailed information via pop-up notifications when a user approaches a specific store.

[0838] Step 9:

[0839] The device creates a travel plan for the places you plan to visit and suggests efficient sightseeing routes.

[0840] Input: User's planned visit information, optimized store information, event information

[0841] Output: Suggested itinerary and sightseeing route information

[0842] How it works: It uses a travel plan generation algorithm to create a list of places to visit and calculate and present the optimal route.

[0843] Example prompts to be input to the generative AI model

[0844] plaintext

[0845] Current location: 35.6895, 139.6917

[0846] Emotion: Tired

[0847] 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.

[0848] 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.

[0849] 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.

[0850] [Third embodiment]

[0851] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0852] 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.

[0853] 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).

[0854] 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.

[0855] 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.

[0856] 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).

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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."

[0863] The system of the present invention guides users to the actual locations where digital content is set, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[0864] Server Roles

[0865] The server manages information about the actual locations where the digital content is set in a database. Using a generative model, it generates new locations and related scene information as needed. The server receives the user's current location information (latitude and longitude), filters information about anime settings near that location, and returns it to the user.

[0866] Receive the user's current location information.

[0867] Filter locations within 10km of the database.

[0868] Randomly generate crowd conditions and add them to each location.

[0869] The filtered anime setting information is returned to the terminal.

[0870] Device Role

[0871] The device plots the information about the anime's setting received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when they arrive within a specified range. It also creates a travel plan for the planned visit locations and suggests efficient sightseeing routes.

[0872] Get the user's current location.

[0873] Current location information is sent to the server and anime setting information is received.

[0874] The received information is displayed on a map.

[0875] When it reaches within a predetermined range, it notifies the relevant scene information.

[0876] Create a travel plan and suggest the best sightseeing route.

[0877] User operations

[0878] Users can receive information about nearby anime locations by launching the app and allowing location information acquisition. They can then select a location to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related scenes from the anime. The app also suggests efficient travel plans for the locations they plan to visit and allows them to check the congestion situation.

[0879] Specific examples

[0880] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of anime settings around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the congestion level is returned to the device as "high." The device then plots the Shinjuku park on a map and displays it visually to the user. As the user approaches the location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests efficient sightseeing routes.

[0881] In this way, the present invention is a system that provides users with real-time information about the locations where electronic content is set, enabling an efficient and smooth sightseeing experience.

[0882] The processing flow will be explained below.

[0883] Step 1:

[0884] The user launches the app and allows location information to be acquired. The device retrieves the user's current location using navigator.geolocation.getCurrentPosition. This data is stored in the form of latitude and longitude.

[0885] Step 2:

[0886] The device sends the acquired latitude and longitude data to the server using an HTTP GET request, with the location information passed to the server as a query parameter.

[0887] Step 3:

[0888] The server receives the request, retrieves all the locations in the anime from its database, and then determines the user's current location based on the latitude and longitude provided.

[0889] Step 4:

[0890] The server uses geopy.distance to calculate the distance between the user's current location and each anime setting. It filters out locations within 10 km and randomly simulates congestion at each location before adding it to the list. This organizes the location information.

[0891] Step 5:

[0892] The server generates a list of filtered anime locations in JSON format and returns it to the device. The list includes the name, description, distance, and congestion status of each location.

[0893] Step 6:

[0894] The device analyzes the information about the anime's settings received from the server and plots it on a map. It also displays a list of the settings to the user. For example, it can visually display the information by placing pins on a map.

[0895] Step 7:

[0896] The device monitors the distance between the user's current location and each setting in real time. When the user reaches a predetermined distance (for example, within 1 km), scene information related to that setting is notified to the device. This allows the user to enjoy anime scene information in real time.

[0897] Step 8:

[0898] The device automatically creates a travel plan based on the planned visit locations and presents it to the user, suggesting an efficient sightseeing route and allowing the user to smoothly visit multiple locations.

[0899] Step 9:

[0900] The user travels based on recommended travel plans and sightseeing routes, and the device notifies users of congestion conditions in real time, providing reference information when choosing destinations to visit.

[0901] In this way, this system provides information about the anime's setting locations based on the user's current location information, making it possible to provide an efficient and immersive sightseeing experience.

[0902] Example 1

[0903] 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."

[0904] It is difficult to effectively guide users to the actual locations where digital content is set and provide relevant scene information and crowding status in real time. Furthermore, there is a lack of means to automatically generate and propose efficient travel plans to users. This can lead to confusion in the tourist experience and reduce its appeal.

[0905] 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.

[0906] In this invention, the server includes means for using a generative model to prepare information about the actual locations that are the setting for the digital content, means for filtering the location information for the digital content based on the user's current location information, generating a congestion status and sending it back to the terminal, and means for receiving and analyzing the user's current location information (latitude and longitude) by the server. This allows the user to obtain the location information for the digital content in real time, enabling an efficient and attractive sightseeing experience.

[0907] A "generative model" is an algorithm or program that generates new data or information based on existing data.

[0908] "Electronic Content" means information or media in digital form that can be displayed or played through an electronic device.

[0909] A "real-world location" is a real-world geographic location where a story or scene is actually set.

[0910] A "terminal" is a portable electronic device or computer device that is directly operated by a user.

[0911] "Plotting on a map" means visually displaying a specific location or information on a map app or software.

[0912] "When the user reaches within a predetermined range" means when the user enters a specific geographical range (for example, within 500 m).

[0913] "Related scene information" refers to detailed information or explanations about a particular scene or episode of electronic content.

[0914] "User's current location information" refers to latitude and longitude data that indicates the user's current geographical location.

[0915] "Crowd situation" refers to information that indicates the degree of crowding or bustle in a particular location or area.

[0916] A "travel plan" is a plan of travel routes and schedules that includes planned visits and tourist spots.

[0917] A "tourist route" is a recommended route for efficiently touring tourist spots and visiting places.

[0918] A "server" is a remote computer or system that stores, processes, and distributes data.

[0919] "Filtering" means selecting and extracting data or information based on specific criteria.

[0920] The system of the present invention guides users to the actual locations where digital content is set, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[0921] (Server role)

[0922] The server uses a generative model to prepare information about the actual locations where digital content is set. For example, OpenAI GPT-3 is used for this generative model. The server also receives the user's current location information (latitude and longitude) and filters information about locations within 10 km of the database based on that location. From the filtered information, the server randomly generates a congestion status and sends the result back to the terminal.

[0923] Specific examples of server side operations:

[0924] 1. Receive the user's current location information (latitude and longitude).

[0925] 2. Search and filter location information within 10km from a database management system (e.g., MySQL).

[0926] 3. Randomly generate congestion levels (using indicators such as "low," "medium," and "high").

[0927] 4. The filtered venue information and congestion status are returned to the terminal.

[0928] (Terminal role)

[0929] The device first uses its GPS function to obtain the user's current location information. It then sends the obtained location information to the server and receives information about the anime's setting and crowding situation returned from the server. The received information is then plotted on a map and presented visually to the user. Furthermore, when the user arrives near a specific setting, it notifies the user of related scene information. The device also creates a travel plan for the planned visit locations and suggests efficient sightseeing routes.

[0930] Specific operation examples on the terminal side:

[0931] 1. Obtain the user's current location using GPS.

[0932] 2. Send your current location to the server (example prompt: "What are the locations of anime films near me?").

[0933] 3. Receive the venue information and congestion status sent from the server.

[0934] 4. Display location information on the map using icons, etc., and visually indicate congestion levels using color coding.

[0935] 5. When the user arrives near the location, relevant scene information is notified.

[0936] 6. If the user wants to visit other destinations, we suggest efficient tourist routes and detailed travel plans.

[0937] (User operation)

[0938] Users can access information about nearby anime settings by launching the app and allowing location information acquisition. They can then select the location they want to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related scenes from the anime. They can also use the app to check efficient travel plans and congestion status for the locations they plan to visit.

[0939] Examples:

[0940] When a tourist in Tokyo launches the app, the device first obtains the current latitude and longitude of their location and sends them to the server. The server then searches a database of anime locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the congestion status is sent to the device as "high." The device can then plot the Shinjuku park on a map and display it visually to the user. When the user approaches the park, the device notifies them of related scene information. If the user is interested in places other than Shinjuku, the app suggests efficient sightseeing routes.

[0941] Thus, the present invention is a system that provides users with real-time information about the locations where electronic content is set, thereby enabling an efficient and attractive tourist experience.

[0942] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0943] Step 1:

[0944] The user launches the app and allows location information to be acquired. Specifically, the user operates the app's location information acquisition permission dialog. The input is the user's permission to acquire location information, and the output is the device obtaining permission to acquire location information.

[0945] Step 2:

[0946] The device uses its GPS function to obtain the user's current location. The input is data from the GPS sensor, and the output is the latitude and longitude of the current location. Specifically, the device receives signals from GPS satellites and calculates the latitude and longitude.

[0947] Step 3:

[0948] The device sends the user's current location information to the server. Example prompt: "Tell me where nearby anime is set." The input is the latitude and longitude of the current location, and the output is the location data sent to the server. Specifically, the device generates an HTTP request and sends it to the server.

[0949] Step 4:

[0950] The server filters the location information of digital content based on the user's current location. The input is the current location information submitted, and the output is a list of locations within 10 km. Specifically, the server executes a database query and extracts nearby locations using a distance calculation algorithm.

[0951] Step 5:

[0952] The server generates congestion status for the filtered locations. The input is the filtered location information, and the output is the location information with congestion status added. Specifically, it uses a random number generation algorithm to assign a congestion status of "low," "medium," or "high" to each location.

[0953] Step 6:

[0954] The server sends the filtered information and congestion status to the terminal. The input is the venue information with congestion status added, and the output is the data sent to the terminal. The specific operation is to send the data via an HTTP response.

[0955] Step 7:

[0956] The device plots the received location information and congestion status on a map. The input is data received from the server, and the output is the location icon and congestion status displayed on the map app. Specifically, it calls the map API and visually displays the information using icons and colors.

