system

Abstract

We provide the system. [Solution] A means for a mobile terminal to acquire location information and transmit data including said location information and language setting information, A server means that retrieves multilingual information of relevant locations from a database based on the received data, A means for processing acquired multilingual information and providing real-time guide information to mobile terminals, A server means that receives a question in natural language from a mobile terminal, generates a response to the question using generative AI, and transmits the response to the mobile terminal. A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the tourism industry, due to the lack of multilingual support and shortage of tourism guide personnel, there is a problem that it is difficult for tourists to fully understand the culture and history of the regions they visit. Furthermore, since the means of conveying the charm of a region from a remote location are limited, there is a problem that information cannot be effectively delivered to local taxpayers and people interested in the region.

Means for Solving the Problems

[0005] This invention provides a system in which a server provides relevant tourist information in multiple languages ​​in real time based on the location information of a mobile terminal. This allows tourists to learn more about local culture and history without experiencing language barriers. Furthermore, it enables a personalized tourist experience by providing specific information through generated AI in response to user questions. In addition, it is possible to provide a remote tourist experience to users in remote locations and effectively communicate the attractions of the region.

[0006] A "mobile terminal" refers to a device that is portable by the user and has communication capabilities, such as a mobile phone or tablet.

[0007] "Location information" refers to data obtained via GPS or Wi-Fi that indicates the geographical location of a device.

[0008] "Language setting information" refers to information indicating the interface language selected by the user on the device.

[0009] A "server" refers to a computer system that processes and stores data and provides information to other devices via a network.

[0010] A "database" refers to a system in which a collection of information is systematically stored and can be easily searched and retrieved.

[0011] "Multilingual information" refers to information that is available in multiple languages.

[0012] "Real-time guide information" refers to descriptions and guidance information about tourist destinations that users can obtain instantly on the spot.

[0013] "Generative AI" refers to artificial intelligence technology that analyzes input data and generates responses in natural language.

[0014] A "natural language question" refers to a question asked using the language format that humans normally use in conversation.

[0015] "Image display means" refers to a device or function for visually displaying content.

[0016] "Remote tourism experience" refers to a technology that allows users to experience the charm of tourist destinations from a remote location without visiting the site.

[0017] "Content" refers to the general term for information and media provided to users.

[0018] "Streaming distribution" refers to a method of transferring content as data in real time and providing it in a form that allows users to view or use it immediately.

Brief Description of Drawings

[0019] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0020] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0023] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0024] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0025] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0027] [First Embodiment]

[0028] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0029] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0032] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0035] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0039] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0040] One embodiment of the present invention relates to a system that provides real-time, multilingual tourist information to users visiting tourist destinations using mobile terminals. This system mainly consists of mobile terminals, a server, and a database.

[0041] The user launches an application installed on their mobile device. The device first obtains its current location information via GPS and simultaneously collects the device's language setting information. This information is sent to a server, which retrieves relevant tourist destination information from its database in multiple languages ​​based on the received information.

[0042] The server processes the acquired tourist destination information in real time and provides it to the device as guide information. This allows users to receive multilingual guidance about the history and culture of tourist destinations through their devices.

[0043] Furthermore, when a user enters a specific question about a tourist destination via their mobile device, that question is sent to the server. The server uses a generative AI to analyze the question and generate a response. This response is sent back to the user's device and displayed in a chat format. This allows users to obtain detailed information tailored to their individual interests.

[0044] Furthermore, even when users are in remote locations, the system provides a remote tourism experience. The server generates and streams content that conveys the appeal of tourist destinations via video display devices. In this way, users can experience the charm of tourist destinations without actually visiting them.

[0045] As a concrete example, consider a scenario where a user visits a historical site with a mobile device. Upon launching the app, the server provides real-time, multilingual guidance to the user, detailing the site's history and points of interest. Furthermore, if the user desires additional information about a specific building or ruin, they can directly input questions and obtain more in-depth information on the spot.

[0046] This system allows tourists to obtain a wealth of information even within a limited time, enabling them to gain a deeper understanding of the essence of their destination.

[0047] The following describes the processing flow.

[0048] Step 1:

[0049] The user launches the application on their mobile device. The device obtains its current location using its built-in GPS and also checks the device's language settings.

[0050] Step 2:

[0051] The device sends the acquired location information and language setting information to the server. The server receives this information and retrieves tourist destination information related to the corresponding location from its database.

[0052] Step 3:

[0053] The server organizes multilingual tourist information according to the user's language settings and sends it to the terminal in real time. The terminal presents the received information to the user in either audio or text format.

[0054] Step 4:

[0055] If a user wants more detailed information about a tourist destination, they enter their question through the chatbot interface on their device. The device then sends the entered question to the server.

[0056] Step 5:

[0057] The server passes the received question to the generating AI, which analyzes the question. Based on the analysis, the generating AI generates an appropriate response and returns it to the server.

[0058] Step 6:

[0059] The server sends back a response generated by the AI ​​to the terminal. The terminal displays the response to the user and provides it in audio format if necessary.

[0060] Step 7:

[0061] If a user requests a remote sightseeing experience, the device sends this request to the server. The server prepares VR experiences and video content of the tourist destination and streams them to the device.

[0062] Step 8:

[0063] The device displays received VR experiences or video content, allowing users to remotely experience the charm of a region.

[0064] (Example 1)

[0065] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0066] In recent years, there has been a growing demand for real-time access to detailed, multilingual information when visiting tourist destinations, as well as the ability to receive information tailored to individual interests. Furthermore, there is a desire to enjoy the allure of tourist destinations through virtual experiences without actually visiting the location. However, conventional systems have not adequately met these needs.

[0067] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0068] In this invention, the server includes means for a mobile terminal to acquire location information and transmit data including said location information and language setting information; information processing means for acquiring multilingual information of a relevant location from an information storage device based on the received data; and means for processing the acquired multilingual information and providing guidance information to the mobile terminal in real time. As a result, users can receive real-time information including multilingual support and individual question answering.

[0069] A "mobile terminal" refers to a portable device that can communicate data while moving between locations, and is an electronic device equipped with GPS and communication functions.

[0070] "Location information" refers to data that indicates the geographical location of a mobile device, and is expressed as numerical values ​​of latitude and longitude.

[0071] "Language setting information" is data that indicates the language set on the mobile device, and is used by the system to determine in which language information will be provided.

[0072] "Data transmission means" refers to a function or device for transmitting data from a mobile terminal to a server, and plays the role of transferring information through a communication protocol.

[0073] An "information storage device" is a device that holds multilingual information and other data, and functions as a database system.

[0074] "Information processing device means" refers to a function or device on a server that analyzes and processes data and searches for, acquires, and generates necessary information.

[0075] "Guidance information" refers to data that includes detailed information about the history, culture, and other aspects of tourist destinations that users are interested in, and is used as an explanation provided to the user.

[0076] "Generative AI" refers to a technology that uses artificial intelligence models to analyze a user's natural language questions and generate appropriate answers.

[0077] A "response" is an answer automatically generated by a generation AI in response to a user's question, and is presented to the user.

[0078] A "video display device" refers to a device for displaying visual content, providing a means for users to visually receive video information.

[0079] "Video distribution" refers to a method of transmitting videos or video data to users, enabling them to view them in real time or on demand.

[0080] This invention relates to a system that provides real-time, multilingual tourist information to users visiting tourist destinations via mobile terminals. This system mainly consists of mobile terminals, a server, and an information storage device.

[0081] The user launches an application installed on their mobile device, and the device uses its built-in GPS function to obtain its current location. Simultaneously, the device's language settings are also collected. This information is transmitted from the mobile device to the server. A secure protocol is used for communication, such as HTTPS.

[0082] The server uses the received location and language setting information to retrieve multilingual information about the relevant tourist destination from the information storage device. A database management system is used for this information processing, and information is retrieved via SQL queries. The server processes the retrieved information and immediately transmits guidance information to the mobile terminal. This processing includes data format conversion and template processing for multilingual support.

[0083] Furthermore, when a user asks a question about a tourist destination using natural language via their device, the question is sent to the server. The server uses a generative AI model and natural language processing techniques such as GPT to analyze the question and generate an appropriate response. The generated response is sent to the mobile device, which displays it in a visual format. This allows users to receive information tailored to their individual interests in real time.

[0084] As a concrete example, consider a scenario where a user visits a historical site. When the user enters a prompt such as "Tell me about the history of this place," the server generates relevant historical information and provides detailed, multilingual guidance.

[0085] Furthermore, the server generates and streams visual information to provide remote users with a virtual sightseeing experience via a video display device. In this process, for example, by using a cloud-based video streaming service, it becomes possible to experience the impression of a tourist destination without actually visiting the location.

[0086] In this way, users can easily obtain multilingual tourist information through their mobile devices and deepen their detailed understanding of tourist destinations.

[0087] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0088] Step 1:

[0089] The user launches an application on a mobile device. The device uses its built-in GPS function to obtain its current location. It also obtains the device's language setting information. The input consists of the user's location and language setting from the device; based on this, the device sends this data to the server. The output is a dataset containing location information and language settings.

[0090] Step 2:

[0091] The server retrieves relevant multilingual tourist information from an information storage device based on location and language setting information received from the terminal. The input is a dataset received from the terminal, and the server uses a database management system to execute SQL queries and extract relevant information. The output is multilingual information about the selected tourist destination.

[0092] Step 3:

[0093] The server processes acquired tourist destination information in real time. It receives multilingual tourist information as input, formats it according to the user's language settings, and prepares it in an appropriate format (e.g., HTML or JSON). The output is formatted multilingual information. The server then transmits this information to mobile devices.

[0094] Step 4:

[0095] The user inputs questions about tourist destinations in natural language via a terminal. The input is the user's question in natural language. The terminal sends this question to the server. The output is the question data sent to the server.

[0096] Step 5:

[0097] The server analyzes received questions using a generative AI model. The input is a natural language question received from the user. The generative AI model understands the question and generates an appropriate response based on the relevant information. The output is the generated response data.

[0098] Step 6:

[0099] The server sends response data to the mobile terminal. The terminal receives this response and displays it on the screen in a chat format. The input is the response data obtained from the generative AI model, and the output is the visual information displayed to the user.

[0100] Step 7:

[0101] The server generates content to provide a virtual sightseeing experience to remote users via a video display device. The input includes visual information about the tourist destination, which is used to generate video data suitable for streaming. The output is streamable video data. The server streams this video to the user's terminal, allowing the user to virtually experience the tourist destination.

[0102] (Application Example 1)

[0103] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0104] In the modern tourism sector, providing real-time, multilingual tourism information is crucial. However, existing systems suffer from shortcomings in multilingual support and low-quality remote tourism experiences. Furthermore, few systems can suggest in real time which information is most useful to a user based on their location and interests.

[0105] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0106] In this invention, the server includes means for determining the user's location based on location data and presenting the user with optimal route information; means for generating tourist destination information as video data in a remote environment and transmitting the data to the user as video; and means for receiving inquiries in natural language, generating responses to those inquiries using a generation AI, and transmitting the responses to a mobile device. As a result, users can obtain a fulfilling tourist experience without actually visiting the locations and can receive optimal information in real time while traveling.

[0107] A "mobile device" is a type of electronic device that a user can carry and use, and is a terminal for processing location data and other information.

[0108] "Location data" refers to information that indicates the current geographical location of a mobile device, and is acquired using technologies such as GPS.

[0109] "Language setting data" refers to information about the display language and audio language that the user has pre-selected on the mobile device.

[0110] An "information recording medium" is a database that stores digital data and manages it so that it can be searched and retrieved as needed.

[0111] "Computing device means" refers to a central processing unit or server for processing information, and is responsible for acquiring and processing multilingual data.

[0112] "Real-time navigation data" refers to location-specific navigation information, including multilingual information, that is provided to users instantly.

[0113] "Natural language" refers to the forms of language that humans use in everyday conversation and writing, and that are expressed in text or audio.

[0114] "Generative AI" is an artificial intelligence algorithm that aims to analyze input data and automatically generate natural-sounding responses.

[0115] "Video data" refers to digital signals, including videos and still images, that are used as visual information.

[0116] "Video transmission" is the process of transferring video data to a receiving device such as a mobile device.

[0117] An "inquiry" is a question or request that a user sends in natural language seeking specific information.

[0118] The system for implementing this invention consists of a mobile device such as a smartphone, a server for data processing, and a database for providing information. First, the mobile device acquires location data using GPS and transmits it to the server along with the user's language setting data. Based on this data, the server processes the acquisition of the corresponding multilingual data from the information recording medium.

[0119] The server processes this data using Python and generates real-time guidance data. This allows for immediate tourist information to be provided to mobile devices. Furthermore, to respond to natural language inquiries from users, the server generates responses using generative AI models (e.g., OpenAI®'s GPT-4®) and sends them to the mobile devices.

[0120] For the remote tourism experience, a server generates video data of the tourist destination and transmits the video in real time using Apache® Kafka. This allows users to enjoy tourist destinations even when they are not physically present.

[0121] For example, if a user asks a question about the Colosseum in Rome, the smartphone will pinpoint their location and provide optimal route information according to their language settings. Also, if a user asks, "Tell me about the history of the Colosseum," the AI ​​will provide detailed historical information as a response.

[0122] An example of a prompt to the generating AI would be: "The user wants to learn about the history of the Colosseum. Please explain in detail the important facts and historical background of the Colosseum." Based on this sentence, the generating AI analyzes the information and generates an appropriate response.

[0123] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0124] Step 1:

[0125] The device acquires location data using a GPS sensor and sends this data, along with the user's language settings, to the server. The input is location data and language settings data, and the output is the process of sending these to the server.

