System

Abstract

A system is provided.SOLUTION: A system including means for receiving data related to a departure point, a destination, and a specific need from a user, means for analyzing collected user data and collecting necessary data from a related geographic information database, means for analyzing walking acceleration data of the user and a past movement history, means for calculating an optimal route by using a generated AI model, means for learning a preference and a behavior pattern of the user and reflecting the preference and the behavior pattern in a next or subsequent route proposal, means for transmitting generated optimal route information to a user terminal, and means for guiding the optimal route to the user in the user terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional navigation systems primarily propose the shortest route, but they have not been able to adequately address the diverse needs of users. As a result, in an aging society, they are unable to propose safe and comfortable routes for elderly people who have difficulty walking, to provide tourists with efficient routes to visit tourist spots, or to provide transportation companies with optimal routes that take into account the characteristics of large vehicles, resulting in inconvenience to users. The present invention aims to solve these problems and provide optimal routes that meet the diverse needs and circumstances of users. [Means for solving the problem]

[0005] The present invention is a system that includes means for receiving data regarding a starting point, a destination, and specific needs from a user, means for analyzing the collected user data and collecting necessary data from a related geographic information database, means for analyzing the user's walking acceleration data and past movement history, means for calculating an optimal route using a generative AI model, means for learning the user's preferences and behavioral patterns and reflecting them in subsequent route suggestions, means for transmitting the generated optimal route information to a user terminal, and means for guiding the user along the optimal route on the user terminal, and further includes means for continuously obtaining the user's current location in real time and dynamically recalculating the route as necessary, and means for extracting road width, slope gradient, and location information of tourist attractions when analyzing the collected geographic information data.

[0006] "User Data" is information provided by a user regarding their origin, destination, and specific needs.

[0007] A "geographic information database" is a database that contains detailed information about a region, such as the width of roads, the gradient of slopes, and the locations of tourist attractions.

[0008] "Walking acceleration data" is data measured by an acceleration sensor while the user is walking, and reflects the user's movement status.

[0009] A "generative AI model" refers to an algorithm or program that uses artificial intelligence to analyze collected data and generate optimal routes.

[0010] An "optimal route" is a travel route that is most suitable in terms of safety, efficiency, comfort, etc. based on the specific needs of the user.

[0011] "User terminal" refers to a device used by a user, such as a computer, smartphone, or tablet, that displays and provides navigation information.

[0012] "Real-time data" refers to data that reflects the latest situation, such as the user's current location information and movement status.

[0013] "Dynamic recalculation" means recalculating the optimal route based on data obtained in real time.

[0014] "Preferences and behavioral patterns" refer to the individual preferences and behavioral characteristics of a user that are obtained through the routes the user has chosen in the past, feedback, etc. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The navigation system of the present invention is designed to meet the diverse needs of users and provide them with the most suitable route. This system operates through cooperation between the server and the terminal, and provides users with a comfortable and efficient route. Below, we will create a system program and explain the flow of each process in natural language.

[0037] User Input Processing

[0038] 1. User provides input (User)

[0039] A user launches an application on the device and inputs their starting point, destination, and specific needs. For example, an elderly person might input their desire to get to city hall but avoid hills.

[0040] 2. Receiving user input (terminal)

[0041] The terminal receives the user's input data and formats it appropriately.

[0042] 3. Data transmission process

[0043] The terminal transmits the received user data to the server.

[0044] Data collection and analysis

[0045] 4. Receive user data (server)

[0046] The server receives the user data from the terminal and begins analyzing it.

[0047] 5. Access the database (server)

[0048] The server accesses a geographic information database and collects information such as road information, slope gradients, and the locations of tourist attractions.

[0049] 6. Analyze the collected data (server)

[0050] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's needs.

[0051] User situation analysis

[0052] 7. Analyze the user's situation (server)

[0053] The server analyzes the user's current state using the user's walking acceleration data and past movement history, for example, to determine whether the user is elderly or using a large vehicle.

[0054] Optimal route generation

[0055] 8. Run the route generation algorithm (server)

[0056] The server uses generative AI models to calculate optimal routes based on the user's characteristics, such as prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[0057] 9. Evaluate the generated route (server)

[0058] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[0059] Route generation and transmission

[0060] 10. Convert route data into coordinate information (server)

[0061] The server converts the optimal route into latitude and longitude coordinate information, making it usable for navigation.

[0062] 11. Learning user preferences (server)

[0063] The server learns data on user behavior and selected routes and reflects this in future route suggestions.

[0064] 12. Generate and send optimal route information (server)

[0065] The server sends the prepared route information to the terminal.

[0066] 13. Start route guidance (device)

[0067] The device provides guidance to the user based on the route information received, using map display and voice guidance to guide the user to their destination.

[0068] Real-time updates

[0069] 14. Data reception and analysis on the move (terminal and server)

[0070] The device tracks the user's current location in real time and sends it to the server, which then dynamically recalculates the route based on the latest information and updates the optimal route.

[0071] 15. Providing the latest route (terminal)

[0072] The terminal guides the user along an updated route based on the latest route information received from the server.

[0073] Specific examples

[0074] Example 1: Route for seniors

[0075] 1. User Input: An elderly user specifies that they want to get from their home to City Hall, but want to avoid hills.

[0076] 2. Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[0077] 3. Optimal route generation: The server calculates and evaluates routes that prioritize flat roads.

[0078] 4. Route guidance: The device displays a smooth and safe route and provides voice guidance.

[0079] Example 2: Tourist Route

[0080] 1. User input: A tourist inputs that he / she wants to visit tourist attractions in the area.

[0081] 2. Data collection and analysis: The server collects and analyzes information such as the location and business hours of tourist attractions.

[0082] 3. Optimal route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[0083] 4. Route guidance: The device displays the route to visit tourist attractions in the optimal order and provides guidance.

[0084] Features of this system

[0085] This navigation system provides routes tailored to the specific needs of users and proposes optimal travel routes that meet the requirements of different users, such as the elderly, tourists, and transportation workers. By utilizing a generative AI model and a geographic information database to analyze the user's walking acceleration data and movement history, route guidance optimized for each user is realized. Furthermore, by analyzing the situation in real time and dynamically updating the route, guidance based on the latest information can always be provided. This solves the issues with conventional navigation systems and enables users to travel comfortably and efficiently.

[0086] The processing flow will be explained below.

[0087] Step 1:

[0088] The terminal receives input from the user of the starting point, destination, and specific needs (e.g., avoiding hills, not wanting to use highways, etc.).

[0089] Step 2:

[0090] The terminal receives the user's input data, formats it appropriately, and sends it to the server.

[0091] Step 3:

[0092] The server receives user data from the terminal and accesses a geographic information database.

[0093] Step 4:

[0094] The server collects relevant data, such as road information, slope gradients, and location information of tourist attractions, from a geographic information database.

[0095] Step 5:

[0096] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[0097] Step 6:

[0098] The server analyzes the user's current status (e.g., elderly, large vehicle user, etc.) using the user's walking acceleration data and past movement history.

[0099] Step 7:

[0100] The server uses a generative AI model to calculate the optimal route based on the user's characteristics, for example prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[0101] Step 8:

[0102] The server evaluates the calculated route to ensure safety, efficiency and user comfort.

[0103] Step 9:

[0104] The server converts the optimal route into latitude and longitude coordinate information and formats it for navigation.

[0105] Step 10:

[0106] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[0107] Step 11:

[0108] The server transmits the generated optimum route information to the terminal.

[0109] Step 12:

[0110] The terminal receives route information from the server and provides on-screen display and audio guidance.

[0111] Step 13:

[0112] The device tracks the user's current location in real time using GPS and transmits the location information to a server.

[0113] Step 14:

[0114] The server dynamically recalculates the route if necessary based on real-time location information and sends the latest optimal route to the device.

[0115] Step 15:

[0116] The terminal keeps the user updated with directions based on the latest route information it receives.

[0117] Example 1

[0118] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0119] Current navigation systems struggle to provide optimal routes tailored to a user's specific needs and characteristics. They also lack the ability to dynamically recalculate routes based on the user's situation in real time, making them unable to respond immediately to changes during travel. Furthermore, they lack the ability to learn the user's preferences and behavioral patterns and incorporate them into future route suggestions, resulting in a lack of personalized guidance.

[0120] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0121] In this invention, the server includes means for receiving data regarding the starting point, destination, and specific needs from the user, means for arranging the received user data in an appropriate format and transmitting it to the server, means for the server to collect and analyze necessary data from an associated geographic information database, means for analyzing the user's walking acceleration data and past movement history to identify the user's characteristics, means for calculating an optimal route based on the user's characteristics using a generative AI model, means for evaluating the optimal route and confirming safety and efficiency, means for learning the user's preferences and behavioral patterns and reflecting them in subsequent route suggestions, means for converting the generated optimal route information into coordinate information and transmitting it to the user terminal, and means for providing guidance to the user based on the received route information.

[0122] This allows for optimal route provision based on the user's specific needs and characteristics, realizing dynamic route recalculation in real time based on the user's situation, and enabling personalized route suggestions based on the user's preferences and behavioral patterns.

[0123] "User" refers to a person or entity that utilizes a navigation system to input data regarding starting point, destination, and specific needs.

[0124] A "terminal" is a device that a user uses to access the navigation system, and includes a smartphone, tablet, car navigation system, etc.

[0125] The term "server" refers to a computer system that receives data sent from a user, accesses a geographic information database to calculate the optimal route, and transmits this information to the user terminal.

[0126] The "starting point" refers to the location information of the point where the user starts moving.

[0127] "Destination" refers to the location information of the point where the user wants to complete their journey.

[0128] "Specific needs" refers to conditions or requirements that the user wants to be particularly considered when traveling, and includes individual wishes such as wanting to avoid slopes or wanting to visit specific tourist spots.

[0129] A "geographic information database" refers to a database that stores geographical data such as road information, slope gradients, and the locations of tourist attractions.

[0130] "Walking acceleration data" refers to data acquired from an acceleration sensor while the user is walking, and is used to analyze the user's movement characteristics.

[0131] "Travel history" refers to historical data such as the route, time, and distance traveled by the user in the past.

[0132] "Generative AI model" refers to an artificial intelligence model used to calculate optimal routes based on user characteristics and needs.

[0133] The "optimal route" refers to the route from the user's starting point to the destination that best satisfies the user's characteristics and specific needs.

[0134] "Coordinate information" refers to latitude and longitude data that indicates a geographic location.

[0135] The "guiding means" refers to a function on the user terminal that provides the user with the optimum route visually or audibly.

[0136] "Real-time" refers to constantly tracking and updating the user's current location and status.

[0137] MODE FOR CARRYING OUT THE INVENTION

[0138] A specific embodiment of the navigation system of the present invention is shown below. This system is designed to meet the diverse needs of users and provide optimal routes. This system operates through cooperation between a server and user terminals, and provides users with comfortable and efficient travel routes.

[0139] A user launches a navigation application on their device and inputs their starting point, destination, and specific needs. For example, an elderly user might input their desire to get from their home to city hall, but avoid hills. The device receives the user's input, formats it appropriately, and transmits it to a server, typically using the HTTPS protocol.

[0140] The server receives the user data sent from the device and converts it into an analyzable format. For example, it stores the data received in JSON format in a structured database. The server then accesses a geographic information database to collect road information, slope gradients, location information of tourist attractions, etc. In this case, a general API (e.g., OpenStreetMap API) can be used to obtain the actual data.

[0141] The server extracts and analyzes information appropriate to the user's conditions based on the collected data. It also includes a phase in which the user's walking acceleration data and past movement history are used to identify the user's characteristics. This makes it possible to identify, for example, whether the user is elderly or uses a large vehicle.

[0142] The server then uses a generative AI model (such as one using TensorFlow or PyTorch) to calculate the optimal route based on the user's characteristics. Depending on the user's characteristics, the server determines whether to prioritize flat roads or roads with less traffic. The calculated route is then further evaluated using an evaluation algorithm to verify safety and efficiency.

[0143] The generated optimal route information is converted into coordinate information (e.g., latitude and longitude) and formatted for use by the navigation system. The server also has the ability to learn the user's past actions and selected routes and reflect this in future route suggestions.

[0144] The server then sends the optimized route information to the user's device, which then analyzes the received route information and starts displaying a map and providing voice guidance in real time, allowing the user to efficiently navigate from their starting point to their destination.

[0145] The system also tracks the user's current location in real time and periodically sends it to the server, allowing it to dynamically recalculate routes and provide the latest route information. Through this process, it is possible to provide optimal route guidance that meets the needs of a variety of users.

[0146] Examples of specific prompts include:

[0147] "What is the best route for an elderly person to get from their home to City Hall, but who wants to avoid hills?"

[0148] "Please tell me the most efficient route for tourists who want to visit the tourist attractions in the area."

[0149] The system's unique features include the ability to provide routes tailored to specific user needs and propose optimal travel routes tailored to the requirements of different users, such as the elderly, tourists, and transportation workers. By utilizing a generative AI model and a geographic information database, the system analyzes the user's walking acceleration data and movement history to provide route guidance optimized for each user. Furthermore, real-time situation analysis and dynamic route updates enable the system to provide guidance based on the latest information at all times.

[0150] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0151] Step 1:

[0152] A user launches a navigation application on a device and inputs their starting point, destination, and specific needs. For example, the user might input a desire to "go from home to city hall, but avoid hills." Input: User's location information and specific needs. Output: User-input data sent to the device.

[0153] Step 2:

[0154] The device receives user input data, formats it as needed, and converts it into a parsable format. For example, it converts the starting point and destination into coordinate data and analyzes it for specific needs. Input: Location information from the user and specific needs. Output: Formatted user data (e.g., JSON format).

[0155] Step 3:

[0156] The terminal sends the prepared user data to the server. At this time, the HTTPS protocol is used to ensure secure data transfer. Input: Prepared user data. Output: User data transferred to the server.

[0157] Step 4:

[0158] The server receives the user data sent from the device and converts it into an analyzable format. For example, data received in JSON format is stored in a structured database. Input: User data in JSON format. Output: User data stored in the database.

[0159] Step 5:

[0160] The server accesses the geographic information database and collects the necessary road information, slope gradients, location information of tourist attractions, etc. For example, it obtains the data using an API (e.g., OpenStreetMap API). Input: User's location information and characteristics. Output: Collected geographic information data.

[0161] Step 6:

[0162] The server analyzes the geographic information data collected and extracts information suitable for the user's conditions. For example, it extracts route information that prioritizes flat roads. Input: Collected geographic information data. Output: Geographic information suitable for the user's conditions.

[0163] Step 7:

[0164] The server analyzes the user's characteristics using the user's walking acceleration data and past movement history. For example, it can identify whether the user is elderly or uses a large vehicle. Input: Walking acceleration data and past movement history. Output: Identified user characteristics.

[0165] Step 8:

[0166] The server uses the generative AI model to calculate the optimal route based on the user's characteristics. For example, route calculations are performed using an AI model using TensorFlow or PyTorch. Input: User characteristics and geographical information data. Output: Optimal route information.

[0167] Step 9:

[0168] The server evaluates the calculated route and checks its safety and efficiency using a scoring algorithm. Input: Calculated optimal route. Output: Evaluated route score.

[0169] Step 10:

[0170] The server converts the optimal route into latitude and longitude coordinate information and formats it for navigation. For example, it converts it into GeoJSON format. Input: Optimal route information. Output: Latitude and longitude coordinate information.

[0171] Step 11:

[0172] The server updates the machine learning model to reflect the user's past behavior and selected routes in future route suggestions. Input: Past user behavior data. Output: Updated machine learning model.

[0173] Step 12:

[0174] The server sends the route information to the device. For example, it sends the route information using the HTTPS protocol. Input: Route information formatted as coordinates. Output: Route information sent to the device.

[0175] Step 13:

[0176] The device analyzes the route information received and starts displaying maps and voice guidance in real time. For example, a navigation application might display a map using the Google Maps API. Input: Received route information. Output: Guidance information for the user.

[0177] Step 14:

[0178] The device tracks the user's location in real time and periodically sends the location information to the server. Input: User's real-time location information. Output: Location data sent to the server.

[0179] Step 15:

[0180] The server dynamically recalculates the user's route based on the latest information and generates new, optimal route information. Input: Current location and updated geographical information data. Output: Recalculated optimal route information.

[0181] Step 16:

[0182] The device provides guidance based on the latest route information, helping users travel safely and efficiently. Input: Latest route information. Output: Updated guidance information.

[0183] (Application example 1)

[0184] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0185] Conventional navigation systems have been unable to adequately address diverse user needs and provide optimal routes based on specific requests. Real-time location updates and dynamic route recalculation are also limited, making it difficult to fully ensure user comfort and safety. Furthermore, there have been few systems that provide visual and audio guidance suitable for autonomous vehicles. This has resulted in inadequate navigation for users, particularly the elderly and those with special needs.

[0186] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0187] In this invention, the server includes means for receiving data on the starting point, destination, and specific requests from the user, means for analyzing the collected user data and collecting necessary data from a related geographic information database, means for analyzing the user's speed / acceleration data and past movement history, means for calculating an optimal route using a generative AI model, means for learning the user's preferences and behavioral patterns and reflecting them in subsequent route provision, means for transmitting the generated optimal route information to the user terminal, means for guiding the user along the optimal route on the user terminal, means for updating the user's location information in real time and providing an optimal route to an autonomous vehicle, means for providing information to the user through audio guidance and visual guidance, and means for dynamically recalculating the route and providing the latest route information. This allows navigation suitable for elderly users and users with specific requests to be provided, and enables always optimal route guidance through real-time location information updates and dynamic route recalculation.

[0188] "User" refers to an individual or organization that uses the System.

[0189] The "starting point" refers to the location where the user starts moving.

[0190] The "destination" refers to the final destination that the user is aiming for.

[0191] "Specific requests" refer to conditions or requirements that the user particularly desires for navigation.

[0192] A "geographic information database" refers to a database that includes geographic information such as road information, slope gradients, and the locations of tourist attractions.

[0193] "Speed ​​and acceleration data" refers to data related to the user's speed and acceleration while moving.

[0194] "Past travel history" refers to data relating to routes and places the user has previously traveled.

[0195] A "generative AI model" refers to an algorithm that uses AI technology to generate optimal routes based on the user's preferences.

[0196] "Preferences and behavioral patterns" refers to the routes and behavioral tendencies that a user has chosen in the past.

[0197] "Real-time" refers to the timing of immediate processing and provision of current information.

[0198] "Voice guidance" refers to a means of providing route guidance to the user using voice.

[0199] "Visual guidance" refers to a means of providing route guidance to a user using visual information.

[0200] "Dynamic recalculation" refers to the process of recalculating a route based on new information or changing conditions.

[0201] An "autonomous vehicle" refers to a vehicle that can drive autonomously and move without user intervention.

[0202] "Terminal" refers to a device that allows a user to input information or receive instructions.

[0203] In this invention, a system is constructed in which users, terminals, and servers work in cooperation with each other. The processing contents and specific examples of the system programs are explained below.

[0204] System configuration

[0205] 1. User: Operates a device such as a smartphone or tablet to input the starting point, destination, and specific requests.

[0206] 2. Terminal: Takes user input, formats it appropriately and sends it to the server.

[0207] 3. Server: Analyzes user data, collects and analyzes necessary data from related geographic information databases, calculates the optimal route using a generative AI model, and sends the generated optimal route information to the device.

[0208] Program processing explanation

[0209] User Input Processing

[0210] The user launches a terminal application and inputs a starting point, a destination, and any specific requests. The terminal receives this data, formats it, and sends it to the server.

[0211] Data collection and analysis

[0212] The server analyzes the received user data, accessing a geographic information database and analyzing the collected data, including road width, slope gradient, location of tourist attractions, traffic conditions, and road conditions.

[0213] User situation analysis

[0214] The server analyzes the user's current state by analyzing the user's speed and acceleration data and past movement history, and based on this analysis, provides the optimal route according to the user's specific needs.

[0215] Optimal Route Generation

[0216] The server uses a generative AI model to calculate the optimal route based on the user's characteristics, preferences, and behavioral patterns, for example prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[0217] Real-time updates

[0218] The system continuously acquires the user's current location and dynamically recalculates routes as needed, responding to sudden changes in traffic conditions and road construction, and providing the latest route information at all times.

[0219] Audio and visual guidance

[0220] The device provides users with audio and visual route guidance, improving safety and comfort.