[0957] Step 8:

[0958] When a user arrives near a specific location, the device notifies them of related scene information. The input is the device's location information and the set notification range, and the output is the notified scene information. Specifically, the device calculates the distance between the user's location and the setting, and activates the notification function if the user is within the specified range.

[0959] Step 9:

[0960] The user selects the places they plan to visit, and the device generates an efficient travel plan and sightseeing route. The input is a list of places selected by the user, and the output is an optimized sightseeing route. Specifically, the device applies a route optimization algorithm to generate and display the travel plan.

[0961] (Application example 1)

[0962] 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."

[0963] Conventional tourist information systems for digital content and anime locations lacked the ability to provide real-time information based on the user's current location. They also lacked the ability to grasp congestion levels or suggest efficient sightseeing routes, making it difficult for users to enjoy comfortable and efficient sightseeing. This led to a decline in user satisfaction and hindered the development of the tourism industry.

[0964] 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.

[0965] In this invention, the server includes means for using a generative model to prepare information about the actual location that will be the setting for the digital content, means for filtering information about nearby tourist spots based on the user's current location information, and means for randomly simulating and providing congestion conditions, allowing the user to receive information about nearby tourist spots in real time, understand congestion conditions, and receive suggestions for efficient tourist routes.

[0966] A "generative model" is a general term for algorithms and methods that learn specific patterns and features from data and generate new ones.

[0967] "Electronic content" refers to information and media provided in digital form, especially location information such as anime and manga.

[0968] "Tourist destination information" refers to information about specific places that tourists want to visit, including their location, characteristics, history, and crowding status.

[0969] "Nearby" refers to a location within a certain distance from the user's current location.

[0970] "Crowding situation" is information that shows the density and concentration of people and vehicles in a specific location in real time.

[0971] "Filtering" refers to the process or method of selecting data based on specific conditions.

[0972] "Tourist route" refers to a route or sequence set up to efficiently visit multiple tourist spots.

[0973] "User's current location" refers to information about the latitude and longitude of the user's current physical location.

[0974] "Scene information" refers to explanatory and image information related to a specific scene in electronic content such as an anime or manga.

[0975] The present invention is a system that guides users to actual locations that are the setting for digital content based on their current location information, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[0976] Server Roles

[0977] The server performs the following main roles:

[0978] 1. Location Management:

[0979] Using the generative model, we create a database of real-world locations where digital content is set, including location information (latitude and longitude) and related scene information.

[0980] 2. Filtering:

[0981] Receives the user's current location information and filters tourist spot information within a certain distance (e.g., 10 km) from that location.

[0982] 3. Congestion generation:

[0983] The system randomly simulates the congestion situation for each tourist spot and provides it to the user.

[0984] Device Role

[0985] The terminal performs the following main roles:

[0986] 1. Obtaining current location information:

[0987] Use the smartphone's GPS function to obtain the user's current location.

[0988] 2. Receiving and Displaying Information:

[0989] The system receives the organized location information and filtered tourist spot information from the server and plots and displays it on a map.

[0990] 3. Scene information notification:

[0991] When the user reaches a predetermined range, relevant scene information is notified.

[0992] 4. Create your travel plan:

[0993] Create a travel plan for the places you plan to visit and suggest efficient sightseeing routes.

[0994] Hardware and software used

[0995] Hardware:

[0996] Smartphone: A typical smartphone with GPS functionality and internet connectivity.

[0997] software:

[0998] Server-side software:

[0999] Database management systems (e.g. MySQL, PostgreSQL)

[1000] Generative models (e.g., TensorFlow, OpenAI GPT)

[1001] Terminal software:

[1002] GPS data acquisition function

[1003] Map display applications (e.g., Google Maps API)

[1004] Notifications (e.g. FCM, APNs)

[1005] Example of operation

[1006] For example, if a user is in Tokyo, when the application is launched, the latitude and longitude of the user's current location are first obtained and sent to the server. The server then searches a database of anime settings around Tokyo and filters locations within 10 km. For example, if a park in Shinjuku is nearby and the location is crowded, the congestion level is returned to the device as "high." The device plots the park on a map and displays it visually to the user. As the user approaches the location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests efficient sightseeing routes.

[1007] Prompt Sentence Examples

[1008] "Please explain about an app that guides users to nearby anime pilgrimage sites based on their current location."

[1009] "Write a prototype for an app called Anime Sacred Site Navigation. The app's function is to get the user's current location, plot nearby anime sacred sites, and display their congestion status."

[1010] As described above, the present invention is a system that provides users with real-time information about the locations where electronic content is set, enabling an efficient and smooth sightseeing experience.

[1011] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1012] Step 1:

[1013] Obtaining the user's current location

[1014] Description: When a user launches the application, the device (smartphone) uses the GPS function to obtain the user's current location information.

[1015] Input: The user's current latitude and longitude.

[1016] Output: Latitude and longitude of current location.

[1017] Specific operation: Uses the smartphone's GPS sensor to obtain location information and generate latitude and longitude data.

[1018] Step 2:

[1019] Sending location information to the server

[1020] Description: Sends the latitude and longitude information of the current location acquired by the device to the server.

[1021] Input: Latitude and longitude information of your current location.

[1022] Output: Send location information to server.

[1023] Specific operation: The device sends the acquired location information to the server as an API request using the HTTP protocol.

[1024] Step 3:

[1025] Location filtering

[1026] Description: The server filters tourist destination information within 10km from the database based on the received current location information.

[1027] Input: Latitude and longitude information of your current location.

[1028] Output: Nearby tourist attractions information.

[1029] Specific operation: The server executes a database query to extract tourist information within a certain range of the user's current location.

[1030] Step 4:

[1031] Generating congestion status

[1032] Description: The server randomly simulates the crowding of each tourist spot and adds it to each location.

[1033] Input: Nearby tourist attractions information.

[1034] Output: Tourist attraction information with crowd status added.

[1035] Specific operation: The server uses a random number generation algorithm to quantify the congestion level of each tourist spot and add it to the tourist spot information.

[1036] Step 5:

[1037] Sending tourist information to devices

[1038] Description: The server sends tourist spot information including congestion status to the terminal.

[1039] Input: Tourist attraction information with added crowd status.

[1040] Output: Send tourist information to the device.

[1041] Specific operation: The server converts the processed tourist attraction information into JSON format and returns it to the terminal as an HTTP response.

[1042] Step 6:

[1043] Plotting tourist destination information

[1044] Description: The tourist destination information received by the device is plotted on a map and presented visually to the user.

[1045] Input: Tourist attraction information with added crowd status.

[1046] Output: Tourist attractions plotted on a map.

[1047] Specific operation: The device uses Google Maps API or similar to display tourist spot information as markers on a map.

[1048] Step 7:

[1049] Scene information notification

[1050] Description: When the user approaches a specific tourist spot, the device notifies them of related scene information.

[1051] Input: User location and tourist destination information.

[1052] Output: Notification of relevant scene information.

[1053] Specific operation: The device compares the user's current location with the location of the tourist attraction and sends a push notification when the user enters within a specified range.

[1054] Step 8:

[1055] Travel plan creation and proposal

[1056] Description: The device creates and suggests efficient travel plans to the user based on the places the user plans to visit.

[1057] Input: The user's planned visit location.

[1058] Output: Efficient sightseeing route suggestions.

[1059] Specific operation: The device calculates a route using an algorithm that takes into account multiple planned destinations and optimizes distance and time, and presents a visual suggestion to the user.

[1060] The above are the specific processing steps of the present invention.

[1061] 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.

[1062] This system guides users to the actual locations where digital content is set, provides relevant scene information and congestion status based on the user's current location information, creates travel plans and suggests efficient sightseeing routes, and recognizes the user's emotions and optimizes the information provided and route suggestions based on those emotions.

[1063] Server Roles

[1064] The server uses the generative model to organize information about the actual locations where the digital content is set in the database. It receives the user's current location information (latitude and longitude), filters information about anime settings near that location, and receives the user's emotional information through an emotion engine to provide the user with optimized information.

[1065] Receive the user's current location information.

[1066] Filter locations within 10km of the database.

[1067] Randomly generate crowd conditions and add them to each location.

[1068] The emotional information of the user is received, and the location information to be presented is optimized based on the information.

[1069] The filtered anime setting information is returned to the terminal.

[1070] Device Role

[1071] The device receives information about the anime's setting from the server, plots it on a map, and presents it visually to the user. It also notifies the user of related scene information when they arrive within a specified range. It also has the function of creating a travel plan for planned visits and proposing efficient sightseeing routes. It recognizes the user's emotions and dynamically changes the information display and route suggestions based on that.

[1072] Get the user's current location.

[1073] Current location information is sent to the server and anime setting information is received.

[1074] The received information is displayed on a map.

[1075] When it reaches within a predetermined range, it notifies the relevant scene information.

[1076] Create a travel plan and suggest the best sightseeing route.

[1077] An emotion engine is used to recognize the user's emotions and dynamically change the display content and route based on those emotions.

[1078] User operations

[1079] Users can receive information about nearby anime locations by launching the app and allowing location information acquisition. They can then select locations to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related anime scenes. The app can also suggest efficient travel plans for the locations they plan to visit, and provide feedback based on crowding and sentiment.

[1080] Specific examples

[1081] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of anime locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the server will return "Crowded: High" to the device. Furthermore, if the user's emotion is recognized as "tired," the server will suggest more relaxing places and shorter routes to the user.

[1082] The device plots Shinjuku parks on a map and visually displays them to the user. When the user approaches a location, the app notifies them of related scene information. If the user wants to visit places outside of Shinjuku, the app can suggest efficient sightseeing routes and include appropriate rest stops along the way based on their emotions.

[1083] In this way, the present invention is a system that provides users with the most optimal sightseeing experience by providing them with information about anime settings based on their current location information and further combining this with emotion recognition.

