system

Abstract

We provide the system. [Solution] Means for collecting user location information, A means of analyzing users' hobbies and preferences, Means for generating and providing content based on location information and hobby / preference information, A system that includes this.

Description

Technical Field

[0001] The technology of this 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] Currently, systems that provide appropriate content based on a user's location information and hobbies are limited, and in particular, technologies for updating and optimizing information in real time through interaction with the user are still in the development stage. Against this background, there is a demand for an integrated system that provides optimal content in real time based on a user's location information and hobbies, and further improves an information provision algorithm based on feedback from the user.

Means for Solving the Problems

[0005] To solve this problem, the present invention provides the following means: a system including means for collecting user location information, means for analyzing user hobby and preference information, and means for generating and providing content based on location information and hobby and preference information. Furthermore, by including means for analyzing conversations with the user and updating hobby and preference information, the system provides appropriate information based on the user's latest interests. In addition, by providing means for collecting user feedback and improving the information provision algorithm, the system provides a system that improves the quality of information provision.

[0006] "User" refers to an individual or organization that uses the system.

[0007] "Location information" refers to data that indicates the user's current geographical location.

[0008] "Hobby and preference information" refers to data that indicates a user's interests, concerns, and preferences.

[0009] "Analysis" is the process of organizing and analyzing data to reveal its meaning and patterns.

[0010] "Content" is a general term for the information and services provided to users.

[0011] "Generation" is the process of creating new content based on data and information.

[0012] "Providing" refers to the act of presenting generated content to the user.

[0013] "Dialogue" refers to the exchange of information between the user and the system.

[0014] "Feedback" is the act of users returning their evaluations and opinions on the information and content provided to the system.

[0015] The "information provision algorithm" refers to the calculation formula and procedure for generating and providing optimal content based on the location information and hobby orientation information of users.

[0016] "Improvement" is a process of adjustment and correction performed to improve the performance and functions of a system.

Brief Explanation of Drawings

[0017] [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 a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 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 Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the language used in the following description will be explained.

[0020] In the following embodiments, the 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 CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), and the like.

[0021] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] This invention is a system that generates and provides appropriate content based on the user's location information and interest / preference information. This system is realized through the cooperation of three parties: the user, the terminal, and the server, each executing their respective processes.

[0039] 1. User Authentication and Initial Setup

[0040] The user installs the application and enters the necessary information for initial setup (e.g., username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0041] 2. Collection and analysis of location information

[0042] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (e.g., tourist attractions, restaurants, transportation, etc.).

[0043] 3. Gathering information about hobbies and preferences through conversation.

[0044] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data. This text data is sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies and preferences to their profile.

[0045] 4. Information generation and provision

[0046] Based on the analysis results, the server generates optimal content based on the user's current location and interests. For example, if the user is interested in historical places, the server prioritizes extracting information about historical tourist spots in that area. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[0047] 5. Gathering feedback and making improvements

[0048] Users provide feedback on the information they receive. They input ratings and opinions such as "This information was helpful" on their device, and the device sends this to the server. The server analyzes the received feedback and uses the results to improve the user profile and information provision algorithm. This improves the accuracy of information provided in the future.

[0049] Specific example

[0050] Specific example 1: Usage case during sightseeing

[0051] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data and sends it to the server. Based on the location information and past conversations, the server determines that the user is interested in historical tourist spots and generates information such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," which it then sends back to the device. The device displays this information and provides the user with an audio guide.

[0052] Example 2: Usage on a bus during a commute

[0053] If a user who commutes daily on the same bus route is looking for a new cafe, the terminal tracks the user's current route and sends this information to the server. The server collects information about new cafes near the route and sends it back to the terminal. The terminal then displays and provides voice guidance such as, "There is a new cafe along this route. It is called XX Cafe and has delicious coffee."

[0054] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information and hobby / preference information, and further improves the information provision algorithm based on feedback, thereby providing users with high-quality information.

[0055] The following describes the processing flow.

[0056] Step 1:

[0057] User: Install the application and enter registration information such as username, email address, and password.

[0058] Step 2:

[0059] Terminal: Sends the entered user information to the server.

[0060] Step 3:

[0061] Server: Stores received information in a database and generates a unique user ID.

[0062] Step 4:

[0063] Server: Sends the generated user ID back to the terminal.

[0064] Step 5:

[0065] Terminal: Complete initial setup and display the login screen to the user.

[0066] Step 6:

[0067] User: Log in to the application and grant location access permissions.

[0068] Step 7:

[0069] Device: Uses the device's GPS sensor to periodically obtain the user's current location.

[0070] Step 8:

[0071] Terminal: Sends acquired location information to the server.

[0072] Step 9:

[0073] Server: Analyzes received location information to determine the user's current location.

[0074] Step 10:

[0075] Server: Collects basic information related to the region (tourist attractions, restaurants, transportation, etc.).

[0076] Step 11:

[0077] User: Speaks to the application and asks questions (e.g., "What are some recommended places to visit in this area?").

[0078] Step 12:

[0079] Device: Uses speech recognition to convert user speech into text data.

[0080] Step 13:

[0081] Terminal: Sends the converted text data to the server.

[0082] Step 14:

[0083] Server: Uses natural language processing (NLP) algorithms to analyze the user's question.

[0084] Step 15:

[0085] Server: Based on the analysis results, it adds and updates the user's hobbies and preferences to their profile.

[0086] Step 16:

[0087] Server: Uses an AI algorithm to generate optimal content based on location information and interest / preference information.

[0088] Step 17:

[0089] Server: Sends the generated information to the terminal.

[0090] Step 18:

[0091] Terminal: Analyzes received information and prepares an interface for displaying it to the user.

[0092] Step 19:

[0093] Device: Provides information via voice guidance using the voice guidance function.

[0094] Step 20:

[0095] User: Provide feedback on the information provided (e.g., "This information was helpful").

[0096] Step 21:

[0097] Terminal: Sends user feedback to the server.

[0098] Step 22:

[0099] Server: Analyzes received feedback to improve user profiles and information provision algorithms.

[0100] (Example 1)

[0101] 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."

[0102] Traditional content delivery systems struggled to provide appropriate content because they could not fully utilize users' location information or preferences. Furthermore, they had limitations in responding to changes in user preferences in real time and in improving information delivery algorithms based on user feedback. As a result, they were unable to provide users with the most optimal information, creating a need for improved user experience.

[0103] 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.

[0104] In this invention, the server includes means for the user to input initial setup information, store that information in a database, and generate a user ID; means for collecting the user's location information; and means for analyzing the user's hobbies and preferences. This enables the generation and provision of optimal content based on the user's location information and hobbies and preferences. Furthermore, by including means for the server to convert conversations with the user from speech to text, analyze the text data to update the hobbies and preferences, and collect feedback from the user, analyze the feedback to improve the information provision algorithm, it becomes possible to respond to changes in hobbies and preferences in real time and improve the accuracy of information provision.

[0105] A "user" refers to an individual or group that uses a system to obtain information.

[0106] "Initial setup information" refers to basic information such as name, email address, and password that a user enters when using the application for the first time.

[0107] A "database" refers to an information management system used to store a user's initial settings, location information, and hobby / preference information.

[0108] A "User ID" refers to a unique identifier generated by the database to identify a user.

[0109] "Location information" refers to data that indicates the user's current geographical location, obtained using technologies such as GPS.

[0110] "Hobby and preference information" refers to information that indicates a user's interests and preferences, and is data that the server analyzes and adds to or updates the user profile.

[0111] "Content" refers to information generated and provided by the server based on the user's location information and preferences. Specifically, this includes information on tourist destinations and restaurant recommendations.

[0112] "Speech recognition" refers to the technology that converts a user's spoken words into text data.

[0113] "Text data" refers to data that has been converted using speech recognition technology and expressed as textual information.

[0114] "Natural language processing" refers to a series of processes used by servers to analyze user utterances and extract their meaning.

[0115] "Feedback" refers to the evaluations and opinions that users give regarding the information provided.

[0116] An "information provision algorithm" refers to the calculation procedures and processing methods used to generate optimal content based on the user's location information, hobbies and preferences, and feedback.

[0117] This invention is a system that generates and provides appropriate content based on the user's location information and hobby / preference information. This system is realized through the cooperation of three parties: the user, the terminal, and the server, each executing their respective processes.

[0118] Initial setup

[0119] The user installs the application on a device such as a smartphone and enters initial setup information (name, email address, password, etc.). This information is sent from the device to the server. The server stores the received information in a database (e.g., MySQL®) and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0120] Location data collection and analysis

[0121] After a user logs into the application, the application requests permission to access location information. If the user grants permission, the device periodically uses its GPS function to obtain its current geographical location and sends it to the server. The server analyzes the received location information using the Google® Maps API to identify the area where the user is currently located. Basic information related to that area (tourist attractions, restaurants, transportation, etc.) is also collected.

[0122] Gathering information on hobbies and preferences

[0123] When a user asks a question to the application using voice (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition (e.g., Google Speech-to-Text) to convert the speech into text data. This text data is sent to a server. The server uses natural language processing (NLP) algorithms (e.g., Google Cloud Natural Language API) to analyze the question and add or update the user's hobbies and preferences to their profile.

[0124] Content creation and delivery

[0125] The server generates optimal content based on the user's current location and interests. For example, if a user is interested in historical places, the server prioritizes extracting information about historical tourist attractions in that area. The generated information is sent to the device, which then displays it to the user. It is also possible to provide information in audio format using an audio guide function (e.g., Google Text-to-Speech).

[0126] Gathering feedback and making improvements

[0127] Users provide feedback on the information they receive. For example, they might input a rating or comment on their device, such as "This information was helpful," and the device sends this information to the server. The server analyzes the received feedback and uses the results to improve the user's profile and the information provision algorithm. This improves the accuracy of information provided in the future.

[0128] Specific example

[0129] Specific example 1: Usage case during sightseeing

[0130] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data and sends it to the server. Based on the location information and past conversations, the server determines that the user is interested in historical tourist spots and generates information such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," which it then sends back to the device. The device displays this information and provides the user with an audio guide.

[0131] Example 2: Usage on a bus during a commute

[0132] If a user who commutes daily on the same bus route is looking for a new cafe, the terminal tracks the user's current route and sends this information to the server. The server collects information about new cafes near the route and sends it back to the terminal. The terminal then displays and provides voice guidance such as, "There is a new cafe along this route. It is called XX Cafe and has delicious coffee."

[0133] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0134] Step 1:

[0135] The user installs the application and enters basic information such as their name, email address, and password during the initial setup. The entered information is then sent from the device to the server.

[0136] Input: User's name, email address, and password

[0137] Processing: The terminal sends this data to the server using an HTTP POST request. The server validates the received data and formats it for database storage.

[0138] Output: Initial configuration information sent to the server

[0139] Step 2:

[0140] The server saves the initial configuration information it receives to a database and generates a unique user ID. The generated user ID is sent back to the terminal. The terminal receives this and completes the initial setup.

[0141] Input: Initial setup information submitted by the user

[0142] Processing: The server stores information in the database and generates a user ID. The user ID uses an algorithm (e.g., UUID) to generate a unique identifier to maintain uniqueness.

[0143] Output: A user ID is generated and sent back to the terminal.

[0144] Step 3:

[0145] The user logs into the application. The device requests permission to access location information, and the user grants permission. Input: User login information, location access permission.

[0146] Process: The device sends login information from the user to the server, and the server performs authentication. If authentication is successful, the device requests permission from the user to access location information. If the user grants permission, the device turns on GPS.

[0147] Output: If authentication is successful, the user will log in and grant permission for location activation.

[0148] Step 4:

[0149] The device periodically acquires its current geographical location information and sends it to the server.

[0150] Input: Location information (latitude, longitude) obtained from the device's GPS.

[0151] Processing: The device acquires its current location information at regular intervals (e.g., every minute), encodes it in a data format (such as JSON), and sends it to the server.

[0152] Output: Location data sent to the server

[0153] Step 5:

[0154] The server analyzes the location information it receives to identify the user's location, and then collects basic information related to that region.

[0155] Input: Location information sent from the device

[0156] Processing: The server uses the Google Maps API to analyze location information and identify the region. Then, it collects basic information related to the region (such as tourist attractions, restaurants, and transportation) from a database or external API.

[0157] Output: Identified regional information and related basic information

[0158] Step 6:

[0159] The user inputs a question into the application using voice. The device converts this voice into text data and sends it to the server.

[0160] Input: User voice input

[0161] Processing: The device uses speech recognition technology (e.g., Google Speech-to-Text) to convert the audio data into text data. The converted text is then sent to the server.

[0162] Output: Text data sent to the server

[0163] Step 7:

[0164] The server analyzes text data and adds / updates hobby and preference information to the profile.

[0165] Input: Text data converted from speech

[0166] Processing: The server uses NLP algorithms (e.g., Google Cloud Natural Language API) to analyze text data and identify the user's interests and preferences. This information is added to or updated in the user profile.

[0167] Output: Updated user profile

[0168] Step 8:

[0169] The server generates and sends optimal content to the device based on the user's location and interests. The device displays the generated content to the user, providing audio guidance as needed.

[0170] Input: User's location information, updated interest information

[0171] Processing: The server generates appropriate content based on this information. It prioritizes extracting high-priority information (e.g., tourist spots that match the user's interests). The generated information is sent to the device. The device displays the received content to the user and uses Google Text-to-Speech if it provides an audio guide.

[0172] Output: Content displayed on the device, audio guide

[0173] Step 9:

[0174] The user provides feedback on the information provided. The device sends this feedback to the server. The server analyzes the received feedback and improves the information provision algorithm.

[0175] Input: User feedback information

[0176] Processing: The terminal sends the user's feedback to the server. The server uses a machine learning algorithm to analyze the feedback and updates the algorithm to improve the accuracy of future information provision.

[0177] Output: Improved information delivery algorithm

[0178] (Application Example 1)

[0179] 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."

[0180] Traditional content delivery systems were capable of providing certain content based on user location and interest information, but they lacked real-time information provision and sufficient updating of interest information based on user feedback. Furthermore, the insufficient use of generative AI models to effectively utilize collected information and provide users with optimal content made it difficult to increase user satisfaction. To address these challenges, a more advanced information delivery system is needed.

[0181] 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.

[0182] In this invention, the server includes means for collecting the user's location information, means for analyzing the user's interests and preferences, means including an algorithm for providing target information in real time based on the collected location information and interests and preferences, and means for a generation AI model to generate prompt sentences and recommend appropriate content based on the collected location information and interests and preferences. This enables the user to receive real-time, personalized, and optimal content based on their location information and interests and preferences.

[0183] "Means for collecting user location information" refers to a system that obtains the user's current geographical location using GPS or other location-determining technologies.

[0184] "Methods for analyzing user hobbies and preferences" refer to algorithms that analyze a user's interests and preferences from past usage history, input data, conversations, etc.

[0185] "Means for generating and providing content based on location information and hobby / preference information" refers to a system that automatically creates and provides content optimized for the user based on collected location information and analyzed hobby / preference information.

[0186] "Means including an algorithm for providing target information in real time" refers to an algorithm that analyzes current geographical information and hobby / preference information in real time, and instantly generates and provides corresponding information.

[0187] "A means by which a generative AI model generates prompt sentences and recommends appropriate content" refers to a system in which a generative AI model generates appropriate instruction sentences or recommendation sentences based on the original information, and then recommends the most suitable content to the user based on those.

[0188] The system of the present invention generates and provides appropriate content in real time based on the user's location information and interest / preference information. Specific embodiments are shown below.

[0189] 1. User Authentication and Initial Setup

[0190] Users install a dedicated application on their smartphones. During the initial setup, users enter information such as their username, email address, and password, and send this information from their device to the server. The server stores the received information in a database, generates a unique user ID, and sends it back to the device. Initial setup is completed when the device receives the user ID.

[0191] 2. Collection and analysis of location information

[0192] After the user logs into the application, it obtains permission to access location information. The device periodically obtains the user's current location using a GPS module and sends it to the server. The server analyzes the location information to determine the region where the user is currently located.

[0193] 3. Collection and analysis of hobbies and preferences

[0194] When a user asks a question to the application (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the speech into text data. This text data is sent to a server, where a natural language processing algorithm (e.g., spaCy) is used to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies and preferences to their profile.

[0195] 4. Information generation and provision

[0196] Based on the analysis results, the server uses a generative AI model to generate optimal content using the user's current location and preferences. Specifically, it generates prompt messages and retrieves and generates corresponding information via an external API. This information is sent from the server to the terminal, which then guides the user through display and audio.

[0197] 5. Gathering feedback and making improvements

[0198] It also includes a function for users to rate and provide feedback on the information provided. The collected feedback is sent to the server, which analyzes it and uses it to improve user profiles and information provision algorithms. This improves the accuracy of information provided in the future.

[0199] Hardware and software to be used

[0200] hardware

[0201] Smartphone GPS module: Used to obtain accurate location information.

[0202] Smartphone microphone: Enables voice interaction with the user.

[0203] software

[0204] Geopy: Obtains geographical addresses from latitude and longitude.

[0205] spaCy: A natural language processing algorithm that analyzes user speech.

[0206] Requests: Communicate with external APIs to retrieve tourist and entertainment information.

[0207] Specific example

[0208] If a user is sightseeing in Tokyo, they might ask the app, "Tell me about historical places in Shinjuku." Based on their past history, the app might determine that the user is a history buff and recommend places like Shinjuku Gyoen National Garden and Hanazono Shrine.

[0209] Example of a prompt:

[0210] Find historical tourist attractions near your current location.

[0211] Example: "Tell me about historical places in Shinjuku."

[0212] When a user is on a business trip to Osaka and asks, "What are some interesting activities nearby?", they are judged to be an adventure enthusiast and recommended an escape game event in Namba.

[0213] Example of a prompt:

[0214] Please provide entertainment information that users might find interesting.

[0215] Example: "What are some interesting activities nearby?"

[0216] Thus, the system of the present invention provides personalized content in real time based on the user's location information and interest / preference information. The collected feedback is also taken into consideration to continuously improve the quality of the service.

[0217] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0218] Step 1:

[0219] The user installs a dedicated application on their smartphone and enters initial setup information (username, email address, password, etc.). The device sends this input data to the server. The server stores the received information in a database, generates a unique user ID, and sends it back to the device. This completes the registration of the user information.

[0220] Input: Username, email address, password, etc.

[0221] Output: Unique User ID

[0222] Specific operation: User enters the necessary information into the app -> Device sends data to the server -> Server stores the information and generates a user ID -> Unique user ID is sent back to the device

[0223] Step 2:

[0224] The user logs into the application and obtains permission to access location information. The device's GPS module periodically obtains the user's current location and sends it to the server. The server analyzes the location information to determine the region where the user is currently located.

