system

Abstract

We provide a system that can respond to diverse user needs and deliver personalized guidance. [Solution] A system comprising means for acquiring location information, means for collecting user interest and behavioral history data, means for generating personalized navigation guidance based on the user's location information, interests, and traffic data using a generating AI, and means for transmitting the generated navigation guidance to a user terminal via a communication network.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional navigation system, a user has to search for static information about a destination by himself / herself, and real-time individual optimization is insufficient. Also, it is difficult to provide personalized guidance based on a user's interests and behavior patterns, and there is a problem that an optimal moving experience for the user cannot be realized. Furthermore, since visual guidance using different languages and augmented reality is not integrated, there is also a problem that various user needs cannot be met.

Means for Solving the Problems

[0005] This invention provides a system that acquires user location information, interest, and behavioral history data, and generates personalized navigation guidance in real time using a generative AI. This system transmits the generated guidance information to the user's terminal via a communication network and can update it in real time according to user requests. Furthermore, by utilizing augmented reality technology, it visually presents information on the user's terminal, optimizing the user's travel experience from various perspectives. This makes it possible to provide users with personalized guidance according to different languages ​​and interests, thereby addressing diverse needs.

[0006] "Location information" refers to geographical data used to determine the user's current location.

[0007] "Interest and behavioral history data" refers to the history of information based on a user's past activities and interests.

[0008] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and automatically generate appropriate information and guidance.

[0009] "Navigation guidance" refers to route information and destination instructions provided to support the user's movement.

[0010] A "communication network" is the communication infrastructure used to send and receive data.

[0011] A "user terminal" refers to a device that a user can directly operate.

[0012] Augmented reality technology is a technique that overlays computer-generated visual information onto the real world. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]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 an 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 an emotion engine is combined.

Mode for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a storage with a reference numeral is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, a communication I / F (Interface) with a reference numeral is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] The system of the present invention implements specific algorithms and processes to improve the user's dynamic navigation experience. The system mainly consists of a server and a user's terminal, and provides navigation guidance using the user's real-time location information, activity history, and interest data.

[0035] When a user activates their device and enters a destination, the device sends its location information along with the user's interests and past activity history to the server. The server receives this data and uses generative AI to generate optimized navigation directions. In this process, the server also considers the latest traffic and event information to provide the user with the most efficient route.

[0036] The generated navigation guidance can be customized to the user's language settings and is also provided as an audio guide through the device. Furthermore, information on visualized landmarks and points of interest is displayed in real time on the device using augmented reality technology. This display is overlaid on the camera feed, allowing users to understand their travel route more intuitively.

[0037] For example, if a user is in a busy area, the system will suggest a walking route that avoids crowds, while also guiding them to interesting cafes and galleries along the way. This suggestion is derived from the user's previously registered cafe-hopping interests. The server also supports multiple languages, allowing it to provide appropriate guidance to tourists from overseas.

[0038] This system allows users to travel efficiently and comfortably by receiving appropriately personalized guidance without having to actively search for the information they need.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The device uses GPS to obtain the user's current location and sends the destination information along with the user's interests and behavioral history data to the server.

[0042] Step 2:

[0043] The server searches and extracts relevant tourist spots and event information from its database based on the received location information and user interest data.

[0044] Step 3:

[0045] The server surveys real-time traffic conditions and uses generative AI to calculate the most efficient and personalized route tailored to the user's preferences.

[0046] Step 4:

[0047] The server generates the calculated route and associated guidance information in multiple languages ​​and formats it in a format that takes into account the user's language setting.

[0048] Step 5:

[0049] The server sends the generated guidance information to the terminal.

[0050] Step 6:

[0051] The terminal displays the received guidance information as a map on its screen and initiates voice guidance as needed.

[0052] Step 7:

[0053] The device activates augmented reality functionality via its camera, displaying landmarks and tourist spots around the user as video.

[0054] Step 8:

[0055] As the user moves, the device periodically communicates with the server, continuously updating information and routes in real time.

[0056] (Example 1)

[0057] 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."

[0058] In modern transportation, users often find it difficult to efficiently and intuitively find the optimal route, requiring them to research multiple sources of information themselves. Furthermore, navigation instructions can be difficult for users who speak different languages ​​to understand.

[0059] 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.

[0060] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, and means for generating personalized navigation guidance, including an optimized route, using generative AI. This enables the user to receive efficient and comfortable navigation guidance.

[0061] "Location information" refers to data that indicates the user's current location or a specific point in time.

[0062] "Interest and behavioral history data" refers to information about a user's past behavior and preferences, which is used to personalize navigation guidance.

[0063] "Generative AI" is a technology that uses artificial intelligence to generate navigation guidance tailored to the user.

[0064] "Navigation guidance" refers to the process of providing instructions and route information to help users efficiently reach a specific destination.

[0065] A "communication network" is a network or platform for information exchange used to send and receive data.

[0066] A "user terminal" refers to a digital device that a user can use to receive and operate information.

[0067] Augmented reality technology is a technique that overlays digital information onto images of the real world, providing visual assistance.

[0068] "Multilingual support" refers to the ability to provide information in the appropriate language to users who speak different languages.

[0069] This invention is a navigation system designed to improve the efficiency of user movement. The system primarily consists of a server and a user terminal, and provides personalized navigation guidance using a generative AI model. Details and specific examples are provided below.

[0070] The server is located on a cloud platform and receives the user's location information, interests, and behavioral history, allowing a generative AI model to calculate the optimal route. In this calculation, the server uses a learning algorithm to suggest points of interest based on the user's preferences. Furthermore, the server acquires traffic data in real time to optimize the generated route. Navigation guidance is transmitted to the user's terminal via the communication network.

[0071] The user's device will be a smartphone or tablet. The device is equipped with a GPS sensor to acquire location information and implements augmented reality technology. This allows the user to visually confirm the location information of objects and landmarks.

[0072] As a concrete example, consider a case where a user specifies, "I want to go to Tokyo Station." Based on the user's past activity history and hobbies, the server proposes the optimal route, including points of interest such as cafes and galleries. By using AR functionality on the device to provide visual guidance, the user can intuitively understand the route.

[0073] An example of a prompt message would be entered as follows:

[0074] "Please suggest the best route from my current location to Tokyo Station. My areas of interest are cafes and art galleries."

[0075] Thus, the present invention provides personalized navigation guidance to each user in real time, enabling efficient travel.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The user enters a destination and activates the device. The device obtains the user's current location using a GPS sensor. Based on the input, the device aggregates the acquired location information, the user's past activity history, and interest data, and sends this information to the server. Specifically, the user opens a smartphone application and enters "Tokyo Station" as the destination.

[0079] Step 2:

[0080] The server receives user location information, interests, and behavioral history data sent from the terminal. The server then activates a generative AI model and performs data calculations to generate the optimal route based on this data. Specifically, it analyzes past data and creates a personalized route that takes into account the user's preferred stops and events. The server analyzes the data received as input and outputs optimized navigation guidance as a result.

[0081] Step 3:

[0082] The server acquires the latest traffic data and event information in real time and optimizes the generated route by adding this information. Specifically, it retrieves congestion information and event status from a database and uses it to determine the most efficient route for the user. It takes real-time external data as input and generates adjusted navigation guidance as output.

[0083] Step 4:

[0084] The server transmits the generated, optimized navigation directions to the user's device via the communication network. The device receives these directions and displays them visually using voice guidance and AR technology. Specifically, arrows and landmark information are overlaid on the device screen, allowing the user to follow them to Tokyo Station. The system receives navigation information from the server as input and provides visual and voice guidance to the user as output.

[0085] (Application Example 1)

[0086] 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."

[0087] Traditional navigation systems have struggled to provide personalized guidance based on user interests and behavioral history. Furthermore, they lacked the ability to effectively implement foreign language audio guides and augmented reality-based visual guidance, leaving room for improvement in user convenience. Additionally, data analysis for real-time route selection based on user interests was insufficient.

[0088] 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.

[0089] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, means for generating personalized travel route guidance based on the user's location information, interests, and traffic data using generative AI, means for transmitting the generated travel route guidance to the user terminal via a communication network, means for visually displaying information on landmarks and points of interest using augmented reality technology, and means for providing audio guidance in multiple languages. This enables route selection according to the user's interests and provides more intuitive and multilingual guidance.

[0090] "Location information" refers to data that indicates the user's current geographical location.

[0091] "Interests" refers to information about the preferences and interests that a user has shown in the past.

[0092] "Behavioral history data" refers to data that records a user's past actions and movements.

[0093] "Generative AI" is an artificial intelligence technology that uses machine learning to analyze data and generate information or guidance for a specific purpose.

[0094] "Route guidance" refers to instructions that show the user the optimal route to reach their destination.

[0095] A "communication network" is a digital or analog communication system used to send and receive information.

[0096] "User terminal" refers to any computer or mobile device used by a user.

[0097] Augmented reality technology is a technique that overlays computer-generated information onto images of the real world.

[0098] A "landmark" refers to a geographically or culturally significant location or building that serves as a landmark.

[0099] A "point of interest" is a location that attracts the user's attention or contains important information along their route.

[0100] "Audio guide" refers to a function that provides guidance information to users through audio.

[0101] "Multilingual support" means having the ability to provide information using multiple languages.

[0102] "Data analysis methods" refer to techniques and technologies used to extract and analyze useful information based on collected data.

[0103] This invention is a system that improves the user's dynamic navigation experience. The following hardware and software are required to implement the invention:

[0104] First, the server obtains real-time geographical information via a GPS module to acquire the user's location. In addition to this location information, the user's past behavioral history and interest data are sent to the server. A generative AI model then analyzes this data to generate personalized travel route guidance for the user. Various machine learning models and data science tools, both domestic and international, can be used as generative AI models.

[0105] The user's terminal receives route guidance generated via the communication network. The terminal displays visual information using augmented reality technology through its display. As a result, landmarks and points of interest are overlaid on the camera image, allowing the user to receive guidance more intuitively.

[0106] Furthermore, the terminals utilize speech synthesis software to provide audio guides in multiple languages. This allows for effective information delivery to users who speak different languages. In addition, data analysis tools optimize route selection in real time based on user interests.

[0107] For example, if a user visiting a busy tourist area sets a certain landmark as their destination, the generating AI model can suggest the optimal route to avoid congestion while also guiding them to shops and cafes along the way that might interest them. An example of a prompt used in this case would be: "The user is currently in a busy area. In their past visit history, they have frequently visited art galleries. Based on their current location and past behavior history, please suggest the optimal route that includes some interesting galleries along the way."

[0108] The above describes the specific forms for carrying out the invention.

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] The server acquires the user's location information. The input is real-time geographical information obtained from a GPS module. The output is prepared to provide the current location coordinate data to a generating AI model. The acquired location information is analyzed in combination with the user's interests and behavioral history.

[0112] Step 2:

[0113] The server collects user interest and behavioral history data. Inputs include past visit history and registered preference information. Outputs include a dataset of interest patterns and behavioral tendencies. This dataset forms the basis for analysis by generative AI models.

[0114] Step 3:

[0115] The server uses a generative AI model to generate personalized travel route guidance based on location, interests, and traffic data. Input includes data obtained in steps 1 and 2, as well as up-to-date traffic information. Output generates optimized travel routes and guidance information. The generative AI model proposes routes based on prompts, ensuring efficient travel.

[0116] Step 4:

[0117] The server transmits the generated route guidance to the user terminal via the communication network. The input is the route guidance generated in step 3. As output, data is transmitted to the terminal via the network. The terminal receives this and prepares to provide visual and auditory guidance.

[0118] Step 5:

[0119] The device uses augmented reality technology to visually display information about landmarks and points of interest. The input is route guidance received from a server. The output provides the user with an augmented reality view that overlays information onto camera footage. The user can navigate intuitively using this information.