[0221] Specific examples

[0222] Route guidance for seniors

[0223] If the user is an elderly person who wants to get from their home to city hall but wants to avoid hills, the system will provide a flat route that avoids hills.

[0224] Route guidance for tourists

[0225] If a user wishes to efficiently tour tourist attractions, the server will calculate the optimal route, taking into account the location information and opening hours of the tourist attractions.

[0226] Prompt Sentence Examples

[0227] "The starting point is home. The destination is City Hall, and I want to avoid the highway."

[0228] This invention provides a navigation system that meets the diverse needs of users and enables optimal route guidance tailored to specific requests. Real-time location information updates and dynamic route recalculation ensure safe and efficient travel based on the latest information.

[0229] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0230] Step 1:

[0231] The user launches a terminal application and inputs a starting point, a destination, and specific requests. The inputs include the coordinates of the starting point, the coordinates of the destination, and the desired conditions (e.g., avoid hills). The terminal formats this data appropriately and sends it to the server.

[0232] Step 2:

[0233] The server analyzes the user data received from the device. The input data includes the starting point, destination, and specific requests. Based on this, the server accesses a geographic information database to collect road information, slope gradients, tourist attraction locations, traffic conditions, and road conditions. The output data is the required geographic information.

[0234] Step 3:

[0235] The server analyzes the collected geographic information data and calculates the optimal route based on the specific request. As input, it receives the geographic information data collected in step 2 and the specific request entered by the user. For data processing, it uses a generative AI model to calculate the optimal route. As output, it obtains candidate optimal routes that take the specific request into account.

[0236] Step 4:

[0237] The server analyzes the user's speed and acceleration data and past movement history to identify the user's state. It receives the user's history data and real-time movement data as input. It uses an analysis algorithm to calculate the data and identify the user's current state (e.g., elderly, type of vehicle). It obtains user characteristic information as output.

[0238] Step 5:

[0239] The server further calculates the optimal route based on the user's characteristics, preferences, and behavioral patterns. As input, it receives the route candidates from step 3 and the user characteristics information from step 4. As output, it obtains the final generated optimal route information.

[0240] Step 6:

[0241] The server sends the generated optimal route information to the user terminal. The optimal route information is received as input. The route data to be sent to the user terminal is obtained as output.

[0242] Step 7:

[0243] The terminal provides route guidance to the user based on the optimal route received. Optimal route data is received from the server as input, and visual and audio route guidance is performed. Data processing involves displaying a map, visualizing the route, and generating audio guidance.

[0244] Step 8:

[0245] The device continuously tracks the user's current location and sends that location information to the server. As input, it receives the user's real-time location information. As output, it periodically sends location information to the server.

[0246] Step 9:

[0247] The server dynamically recalculates the route based on the transmitted real-time location information. It receives location information from the device as input. It recalculates the route by taking into account changes in traffic conditions and road environment as data calculations. It obtains updated optimal route information as output.

[0248] Step 10:

[0249] The terminal provides updated guidance to the user based on the latest route information received from the server. As input, it receives updated route data from the server. As output, it obtains the latest visual and audio guidance provided to the user.

[0250] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0251] This invention is a navigation system that responds to the diverse needs of users and provides optimal routes, and by combining it with an emotion engine that recognizes the user's emotions and reflects them in route guidance, it realizes a more personalized service. The specific operation of this system will be described below.

[0252] User Input Processing

[0253] 1. User provides input (User)

[0254] A user launches the application on the device and inputs their starting point, destination, and specific needs, such as an elderly person wanting to get to city hall but avoiding hills.

[0255] 2. Receiving user input (terminal)

[0256] The terminal receives user input data and transmits the appropriately formatted data to the server.

[0257] Data collection and analysis

[0258] 3. Data transmission and reception (terminal and server)

[0259] The terminal transmits user data to the server, and the server receives the data.

[0260] 4. Database Access (Server)

[0261] The server accesses a geographic information database and collects information such as road information, slope gradients, and the locations of tourist attractions.

[0262] 5. Data analysis (server)

[0263] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[0264] User situation analysis

[0265] 6. User status analysis (server)

[0266] The server analyzes the user's walking acceleration data and past movement history to identify the user's current status (e.g., elderly, large vehicle user).

[0267] Emotion recognition by emotion engine

[0268] 7. Emotion recognition data acquisition (device)

[0269] The device operates an emotion engine that recognizes the user's emotions and obtains the user's current emotional data, for example, through a facial recognition camera or voice analysis.

[0270] 8. Emotional Data Analysis (Server)

[0271] The server analyzes the user's emotion data collected by the emotion engine and reflects it in route suggestions.

[0272] Optimal route generation

[0273] 9. Route calculation (server)

[0274] The server uses a generative AI model to calculate the optimal route for the user based on the collected and analyzed data.

[0275] 10. Route Evaluation (Server)

[0276] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[0277] Personalize and send

[0278] 11. Personalization (Server)

[0279] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[0280] 12. Route information generation and transmission (server)

[0281] The server generates coordinate information for the optimal route and sends it to the terminal.

[0282] 13. Route guidance (terminal)

[0283] The device receives route information and provides users with directions, using map displays, voice guidance, and real-time location tracking.

[0284] Improved user experience for route guidance

[0285] 14. Audio guide adjustments (device)

[0286] Based on the emotional data generated by the emotion engine, the device changes the tone and content of the voice guidance to match the user's emotional state. For example, if a user is feeling anxious, the device will provide guidance in a more friendly tone.

[0287] Real-time updates

[0288] 15. Real-time data reception and updates (terminal and server)

[0289] The device tracks the user's current location in real time using GPS and sends that information to the server, which then recalculates the route as needed based on the latest information and sends the updated route information to the device.

[0290] 16. Latest route guidance (terminal)

[0291] The device continues to update the guidance based on the latest route information received.

[0292] Specific examples

[0293] Example 1: Route for seniors

[0294] 1. User input: An elderly user inputs, "I want to get from my house to city hall, avoiding slopes."

[0295] 2. Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[0296] 3. Emotion recognition: The device recognizes anxiety from the user's facial expressions.

[0297] 4. Route generation: The server calculates and evaluates routes that prioritize flat roads.

[0298] 5. Route guidance: The device displays a smooth and safe route and provides voice guidance in a friendly tone.

[0299] Example 2: Tourist Route

[0300] 1. User input: A tourist inputs, "I would like to visit tourist attractions in the area."

[0301] 2. Data collection and analysis: The server collects and analyzes information such as the location and opening hours of tourist attractions.

[0302] 3. Emotion recognition: The device recognizes excitement from the user's tone of voice.

[0303] 4. Route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[0304] 5. Route guidance: The device displays a route to visit tourist attractions in the optimal order and provides guidance in an energetic tone.

[0305] Features of this system

[0306] This navigation system provides routes tailored to the specific needs of users and suggests optimal travel routes that meet the requirements of different users, such as the elderly, tourists, and transportation workers. It also uses an emotion engine to recognize users' emotional data and provide route guidance tailored to their emotions in real time, providing a better user experience. By utilizing a generative AI model and a geographic information database to analyze users' states and emotions, it provides more personalized services and ensures comfortable and efficient travel.

[0307] The processing flow will be explained below.

[0308] Step 1:

[0309] The user starts the application on the terminal and inputs the starting point, destination, and specific needs (e.g., avoiding hills, not using highways, etc.).

[0310] Step 2:

[0311] The terminal receives the user's input data and formats it appropriately.

[0312] Step 3:

[0313] The terminal transmits the prepared user data to the server.

[0314] Step 4:

[0315] The server receives the user data from the terminal.

[0316] Step 5:

[0317] The server accesses a geographic information database and collects relevant data (e.g., road information, slope gradient, location information of tourist attractions, etc.).

[0318] Step 6:

[0319] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[0320] Step 7:

[0321] The server uses the user's walking acceleration data and past movement history to analyze the user's current state (e.g., elderly, large vehicle user).

[0322] Step 8:

[0323] The device runs an emotion engine to acquire the user's emotion data. For example, emotions are extracted from facial expressions and tone of voice using a camera or microphone.

[0324] Step 9:

[0325] The server receives and analyzes the user's emotion data collected by the emotion engine.

[0326] Step 10:

[0327] The server uses the generative AI model to calculate the optimal route based on the user's characteristics and emotional data, for example, calculating a flat route or a route that efficiently visits tourist spots.

[0328] Step 11:

[0329] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[0330] Step 12:

[0331] The server generates coordinate information for the optimal route and sends it to the terminal.

[0332] Step 13:

[0333] The terminal receives the optimal route information from the server and displays it on the screen to provide guidance to the user. Voice guidance is also provided at the same time.

[0334] Step 14:

[0335] The device tracks the user's current location in real time using GPS and sends that information to a server.

[0336] Step 15:

[0337] The server dynamically recalculates the route if necessary based on real-time location information and sends updated route information to the device.

[0338] Step 16:

[0339] The device continuously updates the guidance based on the latest route information, and adjusts the tone and content of the voice guidance based on the user's emotional state.

[0340] Specific examples

[0341] Example 1: Route for seniors

[0342] Step 1: An elderly user inputs, "I want to walk from my home to city hall, avoiding slopes."

[0343] Step 2: The terminal receives the user's input data and sends it to the server.

[0344] Step 3: The server receives the data and collects road data and slope gradient information from the geographic information database.

[0345] Step 4: The server analyzes the data and extracts information about flat roads.

[0346] Step 5: The device activates its emotion engine and recognizes anxiety from the user's facial expression.

[0347] Step 6: The server analyzes the emotion data and uses it to calculate the route.

[0348] Step 7: The server uses the generative AI model to calculate a flat route.

[0349] Step 8: The server evaluates the calculation results and sends the optimal route to the terminal.

[0350] Step 9: The device displays a flat route and provides voice directions in a friendly tone.

[0351] Example 2: Tourist Route

[0352] Step 1: The tourist enters, "I would like to visit tourist attractions in the area."

[0353] Step 2: The terminal receives the user's input data and sends it to the server.

[0354] Step 3: The server receives the data and collects the location information and business hours data of the tourist attractions.

[0355] Step 4: The server analyzes the data and extracts information for efficiently touring tourist attractions.

[0356] Step 5: The device activates its emotion engine and recognizes excitement from the user's tone of voice.

[0357] Step 6: The server analyzes the emotion data and uses it to calculate the route.

[0358] Step 7: The server uses the generative AI model to calculate an efficient route around the tourist attractions.

[0359] Step 8: The server evaluates the calculation results and sends the optimal route to the terminal.

[0360] Step 9: The device displays the optimal route and provides voice guidance in an energetic tone.

[0361] Example 2

[0362] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0363] Conventional navigation systems focus on simple route guidance based on a starting point and destination, making it difficult to provide personalized routes that take into account the user's specific needs and emotional state. Furthermore, they are unable to adequately adjust route guidance to reflect the user's current location and emotional data in real time, leaving the user experience open to improvement. Information analysis to address specific needs, such as avoiding slopes or visiting tourist attractions, is also limited.

[0364] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0365] In this invention, the server comprises means for receiving data from the user regarding the starting point, destination and specific needs;

[0366] means for analyzing the collected user data and collecting necessary data from related geographic information databases;

[0367] A means for analyzing the user's walking acceleration data and past movement history;

[0368] This allows for personalized routes that take into account the user's specific needs and emotional state.

[0369] The "starting point" is the location where the user starts their journey.

[0370] The "destination" is the final destination of the user's journey.

[0371] "Specific needs" are special requirements or desires that a user has when traveling.

[0372] "User data" refers to information such as starting point, destination, specific needs, walking acceleration data, past movement history, and emotional data.

[0373] A "geographic information database" is a collection of data that stores geographic information, including road width, slope gradient, and location information of tourist attractions.

[0374] "Walking acceleration data" is data obtained from an acceleration sensor while the user is walking.

[0375] "Past movement history" is data on the movement routes and movement patterns that the user has taken in the past.

[0376] "Emotion data" is information that indicates the user's current emotional state, and is obtained by facial expression and voice analysis, for example.

[0377] A "generative AI model" is an artificial intelligence model that makes route suggestions and predictions based on large amounts of data.

[0378] An "optimal route" is one that takes into maximum consideration the user's specific needs and emotional state, and provides an efficient, safe, and comfortable journey.

[0379] A "personalized route" is a route that is tailored based on a user's individual preferences and behavioral patterns.

[0380] "Voice guide" refers to guidance information provided by the navigation system through speech.

[0381] "Continuously obtain in real time" refers to constantly updating and obtaining the user's current location information.

[0382] "Dynamic recalculation" refers to the process of optimizing an existing route on an ongoing basis based on newly acquired data.

[0383] This invention is a navigation system that responds to various user needs and provides optimal routes. This system also realizes more personalized services by combining it with an emotion engine that recognizes the user's emotions and reflects them in route guidance.

[0384] System Overview

[0385] This system mainly operates around three elements: the server, the terminal, and the user.

[0386] 1. User Input Processing:

[0387] Users launch a navigation app on their smartphone or tablet and input their starting point, destination, and specific needs (for example, "I want to avoid hills when getting from my house to city hall").

[0388] The terminal receives user input, formats it in an appropriate format, and sends the data to the server, typically using JSON as the transmission format.

[0389] 2. Data collection and analysis:

[0390] The terminal transmits user data to the server, which receives it.

[0391] The server accesses a geographic information database (e.g., Google Maps API) to collect road information, slope gradients, and location information of tourist attractions.

[0392] The server analyzes the collected data and extracts the necessary information to address the user's specific needs.

[0393] 3. User situation analysis:

[0394] The server analyzes the user's walking acceleration data and past movement history to identify the user's current status (elderly, large vehicle user, etc.).

[0395] 4. Emotion Recognition with Emotion Engine:

[0396] The device runs an emotion recognition engine and acquires the user's emotional data (facial expressions and voice analysis).

[0397] The server analyzes the emotion data and reflects it in route suggestions.

[0398] 5. Optimal route generation:

[0399] The server uses a generative AI model (such as GPT-4) to calculate the optimal route based on the collected and analyzed data.

[0400] The server evaluates the calculated route to ensure safety, efficiency and user comfort.

[0401] 6. Personalization and Delivery:

[0402] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[0403] The server generates coordinate information for the optimal route and sends it to the terminal.

[0404] The device then provides users with directions based on the route information it receives, using map displays, voice guidance, and real-time location tracking.

[0405] 7. Improved user experience for route guidance:

[0406] Based on the emotional data, the device adjusts the tone and content of the voice guidance to match the user's emotional state, providing guidance in a friendly tone to users who are feeling anxious.

[0407] 8. Real-time updates:

[0408] The device tracks the user's current location in real time using GPS and sends that information to a server.

[0409] The server recalculates the route as needed based on the latest information and sends the updated route information to the terminal.

[0410] The device will continue to update the directions based on the latest route information it receives.

[0411] Specific examples

[0412] 1. Route for seniors:

[0413] User input: "I want to avoid hills when walking from my house to City Hall."

[0414] Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[0415] Emotion recognition: The device recognizes anxiety from the user's facial expression.

[0416] Route generation: The server calculates and evaluates routes that prioritize flat roads.

[0417] Route guidance: The device displays a smooth, safe route and provides voice guidance in a friendly tone.

[0418] 2. Tourist Route:

[0419] User input: "I want to visit tourist attractions in the area."

[0420] Data collection and analysis: The server collects and analyzes information about the location and business hours of tourist attractions.

[0421] Emotion recognition: The device recognizes excitement from the user's tone of voice.

[0422] Route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[0423] Route guidance: The device displays a route to visit tourist attractions in the optimal order and provides guidance in an energetic tone.

[0424] As described above, this navigation system can provide a better user experience by providing routes tailored to the user's specific needs and utilizing emotion recognition to provide personalized guidance in real time.

[0425] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0426] Step 1:

[0427] User provides input (User)

[0428] A user launches a navigation app and inputs their starting point, destination, and specific needs (e.g., "I want to avoid hills"). The input is entered into text boxes in a form in the app. The input data is formatted as JSON and sent to the server.

[0429] Input: Starting point, Destination, Specific needs

[0430] Output: User input data in JSON format

[0431] Step 2:

[0432] Accepting user input (terminal)

[0433] The device receives the information entered by the user and sends the data to the server. Specifically, when a button is pressed, an HTTP request is generated and the input data is transferred to the server.

[0434] Input: User-supplied data in JSON format

[0435] Output: Forwarded to the server as an HTTP request

[0436] Step 3:

[0437] Data transmission and reception (terminal and server)

[0438] The device sends user input data to the server, which receives the data and passes it to the analysis module.

[0439] Input: User-supplied data as an HTTP request

[0440] Output: Data objects available on the server

[0441] Step 4:

[0442] Database access (server)

[0443] The server accesses the geographic information database to obtain the necessary road information, slope gradients, and location information for tourist attractions. Specifically, it sends an API request to the geographic information database and passes the data obtained in response to the analysis module.

[0444] Input: User's starting and destination information

[0445] Output: Geographical information (road information, slope gradient, location information of tourist attractions)

[0446] Step 5:

[0447] Data analysis (server)

[0448] The server analyzes the collected geographical information and extracts information to meet the user's specific needs, for example, filtering road gradient information to calculate routes that avoid hills.

[0449] Input: Geographical information data

[0450] Output: Parsed route information

[0451] Step 6:

[0452] User status analysis (server)

[0453] The server analyzes the user's walking acceleration data and past movement history to determine the user's current state, and inputs this data into a machine learning model to determine whether the user is elderly or a wheelchair user.

[0454] Input: Acceleration data during walking, past movement history

[0455] Output: User characteristics data (elderly, wheelchair users, etc.)

[0456] Step 7:

[0457] Emotion recognition data acquisition (device)

[0458] The device activates an emotion recognition engine to obtain user emotional data through facial expression and voice analysis, and uses the camera and microphone to capture the user's emotional state in real time.

[0459] Input: The user's current facial expression and voice data

[0460] Output: Retrieved emotion data

[0461] Step 8:

[0462] Emotion data analysis (server)

[0463] The server analyzes the acquired emotion data to identify the user's current emotional state. The emotion engine inputs the acquired data into multiple emotion models and identifies the user's emotion based on the results.

[0464] Input: Emotion data

[0465] Output: Parsed emotional state

[0466] Step 9:

[0467] Route calculation (server)

[0468] The server uses the generative AI model to calculate the optimal route based on the analyzed data. Specifically, the server inputs the prompt "Please provide the optimal route if the user wants to go from home to city hall while avoiding slopes" into the generative AI model and obtains the calculation result.

[0469] Input: Parsed user data and prompt statements

[0470] Output: Optimal route

[0471] Step 10:

[0472] Route Evaluation (Server)

[0473] The server evaluates the calculated routes to check safety, efficiency, and user comfort, assigns a score based on the evaluation criteria, and selects the best route.

[0474] Input: Optimal route suggestions

[0475] Output: Evaluated route

[0476] Step 11:

[0477] Personalization (Server)

[0478] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions. The learning module analyzes the user's past data and updates the personalized model.

[0479] Input: User's past behavior data

[0480] Output: A trained personalized model

[0481] Step 12:

[0482] Route information generation and transmission (server)

[0483] The server generates coordinate information for the optimal route and sends it to the device. The route data is converted to JSON format and transferred to the device as an HTTP response.

[0484] Input: Evaluated route information

[0485] Output: Route data in JSON format

[0486] Step 13:

[0487] Route guidance (terminal)

[0488] The device provides the user with directions based on the received route information, using map display and voice guidance to provide real-time location tracking and guidance to the user.

[0489] Input: Route data in JSON format

[0490] Output: Map display, voice guidance

[0491] Step 14:

[0492] Audio guide adjustments (device)

[0493] The device adjusts the tone and content of the voice guidance to match the user's emotional state based on the emotion data, providing guidance in a friendly tone to an anxious user and guidance in an energetic tone to an excited user.

[0494] Input: Parsed emotional state data

[0495] Output: Adjusted voice prompts

[0496] Step 15:

[0497] Real-time data reception and updates (terminal and server)

[0498] The device tracks the user's current location in real time using GPS and sends that information to the server, which then recalculates the route as needed based on the latest information and sends the updated route information to the device.

[0499] Input: Real-time location of the user

[0500] Output: Updated route information

[0501] Step 16:

[0502] Latest route guidance (terminal)

[0503] The device continuously updates its guidance based on the latest route information received, providing users with the latest information and helping them reach their destination safely and efficiently.