[0225] Input: Location information (latitude and longitude)

[0226] Output: Regional information of the user's current location

[0227] Specific process: User logs into the app -> Obtains permission to access location information -> Device periodically acquires location information -> Device sends location information to the server -> Server analyzes the location information

[0228] Step 3:

[0229] The user asks a question to the app. The device uses speech recognition to convert the user's voice into text data. The converted text data is sent to the server. The server uses a natural language processing algorithm (e.g., spaCy) to analyze the question and adds or updates the user's hobbies and preferences to their profile.

[0230] Input: Audio data

[0231] Output: Updated profile of hobbies and preferences

[0232] Specific process: User asks a question to the app -> Device converts speech to text -> Device sends text data to the server -> Server analyzes it using natural language processing -> User profile is updated

[0233] Step 4:

[0234] The server generates prompt text using an AI model based on the analysis results. Based on the generated prompt text, it retrieves and generates corresponding content information via an external API. The server sends the retrieved information to the terminal. The terminal displays the content to the user and provides audio guidance as needed.

[0235] Input: User profile, location information

[0236] Output: Optimized content information

[0237] Specific operation: The server generates a prompt message using an AI model based on the analysis results -> Information is retrieved from an external API based on the prompt message -> The server sends the retrieved information to the terminal -> The terminal displays the content and provides audio guidance.

[0238] Step 5:

[0239] Users provide feedback on the content they are given. The device sends the feedback data to the server. The server analyzes the collected feedback and uses it to improve user profiles and information provision algorithms.

[0240] Input: Feedback data

[0241] Output: Improved information delivery algorithm

[0242] Specific process: User enters feedback -> Terminal sends feedback data to server -> Server analyzes feedback -> Server improves profile and algorithm.

[0243] 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.

[0244] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information. This system is realized through the cooperation of four parties: the user, the terminal, the server, and the emotion engine, each executing their respective processes.

[0245] 1. User Authentication and Initial Setup

[0246] The user installs the application and enters the necessary information for initial setup (e.g., username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0247] 2. Collection and analysis of location information

[0248] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (e.g., tourist attractions, restaurants, transportation, etc.).

[0249] 3. Gathering information on hobbies and preferences and recognizing emotions through conversation.

[0250] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and then uses an emotion engine to recognize the emotions expressed during the utterance. The emotion engine analyzes the user's emotions from their tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds and updates the user's hobbies, preferences, and emotional information to their profile.

[0251] 4. Information generation and provision

[0252] Based on the analysis results, the server uses an AI algorithm to generate optimal content based on the user's current location, interests, and emotional state. For example, if a user is interested in historical places and their current emotional state is "excited," the server will prioritize extracting information about historical tourist spots in that area and also add information about lively events and activities. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[0253] 5. Gathering feedback and making improvements

[0254] Users provide feedback on the information they receive. They input ratings and opinions on their device, such as "This information was helpful" or "This information is not appropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves the accuracy of future information provision by improving the user profile, sentiment data, and information delivery algorithm.

[0255] Specific example

[0256] Specific example 1: Usage case during sightseeing

[0257] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information about historical places such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," as well as information about live concerts and major events. The device displays this information and also provides it as an audio guide.

[0258] Example 2: Usage on a bus during a commute

[0259] If a user who commutes daily on the same bus route is looking for a new cafe, they can simply say "I'm looking for a new cafe" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new cafes near the route, prioritizing cafes with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[0260] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[0261] The following describes the processing flow.

[0262] Step 1:

[0263] User: Install the application and enter registration information such as username, email address, and password.

[0264] Step 2:

[0265] Terminal: Sends the entered user information to the server.

[0266] Step 3:

[0267] Server: Stores received information in a database and generates a unique user ID.

[0268] Step 4:

[0269] Server: Sends the generated user ID back to the terminal.

[0270] Step 5:

[0271] Terminal: Complete the initial settings and display the login screen to the user.

[0272] Step 6:

[0273] User: Log in to the application and grant permission to access location information.

[0274] Step 7:

[0275] Terminal: Periodically obtain the user's current location using the device's GPS sensor.

[0276] Step 8:

[0277] Terminal: Transmit the obtained location information to the server.

[0278] Step 9:

[0279] Server: Analyze the received location information to identify the user's current location.

[0280] Step 10:

[0281] Server: Collect basic information related to the region (tourist attractions, restaurants, transportation, etc.).

[0282] Step 11:

[0283] User: Speak to the application and ask a question (e.g., "What are the recommended places in this area?").

[0284] Step 12:

[0285] Terminal: Use the speech recognition function to convert the user's speech into text data.

[0286] Step 13:

[0287] Device: Uses an emotion engine to analyze the user's emotions from their voice tone, vocabulary, and facial expressions.

[0288] Step 14:

[0289] Terminal: Sends converted text data and sentiment data to the server.

[0290] Step 15:

[0291] Server: Uses natural language processing (NLP) algorithms to analyze the user's question.

[0292] Step 16:

[0293] Server: Based on the analysis results, it adds and updates the user's hobbies, preferences, and emotional information to their profile.

[0294] Step 17:

[0295] Server: Uses AI algorithms to generate optimal content based on location information, hobbies and preferences, and emotional information.

[0296] Step 18:

[0297] Server: Sends the generated information to the terminal.

[0298] Step 19:

[0299] Terminal: Analyzes received information and prepares an interface for displaying it to the user.

[0300] Step 20:

[0301] Device: Provides information via voice guidance using the voice guidance function.

[0302] Step 21:

[0303] User: Provide feedback on the provided information (e.g., "This information was useful", "This information is inappropriate").

[0304] Step 22:

[0305] Terminal: Send the user's feedback to the server.

[0306] Step 23:

[0307] Server: Analyze the received feedback and improve the user's profile, sentiment data, and information-providing algorithm.

[0308] Step 24:

[0309] Server: Based on the improved algorithm and profile, improve the accuracy of information provision for subsequent times.

[0310] (Example 2)

[0311] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0312] In a conventional content-providing system, it is mainstream to utilize the user's location information and basic hobby information, and there is a lack of consideration for the user's emotional state and feedback, resulting in problems such as low compatibility and accuracy of the provided content. Also, due to the lack of advanced analysis combining natural language processing and emotion recognition, there is an issue that the user experience is limited.

[0313] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting user location information, means for analyzing user hobby preference information and emotional information, means for generating and providing optimal content using a generation AI model based on location information, hobby preference information and emotional information, and means for collecting user feedback and improving the information provision algorithm. This makes it possible to provide highly accurate content that corresponds to the user's current emotions and detailed hobby preferences.

[0314] "User" refers to a person who uses this system.

[0315] "Location information" refers to data that indicates the user's current geographical location, and is obtained using technologies such as GPS.

[0316] "Hobby and preference information" refers to information about the areas and activities that a user is interested in, and is obtained from the user's past actions and statements.

[0317] "Emotional information" refers to data that indicates the user's current emotional state, and is obtained from sources such as voice tone and facial expression analysis.

[0318] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information or content.

[0319] "Content" is a general term for information and services provided to users, and includes text, images, audio, and video.

[0320] "Feedback" refers to the evaluations and opinions that users give to the content provided.

[0321] "Natural language processing" refers to the technology used to analyze, understand, and generate human language, and is applied to the analysis of text data.

[0322] An "emotion engine" refers to a system that analyzes a user's voice and facial expressions to recognize their emotional state.

[0323] An "information provision algorithm" refers to the computational methods and processes used to provide users with the most suitable content.

[0324] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information. This system is realized through the cooperation of the user, terminal, and server in executing each process.

[0325] 1. User Authentication and Initial Setup

[0326] The user installs the application and enters the necessary information for initial setup (username, email address, password, etc.). The device sends this information to the server, which stores the information in a database and then generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0327] 2. Collection and analysis of location information

[0328] After the user logs in, the application obtains permission from the user to access location information. The device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to determine the user's current location. It then collects basic information related to the area (tourist attractions, restaurants, transportation, etc.).

[0329] 3. Gathering information on hobbies and preferences and recognizing emotions through conversation.

[0330] When a user speaks to the application and asks a question (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and uses an emotion engine to analyze the emotional information within the user's speech. The emotion engine analyzes emotions from the user's tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies, preferences, and emotional information to their profile.

[0331] 4. Information generation and provision

[0332] Based on the analysis results, the server generates optimal content using a generative AI model (e.g., GPT-4®) based on the user's current location, interests, and emotional information. For example, if the user is interested in historical places and is currently excited, the server will prioritize extracting information about historical sites and exciting events in that area. This generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio format using an audio guide function.

[0333] 5. Gathering feedback and making improvements

[0334] Users provide feedback on the information they receive. For example, they input ratings and opinions on their device, such as "This information was helpful" or "This information is inappropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves user profiles, sentiment data, and information delivery algorithms to enhance the accuracy of future information delivery.

[0335] Specific example

[0336] Use cases during sightseeing:

[0337] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information about historical places such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," as well as information about live concerts and major events. The device displays this information and also provides it as an audio guide.

[0338] Usage scenarios on the bus during commute:

[0339] If a user who commutes daily on the same bus route is looking for a new cafe, they can simply say "I'm looking for a new cafe" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new cafes near the route, prioritizing cafes with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[0340] Example of a prompt:

[0341] "This user is currently sightseeing in Shinjuku and is very excited. Please provide them with recommendations for sightseeing spots and events in Shinjuku. This user enjoys visiting historical sites."

[0342] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[0343] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0344] Step 1: User Authentication and Initial Setup

[0345] 1. Input: The user launches the application they installed for the first time and enters their username, email address, and password.

[0346] 2. Specific actions:

[0347] The user enters their username, email address, and password and presses the submit button.

[0348] The device encrypts the information entered.

[0349] 3. Data processing: The device encrypts user information and sends it to the server.

[0350] 4. Output: Encrypted user information is sent to the server.

[0351] 5. Specific actions:

[0352] The server saves the received information to the database.

[0353] The server generates a unique user ID.

[0354] 6. Data processing: The server stores user information and generates a unique user ID.

[0355] 7. Output: The server sends the generated user ID back to the terminal.

[0356] 8. Specific actions:

[0357] The device receives the user ID, saves it to local storage, and completes the initial setup.

[0358] Step 2: Location data collection and analysis

[0359] 1. Input: The user logs into the application and grants permission to access location information.

[0360] 2. Specific actions:

[0361] The device displays a pop-up requesting permission to access its location.

[0362] The user grants permission.

[0363] 3. Data processing: The device periodically acquires its current geographical location information.

[0364] 4. Output: The device obtains its current location information.

[0365] 5. Specific actions:

[0366] The device sends the location information it has acquired to the server.

[0367] 6. Data processing: The server analyzes the location information it receives and identifies the region through reverse geocoding.

[0368] 7. Output: The server collects basic local information (tourist attractions, restaurants, etc.).

[0369] 8. Specific actions:

[0370] The server stores basic information for each region in a database.

[0371] Step 3: Gathering information on hobbies and preferences through conversation and recognizing emotions.

[0372] 1. Input: The user asks a question to the application (e.g., "What are some recommended places to visit in this area?").

[0373] 2. Specific actions:

[0374] The device records audio.

[0375] The device uses speech recognition to convert the spoken words into text data.

[0376] 3. Data processing: The device passes text data to the emotion engine.

[0377] 4. Output: Text data and sentiment data are generated.

[0378] 5. Specific actions:

[0379] The emotion engine analyzes the tone of voice and word choice to generate information about the user's emotions.

[0380] The device sends text data and sentiment data to the server.

[0381] 6. Data processing: The server uses NLP algorithms to analyze text data and understand the question.

[0382] 7. Output: Analysis results are generated and added / updated to the user's profile.

[0383] 8. Specific actions:

[0384] The server updates the user's hobby preferences and emotional data based on the analysis results.

[0385] Step 4: Information generation and provision

[0386] 1. Input: The server generates a prompt message based on the analysis results.

[0387] 2. Specific actions:

[0388] The server inputs a prompt message into the generated AI model (e.g., "The user is currently sightseeing in Shinjuku and is very excited. Please provide this user with recommended sightseeing spots and event information in Shinjuku. The user's hobby is visiting historical sites.").

[0389] 3. Data Processing: The generation AI model generates content based on the prompt text.

[0390] 4. Output: Generated content (tourist spot information, event information) is generated.

[0391] 5. Specific actions:

[0392] The server sends the generated information to the terminal.

[0393] The device displays the received information to the user.

[0394] 6. Data processing: The terminal provides information it has received via voice guidance using its voice guidance function.

[0395] 7. Output: Information and audio guidance are provided to the user.

[0396] Step 5: Gathering feedback and making improvements

[0397] 1. Input: Users provide feedback on the information provided (e.g., "Helpful," "Inappropriate," etc.).

[0398] 2. Specific actions:

[0399] It provides an interface for the device to input feedback.

[0400] The user enters their feedback and presses the submit button.

[0401] 3. Data processing: The device sends feedback data to the server.

[0402] 4. Output: Feedback data is sent to the server.

[0403] 5. Specific actions:

[0404] The server analyzes the feedback data.

[0405] 6. Data Processing: The server improves user profiles and information provision algorithms based on the analysis results.

[0406] 7. Output: The updated algorithms and profiles will be reflected in future information updates.

[0407] 8. Specific actions:

[0408] Based on the updated server information, an algorithm is applied to improve the user experience for subsequent visits.

[0409] (Application Example 2)

[0410] 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".

[0411] In today's world, user needs are extremely diverse, making it difficult to provide satisfying content based solely on location information or personal preferences. Furthermore, there is a demand for real-time, optimal content based on user emotions, but a comprehensive system to achieve this still does not exist. Conventional systems have failed to provide content that takes into account the user's instantaneous emotional state, resulting in a poor user experience.

[0412] 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.

[0413] In this invention, the server includes means for collecting user location information, means for analyzing user hobbies and preferences, means for analyzing user emotional information, means for generating and providing content based on location information, hobbies and preferences, and emotional information, and a terminal for providing the generated content to the user. This makes it possible to provide optimal content in real time based on the user's instantaneous emotional state, location information, and hobbies and preferences.

[0414] A "user" refers to an individual or end-user who uses the system.

[0415] "Location information" refers to data that indicates the geographical location where the user is currently located.

[0416] "Hobby and preference information" refers to data that indicates a user's interests and preferences.

[0417] "Emotional information" refers to data that indicates a user's instantaneous emotional state.

[0418] "Content" refers to information, media, and services provided to users.

[0419] "Means of generation and provision" refers to a part of a system that has methods and functions for creating and providing optimal content to users based on location information, hobby / preference information, and emotional information.

[0420] A "device" refers to a device that the user directly operates (for example, a smartphone or tablet).

[0421] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information.

[0422] User Authentication and Initial Setup

[0423] The user installs the application and enters the necessary information for initial setup (username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0424] Location data collection and analysis

[0425] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (such as tourist attractions, restaurants, and transportation).

[0426] Gathering information on hobbies and preferences through conversation and recognizing emotions.

[0427] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and then uses an emotion engine to recognize the emotions expressed during the utterance. The emotion engine analyzes the user's emotions from their tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds and updates the user's hobbies, preferences, and emotional information to their profile.

[0428] Information generation and provision

[0429] Based on the analysis results, the server uses an AI algorithm to generate optimal content based on the user's current location, interests, and emotional state. For example, if a user is interested in historical places and their current emotional state is "excited," the server will prioritize extracting information about historical tourist spots in that area and also add information about lively events and activities. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[0430] Gathering feedback and making improvements

[0431] Users provide feedback on the information they receive. They input ratings and opinions on their device, such as "This information was helpful" or "This information is not appropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves the accuracy of future information provision by improving the user profile, sentiment data, and information delivery algorithm.

[0432] Specific example

[0433] Specific example 1: Usage case during sightseeing

[0434] If a user is visiting a major city, they might ask the AI ​​system, "What are some interesting places to see in this city?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information on historical places such as "famous parks" and "ancient shrines," as well as information on live concerts and major events. The device displays this information and also provides it as an audio guide.

[0435] Example 2: Usage on a bus during a commute

[0436] If a user who commutes on the same bus route every day is looking for a new restaurant, they can simply say "I'm looking for a new restaurant" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new restaurants near the route, prioritizing places with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[0437] Example of a prompt:

[0438] voice_data = "Tell me some relaxing music you'd like to listen to right now."

[0439] emotion = get_user_emotion(voice_data)

[0440] latitude, longitude = get_geolocation()

[0441] recommendations = recommend_content(emotion, latitude, longitude)

[0442] print(recommendations)

[0443] The system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[0444] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0445] Step 1:

[0446] User Authentication and Initial Setup

[0447] The user installs the application and enters the required information (username, email address, password). The device sends this information to the server. The server stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0448] Input: User's basic information (username, email address, password)

[0449] Output: Unique User ID

[0450] Step 2:

[0451] Location data collection and analysis

[0452] After a user logs in, the application obtains permission from the user to access location information. The device, having received permission, periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the user's current location and collects basic information related to that area.

[0453] Input: User's location information

[0454] Output: User's current location and related basic information

[0455] Step 3:

[0456] Gathering information on hobbies and preferences through conversation and recognizing emotions.

[0457] When a user speaks to the application, the device uses speech recognition to convert the speech into text data. The device then uses an emotion engine to analyze the emotions expressed in the speech and generate emotion information. This text data and emotion information are sent to a server, which analyzes it to add or update the user's profile with their preferences and emotion information.

[0458] Input: User voice input

[0459] Output: Analysis results of text data and sentiment information

[0460] Step 4:

[0461] Information generation and provision

[0462] The server uses an AI algorithm to generate optimal content based on analyzed location information, hobbies and preferences, and emotional information. The generated content is sent to the device, which then displays it to the user. It is also possible to provide information via voice guidance using the voice guidance function.

[0463] Input: Location information, hobbies and preferences, emotional information

[0464] Output: Generated content

[0465] Step 5:

[0466] Gathering feedback and making improvements

[0467] Users provide feedback on the information they receive. The device sends evaluations and opinions, such as "This information was helpful" or "This information is inappropriate," to the server. The server analyzes the received feedback and improves the user profile, sentiment data, and information delivery algorithms.

[0468] Input: User feedback

[0469] Output: Improved information delivery algorithm

[0470] By executing the above steps sequentially, it becomes possible to provide optimal content in real time based on the user's location information, hobbies and preferences, and emotional information.

[0471] 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.

[0472] 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.

[0473] 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.

[0474] [Second Embodiment]

[0475] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0476] 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.

