system

Abstract

We provide the system. [Solution] An input means for inputting the user's hobbies and preferences, An analysis means that generates recommended destinations based on the aforementioned hobby and preference information using a generative AI model, A means for acquiring real-time traffic and weather information and dynamically updating the list of recommended destinations, A presentation means for displaying and providing voice guidance to the user the list of recommended destinations, A route guidance means that calculates the optimal route to the destination selected by the user and provides route guidance, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance 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] Conventional navigation systems can provide route guidance considering real-time traffic information and weather information, but it has been difficult to recommend tourist spots, restaurants, and accommodation facilities based on the individual hobbies and interests of users. As a result, problems have arisen such as taking a long time for planning to enjoy a trip or a drive, and the route planning at the travel destination being uncertain. In addition, traffic congestion on roads and deterioration of moving efficiency due to weather have also been factors that impair the travel experience of users. The present invention aims to solve these problems and provide a more personalized stress-free driving and travel experience.

Means for Solving the Problems

[0005] The present invention is a system comprising: input means for inputting user's hobby and preference information; analysis means for generating recommended destinations based on the hobby and preference information using a generation AI model; acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations; presentation means for presenting the list of recommended destinations to the user via display and voice guidance; and route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance. This enables personalized destination recommendations based on the user's hobbies and preferences, and guidance on the optimal route based on real-time traffic and weather information, providing a comfortable and efficient driving and travel experience. Furthermore, by dynamically updating route guidance according to real-time conditions during travel, even higher travel efficiency can be ensured, and user satisfaction can be improved.

[0006] A "user" is a person who uses an in-car system to enjoy traveling or driving.

[0007] "Hobby and preference information" refers to data about the user's areas of interest and preference.

[0008] An "input method" is an interface that allows users to input information such as their hobbies, preferences, and destinations into the in-vehicle system.

[0009] A "generative AI model" is an artificial intelligence model that performs analysis and predictions based on generated data.

[0010] "Recommended destinations" are candidates for tourist spots, restaurants, accommodations, etc., selected by the generating AI model based on the user's interests and preferences.

[0011] "Analysis means" refers to a method for analyzing a user's hobbies and preferences using a generative AI model and generating recommended destinations.

[0012] "Real-time traffic information" refers to dynamic data about current road conditions.

[0013] "Weather information" refers to data about current and predicted weather conditions.

[0014] "Acquisition methods" refer to the means of collecting real-time traffic and weather information, and analyzing and updating it based on that information.

[0015] "Presentation method" refers to a means of providing users with a list of recommended destinations through visual or audio guidance.

[0016] A "route guidance system" is a system component that calculates the optimal route to the destination selected by the user and guides the user along it. [Brief explanation of the drawing]

[0017] [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] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0018] 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.

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

[0020] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

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

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

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

[0027] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0034] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0037] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0038] This invention relates to an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and guides the user along the optimal route based on real-time traffic and weather information. The aim of this system is to make users' trips and drives more comfortable and stress-free.

[0039] System Configuration

[0040] This system includes the following main components:

[0041] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented through voice input, touch panel input, etc.

[0042] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[0043] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[0044] 4. Presentation methods: Displays and speakers that present recommended destinations and route guidance to the user visually or audibly.

[0045] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[0046] Program processing and operation

[0047] The entire system works as follows:

[0048] 1. Input and collection of user information

[0049] The device asks the user, "Hello, what do you like?" via voice or text.

[0050] The user enters "I like seafood and nature" using voice input or a touch panel.

[0051] The device sends this information to the server, which then records it in the database.

[0052] 2. Data analysis using generative AI models

[0053] The server retrieves user hobbies and preferences from a database and uses a generative AI model to generate a list of recommended destinations.

[0054] The server will add the latest information on tourist attractions, restaurants, and accommodations to this.

[0055] 3. Real-time data integration

[0056] The server collects real-time traffic and weather data from external APIs and updates the recommended destination list.

[0057] The server sends an optimized list to the terminal to avoid traffic congestion and bad weather.

[0058] 4. Presentation of the proposed plan

[0059] The terminal provides voice and screen guidance, saying, "This is AA Restaurant, where you can enjoy fresh seafood dishes, and BB Park, where you can enjoy beautiful nature."

[0060] The user selects "Let's go to AA Restaurant," and the device sends this information to the server.

[0061] 5. Destination Selection and Route Guidance

[0062] The server calculates the optimal route to the selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal.

[0063] The terminal begins giving voice and on-screen instructions saying, "Turn right and then turn left at the next traffic light."

[0064] 6. Adaptation and modification of the plan

[0065] The server monitors traffic conditions and weather changes in real time and calculates a new, optimal route as needed.

[0066] The terminal updates its instructions, saying, "We are changing to a new route. Please turn right at the next intersection."

[0067] Specific example

[0068] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection."

[0069] Thus, the system of the present invention provides a more comfortable driving and travel experience by combining personalized recommendations based on the user's hobbies and preferences with real-time traffic and weather information to provide optimal route guidance.

[0070] The following describes the processing flow.

[0071] Step 1:

[0072] The user logs into the in-vehicle system. The terminal displays a login screen, and the user enters their ID and password.

[0073] Step 2:

[0074] The device asks, "Hello, what do you like?" via voice or text. The user replies, "I like seafood and nature," using voice input or the touchscreen.

[0075] Step 3:

[0076] The terminal sends the entered hobby and preference information to the server, and the server records that information in a database.

[0077] Step 4:

[0078] The server retrieves user hobbies and preferences from a database. Using a generative AI model, it generates a list of recommended destinations based on the user's favorite genres.

[0079] Step 5:

[0080] The server retrieves the latest information on tourist attractions, restaurants, and accommodations from external APIs and integrates it into a list of recommended destinations.

[0081] Step 6:

[0082] The server collects real-time traffic and weather information from external APIs. Based on this information, it dynamically updates the list of recommended destinations.

[0083] Step 7:

[0084] The server sends a real-time optimized list of recommended destinations to the device. The device then provides voice and screen guidance, such as, "We recommend AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature."

[0085] Step 8:

[0086] The user selects "Let's go to AA Restaurant." The device sends this selection information to the server.

[0087] Step 9:

[0088] The server calculates the optimal route to the user's selected destination. It utilizes a generative AI model and real-time traffic and weather data to generate the best route.

[0089] Step 10:

[0090] The server sends the calculated optimal route to the terminal. The terminal then begins route guidance with voice and screen display instructions such as, "Turn right and then left at the next traffic light."

[0091] Step 11:

[0092] The server monitors traffic conditions and weather information in real time while the vehicle is in motion. If an anomaly is detected, it calculates a new, optimal route.

[0093] Step 12:

[0094] The server resends the updated route information to the terminal. The terminal updates its instructions, displaying "Changing to the new route. Turn right at the next intersection."

[0095] In this way, a series of processes are carried out in coordination, starting with user input, followed by server data acquisition and analysis, real-time data integration, and finally, optimal route guidance to the user.

[0096] (Example 1)

[0097] 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."

[0098] Conventional navigation systems often lack destination recommendations based on individual user preferences and dynamic route updates based on real-time traffic and weather information. Furthermore, their voice input and output interfaces are often inadequate, resulting in a limited user experience. A system is needed to address these challenges.

[0099] 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.

[0100] In this invention, the server includes input means for inputting user interest information; analysis means for generating recommended destinations based on the interest information using a generation AI model; acquisition means for collecting real-time road and weather information and dynamically updating the list of recommended destinations; presentation means for presenting the list of recommended destinations to the user via display and voice guidance; route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance; and means for updating the route guidance in real time based on road and weather information during travel. This enables destination recommendations based on individual hobbies and preferences, and dynamic route updates based on real-time traffic conditions and weather information.

[0101] An "input device" is a device or interface for users to input information about their interests and preferences.

[0102] "Analysis means" refers to a device or system that uses a generative AI model to generate recommended destinations based on input interest and preference information.

[0103] "Acquisition method" refers to a device or system that collects real-time road and weather information and dynamically updates a list of recommended destinations based on that information.

[0104] A "presentation means" refers to a device or interface for presenting a list of recommended destinations to a user visually and audibly.

[0105] A "route guidance system" is a device or system that calculates the optimal route to a destination selected by the user and guides them along that route.

[0106] "Means of updating in real time" refers to devices or systems that constantly monitor traffic conditions and weather information while the user is in transit, and correct and update route guidance accordingly.

[0107] A "generative AI model" is an artificial intelligence model that generates specific destinations or recommendation lists based on user input information.

[0108] A "prompt statement" is an instruction statement used to provide specific input to a generative AI model, and is text used to guide the model's output.

[0109] This invention is a system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and further guides users along the optimal route based on real-time road and weather information. The aim of this system is to make users' travel and driving more comfortable and stress-free.

[0110] System Configuration

[0111] This system includes the following main components:

[0112] 1. Input Method: This is an interface for users to input information about their interests and preferences. This can be implemented using voice input or touch panel input. Specifically, Google APIs can be used as voice recognition technology.

[0113] 2. Analysis Method: This is an engine that uses a generative AI model to generate recommended destinations based on the user's interests and preferences. For example, OpenAI's GPT-4 is used as this generative AI model.

[0114] 3. Acquisition Method: This module collects road and weather information in real time and provides that information to the analysis tool. Specifically, it can utilize the Google Maps API or the OpenWeatherMap API.

[0115] 4. Presentation methods: A display and speaker that visually or audibly present recommended destinations and route guidance to the user. A touch panel type display will be used, and speech synthesis technology will be used for voice guidance.

[0116] 5. Route guidance system: This is a navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time. The Google Maps API can be used for this purpose.

[0117] 6. Means of updating in real time: This system constantly monitors traffic conditions and weather information during travel and corrects and updates route guidance as needed.

[0118] Operation description

[0119] Input and collection of user information

[0120] When the device starts up, it asks the user aloud, "Hello, what do you like?" The user answers aloud, "I like seafood and nature," and the device uses speech recognition technology (e.g., Google API) to convert this information into text. The converted text is sent to the server and recorded in the database.

[0121] Data analysis using generative AI models

[0122] The server retrieves user hobbies and preferences from the database and inputs a prompt message into a generative AI model (for example, OpenAI's GPT-4): "I like seafood and am looking for tourist spots where I can enjoy nature. Please recommend some places." The generative AI model generates a list of recommended tourist spots and restaurants and adds the latest information on tourist spots and restaurants to this list.

[0123] Real-time data integration

[0124] The server calls a traffic information API (e.g., Google Maps API) and a weather information API (e.g., OpenWeatherMap API) to retrieve data. Based on this information, the server re-evaluates the recommendation list and sends the optimal list to the device.

[0125] Presentation of proposal

[0126] The terminal suggests to the user via voice and display, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." The user selects "AA Restaurant," and the terminal sends this information to the server.

[0127] Destination selection and route guidance

[0128] The server calculates the optimal route to the selected destination and sends the navigation data to the terminal. The terminal then begins providing directions via voice and display, such as "Turn right and then left at the next traffic light."

[0129] Adaptation and modification of the plan

[0130] While the user is in transit, the server periodically calls traffic information APIs and weather information APIs to obtain the latest conditions. In case of traffic congestion or bad weather, the server calculates a new optimal route, and the terminal notifies the user via voice and display with a message such as, "We are changing to a new route. Please turn right at the next intersection."

[0131] Explanation of specific examples

[0132] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection."

[0133] As described above, the system of the present invention provides a more comfortable driving and travel experience by combining personalized recommendations based on the user's interests with optimal route guidance based on real-time road and weather information.

[0134] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0135] Step 1: Enter and collect user information

[0136] When the device starts up, it will ask the user a voice message saying, "Hello, what do you like?"

[0137] Input: Voice message from the device: "Hello, what do you like?"

[0138] Output: User voice input "I like seafood and nature"

[0139] Specific operation: The user responds verbally with "I like seafood and nature." The device uses speech recognition technology (e.g., Google API) to convert the speech to text. The converted text is sent to the server and recorded in the database.

[0140] Step 2: Data analysis using generative AI models

[0141] The server retrieves user hobbies and preferences information from the database.

[0142] Input: User's hobby and preference information retrieved from the database: "Likes seafood and nature"

[0143] Output: Prompt message: "I like seafood and I'm looking for tourist spots where I can enjoy nature. Please recommend some places."

[0144] Specific operation: The server inputs prompt text into the generating AI model (e.g., OpenAI's GPT-4). The generating AI model generates a list of recommended tourist spots and restaurants. The server then references the latest information on tourist spots and restaurants and updates the list.

[0145] Step 3: Integrate real-time data

[0146] The server collects real-time road and weather information from external APIs.

[0147] Input: Real-time road and weather information collected from external APIs (Google Maps API, OpenWeatherMap API)

[0148] Output: Optimized recommended destination list

[0149] Specific operation: Based on traffic congestion and weather information acquired by the server, the list generated by the generation AI model is re-evaluated. The server optimizes the recommended list and sends the updated list to the terminal.

[0150] Step 4: Presentation of Proposal

[0151] The device displays recommended destinations and route guidance to the user visually and audibly.

[0152] Input: Optimized recommended destination list received from the server

[0153] Output: Suggestion to the user: "AA Restaurant offers fresh seafood dishes, and BB Park allows you to enjoy beautiful nature."

[0154] Specific operation: The terminal announces via voice, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." Detailed information is displayed on the screen. The user touches the screen to select "AA Restaurant." The terminal sends the selection information to the server.

[0155] Step 5: Destination selection and route guidance

[0156] The server calculates the optimal route to the selected destination based on an AI model and real-time data.

[0157] Input: User-selected destination "AA Restaurant"

[0158] Output: Navigation data based on the optimal route

[0159] Specific operation: The server calculates the optimal route to the user-selected "AA Restaurant" using an AI model and traffic and weather data. The calculation result is sent to the terminal. The terminal begins providing voice and display instructions such as "Turn right and then left at the next traffic light."

[0160] Step 6: Adapting and modifying the plan

[0161] The server monitors traffic conditions and weather in real time and calculates the optimal new route.

[0162] Input: Real-time collection of up-to-date traffic and weather information.

[0163] Output: Navigation data based on the updated optimal route

[0164] Specific operation: While the user is in transit, the server periodically calls the traffic information API and weather information API to obtain the latest conditions. In the event of traffic congestion or bad weather, the server calculates a new optimal route, and the terminal notifies the user via voice and display with a message such as, "We are changing to a new route. Please turn right at the next intersection."

[0165] (Application Example 1)

[0166] 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."

[0167] Current in-car systems offer limited services for personalizing users' trips and drives. Furthermore, the optimization of travel plans based on real-time traffic and weather information is insufficient, meaning they cannot fully meet the needs of individual users. This makes it difficult for users to enjoy stress-free and comfortable trips and drives.

[0168] 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.

[0169] In this invention, the server includes input means for inputting the user's hobbies and preferences; analysis means for generating recommended destinations based on the hobbies and preferences using a generation AI model; acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations; presentation means for presenting the list of recommended destinations to the user through display and voice guidance; route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance; and device linkage means for managing and displaying recommended destinations and guidance information on an interface using a smart device. This enables the optimization of personalized travel plans based on the user's hobbies and preferences in conjunction with real-time traffic and weather information, resulting in a comfortable and stress-free travel and driving experience.

[0170] An "input method" is an interface for users to input information about their hobbies and preferences.

[0171] A "generative AI model" is an artificial intelligence analysis engine that generates recommended destinations based on the user's interests and preferences.

[0172] The "analysis method" refers to a function that uses a generative AI model to analyze and generate recommended destinations based on the user's interests and preferences.

[0173] The "acquisition method" refers to a module that collects real-time traffic and weather information and dynamically updates the list of recommended destinations.

[0174] "Presentation means" refers to a function including a display and speaker for presenting a list of recommended destinations to the user through display and audio guidance.

[0175] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides route guidance.

[0176] "Device linking means" refers to a function that uses smart devices to manage and display recommended destinations and guidance information on an interface.

[0177] "Smart devices" refer to interactive devices such as smartphones, smart glasses, or head-mounted displays.

[0178] This invention is a system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and guides them along the optimal route based on real-time traffic and weather information. The aim of this system is to make users' trips and drives more comfortable and stress-free.

[0179] System Configuration

[0180] This system includes the following main components:

[0181] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented through voice input, touch panel input, etc.

[0182] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[0183] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and dynamically updates the list of recommended destinations.

[0184] 4. Presentation methods: Displays and speakers that present recommended destinations and route guidance to the user visually or audibly.

[0185] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[0186] 6. Device integration means: A function for managing and displaying recommended destinations and guidance information on the interface using a smart device.

[0187] Operation and processing

[0188] Input and collection of user information

[0189] The server asks the user, "Hello, what do you like?" via voice or text. The user then inputs their hobbies and preferences via voice input or a touch panel. For example, if the user inputs "I like seafood and nature," that information is sent to the server and recorded in the database.

[0190] Data analysis using generative AI models

[0191] The server retrieves user preferences from a database and uses a generative AI model to generate a list of recommended destinations. For example, using OpenAI's GPT-3, it takes the prompt "User preferences: Likes seafood and nature. What are some recommended tourist spots, restaurants, and accommodations?" and recommends tourist spots and restaurants that match the user's preferences. This recommendation information is integrated with the latest information on tourist spots, restaurants, and accommodations.

[0192] Real-time data integration

[0193] The server uses external APIs to collect real-time traffic and weather data, and updates the recommended destination list based on that information. The recommendation list is optimized to avoid traffic congestion and bad weather, and the updated information is sent to the device.

[0194] Presentation of proposal

[0195] The terminal provides voice and screen guidance, saying, "AA Restaurant offers fresh seafood dishes, and BB Park is a place where you can enjoy beautiful nature." When the user selects "Let's go to AA Restaurant," that information is sent to the server.

[0196] Destination selection and route guidance

[0197] The server calculates the optimal route to the selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal. The terminal then begins providing directions via voice and on-screen display, such as "Turn right and then left at the next traffic light."

[0198] Adaptation and modification of the plan

[0199] The server monitors traffic conditions and weather in real time and calculates a new, optimal route as needed. The terminal updates its instructions with a message such as, "Changing to a new route. Turn right at the next intersection."

[0200] Specific example

[0201] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." The server then generates a recommendation list, integrates it with updated traffic and weather data, and sends it to the terminal. The terminal then advises, "AA Restaurant is a recommended seafood restaurant, and BB Park is a great spot to enjoy nature." Once the user makes their selection, the optimal route is calculated and navigation begins immediately.

[0202] Thus, the system of the present invention can provide a more comfortable driving and travel experience by combining personalized recommendations based on the user's hobbies and preferences with real-time traffic and weather information to provide optimal route guidance.

[0203] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0204] Step 1:

[0205] The server asks the user via voice or text, "Hello, what do you like?" The user inputs their hobbies and preferences, such as "I like seafood and nature," via voice input or touch panel. The terminal sends this information to the server, which records it in a database. The input here is the user's hobbies and preferences, and the output is the recorded hobbies and preferences. This information is used for analysis.

[0206] Step 2:

[0207] The server retrieves user preferences and interests from a database. Then, using a generative AI model (e.g., OpenAI's GPT-3), it takes the prompt "User preferences: Likes seafood and nature. What are some recommended tourist spots, restaurants, and accommodations?" as input and generates a list of recommended destinations. This analysis outputs a list of tourist spots and restaurants that are suitable for the user's preferences.

[0208] Step 3:

[0209] The server uses an external API to collect real-time traffic and weather data. The collected data is reflected in an existing list of recommended destinations and is dynamically updated. The input here is traffic and weather information, and the output is the updated list of recommended destinations.

[0210] Step 4:

[0211] The terminal receives an updated list of recommended destinations and guides the user via voice and on-screen messages, saying, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." If the user selects "Let's go to AA Restaurant," this information is sent to the server. The input here is the user's destination selection information, and the output is the transmission of destination selection information to the server.

[0212] Step 5:

[0213] The server uses a generated AI model and real-time data to calculate the optimal route to the selected destination. The calculated optimal route is sent to the terminal as navigation data. The terminal then begins providing guidance via voice and on-screen display, such as "Turn right and then left at the next traffic light." The input here is destination selection information and real-time data, and the output is the optimal route guidance.

[0214] Step 6:

[0215] The server monitors traffic conditions and weather in real time and calculates a new, optimal route as needed. The terminal updates its directions with a message such as, "Changing to a new route. Turn right at the next intersection." The input here is the latest traffic and weather information, and the output is the updated route guidance.

[0216] 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.