[1084] The processing flow will be explained below.

[1085] Step 1:

[1086] When the user launches the app and grants permission to acquire location information and recognize emotions, the device acquires the user's current location using navigator.geolocation.getCurrentPosition and recognizes the user's emotions using sensors such as the camera and microphone.

[1087] Step 2:

[1088] The device sends the acquired latitude and longitude data and emotion data to the server using an HTTP GET request, with the location information and emotion information passed to the server as query parameters.

[1089] Step 3:

[1090] The server receives the request, retrieves all the locations in the anime from its database, and then determines the user's current location based on the latitude and longitude provided.

[1091] Step 4:

[1092] The server uses geopy.distance to calculate the distance between the user's current location and each anime setting. It filters out locations within 10 km and randomly simulates congestion at each location before adding it to the list. This organizes the location information.

[1093] Step 5:

[1094] The server analyzes the user's emotional information and optimizes the content and order of the location information based on that emotional state. For example, if the server detects that the user is "tired," it will prioritize suggesting less crowded or relaxing locations.

[1095] Step 6:

[1096] The server generates a filtered and optimized list of anime locations in JSON format and returns it to the device, including special suggestions based on each location's name, description, distance, crowding status, and emotion.

[1097] Step 7:

[1098] The device analyzes the information about the anime's settings received from the server and plots it on a map. It also displays a list of the settings to the user. For example, it can visually display the information by placing pins on a map.

[1099] Step 8:

[1100] The device monitors the distance between the user's current location and each setting in real time. When the user reaches a predetermined distance (for example, within 1 km), scene information related to that setting is notified to the device. This allows the user to enjoy anime scene information in real time.

[1101] Step 9:

[1102] The device automatically creates a travel plan based on the planned destinations and presents it to the user. This suggests an efficient sightseeing route, allowing the user to smoothly visit multiple locations. Furthermore, the travel plan is dynamically changed based on the user's emotional information. For example, if the user is "having fun," a new location may be added to the sightseeing route.

[1103] Step 10:

[1104] The user travels based on recommended travel plans and sightseeing routes. The device notifies the user of congestion status and emotion information in real time, providing reference information for the user when choosing destinations. The device also recommends appropriate rest areas along the way based on the user's emotions.

[1105] In this way, this system provides information about anime settings based on the user's current location and emotional information, providing an efficient and immersive sightseeing experience. Furthermore, by optimizing information and routes according to the user's emotions, it is possible to provide a more fulfilling experience.

[1106] Example 2

[1107] 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."

[1108] Conventional tourist information systems lack guidance based on the user's current location information and provide limited information on the locations where digital content is set. Furthermore, they do not provide information or suggest routes that take into account congestion or the user's emotions, making it difficult to provide an optimal tourist experience for each individual user. Therefore, there is a need for information to avoid congestion at the site and for the creation of travel plans that suit the user's emotions.

[1109] 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.

[1110] In this invention, the server includes means for preparing information on actual locations that serve as the setting for the digital content using a generative AI model, means for receiving the prepared location information and plotting it on a map using a terminal, means for notifying the user of related scene information when the user arrives within a predetermined range, means for acquiring the user's current location information and sending it to the server, means for the server to filter locations within the predetermined range from a database, means for the server to receive the user's emotional information using an emotion engine and generate optimized information, and means for the terminal to recognize the user's emotions and dynamically change the information display and route suggestions based on the emotions. This makes it possible to provide optimal tourist routes and information according to the user's current location and emotional state, as well as information on the setting for the digital content.

[1111] A "generative AI model" is a model that uses artificial intelligence techniques to generate optimal results for a specific task.

[1112] "Electronic content" refers to information and data that is stored, transmitted, and played in digital form, including, for example, animation and games.

[1113] "Real-life locations" refers to real-life locations that are depicted as the backdrop for scenes or stories in the digital content.

[1114] A "terminal" is a device used by a user for operation, and includes a smartphone, tablet, etc.

[1115] A "server" is a computer system that receives and processes requests from users.

[1116] "Processing" refers to the process of organizing and structuring data to make it usable.

[1117] "Means for receiving and plotting on a map" refers to the process of receiving the transmitted information at the terminal and displaying the information in a map application.

[1118] The "means for notifying scene information" refers to a mechanism for notifying the user of content information related to a specific location when the user reaches that location.

[1119] "Current location information" refers to latitude and longitude data that indicates the user's location.

[1120] "Means for filtering locations within a predetermined range from a database" refers to a process that searches for information in a database based on the user's current location and extracts only results within a pre-defined range.

[1121] An "emotion engine" is a system that identifies a user's emotional state and provides appropriate answers or responses based on that.

[1122] "Means for dynamically changing information display and route suggestions" refers to a mechanism that instantly changes the information presented and the recommended route according to the user's real-time information and emotions.

[1123] This system guides users to actual locations that are the setting for digital content based on their current location information, and provides related scene information and congestion status. It also creates travel plans and suggests efficient sightseeing routes, and can recognize users' emotions and optimize the information provided and route suggestions based on those emotions.

[1124] Server Roles

[1125] The server uses a generative AI model to organize information about the actual locations in the database where digital content is set. It also receives the user's current location information (latitude and longitude) and filters information about locations near that location. The server also receives the user's emotional information using an emotion engine and provides optimized information to the user. The specific process is as follows:

[1126] Receive the user's current location information.

[1127] Filter locations within 10km of the database.

[1128] Randomly generate crowd conditions and add them to each location.

[1129] The emotional information of the user is received, and the location information to be presented is optimized based on the information.

[1130] The filtered location information is returned to the terminal.

[1131] Device Role

[1132] The device plots the location information received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when the user arrives within a specified range. It also has the function of creating a travel plan for planned visits and proposing efficient sightseeing routes. The device uses an emotion engine to recognize the user's emotions and dynamically changes the information display and route suggestions based on those emotions. The specific process is as follows:

[1133] Get the user's current location.

[1134] Current location information is sent to the server, and location information is received.

[1135] The received information is displayed on a map.

[1136] When it reaches within a predetermined range, it notifies the relevant scene information.

[1137] Create a travel plan and suggest the best sightseeing route.

[1138] An emotion engine is used to recognize the user's emotions and dynamically change the display content and route based on those emotions.

[1139] User operations

[1140] Users can launch the app and allow location information acquisition to receive information about nearby locations. They can select locations to visit from the displayed list or map, and when they arrive at the location, they receive related scene information in real time. The app can also suggest efficient travel plans for the locations they plan to visit and provide feedback based on crowd levels and emotions.

[1141] Specific examples

[1142] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the app will return "Crowded: high" to the device.

[1143] Furthermore, if the user's emotion is recognized as "tired," the server suggests more relaxing places and shorter routes to the user. The device plots Shinjuku parks on a map and visually displays them to the user. When the user approaches a location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests an efficient sightseeing route, including appropriate rest stops along the way based on the user's emotion.

[1144] Prompt Sentence Examples

[1145] An example of an input prompt when a user wants to get a specific sightseeing plan is, "Please tell me some recommended locations around Tokyo. I'm currently in Shinjuku. Also, I'm a little tired, so please suggest some places where I can relax." This makes it possible to provide a sightseeing experience optimized for the user's situation and emotions.

[1146] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1147] Step 1:

[1148] The user launches the app

[1149] A user taps an app on their smartphone to launch it. When the app is launched for the first time, it asks for permission to obtain location information. The inputs are user interaction and permission to obtain location information, and the outputs are confirmation that the app has been launched and the setting for permission to obtain location information.

[1150] Step 2:

[1151] The device obtains location information

[1152] The device uses the smartphone's GPS sensor to obtain the user's current location information (latitude and longitude). For example, if the user is near Shinjuku Station, the latitude will be 35.6895 degrees and the longitude will be 139.6917 degrees. The input required is data from the GPS sensor, and the output is the latitude and longitude data of the current location.

[1153] Step 3:

[1154] The device sends its current location information to the server.

[1155] The device sends the acquired latitude and longitude data to the server in real time. The data is sent in a standard format such as JSON. The input requires the latitude and longitude data of the current location, and the output is the current location data sent to the server.

[1156] Step 4:

[1157] The server filters locations within 10km of the database

[1158] The server executes a database query to filter location information within 10km of the user's current location. It uses SQL SELECT statements to extract records that match the criteria. The input requires the received latitude and longitude data and the database, and the output is the filtered location information within 10km.

[1159] Step 5:

[1160] The server receives the user's emotional information using an emotion engine and generates optimized information.

[1161] The server receives the user's emotional information through the emotion recognition API and generates optimized location information based on that information. For example, if the user is recognized as "tired," the information is saved as internal data and reflected in the filtering results. The input requires the user's emotional information and filtered location information, and the output is optimized location information.

[1162] Step 6:

[1163] The server sends optimized location information to the device.

[1164] The server returns the optimized location information to the device. The information is in JSON format and includes latitude, longitude, congestion status, recommended comments, etc. The input requires the optimized location information, and the output is the optimized information sent to the device.

[1165] Step 7:

[1166] The device plots the information on a map

[1167] The device plots the received location information on a map application. The user can visually check the location and information of each location on the map. The received location information is required as input, and the output is the information plotted on the map.

[1168] Step 8:

[1169] The device detects the user's arrival and notifies them of the scene information.

[1170] The device notifies the user of related scene information when the user arrives within a specified range of the setting. For example, when the user arrives at Shinjuku Park, a description and image of a specific scene from the anime are displayed. GPS data and scene information are required as input, and the output is a scene information notification to the user.

[1171] Step 9:

[1172] The device creates a travel plan for the places you plan to visit.

[1173] The device generates an efficient travel plan based on the user's selected locations. For example, it proposes a route that goes around Takadanobaba, Shinjuku, and Ikebukuro. The input requires the user's selected locations, and the output is a travel plan.