[0477] 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).

[0478] 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.

[0479] 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.

[0480] 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).

[0481] 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.

[0482] 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.

[0483] 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.

[0484] 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.

[0485] 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.

[0486] 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".

[0487] This invention is a system that generates and provides appropriate content based on the user's location information and interest / preference information. This system is realized through the cooperation of three parties: the user, the terminal, and the server, each executing their respective processes.

[0488] 1. User Authentication and Initial Setup

[0489] The user installs the application and enters the necessary information for initial setup (e.g., username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0490] 2. Collection and analysis of location information

[0491] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (e.g., tourist attractions, restaurants, transportation, etc.).

[0492] 3. Gathering information about hobbies and preferences through conversation.

[0493] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data. This text data is sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies and preferences to their profile.

[0494] 4. Information generation and provision

[0495] Based on the analysis results, the server generates optimal content based on the user's current location and interests. For example, if the user is interested in historical places, the server prioritizes extracting information about historical tourist spots in that area. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[0496] 5. Gathering feedback and making improvements

[0497] Users provide feedback on the information they receive. They input ratings and opinions such as "This information was helpful" on their device, and the device sends this to the server. The server analyzes the received feedback and uses the results to improve the user profile and information provision algorithm. This improves the accuracy of information provided in the future.

[0498] Specific example

[0499] Specific example 1: Usage case during sightseeing

[0500] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data and sends it to the server. Based on the location information and past conversations, the server determines that the user is interested in historical tourist spots and generates information such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," which it then sends back to the device. The device displays this information and provides the user with an audio guide.

[0501] Example 2: Usage on a bus during a commute

[0502] If a user who commutes daily on the same bus route is looking for a new cafe, the terminal tracks the user's current route and sends this information to the server. The server collects information about new cafes near the route and sends it back to the terminal. The terminal then displays and provides voice guidance such as, "There is a new cafe along this route. It is called XX Cafe and has delicious coffee."

[0503] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information and hobby / preference information, and further improves the information provision algorithm based on feedback, thereby providing users with high-quality information.

[0504] The following describes the processing flow.

[0505] Step 1:

[0506] User: Install the application and enter registration information such as username, email address, and password.

[0507] Step 2:

[0508] Terminal: Sends the entered user information to the server.

[0509] Step 3:

[0510] Server: Stores received information in a database and generates a unique user ID.

[0511] Step 4:

[0512] Server: Sends the generated user ID back to the terminal.

[0513] Step 5:

[0514] Terminal: Complete initial setup and display the login screen to the user.

[0515] Step 6:

[0516] User: Log in to the application and grant location access permissions.

[0517] Step 7:

[0518] Device: Uses the device's GPS sensor to periodically obtain the user's current location.

[0519] Step 8:

[0520] Terminal: Sends acquired location information to the server.

[0521] Step 9:

[0522] Server: Analyzes received location information to determine the user's current location.

[0523] Step 10:

[0524] Server: Collects basic information related to the region (tourist attractions, restaurants, transportation, etc.).

[0525] Step 11:

[0526] User: Speaks to the application and asks questions (e.g., "What are some recommended places to visit in this area?").

[0527] Step 12:

[0528] Device: Uses speech recognition to convert user speech into text data.

[0529] Step 13:

[0530] Terminal: Sends the converted text data to the server.

[0531] Step 14:

[0532] Server: Uses natural language processing (NLP) algorithms to analyze the user's question.

[0533] Step 15:

[0534] Server: Based on the analysis results, it adds and updates the user's hobbies and preferences to their profile.

[0535] Step 16:

[0536] Server: Uses an AI algorithm to generate optimal content based on location information and interest / preference information.

[0537] Step 17:

[0538] Server: Sends the generated information to the terminal.

[0539] Step 18:

[0540] Terminal: Analyzes received information and prepares an interface for displaying it to the user.

[0541] Step 19:

[0542] Device: Provides information via voice guidance using the voice guidance function.

[0543] Step 20:

[0544] User: Provide feedback on the information provided (e.g., "This information was helpful").

[0545] Step 21:

[0546] Terminal: Sends user feedback to the server.

[0547] Step 22:

[0548] Server: Analyzes received feedback to improve user profiles and information provision algorithms.

[0549] (Example 1)

[0550] 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."

[0551] Traditional content delivery systems struggled to provide appropriate content because they could not fully utilize users' location information or preferences. Furthermore, they had limitations in responding to changes in user preferences in real time and in improving information delivery algorithms based on user feedback. As a result, they were unable to provide users with the most optimal information, creating a need for improved user experience.

[0552] 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.

[0553] In this invention, the server includes means for the user to input initial setup information, store that information in a database, and generate a user ID; means for collecting the user's location information; and means for analyzing the user's hobbies and preferences. This enables the generation and provision of optimal content based on the user's location information and hobbies and preferences. Furthermore, by including means for the server to convert conversations with the user from speech to text, analyze the text data to update the hobbies and preferences, and collect feedback from the user, analyze the feedback to improve the information provision algorithm, it becomes possible to respond to changes in hobbies and preferences in real time and improve the accuracy of information provision.

[0554] A "user" refers to an individual or group that uses a system to obtain information.

[0555] "Initial setup information" refers to basic information such as name, email address, and password that a user enters when using the application for the first time.

[0556] A "database" refers to an information management system used to store a user's initial settings, location information, and hobby / preference information.

[0557] A "User ID" refers to a unique identifier generated by the database to identify a user.

[0558] "Location information" refers to data that indicates the user's current geographical location, obtained using technologies such as GPS.

[0559] "Hobby and preference information" refers to information that indicates a user's interests and preferences, and is data that the server analyzes and adds to or updates the user profile.

[0560] "Content" refers to information generated and provided by the server based on the user's location information and preferences. Specifically, this includes information on tourist destinations and restaurant recommendations.

[0561] "Speech recognition" refers to the technology that converts a user's spoken words into text data.

[0562] "Text data" refers to data that has been converted using speech recognition technology and expressed as textual information.

[0563] "Natural language processing" refers to a series of processes used by servers to analyze user utterances and extract their meaning.

[0564] "Feedback" refers to the evaluations and opinions that users give regarding the information provided.

[0565] An "information provision algorithm" refers to the calculation procedures and processing methods used to generate optimal content based on the user's location information, hobbies and preferences, and feedback.

[0566] This invention is a system that generates and provides appropriate content based on the user's location information and hobby / preference information. This system is realized through the cooperation of three parties: the user, the terminal, and the server, each executing their respective processes.

[0567] Initial setup

[0568] The user installs the application on a device such as a smartphone and enters initial setup information (name, email address, password, etc.). This information is sent from the device to the server. The server stores the received information in a database (e.g., MySQL) and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0569] Location data collection and analysis

[0570] After a user logs into the application, the application requests permission to access location information. If the user grants permission, the device periodically uses its GPS function to obtain its current geographical location and sends it to the server. The server analyzes the received location information using the Google Maps API to identify the user's current location. Basic information related to that area (tourist attractions, restaurants, transportation, etc.) is also collected.

[0571] Gathering information on hobbies and preferences

[0572] When a user asks a question to the application using voice (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition (e.g., Google Speech-to-Text) to convert the speech into text data. This text data is sent to a server. The server uses natural language processing (NLP) algorithms (e.g., Google Cloud Natural Language API) to analyze the question and add or update the user's hobbies and preferences to their profile.

[0573] Content creation and delivery

[0574] The server generates optimal content based on the user's current location and interests. For example, if a user is interested in historical places, the server prioritizes extracting information about historical tourist attractions in that area. The generated information is sent to the device, which then displays it to the user. It is also possible to provide information in audio format using an audio guide function (e.g., Google Text-to-Speech).

[0575] Gathering feedback and making improvements

[0576] Users provide feedback on the information they receive. For example, they might input a rating or comment on their device, such as "This information was helpful," and the device sends this information to the server. The server analyzes the received feedback and uses the results to improve the user's profile and the information provision algorithm. This improves the accuracy of information provided in the future.

[0577] Specific example

[0578] Specific example 1: Usage case during sightseeing

[0579] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data and sends it to the server. Based on the location information and past conversations, the server determines that the user is interested in historical tourist spots and generates information such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," which it then sends back to the device. The device displays this information and provides the user with an audio guide.

[0580] Example 2: Usage on a bus during a commute

[0581] If a user who commutes daily on the same bus route is looking for a new cafe, the terminal tracks the user's current route and sends this information to the server. The server collects information about new cafes near the route and sends it back to the terminal. The terminal then displays and provides voice guidance such as, "There is a new cafe along this route. It is called XX Cafe and has delicious coffee."

[0582] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0583] Step 1:

[0584] The user installs the application and enters basic information such as their name, email address, and password during the initial setup. The entered information is then sent from the device to the server.

[0585] Input: User's name, email address, and password

[0586] Processing: The terminal sends this data to the server using an HTTP POST request. The server validates the received data and formats it for database storage.

[0587] Output: Initial configuration information sent to the server

[0588] Step 2:

[0589] The server saves the initial configuration information it receives to a database and generates a unique user ID. The generated user ID is sent back to the terminal. The terminal receives this and completes the initial setup.

[0590] Input: Initial setup information submitted by the user

[0591] Processing: The server stores information in the database and generates a user ID. The user ID uses an algorithm (e.g., UUID) to generate a unique identifier to maintain uniqueness.

[0592] Output: A user ID is generated and sent back to the terminal.

[0593] Step 3:

[0594] The user logs into the application. The device requests permission to access location information, and the user grants permission. Input: User login information, location access permission.

[0595] Process: The device sends login information from the user to the server, and the server performs authentication. If authentication is successful, the device requests permission from the user to access location information. If the user grants permission, the device turns on GPS.

[0596] Output: If authentication is successful, the user will log in and grant permission for location activation.

[0597] Step 4:

[0598] The device periodically acquires its current geographical location information and sends it to the server.

[0599] Input: Location information (latitude, longitude) obtained from the device's GPS.

[0600] Processing: The device acquires its current location information at regular intervals (e.g., every minute), encodes it in a data format (such as JSON), and sends it to the server.

[0601] Output: Location data sent to the server

[0602] Step 5:

[0603] The server analyzes the location information it receives to identify the user's location, and then collects basic information related to that region.

[0604] Input: Location information sent from the device

[0605] Processing: The server uses the Google Maps API to analyze location information and identify the region. Then, it collects basic information related to the region (such as tourist attractions, restaurants, and transportation) from a database or external API.

[0606] Output: Identified regional information and related basic information

[0607] Step 6:

[0608] The user inputs a question into the application using voice. The device converts this voice into text data and sends it to the server.

[0609] Input: User voice input

[0610] Processing: The device uses speech recognition technology (e.g., Google Speech-to-Text) to convert the audio data into text data. The converted text is then sent to the server.

[0611] Output: Text data sent to the server

[0612] Step 7:

[0613] The server analyzes text data and adds / updates hobby and preference information to the profile.

[0614] Input: Text data converted from speech

[0615] Processing: The server uses NLP algorithms (e.g., Google Cloud Natural Language API) to analyze text data and identify the user's interests and preferences. This information is added to or updated in the user profile.

[0616] Output: Updated user profile

[0617] Step 8:

[0618] The server generates and sends optimal content to the device based on the user's location and interests. The device displays the generated content to the user, providing audio guidance as needed.

[0619] Input: User's location information, updated interest information

[0620] Processing: The server generates appropriate content based on this information. It prioritizes extracting high-priority information (e.g., tourist spots that match the user's interests). The generated information is sent to the device. The device displays the received content to the user and uses Google Text-to-Speech if it provides an audio guide.

[0621] Output: Content displayed on the device, audio guide

[0622] Step 9:

[0623] The user provides feedback on the information provided. The device sends this feedback to the server. The server analyzes the received feedback and improves the information provision algorithm.

[0624] Input: User feedback information

[0625] Processing: The terminal sends the user's feedback to the server. The server uses a machine learning algorithm to analyze the feedback and updates the algorithm to improve the accuracy of future information provision.

[0626] Output: Improved information delivery algorithm

[0627] (Application Example 1)

[0628] 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."

[0629] Traditional content delivery systems were capable of providing certain content based on user location and interest information, but they lacked real-time information provision and sufficient updating of interest information based on user feedback. Furthermore, the insufficient use of generative AI models to effectively utilize collected information and provide users with optimal content made it difficult to increase user satisfaction. To address these challenges, a more advanced information delivery system is needed.

[0630] 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.

[0631] In this invention, the server includes means for collecting the user's location information, means for analyzing the user's interests and preferences, means including an algorithm for providing target information in real time based on the collected location information and interests and preferences, and means for a generation AI model to generate prompt sentences and recommend appropriate content based on the collected location information and interests and preferences. This enables the user to receive real-time, personalized, and optimal content based on their location information and interests and preferences.

[0632] "Means for collecting user location information" refers to a system that obtains the user's current geographical location using GPS or other location-determining technologies.

[0633] "Methods for analyzing user hobbies and preferences" refer to algorithms that analyze a user's interests and preferences from past usage history, input data, conversations, etc.

[0634] "Means for generating and providing content based on location information and hobby / preference information" refers to a system that automatically creates and provides content optimized for the user based on collected location information and analyzed hobby / preference information.

[0635] "Means including an algorithm for providing target information in real time" refers to an algorithm that analyzes current geographical information and hobby / preference information in real time, and instantly generates and provides corresponding information.

[0636] "A means by which a generative AI model generates prompt sentences and recommends appropriate content" refers to a system in which a generative AI model generates appropriate instruction sentences or recommendation sentences based on the original information, and then recommends the most suitable content to the user based on those.

[0637] The system of the present invention generates and provides appropriate content in real time based on the user's location information and interest / preference information. Specific embodiments are shown below.

[0638] 1. User Authentication and Initial Setup

[0639] Users install a dedicated application on their smartphones. During the initial setup, users enter information such as their username, email address, and password, and send this information from their device to the server. The server stores the received information in a database, generates a unique user ID, and sends it back to the device. Initial setup is completed when the device receives the user ID.

[0640] 2. Collection and analysis of location information

[0641] After the user logs into the application, it obtains permission to access location information. The device periodically obtains the user's current location using a GPS module and sends it to the server. The server analyzes the location information to determine the region where the user is currently located.

[0642] 3. Collection and analysis of hobbies and preferences

[0643] When a user asks a question to the application (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the speech into text data. This text data is sent to a server, where a natural language processing algorithm (e.g., spaCy) is used to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies and preferences to their profile.

[0644] 4. Information generation and provision

[0645] Based on the analysis results, the server uses a generative AI model to generate optimal content using the user's current location and preferences. Specifically, it generates prompt messages and retrieves and generates corresponding information via an external API. This information is sent from the server to the terminal, which then guides the user through display and audio.

[0646] 5. Gathering feedback and making improvements

[0647] It also includes a function for users to rate and provide feedback on the information provided. The collected feedback is sent to the server, which analyzes it and uses it to improve user profiles and information provision algorithms. This improves the accuracy of information provided in the future.

[0648] Hardware and software to be used

[0649] hardware

[0650] Smartphone GPS module: Used to obtain accurate location information.

[0651] Smartphone microphone: Enables voice interaction with the user.

[0652] software

[0653] Geopy: Obtains geographical addresses from latitude and longitude.

[0654] spaCy: A natural language processing algorithm that analyzes user speech.

[0655] Requests: Communicate with external APIs to retrieve tourist and entertainment information.

[0656] Specific example

[0657] If a user is sightseeing in Tokyo, they might ask the app, "Tell me about historical places in Shinjuku." Based on their past history, the app might determine that the user is a history buff and recommend places like Shinjuku Gyoen National Garden and Hanazono Shrine.

[0658] Example of a prompt:

[0659] Find historical tourist attractions near your current location.

[0660] Example: "Tell me about historical places in Shinjuku."

[0661] When a user is on a business trip to Osaka and asks, "What are some interesting activities nearby?", they are judged to be an adventure enthusiast and recommended an escape game event in Namba.

[0662] Example of a prompt:

[0663] Please provide entertainment information that users might find interesting.

[0664] Example: "What are some interesting activities nearby?"

[0665] Thus, the system of the present invention provides personalized content in real time based on the user's location information and interest / preference information. The collected feedback is also taken into consideration to continuously improve the quality of the service.

[0666] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0667] Step 1:

[0668] The user installs a dedicated application on their smartphone and enters initial setup information (username, email address, password, etc.). The device sends this input data to the server. The server stores the received information in a database, generates a unique user ID, and sends it back to the device. This completes the registration of the user information.

[0669] Input: Username, email address, password, etc.

[0670] Output: Unique User ID

[0671] Specific operation: User enters the necessary information into the app -> Device sends data to the server -> Server stores the information and generates a user ID -> Unique user ID is sent back to the device

[0672] Step 2:

[0673] The user logs into the application and obtains permission to access location information. The device's GPS module periodically obtains the user's current location and sends it to the server. The server analyzes the location information to determine the region where the user is currently located.

[0674] Input: Location information (latitude and longitude)

[0675] Output: Regional information of the user's current location

[0676] Specific process: User logs into the app -> Obtains permission to access location information -> Device periodically acquires location information -> Device sends location information to the server -> Server analyzes the location information

[0677] Step 3:

[0678] The user asks a question to the app. The device uses speech recognition to convert the user's voice into text data. The converted text data is sent to the server. The server uses a natural language processing algorithm (e.g., spaCy) to analyze the question and adds or updates the user's hobbies and preferences to their profile.

[0679] Input: Audio data

[0680] Output: Updated profile of hobbies and preferences

[0681] Specific process: User asks a question to the app -> Device converts speech to text -> Device sends text data to the server -> Server analyzes it using natural language processing -> User profile is updated

[0682] Step 4:

[0683] The server generates prompt text using an AI model based on the analysis results. Based on the generated prompt text, it retrieves and generates corresponding content information via an external API. The server sends the retrieved information to the terminal. The terminal displays the content to the user and provides audio guidance as needed.

[0684] Input: User profile, location information

[0685] Output: Optimized content information

[0686] Specific operation: The server generates a prompt message using an AI model based on the analysis results -> Information is retrieved from an external API based on the prompt message -> The server sends the retrieved information to the terminal -> The terminal displays the content and provides audio guidance.

[0687] Step 5:

[0688] Users provide feedback on the content they are given. The device sends the feedback data to the server. The server analyzes the collected feedback and uses it to improve user profiles and information provision algorithms.

[0689] Input: Feedback data

[0690] Output: Improved information delivery algorithm

[0691] Specific process: User enters feedback -> Terminal sends feedback data to server -> Server analyzes feedback -> Server improves profile and algorithm.

[0692] 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.