[0217] This invention relates to an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's hobbies, preferences, and emotional state, and guides the user along the optimal route based on real-time traffic and weather information. Furthermore, this invention aims to combine an emotion engine to recognize the user's emotions and dynamically adjust the suggested content and guidance methods.

[0218] System Configuration

[0219] This system includes the following main components:

[0220] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented using voice input, touch panel input, etc.

[0221] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[0222] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[0223] 4. Presentation methods: Displays and speakers for presenting recommended destinations and route guidance to users visually or audibly.

[0224] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[0225] 6. Emotion Engine: An engine that recognizes emotions from the user's voice and actions, and dynamically adjusts the suggested content and guidance methods based on those emotions.

[0226] Program processing and operation

[0227] The entire system works as follows:

[0228] 1. Input and collection of user information

[0229] The device asks the user, "Hello, what do you like?" via voice or text.

[0230] The user enters "I like seafood and nature" via voice input or touch panel.

[0231] The device sends this information to the server, which then records it in the database.

[0232] 2. Data analysis using generative AI models

[0233] The server retrieves user hobbies and preferences from a database and uses a generative AI model to generate a list of recommended destinations.

[0234] The server will add the latest information on tourist attractions, restaurants, and accommodations to this.

[0235] 3. Real-time data integration

[0236] The server collects real-time traffic and weather data from external APIs and updates the recommended destination list.

[0237] The server sends an optimized list to the terminal to avoid traffic congestion and bad weather.

[0238] 4. Presentation of the proposed plan

[0239] The terminal provides voice and screen guidance, saying, "This is AA Restaurant, where you can enjoy fresh seafood dishes, and BB Park, where you can enjoy beautiful nature."

[0240] The user selects "Let's go to AA Restaurant," and the device sends this information to the server.

[0241] 5. Destination Selection and Route Guidance

[0242] The server calculates the optimal route to the user's selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal.

[0243] The terminal begins providing route guidance via voice and on-screen display, saying, "Turn right and then turn left at the next traffic light."

[0244] 6. Emotion Recognition and Optimization of Suggestions and Guidance

[0245] The emotion engine recognizes the user's emotional state from their voice and facial expressions.

[0246] The server uses sentiment information obtained from the sentiment engine to dynamically adjust the content of recommendation lists and route guidance.

[0247] For example, if a user is tired, the server will adjust its recommendations to suggest more relaxing destinations. Conversely, if a user is excited, the server will recommend exciting activities.

[0248] 7. Adaptation and modification of the plan

[0249] The server monitors traffic conditions and weather changes in real time and calculates a new, optimal route as needed.

[0250] The terminal updates its instructions, saying, "We are changing to a new route. Please turn right at the next intersection."

[0251] Specific example

[0252] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection." Furthermore, if the user appears tired, the emotion engine adjusts the system to suggest a relaxing next destination.

[0253] Thus, the system of the present invention provides a more comfortable and efficient driving and travel experience by combining personalized recommendations based on the user's hobbies, preferences, and emotional state with real-time traffic and weather information to provide optimal route guidance.

[0254] The following describes the processing flow.

[0255] Step 1:

[0256] The device asks the user, either by voice or text, "Hello, what do you like?"

[0257] Step 2:

[0258] The user enters "I like seafood and nature" via voice input or touch panel.

[0259] Step 3:

[0260] The terminal sends the entered hobby and preference information to the server, and the server records that information in a database.

[0261] Step 4:

[0262] The server retrieves user hobbies and preferences from a database. Using a generative AI model, it generates a list of recommended destinations based on the user's preferred genres.

[0263] Step 5:

[0264] The server retrieves the latest information on tourist attractions, restaurants, and accommodations from external APIs and integrates it into a list of recommended destinations.

[0265] Step 6:

[0266] The server collects real-time traffic and weather information from external APIs. Based on this information, it dynamically updates the list of recommended destinations.

[0267] Step 7:

[0268] The server sends a real-time optimized list of recommended destinations to the device. The device then provides voice and screen guidance, such as, "We recommend AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature."

[0269] Step 8:

[0270] The user selects "Let's go to AA Restaurant." The device sends this selection information to the server.

[0271] Step 9:

[0272] The server calculates the optimal route to the user's selected destination. It utilizes a generative AI model and real-time traffic and weather data to generate the best route.

[0273] Step 10:

[0274] The server sends the calculated optimal route to the terminal. The terminal then begins route guidance with voice and screen display instructions such as, "Turn right and then left at the next traffic light."

[0275] Step 11:

[0276] While the device is in motion, it analyzes the user's voice and behavior in real time, and an emotion engine recognizes those emotions. For example, if the user appears tired, the device sends that emotion data to the server.

[0277] Step 12:

[0278] The server uses emotion data obtained from the emotion engine to dynamically adjust recommendation lists and route guidance. For example, if the user is tired, it prioritizes relaxing destinations.

[0279] Step 13:

[0280] The server sends the updated recommendation list to the terminal based on the emotion data. The terminal proposes, "Dear user, you seem tired. How about the BB Cafe where you can relax?"

[0281] Step 14:

[0282] The server monitors the traffic situation and weather information in real time during movement. When an abnormality is detected, a new optimal route is calculated.

[0283] Step 15:

[0284] The server sends the updated route information to the terminal again. The terminal updates the guidance with, "Change to the new route. Turn right at the next intersection."

[0285] In this way, the system of the present invention combines personalized recommendations based on the user's hobbies and emotional state with real-time traffic and weather information, and provides optimal route guidance, thereby realizing a comfortable and efficient driving and travel experience for the user.

[0286] (Example 2)

[0287] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0288] The current in-vehicle system has limitations in recommending destinations and route guidance considering the user's hobbies and real-time traffic information and weather information. In addition, there are few systems that have the function of dynamically adjusting the proposed content and guidance method based on the user's emotional state, and the technology for providing a more individualized and comfortable driving experience is lacking, which is an issue.

[0289] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting the user's hobbies and preferences information, an analysis means for generating recommended destinations based on the hobbies and preferences information using a generation AI model, an acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations, a presentation means for presenting the list of recommended destinations to the user through display and voice guidance, a route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance, and an emotion recognition means for recognizing the user's emotional state and dynamically adjusting the suggested content and guidance method based on it. This makes it possible to provide optimal route guidance by combining personalized recommendations based on the user's hobbies and preferences and emotional state with real-time traffic and weather information.

[0290] "Input method" refers to an interface for users to input information about their hobbies and preferences, and includes methods such as voice input and touch panel input.

[0291] A "generative AI model" is an artificial intelligence model that generates recommended destinations based on the user's interests and preferences.

[0292] "Analysis means" refers to a means of generating recommended destinations based on hobby and preference information using a generative AI model.

[0293] "Acquisition method" refers to a method for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations.

[0294] "Presentation means" refers to means such as displays and speakers for presenting a list of recommended destinations to the user visually or audibly.

[0295] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides real-time route guidance.

[0296] An "emotion recognition means" is a method for recognizing a user's emotional state from their voice and facial expressions, and dynamically adjusting the suggested content and guidance methods based on that recognition.

[0297] This invention is an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's hobbies, preferences, and emotional state, and guides the user along the optimal route based on real-time traffic and weather information. Furthermore, this invention aims to incorporate an emotion engine to recognize the user's emotions and dynamically adjust the suggested content and guidance methods.

[0298] System Configuration

[0299] The system consists of the following main components:

[0300] 1. Input Method: This is an interface for users to input information about their hobbies and preferences. This includes voice input and touch panel input. In the case of voice input, speech recognition software (e.g., Google Speech-to-Text) is used.

[0301] 2. Generative AI Models: These are artificial intelligence models used to generate recommended destinations based on the user's interests and preferences. Natural language processing models such as BERT and GPT are used as generative AI models.

[0302] 3. Data Acquisition Method: This module collects real-time traffic and weather information. It utilizes the Google Maps API and the OpenWeatherMap API.

[0303] 4. Presentation means: A display and speaker for presenting recommended destinations and route guidance to the user visually or audibly. Speech synthesis software (e.g., TTS engine) is used for audio output.

[0304] 5. Route guidance means: A navigation system that calculates the optimal route to the destination selected by the user and provides real-time route guidance. Dijkstra or A algorithms are used as the route calculation algorithms.

[0305] 6. Emotion recognition means: An engine that collects the user's voice and facial expressions through a camera and microphone and recognizes the emotional state. A face emotion analysis tool (e.g., Affectiva) is used.

[0306] Specific example

[0307] The user gets into the car and logs in to the system. The terminal asks, "Hello, what do you like?" When the user inputs "I like seafood cuisine and nature" by voice, the voice recognition software converts this into text, and the terminal sends this information to the server. The server retrieves the user's hobby and preference information from the database and generates a list of recommended destinations using the generated AI model. The prompt sentence used is, "Based on the information that the user likes AA, please propose appropriate tourist spots."

[0308] Based on the real-time traffic information and weather data collected by the server, the server updates the list of recommended destinations and sends this to the terminal. The terminal proposes, "AA Restaurant where you can enjoy fresh seafood cuisine and BB Park where you can fully enjoy beautiful nature." If the user selects "AA Restaurant", the server calculates the optimal route and sends the navigation data to the terminal. The terminal starts the guidance with, "Please turn right and then turn left at the next signal."

[0309] If a traffic jam occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance with, "Change to a new route. Please turn right at the next intersection." Further, if the emotion engine senses the user's fatigue, the server adjusts to propose more relaxing destinations.

[0310] Thus, this invention combines real-time data and emotion recognition capabilities to provide optimal recommendations and route guidance tailored to the user's hobbies, preferences, and emotional state. This enables a more comfortable and efficient driving and travel experience.

[0311] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0312] Step 1:

[0313] User input of hobby and preference information

[0314] 1. The device asks the user, "Hello, what do you like?" via voice or text.

[0315] 2. The user responds with "I like seafood and nature." This input is done via voice input or touch panel operation.

[0316] 3. In the case of voice input, speech recognition software (e.g., Google Speech-to-Text) converts the speech into text data.

[0317] Input: User voice or text input

[0318] Output: Text-formatted information on hobbies and interests (e.g., "I like seafood and nature")

[0319] Operation: The device invokes speech recognition software and converts the recognition result into text.

[0320] Step 2:

[0321] Sending hobby and preference information to the server

[0322] 1. The device sends the acquired hobby and preference information to the server. Specifically, it transfers the information to the server using an HTTP request.

[0323] Input: Text-based information about hobbies and interests (e.g., "I like seafood and nature")

[0324] Output: Hobby and preference information stored in a database on the server.

[0325] Operation: The device creates an HTTP request and sends data to the server's API endpoint.

[0326] Step 3:

[0327] Generating recommended candidates using generative AI models

[0328] 1. The server retrieves hobby and preference information from the database.

[0329] 2. The server uses a generation AI model to generate a list of recommended candidates based on the user's interests and preferences. Specifically, the prompt "Based on the information that the user likes AA, please suggest appropriate tourist spots" is input to the generation AI model.

[0330] Input: Information on hobbies and preferences stored in a database on the server.

[0331] Output: List of recommended options (e.g., seafood restaurants and natural spots)

[0332] Operation: The server calls the generated AI model, takes prompts, and extracts recommended candidates.

[0333] Step 4:

[0334] Real-time data collection and list updates

[0335] 1. The server calls external APIs (e.g., Google Maps API, OpenWeatherMap API) to obtain real-time traffic and weather information.

[0336] 2. The recommended candidate list is filtered and optimized based on real-time data collected by the server.

[0337] Input: List of recommended candidates, and real-time traffic and weather information.

[0338] Output: Updated list of recommended candidates

[0339] Operation: The server sends an HTTP request to an external API, retrieves data, and updates the list of recommended candidates.

[0340] Step 5:

[0341] Sending and displaying recommended candidates to devices

[0342] 1. The server sends the updated list of recommended candidates to the terminal.

[0343] 2. The device presents the user with a list of recommended options via voice and on-screen display. For example, it might say, "AA Restaurant is a recommended seafood restaurant, and BB Park is a great spot to enjoy nature."

[0344] Input: Updated list of recommended candidates

[0345] Output: Recommended suggestions presented to the user (audio and on-screen display)

[0346] Operation: The server sends data to the terminal as an HTTP response, and the terminal presents the information using speech synthesis software and a display.

[0347] Step 6:

[0348] User-selected destination

[0349] 1. The user selects "Let's go to AA Restaurant" via their device.

[0350] 2. The terminal sends the selection information to the server.

[0351] Input: User selects destination (voice or touch operation)

[0352] Output: Selected destination information (sent to the server)

[0353] Operation: The user makes a selection on the device, and the device sends the data to the server.

[0354] Step 7:

[0355] Calculates the optimal route to the selected destination.

[0356] 1. The server calculates the optimal route based on the selected destination information, using a generated AI model and real-time data.

[0357] 2. Send navigation data to the device.

[0358] Input: Selected destination information, and real-time traffic and weather information.

[0359] Output: Navigation data (sent from server to terminal)

[0360] Operation: The server generates the optimal route using a route calculation algorithm and sends the data to the terminal.

[0361] Step 8:

[0362] Start of route guidance

[0363] 1. The device will begin providing route guidance via voice and on screen, saying, "Turn right and then turn left at the next traffic light."

[0364] Input: Navigation data

[0365] Output: Audio and screen display of route guidance.

[0366] Operation: The terminal starts providing guidance using speech synthesis software and the display based on the navigation data.

[0367] Step 9:

[0368] Responding to real-time changes in the situation

[0369] 1. The server monitors traffic conditions and weather changes in real time.

[0370] 2. Calculate a new optimal route as needed and notify the device.

[0371] 3. The terminal updates its instructions to "Changing to a new route. Turn right at the next intersection."

[0372] Input: Real-time traffic and weather information

[0373] Output: Updated navigation data and new route guidance.

[0374] Operation: The server recalculates the new optimal route based on real-time data and notifies the terminal. The terminal displays the new directions via voice and display.

[0375] Step 10:

[0376] Proposal adjustment based on emotion recognition

[0377] 1. The emotion engine recognizes the user's emotional state from their voice and facial expressions.

[0378] 2. The server adjusts recommendation lists and route guidance based on sentiment information.

[0379] 3. For example, if the user is tired, the server will suggest many relaxing destinations.

[0380] Input: User's voice and facial expression data

[0381] Output: Sentiment-based recommendation list and guidance content

[0382] Operation: The emotion engine performs sentiment analysis and sends the results to the server. The server updates the recommendations.

[0383] (Application Example 2)

[0384] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0385] While conventional in-car systems offer recommendation features based on user preferences, they lack dynamic adjustments based on emotional states. Furthermore, although they provide optimal route guidance based on real-time information, they do not update suggestions in response to changes in the user's emotions, resulting in a low degree of personalization for individual users. This leads to an insufficient user experience, particularly during long drives or trips, which reduces satisfaction.

[0386] In Application Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for inputting the user's hobby and preference information, an analysis means for generating recommended destinations based on the hobby and preference information using a generation AI model, an acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations, a presentation means for presenting the list of recommended destinations to the user through display and voice guidance, a route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance, and an emotion analysis means for recognizing the user's emotional state and dynamically adjusting the suggested content and guidance method. This enables the provision of dynamic recommendations and guidance based on the user's hobby and preference and emotional state, and enables optimal route guidance in real time.

[0387] "Input method" refers to an interface for inputting information about the user's hobbies, preferences, and emotional state, and includes voice input and touch panel input.

[0388] A "generative AI model" is an analytical engine that calculates recommended destinations based on the user's interests and preferences.

[0389] The "analysis tool" is a module that uses a generative AI model to generate recommended destinations based on the user's interests and preferences.

[0390] The "acquisition method" refers to a data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[0391] "Presentation means" refers to displays and speakers used to present recommended destinations and route guidance to users visually or through audio guidance.

[0392] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[0393] An "emotion analysis tool" is an engine that recognizes the user's emotional state from their voice and facial expressions, and dynamically adjusts the suggested content and guidance methods based on that recognition.

[0394] "Smart glasses" are wearable devices that have a display function and provide information by connecting to the internet or other devices.

[0395] "Voice guidance" is a function that provides information and instructions to users using voice output.

[0396] This system recommends tourist attractions, restaurants, and accommodations based on the user's interests, preferences, and emotional state, and guides them along the optimal route based on real-time traffic and weather information. Specific implementation details are described below.

[0397] Hardware and software to be used

[0398] Hardware:

[0399] Smart glasses: Used as both a display and a voice input device.

[0400] Smartphones: Used as auxiliary interfaces and data processing devices.

[0401] Server: Analyzes data centrally and runs the generated AI model.

[0402] software:

[0403] Generative AI model: Uses natural language processing engines such as OpenAI GPT-3.

[0404] Speech recognition module: Uses the Google Speech-to-Text API.

[0405] Traffic Information API: Uses an external API (e.g., Traffic API) to obtain traffic information.

[0406] Weather Information API: Uses an external API (e.g., OpenWeather API) to obtain the latest weather information.

[0407] The main components of the system and their operation

[0408] 1. Input method:

[0409] This is an interface for users to input information about their hobbies and preferences. Using a voice recognition module, smart glasses and smartphones accept voice input from the user.

[0410] For example, a user wears smart glasses and voice-inputs, "I like historical places and delicious food."

[0411] 2. Generative AI Models:

[0412] The server uses OpenAI GPT-3 to analyze the user's interests and preferences and generate recommended destinations.

[0413] Example of a generated prompt: "The user is interested in historical places and delicious food. What are some recommended tourist spots and restaurants?"

[0414] 3. Acquisition method:

[0415] The server collects traffic and weather information in real time and dynamically updates the list of recommended destinations.

[0416] Traffic information is obtained using the Traffic API, and weather information is obtained using the OpenWeather API.

[0417] 4. Means of presentation:

[0418] The server displays a list of recommended destinations to the user via the smart glasses' display and audio output.

[0419] For example, it might display "Recommended spots: BB Park, □□ Temple" and also provide audio guidance.

[0420] 5. Means of route guidance:

[0421] The server calculates the optimal route to the destination selected by the user and provides navigation information, updating it in real time.

[0422] The smart glasses display "Starting route guidance to □□ Temple" and provide voice guidance such as "Turn right and then left at the next traffic light."

[0423] 6. Emotion analysis means:

[0424] The server analyzes the user's voice and facial expressions to recognize their emotional state.

[0425] For example, if a user indicates they are feeling tired, the server might recommend additional places where they can relax.

[0426] Specific example:

[0427] The user puts on smart glasses and inputs "I like nature and historical places" by voice. Based on this information, the server uses a generated AI model to analyze "recommended tourist spots and restaurants" and presents a list of "BB Park" and "□□ Temple". The user then selects "I want to go to □□ Temple", the server calculates the optimal route, and the smart glasses begin providing directions. The system also analyzes the user's emotional state and, if the user is tired, suggests additional relaxing places such as "□□ Cafe".

[0428] In this way, the system can provide personalized recommendations based on the user's interests, preferences, and emotional state, along with real-time optimal route guidance.

[0429] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0430] Step 1:

[0431] The device, via smart glasses and a smartphone, asks the user a voice question: "Hello, what do you like?" The user's voice response is the input. The device sends this voice data to a speech recognition module, which converts it into text.

[0432] Step 2:

[0433] The device sends the text information (user's hobbies and preferences) converted by speech recognition to the server. The input is the user's hobbies and preferences in text form. The server receives this information and records it in its database.

[0434] Step 3:

[0435] The server uses a generation AI model to generate a list of recommended destinations based on the received hobby and preference information. The input is the user's hobby and preference information. The server creates a prompt, calls the generation AI model, and generates a list of recommended destinations. The generated list of recommended destinations is retrieved and stored for early response display.

[0436] Step 4:

[0437] The server uses an external API to obtain real-time traffic and weather information. The input is an API request for traffic and weather data. The server retrieves this information and integrates it with a generated list of recommended destinations. The output is an updated list of recommended destinations.

[0438] Step 5:

[0439] The server sends an updated list of recommended destinations to the device. The updated list of recommended destinations is the input. The device receives this list and presents it to the user via the smart glasses' display and audio output. For example, it displays and provides audio guidance such as, "Recommended spots are BB Park and □□ Temple."

[0440] Step 6:

[0441] The user selects their desired destination from a presented list. The user's selection serves as input. The terminal records this selection and sends it to the server.

[0442] Step 7:

[0443] The server calculates the optimal route to the user's selected destination. The inputs are the selected destination and real-time traffic and weather information. The server uses a generative AI model to calculate the optimal route. The output is the optimal route.