[1174] Step 10:

[1175] The device suggests the best sightseeing route for the user

[1176] The device then proposes an optimal sightseeing route to the user based on the generated travel plan. The route is presented with a map, and the points to be visited are marked. The travel plan data is required as input, and the output is the proposed sightseeing route to the user.

[1177] Step 11:

[1178] The device dynamically updates the information

[1179] The device dynamically updates the display and route based on the user's real-time location and emotions, suggesting additional rest stops and new routes. The input requires current location information and emotion information, and the output is the updated display and route.

[1180] (Application example 2)

[1181] 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."

[1182] Conventional information provision systems related to digital content have difficulty providing optimal information that takes into account the user's current location and emotions. Furthermore, functions for providing detailed information about store congestion and in-store product information are limited, leaving a lack of means to maximize the user experience. Furthermore, it has been difficult to provide efficient guidance and information in physical stores. For these reasons, a system that can provide flexible information according to the user's situation and optimal in-store navigation is needed.

[1183] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1184] In this invention, the server includes means for using a generative model to prepare information about the actual location where the digital content is set, means for providing guidance to nearby stores based on the user's current location information, and means for providing information about the congestion status and products in the stores. This makes it possible to provide optimal store guidance, congestion information, and product information based on the user's current location information and emotions.

[1185] A "generative model" refers to an algorithm or machine learning model that generates new information based on given data. Examples include natural language generation and image generation.

[1186] "Electronic content" is a general term for information and media content provided in digital form, including, for example, e-books, videos, music, and web pages.

[1187] A "real-world location" refers to a specific geographic location in the real world where electronic content is set and that a user can visit.

[1188] "Current location information" refers to data that indicates the user's location, and typically refers to latitude and longitude information obtained using location measurement technology such as GPS.

[1189] "Plot on a map" means visually displaying the user's location or a particular location on a geographic map.

[1190] "Scene information" refers to information relating to a particular scene or situation in electronic content, and includes, for example, a particular scene in an anime or a particular episode in a story.

[1191] "Crowding status" is information indicating the degree of crowding of people in a particular location, and is usually expressed as levels such as "high," "medium," and "low."

[1192] "Product information" refers to detailed information about products sold in physical stores, including price, features, and stock status.

[1193] "Emotion recognition" refers to technology that grasps a user's emotional state from their facial expressions, voice, etc., and categorizes emotions such as "joy," "surprise," "sadness," and "fatigue."

[1194] "Navigation" means providing directions or guidance information to help a user reach a particular destination.

[1195] "Event information" refers to information about events and campaigns held at physical stores or specific facilities, including sales, tasting sessions, autograph sessions, etc.

[1196] This system guides users to nearby stores based on their current location and provides information on store congestion and product information. It also recognizes the user's emotions and optimizes route guidance and suggests recommended products based on those emotions. It also has the ability to create a travel plan for planned visits, suggest efficient sightseeing routes, and notify users of events being held in stores.

[1197] Server Roles

[1198] The server uses the generative model to organize information about the actual locations in the database where the digital content is set. To do this, it performs the following processes: First, it receives the user's current location information (latitude and longitude) and filters out store information near that location. It also randomly generates congestion information and adds it to each location. It then receives the user's emotional information using an emotion engine and optimizes store guides and product suggestions based on that information. Finally, it returns the filtered store information to the terminal. This allows the user to receive optimized store information in real time.

[1199] Device Role

[1200] The device plots the store information received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when the user arrives within a specified range. It also has the function of creating a travel plan for planned visits and suggesting efficient sightseeing routes. The device recognizes the user's emotions and dynamically changes the information display and route suggestions based on that. For example, if it recognizes that the user is tired, it will prioritize displaying routes to stores that are less crowded.

[1201] User operations

[1202] Users can receive information about nearby stores by launching the smartphone app and allowing location information acquisition. They can select the store they want to visit from the displayed list or map, and when they actually arrive at the location, they can receive real-time information about the store's products and events. The app can also suggest efficient travel plans for the places they plan to visit and provide feedback based on crowding levels and emotions.

[1203] Specific examples

[1204] For example, suppose the user is in Shinjuku, Tokyo. If the server recognizes that the user is tired, it will prioritize providing information on less crowded stores. Specifically, if the user's current location is "latitude 35.6895, longitude 139.6917" and the user's emotion is recognized as "tired," the server will filter store information around Shinjuku and return information on "ABC Store (low crowding)" to the terminal.

[1205] Example prompts to be input to the generative AI model

[1206] plaintext

[1207] Current location: 35.6895, 139.6917

[1208] Emotion: Tired

[1209] In this way, the system combines emotion recognition and location information to provide optimal information to maximize the user experience.

[1210] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1211] Step 1:

[1212] The user launches the smartphone app and allows location information to be obtained.

[1213] Input: Permission to obtain location information from the user, GPS data from the smartphone

[1214] Output: User's current location (latitude and longitude)

[1215] How it works: Uses the smartphone's GPS module to obtain current location information and its latitude and longitude.

[1216] Step 2:

[1217] The terminal transmits the acquired current location information to the server.

[1218] Input: User's current location information (latitude and longitude)

[1219] Output: Location information sent to the server

[1220] What it does: Sends your current location to the server as an HTTP request.

[1221] Step 3:

[1222] The server filters store information within 10 km of the database based on the received current location information.

[1223] Input: Current location information (latitude and longitude), store database

[1224] Output: A filtered list of stores

[1225] What it does: Uses a database query to find stores within 10km of the current location and lists their information.

[1226] Step 4:

[1227] The server randomly generates congestion status for the filtered store information and adds it to each store information.

[1228] Input: A filtered list of store locations

[1229] Output: List of store information with added crowd status

[1230] How it works: A random algorithm is used to generate three levels of congestion status: high, medium, and low, and this is added to the store information.

[1231] Step 5:

[1232] The server receives the user's emotional information using an emotion engine and optimizes store guides and product suggestions based on that information.

[1233] Input: A list of store information with user emotion information and crowding status added

[1234] Output: A list of store information optimized based on user sentiment

[1235] How it works: The emotion engine analyzes the user's emotional data and generates optimal store guide information based on that data, taking into account the level of congestion and the products offered.

[1236] Step 6:

[1237] The server returns the optimized store information to the terminal.

[1238] Input: List of optimized store locations

[1239] Output: Optimized store information sent back to the device

[1240] Operation: Sends optimized store information to the terminal as an HTTP response.

[1241] Step 7:

[1242] The terminal plots the received store information on a map and presents it visually to the user.

[1243] Input: Optimized store information

[1244] Output: Store information displayed on the map

[1245] How it works: Using the map API, the received store information is plotted on the corresponding geographic coordinates and displayed visually.

[1246] Step 8:

[1247] When the user arrives at the store, the terminal notifies the user of related scene information and detailed information.

[1248] Input: User's current location information, optimized store information

[1249] Output: Notified related scene information and detailed information

[1250] How it works: Using geofencing technology, the app provides scene information and detailed information via pop-up notifications when a user approaches a specific store.

[1251] Step 9:

[1252] The device creates a travel plan for the places you plan to visit and suggests efficient sightseeing routes.

[1253] Input: User's planned visit information, optimized store information, event information

[1254] Output: Suggested itinerary and sightseeing route information

[1255] How it works: It uses a travel plan generation algorithm to create a list of places to visit and calculate and present the optimal route.

[1256] Example prompts to be input to the generative AI model

[1257] plaintext

[1258] Current location: 35.6895, 139.6917

[1259] Emotion: Tired

[1260] 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.

[1261] 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.

[1262] 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.

[1263] [Fourth embodiment]

[1264] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1265] 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.

[1266] 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).

[1267] 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.

[1268] 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.

[1269] 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).

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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.

[1274] 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.

[1275] 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.

[1276] 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."

[1277] The system of the present invention guides users to the actual locations where digital content is set, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[1278] Server Roles

[1279] The server manages information about the actual locations where the digital content is set in a database. Using a generative model, it generates new locations and related scene information as needed. The server receives the user's current location information (latitude and longitude), filters information about anime settings near that location, and returns it to the user.

[1280] Receive the user's current location information.

[1281] Filter locations within 10km of the database.

[1282] Randomly generate crowd conditions and add them to each location.

[1283] The filtered anime setting information is returned to the terminal.

[1284] Device Role

[1285] The device plots the information about the anime's setting received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when they arrive within a specified range. It also creates a travel plan for the planned visit locations and suggests efficient sightseeing routes.

[1286] Get the user's current location.

[1287] Current location information is sent to the server and anime setting information is received.

[1288] The received information is displayed on a map.

[1289] When it reaches within a predetermined range, it notifies the relevant scene information.

[1290] Create a travel plan and suggest the best sightseeing route.

[1291] User operations

[1292] Users can receive information about nearby anime locations by launching the app and allowing location information acquisition. They can then select a location to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related scenes from the anime. The app also suggests efficient travel plans for the locations they plan to visit and allows them to check the congestion situation.

[1293] Specific examples

[1294] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of anime settings around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the congestion level is returned to the device as "high." The device then plots the Shinjuku park on a map and displays it visually to the user. As the user approaches the location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests efficient sightseeing routes.

[1295] In this way, the present invention is a system that provides users with real-time information about the locations where electronic content is set, enabling an efficient and smooth sightseeing experience.

[1296] The processing flow will be explained below.

[1297] Step 1:

[1298] The user launches the app and allows location information to be acquired. The device retrieves the user's current location using navigator.geolocation.getCurrentPosition. This data is stored in the form of latitude and longitude.

[1299] Step 2:

[1300] The device sends the acquired latitude and longitude data to the server using an HTTP GET request, with the location information passed to the server as a query parameter.

[1301] Step 3:

[1302] The server receives the request, retrieves all the locations in the anime from its database, and then determines the user's current location based on the latitude and longitude provided.

[1303] Step 4:

[1304] The server uses geopy.distance to calculate the distance between the user's current location and each anime setting. It filters out locations within 10 km and randomly simulates congestion at each location before adding it to the list. This organizes the location information.