[0693] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information. This system is realized through the cooperation of four parties: the user, the terminal, the server, and the emotion engine, each executing their respective processes.

[0694] 1. User Authentication and Initial Setup

[0695] The user installs the application and enters the necessary information for initial setup (e.g., username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0696] 2. Collection and analysis of location information

[0697] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (e.g., tourist attractions, restaurants, transportation, etc.).

[0698] 3. Gathering information on hobbies and preferences and recognizing emotions through conversation.

[0699] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and then uses an emotion engine to recognize the emotions expressed during the utterance. The emotion engine analyzes the user's emotions from their tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds and updates the user's hobbies, preferences, and emotional information to their profile.

[0700] 4. Information generation and provision

[0701] Based on the analysis results, the server uses an AI algorithm to generate optimal content based on the user's current location, interests, and emotional state. For example, if a user is interested in historical places and their current emotional state is "excited," the server will prioritize extracting information about historical tourist spots in that area and also add information about lively events and activities. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[0702] 5. Gathering feedback and making improvements

[0703] Users provide feedback on the information they receive. They input ratings and opinions on their device, such as "This information was helpful" or "This information is not appropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves the accuracy of future information provision by improving the user profile, sentiment data, and information delivery algorithm.

[0704] Specific example

[0705] Specific example 1: Usage case during sightseeing

[0706] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information about historical places such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," as well as information about live concerts and major events. The device displays this information and also provides it as an audio guide.

[0707] Example 2: Usage on a bus during a commute

[0708] If a user who commutes daily on the same bus route is looking for a new cafe, they can simply say "I'm looking for a new cafe" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new cafes near the route, prioritizing cafes with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[0709] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[0710] The following describes the processing flow.

[0711] Step 1:

[0712] User: Install the application and enter registration information such as username, email address, and password.

[0713] Step 2:

[0714] Terminal: Sends the entered user information to the server.

[0715] Step 3:

[0716] Server: Stores received information in a database and generates a unique user ID.

[0717] Step 4:

[0718] Server: Sends the generated user ID back to the terminal.

[0719] Step 5:

[0720] Terminal: Complete initial setup and display the login screen to the user.

[0721] Step 6:

[0722] User: Log in to the application and grant location access permissions.

[0723] Step 7:

[0724] Device: Uses the device's GPS sensor to periodically obtain the user's current location.

[0725] Step 8:

[0726] Terminal: Sends acquired location information to the server.

[0727] Step 9:

[0728] Server: Analyzes received location information to determine the user's current location.

[0729] Step 10:

[0730] Server: Collects basic information related to the region (tourist attractions, restaurants, transportation, etc.).

[0731] Step 11:

[0732] User: Speaks to the application and asks questions (e.g., "What are some recommended places to visit in this area?").

[0733] Step 12:

[0734] Device: Uses speech recognition to convert user speech into text data.

[0735] Step 13:

[0736] Device: Uses an emotion engine to analyze the user's emotions from their voice tone, vocabulary, and facial expressions.

[0737] Step 14:

[0738] Terminal: Sends converted text data and sentiment data to the server.

[0739] Step 15:

[0740] Server: Uses natural language processing (NLP) algorithms to analyze the user's question.

[0741] Step 16:

[0742] Server: Based on the analysis results, it adds and updates the user's hobbies, preferences, and emotional information to their profile.

[0743] Step 17:

[0744] Server: Uses AI algorithms to generate optimal content based on location information, hobbies and preferences, and emotional information.

[0745] Step 18:

[0746] Server: Sends the generated information to the terminal.

[0747] Step 19:

[0748] Terminal: Analyzes received information and prepares an interface for displaying it to the user.

[0749] Step 20:

[0750] Device: Provides information via voice guidance using the voice guidance function.

[0751] Step 21:

[0752] User: Provide feedback on the information provided (e.g., "This information was helpful," "This information is inappropriate").

[0753] Step 22:

[0754] Terminal: Sends user feedback to the server.

[0755] Step 23:

[0756] Server: Analyzes received feedback to improve user profiles, sentiment data, and information delivery algorithms.

[0757] Step 24:

[0758] Server: Based on the improved algorithm and profile, we will improve the accuracy of information provided in future updates.

[0759] (Example 2)

[0760] 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".

[0761] Traditional content delivery systems primarily utilize user location information and basic interest / preference information, but they lack consideration for user emotional states and feedback, resulting in problems with the suitability and accuracy of the delivered content. Furthermore, the lack of advanced analysis combining natural language processing and emotion recognition leads to a limited user experience.

[0762] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting user location information, means for analyzing user hobby preference information and emotional information, means for generating and providing optimal content using a generation AI model based on location information, hobby preference information and emotional information, and means for collecting user feedback and improving the information provision algorithm. This makes it possible to provide highly accurate content that corresponds to the user's current emotions and detailed hobby preferences.

[0763] "User" refers to a person who uses this system.

[0764] "Location information" refers to data that indicates the user's current geographical location, and is obtained using technologies such as GPS.

[0765] "Hobby and preference information" refers to information about the areas and activities that a user is interested in, and is obtained from the user's past actions and statements.

[0766] "Emotional information" refers to data that indicates the user's current emotional state, and is obtained from sources such as voice tone and facial expression analysis.

[0767] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information or content.

[0768] "Content" is a general term for information and services provided to users, and includes text, images, audio, and video.

[0769] "Feedback" refers to the evaluations and opinions that users give to the content provided.

[0770] "Natural language processing" refers to the technology used to analyze, understand, and generate human language, and is applied to the analysis of text data.

[0771] An "emotion engine" refers to a system that analyzes a user's voice and facial expressions to recognize their emotional state.

[0772] An "information provision algorithm" refers to the computational methods and processes used to provide users with the most suitable content.

[0773] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information. This system is realized through the cooperation of the user, terminal, and server in executing each process.

[0774] 1. User Authentication and Initial Setup

[0775] The user installs the application and enters the necessary information for initial setup (username, email address, password, etc.). The device sends this information to the server, which stores the information in a database and then generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0776] 2. Collection and analysis of location information

[0777] After the user logs in, the application obtains permission from the user to access location information. The device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to determine the user's current location. It then collects basic information related to the area (tourist attractions, restaurants, transportation, etc.).

[0778] 3. Gathering information on hobbies and preferences and recognizing emotions through conversation.

[0779] When a user speaks to the application and asks a question (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and uses an emotion engine to analyze the emotional information within the user's speech. The emotion engine analyzes emotions from the user's tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies, preferences, and emotional information to their profile.

[0780] 4. Information generation and provision

[0781] Based on the analysis results, the server generates optimal content using a generative AI model (e.g., GPT-4) that takes into account the user's current location, interests, and emotional state. For example, if a user is interested in historical places and is currently excited, the server will prioritize extracting information about historical sites and exciting events in that area. This generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio format using an audio guide function.

[0782] 5. Gathering feedback and making improvements

[0783] Users provide feedback on the information they receive. For example, they input ratings and opinions on their device, such as "This information was helpful" or "This information is inappropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves user profiles, sentiment data, and information delivery algorithms to enhance the accuracy of future information delivery.

[0784] Specific example

[0785] Use cases during sightseeing:

[0786] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information about historical places such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," as well as information about live concerts and major events. The device displays this information and also provides it as an audio guide.

[0787] Usage scenarios on the bus during commute:

[0788] If a user who commutes daily on the same bus route is looking for a new cafe, they can simply say "I'm looking for a new cafe" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new cafes near the route, prioritizing cafes with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[0789] Example of a prompt:

[0790] "This user is currently sightseeing in Shinjuku and is very excited. Please provide them with recommendations for sightseeing spots and events in Shinjuku. This user enjoys visiting historical sites."

[0791] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[0792] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0793] Step 1: User Authentication and Initial Setup

[0794] 1. Input: The user launches the application they installed for the first time and enters their username, email address, and password.

[0795] 2. Specific actions:

[0796] The user enters their username, email address, and password and presses the submit button.

[0797] The device encrypts the information entered.

[0798] 3. Data processing: The device encrypts user information and sends it to the server.

[0799] 4. Output: Encrypted user information is sent to the server.

[0800] 5. Specific actions:

[0801] The server saves the received information to the database.

[0802] The server generates a unique user ID.

[0803] 6. Data processing: The server stores user information and generates a unique user ID.

[0804] 7. Output: The server sends the generated user ID back to the terminal.

[0805] 8. Specific actions:

[0806] The device receives the user ID, saves it to local storage, and completes the initial setup.

[0807] Step 2: Location data collection and analysis

[0808] 1. Input: The user logs into the application and grants permission to access location information.

[0809] 2. Specific actions:

[0810] The device displays a pop-up requesting permission to access its location.

[0811] The user grants permission.

[0812] 3. Data processing: The device periodically acquires its current geographical location information.

[0813] 4. Output: The device obtains its current location information.

[0814] 5. Specific actions:

[0815] The device sends the location information it has acquired to the server.

[0816] 6. Data processing: The server analyzes the location information it receives and identifies the region through reverse geocoding.

[0817] 7. Output: The server collects basic local information (tourist attractions, restaurants, etc.).

[0818] 8. Specific actions:

[0819] The server stores basic information for each region in a database.

[0820] Step 3: Gathering information on hobbies and preferences through conversation and recognizing emotions.

[0821] 1. Input: The user asks a question to the application (e.g., "What are some recommended places to visit in this area?").

[0822] 2. Specific actions:

[0823] The device records audio.

[0824] The device uses speech recognition to convert the spoken words into text data.

[0825] 3. Data processing: The device passes text data to the emotion engine.

[0826] 4. Output: Text data and sentiment data are generated.

[0827] 5. Specific actions:

[0828] The emotion engine analyzes the tone of voice and word choice to generate information about the user's emotions.

[0829] The device sends text data and sentiment data to the server.

[0830] 6. Data processing: The server uses NLP algorithms to analyze text data and understand the question.

[0831] 7. Output: Analysis results are generated and added / updated to the user's profile.

[0832] 8. Specific actions:

[0833] The server updates the user's hobby preferences and emotional data based on the analysis results.

[0834] Step 4: Information generation and provision

[0835] 1. Input: The server generates a prompt message based on the analysis results.

[0836] 2. Specific actions:

[0837] The server inputs a prompt message into the generated AI model (e.g., "The user is currently sightseeing in Shinjuku and is very excited. Please provide this user with recommended sightseeing spots and event information in Shinjuku. The user's hobby is visiting historical sites.").

[0838] 3. Data Processing: The generation AI model generates content based on the prompt text.

[0839] 4. Output: Generated content (tourist spot information, event information) is generated.

[0840] 5. Specific actions:

[0841] The server sends the generated information to the terminal.

[0842] The device displays the received information to the user.

[0843] 6. Data processing: The terminal provides information it has received via voice guidance using its voice guidance function.

[0844] 7. Output: Information and audio guidance are provided to the user.

[0845] Step 5: Gathering feedback and making improvements

[0846] 1. Input: Users provide feedback on the information provided (e.g., "Helpful," "Inappropriate," etc.).

[0847] 2. Specific actions:

[0848] It provides an interface for the device to input feedback.

[0849] The user enters their feedback and presses the submit button.

[0850] 3. Data processing: The device sends feedback data to the server.

[0851] 4. Output: Feedback data is sent to the server.

[0852] 5. Specific actions:

[0853] The server analyzes the feedback data.

[0854] 6. Data Processing: The server improves user profiles and information provision algorithms based on the analysis results.

[0855] 7. Output: The updated algorithms and profiles will be reflected in future information updates.

[0856] 8. Specific actions:

[0857] Based on the updated server information, an algorithm is applied to improve the user experience for subsequent visits.

[0858] (Application Example 2)

[0859] 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."

[0860] In today's world, user needs are extremely diverse, making it difficult to provide satisfying content based solely on location information or personal preferences. Furthermore, there is a demand for real-time, optimal content based on user emotions, but a comprehensive system to achieve this still does not exist. Conventional systems have failed to provide content that takes into account the user's instantaneous emotional state, resulting in a poor user experience.

[0861] 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.

[0862] In this invention, the server includes means for collecting user location information, means for analyzing user hobbies and preferences, means for analyzing user emotional information, means for generating and providing content based on location information, hobbies and preferences, and emotional information, and a terminal for providing the generated content to the user. This makes it possible to provide optimal content in real time based on the user's instantaneous emotional state, location information, and hobbies and preferences.

[0863] A "user" refers to an individual or end-user who uses the system.

[0864] "Location information" refers to data that indicates the geographical location where the user is currently located.

[0865] "Hobby and preference information" refers to data that indicates a user's interests and preferences.

[0866] "Emotional information" refers to data that indicates a user's instantaneous emotional state.

[0867] "Content" refers to information, media, and services provided to users.

[0868] "Means of generation and provision" refers to a part of a system that has methods and functions for creating and providing optimal content to users based on location information, hobby / preference information, and emotional information.

[0869] A "device" refers to a device that the user directly operates (for example, a smartphone or tablet).

[0870] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information.

[0871] User Authentication and Initial Setup

[0872] The user installs the application and enters the necessary information for initial setup (username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0873] Location data collection and analysis

[0874] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (such as tourist attractions, restaurants, and transportation).

[0875] Gathering information on hobbies and preferences through conversation and recognizing emotions.

[0876] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and then uses an emotion engine to recognize the emotions expressed during the utterance. The emotion engine analyzes the user's emotions from their tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds and updates the user's hobbies, preferences, and emotional information to their profile.

[0877] Information generation and provision

[0878] Based on the analysis results, the server uses an AI algorithm to generate optimal content based on the user's current location, interests, and emotional state. For example, if a user is interested in historical places and their current emotional state is "excited," the server will prioritize extracting information about historical tourist spots in that area and also add information about lively events and activities. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[0879] Gathering feedback and making improvements

[0880] Users provide feedback on the information they receive. They input ratings and opinions on their device, such as "This information was helpful" or "This information is not appropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves the accuracy of future information provision by improving the user profile, sentiment data, and information delivery algorithm.

[0881] Specific example

[0882] Specific example 1: Usage case during sightseeing

[0883] If a user is visiting a major city, they might ask the AI ​​system, "What are some interesting places to see in this city?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information on historical places such as "famous parks" and "ancient shrines," as well as information on live concerts and major events. The device displays this information and also provides it as an audio guide.

[0884] Example 2: Usage on a bus during a commute

[0885] If a user who commutes on the same bus route every day is looking for a new restaurant, they can simply say "I'm looking for a new restaurant" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new restaurants near the route, prioritizing places with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[0886] Example of a prompt:

[0887] voice_data = "Tell me some relaxing music you'd like to listen to right now."

[0888] emotion = get_user_emotion(voice_data)

[0889] latitude, longitude = get_geolocation()

[0890] recommendations = recommend_content(emotion, latitude, longitude)

[0891] print(recommendations)

[0892] The system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[0893] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0894] Step 1:

[0895] User Authentication and Initial Setup

[0896] The user installs the application and enters the required information (username, email address, password). The device sends this information to the server. The server stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0897] Input: User's basic information (username, email address, password)

[0898] Output: Unique User ID

[0899] Step 2:

[0900] Location data collection and analysis

[0901] After a user logs in, the application obtains permission from the user to access location information. The device, having received permission, periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the user's current location and collects basic information related to that area.

[0902] Input: User's location information

[0903] Output: User's current location and related basic information

[0904] Step 3:

[0905] Gathering information on hobbies and preferences through conversation and recognizing emotions.

[0906] When a user speaks to the application, the device uses speech recognition to convert the speech into text data. The device then uses an emotion engine to analyze the emotions expressed in the speech and generate emotion information. This text data and emotion information are sent to a server, which analyzes it to add or update the user's profile with their preferences and emotion information.

[0907] Input: User voice input

[0908] Output: Analysis results of text data and sentiment information

[0909] Step 4:

[0910] Information generation and provision

[0911] The server uses an AI algorithm to generate optimal content based on analyzed location information, hobbies and preferences, and emotional information. The generated content is sent to the device, which then displays it to the user. It is also possible to provide information via voice guidance using the voice guidance function.

[0912] Input: Location information, hobbies and preferences, emotional information

[0913] Output: Generated content

[0914] Step 5:

[0915] Gathering feedback and making improvements

[0916] Users provide feedback on the information they receive. The device sends evaluations and opinions, such as "This information was helpful" or "This information is inappropriate," to the server. The server analyzes the received feedback and improves the user profile, sentiment data, and information delivery algorithms.

[0917] Input: User feedback

[0918] Output: Improved information delivery algorithm

[0919] By executing the above steps sequentially, it becomes possible to provide optimal content in real time based on the user's location information, hobbies and preferences, and emotional information.

[0920] 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.

[0921] 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.

[0922] 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.

[0923] [Third Embodiment]

[0924] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0925] 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.

[0926] 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).

[0927] 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.

[0928] 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.

[0929] 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).

[0930] 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.

[0931] 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.

[0932] 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.

[0933] 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.

[0934] 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.

[0935] 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".

[0936] This invention is a system that generates and provides appropriate content based on the user's location information and interest / preference information. This system is realized through the cooperation of three parties: the user, the terminal, and the server, each executing their respective processes.

[0937] 1. User Authentication and Initial Setup

[0938] The user installs the application and enters the necessary information for initial setup (e.g., username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[0939] 2. Collection and analysis of location information

[0940] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (e.g., tourist attractions, restaurants, transportation, etc.).

[0941] 3. Gathering information about hobbies and preferences through conversation.

[0942] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data. This text data is sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies and preferences to their profile.

[0943] 4. Information generation and provision

[0944] Based on the analysis results, the server generates optimal content based on the user's current location and interests. For example, if the user is interested in historical places, the server prioritizes extracting information about historical tourist spots in that area. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[0945] 5. Gathering feedback and making improvements

[0946] Users provide feedback on the information they receive. They input ratings and opinions such as "This information was helpful" on their device, and the device sends this to the server. The server analyzes the received feedback and uses the results to improve the user profile and information provision algorithm. This improves the accuracy of information provided in the future.

[0947] Specific example

[0948] Specific example 1: Usage case during sightseeing

[0949] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data and sends it to the server. Based on the location information and past conversations, the server determines that the user is interested in historical tourist spots and generates information such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," which it then sends back to the device. The device displays this information and provides the user with an audio guide.

[0950] Example 2: Usage on a bus during a commute

[0951] If a user who commutes daily on the same bus route is looking for a new cafe, the terminal tracks the user's current route and sends this information to the server. The server collects information about new cafes near the route and sends it back to the terminal. The terminal then displays and provides voice guidance such as, "There is a new cafe along this route. It is called XX Cafe and has delicious coffee."