[0120] Step 6:

[0121] The terminal uses speech synthesis software to play audio guides in multiple languages. Inputs are route guidance and language settings from the server. Output provides voice guidance to the destination. This allows the system to accommodate users who speak different languages.

[0122] 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.

[0123] The present invention's system recognizes the user's emotional state by combining navigation guidance based on the user's location information, interests, and behavioral history with an emotion engine, and dynamically adapts the guidance accordingly. This system consists mainly of a server, a user terminal, and an emotion engine, which cooperate via a communication network.

[0124] When a user starts navigation using their device, the device sends location information and interest data to a server. Based on this information, the server uses generative AI to calculate a personalized route and simultaneously sends data to an emotion engine to detect the user's emotional state. This emotion engine analyzes emotions from the user's voice tone, facial expression data, and operation patterns.

[0125] Upon receiving output from the emotion engine, the server adjusts navigation guidance according to the user's current emotional state. For example, if the system determines that the user is stressed, it suggests relaxing routes and rest stops. Conversely, if the system recognizes the user as curious, it can introduce new experiences and tourist attractions. This guidance is provided to the user's device as audio or visual information using augmented reality technology.

[0126] As a concrete example, if a user is visiting a tourist destination during peak season and the emotion engine detects the user's anxiety, the server will suggest a route that avoids crowds and a quiet cafe to rest in. This suggestion is quickly updated on the user's device, providing a more comfortable experience. In this way, by incorporating an emotion engine, it becomes possible to achieve interactive navigation that goes beyond mere information provision and is attentive to the user's emotions.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The device obtains the user's current location and sends that information to the server along with the destination setting. Furthermore, it also sends data on the user's interests and behavioral history.

[0130] Step 2:

[0131] The emotion engine analyzes the user's voice input and facial expression data in real time to estimate the user's emotional state. This emotional data is periodically sent to the server.

[0132] Step 3:

[0133] The server inputs relevant navigation information into a generating AI and analyzes it based on the received location information, interest data, and sentiment data.

[0134] Step 4:

[0135] Based on information analyzed by the generating AI, the server creates personalized navigation guidance that takes into account the user's emotional state. For example, if stress is detected, it will select a relaxing route.

[0136] Step 5:

[0137] The server formats emotion-sensitive navigation instructions along with multilingual options and sends them to the terminal.

[0138] Step 6:

[0139] The device provides the user with received directions and supports their movement using voice and visual guidance. Furthermore, it utilizes augmented reality technology to display surrounding landmarks.

[0140] Step 7:

[0141] The user interacts with the device while on the move, and whenever the device detects a change in emotional data, it sends new input to the server. The server updates the guidance as needed and sends it back to the device.

[0142] (Example 2)

[0143] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0144] Conventional navigation systems have the problem of not taking into account the user's emotional state when providing guidance, making it difficult to provide optimal information tailored to each user's situation. Furthermore, because navigation is not updated in real time in response to dynamic situations, it is difficult to improve user satisfaction.

[0145] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0146] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, means for generating personalized navigation guidance using generative AI, means for estimating emotions from the user's voice tone, facial expression information, and operation patterns, means for dynamically adapting navigation guidance based on the output from the emotion estimation means, and means for transmitting the adapted navigation guidance to the user device via a communication network. This makes it possible to provide optimal navigation in real time according to the user's emotions.

[0147] "Means of acquiring location information" refers to devices and technologies that collect data to determine the user's current location.

[0148] "Means for collecting user interest and behavioral history data" refers to methods or systems for recording a user's past activities and preferences and organizing information based on them.

[0149] "Means for generating personalized navigation guidance using generative AI" refers to a process or engine that utilizes artificial intelligence technology to create the most suitable routes and guidance for individual users.

[0150] "An emotion estimation method that analyzes emotions from a user's voice tone, facial expression information, and operation patterns" refers to a technology or system that analyzes the tone of voice, facial expressions, and device operation behavior, and uses them to infer the user's emotional state.

[0151] "Means for dynamically adapting navigation guidance based on the output from the emotion estimation means" refers to a mechanism for adjusting existing guidance routes and content in real time in a way that reflects the user's emotional state.

[0152] "Means for transmitting the adapted navigation guidance to a user device via a communication network" means a method or technique for transferring improved guidance information to a user's device via a network.

[0153] This system utilizes user location information, interests, and behavioral history data to provide personalized navigation guidance. The server, user terminal, and emotion engine work together in a coordinated manner.

[0154] When a user starts navigation using their device, the device uses its GPS function to obtain its current location. Furthermore, the device collects user interest and behavioral data from application usage and browsing history, and sends this data to a server. Encrypted communication protocols are used throughout this process to ensure data security.

[0155] The server uses a generative AI model based on the received data to generate personalized navigation guidance for the user. This AI model utilizes common cloud services for computation. Specific software includes machine learning frameworks and data analysis tools. Simultaneously, the server sends the user's voice, facial expression data, and action patterns to an emotion engine to analyze the user's emotional state. The emotion engine identifies the user's emotions from their voice tone and facial expressions.

[0156] The server dynamically adapts navigation guidance based on emotional state information from the emotion engine. For example, if the analysis indicates that the user is stressed, it suggests a relaxing route. On the other hand, if the server determines that the user is curious, it adjusts the guidance to show new tourist spots. This guidance is provided to the user's device as audio or visual information using AR technology.

[0157] As a concrete example, consider a situation where a user is traveling in a city and has selected a museum as their destination. In this case, an example of a prompt message might be, "The user's location is in the city center, their interest is history, and their emotion is curiosity. Based on this, suggest an appropriate sightseeing route and related spots." In this way, the system can provide a more interactive and enriching navigation experience that is attentive to the user's emotional state.

[0158] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0159] Step 1:

[0160] The user initiates navigation using the device. The device obtains its current location using GPS and simultaneously collects data on the user's interests and behavioral history. Specifically, the device reads application usage and visit history and reconciles this data. This prepares the location information and user interests as input data, ready to be sent to the server.

[0161] Step 2:

[0162] The device sends collected location information, interest data, and behavioral history data to the server. The server receives this data and generates personalized navigation guidance using a generative AI model. The location information and interest data received as input data are analyzed by the AI ​​algorithm to extract information about the optimal route and points of interest. As output, user-specific navigation guidance is created.

[0163] Step 3:

[0164] The server sends the user's voice tone, facial expression information, and operation patterns to the emotion engine. This provides the emotion engine with voice and visual information as input data, and sentiment analysis is performed. Specifically, the emotion engine uses a machine learning model to analyze the characteristics of the voice and facial expressions to identify the user's emotional state. The output is the emotional state information obtained by the emotion engine.

[0165] Step 4:

[0166] The server dynamically adapts the generated navigation guidance based on emotional state information from the emotion engine. This process includes suggesting relaxation routes when stress is detected and new spots that reflect curiosity. It receives emotion analysis results as input and edits the guidance content based on them. The output is the adjusted navigation guidance, which includes information that corresponds to the user's specific situation and emotions.

[0167] Step 5:

[0168] The adapted navigation guidance is transmitted from the server to the user's device via a communication network. The device then presents the received guidance through voice and AR technology. Specific actions include generating real-time voice guidance using a speech synthesis engine and displaying visual information on the device's display using augmented reality. The output is an interactive navigation experience provided to the user.

[0169] (Application Example 2)

[0170] 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 device 14 will be referred to as the "terminal."

[0171] In modern society, information overload and busy lifestyles often cause stress for many travelers during their journeys. Furthermore, congestion and unexpected problems at popular tourist destinations and events can disrupt plans, diminishing the traveler's experience. Autonomous vehicles, in particular, require flexible responses tailored to the user's psychological state, but current systems fail to adequately address this. To solve this problem, it is necessary to accurately understand the user's emotional state and optimize the travel experience in an individualized manner.

[0172] 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.

[0173] In this invention, the server includes a device for acquiring location information, a device for collecting user interest and activity history data, a device for generating personalized route guidance based on the user's location information, interests, and movement data using a generative AI, a device for recognizing the user's psychological state using an emotion analysis engine and adjusting the route guidance accordingly, and a device for transmitting the adjusted route guidance to the user terminal via a communication network. This enables real-time navigation adjustment in accordance with the user's emotional state and optimization of the in-vehicle environment.

[0174] A "location information acquisition device" is a device that collects and provides data to determine the user's current location.

[0175] A "data collection device for interest and activity history" is a device used to acquire a history of interests and activities that a user has previously shown.

[0176] "Generative AI" refers to artificial intelligence technology that solves complex problems based on the analysis of large amounts of data, and is used to provide personalized services.

[0177] A "personalized route guidance generation device" is a device that generates optimal route guidance according to the user's specific circumstances and preferences.

[0178] An "emotion analysis engine" is a program or device that evaluates a user's emotional state based on their voice, facial expressions, and operation patterns.

[0179] A "transmitting device via a communication network" is a device that includes network communication technology for transmitting generated information to a user's terminal.

[0180] "Navigation adjustment" refers to the act of dynamically changing routes and guidance content based on the user's emotional state.

[0181] "In-vehicle environment" refers to elements such as lighting, temperature, and sound inside an autonomous vehicle, which are adjusted to improve passenger comfort.

[0182] The system for carrying out the present invention consists of a server, a user terminal, an emotion analysis engine, and a communication network. The server receives data from the user using a location information acquisition device and an interest and activity history data collection device. Based on this data, it uses a generative AI to create route guidance optimized for the user. At this time, the emotion analysis engine analyzes the user's voice tone, facial expressions, and operation patterns, and sends the results to the server. The server adjusts the navigation based on this and transmits the information to the user terminal via the communication network.

[0183] The user terminal provides visual guidance by displaying map information and related information using augmented reality technology. This aims to create a comfortable experience inside autonomous vehicles, for example, by changing lighting and sound settings to create an environment suited to the user's psychological state.

[0184] As a concrete example, if a user experiences stress during the morning rush hour commute, the server receives data from the emotion analysis engine, plays relaxing music in the train, and suggests a route that avoids congestion. This reduces the user's stress and allows for a more comfortable journey. An example of a prompt for the generative AI model would be, "Based on the user's emotion data, suggest a way to switch to relaxation mode."

[0185] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0186] Step 1:

[0187] The user terminal acquires location information and interest / activity history data and sends it to the server. Input includes location data from a GPS sensor and past browsing history data. This data is collected and sent to the server as initial information to understand the user's current context. Output is a data packet indicating the user's current state.

[0188] Step 2:

[0189] The server uses a generating AI based on received location information and interest / activity history data to generate personalized route guidance. The input is data packets sent by the user. The generating AI model analyzes this data and generates the optimal route and various guidance information. The output is route guidance information tailored to the user.

[0190] Step 3:

[0191] The emotion analysis engine acquires the user's voice tone and facial expression data and analyzes their emotional state. In this step, the terminal collects voice and video data from the user and sends it to the emotion analysis engine. The input is real-time voice and video data. The emotion analysis engine determines the emotional state and sends the analysis results to the server as output.

[0192] Step 4:

[0193] The server receives the results from the emotion analysis engine and adjusts the route guidance according to the user's emotional state. In this step, the server integrates the analysis results into the route guidance information and makes appropriate adjustments. The inputs are the route guidance information and emotional state data. The adjusted route guidance is the output.

[0194] Step 5:

[0195] The server transmits the adjusted route guidance to the user terminal via the communication network. Here, the input is the adjusted route guidance information, as the server transfers the adjusted guidance information to the terminal. The output is the guidance information data received by the user terminal, which assists user interaction.

[0196] Step 6:

[0197] The user terminal visually displays the received route guidance using augmented reality technology and provides it to the user. Here, the input is guidance information data transmitted from the server. Based on this data, the terminal visualizes map information and other data using AR technology and presents it as output on the user's display.

[0198] 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.

[0199] 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.

[0200] 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.

[0201] [Second Embodiment]

[0202] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0203] 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.

[0204] 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).

[0205] 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.

[0206] 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.

[0207] 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).