[1305] Step 5:

[1306] The server generates a list of filtered anime locations in JSON format and returns it to the device. The list includes the name, description, distance, and congestion status of each location.

[1307] Step 6:

[1308] The device analyzes the information about the anime's settings received from the server and plots it on a map. It also displays a list of the settings to the user. For example, it can visually display the information by placing pins on a map.

[1309] Step 7:

[1310] The device monitors the distance between the user's current location and each setting in real time. When the user reaches a predetermined distance (for example, within 1 km), scene information related to that setting is notified to the device. This allows the user to enjoy anime scene information in real time.

[1311] Step 8:

[1312] The device automatically creates a travel plan based on the planned visit locations and presents it to the user, suggesting an efficient sightseeing route and allowing the user to smoothly visit multiple locations.

[1313] Step 9:

[1314] The user travels based on recommended travel plans and sightseeing routes, and the device notifies users of congestion conditions in real time, providing reference information when choosing destinations to visit.

[1315] In this way, this system provides information about the anime's setting locations based on the user's current location information, making it possible to provide an efficient and immersive sightseeing experience.

[1316] Example 1

[1317] 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."

[1318] It is difficult to effectively guide users to the actual locations where digital content is set and provide relevant scene information and crowding status in real time. Furthermore, there is a lack of means to automatically generate and propose efficient travel plans to users. This can lead to confusion in the tourist experience and reduce its appeal.

[1319] 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.

[1320] In this invention, the server includes means for using a generative model to prepare information about the actual locations that are the setting for the digital content, means for filtering the location information for the digital content based on the user's current location information, generating a congestion status and sending it back to the terminal, and means for receiving and analyzing the user's current location information (latitude and longitude) by the server. This allows the user to obtain the location information for the digital content in real time, enabling an efficient and attractive sightseeing experience.

[1321] A "generative model" is an algorithm or program that generates new data or information based on existing data.

[1322] "Electronic Content" means information or media in digital form that can be displayed or played through an electronic device.

[1323] A "real-world location" is a real-world geographic location where a story or scene is actually set.

[1324] A "terminal" is a portable electronic device or computer device that is directly operated by a user.

[1325] "Plotting on a map" means visually displaying a specific location or information on a map app or software.

[1326] "When the user reaches within a predetermined range" means when the user enters a specific geographical range (for example, within 500 m).

[1327] "Related scene information" refers to detailed information or explanations about a particular scene or episode of electronic content.

[1328] "User's current location information" refers to latitude and longitude data that indicates the user's current geographical location.

[1329] "Crowd situation" refers to information that indicates the degree of crowding or bustle in a particular location or area.

[1330] A "travel plan" is a plan of travel routes and schedules that includes planned visits and tourist spots.

[1331] A "tourist route" is a recommended route for efficiently touring tourist spots and visiting places.

[1332] A "server" is a remote computer or system that stores, processes, and distributes data.

[1333] "Filtering" means selecting and extracting data or information based on specific criteria.

[1334] The system of the present invention guides users to the actual locations where digital content is set, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[1335] (Server role)

[1336] The server uses a generative model to prepare information about the actual locations where digital content is set. For example, OpenAI GPT-3 is used for this generative model. The server also receives the user's current location information (latitude and longitude) and filters information about locations within 10 km of the database based on that location. From the filtered information, the server randomly generates a congestion status and sends the result back to the terminal.

[1337] Specific examples of server side operations:

[1338] 1. Receive the user's current location information (latitude and longitude).

[1339] 2. Search and filter location information within 10km from a database management system (e.g., MySQL).

[1340] 3. Randomly generate congestion levels (using indicators such as "low," "medium," and "high").

[1341] 4. The filtered venue information and congestion status are returned to the terminal.

[1342] (Terminal role)

[1343] The device first uses its GPS function to obtain the user's current location information. It then sends the obtained location information to the server and receives information about the anime's setting and crowding situation returned from the server. The received information is then plotted on a map and presented visually to the user. Furthermore, when the user arrives near a specific setting, it notifies the user of related scene information. The device also creates a travel plan for the planned visit locations and suggests efficient sightseeing routes.

[1344] Specific operation examples on the terminal side:

[1345] 1. Obtain the user's current location using GPS.

[1346] 2. Send your current location to the server (example prompt: "What are the locations of anime films near me?").

[1347] 3. Receive the venue information and congestion status sent from the server.

[1348] 4. Display location information on the map using icons, etc., and visually indicate congestion levels using color coding.

[1349] 5. When the user arrives near the location, relevant scene information is notified.

[1350] 6. If the user wants to visit other destinations, we suggest efficient tourist routes and detailed travel plans.

[1351] (User operation)

[1352] Users can access information about nearby anime settings by launching the app and allowing location information acquisition. They can then select the location they want to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related scenes from the anime. They can also use the app to check efficient travel plans and congestion status for the locations they plan to visit.

[1353] Examples:

[1354] When a tourist in Tokyo launches the app, the device first obtains the current latitude and longitude of their location and sends them to the server. The server then searches a database of anime locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the congestion status is sent to the device as "high." The device can then plot the Shinjuku park on a map and display it visually to the user. When the user approaches the park, the device notifies them of related scene information. If the user is interested in places other than Shinjuku, the app suggests efficient sightseeing routes.

[1355] Thus, the present invention is a system that provides users with real-time information about the locations where electronic content is set, thereby enabling an efficient and attractive tourist experience.

[1356] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1357] Step 1:

[1358] The user launches the app and allows location information to be acquired. Specifically, the user operates the app's location information acquisition permission dialog. The input is the user's permission to acquire location information, and the output is the device obtaining permission to acquire location information.

[1359] Step 2:

[1360] The device uses its GPS function to obtain the user's current location. The input is data from the GPS sensor, and the output is the latitude and longitude of the current location. Specifically, the device receives signals from GPS satellites and calculates the latitude and longitude.

[1361] Step 3:

[1362] The device sends the user's current location information to the server. Example prompt: "Tell me where nearby anime is set." The input is the latitude and longitude of the current location, and the output is the location data sent to the server. Specifically, the device generates an HTTP request and sends it to the server.

[1363] Step 4:

[1364] The server filters the location information of digital content based on the user's current location. The input is the current location information submitted, and the output is a list of locations within 10 km. Specifically, the server executes a database query and extracts nearby locations using a distance calculation algorithm.

[1365] Step 5:

[1366] The server generates congestion status for the filtered locations. The input is the filtered location information, and the output is the location information with congestion status added. Specifically, it uses a random number generation algorithm to assign a congestion status of "low," "medium," or "high" to each location.

[1367] Step 6:

[1368] The server sends the filtered information and congestion status to the terminal. The input is the venue information with congestion status added, and the output is the data sent to the terminal. The specific operation is to send the data via an HTTP response.

[1369] Step 7:

[1370] The device plots the received location information and congestion status on a map. The input is data received from the server, and the output is the location icon and congestion status displayed on the map app. Specifically, it calls the map API and visually displays the information using icons and colors.

[1371] Step 8:

[1372] When a user arrives near a specific location, the device notifies them of related scene information. The input is the device's location information and the set notification range, and the output is the notified scene information. Specifically, the device calculates the distance between the user's location and the setting, and activates the notification function if the user is within the specified range.

[1373] Step 9:

[1374] The user selects the places they plan to visit, and the device generates an efficient travel plan and sightseeing route. The input is a list of places selected by the user, and the output is an optimized sightseeing route. Specifically, the device applies a route optimization algorithm to generate and display the travel plan.

[1375] (Application example 1)

[1376] 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."

[1377] Conventional tourist information systems for digital content and anime locations lacked the ability to provide real-time information based on the user's current location. They also lacked the ability to grasp congestion levels or suggest efficient sightseeing routes, making it difficult for users to enjoy comfortable and efficient sightseeing. This led to a decline in user satisfaction and hindered the development of the tourism industry.

[1378] 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.

[1379] In this invention, the server includes means for using a generative model to prepare information about the actual location that will be the setting for the digital content, means for filtering information about nearby tourist spots based on the user's current location information, and means for randomly simulating and providing congestion conditions, allowing the user to receive information about nearby tourist spots in real time, understand congestion conditions, and receive suggestions for efficient tourist routes.

[1380] A "generative model" is a general term for algorithms and methods that learn specific patterns and features from data and generate new ones.

[1381] "Electronic content" refers to information and media provided in digital form, especially location information such as anime and manga.

[1382] "Tourist destination information" refers to information about specific places that tourists want to visit, including their location, characteristics, history, and crowding status.

[1383] "Nearby" refers to a location within a certain distance from the user's current location.

[1384] "Crowding situation" is information that shows the density and concentration of people and vehicles in a specific location in real time.

[1385] "Filtering" refers to the process or method of selecting data based on specific conditions.

[1386] "Tourist route" refers to a route or sequence set up to efficiently visit multiple tourist spots.

[1387] "User's current location" refers to information about the latitude and longitude of the user's current physical location.

[1388] "Scene information" refers to explanatory and image information related to a specific scene in electronic content such as an anime or manga.

[1389] The present invention is a system that guides users to actual locations that are the setting for digital content based on their current location information, provides relevant scene information and congestion status, and also creates travel plans and suggests efficient sightseeing routes.

[1390] Server Roles

[1391] The server performs the following main roles:

[1392] 1. Location Management:

[1393] Using the generative model, we create a database of real-world locations where digital content is set, including location information (latitude and longitude) and related scene information.

[1394] 2. Filtering:

[1395] Receives the user's current location information and filters tourist spot information within a certain distance (e.g., 10 km) from that location.

[1396] 3. Congestion generation:

[1397] The system randomly simulates the congestion situation for each tourist spot and provides it to the user.

[1398] Device Role

[1399] The terminal performs the following main roles:

[1400] 1. Obtaining current location information:

[1401] Use the smartphone's GPS function to obtain the user's current location.