[0126] Step 2:

[0127] The server accesses the information recording medium based on the received location data and language setting data, and retrieves the corresponding multilingual information. The input is location data and language setting data, and the output is the retrieval of multilingual information.

[0128] Step 3:

[0129] The server processes the acquired multilingual information into real-time guidance data and transmits it to the terminal. The input is multilingual information, and the output is processed real-time guidance data.

[0130] Step 4:

[0131] The user inputs a question into the terminal using natural language. The input is a question in natural language, and the output is sent to the server.

[0132] Step 5:

[0133] The server analyzes the received question and generates a response using a generative AI model. The input is a natural language question, and the output is the generated response.

[0134] Step 6:

[0135] The generated response is sent from the server to the terminal and displayed to the user. The input is the generated response, and the output is the display on the terminal.

[0136] Step 7:

[0137] The server generates video data for the remote sightseeing experience and transmits the video to the terminal in real time using Apache Kafka. The input is tourist destination information, and the output is the transmitted video data in real time.

[0138] Step 8:

[0139] Users can view detailed information about tourist destinations via their devices, based on responses provided by a generated AI model. The input consists of real-time guidance data and generated responses, while the output is tourist information provided to the user.

[0140] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0141] One embodiment of the present invention provides a system that offers real-time, multilingual tourist information to users visiting tourist destinations using a mobile terminal, and further recognizes the user's emotions and adjusts the response accordingly. This system consists of a mobile terminal, a server, a database, and an emotion engine.

[0142] When a user launches an application on their mobile device, the device obtains its current location via GPS and sends it to the server along with its language settings. The server then retrieves relevant tourist information from its database in multiple languages ​​and provides the user with real-time guide information. In this initial stage, the application also transmits the user's voice and facial expressions to an emotion engine via the camera and microphone to analyze the user's emotional state.

[0143] The emotion engine adjusts the information and responses it provides based on the analyzed emotion data. For example, if the user is excited, it will provide more detailed and engaging information, while if the user is tired, it will prioritize providing concise and relaxing information.

[0144] Furthermore, when users input specific questions about tourist destinations via their devices, the emotion engine adjusts the data based on emotional information before inputting it into the generating AI. This allows the generating AI to produce the most relevant response for the user. This response is then sent to the device and presented to the user in either voice or text.

[0145] If a user requests a remote sightseeing experience, the server generates and streams content optimized for the user's state based on emotional data analyzed by the emotion engine. This allows users to fully enjoy the attractions of tourist destinations from the comfort of their own homes.

[0146] For example, if a user visits a historical site and shows great interest, the emotion engine can analyze their excitement, and the server can prepare and deliver VR content that more deeply conveys the atmosphere of the place. This makes the sightseeing experience highly personalized and improves the user experience.

[0147] The following describes the processing flow.

[0148] Step 1:

[0149] The user launches an application on their mobile device. The device obtains its current location information from its built-in GPS and checks the device's language settings.

[0150] Step 2:

[0151] The device sends this location information and language setting information to the server.

[0152] Step 3:

[0153] The server searches the database based on the received information and retrieves relevant tourist destination information in multiple languages.

[0154] Step 4:

[0155] The server organizes the acquired tourist destination information and transmits it to the terminal in real time. The terminal then presents this information to the user.

[0156] Step 5:

[0157] The device sends the user's voice data and camera footage to an emotion engine for emotional analysis.

[0158] Step 6:

[0159] The emotion engine determines the user's emotional state and sends the result to the server.

[0160] Step 7:

[0161] Based on the analyzed sentiment data, the server adjusts the tourist information it provides, selecting more detailed or different information to send to the terminal.

[0162] Step 8:

[0163] The user inputs a question using natural language via a device. The device then sends the question to the server.

[0164] Step 9:

[0165] The server receives a question and requests the generative AI to analyze it while referring to the emotion engine's data. The generative AI generates a response and returns it to the server.

[0166] Step 10:

[0167] The server sends the generated response to the terminal, which then provides it to the user via voice or text.

[0168] Step 11:

[0169] If a user requests a remote sightseeing experience, the device sends a request to the server while referencing emotional data.

[0170] Step 12:

[0171] The server generates optimal remote content based on the user's emotions and streams it to the device.

[0172] Step 13:

[0173] The device plays the received content, allowing the user to experience the appeal of the tourist destination.

[0174] (Example 2)

[0175] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0176] While it was possible to provide real-time, multilingual guide information to mobile users visiting tourist destinations using conventional technology, methods for delivering information that took into account the user's emotional state were not in place. Therefore, the user experience was not sufficiently personalized, making it difficult to improve satisfaction. Furthermore, there is a need to highly customize the tourist experience to suit the user's emotions, even in remote environments.

[0177] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0178] In this invention, the server includes means for processing multilingual information of relevant locations based on received data and sentiment analysis results; means for providing the acquired information in real time and analyzing and adjusting the user's emotional state; and means for creating prompt sentences that take sentiment analysis results into account using a generative AI and generating responses to questions. This enables personalized real-time information provision and a highly customized tourism experience that responds to the user's emotional state.

[0179] A "mobile terminal" is a small, portable communication device that enables users to acquire location information and send and receive data.

[0180] "Location information" refers to geographical data acquired by a mobile device to determine its current location.

[0181] "Language setting information" refers to information used to specify the language a user will use, and is data used to determine the language in which information is provided.

[0182] A "server" is a centralized processing device that handles information processing and management, communicates with databases, and has the function of responding to requests from clients.

[0183] "Multilingual information" refers to information translated into different languages, and is data that enables the provision of information to users who speak different languages.

[0184] "Emotion analysis" is a technology that analyzes and identifies a user's emotional state from their voice and facial expressions, and is applied to optimize the information provided.

[0185] "Generative AI" is a technology that uses artificial intelligence models to generate natural language responses based on input data, and is a system for providing interactive responses.

[0186] A "prompt message" is text data input to a generation AI, and it is a sentence containing instructions or information to generate the desired response.

[0187] "Real-time" refers to events or processes occurring simultaneously with or very close to their occurrence, meaning that information is provided without delay.

[0188] This invention realizes a system that provides a personalized user experience by combining a mobile terminal, a server, a data collection function, and an emotion analysis engine.

[0189] Mobile terminal operation

[0190] The user launches a dedicated application on a mobile device such as a smartphone or tablet. The device uses its built-in GPS module to obtain the user's location information and also checks the language settings the user has configured. The obtained location information and language settings are transmitted to the server via wireless communication.

[0191] Server Processing

[0192] The server retrieves multilingual information about relevant locations from a database based on the received location information. This database uses a relational database management system such as MySQL® or PostgreSQL. The retrieved information is analyzed by an emotion analysis engine according to the user's emotional state and processed appropriately. The server provides this processed information to the terminal in real time.

[0193] Use of sentiment analysis

[0194] The device captures facial expressions with its camera and collects audio with its microphone. This data is sent to an emotion analysis engine to determine the user's emotional state. Emotion analysis uses an emotion recognition API (e.g., an emotion recognition system using common nouns), and the information provided is adjusted depending on whether the user is excited or tired.

[0195] Use of Generative AI Models

[0196] When a user enters a question in natural language into the device, the server generates a prompt that takes sentiment analysis into account and sends it to a generative AI model. A generative language model using common nouns is used as the generative AI model. The generative AI generates a response to the question, which the server then sends to the device.

[0197] Specific example

[0198] For example, if a user visits a historical site in Japan and asks, "Tell me an interesting story about the construction of this temple," the device's sentiment analysis engine evaluates the user's level of excitement. The server sends a prompt message to the generating AI model saying, "The user is very interested, please elaborate on any anecdotes or interesting facts about its construction." The generating AI model follows the prompt and generates a response containing detailed historical information and anecdotes, which it then provides to the user via the device.

[0199] In this way, users can obtain a wealth of information during their visit and enjoy a highly customized tourism experience even in a remote environment.

[0200] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0201] Step 1:

[0202] The user launches an application on a mobile device. The device uses its built-in GPS function to obtain its current location and confirms the language information set by the user. The input is the user's current location and selected language, and this information is compiled into a data packet within the device. As output, the device prepares the configured data packet.

[0203] Step 2:

[0204] The terminal sends the prepared data packets to the server via secure wireless communication. The input is the data packets prepared by the terminal, and the destination is the server. As output, the terminal accurately sends the data packets to the server.

[0205] Step 3:

[0206] The server analyzes data packets received from the terminal and extracts location and language information. The input is data packets from the terminal, and through analysis, two elements are extracted. As output, the server obtains location and language information.

[0207] Step 4:

[0208] The server retrieves multilingual information for related locations from the data aggregation mechanism based on the extracted location information. A DBMS is used to extract the relevant information in multiple languages. The input is location information, and the server obtains multilingual information for related locations as output.

[0209] Step 5:

[0210] The server adjusts the information based on the acquired multilingual information and the user's sentiment analysis results. Using a sentiment analysis engine, it generates personalized information that takes the user's mental state into account. The input is multilingual information and sentiment data, and the output is adjusted information. Specifically, it provides detailed information to excited users and concise information to users feeling fatigued.

[0211] Step 6:

[0212] The terminal receives pre-configured information from the server and displays it to the user in real time. The input is pre-configured information from the server, and the output is the information displayed on the user's screen.

[0213] Step 7:

[0214] The user inputs a question using natural language via a device. The input question is captured as text data by the device. The captured question data is prepared as output.

[0215] Step 8:

[0216] The sentiment analysis engine analyzes the user's mental state based on their input and generates prompts accordingly. The input consists of the user's question and sentiment data, and the output is a prompt based on the question.

[0217] Step 9:

[0218] The server sends the generated prompt to the AI ​​model and receives an appropriate response. The input is the prompt, which is sent to the AI ​​model. The output is the response data from the AI ​​model.

[0219] Step 10:

[0220] The server sends the response obtained from the generated AI model to the terminal. The input is the model's response, and the output is data sent to the terminal.

[0221] Step 11:

[0222] The terminal receives a response from the server and presents it to the user in audio or text format. The input is the response from the server, which is presented to the user as output, completing the response to the user's question.

[0223] (Application Example 2)

[0224] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0225] Traditional tourism information systems provide uniform information without considering the user's emotional state, making it difficult to offer a personalized experience tailored to the user's interests and circumstances. Furthermore, generating appropriate responses based on the user's emotions while providing real-time multilingual support is challenging. Additionally, there is a lack of means to optimize the virtual store experience according to the user's emotions.

[0226] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0227] In this invention, the server includes means for acquiring emotional data via the camera and microphone of a mobile information device and analyzing said emotional data; means for adjusting the information and responses provided based on the analyzed emotional data; and means for generating content to optimize the user experience in a virtual store based on the emotional data and presenting said content to the user. This enables personalized information provision and optimization of the virtual experience according to the user's emotional state.

[0228] A "mobile information device" is a mobile terminal that has the function of acquiring location information and emotional data and transmitting this information to a server.

[0229] An "information processing device" is a machine that acquires and processes multilingual regional information based on received information and provides it to the user in real time.

[0230] "Emotional data" refers to information about a user's emotions, extracted from their facial expressions, voice, etc., and is used to analyze the user's psychological state.

[0231] "Analysis means" refers to technology that analyzes the user's emotional state based on acquired emotional data and adjusts the information provided accordingly.

[0232] "Generative AI" is an artificial intelligence technology that generates the optimal response to inquiries using natural language, while taking into account the user's emotional data.

[0233] A "virtual store" is a store-style platform set up in a virtual space, an online commercial facility that provides users with a realistic product experience.

[0234] "Means of generating content" refers to technologies that create digital information to produce visually and aurally rich experiences based on user emotional data.

[0235] To put this invention into practice, first, smart glasses or other mobile information devices are used. These information terminals have built-in cameras and microphones, making it possible to capture the user's facial expressions and voice in real time.

[0236] The server receives location information, language setting information, and sentiment data transmitted from these terminals and processes them using an information processing device. Based on the received location information, it retrieves multilingual information for the relevant region from a database. In addition, the sentiment data is analyzed using sentiment analysis tools to determine the user's current emotional state.

[0237] Based on the analysis results, the server provides the user with the most relevant information and generates real-time guidance. In this process, the generating AI model responds to natural language queries using specific prompt phrases. An example of such a prompt phrase is, "Please suggest products to recommend when the user is excited."

[0238] Furthermore, when a user visits a virtual store, personalized content is generated based on emotional data. This content is designed using a generative AI model to provide an optimal experience tailored to the user's preferences and emotional state. For example, it overlays visually colorful product images with product information that has a relaxing effect, creating an experience that is uniquely suited to each user.

[0239] This allows users to receive information tailored to their emotional state at any given time, no matter where they are, resulting in a richer and more personalized experience.

[0240] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0241] Step 1:

[0242] The user wears smart glasses and launches the application. The device uses a camera and microphone to capture the user's facial expressions and voice, collecting this data as input. The emotional data obtained here forms the basis for subsequent analysis.

[0243] Step 2:

[0244] The device sends its location information, collected sentiment data, and language setting information to the server. The server uses the location information to retrieve multilingual information from its database. The output of this process is tourist information related to the user's location.

[0245] Step 3:

[0246] The server uses an emotion analysis engine to analyze the emotional data received from the terminal. The input facial expressions and voice data are analyzed, and the user's emotional state is output. Based on the analysis results, the information and content to be provided are determined.

[0247] Step 4:

[0248] The server uses a generative AI model to create prompts that take into account the user's emotional state. An example of such a prompt might be, "Please suggest tourist destinations to recommend when the user is excited." Based on the input emotional data and the inquiry, the optimal response is generated.