[0208] 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.

[0209] 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.

[0210] 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.

[0211] 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.

[0212] 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.

[0213] 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".

[0214] The system of the present invention implements specific algorithms and processes to improve the user's dynamic navigation experience. The system mainly consists of a server and a user's terminal, and provides navigation guidance using the user's real-time location information, activity history, and interest data.

[0215] When a user activates their device and enters a destination, the device sends its location information along with the user's interests and past activity history to the server. The server receives this data and uses generative AI to generate optimized navigation directions. In this process, the server also considers the latest traffic and event information to provide the user with the most efficient route.

[0216] The generated navigation guidance can be customized to the user's language settings and is also provided as an audio guide through the device. Furthermore, information on visualized landmarks and points of interest is displayed in real time on the device using augmented reality technology. This display is overlaid on the camera feed, allowing users to understand their travel route more intuitively.

[0217] For example, if a user is in a busy area, the system will suggest a walking route that avoids crowds, while also guiding them to interesting cafes and galleries along the way. This suggestion is derived from the user's previously registered cafe-hopping interests. The server also supports multiple languages, allowing it to provide appropriate guidance to tourists from overseas.

[0218] This system allows users to travel efficiently and comfortably by receiving appropriately personalized guidance without having to actively search for the information they need.

[0219] The following describes the processing flow.

[0220] Step 1:

[0221] The device uses GPS to obtain the user's current location and sends the destination information along with the user's interests and behavioral history data to the server.

[0222] Step 2:

[0223] The server searches and extracts relevant tourist spots and event information from its database based on the received location information and user interest data.

[0224] Step 3:

[0225] The server surveys real-time traffic conditions and uses generative AI to calculate the most efficient and personalized route tailored to the user's preferences.

[0226] Step 4:

[0227] The server generates the calculated route and associated guidance information in multiple languages ​​and formats it in a format that takes into account the user's language setting.

[0228] Step 5:

[0229] The server sends the generated guidance information to the terminal.

[0230] Step 6:

[0231] The terminal displays the received guidance information as a map on its screen and initiates voice guidance as needed.

[0232] Step 7:

[0233] The device activates augmented reality functionality via its camera, displaying landmarks and tourist attractions around the user as video.

[0234] Step 8:

[0235] As the user moves, the device periodically communicates with the server, continuously updating information and routes in real time.

[0236] (Example 1)

[0237] 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".

[0238] In modern transportation, users often find it difficult to efficiently and intuitively find the optimal route, requiring them to research multiple sources of information themselves. Furthermore, navigation instructions are often difficult for users who speak different languages ​​to understand.

[0239] 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.

[0240] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, and means for generating personalized navigation guidance, including an optimized route, using generative AI. This enables the user to receive efficient and comfortable navigation guidance.

[0241] "Location information" refers to data that indicates the user's current location or a specific point in time.

[0242] "Interest and behavioral history data" refers to information about a user's past behavior and preferences, which is used to personalize navigation guidance.

[0243] "Generative AI" is a technology that uses artificial intelligence to generate navigation guidance tailored to the user.

[0244] "Navigation guidance" refers to the process of providing instructions and route information to help users efficiently reach a specific destination.

[0245] A "communication network" is a network or platform for information exchange used to send and receive data.

[0246] A "user terminal" refers to a digital device that a user can use to receive and operate information.

[0247] Augmented reality technology is a technique that overlays digital information onto images of the real world, providing visual assistance.

[0248] "Multilingual support" refers to the ability to provide information in the appropriate language to users who speak different languages.

[0249] This invention is a navigation system designed to improve the efficiency of user movement. The system primarily consists of a server and a user terminal, and provides personalized navigation guidance using a generative AI model. Details and specific examples are provided below.

[0250] The server is located on a cloud platform and receives the user's location information, interests, and behavioral history, allowing a generative AI model to calculate the optimal route. In this calculation, the server uses a learning algorithm to suggest points of interest based on the user's preferences. Furthermore, the server acquires traffic data in real time to optimize the generated route. Navigation guidance is transmitted to the user's terminal via the communication network.

[0251] The user's device will be a smartphone or tablet. The device is equipped with a GPS sensor to acquire location information and implements augmented reality technology. This allows the user to visually confirm the location information of objects and landmarks.

[0252] As a concrete example, consider a case where a user specifies, "I want to go to Tokyo Station." Based on the user's past activity history and hobbies, the server proposes the optimal route, including points of interest such as cafes and galleries. By using AR functionality on the device to provide visual guidance, the user can intuitively understand the route.

[0253] An example of a prompt statement would be entered as follows:

[0254] "Please suggest the best route from my current location to Tokyo Station. My areas of interest are cafes and art galleries."

[0255] Thus, the present invention provides personalized navigation guidance to each user in real time, enabling efficient travel.

[0256] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0257] Step 1:

[0258] The user enters a destination and activates the device. The device obtains the user's current location using a GPS sensor. Based on the input, the device aggregates the acquired location information, the user's past activity history, and interest data, and sends this information to the server. Specifically, the user opens a smartphone application and enters "Tokyo Station" as the destination.

[0259] Step 2:

[0260] The server receives user location information, interests, and behavioral history data sent from the terminal. The server then activates a generative AI model and performs data calculations to generate the optimal route based on this data. Specifically, it analyzes past data and creates a personalized route that takes into account the user's preferred stops and events. The server analyzes the data received as input and outputs optimized navigation guidance as a result.

[0261] Step 3:

[0262] The server acquires the latest traffic data and event information in real time and optimizes the generated route by adding this information. Specifically, it retrieves congestion information and event status from a database and uses it to determine the most efficient route for the user. It takes real-time external data as input and generates adjusted navigation guidance as output.

[0263] Step 4:

[0264] The server transmits the generated, optimized navigation directions to the user's device via the communication network. The device receives these directions and displays them visually using voice guidance and AR technology. Specifically, arrows and landmark information are overlaid on the device screen, allowing the user to follow them to Tokyo Station. The system receives navigation information from the server as input and provides visual and voice guidance to the user as output.

[0265] (Application Example 1)

[0266] 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."

[0267] Traditional navigation systems have struggled to provide personalized guidance based on user interests and behavioral history. Furthermore, they lacked the ability to effectively implement foreign language audio guides and augmented reality-based visual guidance, leaving room for improvement in user convenience. Additionally, data analysis for real-time route selection based on user interests was insufficient.

[0268] 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.

[0269] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, means for generating personalized travel route guidance based on the user's location information, interests, and traffic data using generative AI, means for transmitting the generated travel route guidance to the user terminal via a communication network, means for visually displaying information on landmarks and points of interest using augmented reality technology, and means for providing audio guidance in multiple languages. This enables route selection according to the user's interests and provides more intuitive and multilingual guidance.

[0270] "Location information" refers to data that indicates the user's current geographical location.

[0271] "Interests" refers to information about the preferences and interests that a user has shown in the past.

[0272] "Behavioral history data" refers to data that records a user's past actions and movements.

[0273] "Generative AI" is an artificial intelligence technology that uses machine learning to analyze data and generate information or guidance for a specific purpose.

[0274] "Route guidance" refers to instructions that show the user the optimal route to reach their destination.

[0275] A "communication network" is a digital or analog communication system used to send and receive information.

[0276] "User terminal" refers to any computer or mobile device used by a user.

[0277] Augmented reality technology is a technique that overlays computer-generated information onto images of the real world.

[0278] A "landmark" refers to a geographically or culturally significant location or building that serves as a landmark.

[0279] A "point of interest" is a location that attracts the user's attention or contains important information along their route.

[0280] "Audio guide" refers to a function that provides guidance information to users through audio.

[0281] "Multilingual support" means having the ability to provide information using multiple languages.

[0282] The "data analysis means" refers to the methods and techniques used to extract and analyze useful information based on the collected data.

[0283] This invention is a system that improves the user's dynamic navigation experience. To implement the invention, the following hardware and software are required.

[0284] First, the server acquires real-time geographical information through a GPS module in order to obtain the user's location information. In addition to this location information, the user's past behavior history and interest data are sent to the server. Thereby, the generated AI model analyzes these data and generates a personalized travel route guidance for the user. As the generated AI model, for example, various machine learning models and data science tools at home and abroad can be used.

[0285] The generated travel route guidance is sent to the user terminal via a communication network. The terminal displays visual information using augmented reality technology through a display. As a result, landmarks and points of interest are superimposed on the camera image and displayed, so that the user can receive guidance more intuitively.

[0286] Also, on the terminal, voice guidance corresponding to multiple languages is provided using voice synthesis software. Thereby, information can be effectively conveyed to users who speak different languages. In addition, the route selection according to the user's interests is optimized in real time by the data analysis means.

[0287] For example, if a user visiting a busy tourist area sets a certain landmark as their destination, the generating AI model can suggest the optimal route to avoid congestion while also guiding them to shops and cafes along the way that might interest them. An example of a prompt used in this case would be: "The user is currently in a busy area. In their past visit history, they have frequently visited art galleries. Based on their current location and past behavior history, please suggest the optimal route that includes some interesting galleries along the way."

[0288] The above describes the specific forms for carrying out the invention.

[0289] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0290] Step 1:

[0291] The server acquires the user's location information. The input is real-time geographical information obtained from a GPS module. The output is prepared to provide the current location coordinate data to a generating AI model. The acquired location information is analyzed in combination with the user's interests and behavioral history.

[0292] Step 2:

[0293] The server collects user interest and behavioral history data. Inputs include past visit history and registered preference information. Outputs include a dataset of interest patterns and behavioral tendencies. This dataset forms the basis for analysis by a generative AI model.

[0294] Step 3:

[0295] The server uses a generative AI model to generate personalized travel route guidance based on location, interests, and traffic data. Input includes data obtained in steps 1 and 2, as well as up-to-date traffic information. Output generates optimized travel routes and guidance information. The generative AI model proposes routes based on prompts, ensuring efficient travel.

[0296] Step 4:

[0297] The server transmits the generated route guidance to the user terminal via the communication network. The input is the route guidance generated in step 3. As output, data is transmitted to the terminal via the network. The terminal receives this and prepares to provide visual and auditory guidance.

[0298] Step 5:

[0299] The device uses augmented reality technology to visually display information about landmarks and points of interest. The input is route guidance received from a server. The output provides the user with an augmented reality view that overlays information onto camera footage. The user can navigate intuitively using this information.

[0300] Step 6:

[0301] The terminal uses speech synthesis software to play audio guides in multiple languages. Inputs are route guidance and language settings from the server. Output provides voice guidance to the destination. This allows the system to accommodate users who speak different languages.

[0302] 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.

[0303] In addition to navigation guidance based on the user's location information, interests, and behavior history, the system of the present invention combines an emotion engine to recognize the user's emotional state and dynamically adapt the guidance. This system mainly consists of a server, a user terminal, and an emotion engine, and they cooperate via a communication network.

[0304] When the user starts navigation using the terminal, the terminal transmits location information and interest data to the server. Based on this information, the server calculates a personalized route using generative AI and simultaneously sends data for detecting the user's emotional state to the emotion engine. This emotion engine analyzes emotions from the user's voice tone, facial expression data, operation patterns, etc.

[0305] Upon receiving the output of the emotion engine, the server adjusts the navigation guidance according to the user's current emotional state. For example, if it is determined that the user is feeling stressed, the system proposes a relaxing route or a rest spot. Conversely, if the user is recognized as being curious, new experiences or tourist spots can be introduced. Such guidance is provided to the user's terminal as voice or visual information using augmented reality technology.

[0306] As a specific example, when the user is visiting a tourist destination during a peak season and the emotion engine detects the user's anxiety, the server proposes a route to avoid congestion and a quiet coffee break spot. This proposal is quickly updated on the user's terminal, providing a more comfortable experience. Thus, by incorporating an emotion engine, it is possible to achieve not only simple information provision but also interactive navigation that takes into account the user's emotions.