[0444] Step 8:

[0445] The server sends the optimal route to the terminal. The terminal displays "Starting route guidance to □□ Temple" on its smart glasses and provides voice guidance such as "Turn right and then left at the next traffic light." Route data is also distributed to the relevant in-vehicle system, and navigation begins.

[0446] Step 9:

[0447] The server recognizes and analyzes the user's emotional state from their voice and facial expressions. The input consists of the user's voice and facial expression data. The server uses an emotion analysis engine to analyze this data and understand the user's emotional state. The output is information about the emotional state.

[0448] Step 10:

[0449] The server dynamically adjusts suggestions and guidance methods based on the user's emotional state. The input is information about the user's emotional state. Based on this emotional state, the server, for example, if it wants to suggest a place to relax, adds "□□ Cafe" to the recommendation list and sends it to the device. The device then displays this information on smart glasses and provides voice guidance.

[0450] Step 11:

[0451] The server monitors traffic conditions and weather changes in real time and calculates a new optimal route as needed. Traffic and weather data are used as input. The server uses a generative AI model to calculate the new optimal route and sends it to the terminal. The terminal updates the display and voice guidance on smart glasses and the in-vehicle system. For example, it might say, "Changing to the new route. Turn right at the next intersection."

[0452] These specifically divided processing steps reveal the details of a system that provides dynamic recommendations and optimal route guidance based on the user's hobbies, preferences, and emotional state.

[0453] 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.

[0454] 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.

[0455] 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.

[0456] [Second Embodiment]

[0457] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0458] 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.

[0459] 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).

[0460] 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.

[0461] 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.

[0462] 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).

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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.

[0468] 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".

[0469] This invention relates to an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and guides the user along the optimal route based on real-time traffic and weather information. The aim of this system is to make users' trips and drives more comfortable and stress-free.

[0470] System Configuration

[0471] This system includes the following main components:

[0472] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented through voice input, touch panel input, etc.

[0473] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[0474] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[0475] 4. Presentation methods: Displays and speakers that present recommended destinations and route guidance to the user visually or audibly.

[0476] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[0477] Program processing and operation

[0478] The entire system works as follows:

[0479] 1. Input and collection of user information

[0480] The device asks the user, "Hello, what do you like?" via voice or text.

[0481] The user enters "I like seafood and nature" using voice input or a touch panel.

[0482] The device sends this information to the server, which then records it in the database.

[0483] 2. Data analysis using generative AI models

[0484] The server retrieves user hobbies and preferences from a database and uses a generative AI model to generate a list of recommended destinations.

[0485] The server will add the latest information on tourist attractions, restaurants, and accommodations to this.

[0486] 3. Real-time data integration

[0487] The server collects real-time traffic and weather data from external APIs and updates the recommended destination list.

[0488] The server sends an optimized list to the terminal to avoid traffic congestion and bad weather.

[0489] 4. Presentation of the proposed plan

[0490] The terminal provides voice and screen guidance, saying, "This is AA Restaurant, where you can enjoy fresh seafood dishes, and BB Park, where you can enjoy beautiful nature."

[0491] The user selects "Let's go to AA Restaurant," and the device sends this information to the server.

[0492] 5. Destination Selection and Route Guidance

[0493] The server calculates the optimal route to the selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal.

[0494] The terminal begins giving voice and on-screen instructions saying, "Turn right and then turn left at the next traffic light."

[0495] 6. Adaptation and modification of the plan

[0496] The server monitors traffic conditions and weather changes in real time and calculates a new, optimal route as needed.

[0497] The terminal updates its instructions, saying, "We are changing to a new route. Please turn right at the next intersection."

[0498] Specific example

[0499] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection."

[0500] Thus, the system of the present invention provides a more comfortable driving and travel experience by combining personalized recommendations based on the user's hobbies and preferences with real-time traffic and weather information to provide optimal route guidance.

[0501] The following describes the processing flow.

[0502] Step 1:

[0503] The user logs into the in-vehicle system. The terminal displays a login screen, and the user enters their ID and password.

[0504] Step 2:

[0505] The device asks, "Hello, what do you like?" via voice or text. The user replies, "I like seafood and nature," using voice input or the touchscreen.

[0506] Step 3:

[0507] The terminal sends the entered hobby and preference information to the server, and the server records that information in a database.

[0508] Step 4:

[0509] The server retrieves user hobbies and preferences from a database. Using a generative AI model, it generates a list of recommended destinations based on the user's favorite genres.

[0510] Step 5:

[0511] The server retrieves the latest information on tourist attractions, restaurants, and accommodations from external APIs and integrates it into a list of recommended destinations.

[0512] Step 6:

[0513] The server collects real-time traffic and weather information from external APIs. Based on this information, it dynamically updates the list of recommended destinations.

[0514] Step 7:

[0515] The server sends a real-time optimized list of recommended destinations to the device. The device then provides voice and screen guidance, such as, "We recommend AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature."

[0516] Step 8:

[0517] The user selects "Let's go to AA Restaurant." The device sends this selection information to the server.

[0518] Step 9:

[0519] The server calculates the optimal route to the user's selected destination. It utilizes a generative AI model and real-time traffic and weather data to generate the best route.

[0520] Step 10:

[0521] The server sends the calculated optimal route to the terminal. The terminal then begins route guidance with voice and screen display instructions such as, "Turn right and then left at the next traffic light."

[0522] Step 11:

[0523] The server monitors traffic conditions and weather information in real time while the vehicle is in motion. If an anomaly is detected, it calculates a new, optimal route.

[0524] Step 12:

[0525] The server resends the updated route information to the terminal. The terminal updates its instructions, displaying "Changing to the new route. Turn right at the next intersection."

[0526] In this way, a series of processes are carried out in coordination, starting with user input, followed by server data acquisition and analysis, real-time data integration, and finally, optimal route guidance to the user.

[0527] (Example 1)

[0528] 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."

[0529] Conventional navigation systems often lack destination recommendations based on individual user preferences and dynamic route updates based on real-time traffic and weather information. Furthermore, their voice input and output interfaces are often inadequate, resulting in a limited user experience. A system is needed to address these challenges.

[0530] 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.

[0531] In this invention, the server includes input means for inputting user interest information; analysis means for generating recommended destinations based on the interest information using a generation AI model; acquisition means for collecting real-time road and weather information and dynamically updating the list of recommended destinations; presentation means for presenting the list of recommended destinations to the user via display and voice guidance; route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance; and means for updating the route guidance in real time based on road and weather information during travel. This enables destination recommendations based on individual hobbies and preferences, and dynamic route updates based on real-time traffic conditions and weather information.

[0532] An "input device" is a device or interface for users to input information about their interests and preferences.

[0533] "Analysis means" refers to a device or system that uses a generative AI model to generate recommended destinations based on input interest and preference information.

[0534] "Acquisition method" refers to a device or system that collects real-time road and weather information and dynamically updates a list of recommended destinations based on that information.

[0535] A "presentation means" refers to a device or interface for presenting a list of recommended destinations to a user visually and audibly.

[0536] A "route guidance system" is a device or system that calculates the optimal route to a destination selected by the user and guides them along that route.

[0537] "Means of updating in real time" refers to devices or systems that constantly monitor traffic conditions and weather information while the user is in transit, and correct and update route guidance accordingly.

[0538] A "generative AI model" is an artificial intelligence model that generates specific destinations or recommendation lists based on user input information.

[0539] A "prompt statement" is an instruction statement used to provide specific input to a generative AI model, and is text used to guide the model's output.

[0540] This invention is a system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and further guides users along the optimal route based on real-time road and weather information. The aim of this system is to make users' travel and driving more comfortable and stress-free.

[0541] System Configuration

[0542] This system includes the following main components:

[0543] 1. Input Method: This is an interface for users to input information about their interests and preferences. This can be implemented using voice input or touch panel input. Specifically, Google APIs can be used as voice recognition technology.

[0544] 2. Analysis Method: This is an engine that uses a generative AI model to generate recommended destinations based on the user's interests and preferences. For example, OpenAI's GPT-4 is used as this generative AI model.

[0545] 3. Acquisition Method: This module collects road and weather information in real time and provides that information to the analysis tool. Specifically, it can utilize the Google Maps API or the OpenWeatherMap API.

[0546] 4. Presentation methods: A display and speaker that visually or audibly present recommended destinations and route guidance to the user. A touch panel type display will be used, and speech synthesis technology will be used for voice guidance.

[0547] 5. Route guidance system: This is a navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time. The Google Maps API can be used for this purpose.

[0548] 6. Means of updating in real time: This system constantly monitors traffic conditions and weather information during travel and corrects and updates route guidance as needed.

[0549] Operation description

[0550] Input and collection of user information

[0551] When the device starts up, it asks the user aloud, "Hello, what do you like?" The user answers aloud, "I like seafood and nature," and the device uses speech recognition technology (e.g., Google API) to convert this information into text. The converted text is sent to the server and recorded in the database.

[0552] Data analysis using generative AI models

[0553] The server retrieves user hobbies and preferences from the database and inputs a prompt message into a generative AI model (for example, OpenAI's GPT-4): "I like seafood and am looking for tourist spots where I can enjoy nature. Please recommend some places." The generative AI model generates a list of recommended tourist spots and restaurants and adds the latest information on tourist spots and restaurants to this list.

[0554] Real-time data integration

[0555] The server calls a traffic information API (e.g., Google Maps API) and a weather information API (e.g., OpenWeatherMap API) to retrieve data. Based on this information, the server re-evaluates the recommendation list and sends the optimal list to the device.

[0556] Presentation of proposal

[0557] The terminal suggests to the user via voice and display, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." The user selects "AA Restaurant," and the terminal sends this information to the server.

[0558] Destination selection and route guidance

[0559] The server calculates the optimal route to the selected destination and sends the navigation data to the terminal. The terminal then begins providing directions via voice and display, such as "Turn right and then left at the next traffic light."

[0560] Adaptation and modification of the plan

[0561] While the user is in transit, the server periodically calls traffic information APIs and weather information APIs to obtain the latest conditions. In case of traffic congestion or bad weather, the server calculates a new optimal route, and the terminal notifies the user via voice and display with a message such as, "We are changing to a new route. Please turn right at the next intersection."

[0562] Explanation of specific examples

[0563] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection."

[0564] As described above, the system of the present invention provides a more comfortable driving and travel experience by combining personalized recommendations based on the user's interests with optimal route guidance based on real-time road and weather information.

[0565] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0566] Step 1: Enter and collect user information

[0567] When the device starts up, it will ask the user a voice message saying, "Hello, what do you like?"

[0568] Input: Voice message from the device: "Hello, what do you like?"

[0569] Output: User voice input "I like seafood and nature"

[0570] Specific operation: The user responds verbally with "I like seafood and nature." The device uses speech recognition technology (e.g., Google API) to convert the speech to text. The converted text is sent to the server and recorded in the database.

[0571] Step 2: Data analysis using generative AI models

[0572] The server retrieves user hobbies and preferences information from the database.

[0573] Input: User's hobby and preference information retrieved from the database: "Likes seafood and nature"

[0574] Output: Prompt message: "I like seafood and I'm looking for tourist spots where I can enjoy nature. Please recommend some places."

[0575] Specific operation: The server inputs prompt text into the generating AI model (e.g., OpenAI's GPT-4). The generating AI model generates a list of recommended tourist spots and restaurants. The server then references the latest information on tourist spots and restaurants and updates the list.

[0576] Step 3: Integrate real-time data

[0577] The server collects real-time road and weather information from external APIs.

[0578] Input: Real-time road and weather information collected from external APIs (Google Maps API, OpenWeatherMap API)

[0579] Output: Optimized recommended destination list

[0580] Specific operation: Based on traffic congestion and weather information acquired by the server, the list generated by the generation AI model is re-evaluated. The server optimizes the recommended list and sends the updated list to the terminal.

[0581] Step 4: Presentation of Proposal

[0582] The device displays recommended destinations and route guidance to the user visually and audibly.

[0583] Input: Optimized recommended destination list received from the server

[0584] Output: Suggestion to the user: "AA Restaurant offers fresh seafood dishes, and BB Park allows you to enjoy beautiful nature."

[0585] Specific operation: The terminal announces via voice, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." Detailed information is displayed on the screen. The user touches the screen to select "AA Restaurant." The terminal sends the selection information to the server.

[0586] Step 5: Destination selection and route guidance

[0587] The server calculates the optimal route to the selected destination based on an AI model and real-time data.

[0588] Input: User-selected destination "AA Restaurant"

[0589] Output: Navigation data based on the optimal route

[0590] Specific operation: The server calculates the optimal route to the user-selected "AA Restaurant" using an AI model and traffic and weather data. The calculation result is sent to the terminal. The terminal begins providing voice and display instructions such as "Turn right and then left at the next traffic light."

[0591] Step 6: Adapting and modifying the plan

[0592] The server monitors traffic conditions and weather in real time and calculates the optimal new route.

[0593] Input: Real-time collection of up-to-date traffic and weather information.

[0594] Output: Navigation data based on the updated optimal route

[0595] Specific operation: While the user is in transit, the server periodically calls the traffic information API and weather information API to obtain the latest conditions. In the event of traffic congestion or bad weather, the server calculates a new optimal route, and the terminal notifies the user via voice and display with a message such as, "We are changing to a new route. Please turn right at the next intersection."

[0596] (Application Example 1)

[0597] 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."

[0598] Current in-car systems offer limited services for personalizing users' trips and drives. Furthermore, the optimization of travel plans based on real-time traffic and weather information is insufficient, meaning they cannot fully meet the needs of individual users. This makes it difficult for users to enjoy stress-free and comfortable trips and drives.

[0599] 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.

[0600] In this invention, the server includes input means for inputting the user's hobbies and preferences; analysis means for generating recommended destinations based on the hobbies and preferences using a generation AI model; acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations; presentation means for presenting the list of recommended destinations to the user through display and voice guidance; route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance; and device linkage means for managing and displaying recommended destinations and guidance information on an interface using a smart device. This enables the optimization of personalized travel plans based on the user's hobbies and preferences in conjunction with real-time traffic and weather information, resulting in a comfortable and stress-free travel and driving experience.

[0601] An "input method" is an interface for users to input information about their hobbies and preferences.

[0602] A "generative AI model" is an artificial intelligence analysis engine that generates recommended destinations based on the user's interests and preferences.

[0603] The "analysis method" refers to a function that uses a generative AI model to analyze and generate recommended destinations based on the user's interests and preferences.

[0604] The "acquisition method" refers to a module that collects real-time traffic and weather information and dynamically updates the list of recommended destinations.

[0605] "Presentation means" refers to a function including a display and speaker for presenting a list of recommended destinations to the user through display and audio guidance.

[0606] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides route guidance.

[0607] "Device linking means" refers to a function that uses smart devices to manage and display recommended destinations and guidance information on an interface.

[0608] "Smart devices" refer to interactive devices such as smartphones, smart glasses, or head-mounted displays.

[0609] This invention is a system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and guides them along the optimal route based on real-time traffic and weather information. The aim of this system is to make users' trips and drives more comfortable and stress-free.

[0610] System Configuration

[0611] This system includes the following main components:

[0612] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented through voice input, touch panel input, etc.

[0613] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[0614] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and dynamically updates the list of recommended destinations.

[0615] 4. Presentation methods: Displays and speakers that present recommended destinations and route guidance to the user visually or audibly.

[0616] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[0617] 6. Device integration means: A function for managing and displaying recommended destinations and guidance information on the interface using a smart device.

[0618] Operation and processing

[0619] Input and collection of user information

[0620] The server asks the user, "Hello, what do you like?" via voice or text. The user then inputs their hobbies and preferences via voice input or a touch panel. For example, if the user inputs "I like seafood and nature," that information is sent to the server and recorded in the database.

[0621] Data analysis using generative AI models

[0622] The server retrieves user preferences from a database and uses a generative AI model to generate a list of recommended destinations. For example, using OpenAI's GPT-3, it takes the prompt "User preferences: Likes seafood and nature. What are some recommended tourist spots, restaurants, and accommodations?" and recommends tourist spots and restaurants that match the user's preferences. This recommendation information is integrated with the latest information on tourist spots, restaurants, and accommodations.

[0623] Real-time data integration

[0624] The server uses external APIs to collect real-time traffic and weather data, and updates the recommended destination list based on that information. The recommendation list is optimized to avoid traffic congestion and bad weather, and the updated information is sent to the device.

[0625] Presentation of proposal

[0626] The terminal provides voice and screen guidance, saying, "AA Restaurant offers fresh seafood dishes, and BB Park is a place where you can enjoy beautiful nature." When the user selects "Let's go to AA Restaurant," that information is sent to the server.

[0627] Destination selection and route guidance

[0628] The server calculates the optimal route to the selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal. The terminal then begins providing directions via voice and on-screen display, such as "Turn right and then left at the next traffic light."

[0629] Adaptation and modification of the plan

[0630] The server monitors traffic conditions and weather in real time and calculates a new, optimal route as needed. The terminal updates its instructions with a message such as, "Changing to a new route. Turn right at the next intersection."

[0631] Specific example

[0632] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." The server then generates a recommendation list, integrates it with updated traffic and weather data, and sends it to the terminal. The terminal then advises, "AA Restaurant is a recommended seafood restaurant, and BB Park is a great spot to enjoy nature." Once the user makes their selection, the optimal route is calculated and navigation begins immediately.

[0633] Thus, the system of the present invention can provide a more comfortable driving and travel experience by combining personalized recommendations based on the user's hobbies and preferences with real-time traffic and weather information to provide optimal route guidance.

[0634] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0635] Step 1:

[0636] The server asks the user via voice or text, "Hello, what do you like?" The user inputs their hobbies and preferences, such as "I like seafood and nature," via voice input or touch panel. The terminal sends this information to the server, which records it in a database. The input here is the user's hobbies and preferences, and the output is the recorded hobbies and preferences. This information is used for analysis.

[0637] Step 2:

[0638] The server retrieves user preferences and interests from a database. Then, using a generative AI model (e.g., OpenAI's GPT-3), it takes the prompt "User preferences: Likes seafood and nature. What are some recommended tourist spots, restaurants, and accommodations?" as input and generates a list of recommended destinations. This analysis outputs a list of tourist spots and restaurants that are suitable for the user's preferences.

[0639] Step 3:

[0640] The server uses an external API to collect real-time traffic and weather data. The collected data is reflected in an existing list of recommended destinations and is dynamically updated. The input here is traffic and weather information, and the output is the updated list of recommended destinations.

[0641] Step 4:

[0642] The terminal receives an updated list of recommended destinations and guides the user via voice and on-screen messages, saying, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." If the user selects "Let's go to AA Restaurant," this information is sent to the server. The input here is the user's destination selection information, and the output is the transmission of destination selection information to the server.

[0643] Step 5:

[0644] The server uses a generated AI model and real-time data to calculate the optimal route to the selected destination. The calculated optimal route is sent to the terminal as navigation data. The terminal then begins providing guidance via voice and on-screen display, such as "Turn right and then left at the next traffic light." The input here is destination selection information and real-time data, and the output is the optimal route guidance.

[0645] Step 6:

[0646] The server monitors traffic conditions and weather in real time and calculates a new, optimal route as needed. The terminal updates its directions with a message such as, "Changing to a new route. Turn right at the next intersection." The input here is the latest traffic and weather information, and the output is the updated route guidance.

[0647] 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.

[0648] This invention relates to an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's hobbies, preferences, and emotional state, and guides the user along the optimal route based on real-time traffic and weather information. Furthermore, this invention aims to combine an emotion engine to recognize the user's emotions and dynamically adjust the suggested content and guidance methods.

[0649] System Configuration

[0650] This system includes the following main components:

[0651] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented using voice input, touch panel input, etc.

[0652] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[0653] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[0654] 4. Presentation methods: Displays and speakers for presenting recommended destinations and route guidance to users visually or audibly.

[0655] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[0656] 6. Emotion Engine: An engine that recognizes emotions from the user's voice and actions, and dynamically adjusts the suggested content and guidance methods based on those emotions.

[0657] Program processing and operation

[0658] The entire system works as follows:

[0659] 1. Input and collection of user information

[0660] The device asks the user, "Hello, what do you like?" via voice or text.

[0661] The user enters "I like seafood and nature" via voice input or touch panel.

[0662] The device sends this information to the server, which then records it in the database.

[0663] 2. Data analysis using generative AI models

[0664] The server retrieves user hobbies and preferences from a database and uses a generative AI model to generate a list of recommended destinations.

[0665] The server will add the latest information on tourist attractions, restaurants, and accommodations to this.

[0666] 3. Real-time data integration

[0667] The server collects real-time traffic and weather data from external APIs and updates the recommended destination list.