[0504] Input: Updated route information

[0505] Output: Updated map display, voice guidance

[0506] (Application example 2)

[0507] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0508] Conventional navigation systems have difficulty providing optimal route guidance to users because they are unable to fully reflect the user's specific needs and real-time emotional state. Furthermore, existing systems do not adapt voice guidance to reflect the user's emotions, and personalized services are not provided. This creates a need for reducing stress during travel and increasing user satisfaction.

[0509] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving data regarding the starting point, destination, and specific needs from the user, means for analyzing the collected user data and collecting necessary data from a related geographic information database, means for calculating an optimal route using a generative AI model, means for acquiring the user's emotional state through facial expression recognition and voice analysis, and means for adjusting the tone and content of audio guidance to suit the user based on the emotional state. This enables optimal route guidance based on the user's specific needs and emotional state, and allows for the provision of personalized, advanced navigation services.

[0510] A "user" is a person who uses the navigation system.

[0511] The "starting point" is the location where the user begins their journey.

[0512] A "destination" is a location that a user wishes to reach.

[0513] "Specific needs" refers to special requirements or desires that a user has while traveling.

[0514] "Means" refers to a method or apparatus for achieving a specific function or operation.

[0515] "Walking acceleration data" is acceleration information acquired while the user is walking.

[0516] "Past travel history" is a record of the routes and places the user has traveled to so far.

[0517] A "generative AI model" is an artificial intelligence model that calculates optimal routes based on large amounts of data.

[0518] "User preferences and behavioral patterns" is data that indicates the movement and preference trends that the user has shown in the past.

[0519] "Transmit" is the act of sending data to another device or system.

[0520] A "user terminal" is a device that can be directly operated by a user.

[0521] "Guidance" refers to providing information to guide the user in a specific direction.

[0522] "Facial expression recognition" is a technology that uses cameras and sensors to analyze a user's facial expressions.

[0523] "Voice analysis" is a technology that analyzes voice data to identify a user's emotions and intentions.

[0524] "Emotional state" refers to the emotional state that the user is currently feeling.

[0525] "Audio guidance" is a method of providing instructions and information to a user using audio.

[0526] "Tone" refers to the pitch and texture of a voice.

[0527] The present invention is a navigation system that provides an optimal route taking into account the specific needs and emotional state of the user. The system is composed of a server and a user terminal.

[0528] User device capabilities:

[0529] The user terminal has the function of receiving data from the user regarding the starting point, destination, and specific needs. It also has the function of obtaining the user's emotional state through facial expression recognition and voice analysis. The user terminal appropriately formats this data and transmits it to the server. At the same time, the user terminal receives the optimal route information transmitted from the server and provides guidance to the user. The guidance also includes the function of changing the tone and content of the voice guidance according to the user's emotional state.

[0530] Server capabilities:

[0531] The server receives and analyzes the data sent from the user's device. First, it accesses a geographic information database to collect the necessary data. Then, it uses a generative AI model to calculate the optimal route, taking into account the user's specific needs and emotional state. It also has the ability to learn the user's preferences and behavioral patterns and reflect them in future route suggestions. The calculated optimal route information is then sent back to the user's device.

[0532] Examples of hardware and software used:

[0533] Smartphones and tablets: Used for user input and display.

[0534] Camera and microphone: Used for facial expression recognition and voice analysis to capture emotional state.

[0535] GPS system: Used to track your location and update your route in real time.

[0536] Python-based application: Used to execute the entire program logic.

[0537] HTTP Requests library (requests): Used to send and receive data.

[0538] Generative AI models: used to calculate optimal routes and generate personalized suggestions.

[0539] Examples:

[0540] The user (driver) opens a smartphone app and inputs the "optimal route from home to work," as well as specific needs and emotions such as "wanting to avoid traffic jams" or "wanting to relax." The app sends this data to a server, which uses a generative AI model to calculate the optimal route. The server then selects the optimal route and an appropriate voice guide (relaxing tone) and provides it to the self-driving vehicle.

[0541] Example prompt sentence:

[0542] "Write Python code for a navigation system for a self-driving car that recognizes emotions and suggests the best route. The user inputs their starting point, destination, specific needs, and emotion. Provide a safe and efficient route, including voice guidance based on the emotion."

[0543] This allows for optimal route guidance based on the user's specific needs and emotional state, providing a highly personalized navigation service.

[0544] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0545] Step 1:

[0546] The user enters the starting point, destination, and specific needs into the text input fields and launches the terminal application. The user then inputs their current location, destination, and specific needs, such as "I want to avoid traffic jams and relax," into the application. The input data is saved in the application as starting point, destination, and specific needs data.

[0547] Step 2:

[0548] The device uses a facial expression recognition camera and voice analysis functions to obtain the user's emotional data. When the user turns their face to the camera or issues a voice command, these devices analyze the user's current emotion (e.g., relaxed, excited, anxious, etc.) and store it as emotional data. The analyzed emotional data is then used to provide personalized guidance.

[0549] Step 3:

[0550] The device sends the user's input data and acquired emotional data to the server. The data sent includes the starting point, destination, specific needs, and emotional data. The device formats this data appropriately and sends it to the server using an HTTP request. This data is converted into a data format that the server can easily receive.

[0551] Step 4:

[0552] The server analyzes the received data and accesses the relevant geographic information database to collect the necessary data. The server retrieves geographic information from the database, including road information between the starting point and the destination, slope gradients, location information of tourist attractions, etc. The server collects this data and begins the analysis process.

[0553] Step 5:

[0554] The server analyzes the collected geographic information data and uses a generative AI model to calculate the optimal route based on the user's specific needs and emotional state. The AI ​​model generates the optimal travel route based on the collected data and the user's requests, and selects information suitable for route guidance. The calculated optimal route data is then provided to the user in the next step.

[0555] Step 6:

[0556] The server evaluates the calculated route information to ensure safety, efficiency, and user comfort. The evaluation process checks whether the generated route is suitable for the user's specific needs and emotional state. The evaluated route data is then ready to be sent to the user's device.

[0557] Step 7:

[0558] The server simultaneously transmits the coordinate information of the optimal route, as well as the appropriate tone and content of the voice guidance. This is generated based on the user's emotional data. For example, a user who wants to relax will be provided with a voice guidance in a calm tone. This information is sent from the server to the user's terminal.

[0559] Step 8:

[0560] The device displays the received route information and audio guide, and provides audio guidance. The device displays the optimal route on a map and supports the user's travel. It also plays audio guidance according to the user's emotional state and gives instructions in real time while traveling. The user travels based on this information.

[0561] Step 9:

[0562] The device tracks the user's current location in real time using GPS and sends that information to the server. The server dynamically recalculates the route as needed based on this current location information. The recalculated route information is sent to the user's device, which immediately updates the guidance. This ensures that the user is always guided along the most up-to-date, optimal route.

[0563] The above processing steps result in an advanced navigation service that responds to the user's specific needs and emotional state.

[0564] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0565] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0566] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0567] [Second embodiment]

[0568] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0569] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0570] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0571] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0572] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0573] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0574] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0575] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0576] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0577] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0578] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0579] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0580] The navigation system of the present invention is designed to meet the diverse needs of users and provide them with the most suitable route. This system operates through cooperation between the server and the terminal, and provides users with a comfortable and efficient route. Below, we will create a system program and explain the flow of each process in natural language.

[0581] User Input Processing

[0582] 1. User provides input (User)

[0583] A user launches an application on the device and inputs their starting point, destination, and specific needs. For example, an elderly person might input their desire to get to city hall but avoid hills.

[0584] 2. Receiving user input (terminal)

[0585] The terminal receives the user's input data and formats it appropriately.

[0586] 3. Data transmission process

[0587] The terminal transmits the received user data to the server.

[0588] Data collection and analysis

[0589] 4. Receive user data (server)

[0590] The server receives the user data from the terminal and begins analyzing it.

[0591] 5. Access the database (server)

[0592] The server accesses a geographic information database and collects information such as road information, slope gradients, and the locations of tourist attractions.

[0593] 6. Analyze the collected data (server)

[0594] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's needs.

[0595] User situation analysis

[0596] 7. Analyze the user's situation (server)

[0597] The server analyzes the user's current state using the user's walking acceleration data and past movement history, for example, to determine whether the user is elderly or using a large vehicle.

[0598] Optimal route generation

[0599] 8. Run the route generation algorithm (server)

[0600] The server uses generative AI models to calculate optimal routes based on the user's characteristics, such as prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[0601] 9. Evaluate the generated route (server)

[0602] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[0603] Route generation and transmission

[0604] 10. Convert route data into coordinate information (server)

[0605] The server converts the optimal route into latitude and longitude coordinate information, making it usable for navigation.

[0606] 11. Learning user preferences (server)

[0607] The server learns data on user behavior and selected routes and reflects this in future route suggestions.

[0608] 12. Generate and send optimal route information (server)

[0609] The server sends the prepared route information to the terminal.

[0610] 13. Start route guidance (device)

[0611] The device provides guidance to the user based on the route information received, using map display and voice guidance to guide the user to their destination.

[0612] Real-time updates

[0613] 14. Data reception and analysis on the move (terminal and server)

[0614] The device tracks the user's current location in real time and sends it to the server, which then dynamically recalculates the route based on the latest information and updates the optimal route.

[0615] 15. Providing the latest route (terminal)

[0616] The terminal guides the user along an updated route based on the latest route information received from the server.

[0617] Specific examples

[0618] Example 1: Route for seniors

[0619] 1. User Input: An elderly user specifies that they want to get from their home to City Hall, but want to avoid hills.

[0620] 2. Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[0621] 3. Optimal route generation: The server calculates and evaluates routes that prioritize flat roads.

[0622] 4. Route guidance: The device displays a smooth and safe route and provides voice guidance.

[0623] Example 2: Tourist Route

[0624] 1. User input: A tourist inputs that he / she wants to visit tourist attractions in the area.

[0625] 2. Data collection and analysis: The server collects and analyzes information such as the location and business hours of tourist attractions.

[0626] 3. Optimal route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[0627] 4. Route guidance: The device displays the route to visit tourist attractions in the optimal order and provides guidance.

[0628] Features of this system

[0629] This navigation system provides routes tailored to the specific needs of users and proposes optimal travel routes that meet the requirements of different users, such as the elderly, tourists, and transportation workers. By utilizing a generative AI model and a geographic information database to analyze the user's walking acceleration data and movement history, route guidance optimized for each user is realized. Furthermore, by analyzing the situation in real time and dynamically updating the route, guidance based on the latest information can always be provided. This solves the issues with conventional navigation systems and enables users to travel comfortably and efficiently.

[0630] The processing flow will be explained below.

[0631] Step 1:

[0632] The terminal receives input from the user of the starting point, destination, and specific needs (e.g., avoiding hills, not wanting to use highways, etc.).

[0633] Step 2:

[0634] The terminal receives the user's input data, formats it appropriately, and sends it to the server.

[0635] Step 3:

[0636] The server receives user data from the terminal and accesses a geographic information database.

[0637] Step 4:

[0638] The server collects relevant data, such as road information, slope gradients, and location information of tourist attractions, from a geographic information database.

[0639] Step 5:

[0640] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[0641] Step 6:

[0642] The server analyzes the user's current status (e.g., elderly, large vehicle user, etc.) using the user's walking acceleration data and past movement history.

[0643] Step 7:

[0644] The server uses a generative AI model to calculate the optimal route based on the user's characteristics, for example prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[0645] Step 8:

[0646] The server evaluates the calculated route to ensure safety, efficiency and user comfort.

[0647] Step 9:

[0648] The server converts the optimal route into latitude and longitude coordinate information and formats it for navigation.

[0649] Step 10:

[0650] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[0651] Step 11:

[0652] The server transmits the generated optimum route information to the terminal.

[0653] Step 12:

[0654] The terminal receives route information from the server and provides on-screen display and audio guidance.

[0655] Step 13:

[0656] The device tracks the user's current location in real time using GPS and transmits the location information to a server.

[0657] Step 14:

[0658] The server dynamically recalculates the route if necessary based on real-time location information and sends the latest optimal route to the device.

[0659] Step 15:

[0660] The terminal keeps the user updated with directions based on the latest route information it receives.

[0661] Example 1

[0662] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0663] Current navigation systems struggle to provide optimal routes tailored to a user's specific needs and characteristics. They also lack the ability to dynamically recalculate routes based on the user's situation in real time, making them unable to respond immediately to changes during travel. Furthermore, they lack the ability to learn the user's preferences and behavioral patterns and incorporate them into future route suggestions, resulting in a lack of personalized guidance.

[0664] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0665] In this invention, the server includes means for receiving data regarding the starting point, destination, and specific needs from the user, means for arranging the received user data in an appropriate format and transmitting it to the server, means for the server to collect and analyze necessary data from an associated geographic information database, means for analyzing the user's walking acceleration data and past movement history to identify the user's characteristics, means for calculating an optimal route based on the user's characteristics using a generative AI model, means for evaluating the optimal route and confirming safety and efficiency, means for learning the user's preferences and behavioral patterns and reflecting them in subsequent route suggestions, means for converting the generated optimal route information into coordinate information and transmitting it to the user terminal, and means for providing guidance to the user based on the received route information.

[0666] This allows for optimal route provision based on the user's specific needs and characteristics, realizing dynamic route recalculation in real time based on the user's situation, and enabling personalized route suggestions based on the user's preferences and behavioral patterns.

[0667] "User" refers to a person or entity that utilizes a navigation system to input data regarding starting point, destination, and specific needs.

[0668] A "terminal" is a device that a user uses to access the navigation system, and includes a smartphone, tablet, car navigation system, etc.

[0669] The term "server" refers to a computer system that receives data sent from a user, accesses a geographic information database to calculate the optimal route, and transmits this information to the user terminal.

[0670] The "starting point" refers to the location information of the point where the user starts moving.

[0671] "Destination" refers to the location information of the point where the user wants to complete their journey.

[0672] "Specific needs" refers to conditions or requirements that the user wants to be particularly considered when traveling, and includes individual wishes such as wanting to avoid slopes or wanting to visit specific tourist spots.

[0673] A "geographic information database" refers to a database that stores geographical data such as road information, slope gradients, and the locations of tourist attractions.

[0674] "Walking acceleration data" refers to data acquired from an acceleration sensor while the user is walking, and is used to analyze the user's movement characteristics.

[0675] "Travel history" refers to historical data such as the route, time, and distance traveled by the user in the past.

[0676] "Generative AI model" refers to an artificial intelligence model used to calculate optimal routes based on user characteristics and needs.

[0677] The "optimal route" refers to the route from the user's starting point to the destination that best satisfies the user's characteristics and specific needs.

[0678] "Coordinate information" refers to latitude and longitude data that indicates a geographic location.

[0679] The "guiding means" refers to a function on the user terminal that provides the user with the optimum route visually or audibly.

[0680] "Real-time" refers to constantly tracking and updating the user's current location and status.

[0681] MODE FOR CARRYING OUT THE INVENTION

[0682] A specific embodiment of the navigation system of the present invention is shown below. This system is designed to meet the diverse needs of users and provide optimal routes. This system operates through cooperation between a server and user terminals, and provides users with comfortable and efficient travel routes.

[0683] A user launches a navigation application on their device and inputs their starting point, destination, and specific needs. For example, an elderly user might input their desire to get from their home to city hall, but avoid hills. The device receives the user's input, formats it appropriately, and transmits it to a server, typically using the HTTPS protocol.

[0684] The server receives the user data sent from the device and converts it into an analyzable format. For example, it stores the data received in JSON format in a structured database. The server then accesses a geographic information database to collect road information, slope gradients, location information of tourist attractions, etc. In this case, a general API (e.g., OpenStreetMap API) can be used to obtain the actual data.

[0685] The server extracts and analyzes information appropriate to the user's conditions based on the collected data. It also includes a phase in which the user's walking acceleration data and past movement history are used to identify the user's characteristics. This makes it possible to identify, for example, whether the user is elderly or uses a large vehicle.

[0686] The server then uses a generative AI model (such as one using TensorFlow or PyTorch) to calculate the optimal route based on the user's characteristics. Depending on the user's characteristics, the server determines whether to prioritize flat roads or roads with less traffic. The calculated route is then further evaluated using an evaluation algorithm to verify safety and efficiency.

[0687] The generated optimal route information is converted into coordinate information (e.g., latitude and longitude) and formatted for use by the navigation system. The server also has the ability to learn the user's past actions and selected routes and reflect this in future route suggestions.

[0688] The server then sends the optimized route information to the user's device, which then analyzes the received route information and starts displaying a map and providing voice guidance in real time, allowing the user to efficiently navigate from their starting point to their destination.

[0689] The system also tracks the user's current location in real time and periodically sends it to the server, allowing it to dynamically recalculate routes and provide the latest route information. Through this process, it is possible to provide optimal route guidance that meets the needs of a variety of users.

[0690] Examples of specific prompts include:

[0691] "What is the best route for an elderly person to get from their home to City Hall, but who wants to avoid hills?"

[0692] "Please tell me the most efficient route for tourists who want to visit the tourist attractions in the area."

[0693] The system's unique features include the ability to provide routes tailored to specific user needs and propose optimal travel routes tailored to the requirements of different users, such as the elderly, tourists, and transportation workers. By utilizing a generative AI model and a geographic information database, the system analyzes the user's walking acceleration data and movement history to provide route guidance optimized for each user. Furthermore, real-time situation analysis and dynamic route updates enable the system to provide guidance based on the latest information at all times.

[0694] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0695] Step 1:

[0696] A user launches a navigation application on a device and inputs their starting point, destination, and specific needs. For example, the user might input a desire to "go from home to city hall, but avoid hills." Input: User's location information and specific needs. Output: User-input data sent to the device.

[0697] Step 2:

[0698] The device receives user input data, formats it as needed, and converts it into a parsable format. For example, it converts the starting point and destination into coordinate data and analyzes it for specific needs. Input: Location information from the user and specific needs. Output: Formatted user data (e.g., JSON format).

[0699] Step 3:

[0700] The terminal sends the prepared user data to the server. At this time, the HTTPS protocol is used to ensure secure data transfer. Input: Prepared user data. Output: User data transferred to the server.

[0701] Step 4:

[0702] The server receives the user data sent from the device and converts it into an analyzable format. For example, data received in JSON format is stored in a structured database. Input: User data in JSON format. Output: User data stored in the database.

[0703] Step 5:

[0704] The server accesses the geographic information database and collects the necessary road information, slope gradients, location information of tourist attractions, etc. For example, it obtains the data using an API (e.g., OpenStreetMap API). Input: User's location information and characteristics. Output: Collected geographic information data.

[0705] Step 6:

[0706] The server analyzes the geographic information data collected and extracts information suitable for the user's conditions. For example, it extracts route information that prioritizes flat roads. Input: Collected geographic information data. Output: Geographic information suitable for the user's conditions.

[0707] Step 7:

[0708] The server analyzes the user's characteristics using the user's walking acceleration data and past movement history. For example, it can identify whether the user is elderly or uses a large vehicle. Input: Walking acceleration data and past movement history. Output: Identified user characteristics.

[0709] Step 8:

[0710] The server uses the generative AI model to calculate the optimal route based on the user's characteristics. For example, route calculations are performed using an AI model using TensorFlow or PyTorch. Input: User characteristics and geographical information data. Output: Optimal route information.

[0711] Step 9:

[0712] The server evaluates the calculated route and checks its safety and efficiency using a scoring algorithm. Input: Calculated optimal route. Output: Evaluated route score.

[0713] Step 10:

[0714] The server converts the optimal route into latitude and longitude coordinate information and formats it for navigation. For example, it converts it into GeoJSON format. Input: Optimal route information. Output: Latitude and longitude coordinate information.

[0715] Step 11:

[0716] The server updates the machine learning model to reflect the user's past behavior and selected routes in future route suggestions. Input: Past user behavior data. Output: Updated machine learning model.

[0717] Step 12:

[0718] The server sends the route information to the device. For example, it sends the route information using the HTTPS protocol. Input: Route information formatted as coordinates. Output: Route information sent to the device.

[0719] Step 13:

[0720] The device analyzes the route information received and starts displaying maps and voice guidance in real time. For example, a navigation application might display a map using the Google Maps API. Input: Received route information. Output: Guidance information for the user.

[0721] Step 14:

[0722] The device tracks the user's location in real time and periodically sends the location information to the server. Input: User's real-time location information. Output: Location data sent to the server.

[0723] Step 15:

[0724] The server dynamically recalculates the user's route based on the latest information and generates new, optimal route information. Input: Current location and updated geographical information data. Output: Recalculated optimal route information.