[0307] The processing flow will be described below.

[0308] Step 1:

[0309] The device obtains the user's current location and sends that information to the server along with the destination setting. Furthermore, it also sends data on the user's interests and behavioral history.

[0310] Step 2:

[0311] The emotion engine analyzes the user's voice input and facial expression data in real time to estimate the user's emotional state. This emotional data is periodically sent to the server.

[0312] Step 3:

[0313] The server inputs relevant navigation information into a generating AI and analyzes it based on the received location information, interest data, and sentiment data.

[0314] Step 4:

[0315] Based on information analyzed by the generating AI, the server creates personalized navigation guidance that takes into account the user's emotional state. For example, if stress is detected, it will select a relaxing route.

[0316] Step 5:

[0317] The server formats emotion-sensitive navigation instructions along with multilingual options and sends them to the terminal.

[0318] Step 6:

[0319] The device provides the user with received directions and supports their movement using voice and visual guidance. Furthermore, it utilizes augmented reality technology to display surrounding landmarks.

[0320] Step 7:

[0321] The user interacts with the device while on the move, and whenever the device detects a change in emotional data, it sends new input to the server. The server updates the guidance as needed and sends it back to the device.

[0322] (Example 2)

[0323] 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".

[0324] Conventional navigation systems have the problem of not taking into account the user's emotional state when providing guidance, making it difficult to provide optimal information tailored to each user's situation. Furthermore, because navigation is not updated in real time in response to dynamic situations, it is difficult to improve user satisfaction.

[0325] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0326] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, means for generating personalized navigation guidance using generative AI, means for estimating emotions from the user's voice tone, facial expression information, and operation patterns, means for dynamically adapting navigation guidance based on the output from the emotion estimation means, and means for transmitting the adapted navigation guidance to the user device via a communication network. This makes it possible to provide optimal navigation in real time according to the user's emotions.

[0327] "Means of acquiring location information" refers to devices and technologies that collect data to determine the user's current location.

[0328] "Means for collecting user interest and behavioral history data" refers to methods or systems for recording a user's past activities and preferences and organizing information based on them.

[0329] "Means for generating personalized navigation guidance using generative AI" refers to a process or engine that utilizes artificial intelligence technology to create the most suitable routes and guidance for individual users.

[0330] "An emotion estimation method that analyzes emotions from a user's voice tone, facial expression information, and operation patterns" refers to a technology or system that analyzes the tone of voice, facial expressions, and device operation behavior, and uses them to infer the user's emotional state.

[0331] "Means for dynamically adapting navigation guidance based on the output from the emotion estimation means" refers to a mechanism for adjusting existing guidance routes and content in real time in a way that reflects the user's emotional state.

[0332] "Means for transmitting the adapted navigation guidance to a user device via a communication network" means a method or technique for transferring improved guidance information to a user's device via a network.

[0333] This system utilizes user location information, interests, and behavioral history data to provide personalized navigation guidance. The server, user terminal, and emotion engine work together in a coordinated manner.

[0334] When a user starts navigation using their device, the device uses its GPS function to obtain its current location. Furthermore, the device collects user interest and behavioral data from application usage and browsing history, and sends this data to a server. Encrypted communication protocols are used throughout this process to ensure data security.

[0335] The server uses a generative AI model based on the received data to generate personalized navigation guidance for the user. This AI model utilizes common cloud services for computation. Specific software includes machine learning frameworks and data analysis tools. Simultaneously, the server sends the user's voice, facial expression data, and action patterns to an emotion engine to analyze the user's emotional state. The emotion engine identifies the user's emotions from their voice tone and facial expressions.

[0336] The server dynamically adapts navigation guidance based on emotional state information from the emotion engine. For example, if the analysis indicates that the user is stressed, it suggests a relaxing route. On the other hand, if the server determines that the user is curious, it adjusts the guidance to show new tourist spots. This guidance is provided to the user's device as audio or visual information using AR technology.

[0337] As a concrete example, consider a situation where a user is traveling in a city and has selected a museum as their destination. In this case, an example of a prompt message might be, "The user's location is in the city center, their interest is history, and their emotion is curiosity. Based on this, suggest an appropriate sightseeing route and related spots." In this way, the system can provide a more interactive and enriching navigation experience that is attentive to the user's emotional state.

[0338] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0339] Step 1:

[0340] The user initiates navigation using the device. The device obtains its current location using GPS and simultaneously collects data on the user's interests and behavioral history. Specifically, the device reads application usage and visit history and reconciles this data. This prepares the location information and user interests as input data, ready to be sent to the server.

[0341] Step 2:

[0342] The device sends collected location information, interest data, and behavioral history data to the server. The server receives this data and generates personalized navigation guidance using a generative AI model. The location information and interest data received as input data are analyzed by the AI ​​algorithm to extract information about the optimal route and points of interest. As output, user-specific navigation guidance is created.

[0343] Step 3:

[0344] The server sends the user's voice tone, facial expression information, and operation patterns to the emotion engine. This provides the emotion engine with voice and visual information as input data, and sentiment analysis is performed. Specifically, the emotion engine uses a machine learning model to analyze the characteristics of the voice and facial expressions to identify the user's emotional state. The output is the emotional state information obtained by the emotion engine.

[0345] Step 4:

[0346] The server dynamically adapts the generated navigation guidance based on emotional state information from the emotion engine. This process includes suggesting relaxation routes when stress is detected and new spots that reflect curiosity. It receives emotion analysis results as input and edits the guidance content based on them. The output is the adjusted navigation guidance, which includes information that corresponds to the user's specific situation and emotions.

[0347] Step 5:

[0348] The adapted navigation guidance is transmitted from the server to the user's device via a communication network. The device then presents the received guidance through voice and AR technology. Specific actions include generating real-time voice guidance using a speech synthesis engine and displaying visual information on the device's display using augmented reality. The output is an interactive navigation experience provided to the user.

[0349] (Application Example 2)

[0350] 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."

[0351] In modern society, information overload and busy lifestyles often cause stress for many travelers during their journeys. Furthermore, congestion and unexpected problems at popular tourist destinations and events can disrupt plans, diminishing the traveler's experience. Autonomous vehicles, in particular, require flexible responses tailored to the user's psychological state, but current systems fail to adequately address this. To solve this problem, it is necessary to accurately understand the user's emotional state and optimize the travel experience in an individualized manner.

[0352] 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.

[0353] In this invention, the server includes a device for acquiring location information, a device for collecting user interest and activity history data, a device for generating personalized route guidance based on the user's location information, interests, and movement data using a generative AI, a device for recognizing the user's psychological state using an emotion analysis engine and adjusting the route guidance accordingly, and a device for transmitting the adjusted route guidance to the user terminal via a communication network. This enables real-time navigation adjustment in accordance with the user's emotional state and optimization of the in-vehicle environment.

[0354] A "location information acquisition device" is a device that collects and provides data to determine the user's current location.

[0355] A "data collection device for interest and activity history" is a device used to acquire a history of interests and activities that a user has previously shown.

[0356] "Generative AI" refers to artificial intelligence technology that solves complex problems based on the analysis of large amounts of data, and is used to provide personalized services.

[0357] A "personalized route guidance generation device" is a device that generates optimal route guidance according to the user's specific circumstances and preferences.

[0358] An "emotion analysis engine" is a program or device that evaluates a user's emotional state based on their voice, facial expressions, and operation patterns.

[0359] A "transmitting device via a communication network" is a device that includes network communication technology for transmitting generated information to a user's terminal.

[0360] "Navigation adjustment" refers to the act of dynamically changing routes and guidance content based on the user's emotional state.

[0361] "In-vehicle environment" refers to elements such as lighting, temperature, and sound inside an autonomous vehicle, which are adjusted to improve passenger comfort.

[0362] The system for carrying out the present invention consists of a server, a user terminal, an emotion analysis engine, and a communication network. The server receives data from the user using a location information acquisition device and an interest and activity history data collection device. Based on this data, it uses a generative AI to create route guidance optimized for the user. At this time, the emotion analysis engine analyzes the user's voice tone, facial expressions, and operation patterns, and sends the results to the server. The server adjusts the navigation based on this and transmits the information to the user terminal via the communication network.

[0363] The user terminal provides visual guidance by displaying map information and related information using augmented reality technology. This aims to create a comfortable experience inside autonomous vehicles, for example, by changing lighting and sound settings to create an environment suited to the user's psychological state.

[0364] As a concrete example, if a user experiences stress during the morning rush hour commute, the server receives data from the emotion analysis engine, plays relaxing music in the train, and suggests a route that avoids congestion. This reduces the user's stress and allows for a more comfortable journey. An example of a prompt for the generative AI model would be, "Based on the user's emotion data, suggest a way to switch to relaxation mode."

[0365] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0366] Step 1:

[0367] The user terminal acquires location information and interest / activity history data and sends it to the server. Input includes location data from a GPS sensor and past browsing history data. This data is collected and sent to the server as initial information to understand the user's current context. Output is a data packet indicating the user's current state.

[0368] Step 2:

[0369] The server uses a generating AI based on received location information and interest / activity history data to generate personalized route guidance. The input is data packets sent by the user. The generating AI model analyzes this data and generates the optimal route and various guidance information. The output is route guidance information tailored to the user.

[0370] Step 3:

[0371] The emotion analysis engine acquires the user's voice tone and facial expression data and analyzes their emotional state. In this step, the terminal collects voice and video data from the user and sends it to the emotion analysis engine. The input is real-time voice and video data. The emotion analysis engine determines the emotional state and sends the analysis results to the server as output.

[0372] Step 4:

[0373] The server receives the results from the emotion analysis engine and adjusts the route guidance according to the user's emotional state. In this step, the server integrates the analysis results into the route guidance information and makes appropriate adjustments. The inputs are route guidance information and emotional state data. The adjusted route guidance is the output.

[0374] Step 5:

[0375] The server transmits the adjusted route guidance to the user terminal via the communication network. Here, the input is the adjusted route guidance information, as the server transfers the adjusted guidance information to the terminal. The output is the guidance information data received by the user terminal, which assists user interaction.

[0376] Step 6:

[0377] The user terminal visually displays the received route guidance using augmented reality technology and provides it to the user. Here, the input is guidance information data transmitted from the server. Based on this data, the terminal visualizes map information and other data using AR technology and presents it as output on the user's display.

[0378] 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.

[0379] 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.

[0380] 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.

[0381] [Third Embodiment]

[0382] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0383] 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.

[0384] 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).

[0385] 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.

[0386] 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.

[0387] 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).

[0388] 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.

[0389] 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.

[0390] 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.

[0391] 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.

[0392] 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.

[0393] 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".

[0394] The system of the present invention implements specific algorithms and processes to improve the user's dynamic navigation experience. The system mainly consists of a server and a user's terminal, and provides navigation guidance using the user's real-time location information, activity history, and interest data.

[0395] When a user activates their device and enters a destination, the device sends its location information along with the user's interests and past activity history to the server. The server receives this data and uses generative AI to generate optimized navigation directions. In this process, the server also considers the latest traffic and event information to provide the user with the most efficient route.

[0396] The generated navigation guidance can be customized to the user's language settings and is also provided as an audio guide through the device. Furthermore, information on visualized landmarks and points of interest is displayed in real time on the device using augmented reality technology. This display is overlaid on the camera feed, allowing users to understand their travel route more intuitively.

[0397] For example, if a user is in a busy area, the system will suggest a walking route that avoids crowds, while also guiding them to interesting cafes and galleries along the way. This suggestion is derived from the user's previously registered cafe-hopping interests. The server also supports multiple languages, allowing it to provide appropriate guidance to tourists from overseas.

[0398] This system allows users to travel efficiently and comfortably by receiving appropriately personalized guidance without having to actively search for the information they need.

[0399] The following describes the processing flow.

[0400] Step 1:

[0401] The device uses GPS to obtain the user's current location and sends the destination information along with the user's interests and behavioral history data to the server.