[0249] Step 5:

[0250] The generated responses and content are sent to the device. The device displays the information and provides it to the user in audio or text format. Information is dynamically displayed to match the user's field of view, providing personalized guide information and a virtual store experience.

[0251] Step 6:

[0252] When a user chooses to enter a virtual store, the server generates content to optimize the store experience based on emotional data. The data used reflects the user's preferences and is tailored to enrich the user's experience visually and aurally. The output is personalized visual and auditory content for the virtual store.

[0253] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0254] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0255] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0256] [Second Embodiment]

[0257] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0258] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0259] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0260] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0261] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0262] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0263] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0264] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0265] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0266] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0267] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0268] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0269] One embodiment of the present invention relates to a system that provides real-time, multilingual tourist information to users visiting tourist destinations using mobile terminals. This system mainly consists of mobile terminals, a server, and a database.

[0270] The user launches an application installed on their mobile device. The device first obtains its current location information via GPS and simultaneously collects the device's language setting information. This information is sent to a server, which retrieves relevant tourist destination information from its database in multiple languages ​​based on the received information.

[0271] The server processes the acquired tourist destination information in real time and provides it to the device as guide information. This allows users to receive multilingual guidance about the history and culture of tourist destinations through their devices.

[0272] Furthermore, when a user enters a specific question about a tourist destination via their mobile device, that question is sent to the server. The server uses a generative AI to analyze the question and generate a response. This response is sent back to the user's device and displayed in a chat format. This allows users to obtain detailed information tailored to their individual interests.

[0273] Furthermore, even when users are in remote locations, the system provides a remote tourism experience. The server generates and streams content that conveys the appeal of tourist destinations via video display devices. In this way, users can experience the charm of tourist destinations without actually visiting them.

[0274] As a concrete example, consider a scenario where a user visits a historical site with a mobile device. Upon launching the app, the server provides real-time, multilingual guidance to the user, detailing the site's history and points of interest. Furthermore, if the user desires additional information about a specific building or ruin, they can directly input questions and obtain more in-depth information on the spot.

[0275] This system allows tourists to obtain a wealth of information even within a limited time, enabling them to gain a deeper understanding of the essence of their destination.

[0276] The following describes the processing flow.

[0277] Step 1:

[0278] The user launches the application on their mobile device. The device obtains its current location using its built-in GPS and also checks the device's language settings.

[0279] Step 2:

[0280] The terminal sends the acquired location information and language setting information to the server. The server receives this information and extracts tourist destination information related to the corresponding location from the database.

[0281] Step 3:

[0282] The server sorts out multilingual tourist destination information according to the user's language setting and sends it to the terminal in real time. The terminal presents the received information to the user in voice or text form.

[0283] Step 4:

[0284] When the user wants to know more detailed information about the tourist destination, the user enters a question through the chatbot interface of the terminal. The terminal sends the entered question to the server. <00​​​​​​​​​​​​​​​​​​​​​​​​​​​​​The device displays received VR experiences or video content, allowing users to remotely experience the charm of a region.

[0293] (Example 1)

[0294] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0295] In recent years, there has been a growing demand for real-time access to detailed, multilingual information when visiting tourist destinations, as well as the ability to receive information tailored to individual interests. Furthermore, there is a desire to enjoy the allure of tourist destinations through virtual experiences without actually visiting the location. However, conventional systems have not adequately met these needs.

[0296] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0297] In this invention, the server includes means for a mobile terminal to acquire location information and transmit data including said location information and language setting information; information processing means for acquiring multilingual information of a relevant location from an information storage device based on the received data; and means for processing the acquired multilingual information and providing guidance information to the mobile terminal in real time. As a result, users can receive real-time information including multilingual support and individual question answering.

[0298] A "mobile terminal" refers to a portable device that can communicate data while moving between locations, and is an electronic device equipped with GPS and communication functions.

[0299] "Location information" refers to data that indicates the geographical location of a mobile device, and is expressed as numerical values ​​of latitude and longitude.

[0300] "Language setting information" is data that indicates the language set on the mobile device, and is used by the system to determine in which language information will be provided.

[0301] "Data transmission means" refers to a function or device for transmitting data from a mobile terminal to a server, and plays a role in transferring information through a communication protocol.

[0302] "Information storage device" is a device that holds multilingual information and other data, and functions as a database system.

[0303] "Information processing device means" refers to a function or device for analyzing and processing data in a server, and searching, obtaining, and generating necessary information.

[0304] "Guiding information" is data that includes detailed information such as the history and culture of tourist destinations that users are interested in, and is used as an explanation provided to users.

[0305] "Generative AI" refers to a technology that uses an artificial intelligence model to analyze questions in a user's natural language and generate appropriate answers.

[0306] "Response" is answer information automatically created by generative AI in response to a user's question, and is presented to the user.

[0307] "Video display device" refers to a device for displaying visual content, and provides a means for users to visually receive video information.

[0308] "Video distribution" refers to a method of transmitting video or video data to users, enabling users to view it in real time or on demand.

[0309] This invention relates to a system for providing tourist information in real time and in multiple languages to users visiting tourist destinations via a mobile terminal. This system mainly consists of a mobile terminal, a server, and an information storage device.

[0310] The user launches an application installed on their mobile device, and the device uses its built-in GPS function to obtain its current location. Simultaneously, the device's language settings are also collected. This information is transmitted from the mobile device to the server. A secure protocol is used for communication, such as HTTPS.

[0311] The server uses the received location and language setting information to retrieve multilingual information about the relevant tourist destination from the information storage device. A database management system is used for this information processing, and information is retrieved via SQL queries. The server processes the retrieved information and immediately transmits guidance information to the mobile terminal. This processing includes data format conversion and template processing for multilingual support.

[0312] Furthermore, when a user asks a question about a tourist destination using natural language via their device, the question is sent to the server. The server uses a generative AI model and natural language processing techniques such as GPT to analyze the question and generate an appropriate response. The generated response is sent to the mobile device, which displays it in a visual format. This allows users to receive information tailored to their individual interests in real time.

[0313] As a concrete example, consider a scenario where a user visits a historical site. When the user enters a prompt such as "Tell me about the history of this place," the server generates relevant historical information and provides detailed, multilingual guidance.

[0314] Furthermore, the server generates and streams visual information to provide remote users with a virtual sightseeing experience via a video display device. In this process, for example, by using a cloud-based video streaming service, it becomes possible to experience the impression of a tourist destination without actually visiting the location.

[0315] In this way, users can easily obtain multilingual tourist information through their mobile devices and deepen their detailed understanding of tourist destinations.

[0316] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0317] Step 1:

[0318] The user launches an application on a mobile device. The device uses its built-in GPS function to obtain its current location. It also obtains the device's language setting information. The input consists of the user's location and language setting from the device; based on this, the device sends this data to the server. The output is a dataset containing location information and language settings.

[0319] Step 2:

[0320] The server retrieves relevant multilingual tourist information from an information storage device based on location and language setting information received from the terminal. The input is a dataset received from the terminal, and the server uses a database management system to execute SQL queries and extract relevant information. The output is multilingual information about the selected tourist destination.

[0321] Step 3:

[0322] The server processes acquired tourist destination information in real time. It receives multilingual tourist information as input, formats it according to the user's language settings, and prepares it in an appropriate format (e.g., HTML or JSON). The output is formatted multilingual information. The server then transmits this information to mobile devices.

[0323] Step 4:

[0324] The user inputs questions about tourist destinations in natural language via a terminal. The input is the user's question in natural language. The terminal sends this question to the server. The output is the question data sent to the server.

[0325] Step 5:

[0326] The server analyzes received questions using a generative AI model. The input is a natural language question received from the user. The generative AI model understands the question and generates an appropriate response based on the relevant information. The output is the generated response data.

[0327] Step 6:

[0328] The server sends response data to the mobile terminal. The terminal receives this response and displays it on the screen in a chat format. The input is the response data obtained from the generative AI model, and the output is the visual information displayed to the user.

[0329] Step 7:

[0330] The server generates content to provide a virtual sightseeing experience to remote users via a video display device. The input includes visual information about the tourist destination, which is used to generate video data suitable for streaming. The output is streamable video data. The server streams this video to the user's terminal, allowing the user to virtually experience the tourist destination.

[0331] (Application Example 1)

[0332] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0333] In the modern tourism sector, providing real-time, multilingual tourism information is crucial. However, existing systems suffer from shortcomings in multilingual support and low-quality remote tourism experiences. Furthermore, few systems can suggest in real time which information is most useful to a user based on their location and interests.

[0334] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0335] In this invention, the server includes means for determining the user's location based on location data and presenting the user with optimal route information; means for generating tourist destination information as video data in a remote environment and transmitting the data to the user as video; and means for receiving inquiries in natural language, generating responses to those inquiries using a generation AI, and transmitting the responses to a mobile device. As a result, users can obtain a fulfilling tourist experience without actually visiting the locations and can receive optimal information in real time while traveling.

[0336] A "mobile device" is a type of electronic device that a user can carry and use, and is a terminal for processing location data and other information.

[0337] "Location data" refers to information that indicates the current geographical location of a mobile device, and is acquired using technologies such as GPS.

[0338] "Language setting data" refers to information about the display language and audio language that the user has pre-selected on the mobile device.

[0339] An "information recording medium" is a database that stores digital data and manages it so that it can be searched and retrieved as needed.

[0340] "Computing device means" refers to a central processing unit or server for processing information, and is responsible for acquiring and processing multilingual data.

[0341] "Real-time navigation data" refers to location-specific navigation information, including multilingual information, that is provided to users instantly.

[0342] "Natural language" refers to the forms of language that humans use in everyday conversation and writing, and that are expressed in text or audio.

[0343] "Generative AI" is an artificial intelligence algorithm that aims to analyze input data and automatically generate natural-sounding responses.

[0344] "Video data" refers to digital signals, including videos and still images, that are used as visual information.

[0345] "Video transmission" is the process of transferring video data to a receiving device such as a mobile device.

[0346] An "inquiry" is a question or request that a user sends in natural language seeking specific information.

[0347] The system for implementing this invention consists of a mobile device such as a smartphone, a server for data processing, and a database for providing information. First, the mobile device acquires location data using GPS and transmits it to the server along with the user's language setting data. Based on this data, the server processes the acquisition of the corresponding multilingual data from the information recording medium.

[0348] The server processes this data using Python and generates real-time guidance data. This allows for immediate tourist information to be provided to mobile devices. Furthermore, to respond to natural language inquiries from users, the server generates responses using generative AI models (e.g., OpenAI's GPT-4) and sends them to the mobile devices.

[0349] For the remote tourism experience, a server generates video data of the tourist destination and transmits the video in real time using Apache Kafka. This allows users to enjoy tourist destinations even when they are not physically present.

[0350] For example, if a user asks a question about the Colosseum in Rome, the smartphone will pinpoint their location and provide optimal route information according to their language settings. Also, if a user asks, "Tell me about the history of the Colosseum," the AI ​​will provide detailed historical information as a response.

[0351] An example of a prompt to the generating AI would be: "The user wants to learn about the history of the Colosseum. Please explain in detail the important facts and historical background of the Colosseum." Based on this sentence, the generating AI analyzes the information and generates an appropriate response.

[0352] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0353] Step 1:

[0354] The device acquires location data using a GPS sensor and sends this data, along with the user's language settings, to the server. The input is location data and language settings data, and the output is the process of sending these to the server.

[0355] Step 2:

[0356] The server accesses the information recording medium based on the received location data and language setting data, and retrieves the corresponding multilingual information. The input is location data and language setting data, and the output is the retrieval of multilingual information.

[0357] Step 3:

[0358] The server processes the acquired multilingual information into real-time guidance data and transmits it to the terminal. The input is multilingual information, and the output is processed real-time guidance data.

[0359] Step 4:

[0360] The user inputs a question into the terminal using natural language. The input is a question in natural language, and the output is sent to the server.

[0361] Step 5:

[0362] The server analyzes the received question and generates a response using a generative AI model. The input is a natural language question, and the output is the generated response.

[0363] Step 6:

[0364] The generated response is sent from the server to the terminal and displayed to the user. The input is the generated response, and the output is the display on the terminal.

[0365] Step 7:

[0366] The server generates video data for the remote sightseeing experience and transmits the video to the terminal in real time using Apache Kafka. The input is tourist destination information, and the output is the transmitted video data in real time.

[0367] Step 8:

[0368] Users can view detailed information about tourist destinations via their devices, based on responses provided by a generated AI model. The input consists of real-time guidance data and generated responses, while the output is tourist information provided to the user.

[0369] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0370] One embodiment of the present invention provides a system that offers real-time, multilingual tourist information to users visiting tourist destinations using a mobile terminal, and further recognizes the user's emotions and adjusts the response accordingly. This system consists of a mobile terminal, a server, a database, and an emotion engine.

[0371] When a user launches an application on their mobile device, the device obtains its current location via GPS and sends it to the server along with its language settings. The server then retrieves relevant tourist information from its database in multiple languages ​​and provides the user with real-time guide information. In this initial stage, the application also transmits the user's voice and facial expressions to an emotion engine via the camera and microphone to analyze the user's emotional state.

[0372] The emotion engine adjusts the information and responses it provides based on the analyzed emotion data. For example, if the user is excited, it will provide more detailed and engaging information, while if the user is tired, it will prioritize providing concise and relaxing information.

[0373] Furthermore, when users input specific questions about tourist destinations via their devices, the emotion engine adjusts the data based on emotional information before inputting it into the generating AI. This allows the generating AI to produce the most relevant response for the user. This response is then sent to the device and presented to the user in either voice or text.