[1402] 2. Receiving and Displaying Information:

[1403] The system receives the organized location information and filtered tourist spot information from the server and plots and displays it on a map.

[1404] 3. Scene information notification:

[1405] When the user reaches a predetermined range, relevant scene information is notified.

[1406] 4. Create your travel plan:

[1407] Create a travel plan for the places you plan to visit and suggest efficient sightseeing routes.

[1408] Hardware and software used

[1409] Hardware:

[1410] Smartphone: A typical smartphone with GPS functionality and internet connectivity.

[1411] software:

[1412] Server-side software:

[1413] Database management systems (e.g. MySQL, PostgreSQL)

[1414] Generative models (e.g., TensorFlow, OpenAI GPT)

[1415] Terminal software:

[1416] GPS data acquisition function

[1417] Map display applications (e.g., Google Maps API)

[1418] Notifications (e.g. FCM, APNs)

[1419] Example of operation

[1420] For example, if a user is in Tokyo, when the application is launched, the latitude and longitude of the user's current location are first obtained and sent to the server. The server then searches a database of anime settings around Tokyo and filters locations within 10 km. For example, if a park in Shinjuku is nearby and the location is crowded, the congestion level is returned to the device as "high." The device plots the park on a map and displays it visually to the user. As the user approaches the location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests efficient sightseeing routes.

[1421] Prompt Sentence Examples

[1422] "Please explain about an app that guides users to nearby anime pilgrimage sites based on their current location."

[1423] "Write a prototype for an app called Anime Sacred Site Navigation. The app's function is to get the user's current location, plot nearby anime sacred sites, and display their congestion status."

[1424] As described above, the present invention is a system that provides users with real-time information about the locations where electronic content is set, enabling an efficient and smooth sightseeing experience.

[1425] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1426] Step 1:

[1427] Obtaining the user's current location

[1428] Description: When a user launches the application, the device (smartphone) uses the GPS function to obtain the user's current location information.

[1429] Input: The user's current latitude and longitude.

[1430] Output: Latitude and longitude of current location.

[1431] Specific operation: Uses the smartphone's GPS sensor to obtain location information and generate latitude and longitude data.

[1432] Step 2:

[1433] Sending location information to the server

[1434] Description: Sends the latitude and longitude information of the current location acquired by the device to the server.

[1435] Input: Latitude and longitude information of your current location.

[1436] Output: Send location information to server.

[1437] Specific operation: The device sends the acquired location information to the server as an API request using the HTTP protocol.

[1438] Step 3:

[1439] Location filtering

[1440] Description: The server filters tourist destination information within 10km from the database based on the received current location information.

[1441] Input: Latitude and longitude information of your current location.

[1442] Output: Nearby tourist attractions information.

[1443] Specific operation: The server executes a database query to extract tourist information within a certain range of the user's current location.

[1444] Step 4:

[1445] Generating congestion status

[1446] Description: The server randomly simulates the crowding of each tourist spot and adds it to each location.

[1447] Input: Nearby tourist attractions information.

[1448] Output: Tourist attraction information with crowd status added.

[1449] Specific operation: The server uses a random number generation algorithm to quantify the congestion level of each tourist spot and add it to the tourist spot information.

[1450] Step 5:

[1451] Sending tourist information to devices

[1452] Description: The server sends tourist spot information including congestion status to the terminal.

[1453] Input: Tourist attraction information with added crowd status.

[1454] Output: Send tourist information to the device.

[1455] Specific operation: The server converts the processed tourist attraction information into JSON format and returns it to the terminal as an HTTP response.

[1456] Step 6:

[1457] Plotting tourist destination information

[1458] Description: The tourist destination information received by the device is plotted on a map and presented visually to the user.

[1459] Input: Tourist attraction information with added crowd status.

[1460] Output: Tourist attractions plotted on a map.

[1461] Specific operation: The device uses Google Maps API or similar to display tourist spot information as markers on a map.

[1462] Step 7:

[1463] Scene information notification

[1464] Description: When the user approaches a specific tourist spot, the device notifies them of related scene information.

[1465] Input: User location and tourist destination information.

[1466] Output: Notification of relevant scene information.

[1467] Specific operation: The device compares the user's current location with the location of the tourist attraction and sends a push notification when the user enters within a specified range.

[1468] Step 8:

[1469] Travel plan creation and proposal

[1470] Description: The device creates and suggests efficient travel plans to the user based on the places the user plans to visit.

[1471] Input: The user's planned visit location.

[1472] Output: Efficient sightseeing route suggestions.

[1473] Specific operation: The device calculates a route using an algorithm that takes into account multiple planned destinations and optimizes distance and time, and presents a visual suggestion to the user.

[1474] The above are the specific processing steps of the present invention.

[1475] 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.

[1476] This system guides users to the actual locations where digital content is set, provides relevant scene information and congestion status based on the user's current location information, creates travel plans and suggests efficient sightseeing routes, and recognizes the user's emotions and optimizes the information provided and route suggestions based on those emotions.

[1477] Server Roles

[1478] The server uses the generative model to organize information about the actual locations where the digital content is set in the database. It receives the user's current location information (latitude and longitude), filters information about anime settings near that location, and receives the user's emotional information through an emotion engine to provide the user with optimized information.

[1479] Receive the user's current location information.

[1480] Filter locations within 10km of the database.

[1481] Randomly generate crowd conditions and add them to each location.

[1482] The emotional information of the user is received, and the location information to be presented is optimized based on the information.

[1483] The filtered anime setting information is returned to the terminal.

[1484] Device Role

[1485] The device receives information about the anime's setting from the server, plots it on a map, and presents it visually to the user. It also notifies the user of related scene information when they arrive within a specified range. It also has the function of creating a travel plan for planned visits and proposing efficient sightseeing routes. It recognizes the user's emotions and dynamically changes the information display and route suggestions based on that.

[1486] Get the user's current location.

[1487] Current location information is sent to the server and anime setting information is received.

[1488] The received information is displayed on a map.

[1489] When it reaches within a predetermined range, it notifies the relevant scene information.

[1490] Create a travel plan and suggest the best sightseeing route.

[1491] An emotion engine is used to recognize the user's emotions and dynamically change the display content and route based on those emotions.

[1492] User operations

[1493] Users can receive information about nearby anime locations by launching the app and allowing location information acquisition. They can then select locations to visit from the displayed list or map, and when they arrive at the location, they will receive real-time information about related anime scenes. The app can also suggest efficient travel plans for the locations they plan to visit, and provide feedback based on crowding and sentiment.

[1494] Specific examples

[1495] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of anime locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the server will return "Crowded: High" to the device. Furthermore, if the user's emotion is recognized as "tired," the server will suggest more relaxing places and shorter routes to the user.

[1496] The device plots Shinjuku parks on a map and visually displays them to the user. When the user approaches a location, the app notifies them of related scene information. If the user wants to visit places outside of Shinjuku, the app can suggest efficient sightseeing routes and include appropriate rest stops along the way based on their emotions.

[1497] In this way, the present invention is a system that provides users with the most optimal sightseeing experience by providing them with information about anime settings based on their current location information and further combining this with emotion recognition.

[1498] The processing flow will be explained below.

[1499] Step 1:

[1500] When the user launches the app and grants permission to acquire location information and recognize emotions, the device acquires the user's current location using navigator.geolocation.getCurrentPosition and recognizes the user's emotions using sensors such as the camera and microphone.

[1501] Step 2:

[1502] The device sends the acquired latitude and longitude data and emotion data to the server using an HTTP GET request, with the location information and emotion information passed to the server as query parameters.

[1503] Step 3:

[1504] The server receives the request, retrieves all the locations in the anime from its database, and then determines the user's current location based on the latitude and longitude provided.

[1505] Step 4:

[1506] The server uses geopy.distance to calculate the distance between the user's current location and each anime setting. It filters out locations within 10 km and randomly simulates congestion at each location before adding it to the list. This organizes the location information.

[1507] Step 5:

[1508] The server analyzes the user's emotional information and optimizes the content and order of the location information based on that emotional state. For example, if the server detects that the user is "tired," it will prioritize suggesting less crowded or relaxing locations.

[1509] Step 6:

[1510] The server generates a filtered and optimized list of anime locations in JSON format and returns it to the device, including special suggestions based on each location's name, description, distance, crowding status, and emotion.

[1511] Step 7:

[1512] The device analyzes the information about the anime's settings received from the server and plots it on a map. It also displays a list of the settings to the user. For example, it can visually display the information by placing pins on a map.

[1513] Step 8:

[1514] The device monitors the distance between the user's current location and each setting in real time. When the user reaches a predetermined distance (for example, within 1 km), scene information related to that setting is notified to the device. This allows the user to enjoy anime scene information in real time.

[1515] Step 9:

[1516] The device automatically creates a travel plan based on the planned destinations and presents it to the user. This suggests an efficient sightseeing route, allowing the user to smoothly visit multiple locations. Furthermore, the travel plan is dynamically changed based on the user's emotional information. For example, if the user is "having fun," a new location may be added to the sightseeing route.

[1517] Step 10:

[1518] The user travels based on recommended travel plans and sightseeing routes. The device notifies the user of congestion status and emotion information in real time, providing reference information for the user when choosing destinations. The device also recommends appropriate rest areas along the way based on the user's emotions.

[1519] In this way, this system provides information about anime settings based on the user's current location and emotional information, providing an efficient and immersive sightseeing experience. Furthermore, by optimizing information and routes according to the user's emotions, it is possible to provide a more fulfilling experience.

[1520] Example 2

[1521] 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."

[1522] Conventional tourist information systems lack guidance based on the user's current location information and provide limited information on the locations where digital content is set. Furthermore, they do not provide information or suggest routes that take into account congestion or the user's emotions, making it difficult to provide an optimal tourist experience for each individual user. Therefore, there is a need for information to avoid congestion at the site and for the creation of travel plans that suit the user's emotions.

[1523] 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.