[0668] The server sends an optimized list to the terminal to avoid traffic congestion and bad weather.

[0669] 4. Presentation of the proposed plan

[0670] The terminal provides voice and screen guidance, saying, "This is AA Restaurant, where you can enjoy fresh seafood dishes, and BB Park, where you can enjoy beautiful nature."

[0671] The user selects "Let's go to AA Restaurant," and the device sends this information to the server.

[0672] 5. Destination Selection and Route Guidance

[0673] The server calculates the optimal route to the user's selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal.

[0674] The terminal begins providing route guidance via voice and on-screen display, saying, "Turn right and then turn left at the next traffic light."

[0675] 6. Emotion Recognition and Optimization of Suggestions and Guidance

[0676] The emotion engine recognizes the user's emotional state from their voice and facial expressions.

[0677] The server uses sentiment information obtained from the sentiment engine to dynamically adjust the content of recommendation lists and route guidance.

[0678] For example, if a user is tired, the server will adjust its recommendations to suggest more relaxing destinations. Conversely, if a user is excited, the server will recommend exciting activities.

[0679] 7. Adaptation and modification of the plan

[0680] The server monitors traffic conditions and weather changes in real time and calculates a new, optimal route as needed.

[0681] The terminal updates its instructions, saying, "We are changing to a new route. Please turn right at the next intersection."

[0682] Specific example

[0683] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection." Furthermore, if the user appears tired, the emotion engine adjusts the system to suggest a relaxing next destination.

[0684] Thus, the system of the present invention provides a more comfortable and efficient driving and travel experience by combining personalized recommendations based on the user's hobbies, preferences, and emotional state with real-time traffic and weather information to provide optimal route guidance.

[0685] The following describes the processing flow.

[0686] Step 1:

[0687] The device asks the user, either by voice or text, "Hello, what do you like?"

[0688] Step 2:

[0689] The user enters "I like seafood and nature" via voice input or touch panel.

[0690] Step 3:

[0691] The terminal sends the entered hobby and preference information to the server, and the server records that information in a database.

[0692] Step 4:

[0693] The server retrieves user hobbies and preferences from a database. Using a generative AI model, it generates a list of recommended destinations based on the user's preferred genres.

[0694] Step 5:

[0695] The server retrieves the latest information on tourist attractions, restaurants, and accommodations from external APIs and integrates it into a list of recommended destinations.

[0696] Step 6:

[0697] The server collects real-time traffic and weather information from external APIs. Based on this information, it dynamically updates the list of recommended destinations.

[0698] Step 7:

[0699] The server sends a real-time optimized list of recommended destinations to the device. The device then provides voice and screen guidance, such as, "We recommend AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature."

[0700] Step 8:

[0701] The user selects "Let's go to AA Restaurant." The device sends this selection information to the server.

[0702] Step 9:

[0703] The server calculates the optimal route to the user's selected destination. It utilizes a generative AI model and real-time traffic and weather data to generate the best route.

[0704] Step 10:

[0705] The server sends the calculated optimal route to the terminal. The terminal then begins route guidance with voice and screen display instructions such as, "Turn right and then left at the next traffic light."

[0706] Step 11:

[0707] While the device is in motion, it analyzes the user's voice and behavior in real time, and an emotion engine recognizes those emotions. For example, if the user appears tired, the device sends that emotion data to the server.

[0708] Step 12:

[0709] The server uses emotion data obtained from the emotion engine to dynamically adjust recommendation lists and route guidance. For example, if the user is tired, it prioritizes relaxing destinations.

[0710] Step 13:

[0711] The server sends an updated recommendation list to the device based on sentiment data. The device then suggests, "You seem tired, user. How about relaxing at BB Cafe?"

[0712] Step 14:

[0713] The server monitors traffic conditions and weather information in real time while the vehicle is in motion. If an anomaly is detected, it calculates a new, optimal route.

[0714] Step 15:

[0715] The server resends the updated route information to the terminal. The terminal updates its instructions, displaying "Changing to the new route. Turn right at the next intersection."

[0716] Thus, the system of the present invention combines personalized recommendations based on the user's hobbies, preferences, and emotional state with real-time traffic and weather information to provide optimal route guidance, thereby realizing a comfortable and efficient driving and travel experience for the user.

[0717] (Example 2)

[0718] 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".

[0719] Current in-car systems have limitations in recommending destinations and providing route guidance that take into account the user's preferences and real-time traffic and weather information. Furthermore, few systems have the functionality to dynamically adjust suggestions and guidance methods based on the user's emotional state, and there is a lack of technology to provide a more personalized and comfortable driving experience.

[0720] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting the user's hobbies and preferences information, an analysis means for generating recommended destinations based on the hobbies and preferences information using a generation AI model, an acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations, a presentation means for presenting the list of recommended destinations to the user through display and voice guidance, a route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance, and an emotion recognition means for recognizing the user's emotional state and dynamically adjusting the suggested content and guidance method based on it. This makes it possible to provide optimal route guidance by combining personalized recommendations based on the user's hobbies and preferences and emotional state with real-time traffic and weather information.

[0721] "Input method" refers to an interface for users to input information about their hobbies and preferences, and includes methods such as voice input and touch panel input.

[0722] A "generative AI model" is an artificial intelligence model that generates recommended destinations based on the user's interests and preferences.

[0723] "Analysis means" refers to a means of generating recommended destinations based on hobby and preference information using a generative AI model.

[0724] "Acquisition method" refers to a method for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations.

[0725] "Presentation means" refers to means such as displays and speakers for presenting a list of recommended destinations to the user visually or audibly.

[0726] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides real-time route guidance.

[0727] An "emotion recognition means" is a method for recognizing a user's emotional state from their voice and facial expressions, and dynamically adjusting the suggested content and guidance methods based on that recognition.

[0728] This invention is an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's hobbies, preferences, and emotional state, and guides the user along the optimal route based on real-time traffic and weather information. Furthermore, this invention aims to incorporate an emotion engine to recognize the user's emotions and dynamically adjust the suggested content and guidance methods.

[0729] System Configuration

[0730] The system consists of the following main components:

[0731] 1. Input Method: This is an interface for users to input information about their hobbies and preferences. This includes voice input and touch panel input. In the case of voice input, speech recognition software (e.g., Google Speech-to-Text) is used.

[0732] 2. Generative AI Models: These are artificial intelligence models used to generate recommended destinations based on the user's interests and preferences. Natural language processing models such as BERT and GPT are used as generative AI models.

[0733] 3. Data Acquisition Method: This module collects real-time traffic and weather information. It utilizes the Google Maps API and the OpenWeatherMap API.

[0734] 4. Presentation means: A display and speaker for presenting recommended destinations and route guidance to the user visually or audibly. Speech synthesis software (e.g., TTS engine) is used for audio output.

[0735] 5. Route guidance system: This is a navigation system that calculates the optimal route to the destination selected by the user and provides real-time route guidance. Dijkstra's algorithm or the A algorithm are used as route calculation algorithms.

[0736] 6. Emotion Recognition Method: This is an engine that collects the user's voice and facial expressions through a camera and microphone and recognizes their emotional state. A face emotion analysis tool (e.g., Affectiva) is used.

[0737] Specific example

[0738] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" The user voice-inputs, "I like seafood and nature," and the speech recognition software converts this to text, and the terminal sends this information to the server. The server retrieves the user's hobbies and preferences from the database and generates a list of recommended destinations using a generative AI model. The prompt used is, "Based on the information that the user likes AA, please suggest appropriate tourist spots."

[0739] Based on real-time traffic and weather data collected by the server, the recommended destination list is updated and sent to the terminal. The terminal suggests, "AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature," and the user selects "AA Restaurant." The server calculates the optimal route and sends navigation data to the terminal. The terminal then begins guiding the user, saying, "Turn right and then left at the next traffic light."

[0740] If traffic congestion occurs during travel, the server calculates a new optimal route, and the terminal updates its guidance with a message such as, "Changing to a new route. Turn right at the next intersection." Furthermore, if the emotion engine detects user fatigue, the server adjusts its suggestions to include more relaxing destinations.

[0741] Thus, this invention combines real-time data and emotion recognition capabilities to provide optimal recommendations and route guidance tailored to the user's hobbies, preferences, and emotional state. This enables a more comfortable and efficient driving and travel experience.

[0742] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0743] Step 1:

[0744] User input of hobby and preference information

[0745] 1. The device asks the user, "Hello, what do you like?" via voice or text.

[0746] 2. The user responds with "I like seafood and nature." This input is done via voice input or touch panel operation.

[0747] 3. In the case of voice input, speech recognition software (e.g., Google Speech-to-Text) converts the speech into text data.

[0748] Input: User voice or text input

[0749] Output: Text-formatted information on hobbies and interests (e.g., "I like seafood and nature")

[0750] Operation: The device invokes speech recognition software and converts the recognition result into text.

[0751] Step 2:

[0752] Sending hobby and preference information to the server

[0753] 1. The device sends the acquired hobby and preference information to the server. Specifically, it transfers the information to the server using an HTTP request.

[0754] Input: Text-based information about hobbies and interests (e.g., "I like seafood and nature")

[0755] Output: Hobby and preference information stored in a database on the server.

[0756] Operation: The device creates an HTTP request and sends data to the server's API endpoint.

[0757] Step 3:

[0758] Generating recommended candidates using generative AI models

[0759] 1. The server retrieves hobby and preference information from the database.

[0760] 2. The server uses a generation AI model to generate a list of recommended candidates based on the user's interests and preferences. Specifically, the prompt "Based on the information that the user likes AA, please suggest appropriate tourist spots" is input to the generation AI model.

[0761] Input: Information on hobbies and preferences stored in a database on the server.

[0762] Output: List of recommended options (e.g., seafood restaurants and natural spots)

[0763] Operation: The server calls the generated AI model, takes prompts, and extracts recommended candidates.

[0764] Step 4:

[0765] Real-time data collection and list updates

[0766] 1. The server calls external APIs (e.g., Google Maps API, OpenWeatherMap API) to obtain real-time traffic and weather information.

[0767] 2. The recommended candidate list is filtered and optimized based on real-time data collected by the server.

[0768] Input: List of recommended candidates, and real-time traffic and weather information.

[0769] Output: Updated list of recommended candidates

[0770] Operation: The server sends an HTTP request to an external API, retrieves data, and updates the list of recommended candidates.

[0771] Step 5:

[0772] Sending and displaying recommended candidates to devices

[0773] 1. The server sends the updated list of recommended candidates to the terminal.

[0774] 2. The device presents the user with a list of recommended options via voice and on-screen display. For example, it might say, "AA Restaurant is a recommended seafood restaurant, and BB Park is a great spot to enjoy nature."

[0775] Input: Updated list of recommended candidates

[0776] Output: Recommended suggestions presented to the user (audio and on-screen display)

[0777] Operation: The server sends data to the terminal as an HTTP response, and the terminal presents the information using speech synthesis software and a display.

[0778] Step 6:

[0779] User-selected destination

[0780] 1. The user selects "Let's go to AA Restaurant" via their device.

[0781] 2. The terminal sends the selection information to the server.

[0782] Input: User selects destination (voice or touch operation)

[0783] Output: Selected destination information (sent to the server)

[0784] Operation: The user makes a selection on the device, and the device sends the data to the server.

[0785] Step 7:

[0786] Calculates the optimal route to the selected destination.

[0787] 1. The server calculates the optimal route based on the selected destination information, using a generated AI model and real-time data.

[0788] 2. Send navigation data to the device.

[0789] Input: Selected destination information, and real-time traffic and weather information.

[0790] Output: Navigation data (sent from server to terminal)

[0791] Operation: The server generates the optimal route using a route calculation algorithm and sends the data to the terminal.

[0792] Step 8:

[0793] Start of route guidance

[0794] 1. The device will begin providing route guidance via voice and on screen, saying, "Turn right and then turn left at the next traffic light."

[0795] Input: Navigation data

[0796] Output: Audio and screen display of route guidance.

[0797] Operation: The terminal starts providing guidance using speech synthesis software and the display based on the navigation data.

[0798] Step 9:

[0799] Responding to real-time changes in the situation

[0800] 1. The server monitors traffic conditions and weather changes in real time.

[0801] 2. Calculate a new optimal route as needed and notify the device.

[0802] 3. The terminal updates its instructions to "Changing to a new route. Turn right at the next intersection."

[0803] Input: Real-time traffic and weather information

[0804] Output: Updated navigation data and new route guidance.

[0805] Operation: The server recalculates the new optimal route based on real-time data and notifies the terminal. The terminal displays the new directions via voice and display.

[0806] Step 10:

[0807] Proposal adjustment based on emotion recognition

[0808] 1. The emotion engine recognizes the user's emotional state from their voice and facial expressions.

[0809] 2. The server adjusts recommendation lists and route guidance based on sentiment information.

[0810] 3. For example, if the user is tired, the server will suggest many relaxing destinations.

[0811] Input: User's voice and facial expression data

[0812] Output: Sentiment-based recommendation list and guidance content

[0813] Operation: The emotion engine performs sentiment analysis and sends the results to the server. The server updates the recommendations.

[0814] (Application Example 2)

[0815] 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."

[0816] While conventional in-car systems offer recommendation features based on user preferences, they lack dynamic adjustments based on emotional states. Furthermore, although they provide optimal route guidance based on real-time information, they do not update suggestions in response to changes in the user's emotions, resulting in a low degree of personalization for individual users. This leads to an insufficient user experience, particularly during long drives or trips, which reduces satisfaction.

[0817] In Application Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for inputting the user's hobby and preference information, an analysis means for generating recommended destinations based on the hobby and preference information using a generation AI model, an acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations, a presentation means for presenting the list of recommended destinations to the user through display and voice guidance, a route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance, and an emotion analysis means for recognizing the user's emotional state and dynamically adjusting the suggested content and guidance method. This enables the provision of dynamic recommendations and guidance based on the user's hobby and preference and emotional state, and enables optimal route guidance in real time.

[0818] "Input method" refers to an interface for inputting information about the user's hobbies, preferences, and emotional state, and includes voice input and touch panel input.

[0819] A "generative AI model" is an analytical engine that calculates recommended destinations based on the user's interests and preferences.

[0820] The "analysis tool" is a module that uses a generative AI model to generate recommended destinations based on the user's interests and preferences.

[0821] The "acquisition method" refers to a data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[0822] "Presentation means" refers to displays and speakers used to present recommended destinations and route guidance to users visually or through audio guidance.

[0823] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[0824] An "emotion analysis tool" is an engine that recognizes the user's emotional state from their voice and facial expressions, and dynamically adjusts the suggested content and guidance methods based on that recognition.

[0825] "Smart glasses" are wearable devices that have a display function and provide information by connecting to the internet or other devices.

[0826] "Voice guidance" is a function that provides information and instructions to users using voice output.

[0827] This system recommends tourist attractions, restaurants, and accommodations based on the user's interests, preferences, and emotional state, and guides users along the optimal route based on real-time traffic and weather information. Specific implementation details are described below.

[0828] Hardware and software to be used

[0829] Hardware:

[0830] Smart glasses: Used as both a display and a voice input device.

[0831] Smartphones: Used as auxiliary interfaces and data processing devices.

[0832] Server: Analyzes data centrally and runs the generated AI model.

[0833] software:

[0834] Generative AI model: Uses natural language processing engines such as OpenAI GPT-3.

[0835] Speech recognition module: Uses the Google Speech-to-Text API.

[0836] Traffic Information API: Uses an external API (e.g., Traffic API) to obtain traffic information.

[0837] Weather Information API: Uses an external API (e.g., OpenWeather API) to obtain the latest weather information.

[0838] The main components of the system and their operation

[0839] 1. Input method:

[0840] This is an interface for users to input information about their hobbies and preferences. Using a voice recognition module, smart glasses and smartphones accept voice input from the user.

[0841] For example, a user wears smart glasses and voice-inputs, "I like historical places and delicious food."

[0842] 2. Generative AI Models:

[0843] The server uses OpenAI GPT-3 to analyze the user's interests and preferences and generate recommended destinations.

[0844] Example of a generated prompt: "The user is interested in historical places and delicious food. What are some recommended tourist spots and restaurants?"

[0845] 3. Acquisition method:

[0846] The server collects traffic and weather information in real time and dynamically updates the list of recommended destinations.

[0847] Traffic information is obtained using the Traffic API, and weather information is obtained using the OpenWeather API.

[0848] 4. Means of presentation:

[0849] The server displays a list of recommended destinations to the user via the smart glasses' display and audio output.

[0850] For example, it might display "Recommended spots: BB Park, □□ Temple" and also provide audio guidance.

[0851] 5. Means of route guidance:

[0852] The server calculates the optimal route to the destination selected by the user and provides navigation information, updating it in real time.

[0853] The smart glasses display "Starting route guidance to □□ Temple" and provide voice guidance such as "Turn right and then left at the next traffic light."

[0854] 6. Emotion analysis means:

[0855] The server analyzes the user's voice and facial expressions to recognize their emotional state.

[0856] For example, if a user indicates they are feeling tired, the server might recommend additional places where they can relax.

[0857] Specific example:

[0858] The user puts on smart glasses and inputs "I like nature and historical places" by voice. Based on this information, the server uses a generated AI model to analyze "recommended tourist spots and restaurants" and presents a list of "BB Park" and "□□ Temple". The user then selects "I want to go to □□ Temple", the server calculates the optimal route, and the smart glasses begin providing directions. The system also analyzes the user's emotional state and, if the user is tired, suggests additional relaxing places such as "□□ Cafe".

[0859] In this way, the system can provide personalized recommendations based on the user's interests, preferences, and emotional state, along with real-time optimal route guidance.

[0860] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0861] Step 1:

[0862] The device, via smart glasses and a smartphone, asks the user a voice question: "Hello, what do you like?" The user's voice response is the input. The device sends this voice data to a speech recognition module, which converts it into text.

[0863] Step 2:

[0864] The device sends the text information (user's hobbies and preferences) converted by speech recognition to the server. The input is the user's hobbies and preferences in text form. The server receives this information and records it in its database.

[0865] Step 3:

[0866] The server uses a generation AI model to generate a list of recommended destinations based on the received hobby and preference information. The input is the user's hobby and preference information. The server creates a prompt, calls the generation AI model, and generates a list of recommended destinations. The generated list of recommended destinations is retrieved and stored for early response display.

[0867] Step 4:

[0868] The server uses an external API to obtain real-time traffic and weather information. The input is an API request for traffic and weather data. The server retrieves this information and integrates it with a generated list of recommended destinations. The output is an updated list of recommended destinations.

[0869] Step 5:

[0870] The server sends an updated list of recommended destinations to the device. The updated list of recommended destinations is the input. The device receives this list and presents it to the user via the smart glasses' display and audio output. For example, it displays and provides audio guidance such as, "Recommended spots are BB Park and □□ Temple."

[0871] Step 6:

[0872] The user selects their desired destination from a presented list. The user's selection serves as input. The terminal records this selection and sends it to the server.

[0873] Step 7:

[0874] The server calculates the optimal route to the user's selected destination. The inputs are the selected destination and real-time traffic and weather information. The server uses a generative AI model to calculate the optimal route. The output is the optimal route.

[0875] Step 8:

[0876] The server sends the optimal route to the terminal. The terminal displays "Starting route guidance to □□ Temple" on its smart glasses and provides voice guidance such as "Turn right and then left at the next traffic light." Route data is also distributed to the relevant in-vehicle system, and navigation begins.

[0877] Step 9:

[0878] The server recognizes and analyzes the user's emotional state from their voice and facial expressions. The input consists of the user's voice and facial expression data. The server uses an emotion analysis engine to analyze this data and understand the user's emotional state. The output is information about the emotional state.

[0879] Step 10:

[0880] The server dynamically adjusts suggestions and guidance methods based on the user's emotional state. The input is information about the user's emotional state. Based on this emotional state, the server, for example, if it wants to suggest a place to relax, adds "□□ Cafe" to the recommendation list and sends it to the device. The device then displays this information on smart glasses and provides voice guidance.

[0881] Step 11:

[0882] The server monitors traffic conditions and weather changes in real time and calculates a new optimal route as needed. Traffic and weather data are used as input. The server uses a generative AI model to calculate the new optimal route and sends it to the terminal. The terminal updates the display and voice guidance on smart glasses and the in-vehicle system. For example, it might say, "Changing to the new route. Turn right at the next intersection."

[0883] These specifically divided processing steps reveal the details of a system that provides dynamic recommendations and optimal route guidance based on the user's hobbies, preferences, and emotional state.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] [Third Embodiment]

[0888] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0889] 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.