[0402] Step 2:

[0403] The server searches and extracts relevant tourist spots and event information from its database based on the received location information and user interest data.

[0404] Step 3:

[0405] The server surveys real-time traffic conditions and uses generative AI to calculate the most efficient and personalized route tailored to the user's preferences.

[0406] Step 4:

[0407] The server generates the calculated route and associated guidance information in multiple languages ​​and formats it in a format that takes into account the user's language setting.

[0408] Step 5:

[0409] The server sends the generated guidance information to the terminal.

[0410] Step 6:

[0411] The terminal displays the received guidance information as a map on its screen and initiates voice guidance as needed.

[0412] Step 7:

[0413] The device activates augmented reality functionality via its camera, displaying landmarks and tourist attractions around the user as video.

[0414] Step 8:

[0415] As the user moves, the device periodically communicates with the server, continuously updating information and routes in real time.

[0416] (Example 1)

[0417] 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."

[0418] In modern transportation, users often find it difficult to efficiently and intuitively find the optimal route, requiring them to research multiple sources of information themselves. Furthermore, navigation instructions are often difficult for users who speak different languages ​​to understand.

[0419] 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.

[0420] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, and means for generating personalized navigation guidance, including an optimized route, using generative AI. This enables the user to receive efficient and comfortable navigation guidance.

[0421] "Location information" refers to data that indicates the user's current location or a specific point in time.

[0422] "Interest and behavioral history data" refers to information about a user's past behavior and preferences, which is used to personalize navigation guidance.

[0423] "Generative AI" is a technology that uses artificial intelligence to generate navigation guidance tailored to the user.

[0424] "Navigation guidance" refers to the process of providing instructions and route information to help users efficiently reach a specific destination.

[0425] A "communication network" is a network or platform for information exchange used to send and receive data.

[0426] A "user terminal" refers to a digital device that a user can use to receive and operate information.

[0427] Augmented reality technology is a technique that overlays digital information onto images of the real world, providing visual assistance.

[0428] "Multilingual support" refers to the ability to provide information in the appropriate language to users who speak different languages.

[0429] This invention is a navigation system designed to improve the efficiency of user movement. The system primarily consists of a server and a user terminal, and provides personalized navigation guidance using a generative AI model. Details and specific examples are provided below.

[0430] The server is located on a cloud platform and receives the user's location information, interests, and behavioral history, allowing a generative AI model to calculate the optimal route. In this calculation, the server uses a learning algorithm to suggest points of interest based on the user's preferences. Furthermore, the server acquires traffic data in real time to optimize the generated route. Navigation guidance is transmitted to the user's terminal via the communication network.

[0431] The user's device will be a smartphone or tablet. The device is equipped with a GPS sensor to acquire location information and implements augmented reality technology. This allows the user to visually confirm the location information of objects and landmarks.

[0432] As a concrete example, consider a case where a user specifies, "I want to go to Tokyo Station." Based on the user's past activity history and hobbies, the server proposes the optimal route, including points of interest such as cafes and galleries. By using AR functionality on the device to provide visual guidance, the user can intuitively understand the route.

[0433] An example of a prompt statement would be entered as follows:

[0434] "Please suggest the best route from my current location to Tokyo Station. My areas of interest are cafes and art galleries."

[0435] Thus, the present invention provides personalized navigation guidance to each user in real time, enabling efficient travel.

[0436] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0437] Step 1:

[0438] The user enters a destination and activates the device. The device obtains the user's current location using a GPS sensor. Based on the input, the device aggregates the acquired location information, the user's past activity history, and interest data, and sends this information to the server. Specifically, the user opens a smartphone application and enters "Tokyo Station" as the destination.

[0439] Step 2:

[0440] The server receives user location information, interests, and behavioral history data sent from the terminal. The server then activates a generative AI model and performs data calculations to generate the optimal route based on this data. Specifically, it analyzes past data and creates a personalized route that takes into account the user's preferred stops and events. The server analyzes the data received as input and outputs optimized navigation guidance as a result.

[0441] Step 3:

[0442] The server acquires the latest traffic data and event information in real time and optimizes the generated route by adding this information. Specifically, it retrieves congestion information and event status from a database and uses it to determine the most efficient route for the user. It takes real-time external data as input and generates adjusted navigation guidance as output.

[0443] Step 4:

[0444] The server transmits the generated, optimized navigation directions to the user's device via the communication network. The device receives these directions and displays them visually using voice guidance and AR technology. Specifically, arrows and landmark information are overlaid on the device screen, allowing the user to follow them to Tokyo Station. The system receives navigation information from the server as input and provides visual and voice guidance to the user as output.

[0445] (Application Example 1)

[0446] 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."

[0447] Traditional navigation systems have struggled to provide personalized guidance based on user interests and behavioral history. Furthermore, they lacked the ability to effectively implement foreign language audio guides and augmented reality-based visual guidance, leaving room for improvement in user convenience. Additionally, data analysis for real-time route selection based on user interests was insufficient.

[0448] 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.

[0449] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, means for generating personalized travel route guidance based on the user's location information, interests, and traffic data using generative AI, means for transmitting the generated travel route guidance to the user terminal via a communication network, means for visually displaying information on landmarks and points of interest using augmented reality technology, and means for providing audio guidance in multiple languages. This enables route selection according to the user's interests and provides more intuitive and multilingual guidance.

[0450] "Location information" refers to data that indicates the user's current geographical location.

[0451] "Interests" refers to information about the preferences and interests that a user has shown in the past.

[0452] "Behavioral history data" refers to data that records a user's past actions and movements.

[0453] "Generative AI" is an artificial intelligence technology that uses machine learning to analyze data and generate information or guidance for a specific purpose.

[0454] "Route guidance" refers to instructions that show the user the optimal route to reach their destination.

[0455] A "communication network" is a digital or analog communication system used to send and receive information.

[0456] "User terminal" refers to any computer or mobile device used by a user.

[0457] Augmented reality technology is a technique that overlays computer-generated information onto images of the real world.

[0458] A "landmark" refers to a geographically or culturally significant location or building that serves as a landmark.

[0459] A "point of interest" is a location that attracts the user's attention or contains important information along their route.

[0460] "Audio guide" refers to a function that provides guidance information to users through audio.

[0461] "Multilingual support" means having the ability to provide information using multiple languages.

[0462] "Data analysis methods" refer to techniques and technologies used to extract and analyze useful information based on collected data.

[0463] This invention is a system that improves the user's dynamic navigation experience. The following hardware and software are required to implement the invention:

[0464] First, the server obtains real-time geographical information via a GPS module to acquire the user's location. In addition to this location information, the user's past behavioral history and interest data are sent to the server. A generative AI model then analyzes this data to generate personalized travel route guidance for the user. Various machine learning models and data science tools, both domestic and international, can be used as generative AI models.

[0465] The user's terminal receives route guidance generated via the communication network. The terminal displays visual information using augmented reality technology through its display. As a result, landmarks and points of interest are overlaid on the camera image, allowing the user to receive guidance more intuitively.

[0466] Furthermore, the terminals utilize speech synthesis software to provide audio guides in multiple languages. This allows for effective information delivery to users who speak different languages. In addition, data analysis tools optimize route selection in real time based on user interests.

[0467] For example, if a user visiting a busy tourist area sets a certain landmark as their destination, the generating AI model can suggest the optimal route to avoid congestion while also guiding them to shops and cafes along the way that might interest them. An example of a prompt used in this case would be: "The user is currently in a busy area. In their past visit history, they have frequently visited art galleries. Based on their current location and past behavior history, please suggest the optimal route that includes some interesting galleries along the way."

[0468] The above describes the specific forms for carrying out the invention.

[0469] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0470] Step 1:

[0471] The server acquires the user's location information. The input is real-time geographical information obtained from a GPS module. The output is prepared to provide the current location coordinate data to a generating AI model. The acquired location information is analyzed in combination with the user's interests and behavioral history.

[0472] Step 2:

[0473] The server collects user interest and behavioral history data. Inputs include past visit history and registered preference information. Outputs include a dataset of interest patterns and behavioral tendencies. This dataset forms the basis for analysis by a generative AI model.

[0474] Step 3:

[0475] The server uses a generative AI model to generate personalized travel route guidance based on location, interests, and traffic data. Input includes data obtained in steps 1 and 2, as well as up-to-date traffic information. Output generates optimized travel routes and guidance information. The generative AI model proposes routes based on prompts, ensuring efficient travel.

[0476] Step 4:

[0477] The server transmits the generated route guidance to the user terminal via the communication network. The input is the route guidance generated in step 3. As output, data is transmitted to the terminal via the network. The terminal receives this and prepares to provide visual and auditory guidance.

[0478] Step 5:

[0479] The device uses augmented reality technology to visually display information about landmarks and points of interest. The input is route guidance received from a server. The output provides the user with an augmented reality view that overlays information onto camera footage. The user can navigate intuitively using this information.

[0480] Step 6:

[0481] The terminal uses speech synthesis software to play audio guides in multiple languages. Inputs are route guidance and language settings from the server. Output provides voice guidance to the destination. This allows the system to accommodate users who speak different languages.

[0482] 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.

[0483] The present invention's system recognizes the user's emotional state by combining navigation guidance based on the user's location information, interests, and behavioral history with an emotion engine, and dynamically adapts the guidance accordingly. This system consists mainly of a server, a user terminal, and an emotion engine, which cooperate via a communication network.

[0484] When a user starts navigation using their device, the device sends location information and interest data to a server. Based on this information, the server uses generative AI to calculate a personalized route and simultaneously sends data to an emotion engine to detect the user's emotional state. This emotion engine analyzes emotions from the user's voice tone, facial expression data, and operation patterns.

[0485] Upon receiving output from the emotion engine, the server adjusts navigation guidance according to the user's current emotional state. For example, if the system determines that the user is stressed, it suggests relaxing routes and rest stops. Conversely, if the system recognizes the user as curious, it can introduce new experiences and tourist attractions. This guidance is provided to the user's device as audio or visual information using augmented reality technology.

[0486] As a concrete example, if a user is visiting a tourist destination during peak season and the emotion engine detects the user's anxiety, the server will suggest a route that avoids crowds and a quiet cafe to rest in. This suggestion is quickly updated on the user's device, providing a more comfortable experience. In this way, by incorporating an emotion engine, it becomes possible to achieve interactive navigation that goes beyond mere information provision and is attentive to the user's emotions.

[0487] The following describes the processing flow.

[0488] Step 1:

[0489] The device obtains the user's current location and sends that information to the server along with the destination setting. Furthermore, it also sends data on the user's interests and behavioral history.

[0490] Step 2:

[0491] The emotion engine analyzes the user's voice input and facial expression data in real time to estimate the user's emotional state. This emotional data is periodically sent to the server.

[0492] Step 3:

[0493] The server inputs relevant navigation information into a generating AI and analyzes it based on the received location information, interest data, and sentiment data.

[0494] Step 4:

[0495] Based on information analyzed by the generating AI, the server creates personalized navigation guidance that takes into account the user's emotional state. For example, if stress is detected, it will select a relaxing route.

[0496] Step 5:

[0497] The server formats emotion-sensitive navigation instructions along with multilingual options and sends them to the terminal.

[0498] Step 6:

[0499] The device provides the user with received directions and supports their movement using voice and visual guidance. Furthermore, it utilizes augmented reality technology to display surrounding landmarks.

[0500] Step 7:

[0501] The user interacts with the device while on the move, and whenever the device detects a change in emotional data, it sends new input to the server. The server updates the guidance as needed and sends it back to the device.

[0502] (Example 2)

[0503] 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."

[0504] Conventional navigation systems have the problem of not taking into account the user's emotional state when providing guidance, making it difficult to provide optimal information tailored to each user's situation. Furthermore, because navigation is not updated in real time in response to dynamic situations, it is difficult to improve user satisfaction.