[1524] In this invention, the server includes means for preparing information on actual locations that serve as the setting for the digital content using a generative AI model, means for receiving the prepared location information and plotting it on a map using a terminal, means for notifying the user of related scene information when the user arrives within a predetermined range, means for acquiring the user's current location information and sending it to the server, means for the server to filter locations within the predetermined range from a database, means for the server to receive the user's emotional information using an emotion engine and generate optimized information, and means for the terminal to recognize the user's emotions and dynamically change the information display and route suggestions based on the emotions. This makes it possible to provide optimal tourist routes and information according to the user's current location and emotional state, as well as information on the setting for the digital content.

[1525] A "generative AI model" is a model that uses artificial intelligence techniques to generate optimal results for a specific task.

[1526] "Electronic content" refers to information and data that is stored, transmitted, and played in digital form, including, for example, animation and games.

[1527] "Real-life locations" refers to real-life locations that are depicted as the backdrop for scenes or stories in the digital content.

[1528] A "terminal" is a device used by a user for operation, and includes a smartphone, tablet, etc.

[1529] A "server" is a computer system that receives and processes requests from users.

[1530] "Processing" refers to the process of organizing and structuring data to make it usable.

[1531] "Means for receiving and plotting on a map" refers to the process of receiving the transmitted information at the terminal and displaying the information in a map application.

[1532] The "means for notifying scene information" refers to a mechanism for notifying the user of content information related to a specific location when the user reaches that location.

[1533] "Current location information" refers to latitude and longitude data that indicates the user's location.

[1534] "Means for filtering locations within a predetermined range from a database" refers to a process that searches for information in a database based on the user's current location and extracts only results within a pre-defined range.

[1535] An "emotion engine" is a system that identifies a user's emotional state and provides appropriate answers or responses based on that.

[1536] "Means for dynamically changing information display and route suggestions" refers to a mechanism that instantly changes the information presented and the recommended route according to the user's real-time information and emotions.

[1537] This system guides users to actual locations that are the setting for digital content based on their current location information, and provides related scene information and congestion status. It also creates travel plans and suggests efficient sightseeing routes, and can recognize users' emotions and optimize the information provided and route suggestions based on those emotions.

[1538] Server Roles

[1539] The server uses a generative AI model to organize information about the actual locations in the database where digital content is set. It also receives the user's current location information (latitude and longitude) and filters information about locations near that location. The server also receives the user's emotional information using an emotion engine and provides optimized information to the user. The specific process is as follows:

[1540] Receive the user's current location information.

[1541] Filter locations within 10km of the database.

[1542] Randomly generate crowd conditions and add them to each location.

[1543] The emotional information of the user is received, and the location information to be presented is optimized based on the information.

[1544] The filtered location information is returned to the terminal.

[1545] Device Role

[1546] The device plots the location information received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when the user arrives within a specified range. It also has the function of creating a travel plan for planned visits and proposing efficient sightseeing routes. The device uses an emotion engine to recognize the user's emotions and dynamically changes the information display and route suggestions based on those emotions. The specific process is as follows:

[1547] Get the user's current location.

[1548] Current location information is sent to the server, and location information is received.

[1549] The received information is displayed on a map.

[1550] When it reaches within a predetermined range, it notifies the relevant scene information.

[1551] Create a travel plan and suggest the best sightseeing route.

[1552] An emotion engine is used to recognize the user's emotions and dynamically change the display content and route based on those emotions.

[1553] User operations

[1554] Users can launch the app and allow location information acquisition to receive information about nearby locations. They can select locations to visit from the displayed list or map, and when they arrive at the location, they receive related scene information in real time. The app can also suggest efficient travel plans for the locations they plan to visit and provide feedback based on crowd levels and emotions.

[1555] Specific examples

[1556] When a tourist in Tokyo launches the app, the latitude and longitude of their current location are first obtained and sent to the server. The server then searches a database of locations around Tokyo and filters locations within 10km. For example, if a famous park in Shinjuku is nearby and the location is crowded, the app will return "Crowded: high" to the device.

[1557] Furthermore, if the user's emotion is recognized as "tired," the server suggests more relaxing places and shorter routes to the user. The device plots Shinjuku parks on a map and visually displays them to the user. When the user approaches a location, related scene information is notified. If the user wants to visit places other than Shinjuku, the app suggests an efficient sightseeing route, including appropriate rest stops along the way based on the user's emotion.

[1558] Prompt Sentence Examples

[1559] An example of an input prompt when a user wants to get a specific sightseeing plan is, "Please tell me some recommended locations around Tokyo. I'm currently in Shinjuku. Also, I'm a little tired, so please suggest some places where I can relax." This makes it possible to provide a sightseeing experience optimized for the user's situation and emotions.

[1560] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1561] Step 1:

[1562] The user launches the app

[1563] A user taps an app on their smartphone to launch it. When the app is launched for the first time, it asks for permission to obtain location information. The inputs are user interaction and permission to obtain location information, and the outputs are confirmation that the app has been launched and the setting for permission to obtain location information.

[1564] Step 2:

[1565] The device obtains location information

[1566] The device uses the smartphone's GPS sensor to obtain the user's current location information (latitude and longitude). For example, if the user is near Shinjuku Station, the latitude will be 35.6895 degrees and the longitude will be 139.6917 degrees. The input required is data from the GPS sensor, and the output is the latitude and longitude data of the current location.

[1567] Step 3:

[1568] The device sends its current location information to the server.

[1569] The device sends the acquired latitude and longitude data to the server in real time. The data is sent in a standard format such as JSON. The input requires the latitude and longitude data of the current location, and the output is the current location data sent to the server.

[1570] Step 4:

[1571] The server filters locations within 10km of the database

[1572] The server executes a database query to filter location information within 10km of the user's current location. It uses SQL SELECT statements to extract records that match the criteria. The input requires the received latitude and longitude data and the database, and the output is the filtered location information within 10km.

[1573] Step 5:

[1574] The server receives the user's emotional information using an emotion engine and generates optimized information.

[1575] The server receives the user's emotional information through the emotion recognition API and generates optimized location information based on that information. For example, if the user is recognized as "tired," the information is saved as internal data and reflected in the filtering results. The input requires the user's emotional information and filtered location information, and the output is optimized location information.

[1576] Step 6:

[1577] The server sends optimized location information to the device.

[1578] The server returns the optimized location information to the device. The information is in JSON format and includes latitude, longitude, congestion status, recommended comments, etc. The input requires the optimized location information, and the output is the optimized information sent to the device.

[1579] Step 7:

[1580] The device plots the information on a map

[1581] The device plots the received location information on a map application. The user can visually check the location and information of each location on the map. The received location information is required as input, and the output is the information plotted on the map.

[1582] Step 8:

[1583] The device detects the user's arrival and notifies them of the scene information.

[1584] The device notifies the user of related scene information when the user arrives within a specified range of the setting. For example, when the user arrives at Shinjuku Park, a description and image of a specific scene from the anime are displayed. GPS data and scene information are required as input, and the output is a scene information notification to the user.

[1585] Step 9:

[1586] The device creates a travel plan for the places you plan to visit.

[1587] The device generates an efficient travel plan based on the user's selected locations. For example, it proposes a route that goes around Takadanobaba, Shinjuku, and Ikebukuro. The input requires the user's selected locations, and the output is a travel plan.

[1588] Step 10:

[1589] The device suggests the best sightseeing route for the user

[1590] The device then proposes an optimal sightseeing route to the user based on the generated travel plan. The route is presented with a map, and the points to be visited are marked. The travel plan data is required as input, and the output is the proposed sightseeing route to the user.

[1591] Step 11:

[1592] The device dynamically updates the information

[1593] The device dynamically updates the display and route based on the user's real-time location and emotions, suggesting additional rest stops and new routes. The input requires current location information and emotion information, and the output is the updated display and route.

[1594] (Application example 2)

[1595] 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."

[1596] Conventional information provision systems related to digital content have difficulty providing optimal information that takes into account the user's current location and emotions. Furthermore, functions for providing detailed information about store congestion and in-store product information are limited, leaving a lack of means to maximize the user experience. Furthermore, it has been difficult to provide efficient guidance and information in physical stores. For these reasons, a system that can provide flexible information according to the user's situation and optimal in-store navigation is needed.

[1597] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1598] In this invention, the server includes means for using a generative model to prepare information about the actual location where the digital content is set, means for providing guidance to nearby stores based on the user's current location information, and means for providing information about the congestion status and products in the stores. This makes it possible to provide optimal store guidance, congestion information, and product information based on the user's current location information and emotions.

[1599] A "generative model" refers to an algorithm or machine learning model that generates new information based on given data. Examples include natural language generation and image generation.

[1600] "Electronic content" is a general term for information and media content provided in digital form, including, for example, e-books, videos, music, and web pages.

[1601] A "real-world location" refers to a specific geographic location in the real world where electronic content is set and that a user can visit.

[1602] "Current location information" refers to data that indicates the user's location, and typically refers to latitude and longitude information obtained using location measurement technology such as GPS.

[1603] "Plot on a map" means visually displaying the user's location or a particular location on a geographic map.

[1604] "Scene information" refers to information relating to a particular scene or situation in electronic content, and includes, for example, a particular scene in an anime or a particular episode in a story.

[1605] "Crowding status" is information indicating the degree of crowding of people in a particular location, and is usually expressed as levels such as "high," "medium," and "low."

[1606] "Product information" refers to detailed information about products sold in physical stores, including price, features, and stock status.

[1607] "Emotion recognition" refers to technology that grasps a user's emotional state from their facial expressions, voice, etc., and categorizes emotions such as "joy," "surprise," "sadness," and "fatigue."

[1608] "Navigation" means providing directions or guidance information to help a user reach a particular destination.

[1609] "Event information" refers to information about events and campaigns held at physical stores or specific facilities, including sales, tasting sessions, autograph sessions, etc.