[0374] If a user requests a remote sightseeing experience, the server generates and streams content optimized for the user's state based on emotional data analyzed by the emotion engine. This allows users to fully enjoy the attractions of tourist destinations from the comfort of their own homes.

[0375] For example, if a user visits a historical site and shows great interest, the emotion engine can analyze their excitement, and the server can prepare and deliver VR content that more deeply conveys the atmosphere of the place. This makes the sightseeing experience highly personalized and improves the user experience.

[0376] The following describes the processing flow.

[0377] Step 1:

[0378] The user launches an application on their mobile device. The device obtains its current location information from its built-in GPS and checks the device's language settings.

[0379] Step 2:

[0380] The device sends this location information and language setting information to the server.

[0381] Step 3:

[0382] The server searches the database based on the received information and retrieves relevant tourist destination information in multiple languages.

[0383] Step 4:

[0384] The server organizes the acquired tourist destination information and transmits it to the terminal in real time. The terminal then presents this information to the user.

[0385] Step 5:

[0386] The device sends the user's voice data and camera footage to an emotion engine for emotional analysis.

[0387] Step 6:

[0388] The emotion engine determines the user's emotional state and sends the result to the server.

[0389] Step 7:

[0390] Based on the analyzed sentiment data, the server adjusts the tourist information it provides, selecting more detailed or different information to send to the terminal.

[0391] Step 8:

[0392] The user inputs a question using natural language via a device. The device then sends the question to the server.

[0393] Step 9:

[0394] The server receives a question and requests the generative AI to analyze it while referring to the emotion engine's data. The generative AI generates a response and returns it to the server.

[0395] Step 10:

[0396] The server sends the generated response to the terminal, which then provides it to the user via voice or text.

[0397] Step 11:

[0398] If a user requests a remote sightseeing experience, the device sends a request to the server while referencing emotional data.

[0399] Step 12:

[0400] The server generates optimal remote content based on the user's emotions and streams it to the device.

[0401] Step 13:

[0402] The device plays the received content, allowing the user to experience the appeal of the tourist destination.

[0403] (Example 2)

[0404] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0405] While it was possible to provide real-time, multilingual guide information to mobile users visiting tourist destinations using conventional technology, methods for delivering information that took into account the user's emotional state were not in place. Therefore, the user experience was not sufficiently personalized, making it difficult to improve satisfaction. Furthermore, there is a need to highly customize the tourist experience to suit the user's emotions, even in remote environments.

[0406] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0407] In this invention, the server includes means for processing multilingual information of relevant locations based on received data and sentiment analysis results; means for providing the acquired information in real time and analyzing and adjusting the user's emotional state; and means for creating prompt sentences that take sentiment analysis results into account using a generative AI and generating responses to questions. This enables personalized real-time information provision and a highly customized tourism experience that responds to the user's emotional state.

[0408] A "mobile terminal" is a small, portable communication device that enables users to acquire location information and send and receive data.

[0409] "Location information" refers to geographical data acquired by a mobile device to determine its current location.

[0410] "Language setting information" refers to information used to specify the language a user will use, and is data used to determine the language in which information is provided.

[0411] A "server" is a centralized processing device that handles information processing and management, communicates with databases, and has the function of responding to requests from clients.

[0412] "Multilingual information" refers to information translated into different languages, and is data that enables the provision of information to users who speak different languages.

[0413] "Emotion analysis" is a technology that analyzes and identifies a user's emotional state from their voice and facial expressions, and is applied to optimize the information provided.

[0414] "Generative AI" is a technology that uses artificial intelligence models to generate natural language responses based on input data, and is a system for providing interactive responses.

[0415] A "prompt message" is text data input to a generation AI, and it is a sentence containing instructions or information to generate the desired response.

[0416] "Real-time" refers to events or processes occurring simultaneously with or very close to their occurrence, meaning that information is provided without delay.

[0417] This invention realizes a system that provides a personalized user experience by combining a mobile terminal, a server, a data collection function, and an emotion analysis engine.

[0418] Mobile terminal operation

[0419] The user launches a dedicated application on a mobile device such as a smartphone or tablet. The device uses its built-in GPS module to obtain the user's location information and also checks the language settings the user has configured. The obtained location information and language settings are transmitted to the server via wireless communication.

[0420] Server Processing

[0421] The server retrieves multilingual information about relevant locations from a database based on the received location data. This database uses a relational database management system such as MySQL or PostgreSQL. The retrieved information is analyzed by an emotion analysis engine according to the user's emotional state and processed appropriately. The server provides this processed information to the terminal in real time.

[0422] Use of sentiment analysis

[0423] The device captures facial expressions with its camera and collects audio with its microphone. This data is sent to an emotion analysis engine to determine the user's emotional state. Emotion analysis uses an emotion recognition API (e.g., an emotion recognition system using common nouns), and the information provided is adjusted depending on whether the user is excited or tired.

[0424] Use of Generative AI Models

[0425] When a user enters a question in natural language into the device, the server generates a prompt that takes sentiment analysis into account and sends it to a generative AI model. A generative language model using common nouns is used as the generative AI model. The generative AI generates a response to the question, which the server then sends to the device.

[0426] Specific example

[0427] For example, if a user visits a historical site in Japan and asks, "Tell me an interesting story about the construction of this temple," the device's sentiment analysis engine evaluates the user's level of excitement. The server sends a prompt message to the generating AI model saying, "The user is very interested, please elaborate on any anecdotes or interesting facts about its construction." The generating AI model follows the prompt and generates a response containing detailed historical information and anecdotes, which it then provides to the user via the device.

[0428] In this way, users can obtain a wealth of information during their visit and enjoy a highly customized tourism experience even in a remote environment.

[0429] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0430] Step 1:

[0431] The user launches an application on a mobile device. The device uses its built-in GPS function to obtain its current location and confirms the language information set by the user. The input is the user's current location and selected language, and this information is compiled into a data packet within the device. As output, the device prepares the configured data packet.

[0432] Step 2:

[0433] The terminal sends the prepared data packets to the server via secure wireless communication. The input is the data packets prepared by the terminal, and the destination is the server. As output, the terminal accurately sends the data packets to the server.

[0434] Step 3:

[0435] The server analyzes data packets received from the terminal and extracts location and language information. The input is data packets from the terminal, and through analysis, two elements are extracted. As output, the server obtains location and language information.

[0436] Step 4:

[0437] The server retrieves multilingual information for related locations from the data aggregation mechanism based on the extracted location information. A DBMS is used to extract the relevant information in multiple languages. The input is location information, and the server obtains multilingual information for related locations as output.

[0438] Step 5:

[0439] The server adjusts the information based on the acquired multilingual information and the user's sentiment analysis results. Using a sentiment analysis engine, it generates personalized information that takes the user's mental state into account. The input is multilingual information and sentiment data, and the output is adjusted information. Specifically, it provides detailed information to excited users and concise information to users feeling fatigued.

[0440] Step 6:

[0441] The terminal receives pre-configured information from the server and displays it to the user in real time. The input is pre-configured information from the server, and the output is the information displayed on the user's screen.

[0442] Step 7:

[0443] The user inputs a question using natural language via a device. The input question is captured as text data by the device. The captured question data is prepared as output.

[0444] Step 8:

[0445] The sentiment analysis engine analyzes the user's mental state based on their input and generates prompts accordingly. The input consists of the user's question and sentiment data, and the output is a prompt based on the question.

[0446] Step 9:

[0447] The server sends the generated prompt to the AI ​​model and receives an appropriate response. The input is the prompt, which is sent to the AI ​​model. The output is the response data from the AI ​​model.

[0448] Step 10:

[0449] The server sends the response obtained from the generated AI model to the terminal. The input is the model's response, and the output is data sent to the terminal.

[0450] Step 11:

[0451] The terminal receives a response from the server and presents it to the user in audio or text format. The input is the response from the server, which is presented to the user as output, completing the response to the user's question.

[0452] (Application Example 2)

[0453] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0454] Traditional tourism information systems provide uniform information without considering the user's emotional state, making it difficult to offer a personalized experience tailored to the user's interests and circumstances. Furthermore, generating appropriate responses based on the user's emotions while providing real-time multilingual support is challenging. Additionally, there is a lack of means to optimize the virtual store experience according to the user's emotions.

[0455] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0456] In this invention, the server includes means for acquiring emotional data via the camera and microphone of a mobile information device and analyzing said emotional data; means for adjusting the information and responses provided based on the analyzed emotional data; and means for generating content to optimize the user experience in a virtual store based on the emotional data and presenting said content to the user. This enables personalized information provision and optimization of the virtual experience according to the user's emotional state.

[0457] A "mobile information device" is a mobile terminal that has the function of acquiring location information and emotional data and transmitting this information to a server.

[0458] An "information processing device" is a machine that acquires and processes multilingual regional information based on received information and provides it to the user in real time.

[0459] "Emotional data" refers to information about a user's emotions, extracted from their facial expressions, voice, etc., and is used to analyze the user's psychological state.

[0460] "Analysis means" refers to technology that analyzes the user's emotional state based on acquired emotional data and adjusts the information provided accordingly.

[0461] "Generative AI" is an artificial intelligence technology that generates the optimal response to inquiries using natural language, while taking into account the user's emotional data.

[0462] A "virtual store" is a store-style platform set up in a virtual space, an online commercial facility that provides users with a realistic product experience.

[0463] "Means of generating content" refers to technologies that create digital information to produce visually and aurally rich experiences based on user emotional data.

[0464] To put this invention into practice, first, smart glasses or other mobile information devices are used. These information terminals have built-in cameras and microphones, making it possible to capture the user's facial expressions and voice in real time.

[0465] The server receives location information, language setting information, and sentiment data transmitted from these terminals and processes them using an information processing device. Based on the received location information, it retrieves multilingual information for the relevant region from a database. In addition, the sentiment data is analyzed using sentiment analysis tools to determine the user's current emotional state.

[0466] Based on the analysis results, the server provides the user with the most relevant information and generates real-time guidance. In this process, the generating AI model responds to natural language queries using specific prompt phrases. An example of such a prompt phrase is, "Please suggest products to recommend when the user is excited."

[0467] Furthermore, when a user visits a virtual store, personalized content is generated based on emotional data. This content is designed using a generative AI model to provide an optimal experience tailored to the user's preferences and emotional state. For example, it overlays visually colorful product images with product information that has a relaxing effect, creating an experience that is uniquely suited to each user.

[0468] This allows users to receive information tailored to their emotional state at any given time, no matter where they are, resulting in a richer and more personalized experience.

[0469] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0470] Step 1:

[0471] The user wears smart glasses and launches the application. The device uses a camera and microphone to capture the user's facial expressions and voice, collecting this data as input. The emotional data obtained here forms the basis for subsequent analysis.

[0472] Step 2:

[0473] The device sends its location information, collected sentiment data, and language setting information to the server. The server uses the location information to retrieve multilingual information from its database. The output of this process is tourist information related to the user's location.

[0474] Step 3:

[0475] The server uses an emotion analysis engine to analyze the emotional data received from the terminal. The input facial expressions and voice data are analyzed, and the user's emotional state is output. Based on the analysis results, the information and content to be provided are determined.

[0476] Step 4:

[0477] The server uses a generative AI model to create prompts that take into account the user's emotional state. An example of such a prompt might be, "Please suggest tourist destinations to recommend when the user is excited." Based on the input emotional data and the inquiry, the optimal response is generated.

[0478] Step 5:

[0479] The generated responses and content are sent to the device. The device displays the information and provides it to the user in audio or text format. Information is dynamically displayed to match the user's field of view, providing personalized guide information and a virtual store experience.

[0480] Step 6:

[0481] When a user chooses to enter a virtual store, the server generates content to optimize the store experience based on emotional data. The data used reflects the user's preferences and is tailored to enrich the user's experience visually and aurally. The output is personalized visual and auditory content for the virtual store.

[0482] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0483] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0484] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0485] [Third Embodiment]

[0486] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0487] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0488] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0489] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0490] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0491] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0492] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0493] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0494] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0495] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0496] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0497] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0498] One embodiment of the present invention relates to a system that provides real-time, multilingual tourist information to users visiting tourist destinations using mobile terminals. This system mainly consists of mobile terminals, a server, and a database.

[0499] The user launches an application installed on their mobile device. The device first obtains its current location information via GPS and simultaneously collects the device's language setting information. This information is sent to a server, which retrieves relevant tourist destination information from its database in multiple languages ​​based on the received information.

[0500] The server processes the acquired tourist destination information in real time and provides it to the device as guide information. This allows users to receive multilingual guidance about the history and culture of tourist destinations through their devices.

[0501] Furthermore, when a user enters a specific question about a tourist destination via their mobile device, that question is sent to the server. The server uses a generative AI to analyze the question and generate a response. This response is sent back to the user's device and displayed in a chat format. This allows users to obtain detailed information tailored to their individual interests.

[0502] Furthermore, even when users are in remote locations, the system provides a remote tourism experience. The server generates and streams content that conveys the appeal of tourist destinations via video display devices. In this way, users can experience the charm of tourist destinations without actually visiting them.

[0503] As a concrete example, consider a scenario where a user visits a historical site with a mobile device. Upon launching the app, the server provides real-time, multilingual guidance to the user, detailing the site's history and points of interest. Furthermore, if the user desires additional information about a specific building or ruin, they can directly input questions and obtain more in-depth information on the spot.

[0504] This system allows tourists to obtain a wealth of information even within a limited time, enabling them to gain a deeper understanding of the essence of their destination.

[0505] The following describes the processing flow.

[0506] Step 1:

[0507] The user launches the application on their mobile device. The device obtains its current location using its built-in GPS and also checks the device's language settings.