[0725] Step 16:

[0726] The device provides guidance based on the latest route information, helping users travel safely and efficiently. Input: Latest route information. Output: Updated guidance information.

[0727] (Application example 1)

[0728] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0729] Conventional navigation systems have been unable to adequately address diverse user needs and provide optimal routes based on specific requests. Real-time location updates and dynamic route recalculation are also limited, making it difficult to fully ensure user comfort and safety. Furthermore, there have been few systems that provide visual and audio guidance suitable for autonomous vehicles. This has resulted in inadequate navigation for users, particularly the elderly and those with special needs.

[0730] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0731] In this invention, the server includes means for receiving data on the starting point, destination, and specific requests from the user, means for analyzing the collected user data and collecting necessary data from a related geographic information database, means for analyzing the user's speed / acceleration data and past movement history, means for calculating an optimal route using a generative AI model, means for learning the user's preferences and behavioral patterns and reflecting them in subsequent route provision, means for transmitting the generated optimal route information to the user terminal, means for guiding the user along the optimal route on the user terminal, means for updating the user's location information in real time and providing an optimal route to an autonomous vehicle, means for providing information to the user through audio guidance and visual guidance, and means for dynamically recalculating the route and providing the latest route information. This allows navigation suitable for elderly users and users with specific requests to be provided, and enables always optimal route guidance through real-time location information updates and dynamic route recalculation.

[0732] "User" refers to an individual or organization that uses the System.

[0733] The "starting point" refers to the location where the user starts moving.

[0734] The "destination" refers to the final destination that the user is aiming for.

[0735] "Specific requests" refer to conditions or requirements that the user particularly desires for navigation.

[0736] A "geographic information database" refers to a database that includes geographic information such as road information, slope gradients, and the locations of tourist attractions.

[0737] "Speed ​​and acceleration data" refers to data related to the user's speed and acceleration while moving.

[0738] "Past travel history" refers to data relating to routes and places the user has previously traveled.

[0739] A "generative AI model" refers to an algorithm that uses AI technology to generate optimal routes based on the user's preferences.

[0740] "Preferences and behavioral patterns" refers to the routes and behavioral tendencies that a user has chosen in the past.

[0741] "Real-time" refers to the timing of immediate processing and provision of current information.

[0742] "Voice guidance" refers to a means of providing route guidance to the user using voice.

[0743] "Visual guidance" refers to a means of providing route guidance to a user using visual information.

[0744] "Dynamic recalculation" refers to the process of recalculating a route based on new information or changing conditions.

[0745] An "autonomous vehicle" refers to a vehicle that can drive autonomously and move without user intervention.

[0746] "Terminal" refers to a device that allows a user to input information or receive instructions.

[0747] In this invention, a system is constructed in which users, terminals, and servers work in cooperation with each other. The processing contents and specific examples of the system programs are explained below.

[0748] System configuration

[0749] 1. User: Operates a device such as a smartphone or tablet to input the starting point, destination, and specific requests.

[0750] 2. Terminal: Takes user input, formats it appropriately and sends it to the server.

[0751] 3. Server: Analyzes user data, collects and analyzes necessary data from related geographic information databases, calculates the optimal route using a generative AI model, and sends the generated optimal route information to the device.

[0752] Program processing explanation

[0753] User Input Processing

[0754] The user launches a terminal application and inputs a starting point, a destination, and any specific requests. The terminal receives this data, formats it, and sends it to the server.

[0755] Data collection and analysis

[0756] The server analyzes the received user data, accessing a geographic information database and analyzing the collected data, including road width, slope gradient, location of tourist attractions, traffic conditions, and road conditions.

[0757] User situation analysis

[0758] The server analyzes the user's current state by analyzing the user's speed and acceleration data and past movement history, and based on this analysis, provides the optimal route according to the user's specific needs.

[0759] Optimal Route Generation

[0760] The server uses a generative AI model to calculate the optimal route based on the user's characteristics, preferences, and behavioral patterns, for example prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[0761] Real-time updates

[0762] The system continuously acquires the user's current location and dynamically recalculates routes as needed, responding to sudden changes in traffic conditions and road construction, and providing the latest route information at all times.

[0763] Audio and visual guidance

[0764] The device provides users with audio and visual route guidance, improving safety and comfort.

[0765] Specific examples

[0766] Route guidance for seniors

[0767] If the user is an elderly person who wants to get from their home to city hall but wants to avoid hills, the system will provide a flat route that avoids hills.

[0768] Route guidance for tourists

[0769] If a user wishes to efficiently tour tourist attractions, the server will calculate the optimal route, taking into account the location information and opening hours of the tourist attractions.

[0770] Prompt Sentence Examples

[0771] "The starting point is home. The destination is City Hall, and I want to avoid the highway."

[0772] This invention provides a navigation system that meets the diverse needs of users and enables optimal route guidance tailored to specific requests. Real-time location information updates and dynamic route recalculation ensure safe and efficient travel based on the latest information.

[0773] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0774] Step 1:

[0775] The user launches a terminal application and inputs a starting point, a destination, and specific requests. The inputs include the coordinates of the starting point, the coordinates of the destination, and the desired conditions (e.g., avoid hills). The terminal formats this data appropriately and sends it to the server.

[0776] Step 2:

[0777] The server analyzes the user data received from the device. The input data includes the starting point, destination, and specific requests. Based on this, the server accesses a geographic information database to collect road information, slope gradients, tourist attraction locations, traffic conditions, and road conditions. The output data is the required geographic information.

[0778] Step 3:

[0779] The server analyzes the collected geographic information data and calculates the optimal route based on the specific request. As input, it receives the geographic information data collected in step 2 and the specific request entered by the user. For data processing, it uses a generative AI model to calculate the optimal route. As output, it obtains candidate optimal routes that take the specific request into account.

[0780] Step 4:

[0781] The server analyzes the user's speed and acceleration data and past movement history to identify the user's state. It receives the user's history data and real-time movement data as input. It uses an analysis algorithm to calculate the data and identify the user's current state (e.g., elderly, type of vehicle). It obtains user characteristic information as output.

[0782] Step 5:

[0783] The server further calculates the optimal route based on the user's characteristics, preferences, and behavioral patterns. As input, it receives the route candidates from step 3 and the user characteristics information from step 4. As output, it obtains the final generated optimal route information.

[0784] Step 6:

[0785] The server sends the generated optimal route information to the user terminal. The optimal route information is received as input. The route data to be sent to the user terminal is obtained as output.

[0786] Step 7:

[0787] The terminal provides route guidance to the user based on the optimal route received. Optimal route data is received from the server as input, and visual and audio route guidance is performed. Data processing involves displaying a map, visualizing the route, and generating audio guidance.

[0788] Step 8:

[0789] The device continuously tracks the user's current location and sends that location information to the server. As input, it receives the user's real-time location information. As output, it periodically sends location information to the server.

[0790] Step 9:

[0791] The server dynamically recalculates the route based on the transmitted real-time location information. It receives location information from the device as input. It recalculates the route by taking into account changes in traffic conditions and road environment as data calculations. It obtains updated optimal route information as output.

[0792] Step 10:

[0793] The terminal provides updated guidance to the user based on the latest route information received from the server. As input, it receives updated route data from the server. As output, it obtains the latest visual and audio guidance provided to the user.

[0794] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0795] This invention is a navigation system that responds to the diverse needs of users and provides optimal routes, and by combining it with an emotion engine that recognizes the user's emotions and reflects them in route guidance, it realizes a more personalized service. The specific operation of this system will be described below.

[0796] User Input Processing

[0797] 1. User provides input (User)

[0798] A user launches the application on the device and inputs their starting point, destination, and specific needs, such as an elderly person wanting to get to city hall but avoiding hills.

[0799] 2. Receiving user input (terminal)

[0800] The terminal receives user input data and transmits the appropriately formatted data to the server.

[0801] Data collection and analysis

[0802] 3. Data transmission and reception (terminal and server)

[0803] The terminal transmits user data to the server, and the server receives the data.

[0804] 4. Database Access (Server)

[0805] The server accesses a geographic information database and collects information such as road information, slope gradients, and the locations of tourist attractions.

[0806] 5. Data analysis (server)

[0807] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[0808] User situation analysis

[0809] 6. User status analysis (server)

[0810] The server analyzes the user's walking acceleration data and past movement history to identify the user's current status (e.g., elderly, large vehicle user).

[0811] Emotion recognition by emotion engine

[0812] 7. Emotion recognition data acquisition (device)

[0813] The device operates an emotion engine that recognizes the user's emotions and obtains the user's current emotional data, for example, through a facial recognition camera or voice analysis.

[0814] 8. Emotional Data Analysis (Server)

[0815] The server analyzes the user's emotion data collected by the emotion engine and reflects it in route suggestions.

[0816] Optimal route generation

[0817] 9. Route calculation (server)

[0818] The server uses a generative AI model to calculate the optimal route for the user based on the collected and analyzed data.

[0819] 10. Route Evaluation (Server)

[0820] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[0821] Personalize and send

[0822] 11. Personalization (Server)

[0823] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[0824] 12. Route information generation and transmission (server)

[0825] The server generates coordinate information for the optimal route and sends it to the terminal.

[0826] 13. Route guidance (terminal)

[0827] The device receives route information and provides users with directions, using map displays, voice guidance, and real-time location tracking.

[0828] Improved user experience for route guidance

[0829] 14. Audio guide adjustments (device)

[0830] Based on the emotional data generated by the emotion engine, the device changes the tone and content of the voice guidance to match the user's emotional state. For example, if a user is feeling anxious, the device will provide guidance in a more friendly tone.

[0831] Real-time updates

[0832] 15. Real-time data reception and updates (terminal and server)

[0833] The device tracks the user's current location in real time using GPS and sends that information to the server, which then recalculates the route as needed based on the latest information and sends the updated route information to the device.

[0834] 16. Latest route guidance (terminal)

[0835] The device continues to update the guidance based on the latest route information received.

[0836] Specific examples

[0837] Example 1: Route for seniors

[0838] 1. User input: An elderly user inputs, "I want to get from my house to city hall, avoiding slopes."

[0839] 2. Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[0840] 3. Emotion recognition: The device recognizes anxiety from the user's facial expressions.

[0841] 4. Route generation: The server calculates and evaluates routes that prioritize flat roads.

[0842] 5. Route guidance: The device displays a smooth and safe route and provides voice guidance in a friendly tone.

[0843] Example 2: Tourist Route

[0844] 1. User input: A tourist inputs, "I would like to visit tourist attractions in the area."

[0845] 2. Data collection and analysis: The server collects and analyzes information such as the location and opening hours of tourist attractions.

[0846] 3. Emotion recognition: The device recognizes excitement from the user's tone of voice.

[0847] 4. Route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[0848] 5. Route guidance: The device displays a route to visit tourist attractions in the optimal order and provides guidance in an energetic tone.

[0849] Features of this system

[0850] This navigation system provides routes tailored to the specific needs of users and suggests optimal travel routes that meet the requirements of different users, such as the elderly, tourists, and transportation workers. It also uses an emotion engine to recognize users' emotional data and provide route guidance tailored to their emotions in real time, providing a better user experience. By utilizing a generative AI model and a geographic information database to analyze users' states and emotions, it provides more personalized services and ensures comfortable and efficient travel.

[0851] The processing flow will be explained below.

[0852] Step 1:

[0853] The user starts the application on the terminal and inputs the starting point, destination, and specific needs (e.g., avoiding hills, not using highways, etc.).

[0854] Step 2:

[0855] The terminal receives the user's input data and formats it appropriately.

[0856] Step 3:

[0857] The terminal transmits the prepared user data to the server.

[0858] Step 4:

[0859] The server receives the user data from the terminal.

[0860] Step 5:

[0861] The server accesses a geographic information database and collects relevant data (e.g., road information, slope gradient, location information of tourist attractions, etc.).

[0862] Step 6:

[0863] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[0864] Step 7:

[0865] The server uses the user's walking acceleration data and past movement history to analyze the user's current state (e.g., elderly, large vehicle user).

[0866] Step 8:

[0867] The device runs an emotion engine to acquire the user's emotion data. For example, emotions are extracted from facial expressions and tone of voice using a camera or microphone.

[0868] Step 9:

[0869] The server receives and analyzes the user's emotion data collected by the emotion engine.

[0870] Step 10:

[0871] The server uses the generative AI model to calculate the optimal route based on the user's characteristics and emotional data, for example, calculating a flat route or a route that efficiently visits tourist spots.

[0872] Step 11:

[0873] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[0874] Step 12:

[0875] The server generates coordinate information for the optimal route and sends it to the terminal.

[0876] Step 13:

[0877] The terminal receives the optimal route information from the server and displays it on the screen to provide guidance to the user. Voice guidance is also provided at the same time.

[0878] Step 14:

[0879] The device tracks the user's current location in real time using GPS and sends that information to a server.

[0880] Step 15:

[0881] The server dynamically recalculates the route if necessary based on real-time location information and sends updated route information to the device.

[0882] Step 16:

[0883] The device continuously updates the guidance based on the latest route information, and adjusts the tone and content of the voice guidance based on the user's emotional state.

[0884] Specific examples

[0885] Example 1: Route for seniors

[0886] Step 1: An elderly user inputs, "I want to walk from my home to city hall, avoiding slopes."

[0887] Step 2: The terminal receives the user's input data and sends it to the server.

[0888] Step 3: The server receives the data and collects road data and slope gradient information from the geographic information database.

[0889] Step 4: The server analyzes the data and extracts information about flat roads.

[0890] Step 5: The device activates its emotion engine and recognizes anxiety from the user's facial expression.

[0891] Step 6: The server analyzes the emotion data and uses it to calculate the route.

[0892] Step 7: The server uses the generative AI model to calculate a flat route.

[0893] Step 8: The server evaluates the calculation results and sends the optimal route to the terminal.

[0894] Step 9: The device displays a flat route and provides voice directions in a friendly tone.

[0895] Example 2: Tourist Route

[0896] Step 1: The tourist enters, "I would like to visit tourist attractions in the area."

[0897] Step 2: The terminal receives the user's input data and sends it to the server.

[0898] Step 3: The server receives the data and collects the location information and business hours data of the tourist attractions.

[0899] Step 4: The server analyzes the data and extracts information for efficiently touring tourist attractions.

[0900] Step 5: The device activates its emotion engine and recognizes excitement from the user's tone of voice.

[0901] Step 6: The server analyzes the emotion data and uses it to calculate the route.

[0902] Step 7: The server uses the generative AI model to calculate an efficient route around the tourist attractions.

[0903] Step 8: The server evaluates the calculation results and sends the optimal route to the terminal.

[0904] Step 9: The device displays the optimal route and provides voice guidance in an energetic tone.

[0905] Example 2

[0906] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0907] Conventional navigation systems focus on simple route guidance based on a starting point and destination, making it difficult to provide personalized routes that take into account the user's specific needs and emotional state. Furthermore, they are unable to adequately adjust route guidance to reflect the user's current location and emotional data in real time, leaving the user experience open to improvement. Information analysis to address specific needs, such as avoiding slopes or visiting tourist attractions, is also limited.

[0908] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0909] In this invention, the server comprises means for receiving data from the user regarding the starting point, destination and specific needs;

[0910] means for analyzing the collected user data and collecting necessary data from related geographic information databases;

[0911] A means for analyzing the user's walking acceleration data and past movement history;

[0912] This allows for personalized routes that take into account the user's specific needs and emotional state.

[0913] The "starting point" is the location where the user starts their journey.

[0914] The "destination" is the final destination of the user's journey.

[0915] "Specific needs" are special requirements or desires that a user has when traveling.

[0916] "User data" refers to information such as starting point, destination, specific needs, walking acceleration data, past movement history, and emotional data.

[0917] A "geographic information database" is a collection of data that stores geographic information, including road width, slope gradient, and location information of tourist attractions.

[0918] "Walking acceleration data" is data obtained from an acceleration sensor while the user is walking.

[0919] "Past movement history" is data on the movement routes and movement patterns that the user has taken in the past.

[0920] "Emotion data" is information that indicates the user's current emotional state, and is obtained by facial expression and voice analysis, for example.

[0921] A "generative AI model" is an artificial intelligence model that makes route suggestions and predictions based on large amounts of data.

[0922] An "optimal route" is one that takes into maximum consideration the user's specific needs and emotional state, and provides an efficient, safe, and comfortable journey.

[0923] A "personalized route" is a route that is tailored based on a user's individual preferences and behavioral patterns.

[0924] "Voice guide" refers to guidance information provided by the navigation system through speech.

[0925] "Continuously obtain in real time" refers to constantly updating and obtaining the user's current location information.

[0926] "Dynamic recalculation" refers to the process of optimizing an existing route on an ongoing basis based on newly acquired data.

[0927] This invention is a navigation system that responds to various user needs and provides optimal routes. This system also realizes more personalized services by combining it with an emotion engine that recognizes the user's emotions and reflects them in route guidance.

[0928] System Overview

[0929] This system mainly operates around three elements: the server, the terminal, and the user.

[0930] 1. User Input Processing:

[0931] Users launch a navigation app on their smartphone or tablet and input their starting point, destination, and specific needs (for example, "I want to avoid hills when getting from my house to city hall").

[0932] The terminal receives user input, formats it in an appropriate format, and sends the data to the server, typically using JSON as the transmission format.

[0933] 2. Data collection and analysis:

[0934] The terminal transmits user data to the server, which receives it.

[0935] The server accesses a geographic information database (e.g., Google Maps API) to collect road information, slope gradients, and location information of tourist attractions.

[0936] The server analyzes the collected data and extracts the necessary information to address the user's specific needs.

[0937] 3. User situation analysis:

[0938] The server analyzes the user's walking acceleration data and past movement history to identify the user's current status (elderly, large vehicle user, etc.).

[0939] 4. Emotion Recognition with Emotion Engine:

[0940] The device runs an emotion recognition engine and acquires the user's emotional data (facial expressions and voice analysis).

[0941] The server analyzes the emotion data and reflects it in route suggestions.

[0942] 5. Optimal route generation:

[0943] The server uses a generative AI model (such as GPT-4) to calculate the optimal route based on the collected and analyzed data.

[0944] The server evaluates the calculated route to ensure safety, efficiency and user comfort.

[0945] 6. Personalization and Delivery:

[0946] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[0947] The server generates coordinate information for the optimal route and sends it to the terminal.

[0948] The device then provides users with directions based on the route information it receives, using map displays, voice guidance, and real-time location tracking.

[0949] 7. Improved user experience for route guidance:

[0950] Based on the emotional data, the device adjusts the tone and content of the voice guidance to match the user's emotional state, providing guidance in a friendly tone to users who are feeling anxious.

[0951] 8. Real-time updates:

[0952] The device tracks the user's current location in real time using GPS and sends that information to a server.

[0953] The server recalculates the route as needed based on the latest information and sends the updated route information to the terminal.

[0954] The device will continue to update the directions based on the latest route information it receives.

[0955] Specific examples

[0956] 1. Route for seniors:

[0957] User input: "I want to avoid hills when walking from my house to City Hall."

[0958] Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[0959] Emotion recognition: The device recognizes anxiety from the user's facial expression.

[0960] Route generation: The server calculates and evaluates routes that prioritize flat roads.

[0961] Route guidance: The device displays a smooth, safe route and provides voice guidance in a friendly tone.

[0962] 2. Tourist Route:

[0963] User input: "I want to visit tourist attractions in the area."

[0964] Data collection and analysis: The server collects and analyzes information about the location and business hours of tourist attractions.

[0965] Emotion recognition: The device recognizes excitement from the user's tone of voice.

[0966] Route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[0967] Route guidance: The device displays a route to visit tourist attractions in the optimal order and provides guidance in an energetic tone.

[0968] As described above, this navigation system can provide a better user experience by providing routes tailored to the user's specific needs and utilizing emotion recognition to provide personalized guidance in real time.

[0969] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0970] Step 1:

[0971] User provides input (User)

[0972] A user launches a navigation app and inputs their starting point, destination, and specific needs (e.g., "I want to avoid hills"). The input is entered into text boxes in a form in the app. The input data is formatted as JSON and sent to the server.

[0973] Input: Starting point, Destination, Specific needs

[0974] Output: User input data in JSON format

[0975] Step 2:

[0976] Accepting user input (terminal)

[0977] The device receives the information entered by the user and sends the data to the server. Specifically, when a button is pressed, an HTTP request is generated and the input data is transferred to the server.