[1610] This system guides users to nearby stores based on their current location and provides information on store congestion and product information. It also recognizes the user's emotions and optimizes route guidance and suggests recommended products based on those emotions. It also has the ability to create a travel plan for planned visits, suggest efficient sightseeing routes, and notify users of events being held in stores.

[1611] Server Roles

[1612] The server uses the generative model to organize information about the actual locations in the database where the digital content is set. To do this, it performs the following processes: First, it receives the user's current location information (latitude and longitude) and filters out store information near that location. It also randomly generates congestion information and adds it to each location. It then receives the user's emotional information using an emotion engine and optimizes store guides and product suggestions based on that information. Finally, it returns the filtered store information to the terminal. This allows the user to receive optimized store information in real time.

[1613] Device Role

[1614] The device plots the store information received from the server on a map and presents it visually to the user. It also notifies the user of related scene information when the user arrives within a specified range. It also has the function of creating a travel plan for planned visits and suggesting efficient sightseeing routes. The device recognizes the user's emotions and dynamically changes the information display and route suggestions based on that. For example, if it recognizes that the user is tired, it will prioritize displaying routes to stores that are less crowded.

[1615] User operations

[1616] Users can receive information about nearby stores by launching the smartphone app and allowing location information acquisition. They can select the store they want to visit from the displayed list or map, and when they actually arrive at the location, they can receive real-time information about the store's products and events. The app can also suggest efficient travel plans for the places they plan to visit and provide feedback based on crowding levels and emotions.

[1617] Specific examples

[1618] For example, suppose the user is in Shinjuku, Tokyo. If the server recognizes that the user is tired, it will prioritize providing information on less crowded stores. Specifically, if the user's current location is "latitude 35.6895, longitude 139.6917" and the user's emotion is recognized as "tired," the server will filter store information around Shinjuku and return information on "ABC Store (low crowding)" to the terminal.

[1619] Example prompts to be input to the generative AI model

[1620] plaintext

[1621] Current location: 35.6895, 139.6917

[1622] Emotion: Tired

[1623] In this way, the system combines emotion recognition and location information to provide optimal information to maximize the user experience.

[1624] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1625] Step 1:

[1626] The user launches the smartphone app and allows location information to be obtained.

[1627] Input: Permission to obtain location information from the user, GPS data from the smartphone

[1628] Output: User's current location (latitude and longitude)

[1629] How it works: Uses the smartphone's GPS module to obtain current location information and its latitude and longitude.

[1630] Step 2:

[1631] The terminal transmits the acquired current location information to the server.

[1632] Input: User's current location information (latitude and longitude)

[1633] Output: Location information sent to the server

[1634] What it does: Sends your current location to the server as an HTTP request.

[1635] Step 3:

[1636] The server filters store information within 10 km of the database based on the received current location information.

[1637] Input: Current location information (latitude and longitude), store database

[1638] Output: A filtered list of stores

[1639] What it does: Uses a database query to find stores within 10km of the current location and lists their information.

[1640] Step 4:

[1641] The server randomly generates congestion status for the filtered store information and adds it to each store information.

[1642] Input: A filtered list of store locations

[1643] Output: List of store information with added crowd status

[1644] How it works: A random algorithm is used to generate three levels of congestion status: high, medium, and low, and this is added to the store information.

[1645] Step 5:

[1646] The server receives the user's emotional information using an emotion engine and optimizes store guides and product suggestions based on that information.

[1647] Input: A list of store information with user emotion information and crowding status added

[1648] Output: A list of store information optimized based on user sentiment

[1649] How it works: The emotion engine analyzes the user's emotional data and generates optimal store guide information based on that data, taking into account the level of congestion and the products offered.

[1650] Step 6:

[1651] The server returns the optimized store information to the terminal.

[1652] Input: List of optimized store locations

[1653] Output: Optimized store information sent back to the device

[1654] Operation: Sends optimized store information to the terminal as an HTTP response.

[1655] Step 7:

[1656] The terminal plots the received store information on a map and presents it visually to the user.

[1657] Input: Optimized store information

[1658] Output: Store information displayed on the map

[1659] How it works: Using the map API, the received store information is plotted on the corresponding geographic coordinates and displayed visually.

[1660] Step 8:

[1661] When the user arrives at the store, the terminal notifies the user of related scene information and detailed information.

[1662] Input: User's current location information, optimized store information

[1663] Output: Notified related scene information and detailed information

[1664] How it works: Using geofencing technology, the app provides scene information and detailed information via pop-up notifications when a user approaches a specific store.

[1665] Step 9:

[1666] The device creates a travel plan for the places you plan to visit and suggests efficient sightseeing routes.

[1667] Input: User's planned visit information, optimized store information, event information

[1668] Output: Suggested itinerary and sightseeing route information

[1669] How it works: It uses a travel plan generation algorithm to create a list of places to visit and calculate and present the optimal route.

[1670] Example prompts to be input to the generative AI model

[1671] plaintext

[1672] Current location: 35.6895, 139.6917

[1673] Emotion: Tired

[1674] 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.

[1675] 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.

[1676] 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.

[1677] 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.

[1678] FIG. 9 illustrates 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 behaviors 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.

[1679] 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.

[1680] 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).

[1681] 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.

[1682] 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."

[1683] 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.

[1684] 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).

[1685] 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.

[1686] 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.

[1687] 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.

[1688] 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.

[1689] 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.

[1690] 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.

[1691] 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.

[1692] 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.

[1693] 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.

[1694] 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.

[1695] The following is further disclosed regarding the above embodiment.

[1696] (Claim 1)

[1697] a means for using a generative model to prepare information about the real-world location in which the digital content is set;

[1698] A means for receiving information on the prepared location by a terminal and plotting it on a map;

[1699] means for notifying the user of related scene information when the user reaches a predetermined range;

[1700] A system including:

[1701] (Claim 2)

[1702] 2. The system according to claim 1, further comprising means for randomly simulating a congestion situation and providing it to said terminal.

[1703] (Claim 3)

[1704] 2. The system according to claim 1, further comprising means for creating a travel plan for planned visits and proposing an efficient sightseeing route.

[1705] "Example 1"

[1706] (Claim 1)

[1707] a means for using a generative model to prepare information about the real-world location in which the digital content is set;

[1708] A means for receiving information on the prepared location by a terminal and plotting it on a map;

[1709] means for notifying the user of related scene information when the user reaches a predetermined range;

[1710] A means for acquiring user's current location information and transmitting it together with the prepared location information to a server;

[1711] a means for filtering information on the locations of the electronic content based on the user's current location information, generating a congestion status and sending it back to the terminal by the server;

[1712] A system including:

[1713] (Claim 2)

[1714] 2. The system according to claim 1, further comprising means for randomly simulating a congestion situation and providing it to said terminal.

[1715] (Claim 3)

[1716] 2. The system according to claim 1, further comprising means for creating a travel plan for planned visits and proposing an efficient sightseeing route.

[1717] "Application Example 1"

[1718] (Claim 1)

[1719] a means for using a generative model to prepare information about the real-world location in which the digital content is set;

[1720] A means for receiving information on the prepared location by a terminal and plotting it on a map;

[1721] means for notifying the user of related scene information when the user reaches a predetermined range;

[1722] A means for filtering nearby tourist spot information based on the user's current location information;

[1723] means for presenting related scene information;

[1724] A means of proposing efficient tourist routes,

[1725] A system including:

[1726] (Claim 2)

[1727] 2. The system according to claim 1, further comprising means for randomly simulating a congestion situation and providing it to said terminal.

[1728] (Claim 3)

[1729] 2. The system according to claim 1, further comprising means for creating a travel plan for planned visits and proposing an efficient sightseeing route.

[1730] "Example 2: Combining Emotion Engines"

[1731] (Claim 1)

[1732] A means for using a generative AI model to prepare information about the real-world locations where digital content is set; and

[1733] A means for receiving information on the prepared location by a terminal and plotting it on a map;

[1734] means for notifying the user of related scene information when the user reaches a predetermined range;

[1735] means for acquiring user's current location information and transmitting it to a server;

[1736] means for the server to filter locations within a predetermined range from the database;

[1737] a means for the server to receive the user's emotion information using an emotion engine and generate optimized information;

[1738] A means for the device to recognize the user's emotions and dynamically change the information display and route suggestions based on the emotions;

[1739] A system including:

[1740] (Claim 2)

[1741] The device further includes means for randomly simulating a congestion situation and providing the simulation result to the terminal.

[1742] 10. The system of claim 1.

[1743] (Claim 3)

[1744] It also includes a means to create a travel plan for the planned visit and suggest efficient sightseeing routes.

[1745] 10. The system of claim 1.

[1746] "Application example 2 when combining emotion engines"

[1747] (Claim 1)

[1748] a means for using a generative model to prepare information about the real-world location in which the digital content is set;

[1749] A means for receiving information on the prepared location by a terminal and plotting it on a map;

[1750] means for notifying the user of related scene information when the user reaches a predetermined range;

[1751] A means for providing information about nearby stores based on current location information of the user;

[1752] A means of providing in-store congestion status and product information,

[1753] A means to recognize user emotions and optimize in-store product recommendations and route guidance based on those emotions,

[1754] A system including:

[1755] (Claim 2)

[1756] 2. The system according to claim 1, further comprising means for randomly simulating a congestion situation and providing it to said terminal.

[1757] (Claim 3)

[1758] 2. The system according to claim 1, further comprising means for creating a travel plan for planned visits and proposing efficient sightseeing routes, and means for notifying the user of information about events being held in stores. [Explanation of symbols]

[1759] 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 using a generative model to prepare information about the real-world location in which the digital content is set; A means for receiving information on the prepared location by a terminal and plotting it on a map; means for notifying the user of related scene information when the user reaches a predetermined range; A system including:

2. 2. The system according to claim 1, further comprising means for randomly simulating a congestion situation and providing it to said terminal.

3. 2. The system according to claim 1, further comprising means for creating a travel plan for planned visits and proposing an efficient sightseeing route.

Images