[0508] Step 2:

[0509] The device sends the acquired location information and language setting information to the server. The server receives this information and retrieves tourist destination information related to the corresponding location from its database.

[0510] Step 3:

[0511] The server organizes multilingual tourist information according to the user's language settings and sends it to the terminal in real time. The terminal presents the received information to the user in audio or text format.

[0512] Step 4:

[0513] If a user wants more detailed information about a tourist destination, they enter their question through the chatbot interface on their device. The device then sends the entered question to the server.

[0514] Step 5:

[0515] The server passes the received question to the generating AI, which analyzes the question. Based on the analysis, the generating AI generates an appropriate response and returns it to the server.

[0516] Step 6:

[0517] The server sends back a response generated by the AI ​​to the terminal. The terminal displays the response to the user and provides it in audio format if necessary.

[0518] Step 7:

[0519] If a user requests a remote sightseeing experience, the device sends this request to the server. The server prepares VR experiences and video content of the tourist destination and streams them to the device.

[0520] Step 8:

[0521] The device displays received VR experiences or video content, allowing users to remotely experience the charm of a region.

[0522] (Example 1)

[0523] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0524] In recent years, there has been a growing demand for real-time access to detailed, multilingual information when visiting tourist destinations, as well as the ability to receive information tailored to individual interests. Furthermore, there is a desire to enjoy the allure of tourist destinations through virtual experiences without actually visiting the location. However, conventional systems have not adequately met these needs.

[0525] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0526] In this invention, the server includes means for a mobile terminal to acquire location information and transmit data including said location information and language setting information; information processing means for acquiring multilingual information of a relevant location from an information storage device based on the received data; and means for processing the acquired multilingual information and providing guidance information to the mobile terminal in real time. As a result, users can receive real-time information including multilingual support and individual question answering.

[0527] A "mobile terminal" refers to a portable device that can communicate data while moving between locations, and is an electronic device equipped with GPS and communication functions.

[0528] "Location information" refers to data that indicates the geographical location of a mobile device, and is expressed as numerical values ​​of latitude and longitude.

[0529] "Language setting information" is data that indicates the language set on the mobile device, and is used by the system to determine in which language information will be provided.

[0530] "Data transmission means" refers to a function or device for transmitting data from a mobile terminal to a server, and plays the role of transferring information through a communication protocol.

[0531] An "information storage device" is a device that holds multilingual information and other data, and functions as a database system.

[0532] "Information processing device means" refers to a function or device on a server that analyzes and processes data and searches, acquires, and generates necessary information.

[0533] "Guidance information" refers to data that includes detailed information about the history, culture, and other aspects of tourist destinations that users are interested in, and is used as an explanation provided to the user.

[0534] "Generative AI" refers to a technology that uses artificial intelligence models to analyze a user's natural language questions and generate appropriate answers.

[0535] A "response" is an answer automatically generated by a generation AI in response to a user's question, and is presented to the user.

[0536] A "video display device" refers to a device for displaying visual content, providing a means for users to visually receive video information.

[0537] "Video distribution" refers to a method of transmitting videos or video data to users, enabling them to view them in real time or on demand.

[0538] This invention relates to a system that provides real-time, multilingual tourist information to users visiting tourist destinations via mobile terminals. This system mainly consists of mobile terminals, a server, and an information storage device.

[0539] The user launches an application installed on their mobile device, and the device uses its built-in GPS function to obtain its current location. Simultaneously, the device's language settings are also collected. This information is transmitted from the mobile device to the server. A secure protocol is used for communication, such as HTTPS.

[0540] The server uses the received location and language setting information to retrieve multilingual information about the relevant tourist destination from the information storage device. A database management system is used for this information processing, and information is retrieved via SQL queries. The server processes the retrieved information and immediately transmits guidance information to the mobile terminal. This processing includes data format conversion and template processing for multilingual support.

[0541] Furthermore, when a user asks a question about a tourist destination using natural language via their device, the question is sent to the server. The server uses a generative AI model and natural language processing techniques such as GPT to analyze the question and generate an appropriate response. The generated response is sent to the mobile device, which displays it in a visual format. This allows users to receive information tailored to their individual interests in real time.

[0542] As a concrete example, consider a scenario where a user visits a historical site. When the user enters a prompt such as "Tell me about the history of this place," the server generates relevant historical information and provides detailed, multilingual guidance.

[0543] Furthermore, the server generates and streams visual information to provide remote users with a virtual sightseeing experience via a video display device. In this process, for example, by using a cloud-based video streaming service, it becomes possible to experience the impression of a tourist destination without actually visiting the location.

[0544] In this way, users can easily obtain multilingual tourist information through their mobile devices and deepen their detailed understanding of tourist destinations.

[0545] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0546] Step 1:

[0547] The user launches an application on a mobile device. The device uses its built-in GPS function to obtain its current location. It also obtains the device's language setting information. The input consists of the user's location and language setting from the device; based on this, the device sends this data to the server. The output is a dataset containing location information and language settings.

[0548] Step 2:

[0549] The server retrieves relevant multilingual tourist information from an information storage device based on location and language setting information received from the terminal. The input is a dataset received from the terminal, and the server uses a database management system to execute SQL queries and extract relevant information. The output is multilingual information about the selected tourist destination.

[0550] Step 3:

[0551] The server processes acquired tourist destination information in real time. It receives multilingual tourist information as input, formats it according to the user's language settings, and prepares it in an appropriate format (e.g., HTML or JSON). The output is formatted multilingual information. The server then transmits this information to mobile devices.

[0552] Step 4:

[0553] The user inputs questions about tourist destinations in natural language via a terminal. The input is the user's question in natural language. The terminal sends this question to the server. The output is the question data sent to the server.

[0554] Step 5:

[0555] The server analyzes received questions using a generative AI model. The input is a natural language question received from the user. The generative AI model understands the question and generates an appropriate response based on the relevant information. The output is the generated response data.

[0556] Step 6:

[0557] The server sends response data to the mobile terminal. The terminal receives this response and displays it on the screen in a chat format. The input is the response data obtained from the generative AI model, and the output is the visual information displayed to the user.

[0558] Step 7:

[0559] The server generates content to provide a virtual sightseeing experience to remote users via a video display device. The input includes visual information about the tourist destination, which is used to generate video data suitable for streaming. The output is streamable video data. The server streams this video to the user's terminal, allowing the user to virtually experience the tourist destination.

[0560] (Application Example 1)

[0561] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0562] In the modern tourism sector, providing real-time, multilingual tourism information is crucial. However, existing systems suffer from shortcomings in multilingual support and low-quality remote tourism experiences. Furthermore, few systems can suggest in real time which information is most useful to a user based on their location and interests.

[0563] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0564] In this invention, the server includes means for determining the user's location based on location data and presenting the user with optimal route information; means for generating tourist destination information as video data in a remote environment and transmitting the data to the user as video; and means for receiving inquiries in natural language, generating responses to those inquiries using a generation AI, and transmitting the responses to a mobile device. As a result, users can obtain a fulfilling tourist experience without actually visiting the locations and can receive optimal information in real time while traveling.

[0565] A "mobile device" is a type of electronic device that a user can carry and use, and is a terminal for processing location data and other information.

[0566] "Location data" refers to information that indicates the current geographical location of a mobile device, and is acquired using technologies such as GPS.

[0567] "Language setting data" refers to information about the display language and audio language that the user has pre-selected on the mobile device.

[0568] An "information recording medium" is a database that stores digital data and manages it so that it can be searched and retrieved as needed.

[0569] "Computing device means" refers to a central processing unit or server for processing information, and is responsible for acquiring and processing multilingual data.

[0570] "Real-time navigation data" refers to location-specific navigation information, including multilingual information, that is provided to users instantly.

[0571] "Natural language" refers to the forms of language that humans use in everyday conversation and writing, and that are expressed in text or audio.

[0572] "Generative AI" is an artificial intelligence algorithm that aims to analyze input data and automatically generate natural-sounding responses.

[0573] "Video data" refers to digital signals, including videos and still images, that are used as visual information.

[0574] "Video transmission" is the process of transferring video data to a receiving device such as a mobile device.

[0575] An "inquiry" is a question or request that a user sends in natural language seeking specific information.

[0576] The system for implementing this invention consists of a mobile device such as a smartphone, a server for data processing, and a database for providing information. First, the mobile device acquires location data using GPS and transmits it to the server along with the user's language setting data. Based on this data, the server processes the acquisition of the corresponding multilingual data from the information recording medium.

[0577] The server processes this data using Python and generates real-time guidance data. This allows for immediate tourist information to be provided to mobile devices. Furthermore, to respond to natural language inquiries from users, the server generates responses using generative AI models (e.g., OpenAI's GPT-4) and sends them to the mobile devices.

[0578] For the remote tourism experience, a server generates video data of the tourist destination and transmits the video in real time using Apache Kafka. This allows users to enjoy the tourist destination even without being physically present.

[0579] For example, if a user asks a question about the Colosseum in Rome, the smartphone will pinpoint their location and provide optimal route information according to their language settings. Also, if a user asks, "Tell me about the history of the Colosseum," the AI ​​will provide detailed historical information as a response.

[0580] An example of a prompt to the generating AI would be: "The user wants to learn about the history of the Colosseum. Please explain in detail the important facts and historical background of the Colosseum." Based on this sentence, the generating AI analyzes the information and generates an appropriate response.

[0581] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0582] Step 1:

[0583] The device acquires location data using a GPS sensor and sends this data, along with the user's language settings, to the server. The input is location data and language settings data, and the output is the process of sending these to the server.

[0584] Step 2:

[0585] The server accesses the information recording medium based on the received location data and language setting data, and retrieves the corresponding multilingual information. The input is location data and language setting data, and the output is the retrieval of multilingual information.

[0586] Step 3:

[0587] The server processes the acquired multilingual information into real-time guidance data and transmits it to the terminal. The input is multilingual information, and the output is processed real-time guidance data.

[0588] Step 4:

[0589] The user enters a question into the terminal using natural language. The input is a question in natural language, and the output is sent to the server.

[0590] Step 5:

[0591] The server analyzes the received question and generates a response using a generative AI model. The input is a natural language question, and the output is the generated response.

[0592] Step 6:

[0593] The generated response is sent from the server to the terminal and displayed to the user. The input is the generated response, and the output is the display on the terminal.

[0594] Step 7:

[0595] The server generates video data for the remote sightseeing experience and transmits the video to the terminal in real time using Apache Kafka. The input is tourist destination information, and the output is the transmitted video data in real time.

[0596] Step 8:

[0597] Users can view detailed information about tourist destinations via their devices, based on responses provided by a generated AI model. The input consists of real-time guidance data and generated responses, while the output is tourist information provided to the user.

[0598] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0599] One embodiment of the present invention provides a system that offers real-time, multilingual tourist information to users visiting tourist destinations using a mobile terminal, and further recognizes the user's emotions and adjusts the response accordingly. This system consists of a mobile terminal, a server, a database, and an emotion engine.

[0600] When a user launches an application on their mobile device, the device obtains its current location via GPS and sends it to the server along with its language settings. The server then retrieves relevant tourist information from its database in multiple languages ​​and provides the user with real-time guide information. In this initial stage, the application also transmits the user's voice and facial expressions to an emotion engine via the camera and microphone to analyze the user's emotional state.

[0601] The emotion engine adjusts the information and responses it provides based on the analyzed emotion data. For example, if the user is excited, it will provide more detailed and engaging information, while if the user is tired, it will prioritize providing concise and relaxing information.

[0602] Furthermore, when users input specific questions about tourist destinations via their devices, the emotion engine adjusts the data based on emotional information before inputting it into the generating AI. This allows the generating AI to produce the most relevant response for the user. This response is then sent to the device and presented to the user in either voice or text.

[0603] If a user requests a remote sightseeing experience, the server generates and streams content optimized for the user's state based on emotional data analyzed by the emotion engine. This allows users to fully enjoy the attractions of tourist destinations from the comfort of their own homes.

[0604] For example, if a user visits a historical site and shows great interest, the emotion engine can analyze their excitement, and the server can prepare and deliver VR content that more deeply conveys the atmosphere of the place. This makes the sightseeing experience highly personalized and improves the user experience.

[0605] The following describes the processing flow.

[0606] Step 1:

[0607] The user launches an application on their mobile device. The device obtains its current location information from its built-in GPS and checks the device's language settings.

[0608] Step 2:

[0609] The device sends this location information and language setting information to the server.

[0610] Step 3:

[0611] The server searches the database based on the received information and retrieves relevant tourist destination information in multiple languages.

[0612] Step 4:

[0613] The server organizes the acquired tourist destination information and transmits it to the terminal in real time. The terminal then presents this information to the user.

[0614] Step 5:

[0615] The device sends the user's voice data and camera footage to an emotion engine for emotional analysis.

[0616] Step 6:

[0617] The emotion engine determines the user's emotional state and sends the result to the server.

[0618] Step 7:

[0619] Based on the analyzed sentiment data, the server adjusts the tourist information it provides, selecting more detailed or different information to send to the terminal.

[0620] Step 8:

[0621] The user inputs a question using natural language via a device. The device then sends the question to the server.

[0622] Step 9:

[0623] The server receives a question and requests the generative AI to analyze it while referring to the emotion engine's data. The generative AI generates a response and returns it to the server.

[0624] Step 10:

[0625] The server sends the generated response to the terminal, which then provides it to the user via voice or text.

[0626] Step 11:

[0627] If a user requests a remote sightseeing experience, the device sends a request to the server while referencing emotional data.

[0628] Step 12:

[0629] The server generates optimal remote content based on the user's emotions and streams it to the device.