[0505] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0506] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, means for generating personalized navigation guidance using generative AI, means for estimating emotions from the user's voice tone, facial expression information, and operation patterns, means for dynamically adapting navigation guidance based on the output from the emotion estimation means, and means for transmitting the adapted navigation guidance to the user device via a communication network. This makes it possible to provide optimal navigation in real time according to the user's emotions.

[0507] "Means of acquiring location information" refers to devices and technologies that collect data to determine the user's current location.

[0508] "Means for collecting user interest and behavioral history data" refers to methods or systems for recording a user's past activities and preferences and organizing information based on them.

[0509] "Means for generating personalized navigation guidance using generative AI" refers to a process or engine that utilizes artificial intelligence technology to create the most suitable routes and guidance for individual users.

[0510] "An emotion estimation method that analyzes emotions from a user's voice tone, facial expression information, and operation patterns" refers to a technology or system that analyzes the tone of voice, facial expressions, and device operation behavior, and uses them to infer the user's emotional state.

[0511] "Means for dynamically adapting navigation guidance based on the output from the emotion estimation means" refers to a mechanism for adjusting existing guidance routes and content in real time in a way that reflects the user's emotional state.

[0512] "Means for transmitting the adapted navigation guidance to a user device via a communication network" means a method or technique for transferring improved guidance information to a user's device via a network.

[0513] This system utilizes user location information, interests, and behavioral history data to provide personalized navigation guidance. The server, user terminal, and emotion engine work together in a coordinated manner.

[0514] When a user starts navigation using their device, the device uses its GPS function to obtain its current location. Furthermore, the device collects user interest and behavioral data from application usage and browsing history, and sends this data to a server. Encrypted communication protocols are used throughout this process to ensure data security.

[0515] The server uses a generative AI model based on the received data to generate personalized navigation guidance for the user. This AI model utilizes common cloud services for computation. Specific software includes machine learning frameworks and data analysis tools. Simultaneously, the server sends the user's voice, facial expression data, and action patterns to an emotion engine to analyze the user's emotional state. The emotion engine identifies the user's emotions from their voice tone and facial expressions.

[0516] The server dynamically adapts navigation guidance based on emotional state information from the emotion engine. For example, if the analysis indicates that the user is stressed, it suggests a relaxing route. On the other hand, if the server determines that the user is curious, it adjusts the guidance to show new tourist spots. This guidance is provided to the user's device as audio or visual information using AR technology.

[0517] As a concrete example, consider a situation where a user is traveling in a city and has selected a museum as their destination. In this case, an example of a prompt message might be, "The user's location is in the city center, their interest is history, and their emotion is curiosity. Based on this, suggest an appropriate sightseeing route and related spots." In this way, the system can provide a more interactive and enriching navigation experience that is attentive to the user's emotional state.

[0518] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0519] Step 1:

[0520] The user initiates navigation using the device. The device obtains its current location using GPS and simultaneously collects data on the user's interests and behavioral history. Specifically, the device reads application usage and visit history and reconciles this data. This prepares the location information and user interests as input data, ready to be sent to the server.

[0521] Step 2:

[0522] The device sends collected location information, interest data, and behavioral history data to the server. The server receives this data and generates personalized navigation guidance using a generative AI model. The location information and interest data received as input data are analyzed by the AI ​​algorithm to extract information about the optimal route and points of interest. As output, user-specific navigation guidance is created.

[0523] Step 3:

[0524] The server sends the user's voice tone, facial expression information, and operation patterns to the emotion engine. This provides the emotion engine with voice and visual information as input data, and sentiment analysis is performed. Specifically, the emotion engine uses a machine learning model to analyze the characteristics of the voice and facial expressions to identify the user's emotional state. The output is the emotional state information obtained by the emotion engine.

[0525] Step 4:

[0526] The server dynamically adapts the generated navigation guidance based on emotional state information from the emotion engine. This process includes suggesting relaxation routes when stress is detected and new spots that reflect curiosity. It receives emotion analysis results as input and edits the guidance content based on them. The output is the adjusted navigation guidance, which includes information that corresponds to the user's specific situation and emotions.

[0527] Step 5:

[0528] The adapted navigation guidance is transmitted from the server to the user's device via a communication network. The device then presents the received guidance through voice and AR technology. Specific actions include generating real-time voice guidance using a speech synthesis engine and displaying visual information on the device's display using augmented reality. The output is an interactive navigation experience provided to the user.

[0529] (Application Example 2)

[0530] 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."

[0531] In modern society, information overload and busy lifestyles often cause stress for many travelers during their journeys. Furthermore, congestion and unexpected problems at popular tourist destinations and events can disrupt plans, diminishing the traveler's experience. Autonomous vehicles, in particular, require flexible responses tailored to the user's psychological state, but current systems fail to adequately address this. To solve this problem, it is necessary to accurately understand the user's emotional state and optimize the travel experience in an individualized manner.

[0532] 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.

[0533] In this invention, the server includes a device for acquiring location information, a device for collecting user interest and activity history data, a device for generating personalized route guidance based on the user's location information, interests, and movement data using a generative AI, a device for recognizing the user's psychological state using an emotion analysis engine and adjusting the route guidance accordingly, and a device for transmitting the adjusted route guidance to the user terminal via a communication network. This enables real-time navigation adjustment in accordance with the user's emotional state and optimization of the in-vehicle environment.

[0534] A "location information acquisition device" is a device that collects and provides data to determine the user's current location.

[0535] A "data collection device for interest and activity history" is a device used to acquire a history of interests and activities that a user has previously shown.

[0536] "Generative AI" refers to artificial intelligence technology that solves complex problems based on the analysis of large amounts of data, and is used to provide personalized services.

[0537] A "personalized route guidance generation device" is a device that generates optimal route guidance according to the user's specific circumstances and preferences.

[0538] An "emotion analysis engine" is a program or device that evaluates a user's emotional state based on their voice, facial expressions, and operation patterns.

[0539] A "transmitting device via a communication network" is a device that includes network communication technology for transmitting generated information to a user's terminal.

[0540] "Navigation adjustment" refers to the act of dynamically changing routes and guidance content based on the user's emotional state.

[0541] "In-vehicle environment" refers to elements such as lighting, temperature, and sound inside an autonomous vehicle, which are adjusted to improve passenger comfort.

[0542] The system for carrying out the present invention consists of a server, a user terminal, an emotion analysis engine, and a communication network. The server receives data from the user using a location information acquisition device and an interest and activity history data collection device. Based on this data, it uses a generative AI to create route guidance optimized for the user. At this time, the emotion analysis engine analyzes the user's voice tone, facial expressions, and operation patterns, and sends the results to the server. The server adjusts the navigation based on this and transmits the information to the user terminal via the communication network.

[0543] The user terminal provides visual guidance by displaying map information and related information using augmented reality technology. This aims to create a comfortable experience inside autonomous vehicles, for example, by changing lighting and sound settings to create an environment suited to the user's psychological state.

[0544] As a concrete example, if a user experiences stress during the morning rush hour commute, the server receives data from the emotion analysis engine, plays relaxing music in the train, and suggests a route that avoids congestion. This reduces the user's stress and allows for a more comfortable journey. An example of a prompt for the generative AI model would be, "Based on the user's emotion data, suggest a way to switch to relaxation mode."

[0545] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0546] Step 1:

[0547] The user terminal acquires location information and interest / activity history data and sends it to the server. Input includes location data from a GPS sensor and past browsing history data. This data is collected and sent to the server as initial information to understand the user's current context. Output is a data packet indicating the user's current state.

[0548] Step 2:

[0549] The server uses a generating AI based on received location information and interest / activity history data to generate personalized route guidance. The input is data packets sent by the user. The generating AI model analyzes this data and generates the optimal route and various guidance information. The output is route guidance information tailored to the user.

[0550] Step 3:

[0551] The emotion analysis engine acquires the user's voice tone and facial expression data and analyzes their emotional state. In this step, the terminal collects voice and video data from the user and sends it to the emotion analysis engine. The input is real-time voice and video data. The emotion analysis engine determines the emotional state and sends the analysis results to the server as output.

[0552] Step 4:

[0553] The server receives the results from the emotion analysis engine and adjusts the route guidance according to the user's emotional state. In this step, the server integrates the analysis results into the route guidance information and makes appropriate adjustments. The inputs are route guidance information and emotional state data. The adjusted route guidance is the output.

[0554] Step 5:

[0555] The server transmits the adjusted route guidance to the user terminal via the communication network. Here, the input is the adjusted route guidance information, as the server transfers the adjusted guidance information to the terminal. The output is the guidance information data received by the user terminal, which assists user interaction.

[0556] Step 6:

[0557] The user terminal visually displays the received route guidance using augmented reality technology and provides it to the user. Here, the input is guidance information data transmitted from the server. Based on this data, the terminal visualizes map information and other data using AR technology and presents it as output on the user's display.

[0558] 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.

[0559] 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.

[0560] 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.

[0561] [Fourth Embodiment]

[0562] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0563] 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.

[0564] 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).

[0565] 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.

[0566] 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.

[0567] 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).

[0568] 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.

[0569] 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.

[0570] 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.

[0571] 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.

[0572] 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.

[0573] 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.

[0574] 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".

[0575] The system of the present invention implements specific algorithms and processes to improve the user's dynamic navigation experience. The system mainly consists of a server and a user's terminal, and provides navigation guidance using the user's real-time location information, activity history, and interest data.

[0576] When a user activates their device and enters a destination, the device sends its location information along with the user's interests and past activity history to the server. The server receives this data and uses generative AI to generate optimized navigation directions. In this process, the server also considers the latest traffic and event information to provide the user with the most efficient route.

[0577] The generated navigation guidance can be customized to the user's language settings and is also provided as an audio guide through the device. Furthermore, information on visualized landmarks and points of interest is displayed in real time on the device using augmented reality technology. This display is overlaid on the camera feed, allowing users to understand their travel route more intuitively.

[0578] For example, if a user is in a busy area, the system will suggest a walking route that avoids crowds, while also guiding them to interesting cafes and galleries along the way. This suggestion is derived from the user's previously registered cafe-hopping interests. The server also supports multiple languages, allowing it to provide appropriate guidance to tourists from overseas.

[0579] This system allows users to travel efficiently and comfortably by receiving appropriately personalized guidance without having to actively search for the information they need.

[0580] The following describes the processing flow.

[0581] Step 1:

[0582] The device uses GPS to obtain the user's current location and sends the destination information along with the user's interests and behavioral history data to the server.

[0583] Step 2:

[0584] The server searches and extracts relevant tourist spots and event information from its database based on the received location information and user interest data.

[0585] Step 3:

[0586] The server surveys real-time traffic conditions and uses generative AI to calculate the most efficient and personalized route tailored to the user's preferences.

[0587] Step 4:

[0588] The server generates the calculated route and associated guidance information in multiple languages ​​and formats it in a format that takes into account the user's language setting.

[0589] Step 5:

[0590] The server sends the generated guidance information to the terminal.

[0591] Step 6:

[0592] The terminal displays the received guidance information as a map on its screen and initiates voice guidance as needed.

[0593] Step 7:

[0594] The device activates augmented reality functionality via its camera, displaying landmarks and tourist attractions around the user as video.

[0595] Step 8:

[0596] As the user moves, the device periodically communicates with the server, continuously updating information and routes in real time.

[0597] (Example 1)

[0598] 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".

[0599] In modern transportation, users often find it difficult to efficiently and intuitively find the optimal route, requiring them to research multiple sources of information themselves. Furthermore, navigation instructions are often difficult for users who speak different languages ​​to understand.

[0600] 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.

[0601] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, and means for generating personalized navigation guidance, including an optimized route, using generative AI. This enables the user to receive efficient and comfortable navigation guidance.

[0602] "Location information" refers to data that indicates the user's current location or a specific point in time.

[0603] "Interest and behavioral history data" refers to information about a user's past behavior and preferences, which is used to personalize navigation guidance.