[0952] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information and hobby / preference information, and further improves the information provision algorithm based on feedback, thereby providing users with high-quality information.

[0953] The following describes the processing flow.

[0954] Step 1:

[0955] User: Install the application and enter registration information such as username, email address, and password.

[0956] Step 2:

[0957] Terminal: Sends the entered user information to the server.

[0958] Step 3:

[0959] Server: Stores received information in a database and generates a unique user ID.

[0960] Step 4:

[0961] Server: Sends the generated user ID back to the terminal.

[0962] Step 5:

[0963] Terminal: Complete initial setup and display the login screen to the user.

[0964] Step 6:

[0965] User: Log in to the application and grant location access permissions.

[0966] Step 7:

[0967] Device: Uses the device's GPS sensor to periodically obtain the user's current location.

[0968] Step 8:

[0969] Terminal: Sends acquired location information to the server.

[0970] Step 9:

[0971] Server: Analyzes received location information to determine the user's current location.

[0972] Step 10:

[0973] Server: Collects basic information related to the region (tourist attractions, restaurants, transportation, etc.).

[0974] Step 11:

[0975] User: Speaks to the application and asks questions (e.g., "What are some recommended places to visit in this area?").

[0976] Step 12:

[0977] Device: Uses speech recognition to convert user speech into text data.

[0978] Step 13:

[0979] Terminal: Sends the converted text data to the server.

[0980] Step 14:

[0981] Server: Uses natural language processing (NLP) algorithms to analyze the user's question.

[0982] Step 15:

[0983] Server: Based on the analysis results, it adds and updates the user's hobbies and preferences to their profile.

[0984] Step 16:

[0985] Server: Uses an AI algorithm to generate optimal content based on location information and interest / preference information.

[0986] Step 17:

[0987] Server: Sends the generated information to the terminal.

[0988] Step 18:

[0989] Terminal: Analyzes received information and prepares an interface for displaying it to the user.

[0990] Step 19:

[0991] Device: Provides information via voice guidance using the voice guidance function.

[0992] Step 20:

[0993] User: Provide feedback on the information provided (e.g., "This information was helpful").

[0994] Step 21:

[0995] Terminal: Sends user feedback to the server.

[0996] Step 22:

[0997] Server: Analyzes received feedback to improve user profiles and information provision algorithms.

[0998] (Example 1)

[0999] 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."

[1000] Traditional content delivery systems struggled to provide appropriate content because they could not fully utilize users' location information or preferences. Furthermore, they had limitations in responding to changes in user preferences in real time and in improving information delivery algorithms based on user feedback. As a result, they were unable to provide users with the most optimal information, creating a need for improved user experience.

[1001] 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.

[1002] In this invention, the server includes means for the user to input initial setup information, store that information in a database, and generate a user ID; means for collecting the user's location information; and means for analyzing the user's hobbies and preferences. This enables the generation and provision of optimal content based on the user's location information and hobbies and preferences. Furthermore, by including means for the server to convert conversations with the user from speech to text, analyze the text data to update the hobbies and preferences, and collect feedback from the user, analyze the feedback to improve the information provision algorithm, it becomes possible to respond to changes in hobbies and preferences in real time and improve the accuracy of information provision.

[1003] A "user" refers to an individual or group that uses a system to obtain information.

[1004] "Initial setup information" refers to basic information such as name, email address, and password that a user enters when using the application for the first time.

[1005] A "database" refers to an information management system used to store a user's initial settings, location information, and hobby / preference information.

[1006] A "User ID" refers to a unique identifier generated by the database to identify a user.

[1007] "Location information" refers to data that indicates the user's current geographical location, obtained using technologies such as GPS.

[1008] "Hobby and preference information" refers to information that indicates a user's interests and preferences, and is data that the server analyzes and adds to or updates the user profile.

[1009] "Content" refers to information generated and provided by the server based on the user's location information and preferences. Specifically, this includes information on tourist destinations and restaurant recommendations.

[1010] "Speech recognition" refers to the technology that converts a user's spoken words into text data.

[1011] "Text data" refers to data that has been converted using speech recognition technology and expressed as textual information.

[1012] "Natural language processing" refers to a series of processes used by servers to analyze user utterances and extract their meaning.

[1013] "Feedback" refers to the evaluations and opinions that users give regarding the information provided.

[1014] An "information provision algorithm" refers to the calculation procedures and processing methods used to generate optimal content based on the user's location information, hobbies and preferences, and feedback.

[1015] This invention is a system that generates and provides appropriate content based on the user's location information and hobby / preference information. This system is realized through the cooperation of three parties: the user, the terminal, and the server, each executing their respective processes.

[1016] Initial setup

[1017] The user installs the application on a device such as a smartphone and enters initial setup information (name, email address, password, etc.). This information is sent from the device to the server. The server stores the received information in a database (e.g., MySQL) and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1018] Location data collection and analysis

[1019] After a user logs into the application, the application requests permission to access location information. If the user grants permission, the device periodically uses its GPS function to obtain its current geographical location and sends it to the server. The server analyzes the received location information using the Google Maps API to identify the user's current location. Basic information related to that area (tourist attractions, restaurants, transportation, etc.) is also collected.

[1020] Gathering information on hobbies and preferences

[1021] When a user asks a question to the application using voice (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition (e.g., Google Speech-to-Text) to convert the speech into text data. This text data is sent to a server. The server uses natural language processing (NLP) algorithms (e.g., Google Cloud Natural Language API) to analyze the question and add or update the user's hobbies and preferences to their profile.

[1022] Content creation and delivery

[1023] The server generates optimal content based on the user's current location and interests. For example, if a user is interested in historical places, the server prioritizes extracting information about historical tourist attractions in that area. The generated information is sent to the device, which then displays it to the user. It is also possible to provide information in audio format using an audio guide function (e.g., Google Text-to-Speech).

[1024] Gathering feedback and making improvements

[1025] Users provide feedback on the information they receive. For example, they might input a rating or comment on their device, such as "This information was helpful," and the device sends this information to the server. The server analyzes the received feedback and uses the results to improve the user's profile and the information provision algorithm. This improves the accuracy of information provided in the future.

[1026] Specific example

[1027] Specific example 1: Usage case during sightseeing

[1028] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data and sends it to the server. Based on the location information and past conversations, the server determines that the user is interested in historical tourist spots and generates information such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," which it then sends back to the device. The device displays this information and provides the user with an audio guide.

[1029] Example 2: Usage on a bus during a commute

[1030] If a user who commutes daily on the same bus route is looking for a new cafe, the terminal tracks the user's current route and sends this information to the server. The server collects information about new cafes near the route and sends it back to the terminal. The terminal then displays and provides voice guidance such as, "There is a new cafe along this route. It is called XX Cafe and has delicious coffee."

[1031] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1032] Step 1:

[1033] The user installs the application and enters basic information such as their name, email address, and password during the initial setup. The entered information is then sent from the device to the server.

[1034] Input: User's name, email address, and password

[1035] Processing: The terminal sends this data to the server using an HTTP POST request. The server validates the received data and formats it for database storage.

[1036] Output: Initial configuration information sent to the server

[1037] Step 2:

[1038] The server saves the initial configuration information it receives to a database and generates a unique user ID. The generated user ID is sent back to the terminal. The terminal receives this and completes the initial setup.

[1039] Input: Initial setup information submitted by the user

[1040] Processing: The server stores information in the database and generates a user ID. The user ID uses an algorithm (e.g., UUID) to generate a unique identifier to maintain uniqueness.

[1041] Output: A user ID is generated and sent back to the terminal.

[1042] Step 3:

[1043] The user logs into the application. The device requests permission to access location information, and the user grants permission. Input: User login information, location access permission.

[1044] Process: The device sends login information from the user to the server, and the server performs authentication. If authentication is successful, the device requests permission from the user to access location information. If the user grants permission, the device turns on GPS.

[1045] Output: If authentication is successful, the user will log in and grant permission for location activation.

[1046] Step 4:

[1047] The device periodically acquires its current geographical location information and sends it to the server.

[1048] Input: Location information (latitude, longitude) obtained from the device's GPS.

[1049] Processing: The device acquires its current location information at regular intervals (e.g., every minute), encodes it in a data format (such as JSON), and sends it to the server.

[1050] Output: Location data sent to the server

[1051] Step 5:

[1052] The server analyzes the location information it receives to identify the user's location, and then collects basic information related to that region.

[1053] Input: Location information sent from the device

[1054] Processing: The server uses the Google Maps API to analyze location information and identify the region. Then, it collects basic information related to the region (such as tourist attractions, restaurants, and transportation) from a database or external API.

[1055] Output: Identified regional information and related basic information

[1056] Step 6:

[1057] The user inputs a question into the application using voice. The device converts this voice into text data and sends it to the server.

[1058] Input: User voice input

[1059] Processing: The device uses speech recognition technology (e.g., Google Speech-to-Text) to convert the audio data into text data. The converted text is then sent to the server.

[1060] Output: Text data sent to the server

[1061] Step 7:

[1062] The server analyzes text data and adds / updates hobby and preference information to the profile.

[1063] Input: Text data converted from speech

[1064] Processing: The server uses NLP algorithms (e.g., Google Cloud Natural Language API) to analyze text data and identify the user's interests and preferences. This information is added to or updated in the user profile.

[1065] Output: Updated user profile

[1066] Step 8:

[1067] The server generates and sends optimal content to the device based on the user's location and interests. The device displays the generated content to the user, providing audio guidance as needed.

[1068] Input: User's location information, updated interest information

[1069] Processing: The server generates appropriate content based on this information. It prioritizes extracting high-priority information (e.g., tourist spots that match the user's interests). The generated information is sent to the device. The device displays the received content to the user and uses Google Text-to-Speech if it provides an audio guide.

[1070] Output: Content displayed on the device, audio guide

[1071] Step 9:

[1072] The user provides feedback on the information provided. The device sends this feedback to the server. The server analyzes the received feedback and improves the information provision algorithm.

[1073] Input: User feedback information

[1074] Processing: The terminal sends the user's feedback to the server. The server uses a machine learning algorithm to analyze the feedback and updates the algorithm to improve the accuracy of future information provision.

[1075] Output: Improved information delivery algorithm

[1076] (Application Example 1)

[1077] 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."

[1078] Traditional content delivery systems were capable of providing certain content based on user location and interest information, but they lacked real-time information provision and sufficient updating of interest information based on user feedback. Furthermore, the insufficient use of generative AI models to effectively utilize collected information and provide users with optimal content made it difficult to increase user satisfaction. To address these challenges, a more advanced information delivery system is needed.

[1079] 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.

[1080] In this invention, the server includes means for collecting the user's location information, means for analyzing the user's interests and preferences, means including an algorithm for providing target information in real time based on the collected location information and interests and preferences, and means for a generation AI model to generate prompt sentences and recommend appropriate content based on the collected location information and interests and preferences. This enables the user to receive real-time, personalized, and optimal content based on their location information and interests and preferences.

[1081] "Means for collecting user location information" refers to a system that obtains the user's current geographical location using GPS or other location-determining technologies.

[1082] "Methods for analyzing user hobbies and preferences" refer to algorithms that analyze a user's interests and preferences from past usage history, input data, conversations, etc.

[1083] "Means for generating and providing content based on location information and hobby / preference information" refers to a system that automatically creates and provides content optimized for the user based on collected location information and analyzed hobby / preference information.

[1084] "Means including an algorithm for providing target information in real time" refers to an algorithm that analyzes current geographical information and hobby / preference information in real time, and instantly generates and provides corresponding information.

[1085] "A means by which a generative AI model generates prompt sentences and recommends appropriate content" refers to a system in which a generative AI model generates appropriate instruction sentences or recommendation sentences based on the original information, and then recommends the most suitable content to the user based on those.

[1086] The system of the present invention generates and provides appropriate content in real time based on the user's location information and interest / preference information. Specific embodiments are shown below.

[1087] 1. User Authentication and Initial Setup

[1088] Users install a dedicated application on their smartphones. During the initial setup, users enter information such as their username, email address, and password, and send this information from their device to the server. The server stores the received information in a database, generates a unique user ID, and sends it back to the device. Initial setup is completed when the device receives the user ID.

[1089] 2. Collection and analysis of location information

[1090] After the user logs into the application, it obtains permission to access location information. The device periodically obtains the user's current location using a GPS module and sends it to the server. The server analyzes the location information to determine the region where the user is currently located.

[1091] 3. Collection and analysis of hobbies and preferences

[1092] When a user asks a question to the application (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the speech into text data. This text data is sent to a server, where a natural language processing algorithm (e.g., spaCy) is used to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies and preferences to their profile.

[1093] 4. Information generation and provision

[1094] Based on the analysis results, the server uses a generative AI model to generate optimal content using the user's current location and preferences. Specifically, it generates prompt messages and retrieves and generates corresponding information via an external API. This information is sent from the server to the terminal, which then guides the user through display and audio.

[1095] 5. Gathering feedback and making improvements

[1096] It also includes a function for users to rate and provide feedback on the information provided. The collected feedback is sent to the server, which analyzes it and uses it to improve user profiles and information provision algorithms. This improves the accuracy of information provided in the future.

[1097] Hardware and software to be used

[1098] hardware

[1099] Smartphone GPS module: Used to obtain accurate location information.

[1100] Smartphone microphone: Enables voice interaction with the user.

[1101] software

[1102] Geopy: Obtains geographical addresses from latitude and longitude.

[1103] spaCy: A natural language processing algorithm that analyzes user speech.

[1104] Requests: Communicate with external APIs to retrieve tourist and entertainment information.

[1105] Specific example

[1106] If a user is sightseeing in Tokyo, they might ask the app, "Tell me about historical places in Shinjuku." Based on their past history, the app might determine that the user is a history buff and recommend places like Shinjuku Gyoen National Garden and Hanazono Shrine.

[1107] Example of a prompt:

[1108] Find historical tourist attractions near your current location.

[1109] Example: "Tell me about historical places in Shinjuku."

[1110] When a user is on a business trip to Osaka and asks, "What are some interesting activities nearby?", they are judged to be an adventure enthusiast and recommended an escape game event in Namba.

[1111] Example of a prompt:

[1112] Please provide entertainment information that users might find interesting.

[1113] Example: "What are some interesting activities nearby?"

[1114] Thus, the system of the present invention provides personalized content in real time based on the user's location information and interest / preference information. The collected feedback is also taken into consideration to continuously improve the quality of the service.

[1115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1116] Step 1:

[1117] The user installs a dedicated application on their smartphone and enters initial setup information (username, email address, password, etc.). The device sends this input data to the server. The server stores the received information in a database, generates a unique user ID, and sends it back to the device. This completes the registration of the user information.

[1118] Input: Username, email address, password, etc.

[1119] Output: Unique User ID

[1120] Specific operation: User enters the necessary information into the app -> Device sends data to the server -> Server stores the information and generates a user ID -> Unique user ID is sent back to the device

[1121] Step 2:

[1122] The user logs into the application and obtains permission to access location information. The device's GPS module periodically obtains the user's current location and sends it to the server. The server analyzes the location information to determine the region where the user is currently located.

[1123] Input: Location information (latitude and longitude)

[1124] Output: Regional information of the user's current location

[1125] Specific process: User logs into the app -> Obtains permission to access location information -> Device periodically acquires location information -> Device sends location information to the server -> Server analyzes the location information

[1126] Step 3:

[1127] The user asks a question to the app. The device uses speech recognition to convert the user's voice into text data. The converted text data is sent to the server. The server uses a natural language processing algorithm (e.g., spaCy) to analyze the question and adds or updates the user's hobbies and preferences to their profile.

[1128] Input: Audio data

[1129] Output: Updated profile of hobbies and preferences

[1130] Specific process: User asks a question to the app -> Device converts speech to text -> Device sends text data to the server -> Server analyzes it using natural language processing -> User profile is updated

[1131] Step 4:

[1132] The server generates prompt text using an AI model based on the analysis results. Based on the generated prompt text, it retrieves and generates corresponding content information via an external API. The server sends the retrieved information to the terminal. The terminal displays the content to the user and provides audio guidance as needed.

[1133] Input: User profile, location information

[1134] Output: Optimized content information

[1135] Specific operation: The server generates a prompt message using an AI model based on the analysis results -> Information is retrieved from an external API based on the prompt message -> The server sends the retrieved information to the terminal -> The terminal displays the content and provides audio guidance.

[1136] Step 5:

[1137] Users provide feedback on the content they are given. The device sends the feedback data to the server. The server analyzes the collected feedback and uses it to improve user profiles and information provision algorithms.

[1138] Input: Feedback data

[1139] Output: Improved information delivery algorithm

[1140] Specific process: User enters feedback -> Terminal sends feedback data to server -> Server analyzes feedback -> Server improves profile and algorithm.

[1141] 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.

[1142] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information. This system is realized through the cooperation of four parties: the user, the terminal, the server, and the emotion engine, each executing their respective processes.

[1143] 1. User Authentication and Initial Setup

[1144] The user installs the application and enters the necessary information for initial setup (e.g., username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1145] 2. Collection and analysis of location information

[1146] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (e.g., tourist attractions, restaurants, transportation, etc.).

[1147] 3. Gathering information on hobbies and preferences and recognizing emotions through conversation.

[1148] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and then uses an emotion engine to recognize the emotions expressed during the utterance. The emotion engine analyzes the user's emotions from their tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds and updates the user's hobbies, preferences, and emotional information to their profile.

[1149] 4. Information generation and provision

[1150] Based on the analysis results, the server uses an AI algorithm to generate optimal content based on the user's current location, interests, and emotional state. For example, if a user is interested in historical places and their current emotional state is "excited," the server will prioritize extracting information about historical tourist spots in that area and also add information about lively events and activities. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[1151] 5. Gathering feedback and making improvements

[1152] Users provide feedback on the information they receive. They input ratings and opinions on their device, such as "This information was helpful" or "This information is not appropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves the accuracy of future information provision by improving the user profile, sentiment data, and information delivery algorithm.

[1153] Specific example

[1154] Specific example 1: Usage case during sightseeing

[1155] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information about historical places such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," as well as information about live concerts and major events. The device displays this information and also provides it as an audio guide.

[1156] Example 2: Usage on a bus during a commute

[1157] If a user who commutes daily on the same bus route is looking for a new cafe, they can simply say "I'm looking for a new cafe" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new cafes near the route, prioritizing cafes with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[1158] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[1159] The following describes the processing flow.

[1160] Step 1:

[1161] User: Install the application and enter registration information such as username, email address, and password.

[1162] Step 2:

[1163] Terminal: Sends the entered user information to the server.

[1164] Step 3:

[1165] Server: Stores received information in a database and generates a unique user ID.