[0630] Step 13:

[0631] The device plays the received content, allowing the user to experience the appeal of the tourist destination.

[0632] (Example 2)

[0633] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0634] While it was possible to provide real-time, multilingual guide information to mobile users visiting tourist destinations using conventional technology, methods for delivering information that took into account the user's emotional state were not in place. Therefore, the user experience was not sufficiently personalized, making it difficult to improve satisfaction. Furthermore, there is a need to highly customize the tourist experience to suit the user's emotions, even in remote environments.

[0635] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0636] In this invention, the server includes means for processing multilingual information of relevant locations based on received data and sentiment analysis results; means for providing the acquired information in real time and analyzing and adjusting the user's emotional state; and means for creating prompt sentences that take sentiment analysis results into account using a generative AI and generating responses to questions. This enables personalized real-time information provision and a highly customized tourism experience that responds to the user's emotional state.

[0637] A "mobile terminal" is a small, portable communication device that enables users to acquire location information and send and receive data.

[0638] "Location information" refers to geographical data acquired by a mobile device to determine its current location.

[0639] "Language setting information" refers to information used to specify the language a user will use, and is data used to determine the language in which information is provided.

[0640] A "server" is a centralized processing device that handles information processing and management, communicates with databases, and has the function of responding to requests from clients.

[0641] "Multilingual information" refers to information translated into different languages, and is data that enables the provision of information to users who speak different languages.

[0642] "Emotion analysis" is a technology that analyzes and identifies a user's emotional state from their voice and facial expressions, and is applied to optimize the information provided.

[0643] "Generative AI" is a technology that uses artificial intelligence models to generate natural language responses based on input data, and is a system for providing interactive responses.

[0644] A "prompt message" is text data input to a generation AI, and it is a sentence containing instructions or information to generate the desired response.

[0645] "Real-time" refers to events or processes occurring simultaneously with or very close to their occurrence, meaning that information is provided without delay.

[0646] This invention realizes a system that provides a personalized user experience by combining a mobile terminal, a server, a data collection function, and an emotion analysis engine.

[0647] Mobile terminal operation

[0648] The user launches a dedicated application on a mobile device such as a smartphone or tablet. The device uses its built-in GPS module to obtain the user's location information and also checks the language settings the user has configured. The obtained location information and language settings are transmitted to the server via wireless communication.

[0649] Server Processing

[0650] The server retrieves multilingual information about relevant locations from a database based on the received location data. This database uses a relational database management system such as MySQL or PostgreSQL. The retrieved information is analyzed by an emotion analysis engine according to the user's emotional state and processed appropriately. The server provides this processed information to the terminal in real time.

[0651] Use of sentiment analysis

[0652] The device captures facial expressions with its camera and collects audio with its microphone. This data is sent to an emotion analysis engine to determine the user's emotional state. Emotion analysis uses an emotion recognition API (e.g., an emotion recognition system using common nouns), and the information provided is adjusted depending on whether the user is excited or tired.

[0653] Use of Generative AI Models

[0654] When a user enters a question in natural language into the device, the server generates a prompt that takes sentiment analysis into account and sends it to a generative AI model. A generative language model using common nouns is used as the generative AI model. The generative AI generates a response to the question, which the server then sends to the device.

[0655] Specific example

[0656] For example, if a user visits a historical site in Japan and asks, "Tell me an interesting story about the construction of this temple," the device's sentiment analysis engine evaluates the user's level of excitement. The server sends a prompt message to the generating AI model saying, "The user is very interested, please elaborate on any anecdotes or interesting facts about its construction." The generating AI model follows the prompt and generates a response containing detailed historical information and anecdotes, which it then provides to the user via the device.

[0657] In this way, users can obtain a wealth of information during their visit and enjoy a highly customized tourism experience even in a remote environment.

[0658] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0659] Step 1:

[0660] The user launches an application on a mobile device. The device uses its built-in GPS function to obtain its current location and confirms the language information set by the user. The input is the user's current location and selected language, and this information is compiled into a data packet within the device. As output, the device prepares the configured data packet.

[0661] Step 2:

[0662] The terminal sends the prepared data packets to the server via secure wireless communication. The input is the data packets prepared by the terminal, and the destination is the server. As output, the terminal accurately sends the data packets to the server.

[0663] Step 3:

[0664] The server analyzes data packets received from the terminal and extracts location and language information. The input is data packets from the terminal, and through analysis, two elements are extracted. As output, the server obtains location and language information.

[0665] Step 4:

[0666] The server retrieves multilingual information for related locations from the data aggregation mechanism based on the extracted location information. A DBMS is used to extract the relevant information in multiple languages. The input is location information, and the server obtains multilingual information for related locations as output.

[0667] Step 5:

[0668] The server adjusts the information based on the acquired multilingual information and the user's sentiment analysis results. Using a sentiment analysis engine, it generates personalized information that takes the user's mental state into account. The input is multilingual information and sentiment data, and the output is adjusted information. Specifically, it provides detailed information to excited users and concise information to users feeling fatigued.

[0669] Step 6:

[0670] The terminal receives pre-configured information from the server and displays it to the user in real time. The input is pre-configured information from the server, and the output is the information displayed on the user's screen.

[0671] Step 7:

[0672] The user inputs a question using natural language via a device. The input question is captured as text data by the device. The captured question data is prepared as output.

[0673] Step 8:

[0674] The sentiment analysis engine analyzes the user's mental state based on their input and generates prompts accordingly. The input consists of the user's question and sentiment data, and the output is a prompt based on the question.

[0675] Step 9:

[0676] The server sends the generated prompt to the AI ​​model and receives an appropriate response. The input is the prompt, which is sent to the AI ​​model. The output is the response data from the AI ​​model.

[0677] Step 10:

[0678] The server sends the response obtained from the generated AI model to the terminal. The input is the model's response, and the output is data sent to the terminal.

[0679] Step 11:

[0680] The terminal receives a response from the server and presents it to the user in audio or text format. The input is the response from the server, which is presented to the user as output, completing the response to the user's question.

[0681] (Application Example 2)

[0682] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0683] Traditional tourism information systems provide uniform information without considering the user's emotional state, making it difficult to offer a personalized experience tailored to the user's interests and circumstances. Furthermore, generating appropriate responses based on the user's emotions while providing real-time multilingual support is challenging. Additionally, there is a lack of means to optimize the virtual store experience according to the user's emotions.

[0684] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0685] In this invention, the server includes means for acquiring emotional data via the camera and microphone of a mobile information device and analyzing said emotional data; means for adjusting the information and responses provided based on the analyzed emotional data; and means for generating content to optimize the user experience in a virtual store based on the emotional data and presenting said content to the user. This enables personalized information provision and optimization of the virtual experience according to the user's emotional state.

[0686] A "mobile information device" is a mobile terminal that has the function of acquiring location information and emotional data and transmitting this information to a server.

[0687] An "information processing device" is a machine that acquires and processes multilingual regional information based on received information and provides it to the user in real time.

[0688] "Emotional data" refers to information about a user's emotions, extracted from their facial expressions, voice, etc., and is used to analyze the user's psychological state.

[0689] "Analysis means" refers to technology that analyzes the user's emotional state based on acquired emotional data and adjusts the information provided accordingly.

[0690] "Generative AI" is an artificial intelligence technology that generates the optimal response to inquiries using natural language, while taking into account the user's emotional data.

[0691] A "virtual store" is a store-style platform set up in a virtual space, an online commercial facility that provides users with a realistic product experience.

[0692] "Means of generating content" refers to technologies that create digital information to produce visually and aurally rich experiences based on user emotional data.

[0693] To put this invention into practice, first, smart glasses or other mobile information devices are used. These information terminals have built-in cameras and microphones, making it possible to capture the user's facial expressions and voice in real time.

[0694] The server receives location information, language setting information, and sentiment data transmitted from these terminals and processes them using an information processing device. Based on the received location information, it retrieves multilingual information for the relevant region from a database. In addition, the sentiment data is analyzed using sentiment analysis tools to determine the user's current emotional state.

[0695] Based on the analysis results, the server provides the user with the most relevant information and generates real-time guidance. In this process, the generating AI model responds to natural language queries using specific prompt phrases. An example of such a prompt phrase is, "Please suggest products to recommend when the user is excited."

[0696] Furthermore, when a user visits a virtual store, personalized content is generated based on emotional data. This content is designed using a generative AI model to provide an optimal experience tailored to the user's preferences and emotional state. For example, it overlays visually colorful product images with product information that has a relaxing effect, creating an experience that is uniquely suited to each user.

[0697] This allows users to receive information tailored to their emotional state at any given time, no matter where they are, resulting in a richer and more personalized experience.

[0698] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0699] Step 1:

[0700] The user wears smart glasses and launches the application. The device uses a camera and microphone to capture the user's facial expressions and voice, collecting this data as input. The emotional data obtained here forms the basis for subsequent analysis.

[0701] Step 2:

[0702] The device sends its location information, collected sentiment data, and language setting information to the server. The server uses the location information to retrieve multilingual information from its database. The output of this process is tourist information related to the user's location.

[0703] Step 3:

[0704] The server uses an emotion analysis engine to analyze the emotional data received from the terminal. The input facial expressions and voice data are analyzed, and the user's emotional state is output. Based on the analysis results, the information and content to be provided are determined.

[0705] Step 4:

[0706] The server uses a generative AI model to create prompts that take into account the user's emotional state. An example of such a prompt might be, "Please suggest tourist destinations to recommend when the user is excited." Based on the input emotional data and the inquiry, the optimal response is generated.

[0707] Step 5:

[0708] The generated responses and content are sent to the device. The device displays the information and provides it to the user in audio or text format. Information is dynamically displayed to match the user's field of view, providing personalized guide information and a virtual store experience.

[0709] Step 6:

[0710] When a user chooses to enter a virtual store, the server generates content to optimize the store experience based on emotional data. The data used reflects the user's preferences and is tailored to enrich the user's experience visually and aurally. The output is personalized visual and auditory content for the virtual store.

[0711] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0712] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0713] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0714] [Fourth Embodiment]

[0715] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0716] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0717] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0718] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0719] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0720] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0721] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0722] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0723] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0724] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0725] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0726] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0727] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0728] One embodiment of the present invention relates to a system that provides real-time, multilingual tourist information to users visiting tourist destinations using mobile terminals. This system mainly consists of mobile terminals, a server, and a database.

[0729] The user launches an application installed on their mobile device. The device first obtains its current location information via GPS and simultaneously collects the device's language setting information. This information is sent to a server, which retrieves relevant tourist destination information from its database in multiple languages ​​based on the received information.

[0730] The server processes the acquired tourist destination information in real time and provides it to the device as guide information. This allows users to receive multilingual guidance about the history and culture of tourist destinations through their devices.

[0731] Furthermore, when a user enters a specific question about a tourist destination via their mobile device, that question is sent to the server. The server uses a generative AI to analyze the question and generate a response. This response is sent back to the user's device and displayed in a chat format. This allows users to obtain detailed information tailored to their individual interests.

[0732] Furthermore, even when users are in remote locations, the system provides a remote tourism experience. The server generates and streams content that conveys the appeal of tourist destinations via video display devices. In this way, users can experience the charm of tourist destinations without actually visiting them.

[0733] As a concrete example, consider a scenario where a user visits a historical site with a mobile device. Upon launching the app, the server provides real-time, multilingual guidance to the user, detailing the site's history and points of interest. Furthermore, if the user desires additional information about a specific building or ruin, they can directly input questions and obtain more in-depth information on the spot.

[0734] This system allows tourists to obtain a wealth of information even within a limited time, enabling them to gain a deeper understanding of the essence of their destination.

[0735] The following describes the processing flow.

[0736] Step 1:

[0737] The user launches the application on their mobile device. The device obtains its current location using its built-in GPS and also checks the device's language settings.

[0738] Step 2:

[0739] The device sends the acquired location information and language setting information to the server. The server receives this information and retrieves tourist destination information related to the corresponding location from its database.

[0740] Step 3:

[0741] The server organizes multilingual tourist information according to the user's language settings and sends it to the terminal in real time. The terminal presents the received information to the user in audio or text format.

[0742] Step 4:

[0743] If a user wants more detailed information about a tourist destination, they enter their question through the chatbot interface on their device. The device then sends the entered question to the server.

[0744] Step 5:

[0745] The server passes the received question to the generating AI, which analyzes the question. Based on the analysis, the generating AI generates an appropriate response and returns it to the server.

[0746] Step 6:

[0747] The server sends back a response generated by the AI ​​to the terminal. The terminal displays the response to the user and provides it in audio format if necessary.

[0748] Step 7:

[0749] If a user requests a remote sightseeing experience, the device sends this request to the server. The server prepares VR experiences and video content of the tourist destination and streams them to the device.

[0750] Step 8:

[0751] The device displays received VR experiences or video content, allowing users to remotely experience the charm of a region.

[0752] (Example 1)

[0753] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0754] In recent years, there has been a growing demand for real-time access to detailed, multilingual information when visiting tourist destinations, as well as the ability to receive information tailored to individual interests. Furthermore, there is a desire to enjoy the allure of tourist destinations through virtual experiences without actually visiting the location. However, conventional systems have not adequately met these needs.

[0755] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0756] In this invention, the server includes means for a mobile terminal to acquire location information and transmit data including said location information and language setting information; information processing means for acquiring multilingual information of a relevant location from an information storage device based on the received data; and means for processing the acquired multilingual information and providing guidance information to the mobile terminal in real time. As a result, users can receive real-time information including multilingual support and individual question answering.

[0757] A "mobile terminal" refers to a portable device that can communicate data while moving between locations, and is an electronic device equipped with GPS and communication functions.