[0604] "Generative AI" is a technology that uses artificial intelligence to generate navigation guidance tailored to the user.

[0605] "Navigation guidance" refers to the process of providing instructions and route information to help users efficiently reach a specific destination.

[0606] A "communication network" is a network or platform for information exchange used to send and receive data.

[0607] A "user terminal" refers to a digital device that a user can use to receive and operate information.

[0608] Augmented reality technology is a technique that overlays digital information onto images of the real world, providing visual assistance.

[0609] "Multilingual support" refers to the ability to provide information in the appropriate language to users who speak different languages.

[0610] This invention is a navigation system designed to improve the efficiency of user movement. The system primarily consists of a server and a user terminal, and provides personalized navigation guidance using a generative AI model. Details and specific examples are provided below.

[0611] The server is located on a cloud platform and receives the user's location information, interests, and behavioral history, allowing a generative AI model to calculate the optimal route. In this calculation, the server uses a learning algorithm to suggest points of interest based on the user's preferences. Furthermore, the server acquires traffic data in real time to optimize the generated route. Navigation guidance is transmitted to the user's terminal via the communication network.

[0612] The user's device will be a smartphone or tablet. The device is equipped with a GPS sensor to acquire location information and implements augmented reality technology. This allows the user to visually confirm the location information of objects and landmarks.

[0613] As a concrete example, consider a case where a user specifies, "I want to go to Tokyo Station." Based on the user's past activity history and hobbies, the server proposes the optimal route, including points of interest such as cafes and galleries. By using AR functionality on the device to provide visual guidance, the user can intuitively understand the route.

[0614] An example of a prompt statement would be entered as follows:

[0615] "Please suggest the best route from my current location to Tokyo Station. My areas of interest are cafes and art galleries."

[0616] Thus, the present invention provides personalized navigation guidance to each user in real time, enabling efficient travel.

[0617] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0618] Step 1:

[0619] The user enters a destination and activates the device. The device obtains the user's current location using a GPS sensor. Based on the input, the device aggregates the acquired location information, the user's past activity history, and interest data, and sends this information to the server. Specifically, the user opens a smartphone application and enters "Tokyo Station" as the destination.

[0620] Step 2:

[0621] The server receives user location information, interests, and behavioral history data sent from the terminal. The server then activates a generative AI model and performs data calculations to generate the optimal route based on this data. Specifically, it analyzes past data and creates a personalized route that takes into account the user's preferred stops and events. The server analyzes the data received as input and outputs optimized navigation guidance as a result.

[0622] Step 3:

[0623] The server acquires the latest traffic data and event information in real time and optimizes the generated route by adding this information. Specifically, it retrieves congestion information and event status from a database and uses it to determine the most efficient route for the user. It takes real-time external data as input and generates adjusted navigation guidance as output.

[0624] Step 4:

[0625] The server transmits the generated, optimized navigation directions to the user's device via the communication network. The device receives these directions and displays them visually using voice guidance and AR technology. Specifically, arrows and landmark information are overlaid on the device screen, allowing the user to follow them to Tokyo Station. The system receives navigation information from the server as input and provides visual and voice guidance to the user as output.

[0626] (Application Example 1)

[0627] 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".

[0628] Traditional navigation systems have struggled to provide personalized guidance based on user interests and behavioral history. Furthermore, they lacked the ability to effectively implement foreign language audio guides and augmented reality-based visual guidance, leaving room for improvement in user convenience. Additionally, data analysis for real-time route selection based on user interests was insufficient.

[0629] 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.

[0630] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, means for generating personalized travel route guidance based on the user's location information, interests, and traffic data using generative AI, means for transmitting the generated travel route guidance to the user terminal via a communication network, means for visually displaying information on landmarks and points of interest using augmented reality technology, and means for providing audio guidance in multiple languages. This enables route selection according to the user's interests and provides more intuitive and multilingual guidance.

[0631] "Location information" refers to data that indicates the user's current geographical location.

[0632] "Interests" refers to information about the preferences and interests that a user has shown in the past.

[0633] "Behavioral history data" refers to data that records a user's past actions and movements.

[0634] "Generative AI" is an artificial intelligence technology that uses machine learning to analyze data and generate information or guidance for a specific purpose.

[0635] "Route guidance" refers to instructions that show the user the optimal route to reach their destination.

[0636] A "communication network" is a digital or analog communication system used to send and receive information.

[0637] "User terminal" refers to any computer or mobile device used by a user.

[0638] Augmented reality technology is a technique that overlays computer-generated information onto images of the real world.

[0639] A "landmark" refers to a geographically or culturally significant location or building that serves as a landmark.

[0640] A "point of interest" is a location that attracts the user's attention or contains important information along their route.

[0641] "Audio guide" refers to a function that provides guidance information to users through audio.

[0642] "Multilingual support" means having the ability to provide information using multiple languages.

[0643] "Data analysis methods" refer to techniques and technologies used to extract and analyze useful information based on collected data.

[0644] This invention is a system that improves the user's dynamic navigation experience. The following hardware and software are required to implement the invention:

[0645] First, the server obtains real-time geographical information via a GPS module to acquire the user's location. In addition to this location information, the user's past behavioral history and interest data are sent to the server. A generative AI model then analyzes this data to generate personalized travel route guidance for the user. Various machine learning models and data science tools, both domestic and international, can be used as generative AI models.

[0646] The user's terminal receives route guidance generated via the communication network. The terminal displays visual information using augmented reality technology through its display. As a result, landmarks and points of interest are overlaid on the camera image, allowing the user to receive guidance more intuitively.

[0647] Furthermore, the terminals utilize speech synthesis software to provide audio guides in multiple languages. This allows for effective information delivery to users who speak different languages. In addition, data analysis tools optimize route selection in real time based on user interests.

[0648] For example, if a user visiting a busy tourist area sets a certain landmark as their destination, the generating AI model can suggest the optimal route to avoid congestion while also guiding them to shops and cafes along the way that might interest them. An example of a prompt used in this case would be: "The user is currently in a busy area. In their past visit history, they have frequently visited art galleries. Based on their current location and past behavior history, please suggest the optimal route that includes some interesting galleries along the way."

[0649] The above describes the specific forms for carrying out the invention.

[0650] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0651] Step 1:

[0652] The server acquires the user's location information. The input is real-time geographical information obtained from a GPS module. The output is prepared to provide the current location coordinate data to a generating AI model. The acquired location information is analyzed in combination with the user's interests and behavioral history.

[0653] Step 2:

[0654] The server collects user interest and behavioral history data. Inputs include past visit history and registered preference information. Outputs include a dataset of interest patterns and behavioral tendencies. This dataset forms the basis for analysis by a generative AI model.

[0655] Step 3:

[0656] The server uses a generative AI model to generate personalized travel route guidance based on location, interests, and traffic data. Input includes data obtained in steps 1 and 2, as well as up-to-date traffic information. Output generates optimized travel routes and guidance information. The generative AI model proposes routes based on prompts, ensuring efficient travel.

[0657] Step 4:

[0658] The server transmits the generated route guidance to the user terminal via the communication network. The input is the route guidance generated in step 3. As output, data is transmitted to the terminal via the network. The terminal receives this and prepares to provide visual and auditory guidance.

[0659] Step 5:

[0660] The device uses augmented reality technology to visually display information about landmarks and points of interest. The input is route guidance received from a server. The output provides the user with an augmented reality view that overlays information onto camera footage. The user can navigate intuitively using this information.

[0661] Step 6:

[0662] The terminal uses speech synthesis software to play audio guides in multiple languages. Inputs are route guidance and language settings from the server. Output provides voice guidance to the destination. This allows the system to accommodate users who speak different languages.

[0663] 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.

[0664] The present invention's system recognizes the user's emotional state by combining navigation guidance based on the user's location information, interests, and behavioral history with an emotion engine, and dynamically adapts the guidance accordingly. This system consists mainly of a server, a user terminal, and an emotion engine, which cooperate via a communication network.

[0665] When a user starts navigation using their device, the device sends location information and interest data to a server. Based on this information, the server uses generative AI to calculate a personalized route and simultaneously sends data to an emotion engine to detect the user's emotional state. This emotion engine analyzes emotions from the user's voice tone, facial expression data, and operation patterns.

[0666] Upon receiving output from the emotion engine, the server adjusts navigation guidance according to the user's current emotional state. For example, if the system determines that the user is stressed, it suggests relaxing routes and rest stops. Conversely, if the system recognizes the user as curious, it can introduce new experiences and tourist attractions. This guidance is provided to the user's device as audio or visual information using augmented reality technology.

[0667] As a concrete example, if a user is visiting a tourist destination during peak season and the emotion engine detects the user's anxiety, the server will suggest a route that avoids crowds and a quiet cafe to rest in. This suggestion is quickly updated on the user's device, providing a more comfortable experience. In this way, by incorporating an emotion engine, it becomes possible to achieve interactive navigation that goes beyond mere information provision and is attentive to the user's emotions.

[0668] The following describes the processing flow.

[0669] Step 1:

[0670] The device obtains the user's current location and sends that information to the server along with the destination setting. Furthermore, it also sends data on the user's interests and behavioral history.

[0671] Step 2:

[0672] The emotion engine analyzes the user's voice input and facial expression data in real time to estimate the user's emotional state. This emotional data is periodically sent to the server.

[0673] Step 3:

[0674] The server inputs relevant navigation information into a generating AI and analyzes it based on the received location information, interest data, and sentiment data.

[0675] Step 4:

[0676] Based on information analyzed by the generating AI, the server creates personalized navigation guidance that takes into account the user's emotional state. For example, if stress is detected, it will select a relaxing route.

[0677] Step 5:

[0678] The server formats emotion-sensitive navigation instructions along with multilingual options and sends them to the terminal.

[0679] Step 6:

[0680] The device provides the user with received directions and supports their movement using voice and visual guidance. Furthermore, it utilizes augmented reality technology to display surrounding landmarks.

[0681] Step 7:

[0682] The user interacts with the device while on the move, and whenever the device detects a change in emotional data, it sends new input to the server. The server updates the guidance as needed and sends it back to the device.

[0683] (Example 2)

[0684] 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".

[0685] Conventional navigation systems have the problem of not taking into account the user's emotional state when providing guidance, making it difficult to provide optimal information tailored to each user's situation. Furthermore, because navigation is not updated in real time in response to dynamic situations, it is difficult to improve user satisfaction.

[0686] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0687] In this invention, the server includes means for acquiring location information, means for collecting user interest and behavioral history data, means for generating personalized navigation guidance using generative AI, means for estimating emotions from the user's voice tone, facial expression information, and operation patterns, means for dynamically adapting navigation guidance based on the output from the emotion estimation means, and means for transmitting the adapted navigation guidance to the user device via a communication network. This makes it possible to provide optimal navigation in real time according to the user's emotions.

[0688] "Means of acquiring location information" refers to devices and technologies that collect data to determine the user's current location.

[0689] "Means for collecting user interest and behavioral history data" refers to methods or systems for recording a user's past activities and preferences and organizing information based on them.

[0690] "Means for generating personalized navigation guidance using generative AI" refers to a process or engine that utilizes artificial intelligence technology to create the most suitable routes and guidance for individual users.

[0691] "An emotion estimation method that analyzes emotions from a user's voice tone, facial expression information, and operation patterns" refers to a technology or system that analyzes the tone of voice, facial expressions, and device operation behavior, and uses them to infer the user's emotional state.

[0692] "Means for dynamically adapting navigation guidance based on the output from the emotion estimation means" refers to a mechanism for adjusting existing guidance routes and content in real time in a way that reflects the user's emotional state.

[0693] "Means for transmitting the adapted navigation guidance to a user device via a communication network" means a method or technique for transferring improved guidance information to a user's device via a network.

[0694] This system utilizes user location information, interests, and behavioral history data to provide personalized navigation guidance. The server, user terminal, and emotion engine work together in a coordinated manner.