[1166] Step 4:

[1167] Server: Sends the generated user ID back to the terminal.

[1168] Step 5:

[1169] Terminal: Complete initial setup and display the login screen to the user.

[1170] Step 6:

[1171] User: Log in to the application and grant location access permissions.

[1172] Step 7:

[1173] Device: Uses the device's GPS sensor to periodically obtain the user's current location.

[1174] Step 8:

[1175] Terminal: Sends acquired location information to the server.

[1176] Step 9:

[1177] Server: Analyzes received location information to determine the user's current location.

[1178] Step 10:

[1179] Server: Collects basic information related to the region (tourist attractions, restaurants, transportation, etc.).

[1180] Step 11:

[1181] User: Speaks to the application and asks questions (e.g., "What are some recommended places to visit in this area?").

[1182] Step 12:

[1183] Device: Uses speech recognition to convert user speech into text data.

[1184] Step 13:

[1185] Device: Uses an emotion engine to analyze the user's emotions from their voice tone, vocabulary, and facial expressions.

[1186] Step 14:

[1187] Terminal: Sends converted text data and sentiment data to the server.

[1188] Step 15:

[1189] Server: Uses natural language processing (NLP) algorithms to analyze the user's question.

[1190] Step 16:

[1191] Server: Based on the analysis results, it adds and updates the user's hobbies, preferences, and emotional information to their profile.

[1192] Step 17:

[1193] Server: Uses AI algorithms to generate optimal content based on location information, hobbies and preferences, and emotional information.

[1194] Step 18:

[1195] Server: Sends the generated information to the terminal.

[1196] Step 19:

[1197] Terminal: Analyzes received information and prepares an interface for displaying it to the user.

[1198] Step 20:

[1199] Device: Provides information via voice guidance using the voice guidance function.

[1200] Step 21:

[1201] User: Provide feedback on the information provided (e.g., "This information was helpful," "This information is inappropriate").

[1202] Step 22:

[1203] Terminal: Sends user feedback to the server.

[1204] Step 23:

[1205] Server: Analyzes received feedback to improve user profiles, sentiment data, and information delivery algorithms.

[1206] Step 24:

[1207] Server: Based on the improved algorithm and profile, we will improve the accuracy of information provided in future updates.

[1208] (Example 2)

[1209] 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."

[1210] Traditional content delivery systems primarily utilize user location information and basic interest / preference information, but they lack consideration for user emotional states and feedback, resulting in problems with the suitability and accuracy of the delivered content. Furthermore, the lack of advanced analysis combining natural language processing and emotion recognition leads to a limited user experience.

[1211] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting user location information, means for analyzing user hobby preference information and emotional information, means for generating and providing optimal content using a generation AI model based on location information, hobby preference information and emotional information, and means for collecting user feedback and improving the information provision algorithm. This makes it possible to provide highly accurate content that corresponds to the user's current emotions and detailed hobby preferences.

[1212] "User" refers to a person who uses this system.

[1213] "Location information" refers to data that indicates the user's current geographical location, and is obtained using technologies such as GPS.

[1214] "Hobby and preference information" refers to information about the areas and activities that a user is interested in, and is obtained from the user's past actions and statements.

[1215] "Emotional information" refers to data that indicates the user's current emotional state, and is obtained from sources such as voice tone and facial expression analysis.

[1216] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information or content.

[1217] "Content" is a general term for information and services provided to users, and includes text, images, audio, and video.

[1218] "Feedback" refers to the evaluations and opinions that users give to the content provided.

[1219] "Natural language processing" refers to the technology used to analyze, understand, and generate human language, and is applied to the analysis of text data.

[1220] An "emotion engine" refers to a system that analyzes a user's voice and facial expressions to recognize their emotional state.

[1221] An "information provision algorithm" refers to the computational methods and processes used to provide users with the most suitable content.

[1222] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information. This system is realized through the cooperation of the user, terminal, and server in executing each process.

[1223] 1. User Authentication and Initial Setup

[1224] The user installs the application and enters the necessary information for initial setup (username, email address, password, etc.). The device sends this information to the server, which stores the information in a database and then generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1225] 2. Collection and analysis of location information

[1226] After the user logs in, the application obtains permission from the user to access location information. The device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to determine the user's current location. It then collects basic information related to the area (tourist attractions, restaurants, transportation, etc.).

[1227] 3. Gathering information on hobbies and preferences and recognizing emotions through conversation.

[1228] When a user speaks to the application and asks a question (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and uses an emotion engine to analyze the emotional information within the user's speech. The emotion engine analyzes emotions from the user's tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies, preferences, and emotional information to their profile.

[1229] 4. Information generation and provision

[1230] Based on the analysis results, the server generates optimal content using a generative AI model (e.g., GPT-4) that takes into account the user's current location, interests, and emotional state. For example, if a user is interested in historical places and is currently excited, the server will prioritize extracting information about historical sites and exciting events in that area. This generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio format using an audio guide function.

[1231] 5. Gathering feedback and making improvements

[1232] Users provide feedback on the information they receive. For example, they input ratings and opinions on their device, such as "This information was helpful" or "This information is inappropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves user profiles, sentiment data, and information delivery algorithms to enhance the accuracy of future information delivery.

[1233] Specific example

[1234] Use cases during sightseeing:

[1235] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information about historical places such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," as well as information about live concerts and major events. The device displays this information and also provides it as an audio guide.

[1236] Usage scenarios on the bus during commute:

[1237] If a user who commutes daily on the same bus route is looking for a new cafe, they can simply say "I'm looking for a new cafe" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new cafes near the route, prioritizing cafes with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[1238] Example of a prompt:

[1239] "This user is currently sightseeing in Shinjuku and is very excited. Please provide them with recommendations for sightseeing spots and events in Shinjuku. This user enjoys visiting historical sites."

[1240] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[1241] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1242] Step 1: User Authentication and Initial Setup

[1243] 1. Input: The user launches the application they installed for the first time and enters their username, email address, and password.

[1244] 2. Specific actions:

[1245] The user enters their username, email address, and password and presses the submit button.

[1246] The device encrypts the information entered.

[1247] 3. Data processing: The device encrypts user information and sends it to the server.

[1248] 4. Output: Encrypted user information is sent to the server.

[1249] 5. Specific actions:

[1250] The server saves the received information to the database.

[1251] The server generates a unique user ID.

[1252] 6. Data processing: The server stores user information and generates a unique user ID.

[1253] 7. Output: The server sends the generated user ID back to the terminal.

[1254] 8. Specific actions:

[1255] The device receives the user ID, saves it to local storage, and completes the initial setup.

[1256] Step 2: Location data collection and analysis

[1257] 1. Input: The user logs into the application and grants permission to access location information.

[1258] 2. Specific actions:

[1259] The device displays a pop-up requesting permission to access its location.

[1260] The user grants permission.

[1261] 3. Data processing: The device periodically acquires its current geographical location information.

[1262] 4. Output: The device obtains its current location information.

[1263] 5. Specific actions:

[1264] The device sends the location information it has acquired to the server.

[1265] 6. Data processing: The server analyzes the location information it receives and identifies the region through reverse geocoding.

[1266] 7. Output: The server collects basic local information (tourist attractions, restaurants, etc.).

[1267] 8. Specific actions:

[1268] The server stores basic information for each region in a database.

[1269] Step 3: Gathering information on hobbies and preferences through conversation and recognizing emotions.

[1270] 1. Input: The user asks a question to the application (e.g., "What are some recommended places to visit in this area?").

[1271] 2. Specific actions:

[1272] The device records audio.

[1273] The device uses speech recognition to convert the spoken words into text data.

[1274] 3. Data processing: The device passes text data to the emotion engine.

[1275] 4. Output: Text data and sentiment data are generated.

[1276] 5. Specific actions:

[1277] The emotion engine analyzes the tone of voice and word choice to generate information about the user's emotions.

[1278] The device sends text data and sentiment data to the server.

[1279] 6. Data processing: The server uses NLP algorithms to analyze text data and understand the question.

[1280] 7. Output: Analysis results are generated and added / updated to the user's profile.

[1281] 8. Specific actions:

[1282] The server updates the user's hobby preferences and emotional data based on the analysis results.

[1283] Step 4: Information generation and provision

[1284] 1. Input: The server generates a prompt message based on the analysis results.

[1285] 2. Specific actions:

[1286] The server inputs a prompt message into the generated AI model (e.g., "The user is currently sightseeing in Shinjuku and is very excited. Please provide this user with recommended sightseeing spots and event information in Shinjuku. The user's hobby is visiting historical sites.").

[1287] 3. Data Processing: The generation AI model generates content based on the prompt text.

[1288] 4. Output: Generated content (tourist spot information, event information) is generated.

[1289] 5. Specific actions:

[1290] The server sends the generated information to the terminal.

[1291] The device displays the received information to the user.

[1292] 6. Data processing: The terminal provides information it has received via voice guidance using its voice guidance function.

[1293] 7. Output: Information and audio guidance are provided to the user.

[1294] Step 5: Gathering feedback and making improvements

[1295] 1. Input: Users provide feedback on the information provided (e.g., "Helpful," "Inappropriate," etc.).

[1296] 2. Specific actions:

[1297] It provides an interface for the device to input feedback.

[1298] The user enters their feedback and presses the submit button.

[1299] 3. Data processing: The device sends feedback data to the server.

[1300] 4. Output: Feedback data is sent to the server.

[1301] 5. Specific actions:

[1302] The server analyzes the feedback data.

[1303] 6. Data Processing: The server improves user profiles and information provision algorithms based on the analysis results.

[1304] 7. Output: The updated algorithms and profiles will be reflected in future information updates.

[1305] 8. Specific actions:

[1306] Based on the updated server information, an algorithm is applied to improve the user experience for subsequent visits.

[1307] (Application Example 2)

[1308] 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."

[1309] In today's world, user needs are extremely diverse, making it difficult to provide satisfying content based solely on location information or personal preferences. Furthermore, there is a demand for real-time, optimal content based on user emotions, but a comprehensive system to achieve this still does not exist. Conventional systems have failed to provide content that takes into account the user's instantaneous emotional state, resulting in a poor user experience.

[1310] 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.

[1311] In this invention, the server includes means for collecting user location information, means for analyzing user hobbies and preferences, means for analyzing user emotional information, means for generating and providing content based on location information, hobbies and preferences, and emotional information, and a terminal for providing the generated content to the user. This makes it possible to provide optimal content in real time based on the user's instantaneous emotional state, location information, and hobbies and preferences.

[1312] A "user" refers to an individual or end-user who uses the system.

[1313] "Location information" refers to data that indicates the geographical location where the user is currently located.

[1314] "Hobby and preference information" refers to data that indicates a user's interests and preferences.

[1315] "Emotional information" refers to data that indicates a user's instantaneous emotional state.

[1316] "Content" refers to information, media, and services provided to users.

[1317] "Means of generation and provision" refers to a part of a system that has methods and functions for creating and providing optimal content to users based on location information, hobby / preference information, and emotional information.

[1318] A "device" refers to a device that the user directly operates (for example, a smartphone or tablet).

[1319] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information.

[1320] User Authentication and Initial Setup

[1321] The user installs the application and enters the necessary information for initial setup (username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1322] Location data collection and analysis

[1323] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (such as tourist attractions, restaurants, and transportation).

[1324] Gathering information on hobbies and preferences through conversation and recognizing emotions.

[1325] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and then uses an emotion engine to recognize the emotions expressed during the utterance. The emotion engine analyzes the user's emotions from their tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds and updates the user's hobbies, preferences, and emotional information to their profile.

[1326] Information generation and provision

[1327] Based on the analysis results, the server uses an AI algorithm to generate optimal content based on the user's current location, interests, and emotional state. For example, if a user is interested in historical places and their current emotional state is "excited," the server will prioritize extracting information about historical tourist spots in that area and also add information about lively events and activities. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[1328] Gathering feedback and making improvements

[1329] Users provide feedback on the information they receive. They input ratings and opinions on their device, such as "This information was helpful" or "This information is not appropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves the accuracy of future information provision by improving the user profile, sentiment data, and information delivery algorithm.

[1330] Specific example

[1331] Specific example 1: Usage case during sightseeing

[1332] If a user is visiting a major city, they might ask the AI ​​system, "What are some interesting places to see in this city?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information on historical places such as "famous parks" and "ancient shrines," as well as information on live concerts and major events. The device displays this information and also provides it as an audio guide.

[1333] Example 2: Usage on a bus during a commute

[1334] If a user who commutes on the same bus route every day is looking for a new restaurant, they can simply say "I'm looking for a new restaurant" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new restaurants near the route, prioritizing places with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[1335] Example of a prompt:

[1336] voice_data = "Tell me some relaxing music you'd like to listen to right now."

[1337] emotion = get_user_emotion(voice_data)

[1338] latitude, longitude = get_geolocation()

[1339] recommendations = recommend_content(emotion, latitude, longitude)

[1340] print(recommendations)

[1341] The system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[1342] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1343] Step 1:

[1344] User Authentication and Initial Setup

[1345] The user installs the application and enters the required information (username, email address, password). The device sends this information to the server. The server stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1346] Input: User's basic information (username, email address, password)

[1347] Output: Unique User ID

[1348] Step 2:

[1349] Location data collection and analysis

[1350] After a user logs in, the application obtains permission from the user to access location information. The device, having received permission, periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the user's current location and collects basic information related to that area.

[1351] Input: User's location information

[1352] Output: User's current location and related basic information

[1353] Step 3:

[1354] Gathering information on hobbies and preferences through conversation and recognizing emotions.

[1355] When a user speaks to the application, the device uses speech recognition to convert the speech into text data. The device then uses an emotion engine to analyze the emotions expressed in the speech and generate emotion information. This text data and emotion information are sent to a server, which analyzes it to add or update the user's profile with their preferences and emotion information.

[1356] Input: User voice input

[1357] Output: Analysis results of text data and sentiment information

[1358] Step 4:

[1359] Information generation and provision

[1360] The server uses an AI algorithm to generate optimal content based on analyzed location information, hobbies and preferences, and emotional information. The generated content is sent to the device, which then displays it to the user. It is also possible to provide information via voice guidance using the voice guidance function.

[1361] Input: Location information, hobbies and preferences, emotional information

[1362] Output: Generated content

[1363] Step 5:

[1364] Gathering feedback and making improvements

[1365] Users provide feedback on the information they receive. The device sends evaluations and opinions, such as "This information was helpful" or "This information is inappropriate," to the server. The server analyzes the received feedback and improves the user profile, sentiment data, and information delivery algorithms.

[1366] Input: User feedback

[1367] Output: Improved information delivery algorithm

[1368] By executing the above steps sequentially, it becomes possible to provide optimal content in real time based on the user's location information, hobbies and preferences, and emotional information.

[1369] 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.

[1370] 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.

[1371] 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.

[1372] [Fourth Embodiment]

[1373] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1374] 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.

[1375] 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).

[1376] 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.

[1377] 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.

[1378] 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).

[1379] 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.

[1380] 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.

[1381] 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.

[1382] 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.

[1383] 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.

[1384] 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.

[1385] 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".

[1386] This invention is a system that generates and provides appropriate content based on the user's location information and interest / preference information. This system is realized through the cooperation of three parties: the user, the terminal, and the server, each executing their respective processes.

[1387] 1. User Authentication and Initial Setup

[1388] The user installs the application and enters the necessary information for initial setup (e.g., username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1389] 2. Collection and analysis of location information

[1390] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (e.g., tourist attractions, restaurants, transportation, etc.).

[1391] 3. Gathering information about hobbies and preferences through conversation.

[1392] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data. This text data is sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies and preferences to their profile.

[1393] 4. Information generation and provision

[1394] Based on the analysis results, the server generates optimal content based on the user's current location and interests. For example, if the user is interested in historical places, the server prioritizes extracting information about historical tourist spots in that area. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[1395] 5. Gathering feedback and making improvements

[1396] Users provide feedback on the information they receive. They input ratings and opinions such as "This information was helpful" on their device, and the device sends this to the server. The server analyzes the received feedback and uses the results to improve the user profile and information provision algorithm. This improves the accuracy of information provided in the future.

[1397] Specific example

[1398] Specific example 1: Usage case during sightseeing

[1399] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data and sends it to the server. Based on the location information and past conversations, the server determines that the user is interested in historical tourist spots and generates information such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," which it then sends back to the device. The device displays this information and provides the user with an audio guide.

[1400] Example 2: Usage on a bus during a commute

[1401] If a user who commutes daily on the same bus route is looking for a new cafe, the terminal tracks the user's current route and sends this information to the server. The server collects information about new cafes near the route and sends it back to the terminal. The terminal then displays and provides voice guidance such as, "There is a new cafe along this route. It is called XX Cafe and has delicious coffee."

[1402] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information and hobby / preference information, and further improves the information provision algorithm based on feedback, thereby providing users with high-quality information.

[1403] The following describes the processing flow.

[1404] Step 1:

[1405] User: Install the application and enter registration information such as username, email address, and password.

[1406] Step 2:

[1407] Terminal: Sends the entered user information to the server.

[1408] Step 3:

[1409] Server: Stores received information in a database and generates a unique user ID.

[1410] Step 4:

[1411] Server: Sends the generated user ID back to the terminal.

[1412] Step 5:

[1413] Terminal: Complete initial setup and display the login screen to the user.

[1414] Step 6:

[1415] User: Log in to the application and grant location access permissions.

[1416] Step 7:

[1417] Device: Uses the device's GPS sensor to periodically obtain the user's current location.

[1418] Step 8:

[1419] Terminal: Sends acquired location information to the server.

[1420] Step 9:

[1421] Server: Analyzes received location information to determine the user's current location.

[1422] Step 10:

[1423] Server: Collects basic information related to the region (tourist attractions, restaurants, transportation, etc.).

[1424] Step 11:

[1425] User: Speaks to the application and asks questions (e.g., "What are some recommended places to visit in this area?").

[1426] Step 12:

[1427] Device: Uses speech recognition to convert user speech into text data.

[1428] Step 13:

[1429] Terminal: Sends the converted text data to the server.

[1430] Step 14:

[1431] Server: Uses natural language processing (NLP) algorithms to analyze the user's question.

[1432] Step 15:

[1433] Server: Based on the analysis results, it adds and updates the user's hobbies and preferences to their profile.

[1434] Step 16:

[1435] Server: Uses an AI algorithm to generate optimal content based on location information and interest / preference information.

[1436] Step 17:

[1437] Server: Sends the generated information to the terminal.

[1438] Step 18:

[1439] Terminal: Analyzes received information and prepares an interface for displaying it to the user.