[0758] "Location information" refers to data that indicates the geographical location of a mobile device, and is expressed as numerical values ​​of latitude and longitude.

[0759] "Language setting information" is data that indicates the language set on the mobile device, and is used by the system to determine in which language information will be provided.

[0760] "Data transmission means" refers to a function or device for transmitting data from a mobile terminal to a server, and plays the role of transferring information through a communication protocol.

[0761] An "information storage device" is a device that holds multilingual information and other data, and functions as a database system.

[0762] "Information processing device means" refers to a function or device on a server that analyzes and processes data and searches, acquires, and generates necessary information.

[0763] "Guidance information" refers to data that includes detailed information about the history, culture, and other aspects of tourist destinations that users are interested in, and is used as an explanation provided to the user.

[0764] "Generative AI" refers to a technology that uses artificial intelligence models to analyze a user's natural language questions and generate appropriate answers.

[0765] A "response" is an answer automatically generated by a generation AI in response to a user's question, and is presented to the user.

[0766] A "video display device" refers to a device for displaying visual content, providing a means for users to visually receive video information.

[0767] "Video distribution" refers to a method of transmitting videos or video data to users, enabling them to view them in real time or on demand.

[0768] This invention relates to a system that provides real-time, multilingual tourist information to users visiting tourist destinations via mobile terminals. This system mainly consists of mobile terminals, a server, and an information storage device.

[0769] The user launches an application installed on their mobile device, and the device uses its built-in GPS function to obtain its current location. Simultaneously, the device's language settings are also collected. This information is transmitted from the mobile device to the server. A secure protocol is used for communication, such as HTTPS.

[0770] The server uses the received location and language setting information to retrieve multilingual information about the relevant tourist destination from the information storage device. A database management system is used for this information processing, and information is retrieved via SQL queries. The server processes the retrieved information and immediately transmits guidance information to the mobile terminal. This processing includes data format conversion and template processing for multilingual support.

[0771] Furthermore, when a user asks a question about a tourist destination using natural language via their device, the question is sent to the server. The server uses a generative AI model and natural language processing techniques such as GPT to analyze the question and generate an appropriate response. The generated response is sent to the mobile device, which displays it in a visual format. This allows users to receive information tailored to their individual interests in real time.

[0772] As a concrete example, consider a scenario where a user visits a historical site. When the user enters a prompt such as "Tell me about the history of this place," the server generates relevant historical information and provides detailed, multilingual guidance.

[0773] Furthermore, the server generates and streams visual information to provide remote users with a virtual sightseeing experience via a video display device. In this process, for example, by using a cloud-based video streaming service, it becomes possible to experience the impression of a tourist destination without actually visiting the location.

[0774] In this way, users can easily obtain multilingual tourist information through their mobile devices and deepen their detailed understanding of tourist destinations.

[0775] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0776] Step 1:

[0777] The user launches an application on a mobile device. The device uses its built-in GPS function to obtain its current location. It also obtains the device's language setting information. The input consists of the user's location and language setting from the device; based on this, the device sends this data to the server. The output is a dataset containing location information and language settings.

[0778] Step 2:

[0779] The server retrieves relevant multilingual tourist information from an information storage device based on location and language setting information received from the terminal. The input is a dataset received from the terminal, and the server uses a database management system to execute SQL queries and extract relevant information. The output is multilingual information about the selected tourist destination.

[0780] Step 3:

[0781] The server processes acquired tourist destination information in real time. It receives multilingual tourist information as input, formats it according to the user's language settings, and prepares it in an appropriate format (e.g., HTML or JSON). The output is formatted multilingual information. The server then transmits this information to mobile devices.

[0782] Step 4:

[0783] The user inputs questions about tourist destinations in natural language via a terminal. The input is the user's question in natural language. The terminal sends this question to the server. The output is the question data sent to the server.

[0784] Step 5:

[0785] The server analyzes received questions using a generative AI model. The input is a natural language question received from the user. The generative AI model understands the question and generates an appropriate response based on the relevant information. The output is the generated response data.

[0786] Step 6:

[0787] The server sends response data to the mobile terminal. The terminal receives this response and displays it on the screen in a chat format. The input is the response data obtained from the generative AI model, and the output is the visual information displayed to the user.

[0788] Step 7:

[0789] The server generates content to provide a virtual sightseeing experience to remote users via a video display device. The input includes visual information about the tourist destination, which is used to generate video data suitable for streaming. The output is streamable video data. The server streams this video to the user's terminal, allowing the user to virtually experience the tourist destination.

[0790] (Application Example 1)

[0791] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0792] In the modern tourism sector, providing real-time, multilingual tourism information is crucial. However, existing systems suffer from shortcomings in multilingual support and low-quality remote tourism experiences. Furthermore, few systems can suggest in real time which information is most useful to a user based on their location and interests.

[0793] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0794] In this invention, the server includes means for determining the user's location based on location data and presenting the user with optimal route information; means for generating tourist destination information as video data in a remote environment and transmitting the data to the user as video; and means for receiving inquiries in natural language, generating responses to those inquiries using a generation AI, and transmitting the responses to a mobile device. As a result, users can obtain a fulfilling tourist experience without actually visiting the locations and can receive optimal information in real time while traveling.

[0795] A "mobile device" is a type of electronic device that a user can carry and use, and is a terminal for processing location data and other information.

[0796] "Location data" refers to information that indicates the current geographical location of a mobile device, and is acquired using technologies such as GPS.

[0797] "Language setting data" refers to information about the display language and audio language that the user has pre-selected on the mobile device.

[0798] An "information recording medium" is a database that stores digital data and manages it so that it can be searched and retrieved as needed.

[0799] "Computing device means" refers to a central processing unit or server for processing information, and is responsible for acquiring and processing multilingual data.

[0800] "Real-time navigation data" refers to location-specific navigation information, including multilingual information, that is provided to users instantly.

[0801] "Natural language" refers to the forms of language that humans use in everyday conversation and writing, and that are expressed in text or audio.

[0802] "Generative AI" is an artificial intelligence algorithm that aims to analyze input data and automatically generate natural-sounding responses.

[0803] "Video data" refers to digital signals, including videos and still images, that are used as visual information.

[0804] "Video transmission" is the process of transferring video data to a receiving device such as a mobile device.

[0805] An "inquiry" is a question or request that a user sends in natural language seeking specific information.

[0806] The system for implementing this invention consists of a mobile device such as a smartphone, a server for data processing, and a database for providing information. First, the mobile device acquires location data using GPS and transmits it to the server along with the user's language setting data. Based on this data, the server processes the acquisition of the corresponding multilingual data from the information recording medium.

[0807] The server processes this data using Python and generates real-time guidance data. This allows for immediate tourist information to be provided to mobile devices. Furthermore, to respond to natural language inquiries from users, the server generates responses using generative AI models (e.g., OpenAI's GPT-4) and sends them to the mobile devices.

[0808] For the remote tourism experience, a server generates video data of the tourist destination and transmits the video in real time using Apache Kafka. This allows users to enjoy the tourist destination even without being physically present.

[0809] For example, if a user asks a question about the Colosseum in Rome, the smartphone will pinpoint their location and provide optimal route information according to their language settings. Also, if a user asks, "Tell me about the history of the Colosseum," the AI ​​will provide detailed historical information as a response.

[0810] An example of a prompt to the generating AI would be: "The user wants to learn about the history of the Colosseum. Please explain in detail the important facts and historical background of the Colosseum." Based on this sentence, the generating AI analyzes the information and generates an appropriate response.

[0811] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0812] Step 1:

[0813] The device acquires location data using a GPS sensor and sends this data, along with the user's language settings, to the server. The input is location data and language settings data, and the output is the process of sending these to the server.

[0814] Step 2:

[0815] The server accesses the information recording medium based on the received location data and language setting data, and retrieves the corresponding multilingual information. The input is location data and language setting data, and the output is the retrieval of multilingual information.

[0816] Step 3:

[0817] The server processes the acquired multilingual information into real-time guidance data and transmits it to the terminal. The input is multilingual information, and the output is processed real-time guidance data.

[0818] Step 4:

[0819] The user enters a question into the terminal using natural language. The input is a question in natural language, and the output is sent to the server.

[0820] Step 5:

[0821] The server analyzes the received question and generates a response using a generative AI model. The input is a natural language question, and the output is the generated response.

[0822] Step 6:

[0823] The generated response is sent from the server to the terminal and displayed to the user. The input is the generated response, and the output is the display on the terminal.

[0824] Step 7:

[0825] The server generates video data for the remote sightseeing experience and transmits the video to the terminal in real time using Apache Kafka. The input is tourist destination information, and the output is the transmitted video data in real time.

[0826] Step 8:

[0827] Users can view detailed information about tourist destinations via their devices, based on responses provided by a generated AI model. The input consists of real-time guidance data and generated responses, while the output is tourist information provided to the user.

[0828] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0829] One embodiment of the present invention provides a system that offers real-time, multilingual tourist information to users visiting tourist destinations using a mobile terminal, and further recognizes the user's emotions and adjusts the response accordingly. This system consists of a mobile terminal, a server, a database, and an emotion engine.

[0830] When a user launches an application on their mobile device, the device obtains its current location via GPS and sends it to the server along with its language settings. The server then retrieves relevant tourist information from its database in multiple languages ​​and provides the user with real-time guide information. In this initial stage, the application also transmits the user's voice and facial expressions to an emotion engine via the camera and microphone to analyze the user's emotional state.

[0831] The emotion engine adjusts the information and responses it provides based on the analyzed emotion data. For example, if the user is excited, it will provide more detailed and engaging information, while if the user is tired, it will prioritize providing concise and relaxing information.

[0832] Furthermore, when users input specific questions about tourist destinations via their devices, the emotion engine adjusts the data based on emotional information before inputting it into the generating AI. This allows the generating AI to produce the most relevant response for the user. This response is then sent to the device and presented to the user in either voice or text.

[0833] If a user requests a remote sightseeing experience, the server generates and streams content optimized for the user's state based on emotional data analyzed by the emotion engine. This allows users to fully enjoy the attractions of tourist destinations from the comfort of their own homes.

[0834] For example, if a user visits a historical site and shows great interest, the emotion engine can analyze their excitement, and the server can prepare and deliver VR content that more deeply conveys the atmosphere of the place. This makes the sightseeing experience highly personalized and improves the user experience.

[0835] The following describes the processing flow.

[0836] Step 1:

[0837] The user launches an application on their mobile device. The device obtains its current location information from its built-in GPS and checks the device's language settings.

[0838] Step 2:

[0839] The device sends this location information and language setting information to the server.

[0840] Step 3:

[0841] The server searches the database based on the received information and retrieves relevant tourist destination information in multiple languages.

[0842] Step 4:

[0843] The server organizes the acquired tourist destination information and transmits it to the terminal in real time. The terminal then presents this information to the user.

[0844] Step 5:

[0845] The device sends the user's voice data and camera footage to an emotion engine for emotional analysis.

[0846] Step 6:

[0847] The emotion engine determines the user's emotional state and sends the result to the server.

[0848] Step 7:

[0849] Based on the analyzed sentiment data, the server adjusts the tourist information it provides, selecting more detailed or different information to send to the terminal.

[0850] Step 8:

[0851] The user inputs a question using natural language via a device. The device then sends the question to the server.

[0852] Step 9:

[0853] The server receives a question and requests the generative AI to analyze it while referring to the emotion engine's data. The generative AI generates a response and returns it to the server.

[0854] Step 10:

[0855] The server sends the generated response to the terminal, which then provides it to the user via voice or text.

[0856] Step 11:

[0857] If a user requests a remote sightseeing experience, the device sends a request to the server while referencing emotional data.

[0858] Step 12:

[0859] The server generates optimal remote content based on the user's emotions and streams it to the device.

[0860] Step 13:

[0861] The device plays the received content, allowing the user to experience the appeal of the tourist destination.

[0862] (Example 2)

[0863] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0864] While it was possible to provide real-time, multilingual guide information to mobile users visiting tourist destinations using conventional technology, methods for delivering information that took into account the user's emotional state were not in place. Therefore, the user experience was not sufficiently personalized, making it difficult to improve satisfaction. Furthermore, there is a need to highly customize the tourist experience to suit the user's emotions, even in remote environments.

[0865] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0866] In this invention, the server includes means for processing multilingual information of relevant locations based on received data and sentiment analysis results; means for providing the acquired information in real time and analyzing and adjusting the user's emotional state; and means for creating prompt sentences that take sentiment analysis results into account using a generative AI and generating responses to questions. This enables personalized real-time information provision and a highly customized tourism experience that responds to the user's emotional state.

[0867] A "mobile terminal" is a small, portable communication device that enables users to acquire location information and send and receive data.

[0868] "Location information" refers to geographical data acquired by a mobile device to determine its current location.

[0869] "Language setting information" refers to information used to specify the language a user will use, and is data used to determine the language in which information is provided.

[0870] A "server" is a centralized processing device that handles information processing and management, communicates with databases, and has the function of responding to requests from clients.

[0871] "Multilingual information" refers to information translated into different languages, and is data that enables the provision of information to users who speak different languages.

[0872] "Emotion analysis" is a technology that analyzes and identifies a user's emotional state from their voice and facial expressions, and is applied to optimize the information provided.

[0873] "Generative AI" is a technology that uses artificial intelligence models to generate natural language responses based on input data, and is a system for providing interactive responses.

[0874] A "prompt message" is text data input to a generation AI, and it is a sentence containing instructions or information to generate the desired response.

[0875] "Real-time" refers to events or processes occurring simultaneously with or very close to their occurrence, meaning that information is provided without delay.