[0890] 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).

[0891] 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.

[0892] 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.

[0893] 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).

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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".

[0900] This invention relates to an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and guides the user along the optimal route based on real-time traffic and weather information. The aim of this system is to make users' trips and drives more comfortable and stress-free.

[0901] System Configuration

[0902] This system includes the following main components:

[0903] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented through voice input, touch panel input, etc.

[0904] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[0905] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[0906] 4. Presentation methods: Displays and speakers that present recommended destinations and route guidance to the user visually or audibly.

[0907] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[0908] Program processing and operation

[0909] The entire system works as follows:

[0910] 1. Input and collection of user information

[0911] The device asks the user, "Hello, what do you like?" via voice or text.

[0912] The user enters "I like seafood and nature" using voice input or a touch panel.

[0913] The device sends this information to the server, which then records it in the database.

[0914] 2. Data analysis using generative AI models

[0915] The server retrieves user hobbies and preferences from a database and uses a generative AI model to generate a list of recommended destinations.

[0916] The server will add the latest information on tourist attractions, restaurants, and accommodations to this.

[0917] 3. Real-time data integration

[0918] The server collects real-time traffic and weather data from external APIs and updates the recommended destination list.

[0919] The server sends an optimized list to the terminal to avoid traffic congestion and bad weather.

[0920] 4. Presentation of the proposed plan

[0921] The terminal provides voice and screen guidance, saying, "This is AA Restaurant, where you can enjoy fresh seafood dishes, and BB Park, where you can enjoy beautiful nature."

[0922] The user selects "Let's go to AA Restaurant," and the device sends this information to the server.

[0923] 5. Destination Selection and Route Guidance

[0924] The server calculates the optimal route to the selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal.

[0925] The terminal begins giving voice and on-screen instructions saying, "Turn right and then turn left at the next traffic light."

[0926] 6. Adaptation and modification of the plan

[0927] The server monitors traffic conditions and weather changes in real time and calculates a new, optimal route as needed.

[0928] The terminal updates its instructions, saying, "We are changing to a new route. Please turn right at the next intersection."

[0929] Specific example

[0930] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection."

[0931] Thus, the system of the present invention provides a more comfortable driving and travel experience by combining personalized recommendations based on the user's hobbies and preferences with real-time traffic and weather information to provide optimal route guidance.

[0932] The following describes the processing flow.

[0933] Step 1:

[0934] The user logs into the in-vehicle system. The terminal displays a login screen, and the user enters their ID and password.

[0935] Step 2:

[0936] The device asks, "Hello, what do you like?" via voice or text. The user replies, "I like seafood and nature," using voice input or the touchscreen.

[0937] Step 3:

[0938] The terminal sends the entered hobby and preference information to the server, and the server records that information in a database.

[0939] Step 4:

[0940] The server retrieves user hobbies and preferences from a database. Using a generative AI model, it generates a list of recommended destinations based on the user's favorite genres.

[0941] Step 5:

[0942] The server retrieves the latest information on tourist attractions, restaurants, and accommodations from external APIs and integrates it into a list of recommended destinations.

[0943] Step 6:

[0944] The server collects real-time traffic and weather information from external APIs. Based on this information, it dynamically updates the list of recommended destinations.

[0945] Step 7:

[0946] The server sends a real-time optimized list of recommended destinations to the device. The device then provides voice and screen guidance, such as, "We recommend AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature."

[0947] Step 8:

[0948] The user selects "Let's go to AA Restaurant." The device sends this selection information to the server.

[0949] Step 9:

[0950] The server calculates the optimal route to the user's selected destination. It utilizes a generative AI model and real-time traffic and weather data to generate the best route.

[0951] Step 10:

[0952] The server sends the calculated optimal route to the terminal. The terminal then begins route guidance with voice and screen display instructions such as, "Turn right and then left at the next traffic light."

[0953] Step 11:

[0954] The server monitors traffic conditions and weather information in real time while the vehicle is in motion. If an anomaly is detected, it calculates a new, optimal route.

[0955] Step 12:

[0956] The server resends the updated route information to the terminal. The terminal updates its instructions, displaying "Changing to the new route. Turn right at the next intersection."

[0957] In this way, a series of processes are carried out in coordination, starting with user input, followed by server data acquisition and analysis, real-time data integration, and finally, optimal route guidance to the user.

[0958] (Example 1)

[0959] 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."

[0960] Conventional navigation systems often lack destination recommendations based on individual user preferences and dynamic route updates based on real-time traffic and weather information. Furthermore, their voice input and output interfaces are often inadequate, resulting in a limited user experience. A system is needed to address these challenges.

[0961] 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.

[0962] In this invention, the server includes input means for inputting user interest information; analysis means for generating recommended destinations based on the interest information using a generation AI model; acquisition means for collecting real-time road and weather information and dynamically updating the list of recommended destinations; presentation means for presenting the list of recommended destinations to the user via display and voice guidance; route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance; and means for updating the route guidance in real time based on road and weather information during travel. This enables destination recommendations based on individual hobbies and preferences, and dynamic route updates based on real-time traffic conditions and weather information.

[0963] An "input device" is a device or interface for users to input information about their interests and preferences.

[0964] "Analysis means" refers to a device or system that uses a generative AI model to generate recommended destinations based on input interest and preference information.

[0965] "Acquisition method" refers to a device or system that collects real-time road and weather information and dynamically updates a list of recommended destinations based on that information.

[0966] A "presentation means" refers to a device or interface for presenting a list of recommended destinations to a user visually and audibly.

[0967] A "route guidance system" is a device or system that calculates the optimal route to a destination selected by the user and guides them along that route.

[0968] "Means of updating in real time" refers to devices or systems that constantly monitor traffic conditions and weather information while the user is in transit, and correct and update route guidance accordingly.

[0969] A "generative AI model" is an artificial intelligence model that generates specific destinations or recommendation lists based on user input information.

[0970] A "prompt statement" is an instruction statement used to provide specific input to a generative AI model, and is text used to guide the model's output.

[0971] This invention is a system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and further guides users along the optimal route based on real-time road and weather information. The aim of this system is to make users' travel and driving more comfortable and stress-free.

[0972] System Configuration

[0973] This system includes the following main components:

[0974] 1. Input Method: This is an interface for users to input information about their interests and preferences. This can be implemented using voice input or touch panel input. Specifically, Google APIs can be used as voice recognition technology.

[0975] 2. Analysis Method: This is an engine that uses a generative AI model to generate recommended destinations based on the user's interests and preferences. For example, OpenAI's GPT-4 is used as this generative AI model.

[0976] 3. Acquisition Method: This module collects road and weather information in real time and provides that information to the analysis tool. Specifically, it can utilize the Google Maps API or the OpenWeatherMap API.

[0977] 4. Presentation methods: A display and speaker that visually or audibly present recommended destinations and route guidance to the user. A touch panel type display will be used, and speech synthesis technology will be used for voice guidance.

[0978] 5. Route guidance system: This is a navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time. The Google Maps API can be used for this purpose.

[0979] 6. Means of updating in real time: This system constantly monitors traffic conditions and weather information during travel and corrects and updates route guidance as needed.

[0980] Operation description

[0981] Input and collection of user information

[0982] When the device starts up, it asks the user aloud, "Hello, what do you like?" The user answers aloud, "I like seafood and nature," and the device uses speech recognition technology (e.g., Google API) to convert this information into text. The converted text is sent to the server and recorded in the database.

[0983] Data analysis using generative AI models

[0984] The server retrieves user hobbies and preferences from the database and inputs a prompt message into a generative AI model (for example, OpenAI's GPT-4): "I like seafood and am looking for tourist spots where I can enjoy nature. Please recommend some places." The generative AI model generates a list of recommended tourist spots and restaurants and adds the latest information on tourist spots and restaurants to this list.

[0985] Real-time data integration

[0986] The server calls a traffic information API (e.g., Google Maps API) and a weather information API (e.g., OpenWeatherMap API) to retrieve data. Based on this information, the server re-evaluates the recommendation list and sends the optimal list to the device.

[0987] Presentation of proposal

[0988] The terminal suggests to the user via voice and display, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." The user selects "AA Restaurant," and the terminal sends this information to the server.

[0989] Destination selection and route guidance

[0990] The server calculates the optimal route to the selected destination and sends the navigation data to the terminal. The terminal then begins providing directions via voice and display, such as "Turn right and then left at the next traffic light."

[0991] Adaptation and modification of the plan

[0992] While the user is in transit, the server periodically calls traffic information APIs and weather information APIs to obtain the latest conditions. In case of traffic congestion or bad weather, the server calculates a new optimal route, and the terminal notifies the user via voice and display with a message such as, "We are changing to a new route. Please turn right at the next intersection."

[0993] Explanation of specific examples

[0994] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection."

[0995] As described above, the system of the present invention provides a more comfortable driving and travel experience by combining personalized recommendations based on the user's interests with optimal route guidance based on real-time road and weather information.

[0996] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0997] Step 1: Enter and collect user information

[0998] When the device starts up, it will ask the user a voice message saying, "Hello, what do you like?"

[0999] Input: Voice message from the device: "Hello, what do you like?"

[1000] Output: User voice input "I like seafood and nature"

[1001] Specific operation: The user responds verbally with "I like seafood and nature." The device uses speech recognition technology (e.g., Google API) to convert the speech to text. The converted text is sent to the server and recorded in the database.

[1002] Step 2: Data analysis using generative AI models

[1003] The server retrieves user hobbies and preferences information from the database.

[1004] Input: User's hobby and preference information retrieved from the database: "Likes seafood and nature"

[1005] Output: Prompt message: "I like seafood and I'm looking for tourist spots where I can enjoy nature. Please recommend some places."

[1006] Specific operation: The server inputs prompt text into the generating AI model (e.g., OpenAI's GPT-4). The generating AI model generates a list of recommended tourist spots and restaurants. The server then references the latest information on tourist spots and restaurants and updates the list.

[1007] Step 3: Integrate real-time data

[1008] The server collects real-time road and weather information from external APIs.

[1009] Input: Real-time road and weather information collected from external APIs (Google Maps API, OpenWeatherMap API)

[1010] Output: Optimized recommended destination list

[1011] Specific operation: Based on traffic congestion and weather information acquired by the server, the list generated by the generation AI model is re-evaluated. The server optimizes the recommended list and sends the updated list to the terminal.

[1012] Step 4: Presentation of Proposal

[1013] The device displays recommended destinations and route guidance to the user visually and audibly.

[1014] Input: Optimized recommended destination list received from the server

[1015] Output: Suggestion to the user: "AA Restaurant offers fresh seafood dishes, and BB Park allows you to enjoy beautiful nature."

[1016] Specific operation: The terminal announces via voice, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." Detailed information is displayed on the screen. The user touches the screen to select "AA Restaurant." The terminal sends the selection information to the server.

[1017] Step 5: Destination selection and route guidance

[1018] The server calculates the optimal route to the selected destination based on an AI model and real-time data.

[1019] Input: User-selected destination "AA Restaurant"

[1020] Output: Navigation data based on the optimal route

[1021] Specific operation: The server calculates the optimal route to the user-selected "AA Restaurant" using an AI model and traffic and weather data. The calculation result is sent to the terminal. The terminal begins providing voice and display instructions such as "Turn right and then left at the next traffic light."

[1022] Step 6: Adapting and modifying the plan

[1023] The server monitors traffic conditions and weather in real time and calculates the optimal new route.

[1024] Input: Real-time collection of up-to-date traffic and weather information.

[1025] Output: Navigation data based on the updated optimal route

[1026] Specific operation: While the user is in transit, the server periodically calls the traffic information API and weather information API to obtain the latest conditions. In the event of traffic congestion or bad weather, the server calculates a new optimal route, and the terminal notifies the user via voice and display with a message such as, "We are changing to a new route. Please turn right at the next intersection."

[1027] (Application Example 1)

[1028] 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."

[1029] Current in-car systems offer limited services for personalizing users' trips and drives. Furthermore, the optimization of travel plans based on real-time traffic and weather information is insufficient, meaning they cannot fully meet the needs of individual users. This makes it difficult for users to enjoy stress-free and comfortable trips and drives.

[1030] 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.

[1031] In this invention, the server includes input means for inputting the user's hobbies and preferences; analysis means for generating recommended destinations based on the hobbies and preferences using a generation AI model; acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations; presentation means for presenting the list of recommended destinations to the user through display and voice guidance; route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance; and device linkage means for managing and displaying recommended destinations and guidance information on an interface using a smart device. This enables the optimization of personalized travel plans based on the user's hobbies and preferences in conjunction with real-time traffic and weather information, resulting in a comfortable and stress-free travel and driving experience.

[1032] An "input method" is an interface for users to input information about their hobbies and preferences.

[1033] A "generative AI model" is an artificial intelligence analysis engine that generates recommended destinations based on the user's interests and preferences.

[1034] The "analysis method" refers to a function that uses a generative AI model to analyze and generate recommended destinations based on the user's interests and preferences.

[1035] The "acquisition method" refers to a module that collects real-time traffic and weather information and dynamically updates the list of recommended destinations.

[1036] "Presentation means" refers to a function including a display and speaker for presenting a list of recommended destinations to the user through display and audio guidance.

[1037] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides route guidance.

[1038] "Device linking means" refers to a function that uses smart devices to manage and display recommended destinations and guidance information on an interface.

[1039] "Smart devices" refer to interactive devices such as smartphones, smart glasses, or head-mounted displays.

[1040] This invention is a system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and guides them along the optimal route based on real-time traffic and weather information. The aim of this system is to make users' trips and drives more comfortable and stress-free.

[1041] System Configuration

[1042] This system includes the following main components:

[1043] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented through voice input, touch panel input, etc.

[1044] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[1045] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and dynamically updates the list of recommended destinations.

[1046] 4. Presentation methods: Displays and speakers that present recommended destinations and route guidance to the user visually or audibly.

[1047] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[1048] 6. Device integration means: A function for managing and displaying recommended destinations and guidance information on the interface using a smart device.

[1049] Operation and processing

[1050] Input and collection of user information

[1051] The server asks the user, "Hello, what do you like?" via voice or text. The user then inputs their hobbies and preferences via voice input or a touch panel. For example, if the user inputs "I like seafood and nature," that information is sent to the server and recorded in the database.

[1052] Data analysis using generative AI models

[1053] The server retrieves user preferences from a database and uses a generative AI model to generate a list of recommended destinations. For example, using OpenAI's GPT-3, it takes the prompt "User preferences: Likes seafood and nature. What are some recommended tourist spots, restaurants, and accommodations?" and recommends tourist spots and restaurants that match the user's preferences. This recommendation information is integrated with the latest information on tourist spots, restaurants, and accommodations.

[1054] Real-time data integration

[1055] The server uses external APIs to collect real-time traffic and weather data, and updates the recommended destination list based on that information. The recommendation list is optimized to avoid traffic congestion and bad weather, and the updated information is sent to the device.

[1056] Presentation of proposal

[1057] The terminal provides voice and screen guidance, saying, "AA Restaurant offers fresh seafood dishes, and BB Park is a place where you can enjoy beautiful nature." When the user selects "Let's go to AA Restaurant," that information is sent to the server.

[1058] Destination selection and route guidance

[1059] The server calculates the optimal route to the selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal. The terminal then begins providing directions via voice and on-screen display, such as "Turn right and then left at the next traffic light."

[1060] Adaptation and modification of the plan

[1061] The server monitors traffic conditions and weather in real time and calculates a new, optimal route as needed. The terminal updates its instructions with a message such as, "Changing to a new route. Turn right at the next intersection."

[1062] Specific example

[1063] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." The server then generates a recommendation list, integrates it with updated traffic and weather data, and sends it to the terminal. The terminal then advises, "AA Restaurant is a recommended seafood restaurant, and BB Park is a great spot to enjoy nature." Once the user makes their selection, the optimal route is calculated and navigation begins immediately.

[1064] Thus, the system of the present invention can provide a more comfortable driving and travel experience by combining personalized recommendations based on the user's hobbies and preferences with real-time traffic and weather information to provide optimal route guidance.

[1065] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1066] Step 1:

[1067] The server asks the user via voice or text, "Hello, what do you like?" The user inputs their hobbies and preferences, such as "I like seafood and nature," via voice input or touch panel. The terminal sends this information to the server, which records it in a database. The input here is the user's hobbies and preferences, and the output is the recorded hobbies and preferences. This information is used for analysis.

[1068] Step 2:

[1069] The server retrieves user preferences and interests from a database. Then, using a generative AI model (e.g., OpenAI's GPT-3), it takes the prompt "User preferences: Likes seafood and nature. What are some recommended tourist spots, restaurants, and accommodations?" as input and generates a list of recommended destinations. This analysis outputs a list of tourist spots and restaurants that are suitable for the user's preferences.

[1070] Step 3:

[1071] The server uses an external API to collect real-time traffic and weather data. The collected data is reflected in an existing list of recommended destinations and is dynamically updated. The input here is traffic and weather information, and the output is the updated list of recommended destinations.

[1072] Step 4:

[1073] The terminal receives an updated list of recommended destinations and guides the user via voice and on-screen messages, saying, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." If the user selects "Let's go to AA Restaurant," this information is sent to the server. The input here is the user's destination selection information, and the output is the transmission of destination selection information to the server.

[1074] Step 5:

[1075] The server uses a generated AI model and real-time data to calculate the optimal route to the selected destination. The calculated optimal route is sent to the terminal as navigation data. The terminal then begins providing guidance via voice and on-screen display, such as "Turn right and then left at the next traffic light." The input here is destination selection information and real-time data, and the output is the optimal route guidance.

[1076] Step 6:

[1077] The server monitors traffic conditions and weather in real time and calculates a new, optimal route as needed. The terminal updates its directions with a message such as, "Changing to a new route. Turn right at the next intersection." The input here is the latest traffic and weather information, and the output is the updated route guidance.

[1078] 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.

[1079] This invention relates to an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's hobbies, preferences, and emotional state, and guides the user along the optimal route based on real-time traffic and weather information. Furthermore, this invention aims to combine an emotion engine to recognize the user's emotions and dynamically adjust the suggested content and guidance methods.

[1080] System Configuration

[1081] This system includes the following main components:

[1082] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented using voice input, touch panel input, etc.

[1083] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[1084] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[1085] 4. Presentation methods: Displays and speakers for presenting recommended destinations and route guidance to users visually or audibly.

[1086] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[1087] 6. Emotion Engine: An engine that recognizes emotions from the user's voice and actions, and dynamically adjusts the suggested content and guidance methods based on those emotions.

[1088] Program processing and operation

[1089] The entire system works as follows:

[1090] 1. Input and collection of user information

[1091] The device asks the user, "Hello, what do you like?" via voice or text.

[1092] The user enters "I like seafood and nature" via voice input or touch panel.

[1093] The device sends this information to the server, which then records it in the database.

[1094] 2. Data analysis using generative AI models

[1095] The server retrieves user hobbies and preferences from a database and uses a generative AI model to generate a list of recommended destinations.

[1096] The server will add the latest information on tourist attractions, restaurants, and accommodations to this.

[1097] 3. Real-time data integration

[1098] The server collects real-time traffic and weather data from external APIs and updates the recommended destination list.

[1099] The server sends an optimized list to the terminal to avoid traffic congestion and bad weather.

[1100] 4. Presentation of the proposed plan

[1101] The terminal provides voice and screen guidance, saying, "This is AA Restaurant, where you can enjoy fresh seafood dishes, and BB Park, where you can enjoy beautiful nature."

[1102] The user selects "Let's go to AA Restaurant," and the device sends this information to the server.

[1103] 5. Destination Selection and Route Guidance

[1104] The server calculates the optimal route to the user's selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal.

[1105] The terminal begins providing route guidance via voice and on-screen display, saying, "Turn right and then turn left at the next traffic light."

[1106] 6. Emotion Recognition and Optimization of Suggestions and Guidance

[1107] The emotion engine recognizes the user's emotional state from their voice and facial expressions.

[1108] The server uses sentiment information obtained from the sentiment engine to dynamically adjust the content of recommendation lists and route guidance.

[1109] For example, if a user is tired, the server will adjust its recommendations to suggest more relaxing destinations. Conversely, if a user is excited, the server will recommend exciting activities.

[1110] 7. Adaptation and modification of the plan

[1111] The server monitors traffic conditions and weather changes in real time and calculates a new, optimal route as needed.

[1112] The terminal updates its instructions, saying, "We are changing to a new route. Please turn right at the next intersection."

[1113] Specific example

[1114] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection." Furthermore, if the user appears tired, the emotion engine adjusts the system to suggest a relaxing next destination.