[1440] Step 19:

[1441] Device: Provides information via voice guidance using the voice guidance function.

[1442] Step 20:

[1443] User: Provide feedback on the information provided (e.g., "This information was helpful").

[1444] Step 21:

[1445] Terminal: Sends user feedback to the server.

[1446] Step 22:

[1447] Server: Analyzes received feedback to improve user profiles and information provision algorithms.

[1448] (Example 1)

[1449] 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".

[1450] Traditional content delivery systems struggled to provide appropriate content because they could not fully utilize users' location information or preferences. Furthermore, they had limitations in responding to changes in user preferences in real time and in improving information delivery algorithms based on user feedback. As a result, they were unable to provide users with the most optimal information, creating a need for improved user experience.

[1451] 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.

[1452] In this invention, the server includes means for the user to input initial setup information, store that information in a database, and generate a user ID; means for collecting the user's location information; and means for analyzing the user's hobbies and preferences. This enables the generation and provision of optimal content based on the user's location information and hobbies and preferences. Furthermore, by including means for the server to convert conversations with the user from speech to text, analyze the text data to update the hobbies and preferences, and collect feedback from the user, analyze the feedback to improve the information provision algorithm, it becomes possible to respond to changes in hobbies and preferences in real time and improve the accuracy of information provision.

[1453] A "user" refers to an individual or group that uses a system to obtain information.

[1454] "Initial setup information" refers to basic information such as name, email address, and password that a user enters when using the application for the first time.

[1455] A "database" refers to an information management system used to store a user's initial settings, location information, and hobby / preference information.

[1456] A "User ID" refers to a unique identifier generated by the database to identify a user.

[1457] "Location information" refers to data that indicates the user's current geographical location, obtained using technologies such as GPS.

[1458] "Hobby and preference information" refers to information that indicates a user's interests and preferences, and is data that the server analyzes and adds to or updates the user profile.

[1459] "Content" refers to information generated and provided by the server based on the user's location information and preferences. Specifically, this includes information on tourist destinations and restaurant recommendations.

[1460] "Speech recognition" refers to the technology that converts a user's spoken words into text data.

[1461] "Text data" refers to data that has been converted using speech recognition technology and expressed as textual information.

[1462] "Natural language processing" refers to a series of processes used by servers to analyze user utterances and extract their meaning.

[1463] "Feedback" refers to the evaluations and opinions that users give regarding the information provided.

[1464] An "information provision algorithm" refers to the calculation procedures and processing methods used to generate optimal content based on the user's location information, hobbies and preferences, and feedback.

[1465] This invention is a system that generates and provides appropriate content based on the user's location information and hobby / preference information. This system is realized through the cooperation of three parties: the user, the terminal, and the server, each executing their respective processes.

[1466] Initial setup

[1467] The user installs the application on a device such as a smartphone and enters initial setup information (name, email address, password, etc.). This information is sent from the device to the server. The server stores the received information in a database (e.g., MySQL) and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1468] Location data collection and analysis

[1469] After a user logs into the application, the application requests permission to access location information. If the user grants permission, the device periodically uses its GPS function to obtain its current geographical location and sends it to the server. The server analyzes the received location information using the Google Maps API to identify the user's current location. Basic information related to that area (tourist attractions, restaurants, transportation, etc.) is also collected.

[1470] Gathering information on hobbies and preferences

[1471] When a user asks a question to the application using voice (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition (e.g., Google Speech-to-Text) to convert the speech into text data. This text data is sent to a server. The server uses natural language processing (NLP) algorithms (e.g., Google Cloud Natural Language API) to analyze the question and add or update the user's hobbies and preferences to their profile.

[1472] Content creation and delivery

[1473] The server generates optimal content based on the user's current location and interests. For example, if a user is interested in historical places, the server prioritizes extracting information about historical tourist attractions in that area. The generated information is sent to the device, which then displays it to the user. It is also possible to provide information in audio format using an audio guide function (e.g., Google Text-to-Speech).

[1474] Gathering feedback and making improvements

[1475] Users provide feedback on the information they receive. For example, they might input a rating or comment on their device, such as "This information was helpful," and the device sends this information to the server. The server analyzes the received feedback and uses the results to improve the user's profile and the information provision algorithm. This improves the accuracy of information provided in the future.

[1476] Specific example

[1477] Specific example 1: Usage case during sightseeing

[1478] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data and sends it to the server. Based on the location information and past conversations, the server determines that the user is interested in historical tourist spots and generates information such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," which it then sends back to the device. The device displays this information and provides the user with an audio guide.

[1479] Example 2: Usage on a bus during a commute

[1480] If a user who commutes daily on the same bus route is looking for a new cafe, the terminal tracks the user's current route and sends this information to the server. The server collects information about new cafes near the route and sends it back to the terminal. The terminal then displays and provides voice guidance such as, "There is a new cafe along this route. It is called XX Cafe and has delicious coffee."

[1481] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1482] Step 1:

[1483] The user installs the application and enters basic information such as their name, email address, and password during the initial setup. The entered information is then sent from the device to the server.

[1484] Input: User's name, email address, and password

[1485] Processing: The terminal sends this data to the server using an HTTP POST request. The server validates the received data and formats it for database storage.

[1486] Output: Initial configuration information sent to the server

[1487] Step 2:

[1488] The server saves the initial configuration information it receives to a database and generates a unique user ID. The generated user ID is sent back to the terminal. The terminal receives this and completes the initial setup.

[1489] Input: Initial setup information submitted by the user

[1490] Processing: The server stores information in the database and generates a user ID. The user ID uses an algorithm (e.g., UUID) to generate a unique identifier to maintain uniqueness.

[1491] Output: A user ID is generated and sent back to the terminal.

[1492] Step 3:

[1493] The user logs into the application. The device requests permission to access location information, and the user grants permission. Input: User login information, location access permission.

[1494] Process: The device sends login information from the user to the server, and the server performs authentication. If authentication is successful, the device requests permission from the user to access location information. If the user grants permission, the device turns on GPS.

[1495] Output: If authentication is successful, the user will log in and grant permission for location activation.

[1496] Step 4:

[1497] The device periodically acquires its current geographical location information and sends it to the server.

[1498] Input: Location information (latitude, longitude) obtained from the device's GPS.

[1499] Processing: The device acquires its current location information at regular intervals (e.g., every minute), encodes it in a data format (such as JSON), and sends it to the server.

[1500] Output: Location data sent to the server

[1501] Step 5:

[1502] The server analyzes the location information it receives to identify the user's location, and then collects basic information related to that region.

[1503] Input: Location information sent from the device

[1504] Processing: The server uses the Google Maps API to analyze location information and identify the region. It then collects basic information related to the region (such as tourist attractions, restaurants, and transportation) from a database or external API.

[1505] Output: Identified regional information and related basic information

[1506] Step 6:

[1507] The user inputs a question into the application using voice. The device converts this voice into text data and sends it to the server.

[1508] Input: User voice input

[1509] Processing: The device uses speech recognition technology (e.g., Google Speech-to-Text) to convert the audio data into text data. The converted text is then sent to the server.

[1510] Output: Text data sent to the server

[1511] Step 7:

[1512] The server analyzes text data and adds / updates hobby and preference information to the profile.

[1513] Input: Text data converted from speech

[1514] Processing: The server uses NLP algorithms (e.g., Google Cloud Natural Language API) to analyze text data and identify the user's interests and preferences. This information is added to or updated in the user profile.

[1515] Output: Updated user profile

[1516] Step 8:

[1517] The server generates and sends optimal content to the device based on the user's location and interests. The device displays the generated content to the user, providing audio guidance as needed.

[1518] Input: User's location information, updated interest information

[1519] Processing: The server generates appropriate content based on this information. It prioritizes extracting high-priority information (e.g., tourist spots that match the user's interests). The generated information is sent to the device. The device displays the received content to the user and uses Google Text-to-Speech if it provides an audio guide.

[1520] Output: Content displayed on the device, audio guide

[1521] Step 9:

[1522] The user provides feedback on the information provided. The device sends this feedback to the server. The server analyzes the received feedback and improves the information provision algorithm.

[1523] Input: User feedback information

[1524] Processing: The terminal sends the user's feedback to the server. The server uses a machine learning algorithm to analyze the feedback and updates the algorithm to improve the accuracy of future information provision.

[1525] Output: Improved information delivery algorithm

[1526] (Application Example 1)

[1527] 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".

[1528] Traditional content delivery systems were capable of providing certain content based on user location and interest information, but they lacked real-time information provision and sufficient updating of interest information based on user feedback. Furthermore, the insufficient use of generative AI models to effectively utilize collected information and provide users with optimal content made it difficult to increase user satisfaction. To address these challenges, a more advanced information delivery system is needed.

[1529] 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.

[1530] In this invention, the server includes means for collecting the user's location information, means for analyzing the user's interests and preferences, means including an algorithm for providing target information in real time based on the collected location information and interests and preferences, and means for a generation AI model to generate prompt sentences and recommend appropriate content based on the collected location information and interests and preferences. This enables the user to receive real-time, personalized, and optimal content based on their location information and interests and preferences.

[1531] "Means for collecting user location information" refers to a system that obtains the user's current geographical location using GPS or other location-determining technologies.

[1532] "Methods for analyzing user hobbies and preferences" refer to algorithms that analyze a user's interests and preferences from past usage history, input data, conversations, etc.

[1533] "Means for generating and providing content based on location information and hobby / preference information" refers to a system that automatically creates and provides content optimized for the user based on collected location information and analyzed hobby / preference information.

[1534] "Means including an algorithm for providing target information in real time" refers to an algorithm that analyzes current geographical information and hobby / preference information in real time, and instantly generates and provides corresponding information.

[1535] "A means by which a generative AI model generates prompt sentences and recommends appropriate content" refers to a system in which a generative AI model generates appropriate instruction sentences or recommendation sentences based on the original information, and then recommends the most suitable content to the user based on those.

[1536] The system of the present invention generates and provides appropriate content in real time based on the user's location information and interest / preference information. Specific embodiments are shown below.

[1537] 1. User Authentication and Initial Setup

[1538] Users install a dedicated application on their smartphones. During the initial setup, users enter information such as their username, email address, and password, and send this information from their device to the server. The server stores the received information in a database, generates a unique user ID, and sends it back to the device. Initial setup is completed when the device receives the user ID.

[1539] 2. Collection and analysis of location information

[1540] After the user logs into the application, it obtains permission to access location information. The device periodically obtains the user's current location using a GPS module and sends it to the server. The server analyzes the location information to determine the region where the user is currently located.

[1541] 3. Collection and analysis of hobbies and preferences

[1542] When a user asks a question to the application (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the speech into text data. This text data is sent to a server, where a natural language processing algorithm (e.g., spaCy) is used to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies and preferences to their profile.

[1543] 4. Information generation and provision

[1544] Based on the analysis results, the server uses a generative AI model to generate optimal content using the user's current location and preferences. Specifically, it generates prompt messages and retrieves and generates corresponding information via an external API. This information is sent from the server to the terminal, which then guides the user through display and audio.

[1545] 5. Gathering feedback and making improvements

[1546] It also includes a function for users to rate and provide feedback on the information provided. The collected feedback is sent to the server, which analyzes it and uses it to improve user profiles and information provision algorithms. This improves the accuracy of information provided in the future.

[1547] Hardware and software to be used

[1548] hardware

[1549] Smartphone GPS module: Used to obtain accurate location information.

[1550] Smartphone microphone: Enables voice interaction with the user.

[1551] software

[1552] Geopy: Obtains geographical addresses from latitude and longitude.

[1553] spaCy: A natural language processing algorithm that analyzes user speech.

[1554] Requests: Communicate with external APIs to retrieve tourist and entertainment information.

[1555] Specific example

[1556] If a user is sightseeing in Tokyo, they might ask the app, "Tell me about historical places in Shinjuku." Based on their past history, the app might determine that the user is a history buff and recommend places like Shinjuku Gyoen National Garden and Hanazono Shrine.

[1557] Example of a prompt:

[1558] Find historical tourist attractions near your current location.

[1559] Example: "Tell me about historical places in Shinjuku."

[1560] When a user is on a business trip to Osaka and asks, "What are some interesting activities nearby?", they are judged to be an adventure enthusiast and recommended an escape game event in Namba.

[1561] Example of a prompt:

[1562] Please provide entertainment information that users might find interesting.

[1563] Example: "What are some interesting activities nearby?"

[1564] Thus, the system of the present invention provides personalized content in real time based on the user's location information and interest / preference information. The collected feedback is also taken into consideration to continuously improve the quality of the service.

[1565] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1566] Step 1:

[1567] The user installs a dedicated application on their smartphone and enters initial setup information (username, email address, password, etc.). The device sends this input data to the server. The server stores the received information in a database, generates a unique user ID, and sends it back to the device. This completes the registration of the user information.

[1568] Input: Username, email address, password, etc.

[1569] Output: Unique User ID

[1570] Specific operation: User enters the necessary information into the app -> Device sends data to the server -> Server stores the information and generates a user ID -> Unique user ID is sent back to the device

[1571] Step 2:

[1572] The user logs into the application and obtains permission to access location information. The device's GPS module periodically obtains the user's current location and sends it to the server. The server analyzes the location information to determine the region where the user is currently located.

[1573] Input: Location information (latitude and longitude)

[1574] Output: Regional information of the user's current location

[1575] Specific process: User logs into the app -> Obtains permission to access location information -> Device periodically acquires location information -> Device sends location information to the server -> Server analyzes the location information

[1576] Step 3:

[1577] The user asks a question to the app. The device uses speech recognition to convert the user's voice into text data. The converted text data is sent to the server. The server uses a natural language processing algorithm (e.g., spaCy) to analyze the question and adds or updates the user's hobbies and preferences to their profile.

[1578] Input: Audio data

[1579] Output: Updated profile of hobbies and preferences

[1580] Specific process: User asks a question to the app -> Device converts speech to text -> Device sends text data to the server -> Server analyzes it using natural language processing -> User profile is updated

[1581] Step 4:

[1582] The server generates prompt text using an AI model based on the analysis results. Based on the generated prompt text, it retrieves and generates corresponding content information via an external API. The server sends the retrieved information to the terminal. The terminal displays the content to the user and provides audio guidance as needed.

[1583] Input: User profile, location information

[1584] Output: Optimized content information

[1585] Specific operation: The server generates a prompt message using an AI model based on the analysis results -> Information is retrieved from an external API based on the prompt message -> The server sends the retrieved information to the terminal -> The terminal displays the content and provides audio guidance.

[1586] Step 5:

[1587] Users provide feedback on the content they are given. The device sends the feedback data to the server. The server analyzes the collected feedback and uses it to improve user profiles and information provision algorithms.

[1588] Input: Feedback data

[1589] Output: Improved information delivery algorithm

[1590] Specific process: User enters feedback -> Terminal sends feedback data to server -> Server analyzes feedback -> Server improves profile and algorithm.

[1591] 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.

[1592] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information. This system is realized through the cooperation of four parties: the user, the terminal, the server, and the emotion engine, each executing their respective processes.

[1593] 1. User Authentication and Initial Setup

[1594] The user installs the application and enters the necessary information for initial setup (e.g., username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1595] 2. Collection and analysis of location information

[1596] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (e.g., tourist attractions, restaurants, transportation, etc.).

[1597] 3. Gathering information on hobbies and preferences and recognizing emotions through conversation.

[1598] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and then uses an emotion engine to recognize the emotions expressed during the utterance. The emotion engine analyzes the user's emotions from their tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds and updates the user's hobbies, preferences, and emotional information to their profile.

[1599] 4. Information generation and provision

[1600] Based on the analysis results, the server uses an AI algorithm to generate optimal content based on the user's current location, interests, and emotional state. For example, if a user is interested in historical places and their current emotional state is "excited," the server will prioritize extracting information about historical tourist spots in that area and also add information about lively events and activities. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[1601] 5. Gathering feedback and making improvements

[1602] Users provide feedback on the information they receive. They input ratings and opinions on their device, such as "This information was helpful" or "This information is not appropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves the accuracy of future information provision by improving the user profile, sentiment data, and information delivery algorithm.

[1603] Specific example

[1604] Specific example 1: Usage case during sightseeing

[1605] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information about historical places such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," as well as information about live concerts and major events. The device displays this information and also provides it as an audio guide.

[1606] Example 2: Usage on a bus during a commute

[1607] If a user who commutes daily on the same bus route is looking for a new cafe, they can simply say "I'm looking for a new cafe" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new cafes near the route, prioritizing cafes with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[1608] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[1609] The following describes the processing flow.

[1610] Step 1:

[1611] User: Install the application and enter registration information such as username, email address, and password.

[1612] Step 2:

[1613] Terminal: Sends the entered user information to the server.

[1614] Step 3:

[1615] Server: Stores received information in a database and generates a unique user ID.

[1616] Step 4:

[1617] Server: Sends the generated user ID back to the terminal.

[1618] Step 5:

[1619] Terminal: Complete initial setup and display the login screen to the user.

[1620] Step 6:

[1621] User: Log in to the application and grant location access permissions.

[1622] Step 7:

[1623] Device: Uses the device's GPS sensor to periodically obtain the user's current location.

[1624] Step 8:

[1625] Terminal: Sends acquired location information to the server.

[1626] Step 9:

[1627] Server: Analyzes received location information to determine the user's current location.

[1628] Step 10:

[1629] Server: Collects basic information related to the region (tourist attractions, restaurants, transportation, etc.).

[1630] Step 11:

[1631] User: Speaks to the application and asks questions (e.g., "What are some recommended places to visit in this area?").

[1632] Step 12:

[1633] Device: Uses speech recognition to convert user speech into text data.

[1634] Step 13:

[1635] Device: Uses an emotion engine to analyze the user's emotions from their voice tone, vocabulary, and facial expressions.

[1636] Step 14:

[1637] Terminal: Sends converted text data and sentiment data to the server.

[1638] Step 15:

[1639] Server: Uses natural language processing (NLP) algorithms to analyze the user's question.

[1640] Step 16:

[1641] Server: Based on the analysis results, it adds and updates the user's hobbies, preferences, and emotional information to their profile.

[1642] Step 17:

[1643] Server: Uses AI algorithms to generate optimal content based on location information, hobbies and preferences, and emotional information.

[1644] Step 18:

[1645] Server: Sends the generated information to the terminal.

[1646] Step 19:

[1647] Terminal: Analyzes received information and prepares an interface for displaying it to the user.

[1648] Step 20:

[1649] Device: Provides information via voice guidance using the voice guidance function.

[1650] Step 21:

[1651] User: Provide feedback on the information provided (e.g., "This information was helpful," "This information is inappropriate").