[0876] This invention realizes a system that provides a personalized user experience by combining a mobile terminal, a server, a data collection function, and an emotion analysis engine.

[0877] Mobile terminal operation

[0878] The user launches a dedicated application on a mobile device such as a smartphone or tablet. The device uses its built-in GPS module to obtain the user's location information and also checks the language settings the user has configured. The obtained location information and language settings are transmitted to the server via wireless communication.

[0879] Server Processing

[0880] The server retrieves multilingual information about relevant locations from a database based on the received location data. This database uses a relational database management system such as MySQL or PostgreSQL. The retrieved information is analyzed by an emotion analysis engine according to the user's emotional state and processed appropriately. The server provides this processed information to the terminal in real time.

[0881] Use of sentiment analysis

[0882] The device captures facial expressions with its camera and collects audio with its microphone. This data is sent to an emotion analysis engine to determine the user's emotional state. Emotion analysis uses an emotion recognition API (e.g., an emotion recognition system using common nouns), and the information provided is adjusted depending on whether the user is excited or tired.

[0883] Use of Generative AI Models

[0884] When a user enters a question in natural language into the device, the server generates a prompt that takes sentiment analysis into account and sends it to a generative AI model. A generative language model using common nouns is used as the generative AI model. The generative AI generates a response to the question, which the server then sends to the device.

[0885] Specific example

[0886] For example, if a user visits a historical site in Japan and asks, "Tell me an interesting story about the construction of this temple," the device's sentiment analysis engine evaluates the user's level of excitement. The server sends a prompt message to the generating AI model saying, "The user is very interested, please elaborate on any anecdotes or interesting facts about its construction." The generating AI model follows the prompt and generates a response containing detailed historical information and anecdotes, which it then provides to the user via the device.

[0887] In this way, users can obtain a wealth of information during their visit and enjoy a highly customized tourism experience even in a remote environment.

[0888] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0889] Step 1:

[0890] The user launches an application on a mobile device. The device uses its built-in GPS function to obtain its current location and confirms the language information set by the user. The input is the user's current location and selected language, and this information is compiled into a data packet within the device. As output, the device prepares the configured data packet.

[0891] Step 2:

[0892] The terminal sends the prepared data packets to the server via secure wireless communication. The input is the data packets prepared by the terminal, and the destination is the server. As output, the terminal accurately sends the data packets to the server.

[0893] Step 3:

[0894] The server analyzes data packets received from the terminal and extracts location and language information. The input is data packets from the terminal, and through analysis, two elements are extracted. As output, the server obtains location and language information.

[0895] Step 4:

[0896] The server retrieves multilingual information for related locations from the data aggregation mechanism based on the extracted location information. A DBMS is used to extract the relevant information in multiple languages. The input is location information, and the server obtains multilingual information for related locations as output.

[0897] Step 5:

[0898] The server adjusts the information based on the acquired multilingual information and the user's sentiment analysis results. Using a sentiment analysis engine, it generates personalized information that takes the user's mental state into account. The input is multilingual information and sentiment data, and the output is adjusted information. Specifically, it provides detailed information to excited users and concise information to users feeling fatigued.

[0899] Step 6:

[0900] The terminal receives pre-configured information from the server and displays it to the user in real time. The input is pre-configured information from the server, and the output is the information displayed on the user's screen.

[0901] Step 7:

[0902] The user inputs a question using natural language via a device. The input question is captured as text data by the device. The captured question data is prepared as output.

[0903] Step 8:

[0904] The sentiment analysis engine analyzes the user's mental state based on their input and generates prompts accordingly. The input consists of the user's question and sentiment data, and the output is a prompt based on the question.

[0905] Step 9:

[0906] The server sends the generated prompt to the AI ​​model and receives an appropriate response. The input is the prompt, which is sent to the AI ​​model. The output is the response data from the AI ​​model.

[0907] Step 10:

[0908] The server sends the response obtained from the generated AI model to the terminal. The input is the model's response, and the output is data sent to the terminal.

[0909] Step 11:

[0910] The terminal receives a response from the server and presents it to the user in audio or text format. The input is the response from the server, which is presented to the user as output, completing the response to the user's question.

[0911] (Application Example 2)

[0912] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0913] Traditional tourism information systems provide uniform information without considering the user's emotional state, making it difficult to offer a personalized experience tailored to the user's interests and circumstances. Furthermore, generating appropriate responses based on the user's emotions while providing real-time multilingual support is challenging. Additionally, there is a lack of means to optimize the virtual store experience according to the user's emotions.

[0914] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0915] In this invention, the server includes means for acquiring emotional data via the camera and microphone of a mobile information device and analyzing said emotional data; means for adjusting the information and responses provided based on the analyzed emotional data; and means for generating content to optimize the user experience in a virtual store based on the emotional data and presenting said content to the user. This enables personalized information provision and optimization of the virtual experience according to the user's emotional state.

[0916] A "mobile information device" is a mobile terminal that has the function of acquiring location information and emotional data and transmitting this information to a server.

[0917] An "information processing device" is a machine that acquires and processes multilingual regional information based on received information and provides it to the user in real time.

[0918] "Emotional data" refers to information about a user's emotions, extracted from their facial expressions, voice, etc., and is used to analyze the user's psychological state.

[0919] "Analysis means" refers to technology that analyzes the user's emotional state based on acquired emotional data and adjusts the information provided accordingly.

[0920] "Generative AI" is an artificial intelligence technology that generates the optimal response to inquiries using natural language, while taking into account the user's emotional data.

[0921] A "virtual store" is a store-style platform set up in a virtual space, an online commercial facility that provides users with a realistic product experience.

[0922] "Means of generating content" refers to technologies that create digital information to produce visually and aurally rich experiences based on user emotional data.

[0923] To put this invention into practice, first, smart glasses or other mobile information devices are used. These information terminals have built-in cameras and microphones, making it possible to capture the user's facial expressions and voice in real time.

[0924] The server receives location information, language setting information, and sentiment data transmitted from these terminals and processes them using an information processing device. Based on the received location information, it retrieves multilingual information for the relevant region from a database. In addition, the sentiment data is analyzed using sentiment analysis tools to determine the user's current emotional state.

[0925] Based on the analysis results, the server provides the user with the most relevant information and generates real-time guidance. In this process, the generating AI model responds to natural language queries using specific prompt phrases. An example of such a prompt phrase is, "Please suggest products to recommend when the user is excited."

[0926] Furthermore, when a user visits a virtual store, personalized content is generated based on emotional data. This content is designed using a generative AI model to provide an optimal experience tailored to the user's preferences and emotional state. For example, it overlays visually colorful product images with product information that has a relaxing effect, creating an experience that is uniquely suited to each user.

[0927] This allows users to receive information tailored to their emotional state at any given time, no matter where they are, resulting in a richer and more personalized experience.

[0928] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0929] Step 1:

[0930] The user wears smart glasses and launches the application. The device uses a camera and microphone to capture the user's facial expressions and voice, collecting this data as input. The emotional data obtained here forms the basis for subsequent analysis.

[0931] Step 2:

[0932] The device sends its location information, collected sentiment data, and language setting information to the server. The server uses the location information to retrieve multilingual information from its database. The output of this process is tourist information related to the user's location.

[0933] Step 3:

[0934] The server uses an emotion analysis engine to analyze the emotional data received from the terminal. The input facial expressions and voice data are analyzed, and the user's emotional state is output. Based on the analysis results, the information and content to be provided are determined.

[0935] Step 4:

[0936] The server uses a generative AI model to create prompts that take into account the user's emotional state. An example of such a prompt might be, "Please suggest tourist destinations to recommend when the user is excited." Based on the input emotional data and the inquiry, the optimal response is generated.

[0937] Step 5:

[0938] The generated responses and content are sent to the device. The device displays the information and provides it to the user in audio or text format. Information is dynamically displayed to match the user's field of view, providing personalized guide information and a virtual store experience.

[0939] Step 6:

[0940] When a user chooses to enter a virtual store, the server generates content to optimize the store experience based on emotional data. The data used reflects the user's preferences and is tailored to enrich the user's experience visually and aurally. The output is personalized visual and auditory content for the virtual store.

[0941] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0942] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0943] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0944] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0945] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0946] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0947] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0948] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0949] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0950] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0951] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0952] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0953] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0954] 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.

[0955] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0956] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0957] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0958] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0959] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0960] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0961] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0962] The following is further disclosed regarding the embodiments described above.

[0963] (Claim 1)

[0964] A means for a mobile terminal to acquire location information and transmit data including said location information and language setting information,

[0965] A server means that retrieves multilingual information of relevant locations from a database based on the received data,

[0966] A means for processing acquired multilingual information and providing real-time guide information to mobile terminals,

[0967] A server means that receives a question in natural language from a mobile terminal, generates a response to the question using generative AI, and transmits the response to the mobile terminal.

[0968] A system that includes this.

[0969] (Claim 2)

[0970] The system according to claim 1, which displays a response received by a mobile terminal and provides it to the user by voice or text.

[0971] (Claim 3)

[0972] The system according to claim 1, which generates content to provide a remote tourism experience to a user via a video display means and streams the content to the user.

[0973] "Example 1"

[0974] (Claim 1)

[0975] A means for a mobile terminal to acquire location information and transmit data including said location information and language setting information,

[0976] An information processing device means that acquires multilingual information of a relevant location from an information storage device based on the received data,

[0977] A means for processing acquired multilingual information and providing guidance information to mobile terminals in real time,

[0978] Information processing device means that receives a question in natural language from a mobile terminal, generates a response to the question using generative AI, and transmits the response to the mobile terminal.

[0979] A means of displaying responses received by a mobile terminal in a chat format and prompting the user for further questions,

[0980] A means for generating visual information to provide a virtual sightseeing experience to a user in a remote location via a video display device, and for distributing said visual information to the user as video,

[0981] A system that includes this.

[0982] (Claim 2)

[0983] The system according to claim 1, which presents the received response to the user visually or aurally, thereby enabling two-way communication.

[0984] (Claim 3)

[0985] The system according to claim 1, wherein a terminal receives a video stream, enabling the user to virtually obtain an impression of a tourist destination without actually visiting the location.

[0986] "Application Example 1"

[0987] (Claim 1)

[0988] A means for a mobile device to acquire location data and transmit information including said location data and language setting data,

[0989] A computing device means that acquires multilingual data of a relevant location from an information recording medium based on the received information,

[0990] A means for processing acquired multilingual data and providing real-time guidance data to a mobile device,

[0991] A computing device means that receives a query in natural language from a mobile device, generates a response to the query using generative AI, and transmits the response to the mobile device.

[0992] A means to determine the user's location based on the acquired data and present the user with optimal route information,

[0993] A means for generating tourist destination information as video data in a remote environment and transmitting said data to the user as video,

[0994] A system that includes this.

[0995] (Claim 2)

[0996] The system according to claim 1, which determines the user's location based on location data and presents the user with optimal route information.

[0997] (Claim 3)

[0998] The system according to claim 1, which generates information for conducting a remote tourism experience through video data and transmits said information to the user via video.

[0999] "Example 2 of combining an emotion engine"

[1000] (Claim 1)

[1001] A means for a mobile terminal to acquire location information and transmit data including said location information and language setting information,

[1002] A server means that, based on the received data, acquires multilingual information of relevant locations from a data aggregation mechanism and processes the information based on sentiment analysis results,

[1003] A means for providing acquired multilingual information to mobile terminals in real time, analyzing the user's emotional state, and adjusting the information provided,

[1004] A server means that receives a question in natural language from a mobile terminal, creates a prompt sentence that takes into account the sentiment analysis results using a generative AI, generates a response to the question, and sends the response to the mobile terminal.

[1005] A system that includes this.

[1006] (Claim 2)

[1007] The system according to claim 1, which displays a response received by a mobile terminal and provides it to the user by voice or text.

[1008] (Claim 3)

[1009] The system according to claim 1, which generates optimized content based on the results of user emotion analysis via video display means and streams a remote sightseeing experience to the user.

[1010] "Application example 2 when combining with an emotional engine"

[1011] (Claim 1)

[1012] A means for a mobile information device to acquire location information and transmit information including said location information and language setting information,

[1013] Information processing device means that obtains multilingual information for the relevant region from a database based on the received information,

[1014] A means for processing acquired multilingual information and providing real-time guidance information to a mobile information device,

[1015] An analysis means for acquiring emotional data via the camera and microphone of a mobile information device and analyzing said emotional data,

[1016] Means for adjusting the information and responses provided based on analyzed emotional data,

[1017] Information processing device means that receives a query in natural language, generates a response to the query using generative AI, and transmits the response to a mobile information device.

[1018] A means for generating content to optimize the user experience in a virtual store based on emotional data, and for presenting said content to the user,

[1019] A system that includes this.

[1020] (Claim 2)

[1021] The system according to claim 1, which displays responses and content received by a mobile information device and provides them to the user by voice or text.

[1022] (Claim 3)

[1023] The system according to claim 1, which generates content to provide a user with a virtual store experience based on emotional data via a video display means, and streams the content to the user. [Explanation of Symbols]

[1024] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for a mobile terminal to acquire location information and transmit data including said location information and language setting information, A server means that retrieves multilingual information of relevant locations from a database based on the received data, A means for processing acquired multilingual information and providing real-time guide information to mobile terminals, A server means that receives a question in natural language from a mobile terminal, generates a response to the question using generative AI, and transmits the response to the mobile terminal. A system that includes this.

2. The system according to claim 1, which displays a response received by a mobile terminal and provides it to the user by voice or text.

3. The system according to claim 1, which generates content for providing a remote tourism experience to a user via a video display means and streams the content to the user.

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