[0978] Input: User-supplied data in JSON format

[0979] Output: Forwarded to the server as an HTTP request

[0980] Step 3:

[0981] Data transmission and reception (terminal and server)

[0982] The device sends user input data to the server, which receives the data and passes it to the analysis module.

[0983] Input: User-supplied data as an HTTP request

[0984] Output: Data objects available on the server

[0985] Step 4:

[0986] Database access (server)

[0987] The server accesses the geographic information database to obtain the necessary road information, slope gradients, and location information for tourist attractions. Specifically, it sends an API request to the geographic information database and passes the data obtained in response to the analysis module.

[0988] Input: User's starting and destination information

[0989] Output: Geographical information (road information, slope gradient, location information of tourist attractions)

[0990] Step 5:

[0991] Data analysis (server)

[0992] The server analyzes the collected geographical information and extracts information to meet the user's specific needs, for example, filtering road gradient information to calculate routes that avoid hills.

[0993] Input: Geographical information data

[0994] Output: Parsed route information

[0995] Step 6:

[0996] User status analysis (server)

[0997] The server analyzes the user's walking acceleration data and past movement history to determine the user's current state, and inputs this data into a machine learning model to determine whether the user is elderly or a wheelchair user.

[0998] Input: Acceleration data during walking, past movement history

[0999] Output: User characteristics data (elderly, wheelchair users, etc.)

[1000] Step 7:

[1001] Emotion recognition data acquisition (device)

[1002] The device activates an emotion recognition engine to obtain user emotional data through facial expression and voice analysis, and uses the camera and microphone to capture the user's emotional state in real time.

[1003] Input: The user's current facial expression and voice data

[1004] Output: Retrieved emotion data

[1005] Step 8:

[1006] Emotion data analysis (server)

[1007] The server analyzes the acquired emotion data to identify the user's current emotional state. The emotion engine inputs the acquired data into multiple emotion models and identifies the user's emotion based on the results.

[1008] Input: Emotion data

[1009] Output: Parsed emotional state

[1010] Step 9:

[1011] Route calculation (server)

[1012] The server uses the generative AI model to calculate the optimal route based on the analyzed data. Specifically, the server inputs the prompt "Please provide the optimal route if the user wants to go from home to city hall while avoiding slopes" into the generative AI model and obtains the calculation result.

[1013] Input: Parsed user data and prompt statements

[1014] Output: Optimal route

[1015] Step 10:

[1016] Route Evaluation (Server)

[1017] The server evaluates the calculated routes to check safety, efficiency, and user comfort, assigns a score based on the evaluation criteria, and selects the best route.

[1018] Input: Optimal route suggestions

[1019] Output: Evaluated route

[1020] Step 11:

[1021] Personalization (Server)

[1022] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions. The learning module analyzes the user's past data and updates the personalized model.

[1023] Input: User's past behavior data

[1024] Output: A trained personalized model

[1025] Step 12:

[1026] Route information generation and transmission (server)

[1027] The server generates coordinate information for the optimal route and sends it to the device. The route data is converted to JSON format and transferred to the device as an HTTP response.

[1028] Input: Evaluated route information

[1029] Output: Route data in JSON format

[1030] Step 13:

[1031] Route guidance (terminal)

[1032] The device provides the user with directions based on the received route information, using map display and voice guidance to provide real-time location tracking and guidance to the user.

[1033] Input: Route data in JSON format

[1034] Output: Map display, voice guidance

[1035] Step 14:

[1036] Audio guide adjustments (device)

[1037] The device adjusts the tone and content of the voice guidance to match the user's emotional state based on the emotion data, providing guidance in a friendly tone to an anxious user and guidance in an energetic tone to an excited user.

[1038] Input: Parsed emotional state data

[1039] Output: Adjusted voice prompts

[1040] Step 15:

[1041] Real-time data reception and updates (terminal and server)

[1042] The device tracks the user's current location in real time using GPS and sends that information to the server, which then recalculates the route as needed based on the latest information and sends the updated route information to the device.

[1043] Input: Real-time location of the user

[1044] Output: Updated route information

[1045] Step 16:

[1046] Latest route guidance (terminal)

[1047] The device continuously updates its guidance based on the latest route information received, providing users with the latest information and helping them reach their destination safely and efficiently.

[1048] Input: Updated route information

[1049] Output: Updated map display, voice guidance

[1050] (Application example 2)

[1051] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1052] Conventional navigation systems have difficulty providing optimal route guidance to users because they are unable to fully reflect the user's specific needs and real-time emotional state. Furthermore, existing systems do not adapt voice guidance to reflect the user's emotions, and personalized services are not provided. This creates a need for reducing stress during travel and increasing user satisfaction.

[1053] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving data regarding the starting point, destination, and specific needs from the user, means for analyzing the collected user data and collecting necessary data from a related geographic information database, means for calculating an optimal route using a generative AI model, means for acquiring the user's emotional state through facial expression recognition and voice analysis, and means for adjusting the tone and content of audio guidance to suit the user based on the emotional state. This enables optimal route guidance based on the user's specific needs and emotional state, and allows for the provision of personalized, advanced navigation services.

[1054] A "user" is a person who uses the navigation system.

[1055] The "starting point" is the location where the user begins their journey.

[1056] A "destination" is a location that a user wishes to reach.

[1057] "Specific needs" refers to special requirements or desires that a user has while traveling.

[1058] "Means" refers to a method or apparatus for achieving a specific function or operation.

[1059] "Walking acceleration data" is acceleration information acquired while the user is walking.

[1060] "Past travel history" is a record of the routes and places the user has traveled to so far.

[1061] A "generative AI model" is an artificial intelligence model that calculates optimal routes based on large amounts of data.

[1062] "User preferences and behavioral patterns" is data that indicates the movement and preference trends that the user has shown in the past.

[1063] "Transmit" is the act of sending data to another device or system.

[1064] A "user terminal" is a device that can be directly operated by a user.

[1065] "Guidance" refers to providing information to guide the user in a specific direction.

[1066] "Facial expression recognition" is a technology that uses cameras and sensors to analyze a user's facial expressions.

[1067] "Voice analysis" is a technology that analyzes voice data to identify a user's emotions and intentions.

[1068] "Emotional state" refers to the emotional state that the user is currently feeling.

[1069] "Audio guidance" is a method of providing instructions and information to a user using audio.

[1070] "Tone" refers to the pitch and texture of a voice.

[1071] The present invention is a navigation system that provides an optimal route taking into account the specific needs and emotional state of the user. The system is composed of a server and a user terminal.

[1072] User device capabilities:

[1073] The user terminal has the function of receiving data from the user regarding the starting point, destination, and specific needs. It also has the function of obtaining the user's emotional state through facial expression recognition and voice analysis. The user terminal appropriately formats this data and transmits it to the server. At the same time, the user terminal receives the optimal route information transmitted from the server and provides guidance to the user. The guidance also includes the function of changing the tone and content of the voice guidance according to the user's emotional state.

[1074] Server capabilities:

[1075] The server receives and analyzes the data sent from the user's device. First, it accesses a geographic information database to collect the necessary data. Then, it uses a generative AI model to calculate the optimal route, taking into account the user's specific needs and emotional state. It also has the ability to learn the user's preferences and behavioral patterns and reflect them in future route suggestions. The calculated optimal route information is then sent back to the user's device.

[1076] Examples of hardware and software used:

[1077] Smartphones and tablets: Used for user input and display.

[1078] Camera and microphone: Used for facial expression recognition and voice analysis to capture emotional state.

[1079] GPS system: Used to track your location and update your route in real time.

[1080] Python-based application: Used to execute the entire program logic.

[1081] HTTP Requests library (requests): Used to send and receive data.

[1082] Generative AI models: used to calculate optimal routes and generate personalized suggestions.

[1083] Examples:

[1084] The user (driver) opens a smartphone app and inputs the "optimal route from home to work," as well as specific needs and emotions such as "wanting to avoid traffic jams" or "wanting to relax." The app sends this data to a server, which uses a generative AI model to calculate the optimal route. The server then selects the optimal route and an appropriate voice guide (relaxing tone) and provides it to the self-driving vehicle.

[1085] Example prompt sentence:

[1086] "Write Python code for a navigation system for a self-driving car that recognizes emotions and suggests the best route. The user inputs their starting point, destination, specific needs, and emotion. Provide a safe and efficient route, including voice guidance based on the emotion."

[1087] This allows for optimal route guidance based on the user's specific needs and emotional state, providing a highly personalized navigation service.

[1088] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1089] Step 1:

[1090] The user enters the starting point, destination, and specific needs into the text input fields and launches the terminal application. The user then inputs their current location, destination, and specific needs, such as "I want to avoid traffic jams and relax," into the application. The input data is saved in the application as starting point, destination, and specific needs data.

[1091] Step 2:

[1092] The device uses a facial expression recognition camera and voice analysis functions to obtain the user's emotional data. When the user turns their face to the camera or issues a voice command, these devices analyze the user's current emotion (e.g., relaxed, excited, anxious, etc.) and store it as emotional data. The analyzed emotional data is then used to provide personalized guidance.

[1093] Step 3:

[1094] The device sends the user's input data and acquired emotional data to the server. The data sent includes the starting point, destination, specific needs, and emotional data. The device formats this data appropriately and sends it to the server using an HTTP request. This data is converted into a data format that the server can easily receive.

[1095] Step 4:

[1096] The server analyzes the received data and accesses the relevant geographic information database to collect the necessary data. The server retrieves geographic information from the database, including road information between the starting point and the destination, slope gradients, location information of tourist attractions, etc. The server collects this data and begins the analysis process.

[1097] Step 5:

[1098] The server analyzes the collected geographic information data and uses a generative AI model to calculate the optimal route based on the user's specific needs and emotional state. The AI ​​model generates the optimal travel route based on the collected data and the user's requests, and selects information suitable for route guidance. The calculated optimal route data is then provided to the user in the next step.

[1099] Step 6:

[1100] The server evaluates the calculated route information to ensure safety, efficiency, and user comfort. The evaluation process checks whether the generated route is suitable for the user's specific needs and emotional state. The evaluated route data is then ready to be sent to the user's device.

[1101] Step 7:

[1102] The server simultaneously transmits the coordinate information of the optimal route, as well as the appropriate tone and content of the voice guidance. This is generated based on the user's emotional data. For example, a user who wants to relax will be provided with a voice guidance in a calm tone. This information is sent from the server to the user's terminal.

[1103] Step 8:

[1104] The device displays the received route information and audio guide, and provides audio guidance. The device displays the optimal route on a map and supports the user's travel. It also plays audio guidance according to the user's emotional state and gives instructions in real time while traveling. The user travels based on this information.

[1105] Step 9:

[1106] The device tracks the user's current location in real time using GPS and sends that information to the server. The server dynamically recalculates the route as needed based on this current location information. The recalculated route information is sent to the user's device, which immediately updates the guidance. This ensures that the user is always guided along the most up-to-date, optimal route.

[1107] The above processing steps result in an advanced navigation service that responds to the user's specific needs and emotional state.

[1108] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1109] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1110] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1111] [Third embodiment]

[1112] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1113] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1114] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1115] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1116] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1117] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1118] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1119] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1120] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1121] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1122] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1123] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1124] The navigation system of the present invention is designed to meet the diverse needs of users and provide them with the most suitable route. This system operates through cooperation between the server and the terminal, and provides users with a comfortable and efficient route. Below, we will create a system program and explain the flow of each process in natural language.

[1125] User Input Processing

[1126] 1. User provides input (User)

[1127] A user launches an application on the device and inputs their starting point, destination, and specific needs. For example, an elderly person might input their desire to get to city hall but avoid hills.

[1128] 2. Receiving user input (terminal)

[1129] The terminal receives the user's input data and formats it appropriately.

[1130] 3. Data transmission process

[1131] The terminal transmits the received user data to the server.

[1132] Data collection and analysis

[1133] 4. Receive user data (server)

[1134] The server receives the user data from the terminal and begins analyzing it.

[1135] 5. Access the database (server)

[1136] The server accesses a geographic information database and collects information such as road information, slope gradients, and the locations of tourist attractions.

[1137] 6. Analyze the collected data (server)

[1138] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's needs.

[1139] User situation analysis

[1140] 7. Analyze the user's situation (server)

[1141] The server analyzes the user's current state using the user's walking acceleration data and past movement history, for example, to determine whether the user is elderly or using a large vehicle.

[1142] Optimal route generation

[1143] 8. Run the route generation algorithm (server)

[1144] The server uses generative AI models to calculate optimal routes based on the user's characteristics, such as prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[1145] 9. Evaluate the generated route (server)

[1146] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[1147] Route generation and transmission

[1148] 10. Convert route data into coordinate information (server)

[1149] The server converts the optimal route into latitude and longitude coordinate information, making it usable for navigation.

[1150] 11. Learning user preferences (server)

[1151] The server learns data on user behavior and selected routes and reflects this in future route suggestions.

[1152] 12. Generate and send optimal route information (server)

[1153] The server sends the prepared route information to the terminal.

[1154] 13. Start route guidance (device)

[1155] The device provides guidance to the user based on the route information received, using map display and voice guidance to guide the user to their destination.

[1156] Real-time updates

[1157] 14. Data reception and analysis on the move (terminal and server)

[1158] The device tracks the user's current location in real time and sends it to the server, which then dynamically recalculates the route based on the latest information and updates the optimal route.

[1159] 15. Providing the latest route (terminal)

[1160] The terminal guides the user along an updated route based on the latest route information received from the server.

[1161] Specific examples

[1162] Example 1: Route for seniors

[1163] 1. User Input: An elderly user specifies that they want to get from their home to City Hall, but want to avoid hills.

[1164] 2. Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[1165] 3. Optimal route generation: The server calculates and evaluates routes that prioritize flat roads.

[1166] 4. Route guidance: The device displays a smooth and safe route and provides voice guidance.

[1167] Example 2: Tourist Route

[1168] 1. User input: A tourist inputs that he / she wants to visit tourist attractions in the area.

[1169] 2. Data collection and analysis: The server collects and analyzes information such as the location and business hours of tourist attractions.

[1170] 3. Optimal route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[1171] 4. Route guidance: The device displays the route to visit tourist attractions in the optimal order and provides guidance.

[1172] Features of this system

[1173] This navigation system provides routes tailored to the specific needs of users and proposes optimal travel routes that meet the requirements of different users, such as the elderly, tourists, and transportation workers. By utilizing a generative AI model and a geographic information database to analyze the user's walking acceleration data and movement history, route guidance optimized for each user is realized. Furthermore, by analyzing the situation in real time and dynamically updating the route, guidance based on the latest information can always be provided. This solves the issues with conventional navigation systems and enables users to travel comfortably and efficiently.

[1174] The processing flow will be explained below.

[1175] Step 1:

[1176] The terminal receives input from the user of the starting point, destination, and specific needs (e.g., avoiding hills, not wanting to use highways, etc.).

[1177] Step 2:

[1178] The terminal receives the user's input data, formats it appropriately, and sends it to the server.

[1179] Step 3:

[1180] The server receives user data from the terminal and accesses a geographic information database.

[1181] Step 4:

[1182] The server collects relevant data, such as road information, slope gradients, and location information of tourist attractions, from a geographic information database.

[1183] Step 5:

[1184] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[1185] Step 6:

[1186] The server analyzes the user's current status (e.g., elderly, large vehicle user, etc.) using the user's walking acceleration data and past movement history.

[1187] Step 7:

[1188] The server uses a generative AI model to calculate the optimal route based on the user's characteristics, for example prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[1189] Step 8:

[1190] The server evaluates the calculated route to ensure safety, efficiency and user comfort.

[1191] Step 9:

[1192] The server converts the optimal route into latitude and longitude coordinate information and formats it for navigation.

[1193] Step 10:

[1194] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[1195] Step 11:

[1196] The server transmits the generated optimum route information to the terminal.

[1197] Step 12:

[1198] The terminal receives route information from the server and provides on-screen display and audio guidance.

[1199] Step 13:

[1200] The device tracks the user's current location in real time using GPS and transmits the location information to a server.

[1201] Step 14:

[1202] The server dynamically recalculates the route if necessary based on real-time location information and sends the latest optimal route to the device.

[1203] Step 15:

[1204] The terminal keeps the user updated with directions based on the latest route information it receives.

[1205] Example 1

[1206] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1207] Current navigation systems struggle to provide optimal routes tailored to a user's specific needs and characteristics. They also lack the ability to dynamically recalculate routes based on the user's situation in real time, making them unable to respond immediately to changes during travel. Furthermore, they lack the ability to learn the user's preferences and behavioral patterns and incorporate them into future route suggestions, resulting in a lack of personalized guidance.

[1208] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1209] In this invention, the server includes means for receiving data regarding the starting point, destination, and specific needs from the user, means for arranging the received user data in an appropriate format and transmitting it to the server, means for the server to collect and analyze necessary data from an associated geographic information database, means for analyzing the user's walking acceleration data and past movement history to identify the user's characteristics, means for calculating an optimal route based on the user's characteristics using a generative AI model, means for evaluating the optimal route and confirming safety and efficiency, means for learning the user's preferences and behavioral patterns and reflecting them in subsequent route suggestions, means for converting the generated optimal route information into coordinate information and transmitting it to the user terminal, and means for providing guidance to the user based on the received route information.

[1210] This allows for optimal route provision based on the user's specific needs and characteristics, realizing dynamic route recalculation in real time based on the user's situation, and enabling personalized route suggestions based on the user's preferences and behavioral patterns.

[1211] "User" refers to a person or entity that utilizes a navigation system to input data regarding starting point, destination, and specific needs.

[1212] A "terminal" is a device that a user uses to access the navigation system, and includes a smartphone, tablet, car navigation system, etc.

[1213] The term "server" refers to a computer system that receives data sent from a user, accesses a geographic information database to calculate the optimal route, and transmits this information to the user terminal.

[1214] The "starting point" refers to the location information of the point where the user starts moving.

[1215] "Destination" refers to the location information of the point where the user wants to complete their journey.

[1216] "Specific needs" refers to conditions or requirements that the user wants to be particularly considered when traveling, and includes individual wishes such as wanting to avoid slopes or wanting to visit specific tourist spots.

[1217] A "geographic information database" refers to a database that stores geographical data such as road information, slope gradients, and the locations of tourist attractions.

[1218] "Walking acceleration data" refers to data acquired from an acceleration sensor while the user is walking, and is used to analyze the user's movement characteristics.

[1219] "Travel history" refers to historical data such as the route, time, and distance traveled by the user in the past.

[1220] "Generative AI model" refers to an artificial intelligence model used to calculate optimal routes based on user characteristics and needs.

[1221] The "optimal route" refers to the route from the user's starting point to the destination that best satisfies the user's characteristics and specific needs.

[1222] "Coordinate information" refers to latitude and longitude data that indicates a geographic location.

[1223] The "guiding means" refers to a function on the user terminal that provides the user with the optimum route visually or audibly.

[1224] "Real-time" refers to constantly tracking and updating the user's current location and status.

[1225] MODE FOR CARRYING OUT THE INVENTION

[1226] A specific embodiment of the navigation system of the present invention is shown below. This system is designed to meet the diverse needs of users and provide optimal routes. This system operates through cooperation between a server and user terminals, and provides users with comfortable and efficient travel routes.

[1227] A user launches a navigation application on their device and inputs their starting point, destination, and specific needs. For example, an elderly user might input their desire to get from their home to city hall, but avoid hills. The device receives the user's input, formats it appropriately, and transmits it to a server, typically using the HTTPS protocol.

[1228] The server receives the user data sent from the device and converts it into an analyzable format. For example, it stores the data received in JSON format in a structured database. The server then accesses a geographic information database to collect road information, slope gradients, location information of tourist attractions, etc. In this case, a general API (e.g., OpenStreetMap API) can be used to obtain the actual data.

[1229] The server extracts and analyzes information appropriate to the user's conditions based on the collected data. It also includes a phase in which the user's walking acceleration data and past movement history are used to identify the user's characteristics. This makes it possible to identify, for example, whether the user is elderly or uses a large vehicle.

[1230] The server then uses a generative AI model (such as one using TensorFlow or PyTorch) to calculate the optimal route based on the user's characteristics. Depending on the user's characteristics, the server determines whether to prioritize flat roads or roads with less traffic. The calculated route is then further evaluated using an evaluation algorithm to verify safety and efficiency.

[1231] The generated optimal route information is converted into coordinate information (e.g., latitude and longitude) and formatted for use by the navigation system. The server also has the ability to learn the user's past actions and selected routes and reflect this in future route suggestions.