[0695] When a user starts navigation using their device, the device uses its GPS function to obtain its current location. Furthermore, the device collects user interest and behavioral data from application usage and browsing history, and sends this data to a server. Encrypted communication protocols are used throughout this process to ensure data security.

[0696] The server uses a generative AI model based on the received data to generate personalized navigation guidance for the user. This AI model utilizes common cloud services for computation. Specific software includes machine learning frameworks and data analysis tools. Simultaneously, the server sends the user's voice, facial expression data, and action patterns to an emotion engine to analyze the user's emotional state. The emotion engine identifies the user's emotions from their voice tone and facial expressions.

[0697] The server dynamically adapts navigation guidance based on emotional state information from the emotion engine. For example, if the analysis indicates that the user is stressed, it suggests a relaxing route. On the other hand, if the server determines that the user is curious, it adjusts the guidance to show new tourist spots. This guidance is provided to the user's device as audio or visual information using AR technology.

[0698] As a concrete example, consider a situation where a user is traveling in a city and has selected a museum as their destination. In this case, an example of a prompt message might be, "The user's location is in the city center, their interest is history, and their emotion is curiosity. Based on this, suggest an appropriate sightseeing route and related spots." In this way, the system can provide a more interactive and enriching navigation experience that is attentive to the user's emotional state.

[0699] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0700] Step 1:

[0701] The user initiates navigation using the device. The device obtains its current location using GPS and simultaneously collects data on the user's interests and behavioral history. Specifically, the device reads application usage and visit history and reconciles this data. This prepares the location information and user interests as input data, ready to be sent to the server.

[0702] Step 2:

[0703] The device sends collected location information, interest data, and behavioral history data to the server. The server receives this data and generates personalized navigation guidance using a generative AI model. The location information and interest data received as input data are analyzed by the AI ​​algorithm to extract information about the optimal route and points of interest. As output, user-specific navigation guidance is created.

[0704] Step 3:

[0705] The server sends the user's voice tone, facial expression information, and operation patterns to the emotion engine. This provides the emotion engine with voice and visual information as input data, and sentiment analysis is performed. Specifically, the emotion engine uses a machine learning model to analyze the characteristics of the voice and facial expressions to identify the user's emotional state. The output is the emotional state information obtained by the emotion engine.

[0706] Step 4:

[0707] The server dynamically adapts the generated navigation guidance based on emotional state information from the emotion engine. This process includes suggesting relaxation routes when stress is detected and new spots that reflect curiosity. It receives emotion analysis results as input and edits the guidance content based on them. The output is the adjusted navigation guidance, which includes information that corresponds to the user's specific situation and emotions.

[0708] Step 5:

[0709] The adapted navigation guidance is transmitted from the server to the user's device via a communication network. The device then presents the received guidance through voice and AR technology. Specific actions include generating real-time voice guidance using a speech synthesis engine and displaying visual information on the device's display using augmented reality. The output is an interactive navigation experience provided to the user.

[0710] (Application Example 2)

[0711] 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".

[0712] In modern society, information overload and busy lifestyles often cause stress for many travelers during their journeys. Furthermore, congestion and unexpected problems at popular tourist destinations and events can disrupt plans, diminishing the traveler's experience. Autonomous vehicles, in particular, require flexible responses tailored to the user's psychological state, but current systems fail to adequately address this. To solve this problem, it is necessary to accurately understand the user's emotional state and optimize the travel experience in an individualized manner.

[0713] 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.

[0714] In this invention, the server includes a device for acquiring location information, a device for collecting user interest and activity history data, a device for generating personalized route guidance based on the user's location information, interests, and movement data using a generative AI, a device for recognizing the user's psychological state using an emotion analysis engine and adjusting the route guidance accordingly, and a device for transmitting the adjusted route guidance to the user terminal via a communication network. This enables real-time navigation adjustment in accordance with the user's emotional state and optimization of the in-vehicle environment.

[0715] A "location information acquisition device" is a device that collects and provides data to determine the user's current location.

[0716] A "data collection device for interest and activity history" is a device used to acquire a history of interests and activities that a user has previously shown.

[0717] "Generative AI" refers to artificial intelligence technology that solves complex problems based on the analysis of large amounts of data, and is used to provide personalized services.

[0718] A "personalized route guidance generation device" is a device that generates optimal route guidance according to the user's specific circumstances and preferences.

[0719] An "emotion analysis engine" is a program or device that evaluates a user's emotional state based on their voice, facial expressions, and operation patterns.

[0720] A "transmitting device via a communication network" is a device that includes network communication technology for transmitting generated information to a user's terminal.

[0721] "Navigation adjustment" refers to the act of dynamically changing routes and guidance content based on the user's emotional state.

[0722] "In-vehicle environment" refers to elements such as lighting, temperature, and sound inside an autonomous vehicle, which are adjusted to improve passenger comfort.

[0723] The system for carrying out the present invention consists of a server, a user terminal, an emotion analysis engine, and a communication network. The server receives data from the user using a location information acquisition device and an interest and activity history data collection device. Based on this data, it uses a generative AI to create route guidance optimized for the user. At this time, the emotion analysis engine analyzes the user's voice tone, facial expressions, and operation patterns, and sends the results to the server. The server adjusts the navigation based on this and transmits the information to the user terminal via the communication network.

[0724] The user terminal provides visual guidance by displaying map information and related information using augmented reality technology. This aims to create a comfortable experience inside autonomous vehicles, for example, by changing lighting and sound settings to create an environment suited to the user's psychological state.

[0725] As a concrete example, if a user experiences stress during the morning rush hour commute, the server receives data from the emotion analysis engine, plays relaxing music in the train, and suggests a route that avoids congestion. This reduces the user's stress and allows for a more comfortable journey. An example of a prompt for the generative AI model would be, "Based on the user's emotion data, suggest a way to switch to relaxation mode."

[0726] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0727] Step 1:

[0728] The user terminal acquires location information and interest / activity history data and sends it to the server. Input includes location data from a GPS sensor and past browsing history data. This data is collected and sent to the server as initial information to understand the user's current context. Output is a data packet indicating the user's current state.

[0729] Step 2:

[0730] The server uses a generating AI based on received location information and interest / activity history data to generate personalized route guidance. The input is data packets sent by the user. The generating AI model analyzes this data and generates the optimal route and various guidance information. The output is route guidance information tailored to the user.

[0731] Step 3:

[0732] The emotion analysis engine acquires the user's voice tone and facial expression data and analyzes their emotional state. In this step, the terminal collects voice and video data from the user and sends it to the emotion analysis engine. The input is real-time voice and video data. The emotion analysis engine determines the emotional state and sends the analysis results to the server as output.

[0733] Step 4:

[0734] The server receives the results from the emotion analysis engine and adjusts the route guidance according to the user's emotional state. In this step, the server integrates the analysis results into the route guidance information and makes appropriate adjustments. The inputs are route guidance information and emotional state data. The adjusted route guidance is the output.

[0735] Step 5:

[0736] The server transmits the adjusted route guidance to the user terminal via the communication network. Here, the input is the adjusted route guidance information, as the server transfers the adjusted guidance information to the terminal. The output is the guidance information data received by the user terminal, which assists user interaction.

[0737] Step 6:

[0738] The user terminal visually displays the received route guidance using augmented reality technology and provides it to the user. Here, the input is guidance information data transmitted from the server. Based on this data, the terminal visualizes map information and other data using AR technology and presents it as output on the user's display.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] 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.

[0743] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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."

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] The following is further disclosed regarding the embodiments described above.

[0761] (Claim 1)

[0762] Means for obtaining location information,

[0763] Means for collecting user interest and behavioral history data,

[0764] A means for generating personalized navigation guidance based on the user's location information, interests, and traffic data using a generation AI,

[0765] Means for transmitting the generated navigation guidance to a user terminal via a communication network,

[0766] A system that includes this.

[0767] (Claim 2)

[0768] The system according to claim 1, further comprising means for updating the navigation guidance in real time in response to a user's request.

[0769] (Claim 3)

[0770] The system according to claim 1, further comprising means for visually displaying map information and related guidance on the user terminal using augmented reality technology.

[0771] "Example 1"

[0772] (Claim 1)

[0773] Means for obtaining location information,

[0774] Means for collecting user interest and behavioral history data,

[0775] A means for generating personalized navigation guidance, including an optimized route, based on the user's location information, interests, and traffic data, using a generation AI.

[0776] Means for transmitting the generated navigation guidance to a user terminal via a communication network,

[0777] A means of displaying landmarks and related information overlaid on a user's terminal using augmented reality technology,

[0778] A system that includes this.

[0779] (Claim 2)

[0780] The system according to claim 1, further comprising means for updating navigation guidance in real time in response to user requests and presenting it in a format that is easy for the user to understand.

[0781] (Claim 3)

[0782] The system according to claim 1, further comprising means for providing navigation guidance according to the user's language settings through multi-language support.

[0783] "Application Example 1"

[0784] (Claim 1)

[0785] Means for obtaining location information,

[0786] Means for collecting user interest and behavioral history data,

[0787] A means for generating personalized travel route guidance based on the user's location information, interests, and traffic data using a generative AI,

[0788] A means for transmitting the generated travel route guidance to the user terminal via a communication network,

[0789] A means of visually displaying information about landmarks and points of interest using augmented reality technology,

[0790] A means of providing audio guides in multiple languages,

[0791] A system that includes this.

[0792] (Claim 2)

[0793] The system according to claim 1, further comprising means for updating the travel route guidance in real time in response to a user's request.

[0794] (Claim 3)

[0795] The system according to claim 1, further comprising data analysis means for selecting routes according to the user's interests.

[0796] "Example 2 of combining an emotion engine"

[0797] (Claim 1)

[0798] Means for obtaining location information,

[0799] Means for collecting user interest and behavioral history data,

[0800] A means for generating personalized navigation guidance based on the user's location information, interests, and traffic information using a generation AI,

[0801] An emotion estimation means that analyzes emotions from the user's voice tone, facial expression information, and operation patterns,

[0802] A means for dynamically adapting the generated navigation guidance based on the output from the emotion estimation means,

[0803] Means for transmitting the adapted navigation guidance to a user device via a communication network,

[0804] ...

[0805] A system that includes this.

[0806] (Claim 2)

[0807] The system according to claim 1, further comprising means for updating the navigation guidance in real time in response to a user's request.

[0808] (Claim 3)

[0809] The system according to claim 1, further comprising means for visually displaying map information and related guidance on the user device using augmented reality technology.

[0810] "Application example 2 when combining with an emotional engine"

[0811] (Claim 1)

[0812] A device for acquiring location information,

[0813] A device for collecting user interest and activity history data,

[0814] A device that generates personalized route guidance based on the user's location information, interests, and movement data using a generation AI,

[0815] In addition to the generated route guidance, the device uses an emotion analysis engine to recognize the user's psychological state and adjusts the route guidance accordingly.

[0816] A device that transmits the adjusted route guidance to a user terminal via a communication network,

[0817] A system that includes this.

[0818] (Claim 2)

[0819] The system according to claim 1, further comprising a device that dynamically updates the route guidance and adjusts the in-vehicle environment in response to user requests.

[0820] (Claim 3)

[0821] The system according to claim 1, further comprising a device that uses augmented reality technology to visually present map information and related guidance on the user terminal and optimizes the experience based on the emotional state. [Explanation of Symbols]

[0822] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for obtaining location information, Means for collecting user interest and behavioral history data, A means for generating personalized navigation guidance based on the user's location information, interests, and traffic data using a generation AI, Means for transmitting the generated navigation guidance to a user terminal via a communication network, A system that includes this.

2. The system according to claim 1, further comprising means for updating the navigation guidance in real time in response to a user's request.

3. The system according to claim 1, further comprising means for visually displaying map information and related guidance on the user terminal using augmented reality technology.

Images