[1652] Step 22:

[1653] Terminal: Sends user feedback to the server.

[1654] Step 23:

[1655] Server: Analyzes received feedback to improve user profiles, sentiment data, and information delivery algorithms.

[1656] Step 24:

[1657] Server: Based on the improved algorithm and profile, we will improve the accuracy of information provided in future updates.

[1658] (Example 2)

[1659] 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".

[1660] Traditional content delivery systems primarily utilize user location information and basic interest / preference information, but they lack consideration for user emotional states and feedback, resulting in problems with the suitability and accuracy of the delivered content. Furthermore, the lack of advanced analysis combining natural language processing and emotion recognition leads to a limited user experience.

[1661] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting user location information, means for analyzing user hobby preference information and emotional information, means for generating and providing optimal content using a generation AI model based on location information, hobby preference information and emotional information, and means for collecting user feedback and improving the information provision algorithm. This makes it possible to provide highly accurate content that corresponds to the user's current emotions and detailed hobby preferences.

[1662] "User" refers to a person who uses this system.

[1663] "Location information" refers to data that indicates the user's current geographical location, and is obtained using technologies such as GPS.

[1664] "Hobby and preference information" refers to information about the areas and activities that a user is interested in, and is obtained from the user's past actions and statements.

[1665] "Emotional information" refers to data that indicates the user's current emotional state, and is obtained from sources such as voice tone and facial expression analysis.

[1666] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information or content.

[1667] "Content" is a general term for information and services provided to users, and includes text, images, audio, and video.

[1668] "Feedback" refers to the evaluations and opinions that users give to the content provided.

[1669] "Natural language processing" refers to the technology used to analyze, understand, and generate human language, and is applied to the analysis of text data.

[1670] An "emotion engine" refers to a system that analyzes a user's voice and facial expressions to recognize their emotional state.

[1671] An "information provision algorithm" refers to the computational methods and processes used to provide users with the most suitable content.

[1672] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information. This system is realized through the cooperation of the user, terminal, and server in executing each process.

[1673] 1. User Authentication and Initial Setup

[1674] The user installs the application and enters the necessary information for initial setup (username, email address, password, etc.). The device sends this information to the server, which stores the information in a database and then generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1675] 2. Collection and analysis of location information

[1676] After the user logs in, the application obtains permission from the user to access location information. The device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to determine the user's current location. It then collects basic information related to the area (tourist attractions, restaurants, transportation, etc.).

[1677] 3. Gathering information on hobbies and preferences and recognizing emotions through conversation.

[1678] When a user speaks to the application and asks a question (e.g., "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and uses an emotion engine to analyze the emotional information within the user's speech. The emotion engine analyzes emotions from the user's tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds or updates the user's hobbies, preferences, and emotional information to their profile.

[1679] 4. Information generation and provision

[1680] Based on the analysis results, the server generates optimal content using a generative AI model (e.g., GPT-4) that takes into account the user's current location, interests, and emotional state. For example, if a user is interested in historical places and is currently excited, the server will prioritize extracting information about historical sites and exciting events in that area. This generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio format using an audio guide function.

[1681] 5. Gathering feedback and making improvements

[1682] Users provide feedback on the information they receive. For example, they input ratings and opinions on their device, such as "This information was helpful" or "This information is inappropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves user profiles, sentiment data, and information delivery algorithms to enhance the accuracy of future information delivery.

[1683] Specific example

[1684] Use cases during sightseeing:

[1685] If a user is sightseeing in Shinjuku, Tokyo, they might ask the AI ​​system, "What are some interesting places to see in Shinjuku?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information about historical places such as "Shinjuku Gyoen National Garden" and "Hanazono Shrine," as well as information about live concerts and major events. The device displays this information and also provides it as an audio guide.

[1686] Usage scenarios on the bus during commute:

[1687] If a user who commutes daily on the same bus route is looking for a new cafe, they can simply say "I'm looking for a new cafe" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new cafes near the route, prioritizing cafes with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[1688] Example of a prompt:

[1689] "This user is currently sightseeing in Shinjuku and is very excited. Please provide them with recommendations for sightseeing spots and events in Shinjuku. This user enjoys visiting historical sites."

[1690] Thus, the system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[1691] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1692] Step 1: User Authentication and Initial Setup

[1693] 1. Input: The user launches the application they installed for the first time and enters their username, email address, and password.

[1694] 2. Specific actions:

[1695] The user enters their username, email address, and password and presses the submit button.

[1696] The device encrypts the information entered.

[1697] 3. Data processing: The device encrypts user information and sends it to the server.

[1698] 4. Output: Encrypted user information is sent to the server.

[1699] 5. Specific actions:

[1700] The server saves the received information to the database.

[1701] The server generates a unique user ID.

[1702] 6. Data processing: The server stores user information and generates a unique user ID.

[1703] 7. Output: The server sends the generated user ID back to the terminal.

[1704] 8. Specific actions:

[1705] The device receives the user ID, saves it to local storage, and completes the initial setup.

[1706] Step 2: Location data collection and analysis

[1707] 1. Input: The user logs into the application and grants permission to access location information.

[1708] 2. Specific actions:

[1709] The device displays a pop-up requesting permission to access its location.

[1710] The user grants permission.

[1711] 3. Data processing: The device periodically acquires its current geographical location information.

[1712] 4. Output: The device obtains its current location information.

[1713] 5. Specific actions:

[1714] The device sends the location information it has acquired to the server.

[1715] 6. Data processing: The server analyzes the location information it receives and identifies the region through reverse geocoding.

[1716] 7. Output: The server collects basic local information (tourist attractions, restaurants, etc.).

[1717] 8. Specific actions:

[1718] The server stores basic information for each region in a database.

[1719] Step 3: Gathering information on hobbies and preferences through conversation and recognizing emotions.

[1720] 1. Input: The user asks a question to the application (e.g., "What are some recommended places to visit in this area?").

[1721] 2. Specific actions:

[1722] The device records audio.

[1723] The device uses speech recognition to convert the spoken words into text data.

[1724] 3. Data processing: The device passes text data to the emotion engine.

[1725] 4. Output: Text data and sentiment data are generated.

[1726] 5. Specific actions:

[1727] The emotion engine analyzes the tone of voice and word choice to generate information about the user's emotions.

[1728] The device sends text data and sentiment data to the server.

[1729] 6. Data processing: The server uses NLP algorithms to analyze text data and understand the question.

[1730] 7. Output: Analysis results are generated and added / updated to the user's profile.

[1731] 8. Specific actions:

[1732] The server updates the user's hobby preferences and emotional data based on the analysis results.

[1733] Step 4: Information generation and provision

[1734] 1. Input: The server generates a prompt message based on the analysis results.

[1735] 2. Specific actions:

[1736] The server inputs a prompt message into the generated AI model (e.g., "The user is currently sightseeing in Shinjuku and is very excited. Please provide this user with recommended sightseeing spots and event information in Shinjuku. The user's hobby is visiting historical sites.").

[1737] 3. Data Processing: The generation AI model generates content based on the prompt text.

[1738] 4. Output: Generated content (tourist spot information, event information) is generated.

[1739] 5. Specific actions:

[1740] The server sends the generated information to the terminal.

[1741] The device displays the received information to the user.

[1742] 6. Data processing: The terminal provides information it has received via voice guidance using its voice guidance function.

[1743] 7. Output: Information and audio guidance are provided to the user.

[1744] Step 5: Gathering feedback and making improvements

[1745] 1. Input: Users provide feedback on the information provided (e.g., "Helpful," "Inappropriate," etc.).

[1746] 2. Specific actions:

[1747] It provides an interface for the device to input feedback.

[1748] The user enters their feedback and presses the submit button.

[1749] 3. Data processing: The device sends feedback data to the server.

[1750] 4. Output: Feedback data is sent to the server.

[1751] 5. Specific actions:

[1752] The server analyzes the feedback data.

[1753] 6. Data Processing: The server improves user profiles and information provision algorithms based on the analysis results.

[1754] 7. Output: The updated algorithms and profiles will be reflected in future information updates.

[1755] 8. Specific actions:

[1756] Based on the updated server information, an algorithm is applied to improve the user experience for subsequent visits.

[1757] (Application Example 2)

[1758] 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".

[1759] In today's world, user needs are extremely diverse, making it difficult to provide satisfying content based solely on location information or personal preferences. Furthermore, there is a demand for real-time, optimal content based on user emotions, but a comprehensive system to achieve this still does not exist. Conventional systems have failed to provide content that takes into account the user's instantaneous emotional state, resulting in a poor user experience.

[1760] 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.

[1761] In this invention, the server includes means for collecting user location information, means for analyzing user hobbies and preferences, means for analyzing user emotional information, means for generating and providing content based on location information, hobbies and preferences, and emotional information, and a terminal for providing the generated content to the user. This makes it possible to provide optimal content in real time based on the user's instantaneous emotional state, location information, and hobbies and preferences.

[1762] A "user" refers to an individual or end-user who uses the system.

[1763] "Location information" refers to data that indicates the geographical location where the user is currently located.

[1764] "Hobby and preference information" refers to data that indicates a user's interests and preferences.

[1765] "Emotional information" refers to data that indicates a user's instantaneous emotional state.

[1766] "Content" refers to information, media, and services provided to users.

[1767] "Means of generation and provision" refers to a part of a system that has methods and functions for creating and providing optimal content to users based on location information, hobby / preference information, and emotional information.

[1768] A "device" refers to a device that the user directly operates (for example, a smartphone or tablet).

[1769] This invention is a system that generates and provides appropriate content based on the user's location information, hobbies and preferences, and emotional information.

[1770] User Authentication and Initial Setup

[1771] The user installs the application and enters the necessary information for initial setup (username, email address, password, etc.). The entered information is sent from the device to the server, which stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1772] Location data collection and analysis

[1773] After a user logs in, the application obtains permission from the user to access location information. Based on this permission, the device periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the region where the user is currently located. Next, it collects basic information related to that region (such as tourist attractions, restaurants, and transportation).

[1774] Gathering information on hobbies and preferences through conversation and recognizing emotions.

[1775] When a user speaks to the application and asks a question (for example, "What are some recommended places to visit in this area?"), the device uses speech recognition to convert the utterance into text data and then uses an emotion engine to recognize the emotions expressed during the utterance. The emotion engine analyzes the user's emotions from their tone of voice, vocabulary, and facial expressions (if a camera is available). This text data and emotion data are sent to a server, which uses natural language processing (NLP) algorithms to analyze the question. Based on the analysis results, the server adds and updates the user's hobbies, preferences, and emotional information to their profile.

[1776] Information generation and provision

[1777] Based on the analysis results, the server uses an AI algorithm to generate optimal content based on the user's current location, interests, and emotional state. For example, if a user is interested in historical places and their current emotional state is "excited," the server will prioritize extracting information about historical tourist spots in that area and also add information about lively events and activities. The generated information is sent to the device, which then displays the received information to the user. It is also possible to provide information in audio form using an audio guide function.

[1778] Gathering feedback and making improvements

[1779] Users provide feedback on the information they receive. They input ratings and opinions on their device, such as "This information was helpful" or "This information is not appropriate." The device sends this feedback to the server, which analyzes the received feedback. Based on the results, the server improves the accuracy of future information provision by improving the user profile, sentiment data, and information delivery algorithm.

[1780] Specific example

[1781] Specific example 1: Usage case during sightseeing

[1782] If a user is visiting a major city, they might ask the AI ​​system, "What are some interesting places to see in this city?" The device converts this inquiry into text data, and an emotion engine recognizes the user's level of excitement. The server analyzes the text and emotion data sent from the device and, based on the user's interests and level of excitement, generates and provides information on historical places such as "famous parks" and "ancient shrines," as well as information on live concerts and major events. The device displays this information and also provides it as an audio guide.

[1783] Example 2: Usage on a bus during a commute

[1784] If a user who commutes on the same bus route every day is looking for a new restaurant, they can simply say "I'm looking for a new restaurant" to the AI ​​system. The emotion engine recognizes that the user is feeling "tired." The server then extracts information on new restaurants near the route, prioritizing places with a relaxing atmosphere and quiet seating, and provides this information to the device. The device displays this information and also provides voice guidance.

[1785] Example of a prompt:

[1786] voice_data = "Tell me some relaxing music you'd like to listen to right now."

[1787] emotion = get_user_emotion(voice_data)

[1788] latitude, longitude = get_geolocation()

[1789] recommendations = recommend_content(emotion, latitude, longitude)

[1790] print(recommendations)

[1791] The system of the present invention generates and provides optimal content in real time based on the user's location information, hobbies and preferences, and emotional information, and further improves the information provision algorithm based on feedback, thereby providing high-quality information to the user.

[1792] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1793] Step 1:

[1794] User Authentication and Initial Setup

[1795] The user installs the application and enters the required information (username, email address, password). The device sends this information to the server. The server stores the received information in a database and generates a unique user ID. The generated user ID is sent back to the device, which receives it and completes the initial setup.

[1796] Input: User's basic information (username, email address, password)

[1797] Output: Unique User ID

[1798] Step 2:

[1799] Location data collection and analysis

[1800] After a user logs in, the application obtains permission from the user to access location information. The device, having received permission, periodically retrieves its current geographical location and sends it to the server. The server analyzes the received location information to identify the user's current location and collects basic information related to that area.

[1801] Input: User's location information

[1802] Output: User's current location and related basic information

[1803] Step 3:

[1804] Gathering information on hobbies and preferences through conversation and recognizing emotions.

[1805] When a user speaks to the application, the device uses speech recognition to convert the speech into text data. The device then uses an emotion engine to analyze the emotions expressed in the speech and generate emotion information. This text data and emotion information are sent to a server, which analyzes it to add or update the user's profile with their preferences and emotion information.

[1806] Input: User voice input

[1807] Output: Analysis results of text data and sentiment information

[1808] Step 4:

[1809] Information generation and provision

[1810] The server uses an AI algorithm to generate optimal content based on analyzed location information, hobbies and preferences, and emotional information. The generated content is sent to the device, which then displays it to the user. It is also possible to provide information via voice guidance using the voice guidance function.

[1811] Input: Location information, hobbies and preferences, emotional information

[1812] Output: Generated content

[1813] Step 5:

[1814] Gathering feedback and making improvements

[1815] Users provide feedback on the information they receive. The device sends evaluations and opinions, such as "This information was helpful" or "This information is inappropriate," to the server. The server analyzes the received feedback and improves the user profile, sentiment data, and information delivery algorithms.

[1816] Input: User feedback

[1817] Output: Improved information delivery algorithm

[1818] By executing the above steps sequentially, it becomes possible to provide optimal content in real time based on the user's location information, hobbies and preferences, and emotional information.

[1819] 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.

[1820] 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.

[1821] 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.

[1822] 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.

[1823] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[1824] 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.

[1825] 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.

[1826] 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.

[1827] 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."

[1828] 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.

[1829] 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.

[1830] 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.

[1831] 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.

[1832] 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.

[1833] 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.

[1834] 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.

[1835] 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.

[1836] 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.

[1837] 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.

[1838] 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.

[1839] 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 as being incorporated by reference.

[1840] The following is further disclosed regarding the embodiments described above.

[1841] (Claim 1)

[1842] A means of collecting user location information,

[1843] A means of analyzing users' hobbies and preferences,

[1844] Means for generating and providing content based on location information and hobby / preference information,

[1845] A system that includes this.

[1846] (Claim 2)

[1847] The system according to claim 1, further comprising means for analyzing conversations with users and updating their hobby and preference information.

[1848] (Claim 3)

[1849] The system according to claim 1, further comprising means for collecting user feedback and improving the information provision algorithm.

[1850] "Example 1"

[1851] (Claim 1)

[1852] A means by which the user enters initial setup information, saves that information in a database, and generates a user ID,

[1853] A means of collecting user location information,

[1854] A means of analyzing users' hobbies and preferences,

[1855] Means for generating and providing content based on location information and hobby / preference information,

[1856] A system that includes this.

[1857] (Claim 2)

[1858] The system according to claim 1, further comprising means for converting conversations with a user from speech to text, and for analyzing the text data to update information on hobbies and preferences.

[1859] (Claim 3)

[1860] The system according to claim 1, further comprising means for collecting user feedback and analyzing the feedback to improve the information provision algorithm.

[1861] "Application Example 1"

[1862] (Claim 1)

[1863] A means of collecting user location information,

[1864] A means of analyzing users' hobbies and preferences,

[1865] Means for generating and providing content based on location information and hobby / preference information,

[1866] A means including an algorithm for providing real-time information on a target based on collected location information and hobby / preference information,

[1867] A means for generating prompt sentences and recommending appropriate content based on collected location information and hobby / preference information,

[1868] A system that includes this.

[1869] (Claim 2)

[1870] The system according to claim 1, further comprising means for analyzing conversations with users and updating their hobby and preference information.

[1871] (Claim 3)

[1872] The system according to claim 1, further comprising means for collecting user feedback and improving the information provision algorithm.

[1873] "Example 2 of combining an emotion engine"

[1874] (Claim 1)

[1875] A means of collecting user location information,

[1876] A means for analyzing user hobbies, preferences, and emotional information,

[1877] A means of generating and providing optimal content using a generation AI model based on location information, hobby / preference information, and emotional information,

[1878] A means of collecting user feedback and improving the information provision algorithm,

[1879] A system that includes this.

[1880] (Claim 2)

[1881] The system according to claim 1, further comprising means for analyzing user speech using speech recognition and natural language processing, and updating hobby preference information and emotional information.

[1882] (Claim 3)

[1883] The system according to claim 1, further comprising an emotion engine that recognizes the user's emotions by analyzing voice tone and facial expressions.

[1884] "Application example 2 when combining with an emotional engine"

[1885] (Claim 1)

[1886] A means of collecting user location information,

[1887] A means of analyzing users' hobbies and preferences,

[1888] A means of analyzing user emotional information,

[1889] Means for generating and providing content based on location information, hobby / preference information, and emotional information,

[1890] A device that provides the generated content to the user,

[1891] A system that includes this.

[1892] (Claim 2)

[1893] The system according to claim 1, further comprising means for analyzing conversations with users and updating hobby preference information and emotional information.

[1894] (Claim 3)

[1895] The system according to claim 1, further comprising means for collecting user feedback and improving the information provision algorithm. [Explanation of symbols]

[1896] 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 of collecting user location information, A means of analyzing users' hobbies and preferences, A means of generating and providing content based on location information and hobby / preference information, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing conversations with users and updating their hobby and preference information.

3. The system according to claim 1, further comprising means for collecting user feedback and improving the information provision algorithm.

Images