[1232] The server then sends the optimized route information to the user's device, which then analyzes the received route information and starts displaying a map and providing voice guidance in real time, allowing the user to efficiently navigate from their starting point to their destination.

[1233] The system also tracks the user's current location in real time and periodically sends it to the server, allowing it to dynamically recalculate routes and provide the latest route information. Through this process, it is possible to provide optimal route guidance that meets the needs of a variety of users.

[1234] Examples of specific prompts include:

[1235] "What is the best route for an elderly person to get from their home to City Hall, but who wants to avoid hills?"

[1236] "Please tell me the most efficient route for tourists who want to visit the tourist attractions in the area."

[1237] The system's unique features include the ability to provide routes tailored to specific user needs and propose optimal travel routes tailored to the requirements of different users, such as the elderly, tourists, and transportation workers. By utilizing a generative AI model and a geographic information database, the system analyzes the user's walking acceleration data and movement history to provide route guidance optimized for each user. Furthermore, real-time situation analysis and dynamic route updates enable the system to provide guidance based on the latest information at all times.

[1238] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1239] Step 1:

[1240] A user launches a navigation application on a device and inputs their starting point, destination, and specific needs. For example, the user might input a desire to "go from home to city hall, but avoid hills." Input: User's location information and specific needs. Output: User-input data sent to the device.

[1241] Step 2:

[1242] The device receives user input data, formats it as needed, and converts it into a parsable format. For example, it converts the starting point and destination into coordinate data and analyzes it for specific needs. Input: Location information from the user and specific needs. Output: Formatted user data (e.g., JSON format).

[1243] Step 3:

[1244] The terminal sends the prepared user data to the server. At this time, the HTTPS protocol is used to ensure secure data transfer. Input: Prepared user data. Output: User data transferred to the server.

[1245] Step 4:

[1246] The server receives the user data sent from the device and converts it into an analyzable format. For example, data received in JSON format is stored in a structured database. Input: User data in JSON format. Output: User data stored in the database.

[1247] Step 5:

[1248] The server accesses the geographic information database and collects the necessary road information, slope gradients, location information of tourist attractions, etc. For example, it obtains the data using an API (e.g., OpenStreetMap API). Input: User's location information and characteristics. Output: Collected geographic information data.

[1249] Step 6:

[1250] The server analyzes the geographic information data collected and extracts information suitable for the user's conditions. For example, it extracts route information that prioritizes flat roads. Input: Collected geographic information data. Output: Geographic information suitable for the user's conditions.

[1251] Step 7:

[1252] The server analyzes the user's characteristics using the user's walking acceleration data and past movement history. For example, it can identify whether the user is elderly or uses a large vehicle. Input: Walking acceleration data and past movement history. Output: Identified user characteristics.

[1253] Step 8:

[1254] The server uses the generative AI model to calculate the optimal route based on the user's characteristics. For example, route calculations are performed using an AI model using TensorFlow or PyTorch. Input: User characteristics and geographical information data. Output: Optimal route information.

[1255] Step 9:

[1256] The server evaluates the calculated route and checks its safety and efficiency using a scoring algorithm. Input: Calculated optimal route. Output: Evaluated route score.

[1257] Step 10:

[1258] The server converts the optimal route into latitude and longitude coordinate information and formats it for navigation. For example, it converts it into GeoJSON format. Input: Optimal route information. Output: Latitude and longitude coordinate information.

[1259] Step 11:

[1260] The server updates the machine learning model to reflect the user's past behavior and selected routes in future route suggestions. Input: Past user behavior data. Output: Updated machine learning model.

[1261] Step 12:

[1262] The server sends the route information to the device. For example, it sends the route information using the HTTPS protocol. Input: Route information formatted as coordinates. Output: Route information sent to the device.

[1263] Step 13:

[1264] The device analyzes the route information received and starts displaying maps and voice guidance in real time. For example, a navigation application might display a map using the Google Maps API. Input: Received route information. Output: Guidance information for the user.

[1265] Step 14:

[1266] The device tracks the user's location in real time and periodically sends the location information to the server. Input: User's real-time location information. Output: Location data sent to the server.

[1267] Step 15:

[1268] The server dynamically recalculates the user's route based on the latest information and generates new, optimal route information. Input: Current location and updated geographical information data. Output: Recalculated optimal route information.

[1269] Step 16:

[1270] The device provides guidance based on the latest route information, helping users travel safely and efficiently. Input: Latest route information. Output: Updated guidance information.

[1271] (Application example 1)

[1272] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1273] Conventional navigation systems have been unable to adequately address diverse user needs and provide optimal routes based on specific requests. Real-time location updates and dynamic route recalculation are also limited, making it difficult to fully ensure user comfort and safety. Furthermore, there have been few systems that provide visual and audio guidance suitable for autonomous vehicles. This has resulted in inadequate navigation for users, particularly the elderly and those with special needs.

[1274] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1275] In this invention, the server includes means for receiving data on the starting point, destination, and specific requests from the user, means for analyzing the collected user data and collecting necessary data from a related geographic information database, means for analyzing the user's speed / acceleration data and past movement history, means for calculating an optimal route using a generative AI model, means for learning the user's preferences and behavioral patterns and reflecting them in subsequent route provision, means for transmitting the generated optimal route information to the user terminal, means for guiding the user along the optimal route on the user terminal, means for updating the user's location information in real time and providing an optimal route to an autonomous vehicle, means for providing information to the user through audio guidance and visual guidance, and means for dynamically recalculating the route and providing the latest route information. This allows navigation suitable for elderly users and users with specific requests to be provided, and enables always optimal route guidance through real-time location information updates and dynamic route recalculation.

[1276] "User" refers to an individual or organization that uses the System.

[1277] The "starting point" refers to the location where the user starts moving.

[1278] The "destination" refers to the final destination that the user is aiming for.

[1279] "Specific requests" refer to conditions or requirements that the user particularly desires for navigation.

[1280] A "geographic information database" refers to a database that includes geographic information such as road information, slope gradients, and the locations of tourist attractions.

[1281] "Speed ​​and acceleration data" refers to data related to the user's speed and acceleration while moving.

[1282] "Past travel history" refers to data relating to routes and places the user has previously traveled.

[1283] A "generative AI model" refers to an algorithm that uses AI technology to generate optimal routes based on the user's preferences.

[1284] "Preferences and behavioral patterns" refers to the routes and behavioral tendencies that a user has chosen in the past.

[1285] "Real-time" refers to the timing of immediate processing and provision of current information.

[1286] "Voice guidance" refers to a means of providing route guidance to the user using voice.

[1287] "Visual guidance" refers to a means of providing route guidance to a user using visual information.

[1288] "Dynamic recalculation" refers to the process of recalculating a route based on new information or changing conditions.

[1289] An "autonomous vehicle" refers to a vehicle that can drive autonomously and move without user intervention.

[1290] "Terminal" refers to a device that allows a user to input information or receive instructions.

[1291] In this invention, a system is constructed in which users, terminals, and servers work in cooperation with each other. The processing contents and specific examples of the system programs are explained below.

[1292] System configuration

[1293] 1. User: Operates a device such as a smartphone or tablet to input the starting point, destination, and specific requests.

[1294] 2. Terminal: Takes user input, formats it appropriately and sends it to the server.

[1295] 3. Server: Analyzes user data, collects and analyzes necessary data from related geographic information databases, calculates the optimal route using a generative AI model, and sends the generated optimal route information to the device.

[1296] Program processing explanation

[1297] User Input Processing

[1298] The user launches a terminal application and inputs a starting point, a destination, and any specific requests. The terminal receives this data, formats it, and sends it to the server.

[1299] Data collection and analysis

[1300] The server analyzes the received user data, accessing a geographic information database and analyzing the collected data, including road width, slope gradient, location of tourist attractions, traffic conditions, and road conditions.

[1301] User situation analysis

[1302] The server analyzes the user's current state by analyzing the user's speed and acceleration data and past movement history, and based on this analysis, provides the optimal route according to the user's specific needs.

[1303] Optimal Route Generation

[1304] The server uses a generative AI model to calculate the optimal route based on the user's characteristics, preferences, and behavioral patterns, for example prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[1305] Real-time updates

[1306] The system continuously acquires the user's current location and dynamically recalculates routes as needed, responding to sudden changes in traffic conditions and road construction, and providing the latest route information at all times.

[1307] Audio and visual guidance

[1308] The device provides users with audio and visual route guidance, improving safety and comfort.

[1309] Specific examples

[1310] Route guidance for seniors

[1311] If the user is an elderly person who wants to get from their home to city hall but wants to avoid hills, the system will provide a flat route that avoids hills.

[1312] Route guidance for tourists

[1313] If a user wishes to efficiently tour tourist attractions, the server will calculate the optimal route, taking into account the location information and opening hours of the tourist attractions.

[1314] Prompt Sentence Examples

[1315] "The starting point is home. The destination is City Hall, and I want to avoid the highway."

[1316] This invention provides a navigation system that meets the diverse needs of users and enables optimal route guidance tailored to specific requests. Real-time location information updates and dynamic route recalculation ensure safe and efficient travel based on the latest information.

[1317] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1318] Step 1:

[1319] The user launches a terminal application and inputs a starting point, a destination, and specific requests. The inputs include the coordinates of the starting point, the coordinates of the destination, and the desired conditions (e.g., avoid hills). The terminal formats this data appropriately and sends it to the server.

[1320] Step 2:

[1321] The server analyzes the user data received from the device. The input data includes the starting point, destination, and specific requests. Based on this, the server accesses a geographic information database to collect road information, slope gradients, tourist attraction locations, traffic conditions, and road conditions. The output data is the required geographic information.

[1322] Step 3:

[1323] The server analyzes the collected geographic information data and calculates the optimal route based on the specific request. As input, it receives the geographic information data collected in step 2 and the specific request entered by the user. For data processing, it uses a generative AI model to calculate the optimal route. As output, it obtains candidate optimal routes that take the specific request into account.

[1324] Step 4:

[1325] The server analyzes the user's speed and acceleration data and past movement history to identify the user's state. It receives the user's history data and real-time movement data as input. It uses an analysis algorithm to calculate the data and identify the user's current state (e.g., elderly, type of vehicle). It obtains user characteristic information as output.

[1326] Step 5:

[1327] The server further calculates the optimal route based on the user's characteristics, preferences, and behavioral patterns. As input, it receives the route candidates from step 3 and the user characteristics information from step 4. As output, it obtains the final generated optimal route information.

[1328] Step 6:

[1329] The server sends the generated optimal route information to the user terminal. The optimal route information is received as input. The route data to be sent to the user terminal is obtained as output.

[1330] Step 7:

[1331] The terminal provides route guidance to the user based on the optimal route received. Optimal route data is received from the server as input, and visual and audio route guidance is performed. Data processing involves displaying a map, visualizing the route, and generating audio guidance.

[1332] Step 8:

[1333] The device continuously tracks the user's current location and sends that location information to the server. As input, it receives the user's real-time location information. As output, it periodically sends location information to the server.

[1334] Step 9:

[1335] The server dynamically recalculates the route based on the transmitted real-time location information. It receives location information from the device as input. It recalculates the route by taking into account changes in traffic conditions and road environment as data calculations. It obtains updated optimal route information as output.

[1336] Step 10:

[1337] The terminal provides updated guidance to the user based on the latest route information received from the server. As input, it receives updated route data from the server. As output, it obtains the latest visual and audio guidance provided to the user.

[1338] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1339] This invention is a navigation system that responds to the diverse needs of users and provides optimal routes, and by combining it with an emotion engine that recognizes the user's emotions and reflects them in route guidance, it realizes a more personalized service. The specific operation of this system will be described below.

[1340] User Input Processing

[1341] 1. User provides input (User)

[1342] A user launches the application on the device and inputs their starting point, destination, and specific needs, such as an elderly person wanting to get to city hall but avoiding hills.

[1343] 2. Receiving user input (terminal)

[1344] The terminal receives user input data and transmits the appropriately formatted data to the server.

[1345] Data collection and analysis

[1346] 3. Data transmission and reception (terminal and server)

[1347] The terminal transmits user data to the server, and the server receives the data.

[1348] 4. Database Access (Server)

[1349] The server accesses a geographic information database and collects information such as road information, slope gradients, and the locations of tourist attractions.

[1350] 5. Data analysis (server)

[1351] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[1352] User situation analysis

[1353] 6. User status analysis (server)

[1354] The server analyzes the user's walking acceleration data and past movement history to identify the user's current status (e.g., elderly, large vehicle user).

[1355] Emotion recognition by emotion engine

[1356] 7. Emotion recognition data acquisition (device)

[1357] The device operates an emotion engine that recognizes the user's emotions and obtains the user's current emotional data, for example, through a facial recognition camera or voice analysis.

[1358] 8. Emotional Data Analysis (Server)

[1359] The server analyzes the user's emotion data collected by the emotion engine and reflects it in route suggestions.

[1360] Optimal route generation

[1361] 9. Route calculation (server)

[1362] The server uses a generative AI model to calculate the optimal route for the user based on the collected and analyzed data.

[1363] 10. Route Evaluation (Server)

[1364] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[1365] Personalize and send

[1366] 11. Personalization (Server)

[1367] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[1368] 12. Route information generation and transmission (server)

[1369] The server generates coordinate information for the optimal route and sends it to the terminal.

[1370] 13. Route guidance (terminal)

[1371] The device receives route information and provides users with directions, using map displays, voice guidance, and real-time location tracking.

[1372] Improved user experience for route guidance

[1373] 14. Audio guide adjustments (device)

[1374] Based on the emotional data generated by the emotion engine, the device changes the tone and content of the voice guidance to match the user's emotional state. For example, if a user is feeling anxious, the device will provide guidance in a more friendly tone.

[1375] Real-time updates

[1376] 15. Real-time data reception and updates (terminal and server)

[1377] The device tracks the user's current location in real time using GPS and sends that information to the server, which then recalculates the route as needed based on the latest information and sends the updated route information to the device.

[1378] 16. Latest route guidance (terminal)

[1379] The device continues to update the guidance based on the latest route information received.

[1380] Specific examples

[1381] Example 1: Route for seniors

[1382] 1. User input: An elderly user inputs, "I want to get from my house to city hall, avoiding slopes."

[1383] 2. Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[1384] 3. Emotion recognition: The device recognizes anxiety from the user's facial expressions.

[1385] 4. Route generation: The server calculates and evaluates routes that prioritize flat roads.

[1386] 5. Route guidance: The device displays a smooth and safe route and provides voice guidance in a friendly tone.

[1387] Example 2: Tourist Route

[1388] 1. User input: A tourist inputs, "I would like to visit tourist attractions in the area."

[1389] 2. Data collection and analysis: The server collects and analyzes information such as the location and opening hours of tourist attractions.

[1390] 3. Emotion recognition: The device recognizes excitement from the user's tone of voice.

[1391] 4. Route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[1392] 5. Route guidance: The device displays a route to visit tourist attractions in the optimal order and provides guidance in an energetic tone.

[1393] Features of this system

[1394] This navigation system provides routes tailored to the specific needs of users and suggests optimal travel routes that meet the requirements of different users, such as the elderly, tourists, and transportation workers. It also uses an emotion engine to recognize users' emotional data and provide route guidance tailored to their emotions in real time, providing a better user experience. By utilizing a generative AI model and a geographic information database to analyze users' states and emotions, it provides more personalized services and ensures comfortable and efficient travel.

[1395] The processing flow will be explained below.

[1396] Step 1:

[1397] The user starts the application on the terminal and inputs the starting point, destination, and specific needs (e.g., avoiding hills, not using highways, etc.).

[1398] Step 2:

[1399] The terminal receives the user's input data and formats it appropriately.

[1400] Step 3:

[1401] The terminal transmits the prepared user data to the server.

[1402] Step 4:

[1403] The server receives the user data from the terminal.

[1404] Step 5:

[1405] The server accesses a geographic information database and collects relevant data (e.g., road information, slope gradient, location information of tourist attractions, etc.).

[1406] Step 6:

[1407] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[1408] Step 7:

[1409] The server uses the user's walking acceleration data and past movement history to analyze the user's current state (e.g., elderly, large vehicle user).

[1410] Step 8:

[1411] The device runs an emotion engine to acquire the user's emotion data. For example, emotions are extracted from facial expressions and tone of voice using a camera or microphone.

[1412] Step 9:

[1413] The server receives and analyzes the user's emotion data collected by the emotion engine.

[1414] Step 10:

[1415] The server uses the generative AI model to calculate the optimal route based on the user's characteristics and emotional data, for example, calculating a flat route or a route that efficiently visits tourist spots.

[1416] Step 11:

[1417] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[1418] Step 12:

[1419] The server generates coordinate information for the optimal route and sends it to the terminal.

[1420] Step 13:

[1421] The terminal receives the optimal route information from the server and displays it on the screen to provide guidance to the user. Voice guidance is also provided at the same time.

[1422] Step 14:

[1423] The device tracks the user's current location in real time using GPS and sends that information to a server.

[1424] Step 15:

[1425] The server dynamically recalculates the route if necessary based on real-time location information and sends updated route information to the device.

[1426] Step 16:

[1427] The device continuously updates the guidance based on the latest route information, and adjusts the tone and content of the voice guidance based on the user's emotional state.

[1428] Specific examples

[1429] Example 1: Route for seniors

[1430] Step 1: An elderly user inputs, "I want to walk from my home to city hall, avoiding slopes."

[1431] Step 2: The terminal receives the user's input data and sends it to the server.

[1432] Step 3: The server receives the data and collects road data and slope gradient information from the geographic information database.

[1433] Step 4: The server analyzes the data and extracts information about flat roads.

[1434] Step 5: The device activates its emotion engine and recognizes anxiety from the user's facial expression.

[1435] Step 6: The server analyzes the emotion data and uses it to calculate the route.

[1436] Step 7: The server uses the generative AI model to calculate a flat route.

[1437] Step 8: The server evaluates the calculation results and sends the optimal route to the terminal.

[1438] Step 9: The device displays a flat route and provides voice directions in a friendly tone.

[1439] Example 2: Tourist Route

[1440] Step 1: The tourist enters, "I would like to visit tourist attractions in the area."

[1441] Step 2: The terminal receives the user's input data and sends it to the server.

[1442] Step 3: The server receives the data and collects the location information and business hours data of the tourist attractions.

[1443] Step 4: The server analyzes the data and extracts information for efficiently touring tourist attractions.

[1444] Step 5: The device activates its emotion engine and recognizes excitement from the user's tone of voice.

[1445] Step 6: The server analyzes the emotion data and uses it to calculate the route.

[1446] Step 7: The server uses the generative AI model to calculate an efficient route around the tourist attractions.

[1447] Step 8: The server evaluates the calculation results and sends the optimal route to the terminal.

[1448] Step 9: The device displays the optimal route and provides voice guidance in an energetic tone.

[1449] Example 2

[1450] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1451] Conventional navigation systems focus on simple route guidance based on a starting point and destination, making it difficult to provide personalized routes that take into account the user's specific needs and emotional state. Furthermore, they are unable to adequately adjust route guidance to reflect the user's current location and emotional data in real time, leaving the user experience open to improvement. Information analysis to address specific needs, such as avoiding slopes or visiting tourist attractions, is also limited.

[1452] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1453] In this invention, the server comprises means for receiving data from the user regarding the starting point, destination and specific needs;

[1454] means for analyzing the collected user data and collecting necessary data from related geographic information databases;

[1455] A means for analyzing the user's walking acceleration data and past movement history;

[1456] This allows for personalized routes that take into account the user's specific needs and emotional state.

[1457] The "starting point" is the location where the user starts their journey.

[1458] The "destination" is the final destination of the user's journey.

[1459] "Specific needs" are special requirements or desires that a user has when traveling.

[1460] "User data" refers to information such as starting point, destination, specific needs, walking acceleration data, past movement history, and emotional data.

[1461] A "geographic information database" is a collection of data that stores geographic information, including road width, slope gradient, and location information of tourist attractions.

[1462] "Walking acceleration data" is data obtained from an acceleration sensor while the user is walking.

[1463] "Past movement history" is data on the movement routes and movement patterns that the user has taken in the past.

[1464] "Emotion data" is information that indicates the user's current emotional state, and is obtained by facial expression and voice analysis, for example.

[1465] A "generative AI model" is an artificial intelligence model that makes route suggestions and predictions based on large amounts of data.

[1466] An "optimal route" is one that takes into maximum consideration the user's specific needs and emotional state, and provides an efficient, safe, and comfortable journey.