[1115] Thus, the system of the present invention provides a more comfortable and efficient driving and travel experience by combining personalized recommendations based on the user's hobbies, preferences, and emotional state with real-time traffic and weather information to provide optimal route guidance.

[1116] The following describes the processing flow.

[1117] Step 1:

[1118] The device asks the user, either by voice or text, "Hello, what do you like?"

[1119] Step 2:

[1120] The user enters "I like seafood and nature" via voice input or touch panel.

[1121] Step 3:

[1122] The terminal sends the entered hobby and preference information to the server, and the server records that information in a database.

[1123] Step 4:

[1124] The server retrieves user hobbies and preferences from a database. Using a generative AI model, it generates a list of recommended destinations based on the user's preferred genres.

[1125] Step 5:

[1126] The server retrieves the latest information on tourist attractions, restaurants, and accommodations from external APIs and integrates it into a list of recommended destinations.

[1127] Step 6:

[1128] The server collects real-time traffic and weather information from external APIs. Based on this information, it dynamically updates the list of recommended destinations.

[1129] Step 7:

[1130] The server sends a real-time optimized list of recommended destinations to the device. The device then provides voice and screen guidance, such as, "We recommend AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature."

[1131] Step 8:

[1132] The user selects "Let's go to AA Restaurant." The device sends this selection information to the server.

[1133] Step 9:

[1134] The server calculates the optimal route to the user's selected destination. It utilizes a generative AI model and real-time traffic and weather data to generate the best route.

[1135] Step 10:

[1136] The server sends the calculated optimal route to the terminal. The terminal then begins route guidance with voice and screen display instructions such as, "Turn right and then left at the next traffic light."

[1137] Step 11:

[1138] While the device is in motion, it analyzes the user's voice and behavior in real time, and an emotion engine recognizes those emotions. For example, if the user appears tired, the device sends that emotion data to the server.

[1139] Step 12:

[1140] The server uses emotion data obtained from the emotion engine to dynamically adjust recommendation lists and route guidance. For example, if the user is tired, it prioritizes relaxing destinations.

[1141] Step 13:

[1142] The server sends an updated recommendation list to the device based on sentiment data. The device then suggests, "You seem tired, user. How about relaxing at BB Cafe?"

[1143] Step 14:

[1144] The server monitors traffic conditions and weather information in real time while the vehicle is in motion. If an anomaly is detected, it calculates a new, optimal route.

[1145] Step 15:

[1146] The server resends the updated route information to the terminal. The terminal updates its instructions, displaying "Changing to the new route. Turn right at the next intersection."

[1147] Thus, the system of the present invention combines personalized recommendations based on the user's hobbies, preferences, and emotional state with real-time traffic and weather information to provide optimal route guidance, thereby realizing a comfortable and efficient driving and travel experience for the user.

[1148] (Example 2)

[1149] 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."

[1150] Current in-car systems have limitations in recommending destinations and providing route guidance that take into account the user's preferences and real-time traffic and weather information. Furthermore, few systems have the functionality to dynamically adjust suggestions and guidance methods based on the user's emotional state, and there is a lack of technology to provide a more personalized and comfortable driving experience.

[1151] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting the user's hobbies and preferences information, an analysis means for generating recommended destinations based on the hobbies and preferences information using a generation AI model, an acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations, a presentation means for presenting the list of recommended destinations to the user through display and voice guidance, a route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance, and an emotion recognition means for recognizing the user's emotional state and dynamically adjusting the suggested content and guidance method based on it. This makes it possible to provide optimal route guidance by combining personalized recommendations based on the user's hobbies and preferences and emotional state with real-time traffic and weather information.

[1152] "Input method" refers to an interface for users to input information about their hobbies and preferences, and includes methods such as voice input and touch panel input.

[1153] A "generative AI model" is an artificial intelligence model that generates recommended destinations based on the user's interests and preferences.

[1154] "Analysis means" refers to a means of generating recommended destinations based on hobby and preference information using a generative AI model.

[1155] "Acquisition method" refers to a method for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations.

[1156] "Presentation means" refers to means such as displays and speakers for presenting a list of recommended destinations to the user visually or audibly.

[1157] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides real-time route guidance.

[1158] An "emotion recognition means" is a method for recognizing a user's emotional state from their voice and facial expressions, and dynamically adjusting the suggested content and guidance methods based on that recognition.

[1159] This invention is an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's hobbies, preferences, and emotional state, and guides the user along the optimal route based on real-time traffic and weather information. Furthermore, this invention aims to incorporate an emotion engine to recognize the user's emotions and dynamically adjust the suggested content and guidance methods.

[1160] System Configuration

[1161] The system consists of the following main components:

[1162] 1. Input Method: This is an interface for users to input information about their hobbies and preferences. This includes voice input and touch panel input. In the case of voice input, speech recognition software (e.g., Google Speech-to-Text) is used.

[1163] 2. Generative AI Models: These are artificial intelligence models used to generate recommended destinations based on the user's interests and preferences. Natural language processing models such as BERT and GPT are used as generative AI models.

[1164] 3. Data Acquisition Method: This module collects real-time traffic and weather information. It utilizes the Google Maps API and the OpenWeatherMap API.

[1165] 4. Presentation means: A display and speaker for presenting recommended destinations and route guidance to the user visually or audibly. Speech synthesis software (e.g., TTS engine) is used for audio output.

[1166] 5. Route guidance system: This is a navigation system that calculates the optimal route to the destination selected by the user and provides real-time route guidance. Dijkstra's algorithm or the A algorithm are used as route calculation algorithms.

[1167] 6. Emotion Recognition Method: This is an engine that collects the user's voice and facial expressions through a camera and microphone and recognizes their emotional state. A face emotion analysis tool (e.g., Affectiva) is used.

[1168] Specific example

[1169] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" The user voice-inputs, "I like seafood and nature," and the speech recognition software converts this to text, and the terminal sends this information to the server. The server retrieves the user's hobbies and preferences from the database and generates a list of recommended destinations using a generative AI model. The prompt used is, "Based on the information that the user likes AA, please suggest appropriate tourist spots."

[1170] Based on real-time traffic and weather data collected by the server, the recommended destination list is updated and sent to the terminal. The terminal suggests, "AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature," and the user selects "AA Restaurant." The server calculates the optimal route and sends navigation data to the terminal. The terminal then begins guiding the user, saying, "Turn right and then left at the next traffic light."

[1171] If traffic congestion occurs during travel, the server calculates a new optimal route, and the terminal updates its guidance with a message such as, "Changing to a new route. Turn right at the next intersection." Furthermore, if the emotion engine detects user fatigue, the server adjusts its suggestions to include more relaxing destinations.

[1172] Thus, this invention combines real-time data and emotion recognition capabilities to provide optimal recommendations and route guidance tailored to the user's hobbies, preferences, and emotional state. This enables a more comfortable and efficient driving and travel experience.

[1173] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1174] Step 1:

[1175] User input of hobby and preference information

[1176] 1. The device asks the user, "Hello, what do you like?" via voice or text.

[1177] 2. The user responds with "I like seafood and nature." This input is done via voice input or touch panel operation.

[1178] 3. In the case of voice input, speech recognition software (e.g., Google Speech-to-Text) converts the speech into text data.

[1179] Input: User voice or text input

[1180] Output: Text-formatted information on hobbies and interests (e.g., "I like seafood and nature")

[1181] Operation: The device invokes speech recognition software and converts the recognition result into text.

[1182] Step 2:

[1183] Sending hobby and preference information to the server

[1184] 1. The device sends the acquired hobby and preference information to the server. Specifically, it transfers the information to the server using an HTTP request.

[1185] Input: Text-based information about hobbies and interests (e.g., "I like seafood and nature")

[1186] Output: Hobby and preference information stored in a database on the server.

[1187] Operation: The device creates an HTTP request and sends data to the server's API endpoint.

[1188] Step 3:

[1189] Generating recommended candidates using generative AI models

[1190] 1. The server retrieves hobby and preference information from the database.

[1191] 2. The server uses a generation AI model to generate a list of recommended candidates based on the user's interests and preferences. Specifically, the prompt "Based on the information that the user likes AA, please suggest appropriate tourist spots" is input to the generation AI model.

[1192] Input: Information on hobbies and preferences stored in a database on the server.

[1193] Output: List of recommended options (e.g., seafood restaurants and natural spots)

[1194] Operation: The server calls the generated AI model, takes prompts, and extracts recommended candidates.

[1195] Step 4:

[1196] Real-time data collection and list updates

[1197] 1. The server calls external APIs (e.g., Google Maps API, OpenWeatherMap API) to obtain real-time traffic and weather information.

[1198] 2. The recommended candidate list is filtered and optimized based on real-time data collected by the server.

[1199] Input: List of recommended candidates, and real-time traffic and weather information.

[1200] Output: Updated list of recommended candidates

[1201] Operation: The server sends an HTTP request to an external API, retrieves data, and updates the list of recommended candidates.

[1202] Step 5:

[1203] Sending and displaying recommended candidates to devices

[1204] 1. The server sends the updated list of recommended candidates to the terminal.

[1205] 2. The device presents the user with a list of recommended options via voice and on-screen display. For example, it might say, "AA Restaurant is a recommended seafood restaurant, and BB Park is a great spot to enjoy nature."

[1206] Input: Updated list of recommended candidates

[1207] Output: Recommended suggestions presented to the user (audio and on-screen display)

[1208] Operation: The server sends data to the terminal as an HTTP response, and the terminal presents the information using speech synthesis software and a display.

[1209] Step 6:

[1210] User-selected destination

[1211] 1. The user selects "Let's go to AA Restaurant" via their device.

[1212] 2. The terminal sends the selection information to the server.

[1213] Input: User selects destination (voice or touch operation)

[1214] Output: Selected destination information (sent to the server)

[1215] Operation: The user makes a selection on the device, and the device sends the data to the server.

[1216] Step 7:

[1217] Calculates the optimal route to the selected destination.

[1218] 1. The server calculates the optimal route based on the selected destination information, using a generated AI model and real-time data.

[1219] 2. Send navigation data to the device.

[1220] Input: Selected destination information, and real-time traffic and weather information.

[1221] Output: Navigation data (sent from server to terminal)

[1222] Operation: The server generates the optimal route using a route calculation algorithm and sends the data to the terminal.

[1223] Step 8:

[1224] Start of route guidance

[1225] 1. The device will begin providing route guidance via voice and on screen, saying, "Turn right and then turn left at the next traffic light."

[1226] Input: Navigation data

[1227] Output: Audio and screen display of route guidance.

[1228] Operation: The terminal starts providing guidance using speech synthesis software and the display based on the navigation data.

[1229] Step 9:

[1230] Responding to real-time changes in the situation

[1231] 1. The server monitors traffic conditions and weather changes in real time.

[1232] 2. Calculate a new optimal route as needed and notify the device.

[1233] 3. The terminal updates its instructions to "Changing to a new route. Turn right at the next intersection."

[1234] Input: Real-time traffic and weather information

[1235] Output: Updated navigation data and new route guidance.

[1236] Operation: The server recalculates the new optimal route based on real-time data and notifies the terminal. The terminal displays the new directions via voice and display.

[1237] Step 10:

[1238] Proposal adjustment based on emotion recognition

[1239] 1. The emotion engine recognizes the user's emotional state from their voice and facial expressions.

[1240] 2. The server adjusts recommendation lists and route guidance based on sentiment information.

[1241] 3. For example, if the user is tired, the server will suggest many relaxing destinations.

[1242] Input: User's voice and facial expression data

[1243] Output: Sentiment-based recommendation list and guidance content

[1244] Operation: The emotion engine performs sentiment analysis and sends the results to the server. The server updates the recommendations.

[1245] (Application Example 2)

[1246] 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."

[1247] While conventional in-car systems offer recommendation features based on user preferences, they lack dynamic adjustments based on emotional states. Furthermore, although they provide optimal route guidance based on real-time information, they do not update suggestions in response to changes in the user's emotions, resulting in a low degree of personalization for individual users. This leads to an insufficient user experience, particularly during long drives or trips, which reduces satisfaction.

[1248] In Application Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for inputting the user's hobby and preference information, an analysis means for generating recommended destinations based on the hobby and preference information using a generation AI model, an acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations, a presentation means for presenting the list of recommended destinations to the user through display and voice guidance, a route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance, and an emotion analysis means for recognizing the user's emotional state and dynamically adjusting the suggested content and guidance method. This enables the provision of dynamic recommendations and guidance based on the user's hobby and preference and emotional state, and enables optimal route guidance in real time.

[1249] "Input method" refers to an interface for inputting information about the user's hobbies, preferences, and emotional state, and includes voice input and touch panel input.

[1250] A "generative AI model" is an analytical engine that calculates recommended destinations based on the user's interests and preferences.

[1251] The "analysis tool" is a module that uses a generative AI model to generate recommended destinations based on the user's interests and preferences.

[1252] The "acquisition method" refers to a data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[1253] "Presentation means" refers to displays and speakers used to present recommended destinations and route guidance to users visually or through audio guidance.

[1254] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[1255] An "emotion analysis tool" is an engine that recognizes the user's emotional state from their voice and facial expressions, and dynamically adjusts the suggested content and guidance methods based on that recognition.

[1256] "Smart glasses" are wearable devices that have a display function and provide information by connecting to the internet or other devices.

[1257] "Voice guidance" is a function that provides information and instructions to users using voice output.

[1258] This system recommends tourist attractions, restaurants, and accommodations based on the user's interests, preferences, and emotional state, and guides users along the optimal route based on real-time traffic and weather information. Specific implementation details are described below.

[1259] Hardware and software to be used

[1260] Hardware:

[1261] Smart glasses: Used as both a display and a voice input device.

[1262] Smartphones: Used as auxiliary interfaces and data processing devices.

[1263] Server: Analyzes data centrally and runs the generated AI model.

[1264] software:

[1265] Generative AI model: Uses natural language processing engines such as OpenAI GPT-3.

[1266] Speech recognition module: Uses the Google Speech-to-Text API.

[1267] Traffic Information API: Uses an external API (e.g., Traffic API) to obtain traffic information.

[1268] Weather Information API: Uses an external API (e.g., OpenWeather API) to obtain the latest weather information.

[1269] The main components of the system and their operation

[1270] 1. Input method:

[1271] This is an interface for users to input information about their hobbies and preferences. Using a voice recognition module, smart glasses and smartphones accept voice input from the user.

[1272] For example, a user wears smart glasses and voice-inputs, "I like historical places and delicious food."

[1273] 2. Generative AI Models:

[1274] The server uses OpenAI GPT-3 to analyze the user's interests and preferences and generate recommended destinations.

[1275] Example of a generated prompt: "The user is interested in historical places and delicious food. What are some recommended tourist spots and restaurants?"

[1276] 3. Acquisition method:

[1277] The server collects traffic and weather information in real time and dynamically updates the list of recommended destinations.

[1278] Traffic information is obtained using the Traffic API, and weather information is obtained using the OpenWeather API.

[1279] 4. Means of presentation:

[1280] The server displays a list of recommended destinations to the user via the smart glasses' display and audio output.

[1281] For example, it might display "Recommended spots: BB Park, □□ Temple" and also provide audio guidance.

[1282] 5. Means of route guidance:

[1283] The server calculates the optimal route to the destination selected by the user and provides navigation information, updating it in real time.

[1284] The smart glasses display "Starting route guidance to □□ Temple" and provide voice guidance such as "Turn right and then left at the next traffic light."

[1285] 6. Emotion analysis means:

[1286] The server analyzes the user's voice and facial expressions to recognize their emotional state.

[1287] For example, if a user indicates they are feeling tired, the server might recommend additional places where they can relax.

[1288] Specific example:

[1289] The user puts on smart glasses and inputs "I like nature and historical places" by voice. Based on this information, the server uses a generated AI model to analyze "recommended tourist spots and restaurants" and presents a list of "BB Park" and "□□ Temple". The user then selects "I want to go to □□ Temple", the server calculates the optimal route, and the smart glasses begin providing directions. The system also analyzes the user's emotional state and, if the user is tired, suggests additional relaxing places such as "□□ Cafe".

[1290] In this way, the system can provide personalized recommendations based on the user's interests, preferences, and emotional state, along with real-time optimal route guidance.

[1291] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1292] Step 1:

[1293] The device, via smart glasses and a smartphone, asks the user a voice question: "Hello, what do you like?" The user's voice response is the input. The device sends this voice data to a speech recognition module, which converts it into text.

[1294] Step 2:

[1295] The device sends the text information (user's hobbies and preferences) converted by speech recognition to the server. The input is the user's hobbies and preferences in text form. The server receives this information and records it in its database.

[1296] Step 3:

[1297] The server uses a generation AI model to generate a list of recommended destinations based on the received hobby and preference information. The input is the user's hobby and preference information. The server creates a prompt, calls the generation AI model, and generates a list of recommended destinations. The generated list of recommended destinations is retrieved and stored for early response display.

[1298] Step 4:

[1299] The server uses an external API to obtain real-time traffic and weather information. The input is an API request for traffic and weather data. The server retrieves this information and integrates it with a generated list of recommended destinations. The output is an updated list of recommended destinations.

[1300] Step 5:

[1301] The server sends an updated list of recommended destinations to the device. The updated list of recommended destinations is the input. The device receives this list and presents it to the user via the smart glasses' display and audio output. For example, it displays and provides audio guidance such as, "Recommended spots are BB Park and □□ Temple."

[1302] Step 6:

[1303] The user selects their desired destination from a presented list. The user's selection serves as input. The terminal records this selection and sends it to the server.

[1304] Step 7:

[1305] The server calculates the optimal route to the user's selected destination. The inputs are the selected destination and real-time traffic and weather information. The server uses a generative AI model to calculate the optimal route. The output is the optimal route.

[1306] Step 8:

[1307] The server sends the optimal route to the terminal. The terminal displays "Starting route guidance to □□ Temple" on its smart glasses and provides voice guidance such as "Turn right and then left at the next traffic light." Route data is also distributed to the relevant in-vehicle system, and navigation begins.

[1308] Step 9:

[1309] The server recognizes and analyzes the user's emotional state from their voice and facial expressions. The input consists of the user's voice and facial expression data. The server uses an emotion analysis engine to analyze this data and understand the user's emotional state. The output is information about the emotional state.

[1310] Step 10:

[1311] The server dynamically adjusts suggestions and guidance methods based on the user's emotional state. The input is information about the user's emotional state. Based on this emotional state, the server, for example, if it wants to suggest a place to relax, adds "□□ Cafe" to the recommendation list and sends it to the device. The device then displays this information on smart glasses and provides voice guidance.

[1312] Step 11:

[1313] The server monitors traffic conditions and weather changes in real time and calculates a new optimal route as needed. Traffic and weather data are used as input. The server uses a generative AI model to calculate the new optimal route and sends it to the terminal. The terminal updates the display and voice guidance on smart glasses and the in-vehicle system. For example, it might say, "Changing to the new route. Turn right at the next intersection."

[1314] These specifically divided processing steps reveal the details of a system that provides dynamic recommendations and optimal route guidance based on the user's hobbies, preferences, and emotional state.

[1315] 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.

[1316] 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.

[1317] 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.

[1318] [Fourth Embodiment]

[1319] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1320] 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.

[1321] 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).

[1322] 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.

[1323] 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.

[1324] 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).

[1325] 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.

[1326] 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.

[1327] 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.

[1328] 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.

[1329] 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.

[1330] 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.

[1331] 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".

[1332] This invention relates to an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and guides the user along the optimal route based on real-time traffic and weather information. The aim of this system is to make users' trips and drives more comfortable and stress-free.

[1333] System Configuration

[1334] This system includes the following main components:

[1335] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented through voice input, touch panel input, etc.

[1336] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[1337] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[1338] 4. Presentation methods: Displays and speakers that present recommended destinations and route guidance to the user visually or audibly.

[1339] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[1340] Program processing and operation

[1341] The entire system works as follows:

[1342] 1. Input and collection of user information

[1343] The device asks the user, "Hello, what do you like?" via voice or text.

[1344] The user enters "I like seafood and nature" using voice input or a touch panel.

[1345] The device sends this information to the server, which then records it in the database.

[1346] 2. Data analysis using generative AI models

[1347] The server retrieves user hobbies and preferences from a database and uses a generative AI model to generate a list of recommended destinations.

[1348] The server will add the latest information on tourist attractions, restaurants, and accommodations to this.

[1349] 3. Real-time data integration

[1350] The server collects real-time traffic and weather data from external APIs and updates the recommended destination list.