[1467] A "personalized route" is a route that is tailored based on a user's individual preferences and behavioral patterns.

[1468] "Voice guide" refers to guidance information provided by the navigation system through speech.

[1469] "Continuously obtain in real time" refers to constantly updating and obtaining the user's current location information.

[1470] "Dynamic recalculation" refers to the process of optimizing an existing route on an ongoing basis based on newly acquired data.

[1471] This invention is a navigation system that responds to various user needs and provides optimal routes. This system also realizes more personalized services by combining it with an emotion engine that recognizes the user's emotions and reflects them in route guidance.

[1472] System Overview

[1473] This system mainly operates around three elements: the server, the terminal, and the user.

[1474] 1. User Input Processing:

[1475] Users launch a navigation app on their smartphone or tablet and input their starting point, destination, and specific needs (for example, "I want to avoid hills when getting from my house to city hall").

[1476] The terminal receives user input, formats it in an appropriate format, and sends the data to the server, typically using JSON as the transmission format.

[1477] 2. Data collection and analysis:

[1478] The terminal transmits user data to the server, which receives it.

[1479] The server accesses a geographic information database (e.g., Google Maps API) to collect road information, slope gradients, and location information of tourist attractions.

[1480] The server analyzes the collected data and extracts the necessary information to address the user's specific needs.

[1481] 3. User situation analysis:

[1482] The server analyzes the user's walking acceleration data and past movement history to identify the user's current status (elderly, large vehicle user, etc.).

[1483] 4. Emotion Recognition with Emotion Engine:

[1484] The device runs an emotion recognition engine and acquires the user's emotional data (facial expressions and voice analysis).

[1485] The server analyzes the emotion data and reflects it in route suggestions.

[1486] 5. Optimal route generation:

[1487] The server uses a generative AI model (such as GPT-4) to calculate the optimal route based on the collected and analyzed data.

[1488] The server evaluates the calculated route to ensure safety, efficiency and user comfort.

[1489] 6. Personalization and Delivery:

[1490] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[1491] The server generates coordinate information for the optimal route and sends it to the terminal.

[1492] The device then provides users with directions based on the route information it receives, using map displays, voice guidance, and real-time location tracking.

[1493] 7. Improved user experience for route guidance:

[1494] Based on the emotional data, the device adjusts the tone and content of the voice guidance to match the user's emotional state, providing guidance in a friendly tone to users who are feeling anxious.

[1495] 8. Real-time updates:

[1496] The device tracks the user's current location in real time using GPS and sends that information to a server.

[1497] The server recalculates the route as needed based on the latest information and sends the updated route information to the terminal.

[1498] The device will continue to update the directions based on the latest route information it receives.

[1499] Specific examples

[1500] 1. Route for seniors:

[1501] User input: "I want to avoid hills when walking from my house to City Hall."

[1502] Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[1503] Emotion recognition: The device recognizes anxiety from the user's facial expression.

[1504] Route generation: The server calculates and evaluates routes that prioritize flat roads.

[1505] Route guidance: The device displays a smooth, safe route and provides voice guidance in a friendly tone.

[1506] 2. Tourist Route:

[1507] User input: "I want to visit tourist attractions in the area."

[1508] Data collection and analysis: The server collects and analyzes information about the location and business hours of tourist attractions.

[1509] Emotion recognition: The device recognizes excitement from the user's tone of voice.

[1510] Route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[1511] Route guidance: The device displays a route to visit tourist attractions in the optimal order and provides guidance in an energetic tone.

[1512] As described above, this navigation system can provide a better user experience by providing routes tailored to the user's specific needs and utilizing emotion recognition to provide personalized guidance in real time.

[1513] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1514] Step 1:

[1515] User provides input (User)

[1516] A user launches a navigation app and inputs their starting point, destination, and specific needs (e.g., "I want to avoid hills"). The input is entered into text boxes in a form in the app. The input data is formatted as JSON and sent to the server.

[1517] Input: Starting point, Destination, Specific needs

[1518] Output: User input data in JSON format

[1519] Step 2:

[1520] Accepting user input (terminal)

[1521] The device receives the information entered by the user and sends the data to the server. Specifically, when a button is pressed, an HTTP request is generated and the input data is transferred to the server.

[1522] Input: User-supplied data in JSON format

[1523] Output: Forwarded to the server as an HTTP request

[1524] Step 3:

[1525] Data transmission and reception (terminal and server)

[1526] The device sends user input data to the server, which receives the data and passes it to the analysis module.

[1527] Input: User-supplied data as an HTTP request

[1528] Output: Data objects available on the server

[1529] Step 4:

[1530] Database access (server)

[1531] The server accesses the geographic information database to obtain the necessary road information, slope gradients, and location information for tourist attractions. Specifically, it sends an API request to the geographic information database and passes the data obtained in response to the analysis module.

[1532] Input: User's starting and destination information

[1533] Output: Geographical information (road information, slope gradient, location information of tourist attractions)

[1534] Step 5:

[1535] Data analysis (server)

[1536] The server analyzes the collected geographical information and extracts information to meet the user's specific needs, for example, filtering road gradient information to calculate routes that avoid hills.

[1537] Input: Geographical information data

[1538] Output: Parsed route information

[1539] Step 6:

[1540] User status analysis (server)

[1541] The server analyzes the user's walking acceleration data and past movement history to determine the user's current state, and inputs this data into a machine learning model to determine whether the user is elderly or a wheelchair user.

[1542] Input: Acceleration data during walking, past movement history

[1543] Output: User characteristics data (elderly, wheelchair users, etc.)

[1544] Step 7:

[1545] Emotion recognition data acquisition (device)

[1546] The device activates an emotion recognition engine to obtain user emotional data through facial expression and voice analysis, and uses the camera and microphone to capture the user's emotional state in real time.

[1547] Input: The user's current facial expression and voice data

[1548] Output: Retrieved emotion data

[1549] Step 8:

[1550] Emotion data analysis (server)

[1551] The server analyzes the acquired emotion data to identify the user's current emotional state. The emotion engine inputs the acquired data into multiple emotion models and identifies the user's emotion based on the results.

[1552] Input: Emotion data

[1553] Output: Parsed emotional state

[1554] Step 9:

[1555] Route calculation (server)

[1556] The server uses the generative AI model to calculate the optimal route based on the analyzed data. Specifically, the server inputs the prompt "Please provide the optimal route if the user wants to go from home to city hall while avoiding slopes" into the generative AI model and obtains the calculation result.

[1557] Input: Parsed user data and prompt statements

[1558] Output: Optimal route

[1559] Step 10:

[1560] Route Evaluation (Server)

[1561] The server evaluates the calculated routes to check safety, efficiency, and user comfort, assigns a score based on the evaluation criteria, and selects the best route.

[1562] Input: Optimal route suggestions

[1563] Output: Evaluated route

[1564] Step 11:

[1565] Personalization (Server)

[1566] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions. The learning module analyzes the user's past data and updates the personalized model.

[1567] Input: User's past behavior data

[1568] Output: A trained personalized model

[1569] Step 12:

[1570] Route information generation and transmission (server)

[1571] The server generates coordinate information for the optimal route and sends it to the device. The route data is converted to JSON format and transferred to the device as an HTTP response.

[1572] Input: Evaluated route information

[1573] Output: Route data in JSON format

[1574] Step 13:

[1575] Route guidance (terminal)

[1576] The device provides the user with directions based on the received route information, using map display and voice guidance to provide real-time location tracking and guidance to the user.

[1577] Input: Route data in JSON format

[1578] Output: Map display, voice guidance

[1579] Step 14:

[1580] Audio guide adjustments (device)

[1581] The device adjusts the tone and content of the voice guidance to match the user's emotional state based on the emotion data, providing guidance in a friendly tone to an anxious user and guidance in an energetic tone to an excited user.

[1582] Input: Parsed emotional state data

[1583] Output: Adjusted voice prompts

[1584] Step 15:

[1585] Real-time data reception and updates (terminal and server)

[1586] The device tracks the user's current location in real time using GPS and sends that information to the server, which then recalculates the route as needed based on the latest information and sends the updated route information to the device.

[1587] Input: Real-time location of the user

[1588] Output: Updated route information

[1589] Step 16:

[1590] Latest route guidance (terminal)

[1591] The device continuously updates its guidance based on the latest route information received, providing users with the latest information and helping them reach their destination safely and efficiently.

[1592] Input: Updated route information

[1593] Output: Updated map display, voice guidance

[1594] (Application example 2)

[1595] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1596] Conventional navigation systems have difficulty providing optimal route guidance to users because they are unable to fully reflect the user's specific needs and real-time emotional state. Furthermore, existing systems do not adapt voice guidance to reflect the user's emotions, and personalized services are not provided. This creates a need for reducing stress during travel and increasing user satisfaction.

[1597] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving data regarding the starting point, destination, and specific needs from the user, means for analyzing the collected user data and collecting necessary data from a related geographic information database, means for calculating an optimal route using a generative AI model, means for acquiring the user's emotional state through facial expression recognition and voice analysis, and means for adjusting the tone and content of audio guidance to suit the user based on the emotional state. This enables optimal route guidance based on the user's specific needs and emotional state, and allows for the provision of personalized, advanced navigation services.

[1598] A "user" is a person who uses the navigation system.

[1599] The "starting point" is the location where the user begins their journey.

[1600] A "destination" is a location that a user wishes to reach.

[1601] "Specific needs" refers to special requirements or desires that a user has while traveling.

[1602] "Means" refers to a method or apparatus for achieving a specific function or operation.

[1603] "Walking acceleration data" is acceleration information acquired while the user is walking.

[1604] "Past travel history" is a record of the routes and places the user has traveled to so far.

[1605] A "generative AI model" is an artificial intelligence model that calculates optimal routes based on large amounts of data.

[1606] "User preferences and behavioral patterns" is data that indicates the movement and preference trends that the user has shown in the past.

[1607] "Transmit" is the act of sending data to another device or system.

[1608] A "user terminal" is a device that can be directly operated by a user.

[1609] "Guidance" refers to providing information to guide the user in a specific direction.

[1610] "Facial expression recognition" is a technology that uses cameras and sensors to analyze a user's facial expressions.

[1611] "Voice analysis" is a technology that analyzes voice data to identify a user's emotions and intentions.

[1612] "Emotional state" refers to the emotional state that the user is currently feeling.

[1613] "Audio guidance" is a method of providing instructions and information to a user using audio.

[1614] "Tone" refers to the pitch and texture of a voice.

[1615] The present invention is a navigation system that provides an optimal route taking into account the specific needs and emotional state of the user. The system is composed of a server and a user terminal.

[1616] User device capabilities:

[1617] The user terminal has the function of receiving data from the user regarding the starting point, destination, and specific needs. It also has the function of obtaining the user's emotional state through facial expression recognition and voice analysis. The user terminal appropriately formats this data and transmits it to the server. At the same time, the user terminal receives the optimal route information transmitted from the server and provides guidance to the user. The guidance also includes the function of changing the tone and content of the voice guidance according to the user's emotional state.

[1618] Server capabilities:

[1619] The server receives and analyzes the data sent from the user's device. First, it accesses a geographic information database to collect the necessary data. Then, it uses a generative AI model to calculate the optimal route, taking into account the user's specific needs and emotional state. It also has the ability to learn the user's preferences and behavioral patterns and reflect them in future route suggestions. The calculated optimal route information is then sent back to the user's device.

[1620] Examples of hardware and software used:

[1621] Smartphones and tablets: Used for user input and display.

[1622] Camera and microphone: Used for facial expression recognition and voice analysis to capture emotional state.

[1623] GPS system: Used to track your location and update your route in real time.

[1624] Python-based application: Used to execute the entire program logic.

[1625] HTTP Requests library (requests): Used to send and receive data.

[1626] Generative AI models: used to calculate optimal routes and generate personalized suggestions.

[1627] Examples:

[1628] The user (driver) opens a smartphone app and inputs the "optimal route from home to work," as well as specific needs and emotions such as "wanting to avoid traffic jams" or "wanting to relax." The app sends this data to a server, which uses a generative AI model to calculate the optimal route. The server then selects the optimal route and an appropriate voice guide (relaxing tone) and provides it to the self-driving vehicle.

[1629] Example prompt sentence:

[1630] "Write Python code for a navigation system for a self-driving car that recognizes emotions and suggests the best route. The user inputs their starting point, destination, specific needs, and emotion. Provide a safe and efficient route, including voice guidance based on the emotion."

[1631] This allows for optimal route guidance based on the user's specific needs and emotional state, providing a highly personalized navigation service.

[1632] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1633] Step 1:

[1634] The user enters the starting point, destination, and specific needs into the text input fields and launches the terminal application. The user then inputs their current location, destination, and specific needs, such as "I want to avoid traffic jams and relax," into the application. The input data is saved in the application as starting point, destination, and specific needs data.

[1635] Step 2:

[1636] The device uses a facial expression recognition camera and voice analysis functions to obtain the user's emotional data. When the user turns their face to the camera or issues a voice command, these devices analyze the user's current emotion (e.g., relaxed, excited, anxious, etc.) and store it as emotional data. The analyzed emotional data is then used to provide personalized guidance.

[1637] Step 3:

[1638] The device sends the user's input data and acquired emotional data to the server. The data sent includes the starting point, destination, specific needs, and emotional data. The device formats this data appropriately and sends it to the server using an HTTP request. This data is converted into a data format that the server can easily receive.

[1639] Step 4:

[1640] The server analyzes the received data and accesses the relevant geographic information database to collect the necessary data. The server retrieves geographic information from the database, including road information between the starting point and the destination, slope gradients, location information of tourist attractions, etc. The server collects this data and begins the analysis process.

[1641] Step 5:

[1642] The server analyzes the collected geographic information data and uses a generative AI model to calculate the optimal route based on the user's specific needs and emotional state. The AI ​​model generates the optimal travel route based on the collected data and the user's requests, and selects information suitable for route guidance. The calculated optimal route data is then provided to the user in the next step.

[1643] Step 6:

[1644] The server evaluates the calculated route information to ensure safety, efficiency, and user comfort. The evaluation process checks whether the generated route is suitable for the user's specific needs and emotional state. The evaluated route data is then ready to be sent to the user's device.

[1645] Step 7:

[1646] The server simultaneously transmits the coordinate information of the optimal route, as well as the appropriate tone and content of the voice guidance. This is generated based on the user's emotional data. For example, a user who wants to relax will be provided with a voice guidance in a calm tone. This information is sent from the server to the user's terminal.

[1647] Step 8:

[1648] The device displays the received route information and audio guide, and provides audio guidance. The device displays the optimal route on a map and supports the user's travel. It also plays audio guidance according to the user's emotional state and gives instructions in real time while traveling. The user travels based on this information.

[1649] Step 9:

[1650] The device tracks the user's current location in real time using GPS and sends that information to the server. The server dynamically recalculates the route as needed based on this current location information. The recalculated route information is sent to the user's device, which immediately updates the guidance. This ensures that the user is always guided along the most up-to-date, optimal route.

[1651] The above processing steps result in an advanced navigation service that responds to the user's specific needs and emotional state.

[1652] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1653] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1654] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1655] [Fourth embodiment]

[1656] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1657] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1658] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1659] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1660] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1661] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1662] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1663] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1664] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1665] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1666] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1667] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1668] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1669] The navigation system of the present invention is designed to meet the diverse needs of users and provide them with the most suitable route. This system operates through cooperation between the server and the terminal, and provides users with a comfortable and efficient route. Below, we will create a system program and explain the flow of each process in natural language.

[1670] User Input Processing

[1671] 1. User provides input (User)

[1672] A user launches an application on the device and inputs their starting point, destination, and specific needs. For example, an elderly person might input their desire to get to city hall but avoid hills.

[1673] 2. Receiving user input (terminal)

[1674] The terminal receives the user's input data and formats it appropriately.

[1675] 3. Data transmission process

[1676] The terminal transmits the received user data to the server.

[1677] Data collection and analysis

[1678] 4. Receive user data (server)

[1679] The server receives the user data from the terminal and begins analyzing it.

[1680] 5. Access the database (server)

[1681] The server accesses a geographic information database and collects information such as road information, slope gradients, and the locations of tourist attractions.

[1682] 6. Analyze the collected data (server)

[1683] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's needs.

[1684] User situation analysis

[1685] 7. Analyze the user's situation (server)

[1686] The server analyzes the user's current state using the user's walking acceleration data and past movement history, for example, to determine whether the user is elderly or using a large vehicle.

[1687] Optimal route generation

[1688] 8. Run the route generation algorithm (server)

[1689] The server uses generative AI models to calculate optimal routes based on the user's characteristics, such as prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[1690] 9. Evaluate the generated route (server)

[1691] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[1692] Route generation and transmission

[1693] 10. Convert route data into coordinate information (server)

[1694] The server converts the optimal route into latitude and longitude coordinate information, making it usable for navigation.

[1695] 11. Learning user preferences (server)

[1696] The server learns data on user behavior and selected routes and reflects this in future route suggestions.

[1697] 12. Generate and send optimal route information (server)

[1698] The server sends the prepared route information to the terminal.

[1699] 13. Start route guidance (device)

[1700] The device provides guidance to the user based on the route information received, using map display and voice guidance to guide the user to their destination.

[1701] Real-time updates

[1702] 14. Data reception and analysis on the move (terminal and server)

[1703] The device tracks the user's current location in real time and sends it to the server, which then dynamically recalculates the route based on the latest information and updates the optimal route.

[1704] 15. Providing the latest route (terminal)

[1705] The terminal guides the user along an updated route based on the latest route information received from the server.

[1706] Specific examples

[1707] Example 1: Route for seniors

[1708] 1. User Input: An elderly user specifies that they want to get from their home to City Hall, but want to avoid hills.

[1709] 2. Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[1710] 3. Optimal route generation: The server calculates and evaluates routes that prioritize flat roads.

[1711] 4. Route guidance: The device displays a smooth and safe route and provides voice guidance.

[1712] Example 2: Tourist Route

[1713] 1. User input: A tourist inputs that he / she wants to visit tourist attractions in the area.

[1714] 2. Data collection and analysis: The server collects and analyzes information such as the location and business hours of tourist attractions.

[1715] 3. Optimal route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[1716] 4. Route guidance: The device displays the route to visit tourist attractions in the optimal order and provides guidance.

[1717] Features of this system

[1718] This navigation system provides routes tailored to the specific needs of users and proposes optimal travel routes that meet the requirements of different users, such as the elderly, tourists, and transportation workers. By utilizing a generative AI model and a geographic information database to analyze the user's walking acceleration data and movement history, route guidance optimized for each user is realized. Furthermore, by analyzing the situation in real time and dynamically updating the route, guidance based on the latest information can always be provided. This solves the issues with conventional navigation systems and enables users to travel comfortably and efficiently.

[1719] The processing flow will be explained below.

[1720] Step 1:

[1721] The terminal receives input from the user of the starting point, destination, and specific needs (e.g., avoiding hills, not wanting to use highways, etc.).

[1722] Step 2:

[1723] The terminal receives the user's input data, formats it appropriately, and sends it to the server.

[1724] Step 3:

[1725] The server receives user data from the terminal and accesses a geographic information database.

[1726] Step 4:

[1727] The server collects relevant data, such as road information, slope gradients, and location information of tourist attractions, from a geographic information database.

[1728] Step 5:

[1729] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[1730] Step 6:

[1731] The server analyzes the user's current status (e.g., elderly, large vehicle user, etc.) using the user's walking acceleration data and past movement history.

[1732] Step 7:

[1733] The server uses a generative AI model to calculate the optimal route based on the user's characteristics, for example prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[1734] Step 8:

[1735] The server evaluates the calculated route to ensure safety, efficiency and user comfort.

[1736] Step 9:

[1737] The server converts the optimal route into latitude and longitude coordinate information and formats it for navigation.

[1738] Step 10:

[1739] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[1740] Step 11:

[1741] The server transmits the generated optimum route information to the terminal.

[1742] Step 12:

[1743] The terminal receives route information from the server and provides on-screen display and audio guidance.

[1744] Step 13:

[1745] The device tracks the user's current location in real time using GPS and transmits the location information to a server.

[1746] Step 14:

[1747] The server dynamically recalculates the route if necessary based on real-time location information and sends the latest optimal route to the device.

[1748] Step 15:

[1749] The terminal keeps the user updated with directions based on the latest route information it receives.