[1351] The server sends an optimized list to the terminal to avoid traffic congestion and bad weather.

[1352] 4. Presentation of the proposed plan

[1353] The terminal provides voice and screen guidance, saying, "This is AA Restaurant, where you can enjoy fresh seafood dishes, and BB Park, where you can enjoy beautiful nature."

[1354] The user selects "Let's go to AA Restaurant," and the device sends this information to the server.

[1355] 5. Destination Selection and Route Guidance

[1356] The server calculates the optimal route to the selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal.

[1357] The terminal begins giving voice and on-screen instructions saying, "Turn right and then turn left at the next traffic light."

[1358] 6. Adaptation and modification of the plan

[1359] The server monitors traffic conditions and weather changes in real time and calculates a new, optimal route as needed.

[1360] The terminal updates its instructions, saying, "We are changing to a new route. Please turn right at the next intersection."

[1361] Specific example

[1362] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection."

[1363] Thus, the system of the present invention provides a more comfortable driving and travel experience by combining personalized recommendations based on the user's hobbies and preferences with real-time traffic and weather information to provide optimal route guidance.

[1364] The following describes the processing flow.

[1365] Step 1:

[1366] The user logs into the in-vehicle system. The terminal displays a login screen, and the user enters their ID and password.

[1367] Step 2:

[1368] The device asks, "Hello, what do you like?" via voice or text. The user replies, "I like seafood and nature," using voice input or the touchscreen.

[1369] Step 3:

[1370] The terminal sends the entered hobby and preference information to the server, and the server records that information in a database.

[1371] Step 4:

[1372] The server retrieves user hobbies and preferences from a database. Using a generative AI model, it generates a list of recommended destinations based on the user's favorite genres.

[1373] Step 5:

[1374] The server retrieves the latest information on tourist attractions, restaurants, and accommodations from external APIs and integrates it into a list of recommended destinations.

[1375] Step 6:

[1376] The server collects real-time traffic and weather information from external APIs. Based on this information, it dynamically updates the list of recommended destinations.

[1377] Step 7:

[1378] The server sends a real-time optimized list of recommended destinations to the device. The device then provides voice and screen guidance, such as, "We recommend AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature."

[1379] Step 8:

[1380] The user selects "Let's go to AA Restaurant." The device sends this selection information to the server.

[1381] Step 9:

[1382] The server calculates the optimal route to the user's selected destination. It utilizes a generative AI model and real-time traffic and weather data to generate the best route.

[1383] Step 10:

[1384] The server sends the calculated optimal route to the terminal. The terminal then begins route guidance with voice and screen display instructions such as, "Turn right and then left at the next traffic light."

[1385] Step 11:

[1386] The server monitors traffic conditions and weather information in real time while the vehicle is in motion. If an anomaly is detected, it calculates a new, optimal route.

[1387] Step 12:

[1388] The server resends the updated route information to the terminal. The terminal updates its instructions, displaying "Changing to the new route. Turn right at the next intersection."

[1389] In this way, a series of processes are carried out in coordination, starting with user input, followed by server data acquisition and analysis, real-time data integration, and finally, optimal route guidance to the user.

[1390] (Example 1)

[1391] 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".

[1392] Conventional navigation systems often lack destination recommendations based on individual user preferences and dynamic route updates based on real-time traffic and weather information. Furthermore, their voice input and output interfaces are often inadequate, resulting in a limited user experience. A system is needed to address these challenges.

[1393] 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.

[1394] In this invention, the server includes input means for inputting user interest information; analysis means for generating recommended destinations based on the interest information using a generation AI model; acquisition means for collecting real-time road and weather information and dynamically updating the list of recommended destinations; presentation means for presenting the list of recommended destinations to the user via display and voice guidance; route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance; and means for updating the route guidance in real time based on road and weather information during travel. This enables destination recommendations based on individual hobbies and preferences, and dynamic route updates based on real-time traffic conditions and weather information.

[1395] An "input device" is a device or interface for users to input information about their interests and preferences.

[1396] "Analysis means" refers to a device or system that uses a generative AI model to generate recommended destinations based on input interest and preference information.

[1397] "Acquisition method" refers to a device or system that collects real-time road and weather information and dynamically updates a list of recommended destinations based on that information.

[1398] A "presentation means" refers to a device or interface for presenting a list of recommended destinations to a user visually and audibly.

[1399] A "route guidance system" is a device or system that calculates the optimal route to a destination selected by the user and guides them along that route.

[1400] "Means of updating in real time" refers to devices or systems that constantly monitor traffic conditions and weather information while the user is in transit, and correct and update route guidance accordingly.

[1401] A "generative AI model" is an artificial intelligence model that generates specific destinations or recommendation lists based on user input information.

[1402] A "prompt statement" is an instruction statement used to provide specific input to a generative AI model, and is text used to guide the model's output.

[1403] This invention is a system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and further guides users along the optimal route based on real-time road and weather information. The aim of this system is to make users' travel and driving more comfortable and stress-free.

[1404] System Configuration

[1405] This system includes the following main components:

[1406] 1. Input Method: This is an interface for users to input information about their interests and preferences. This can be implemented using voice input or touch panel input. Specifically, Google APIs can be used as voice recognition technology.

[1407] 2. Analysis Method: This is an engine that uses a generative AI model to generate recommended destinations based on the user's interests and preferences. For example, OpenAI's GPT-4 is used as this generative AI model.

[1408] 3. Acquisition Method: This module collects road and weather information in real time and provides that information to the analysis tool. Specifically, it can utilize the Google Maps API or the OpenWeatherMap API.

[1409] 4. Presentation methods: A display and speaker that visually or audibly present recommended destinations and route guidance to the user. A touch panel type display will be used, and speech synthesis technology will be used for voice guidance.

[1410] 5. Route guidance system: This is a navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time. The Google Maps API can be used for this purpose.

[1411] 6. Means of updating in real time: This system constantly monitors traffic conditions and weather information during travel and corrects and updates route guidance as needed.

[1412] Operation description

[1413] Input and collection of user information

[1414] When the device starts up, it asks the user aloud, "Hello, what do you like?" The user answers aloud, "I like seafood and nature," and the device uses speech recognition technology (e.g., Google API) to convert this information into text. The converted text is sent to the server and recorded in the database.

[1415] Data analysis using generative AI models

[1416] The server retrieves user hobbies and preferences from the database and inputs a prompt message into a generative AI model (for example, OpenAI's GPT-4): "I like seafood and am looking for tourist spots where I can enjoy nature. Please recommend some places." The generative AI model generates a list of recommended tourist spots and restaurants and adds the latest information on tourist spots and restaurants to this list.

[1417] Real-time data integration

[1418] The server calls a traffic information API (e.g., Google Maps API) and a weather information API (e.g., OpenWeatherMap API) to retrieve data. Based on this information, the server re-evaluates the recommendation list and sends the optimal list to the device.

[1419] Presentation of proposal

[1420] The terminal suggests to the user via voice and display, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." The user selects "AA Restaurant," and the terminal sends this information to the server.

[1421] Destination selection and route guidance

[1422] The server calculates the optimal route to the selected destination and sends the navigation data to the terminal. The terminal then begins providing directions via voice and display, such as "Turn right and then left at the next traffic light."

[1423] Adaptation and modification of the plan

[1424] While the user is in transit, the server periodically calls traffic information APIs and weather information APIs to obtain the latest conditions. In case of traffic congestion or bad weather, the server calculates a new optimal route, and the terminal notifies the user via voice and display with a message such as, "We are changing to a new route. Please turn right at the next intersection."

[1425] Explanation of specific examples

[1426] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection."

[1427] As described above, the system of the present invention provides a more comfortable driving and travel experience by combining personalized recommendations based on the user's interests with optimal route guidance based on real-time road and weather information.

[1428] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1429] Step 1: Enter and collect user information

[1430] When the device starts up, it will ask the user a voice message saying, "Hello, what do you like?"

[1431] Input: Voice message from the device: "Hello, what do you like?"

[1432] Output: User voice input "I like seafood and nature"

[1433] Specific operation: The user responds verbally with "I like seafood and nature." The device uses speech recognition technology (e.g., Google API) to convert the speech to text. The converted text is sent to the server and recorded in the database.

[1434] Step 2: Data analysis using generative AI models

[1435] The server retrieves user hobbies and preferences information from the database.

[1436] Input: User's hobby and preference information retrieved from the database: "Likes seafood and nature"

[1437] Output: Prompt message: "I like seafood and I'm looking for tourist spots where I can enjoy nature. Please recommend some places."

[1438] Specific operation: The server inputs prompt text into the generating AI model (e.g., OpenAI's GPT-4). The generating AI model generates a list of recommended tourist spots and restaurants. The server then references the latest information on tourist spots and restaurants and updates the list.

[1439] Step 3: Integrate real-time data

[1440] The server collects real-time road and weather information from external APIs.

[1441] Input: Real-time road and weather information collected from external APIs (Google Maps API, OpenWeatherMap API)

[1442] Output: Optimized recommended destination list

[1443] Specific operation: Based on traffic congestion and weather information acquired by the server, the list generated by the generation AI model is re-evaluated. The server optimizes the recommended list and sends the updated list to the terminal.

[1444] Step 4: Presentation of Proposal

[1445] The device displays recommended destinations and route guidance to the user visually and audibly.

[1446] Input: Optimized recommended destination list received from the server

[1447] Output: Suggestion to the user: "AA Restaurant offers fresh seafood dishes, and BB Park allows you to enjoy beautiful nature."

[1448] Specific operation: The terminal announces via voice, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." Detailed information is displayed on the screen. The user touches the screen to select "AA Restaurant." The terminal sends the selection information to the server.

[1449] Step 5: Destination selection and route guidance

[1450] The server calculates the optimal route to the selected destination based on an AI model and real-time data.

[1451] Input: User-selected destination "AA Restaurant"

[1452] Output: Navigation data based on the optimal route

[1453] Specific operation: The server calculates the optimal route to the user-selected "AA Restaurant" using an AI model and traffic and weather data. The calculation result is sent to the terminal. The terminal begins providing voice and display instructions such as "Turn right and then left at the next traffic light."

[1454] Step 6: Adapting and modifying the plan

[1455] The server monitors traffic conditions and weather in real time and calculates the optimal new route.

[1456] Input: Real-time collection of up-to-date traffic and weather information.

[1457] Output: Navigation data based on the updated optimal route

[1458] Specific operation: While the user is in transit, the server periodically calls the traffic information API and weather information API to obtain the latest conditions. In the event of traffic congestion or bad weather, the server calculates a new optimal route, and the terminal notifies the user via voice and display with a message such as, "We are changing to a new route. Please turn right at the next intersection."

[1459] (Application Example 1)

[1460] 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".

[1461] Current in-car systems offer limited services for personalizing users' trips and drives. Furthermore, the optimization of travel plans based on real-time traffic and weather information is insufficient, meaning they cannot fully meet the needs of individual users. This makes it difficult for users to enjoy stress-free and comfortable trips and drives.

[1462] 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.

[1463] In this invention, the server includes input means for inputting the user's hobbies and preferences; analysis means for generating recommended destinations based on the hobbies and preferences using a generation AI model; acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations; presentation means for presenting the list of recommended destinations to the user through display and voice guidance; route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance; and device linkage means for managing and displaying recommended destinations and guidance information on an interface using a smart device. This enables the optimization of personalized travel plans based on the user's hobbies and preferences in conjunction with real-time traffic and weather information, resulting in a comfortable and stress-free travel and driving experience.

[1464] An "input method" is an interface for users to input information about their hobbies and preferences.

[1465] A "generative AI model" is an artificial intelligence analysis engine that generates recommended destinations based on the user's interests and preferences.

[1466] The "analysis method" refers to a function that uses a generative AI model to analyze and generate recommended destinations based on the user's interests and preferences.

[1467] The "acquisition method" refers to a module that collects real-time traffic and weather information and dynamically updates the list of recommended destinations.

[1468] "Presentation means" refers to a function including a display and speaker for presenting a list of recommended destinations to the user through display and audio guidance.

[1469] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides route guidance.

[1470] "Device linking means" refers to a function that uses smart devices to manage and display recommended destinations and guidance information on an interface.

[1471] "Smart devices" refer to interactive devices such as smartphones, smart glasses, or head-mounted displays.

[1472] This invention is a system that recommends tourist spots, restaurants, and accommodations based on the user's interests and preferences, and guides them along the optimal route based on real-time traffic and weather information. The aim of this system is to make users' trips and drives more comfortable and stress-free.

[1473] System Configuration

[1474] This system includes the following main components:

[1475] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented through voice input, touch panel input, etc.

[1476] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[1477] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and dynamically updates the list of recommended destinations.

[1478] 4. Presentation methods: Displays and speakers that present recommended destinations and route guidance to the user visually or audibly.

[1479] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[1480] 6. Device integration means: A function for managing and displaying recommended destinations and guidance information on the interface using a smart device.

[1481] Operation and processing

[1482] Input and collection of user information

[1483] The server asks the user, "Hello, what do you like?" via voice or text. The user then inputs their hobbies and preferences via voice input or a touch panel. For example, if the user inputs "I like seafood and nature," that information is sent to the server and recorded in the database.

[1484] Data analysis using generative AI models

[1485] The server retrieves user preferences from a database and uses a generative AI model to generate a list of recommended destinations. For example, using OpenAI's GPT-3, it takes the prompt "User preferences: Likes seafood and nature. What are some recommended tourist spots, restaurants, and accommodations?" and recommends tourist spots and restaurants that match the user's preferences. This recommendation information is integrated with the latest information on tourist spots, restaurants, and accommodations.

[1486] Real-time data integration

[1487] The server uses external APIs to collect real-time traffic and weather data, and updates the recommended destination list based on that information. The recommendation list is optimized to avoid traffic congestion and bad weather, and the updated information is sent to the device.

[1488] Presentation of proposal

[1489] The terminal provides voice and screen guidance, saying, "AA Restaurant offers fresh seafood dishes, and BB Park is a place where you can enjoy beautiful nature." When the user selects "Let's go to AA Restaurant," that information is sent to the server.

[1490] Destination selection and route guidance

[1491] The server calculates the optimal route to the selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal. The terminal then begins providing directions via voice and on-screen display, such as "Turn right and then left at the next traffic light."

[1492] Adaptation and modification of the plan

[1493] The server monitors traffic conditions and weather in real time and calculates a new, optimal route as needed. The terminal updates its instructions with a message such as, "Changing to a new route. Turn right at the next intersection."

[1494] Specific example

[1495] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." The server then generates a recommendation list, integrates it with updated traffic and weather data, and sends it to the terminal. The terminal then advises, "AA Restaurant is a recommended seafood restaurant, and BB Park is a great spot to enjoy nature." Once the user makes their selection, the optimal route is calculated and navigation begins immediately.

[1496] Thus, the system of the present invention can provide a more comfortable driving and travel experience by combining personalized recommendations based on the user's hobbies and preferences with real-time traffic and weather information to provide optimal route guidance.

[1497] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1498] Step 1:

[1499] The server asks the user via voice or text, "Hello, what do you like?" The user inputs their hobbies and preferences, such as "I like seafood and nature," via voice input or touch panel. The terminal sends this information to the server, which records it in a database. The input here is the user's hobbies and preferences, and the output is the recorded hobbies and preferences. This information is used for analysis.

[1500] Step 2:

[1501] The server retrieves user preferences and interests from a database. Then, using a generative AI model (e.g., OpenAI's GPT-3), it takes the prompt "User preferences: Likes seafood and nature. What are some recommended tourist spots, restaurants, and accommodations?" as input and generates a list of recommended destinations. This analysis outputs a list of tourist spots and restaurants that are suitable for the user's preferences.

[1502] Step 3:

[1503] The server uses an external API to collect real-time traffic and weather data. The collected data is reflected in an existing list of recommended destinations and is dynamically updated. The input here is traffic and weather information, and the output is the updated list of recommended destinations.

[1504] Step 4:

[1505] The terminal receives an updated list of recommended destinations and guides the user via voice and on-screen messages, saying, "AA Restaurant offers fresh seafood dishes, and BB Park provides beautiful natural scenery." If the user selects "Let's go to AA Restaurant," this information is sent to the server. The input here is the user's destination selection information, and the output is the transmission of destination selection information to the server.

[1506] Step 5:

[1507] The server uses a generated AI model and real-time data to calculate the optimal route to the selected destination. The calculated optimal route is sent to the terminal as navigation data. The terminal then begins providing guidance via voice and on-screen display, such as "Turn right and then left at the next traffic light." The input here is destination selection information and real-time data, and the output is the optimal route guidance.

[1508] Step 6:

[1509] The server monitors traffic conditions and weather in real time and calculates a new, optimal route as needed. The terminal updates its directions with a message such as, "Changing to a new route. Turn right at the next intersection." The input here is the latest traffic and weather information, and the output is the updated route guidance.

[1510] 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.

[1511] This invention relates to an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's hobbies, preferences, and emotional state, and guides the user along the optimal route based on real-time traffic and weather information. Furthermore, this invention aims to combine an emotion engine to recognize the user's emotions and dynamically adjust the suggested content and guidance methods.

[1512] System Configuration

[1513] This system includes the following main components:

[1514] 1. Input method: An interface for users to input information about their hobbies and preferences. This can be implemented using voice input, touch panel input, etc.

[1515] 2. Generative AI Model: An analytical engine for generating recommended destinations based on the user's interests and preferences.

[1516] 3. Acquisition method: A data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[1517] 4. Presentation methods: Displays and speakers for presenting recommended destinations and route guidance to users visually or audibly.

[1518] 5. Route guidance system: A navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[1519] 6. Emotion Engine: An engine that recognizes emotions from the user's voice and actions, and dynamically adjusts the suggested content and guidance methods based on those emotions.

[1520] Program processing and operation

[1521] The entire system works as follows:

[1522] 1. Input and collection of user information

[1523] The device asks the user, "Hello, what do you like?" via voice or text.

[1524] The user enters "I like seafood and nature" via voice input or touch panel.

[1525] The device sends this information to the server, which then records it in the database.

[1526] 2. Data analysis using generative AI models

[1527] The server retrieves user hobbies and preferences from a database and uses a generative AI model to generate a list of recommended destinations.

[1528] The server will add the latest information on tourist attractions, restaurants, and accommodations to this.

[1529] 3. Real-time data integration

[1530] The server collects real-time traffic and weather data from external APIs and updates the recommended destination list.

[1531] The server sends an optimized list to the terminal to avoid traffic congestion and bad weather.

[1532] 4. Presentation of the proposed plan

[1533] The terminal provides voice and screen guidance, saying, "This is AA Restaurant, where you can enjoy fresh seafood dishes, and BB Park, where you can enjoy beautiful nature."

[1534] The user selects "Let's go to AA Restaurant," and the device sends this information to the server.

[1535] 5. Destination Selection and Route Guidance

[1536] The server calculates the optimal route to the user's selected destination based on a generating AI model and real-time data, and sends the navigation data to the terminal.

[1537] The terminal begins providing route guidance via voice and on-screen display, saying, "Turn right and then turn left at the next traffic light."

[1538] 6. Emotion Recognition and Optimization of Suggestions and Guidance

[1539] The emotion engine recognizes the user's emotional state from their voice and facial expressions.

[1540] The server uses sentiment information obtained from the sentiment engine to dynamically adjust the content of recommendation lists and route guidance.

[1541] For example, if a user is tired, the server will adjust its recommendations to suggest more relaxing destinations. Conversely, if a user is excited, the server will recommend exciting activities.

[1542] 7. Adaptation and modification of the plan

[1543] The server monitors traffic conditions and weather changes in real time and calculates a new, optimal route as needed.

[1544] The terminal updates its instructions, saying, "We are changing to a new route. Please turn right at the next intersection."

[1545] Specific example

[1546] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" and the user replies, "I like seafood and nature." Based on this information, the server generates a list of "recommended seafood restaurants nearby" and "sightseeing spots with abundant nature," and updates it to reflect traffic and weather data. The terminal suggests, "AA Restaurant is a recommended seafood restaurant, and BB Park is a spot where you can enjoy nature," and the user selects "AA Restaurant." The server then calculates the optimal route, and the terminal begins guiding the user, saying, "Turn right and then left at the next traffic light." If traffic congestion occurs during the journey, the server calculates a new optimal route, and the terminal updates the guidance, saying, "Changing to a new route. Turn right at the next intersection." Furthermore, if the user appears tired, the emotion engine adjusts the system to suggest a relaxing next destination.

[1547] Thus, the system of the present invention provides a more comfortable and efficient driving and travel experience by combining personalized recommendations based on the user's hobbies, preferences, and emotional state with real-time traffic and weather information to provide optimal route guidance.

[1548] The following describes the processing flow.

[1549] Step 1:

[1550] The device asks the user, either by voice or text, "Hello, what do you like?"

[1551] Step 2:

[1552] The user enters "I like seafood and nature" via voice input or touch panel.

[1553] Step 3:

[1554] The terminal sends the entered hobby and preference information to the server, and the server records that information in a database.

[1555] Step 4:

[1556] The server retrieves user hobbies and preferences from a database. Using a generative AI model, it generates a list of recommended destinations based on the user's preferred genres.

[1557] Step 5:

[1558] The server retrieves the latest information on tourist attractions, restaurants, and accommodations from external APIs and integrates it into a list of recommended destinations.

[1559] Step 6:

[1560] The server collects real-time traffic and weather information from external APIs. Based on this information, it dynamically updates the list of recommended destinations.

[1561] Step 7:

[1562] The server sends a real-time optimized list of recommended destinations to the device. The device then provides voice and screen guidance, such as, "We recommend AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature."

[1563] Step 8:

[1564] The user selects "Let's go to AA Restaurant." The device sends this selection information to the server.

[1565] Step 9:

[1566] The server calculates the optimal route to the user's selected destination. It utilizes a generative AI model and real-time traffic and weather data to generate the best route.

[1567] Step 10:

[1568] The server sends the calculated optimal route to the terminal. The terminal then begins route guidance with voice and screen display instructions such as, "Turn right and then left at the next traffic light."

[1569] Step 11:

[1570] While the device is in motion, it analyzes the user's voice and behavior in real time, and an emotion engine recognizes those emotions. For example, if the user appears tired, the device sends that emotion data to the server.

[1571] Step 12:

[1572] The server uses emotion data obtained from the emotion engine to dynamically adjust recommendation lists and route guidance. For example, if the user is tired, it prioritizes relaxing destinations.

[1573] Step 13:

[1574] The server sends an updated recommendation list to the device based on sentiment data. The device then suggests, "You seem tired, user. How about relaxing at BB Cafe?"

[1575] Step 14:

[1576] The server monitors traffic conditions and weather information in real time while the vehicle is in motion. If an anomaly is detected, it calculates a new, optimal route.

[1577] Step 15:

[1578] The server resends the updated route information to the terminal. The terminal updates its instructions, displaying "Changing to the new route. Turn right at the next intersection."

[1579] Thus, the system of the present invention combines personalized recommendations based on the user's hobbies, preferences, and emotional state with real-time traffic and weather information to provide optimal route guidance, thereby realizing a comfortable and efficient driving and travel experience for the user.

[1580] (Example 2)

[1581] 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".

[1582] Current in-car systems have limitations in recommending destinations and providing route guidance that take into account the user's preferences and real-time traffic and weather information. Furthermore, few systems have the functionality to dynamically adjust suggestions and guidance methods based on the user's emotional state, and there is a lack of technology to provide a more personalized and comfortable driving experience.

[1583] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for inputting the user's hobbies and preferences information, an analysis means for generating recommended destinations based on the hobbies and preferences information using a generation AI model, an acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations, a presentation means for presenting the list of recommended destinations to the user through display and voice guidance, a route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance, and an emotion recognition means for recognizing the user's emotional state and dynamically adjusting the suggested content and guidance method based on it. This makes it possible to provide optimal route guidance by combining personalized recommendations based on the user's hobbies and preferences and emotional state with real-time traffic and weather information.

[1584] "Input method" refers to an interface for users to input information about their hobbies and preferences, and includes methods such as voice input and touch panel input.

[1585] A "generative AI model" is an artificial intelligence model that generates recommended destinations based on the user's interests and preferences.

[1586] "Analysis means" refers to a means of generating recommended destinations based on hobby and preference information using a generative AI model.

[1587] "Acquisition method" refers to a method for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations.

[1588] "Presentation means" refers to means such as displays and speakers for presenting a list of recommended destinations to the user visually or audibly.

[1589] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides real-time route guidance.

[1590] An "emotion recognition means" is a method for recognizing a user's emotional state from their voice and facial expressions, and dynamically adjusting the suggested content and guidance methods based on that recognition.

[1591] This invention is an in-vehicle system that recommends tourist spots, restaurants, and accommodations based on the user's hobbies, preferences, and emotional state, and guides the user along the optimal route based on real-time traffic and weather information. Furthermore, this invention aims to incorporate an emotion engine to recognize the user's emotions and dynamically adjust the suggested content and guidance methods.

[1592] System Configuration

[1593] The system consists of the following main components:

[1594] 1. Input Method: This is an interface for users to input information about their hobbies and preferences. This includes voice input and touch panel input. In the case of voice input, speech recognition software (e.g., Google Speech-to-Text) is used.

[1595] 2. Generative AI Models: These are artificial intelligence models used to generate recommended destinations based on the user's interests and preferences. Natural language processing models such as BERT and GPT are used as generative AI models.

[1596] 3. Data Acquisition Method: This module collects real-time traffic and weather information. It utilizes the Google Maps API and the OpenWeatherMap API.

[1597] 4. Presentation means: A display and speaker for presenting recommended destinations and route guidance to the user visually or audibly. Speech synthesis software (e.g., TTS engine) is used for audio output.

[1598] 5. Route guidance system: This is a navigation system that calculates the optimal route to the destination selected by the user and provides real-time route guidance. Dijkstra's algorithm or the A algorithm are used as route calculation algorithms.

[1599] 6. Emotion Recognition Method: This is an engine that collects the user's voice and facial expressions through a camera and microphone and recognizes their emotional state. A face emotion analysis tool (e.g., Affectiva) is used.

[1600] Specific example

[1601] The user gets into their car and logs into the system. The terminal asks, "Hello, what do you like?" The user voice-inputs, "I like seafood and nature," and the speech recognition software converts this to text, and the terminal sends this information to the server. The server retrieves the user's hobbies and preferences from the database and generates a list of recommended destinations using a generative AI model. The prompt used is, "Based on the information that the user likes AA, please suggest appropriate tourist spots."

[1602] Based on real-time traffic and weather data collected by the server, the recommended destination list is updated and sent to the terminal. The terminal suggests, "AA Restaurant, where you can enjoy fresh seafood, and BB Park, where you can enjoy beautiful nature," and the user selects "AA Restaurant." The server calculates the optimal route and sends navigation data to the terminal. The terminal then begins guiding the user, saying, "Turn right and then left at the next traffic light."

[1603] If traffic congestion occurs during travel, the server calculates a new optimal route, and the terminal updates its guidance with a message such as, "Changing to a new route. Turn right at the next intersection." Furthermore, if the emotion engine detects user fatigue, the server adjusts its suggestions to include more relaxing destinations.

[1604] Thus, this invention combines real-time data and emotion recognition capabilities to provide optimal recommendations and route guidance tailored to the user's hobbies, preferences, and emotional state. This enables a more comfortable and efficient driving and travel experience.

[1605] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1606] Step 1:

[1607] User input of hobby and preference information

[1608] 1. The device asks the user, "Hello, what do you like?" via voice or text.

[1609] 2. The user responds with "I like seafood and nature." This input is done via voice input or touch panel operation.

[1610] 3. In the case of voice input, speech recognition software (e.g., Google Speech-to-Text) converts the speech into text data.

[1611] Input: User voice or text input

[1612] Output: Text-formatted information on hobbies and interests (e.g., "I like seafood and nature")

[1613] Operation: The device invokes speech recognition software and converts the recognition result into text.

[1614] Step 2:

[1615] Sending hobby and preference information to the server

[1616] 1. The device sends the acquired hobby and preference information to the server. Specifically, it transfers the information to the server using an HTTP request.

[1617] Input: Text-based information about hobbies and interests (e.g., "I like seafood and nature")

[1618] Output: Hobby and preference information stored in a database on the server.

[1619] Operation: The device creates an HTTP request and sends data to the server's API endpoint.

[1620] Step 3:

[1621] Generating recommended candidates using generative AI models

[1622] 1. The server retrieves hobby and preference information from the database.

[1623] 2. The server uses a generation AI model to generate a list of recommended candidates based on the user's interests and preferences. Specifically, the prompt "Based on the information that the user likes AA, please suggest appropriate tourist spots" is input to the generation AI model.

[1624] Input: Information on hobbies and preferences stored in a database on the server.

[1625] Output: List of recommended options (e.g., seafood restaurants and natural spots)

[1626] Operation: The server calls the generated AI model, takes prompts, and extracts recommended candidates.

[1627] Step 4:

[1628] Real-time data collection and list updates

[1629] 1. The server calls external APIs (e.g., Google Maps API, OpenWeatherMap API) to obtain real-time traffic and weather information.

[1630] 2. The recommended candidate list is filtered and optimized based on real-time data collected by the server.

[1631] Input: List of recommended candidates, and real-time traffic and weather information.

[1632] Output: Updated list of recommended candidates

[1633] Operation: The server sends an HTTP request to an external API, retrieves data, and updates the list of recommended candidates.

[1634] Step 5:

[1635] Sending and displaying recommended candidates to devices

[1636] 1. The server sends the updated list of recommended candidates to the terminal.

[1637] 2. The device presents the user with a list of recommended options via voice and on-screen display. For example, it might say, "AA Restaurant is a recommended seafood restaurant, and BB Park is a great spot to enjoy nature."

[1638] Input: Updated list of recommended candidates

[1639] Output: Recommended suggestions presented to the user (audio and on-screen display)

[1640] Operation: The server sends data to the terminal as an HTTP response, and the terminal presents the information using speech synthesis software and a display.

[1641] Step 6:

[1642] User-selected destination

[1643] 1. The user selects "Let's go to AA Restaurant" via their device.

[1644] 2. The terminal sends the selection information to the server.

[1645] Input: User selects destination (voice or touch operation)

[1646] Output: Selected destination information (sent to the server)

[1647] Operation: The user makes a selection on the device, and the device sends the data to the server.

[1648] Step 7:

[1649] Calculates the optimal route to the selected destination.

[1650] 1. The server calculates the optimal route based on the selected destination information, using a generated AI model and real-time data.

[1651] 2. Send navigation data to the device.

[1652] Input: Selected destination information, and real-time traffic and weather information.

[1653] Output: Navigation data (sent from server to terminal)

[1654] Operation: The server generates the optimal route using a route calculation algorithm and sends the data to the terminal.

[1655] Step 8:

[1656] Start of route guidance

[1657] 1. The device will begin providing route guidance via voice and on screen, saying, "Turn right and then turn left at the next traffic light."

[1658] Input: Navigation data

[1659] Output: Audio and screen display of route guidance.

[1660] Operation: The terminal starts providing guidance using speech synthesis software and the display based on the navigation data.

[1661] Step 9:

[1662] Responding to real-time changes in the situation

[1663] 1. The server monitors traffic conditions and weather changes in real time.

[1664] 2. Calculate a new optimal route as needed and notify the device.

[1665] 3. The terminal updates its instructions to "Changing to a new route. Turn right at the next intersection."

[1666] Input: Real-time traffic and weather information

[1667] Output: Updated navigation data and new route guidance.

[1668] Operation: The server recalculates the new optimal route based on real-time data and notifies the terminal. The terminal displays the new directions via voice and display.

[1669] Step 10:

[1670] Proposal adjustment based on emotion recognition

[1671] 1. The emotion engine recognizes the user's emotional state from their voice and facial expressions.

[1672] 2. The server adjusts recommendation lists and route guidance based on sentiment information.

[1673] 3. For example, if the user is tired, the server will suggest many relaxing destinations.

[1674] Input: User's voice and facial expression data

[1675] Output: Sentiment-based recommendation list and guidance content

[1676] Operation: The emotion engine performs sentiment analysis and sends the results to the server. The server updates the recommendations.

[1677] (Application Example 2)

[1678] 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".

[1679] While conventional in-car systems offer recommendation features based on user preferences, they lack dynamic adjustments based on emotional states. Furthermore, although they provide optimal route guidance based on real-time information, they do not update suggestions in response to changes in the user's emotions, resulting in a low degree of personalization for individual users. This leads to an insufficient user experience, particularly during long drives or trips, which reduces satisfaction.

[1680] In Application Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for inputting the user's hobby and preference information, an analysis means for generating recommended destinations based on the hobby and preference information using a generation AI model, an acquisition means for collecting real-time traffic and weather information and dynamically updating the list of recommended destinations, a presentation means for presenting the list of recommended destinations to the user through display and voice guidance, a route guidance means for calculating the optimal route to the destination selected by the user and providing route guidance, and an emotion analysis means for recognizing the user's emotional state and dynamically adjusting the suggested content and guidance method. This enables the provision of dynamic recommendations and guidance based on the user's hobby and preference and emotional state, and enables optimal route guidance in real time.

[1681] "Input method" refers to an interface for inputting information about the user's hobbies, preferences, and emotional state, and includes voice input and touch panel input.

[1682] A "generative AI model" is an analytical engine that calculates recommended destinations based on the user's interests and preferences.

[1683] The "analysis tool" is a module that uses a generative AI model to generate recommended destinations based on the user's interests and preferences.

[1684] The "acquisition method" refers to a data acquisition module that collects real-time traffic and weather information and uses it for analysis.

[1685] "Presentation means" refers to displays and speakers used to present recommended destinations and route guidance to users visually or through audio guidance.

[1686] A "route guidance system" is a navigation system that calculates the optimal route to the destination selected by the user and provides guidance in real time.

[1687] An "emotion analysis tool" is an engine that recognizes the user's emotional state from their voice and facial expressions, and dynamically adjusts the suggested content and guidance methods based on that recognition.

[1688] "Smart glasses" are wearable devices that have a display function and provide information by connecting to the internet or other devices.

[1689] "Voice guidance" is a function that provides information and instructions to users using voice output.

[1690] This system recommends tourist attractions, restaurants, and accommodations based on the user's interests, preferences, and emotional state, and guides users along the optimal route based on real-time traffic and weather information. Specific implementation details are described below.

[1691] Hardware and software to be used

[1692] Hardware:

[1693] Smart glasses: Used as both a display and a voice input device.

[1694] Smartphones: Used as auxiliary interfaces and data processing devices.

[1695] Server: Analyzes data centrally and runs the generated AI model.

[1696] software:

[1697] Generative AI model: Uses natural language processing engines such as OpenAI GPT-3.

[1698] Speech recognition module: Uses the Google Speech-to-Text API.

[1699] Traffic Information API: Uses an external API (e.g., Traffic API) to obtain traffic information.

[1700] Weather Information API: Uses an external API (e.g., OpenWeather API) to obtain the latest weather information.

[1701] The main components of the system and their operation

[1702] 1. Input method:

[1703] This is an interface for users to input information about their hobbies and preferences. Using a voice recognition module, smart glasses and smartphones accept voice input from the user.

[1704] For example, a user wears smart glasses and voice-inputs, "I like historical places and delicious food."

[1705] 2. Generative AI Models:

[1706] The server uses OpenAI GPT-3 to analyze the user's interests and preferences and generate recommended destinations.

[1707] Example of a generated prompt: "The user is interested in historical places and delicious food. What are some recommended tourist spots and restaurants?"

[1708] 3. Acquisition method:

[1709] The server collects traffic and weather information in real time and dynamically updates the list of recommended destinations.

[1710] Traffic information is obtained using the Traffic API, and weather information is obtained using the OpenWeather API.

[1711] 4. Means of presentation:

[1712] The server displays a list of recommended destinations to the user via the smart glasses' display and audio output.

[1713] For example, it might display "Recommended spots: BB Park, □□ Temple" and also provide audio guidance.

[1714] 5. Means of route guidance:

[1715] The server calculates the optimal route to the destination selected by the user and provides navigation information, updating it in real time.

[1716] The smart glasses display "Starting route guidance to □□ Temple" and provide voice guidance such as "Turn right and then left at the next traffic light."

[1717] 6. Emotion analysis means:

[1718] The server analyzes the user's voice and facial expressions to recognize their emotional state.

[1719] For example, if a user indicates they are feeling tired, the server might recommend additional places where they can relax.

[1720] Specific example:

[1721] The user puts on smart glasses and inputs "I like nature and historical places" by voice. Based on this information, the server uses a generated AI model to analyze "recommended tourist spots and restaurants" and presents a list of "BB Park" and "□□ Temple". The user then selects "I want to go to □□ Temple", the server calculates the optimal route, and the smart glasses begin providing directions. The system also analyzes the user's emotional state and, if the user is tired, suggests additional relaxing places such as "□□ Cafe".

[1722] In this way, the system can provide personalized recommendations based on the user's interests, preferences, and emotional state, along with real-time optimal route guidance.

[1723] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1724] Step 1:

[1725] The device, via smart glasses and a smartphone, asks the user a voice question: "Hello, what do you like?" The user's voice response is the input. The device sends this voice data to a speech recognition module, which converts it into text.

[1726] Step 2:

[1727] The device sends the text information (user's hobbies and preferences) converted by speech recognition to the server. The input is the user's hobbies and preferences in text form. The server receives this information and records it in its database.

[1728] Step 3:

[1729] The server uses a generation AI model to generate a list of recommended destinations based on the received hobby and preference information. The input is the user's hobby and preference information. The server creates a prompt, calls the generation AI model, and generates a list of recommended destinations. The generated list of recommended destinations is retrieved and stored for early response display.

[1730] Step 4:

[1731] The server uses an external API to obtain real-time traffic and weather information. The input is an API request for traffic and weather data. The server retrieves this information and integrates it with a generated list of recommended destinations. The output is an updated list of recommended destinations.

[1732] Step 5:

[1733] The server sends an updated list of recommended destinations to the device. The updated list of recommended destinations is the input. The device receives this list and presents it to the user via the smart glasses' display and audio output. For example, it displays and provides audio guidance such as, "Recommended spots are BB Park and □□ Temple."

[1734] Step 6:

[1735] The user selects their desired destination from a presented list. The user's selection serves as input. The terminal records this selection and sends it to the server.

[1736] Step 7:

[1737] The server calculates the optimal route to the user's selected destination. The inputs are the selected destination and real-time traffic and weather information. The server uses a generative AI model to calculate the optimal route. The output is the optimal route.

[1738] Step 8:

[1739] The server sends the optimal route to the terminal. The terminal displays "Starting route guidance to □□ Temple" on its smart glasses and provides voice guidance such as "Turn right and then left at the next traffic light." Route data is also distributed to the relevant in-vehicle system, and navigation begins.

[1740] Step 9:

[1741] The server recognizes and analyzes the user's emotional state from their voice and facial expressions. The input consists of the user's voice and facial expression data. The server uses an emotion analysis engine to analyze this data and understand the user's emotional state. The output is information about the emotional state.

[1742] Step 10:

[1743] The server dynamically adjusts suggestions and guidance methods based on the user's emotional state. The input is information about the user's emotional state. Based on this emotional state, the server, for example, if it wants to suggest a place to relax, adds "□□ Cafe" to the recommendation list and sends it to the device. The device then displays this information on smart glasses and provides voice guidance.

[1744] Step 11:

[1745] The server monitors traffic conditions and weather changes in real time and calculates a new optimal route as needed. Traffic and weather data are used as input. The server uses a generative AI model to calculate the new optimal route and sends it to the terminal. The terminal updates the display and voice guidance on smart glasses and the in-vehicle system. For example, it might say, "Changing to the new route. Turn right at the next intersection."

[1746] These specifically divided processing steps reveal the details of a system that provides dynamic recommendations and optimal route guidance based on the user's hobbies, preferences, and emotional state.

[1747] 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.

[1748] 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.

[1749] 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 robot 414.

[1750] 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.

[1751] 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.

[1752] 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.

[1753] 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.

[1754] 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.

[1755] 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."

[1756] 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.

[1757] 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.

[1758] 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.

[1759] 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.

[1760] 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.

[1761] 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.

[1762] 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.

[1763] 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.

[1764] 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.

[1765] 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.

[1766] 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 aspe...

Claims

1. An input method for entering user's hobbies and preferences, An analysis means that generates recommended destinations based on the aforementioned hobby and preference information using a generative AI model, A means for acquiring real-time traffic and weather information and dynamically updating the list of recommended destinations, A presentation means for displaying and providing voice guidance to the user the list of recommended destinations, A route guidance means that calculates the optimal route to the destination selected by the user and provides route guidance, A system that includes this.

2. The system according to claim 1, characterized in that the route guidance means updates the route guidance based on traffic conditions and weather that change in real time during travel.

3. The system according to claim 1, characterized in that the input means accepts voice input from a user, and the presentation means also uses a voice output means.

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