[1750] Example 1

[1751] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1752] Current navigation systems struggle to provide optimal routes tailored to a user's specific needs and characteristics. They also lack the ability to dynamically recalculate routes based on the user's situation in real time, making them unable to respond immediately to changes during travel. Furthermore, they lack the ability to learn the user's preferences and behavioral patterns and incorporate them into future route suggestions, resulting in a lack of personalized guidance.

[1753] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1754] In this invention, the server includes means for receiving data regarding the starting point, destination, and specific needs from the user, means for arranging the received user data in an appropriate format and transmitting it to the server, means for the server to collect and analyze necessary data from an associated geographic information database, means for analyzing the user's walking acceleration data and past movement history to identify the user's characteristics, means for calculating an optimal route based on the user's characteristics using a generative AI model, means for evaluating the optimal route and confirming safety and efficiency, means for learning the user's preferences and behavioral patterns and reflecting them in subsequent route suggestions, means for converting the generated optimal route information into coordinate information and transmitting it to the user terminal, and means for providing guidance to the user based on the received route information.

[1755] This allows for optimal route provision based on the user's specific needs and characteristics, realizing dynamic route recalculation in real time based on the user's situation, and enabling personalized route suggestions based on the user's preferences and behavioral patterns.

[1756] "User" refers to a person or entity that utilizes a navigation system to input data regarding starting point, destination, and specific needs.

[1757] A "terminal" is a device that a user uses to access the navigation system, and includes a smartphone, tablet, car navigation system, etc.

[1758] The term "server" refers to a computer system that receives data sent from a user, accesses a geographic information database to calculate the optimal route, and transmits this information to the user terminal.

[1759] The "starting point" refers to the location information of the point where the user starts moving.

[1760] "Destination" refers to the location information of the point where the user wants to complete their journey.

[1761] "Specific needs" refers to conditions or requirements that the user wants to be particularly considered when traveling, and includes individual wishes such as wanting to avoid slopes or wanting to visit specific tourist spots.

[1762] A "geographic information database" refers to a database that stores geographical data such as road information, slope gradients, and the locations of tourist attractions.

[1763] "Walking acceleration data" refers to data acquired from an acceleration sensor while the user is walking, and is used to analyze the user's movement characteristics.

[1764] "Travel history" refers to historical data such as the route, time, and distance traveled by the user in the past.

[1765] "Generative AI model" refers to an artificial intelligence model used to calculate optimal routes based on user characteristics and needs.

[1766] The "optimal route" refers to the route from the user's starting point to the destination that best satisfies the user's characteristics and specific needs.

[1767] "Coordinate information" refers to latitude and longitude data that indicates a geographic location.

[1768] The "guiding means" refers to a function on the user terminal that provides the user with the optimum route visually or audibly.

[1769] "Real-time" refers to constantly tracking and updating the user's current location and status.

[1770] MODE FOR CARRYING OUT THE INVENTION

[1771] A specific embodiment of the navigation system of the present invention is shown below. This system is designed to meet the diverse needs of users and provide optimal routes. This system operates through cooperation between a server and user terminals, and provides users with comfortable and efficient travel routes.

[1772] A user launches a navigation application on their device and inputs their starting point, destination, and specific needs. For example, an elderly user might input their desire to get from their home to city hall, but avoid hills. The device receives the user's input, formats it appropriately, and transmits it to a server, typically using the HTTPS protocol.

[1773] The server receives the user data sent from the device and converts it into an analyzable format. For example, it stores the data received in JSON format in a structured database. The server then accesses a geographic information database to collect road information, slope gradients, location information of tourist attractions, etc. In this case, a general API (e.g., OpenStreetMap API) can be used to obtain the actual data.

[1774] The server extracts and analyzes information appropriate to the user's conditions based on the collected data. It also includes a phase in which the user's walking acceleration data and past movement history are used to identify the user's characteristics. This makes it possible to identify, for example, whether the user is elderly or uses a large vehicle.

[1775] The server then uses a generative AI model (such as one using TensorFlow or PyTorch) to calculate the optimal route based on the user's characteristics. Depending on the user's characteristics, the server determines whether to prioritize flat roads or roads with less traffic. The calculated route is then further evaluated using an evaluation algorithm to verify safety and efficiency.

[1776] The generated optimal route information is converted into coordinate information (e.g., latitude and longitude) and formatted for use by the navigation system. The server also has the ability to learn the user's past actions and selected routes and reflect this in future route suggestions.

[1777] The server then sends the optimized route information to the user's device, which then analyzes the received route information and starts displaying a map and providing voice guidance in real time, allowing the user to efficiently navigate from their starting point to their destination.

[1778] The system also tracks the user's current location in real time and periodically sends it to the server, allowing it to dynamically recalculate routes and provide the latest route information. Through this process, it is possible to provide optimal route guidance that meets the needs of a variety of users.

[1779] Examples of specific prompts include:

[1780] "What is the best route for an elderly person to get from their home to City Hall, but who wants to avoid hills?"

[1781] "Please tell me the most efficient route for tourists who want to visit the tourist attractions in the area."

[1782] The system's unique features include the ability to provide routes tailored to specific user needs and propose optimal travel routes tailored to the requirements of different users, such as the elderly, tourists, and transportation workers. By utilizing a generative AI model and a geographic information database, the system analyzes the user's walking acceleration data and movement history to provide route guidance optimized for each user. Furthermore, real-time situation analysis and dynamic route updates enable the system to provide guidance based on the latest information at all times.

[1783] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1784] Step 1:

[1785] A user launches a navigation application on a device and inputs their starting point, destination, and specific needs. For example, the user might input a desire to "go from home to city hall, but avoid hills." Input: User's location information and specific needs. Output: User-input data sent to the device.

[1786] Step 2:

[1787] The device receives user input data, formats it as needed, and converts it into a parsable format. For example, it converts the starting point and destination into coordinate data and analyzes it for specific needs. Input: Location information from the user and specific needs. Output: Formatted user data (e.g., JSON format).

[1788] Step 3:

[1789] The terminal sends the prepared user data to the server. At this time, the HTTPS protocol is used to ensure secure data transfer. Input: Prepared user data. Output: User data transferred to the server.

[1790] Step 4:

[1791] The server receives the user data sent from the device and converts it into an analyzable format. For example, data received in JSON format is stored in a structured database. Input: User data in JSON format. Output: User data stored in the database.

[1792] Step 5:

[1793] The server accesses the geographic information database and collects the necessary road information, slope gradients, location information of tourist attractions, etc. For example, it obtains the data using an API (e.g., OpenStreetMap API). Input: User's location information and characteristics. Output: Collected geographic information data.

[1794] Step 6:

[1795] The server analyzes the geographic information data collected and extracts information suitable for the user's conditions. For example, it extracts route information that prioritizes flat roads. Input: Collected geographic information data. Output: Geographic information suitable for the user's conditions.

[1796] Step 7:

[1797] The server analyzes the user's characteristics using the user's walking acceleration data and past movement history. For example, it can identify whether the user is elderly or uses a large vehicle. Input: Walking acceleration data and past movement history. Output: Identified user characteristics.

[1798] Step 8:

[1799] The server uses the generative AI model to calculate the optimal route based on the user's characteristics. For example, route calculations are performed using an AI model using TensorFlow or PyTorch. Input: User characteristics and geographical information data. Output: Optimal route information.

[1800] Step 9:

[1801] The server evaluates the calculated route and checks its safety and efficiency using a scoring algorithm. Input: Calculated optimal route. Output: Evaluated route score.

[1802] Step 10:

[1803] The server converts the optimal route into latitude and longitude coordinate information and formats it for navigation. For example, it converts it into GeoJSON format. Input: Optimal route information. Output: Latitude and longitude coordinate information.

[1804] Step 11:

[1805] The server updates the machine learning model to reflect the user's past behavior and selected routes in future route suggestions. Input: Past user behavior data. Output: Updated machine learning model.

[1806] Step 12:

[1807] The server sends the route information to the device. For example, it sends the route information using the HTTPS protocol. Input: Route information formatted as coordinates. Output: Route information sent to the device.

[1808] Step 13:

[1809] The device analyzes the route information received and starts displaying maps and voice guidance in real time. For example, a navigation application might display a map using the Google Maps API. Input: Received route information. Output: Guidance information for the user.

[1810] Step 14:

[1811] The device tracks the user's location in real time and periodically sends the location information to the server. Input: User's real-time location information. Output: Location data sent to the server.

[1812] Step 15:

[1813] The server dynamically recalculates the user's route based on the latest information and generates new, optimal route information. Input: Current location and updated geographical information data. Output: Recalculated optimal route information.

[1814] Step 16:

[1815] The device provides guidance based on the latest route information, helping users travel safely and efficiently. Input: Latest route information. Output: Updated guidance information.

[1816] (Application example 1)

[1817] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1818] Conventional navigation systems have been unable to adequately address diverse user needs and provide optimal routes based on specific requests. Real-time location updates and dynamic route recalculation are also limited, making it difficult to fully ensure user comfort and safety. Furthermore, there have been few systems that provide visual and audio guidance suitable for autonomous vehicles. This has resulted in inadequate navigation for users, particularly the elderly and those with special needs.

[1819] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1820] In this invention, the server includes means for receiving data on the starting point, destination, and specific requests from the user, means for analyzing the collected user data and collecting necessary data from a related geographic information database, means for analyzing the user's speed / acceleration data and past movement history, means for calculating an optimal route using a generative AI model, means for learning the user's preferences and behavioral patterns and reflecting them in subsequent route provision, means for transmitting the generated optimal route information to the user terminal, means for guiding the user along the optimal route on the user terminal, means for updating the user's location information in real time and providing an optimal route to an autonomous vehicle, means for providing information to the user through audio guidance and visual guidance, and means for dynamically recalculating the route and providing the latest route information. This allows navigation suitable for elderly users and users with specific requests to be provided, and enables always optimal route guidance through real-time location information updates and dynamic route recalculation.

[1821] "User" refers to an individual or organization that uses the System.

[1822] The "starting point" refers to the location where the user starts moving.

[1823] The "destination" refers to the final destination that the user is aiming for.

[1824] "Specific requests" refer to conditions or requirements that the user particularly desires for navigation.

[1825] A "geographic information database" refers to a database that includes geographic information such as road information, slope gradients, and the locations of tourist attractions.

[1826] "Speed ​​and acceleration data" refers to data related to the user's speed and acceleration while moving.

[1827] "Past travel history" refers to data relating to routes and places the user has previously traveled.

[1828] A "generative AI model" refers to an algorithm that uses AI technology to generate optimal routes based on the user's preferences.

[1829] "Preferences and behavioral patterns" refers to the routes and behavioral tendencies that a user has chosen in the past.

[1830] "Real-time" refers to the timing of immediate processing and provision of current information.

[1831] "Voice guidance" refers to a means of providing route guidance to the user using voice.

[1832] "Visual guidance" refers to a means of providing route guidance to a user using visual information.

[1833] "Dynamic recalculation" refers to the process of recalculating a route based on new information or changing conditions.

[1834] An "autonomous vehicle" refers to a vehicle that can drive autonomously and move without user intervention.

[1835] "Terminal" refers to a device that allows a user to input information or receive instructions.

[1836] In this invention, a system is constructed in which users, terminals, and servers work in cooperation with each other. The processing contents and specific examples of the system programs are explained below.

[1837] System configuration

[1838] 1. User: Operates a device such as a smartphone or tablet to input the starting point, destination, and specific requests.

[1839] 2. Terminal: Takes user input, formats it appropriately and sends it to the server.

[1840] 3. Server: Analyzes user data, collects and analyzes necessary data from related geographic information databases, calculates the optimal route using a generative AI model, and sends the generated optimal route information to the device.

[1841] Program processing explanation

[1842] User Input Processing

[1843] The user launches a terminal application and inputs a starting point, a destination, and any specific requests. The terminal receives this data, formats it, and sends it to the server.

[1844] Data collection and analysis

[1845] The server analyzes the received user data, accessing a geographic information database and analyzing the collected data, including road width, slope gradient, location of tourist attractions, traffic conditions, and road conditions.

[1846] User situation analysis

[1847] The server analyzes the user's current state by analyzing the user's speed and acceleration data and past movement history, and based on this analysis, provides the optimal route according to the user's specific needs.

[1848] Optimal Route Generation

[1849] The server uses a generative AI model to calculate the optimal route based on the user's characteristics, preferences, and behavioral patterns, for example prioritizing flatter routes for elderly people and wider roads for larger vehicles.

[1850] Real-time updates

[1851] The system continuously acquires the user's current location and dynamically recalculates routes as needed, responding to sudden changes in traffic conditions and road construction, and providing the latest route information at all times.

[1852] Audio and visual guidance

[1853] The device provides users with audio and visual route guidance, improving safety and comfort.

[1854] Specific examples

[1855] Route guidance for seniors

[1856] If the user is an elderly person who wants to get from their home to city hall but wants to avoid hills, the system will provide a flat route that avoids hills.

[1857] Route guidance for tourists

[1858] If a user wishes to efficiently tour tourist attractions, the server will calculate the optimal route, taking into account the location information and opening hours of the tourist attractions.

[1859] Prompt Sentence Examples

[1860] "The starting point is home. The destination is City Hall, and I want to avoid the highway."

[1861] This invention provides a navigation system that meets the diverse needs of users and enables optimal route guidance tailored to specific requests. Real-time location information updates and dynamic route recalculation ensure safe and efficient travel based on the latest information.

[1862] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1863] Step 1:

[1864] The user launches a terminal application and inputs a starting point, a destination, and specific requests. The inputs include the coordinates of the starting point, the coordinates of the destination, and the desired conditions (e.g., avoid hills). The terminal formats this data appropriately and sends it to the server.

[1865] Step 2:

[1866] The server analyzes the user data received from the device. The input data includes the starting point, destination, and specific requests. Based on this, the server accesses a geographic information database to collect road information, slope gradients, tourist attraction locations, traffic conditions, and road conditions. The output data is the required geographic information.

[1867] Step 3:

[1868] The server analyzes the collected geographic information data and calculates the optimal route based on the specific request. As input, it receives the geographic information data collected in step 2 and the specific request entered by the user. For data processing, it uses a generative AI model to calculate the optimal route. As output, it obtains candidate optimal routes that take the specific request into account.

[1869] Step 4:

[1870] The server analyzes the user's speed and acceleration data and past movement history to identify the user's state. It receives the user's history data and real-time movement data as input. It uses an analysis algorithm to calculate the data and identify the user's current state (e.g., elderly, type of vehicle). It obtains user characteristic information as output.

[1871] Step 5:

[1872] The server further calculates the optimal route based on the user's characteristics, preferences, and behavioral patterns. As input, it receives the route candidates from step 3 and the user characteristics information from step 4. As output, it obtains the final generated optimal route information.

[1873] Step 6:

[1874] The server sends the generated optimal route information to the user terminal. The optimal route information is received as input. The route data to be sent to the user terminal is obtained as output.

[1875] Step 7:

[1876] The terminal provides route guidance to the user based on the optimal route received. Optimal route data is received from the server as input, and visual and audio route guidance is performed. Data processing involves displaying a map, visualizing the route, and generating audio guidance.

[1877] Step 8:

[1878] The device continuously tracks the user's current location and sends that location information to the server. As input, it receives the user's real-time location information. As output, it periodically sends location information to the server.

[1879] Step 9:

[1880] The server dynamically recalculates the route based on the transmitted real-time location information. It receives location information from the device as input. It recalculates the route by taking into account changes in traffic conditions and road environment as data calculations. It obtains updated optimal route information as output.

[1881] Step 10:

[1882] The terminal provides updated guidance to the user based on the latest route information received from the server. As input, it receives updated route data from the server. As output, it obtains the latest visual and audio guidance provided to the user.

[1883] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1884] This invention is a navigation system that responds to the diverse needs of users and provides optimal routes, and by combining it with an emotion engine that recognizes the user's emotions and reflects them in route guidance, it realizes a more personalized service. The specific operation of this system will be described below.

[1885] User Input Processing

[1886] 1. User provides input (User)

[1887] A user launches the application on the device and inputs their starting point, destination, and specific needs, such as an elderly person wanting to get to city hall but avoiding hills.

[1888] 2. Receiving user input (terminal)

[1889] The terminal receives user input data and transmits the appropriately formatted data to the server.

[1890] Data collection and analysis

[1891] 3. Data transmission and reception (terminal and server)

[1892] The terminal transmits user data to the server, and the server receives the data.

[1893] 4. Database Access (Server)

[1894] The server accesses a geographic information database and collects information such as road information, slope gradients, and the locations of tourist attractions.

[1895] 5. Data analysis (server)

[1896] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[1897] User situation analysis

[1898] 6. User status analysis (server)

[1899] The server analyzes the user's walking acceleration data and past movement history to identify the user's current status (e.g., elderly, large vehicle user).

[1900] Emotion recognition by emotion engine

[1901] 7. Emotion recognition data acquisition (device)

[1902] The device operates an emotion engine that recognizes the user's emotions and obtains the user's current emotional data, for example, through a facial recognition camera or voice analysis.

[1903] 8. Emotional Data Analysis (Server)

[1904] The server analyzes the user's emotion data collected by the emotion engine and reflects it in route suggestions.

[1905] Optimal route generation

[1906] 9. Route calculation (server)

[1907] The server uses a generative AI model to calculate the optimal route for the user based on the collected and analyzed data.

[1908] 10. Route Evaluation (Server)

[1909] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[1910] Personalize and send

[1911] 11. Personalization (Server)

[1912] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[1913] 12. Route information generation and transmission (server)

[1914] The server generates coordinate information for the optimal route and sends it to the terminal.

[1915] 13. Route guidance (terminal)

[1916] The device receives route information and provides users with directions, using map displays, voice guidance, and real-time location tracking.

[1917] Improved user experience for route guidance

[1918] 14. Audio guide adjustments (device)

[1919] Based on the emotional data generated by the emotion engine, the device changes the tone and content of the voice guidance to match the user's emotional state. For example, if a user is feeling anxious, the device will provide guidance in a more friendly tone.

[1920] Real-time updates

[1921] 15. Real-time data reception and updates (terminal and server)

[1922] The device tracks the user's current location in real time using GPS and sends that information to the server, which then recalculates the route as needed based on the latest information and sends the updated route information to the device.

[1923] 16. Latest route guidance (terminal)

[1924] The device continues to update the guidance based on the latest route information received.

[1925] Specific examples

[1926] Example 1: Route for seniors

[1927] 1. User input: An elderly user inputs, "I want to get from my house to city hall, avoiding slopes."

[1928] 2. Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[1929] 3. Emotion recognition: The device recognizes anxiety from the user's facial expressions.

[1930] 4. Route generation: The server calculates and evaluates routes that prioritize flat roads.

[1931] 5. Route guidance: The device displays a smooth and safe route and provides voice guidance in a friendly tone.

[1932] Example 2: Tourist Route

[1933] 1. User input: A tourist inputs, "I would like to visit tourist attractions in the area."

[1934] 2. Data collection and analysis: The server collects and analyzes information such as the location and opening hours of tourist attractions.

[1935] 3. Emotion recognition: The device recognizes excitement from the user's tone of voice.

[1936] 4. Route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[1937] 5. Route guidance: The device displays a route to visit tourist attractions in the optimal order and provides guidance in an energetic tone.

[1938] Features of this system

[1939] This navigation system provides routes tailored to the specific needs of users and suggests optimal travel routes that meet the requirements of different users, such as the elderly, tourists, and transportation workers. It also uses an emotion engine to recognize users' emotional data and provide route guidance tailored to their emotions in real time, providing a better user experience. By utilizing a generative AI model and a geographic information database to analyze users' states and emotions, it provides more personalized services and ensures comfortable and efficient travel.

[1940] The processing flow will be explained below.

[1941] Step 1:

[1942] The user starts the application on the terminal and inputs the starting point, destination, and specific needs (e.g., avoiding hills, not using highways, etc.).

[1943] Step 2:

[1944] The terminal receives the user's input data and formats it appropriately.

[1945] Step 3:

[1946] The terminal transmits the prepared user data to the server.

[1947] Step 4:

[1948] The server receives the user data from the terminal.

[1949] Step 5:

[1950] The server accesses a geographic information database and collects relevant data (e.g., road information, slope gradient, location information of tourist attractions, etc.).

[1951] Step 6:

[1952] The server analyzes the collected geographic information data and extracts the information necessary to meet the user's specific needs.

[1953] Step 7:

[1954] The server uses the user's walking acceleration data and past movement history to analyze the user's current state (e.g., elderly, large vehicle user).

[1955] Step 8:

[1956] The device runs an emotion engine to acquire the user's emotion data. For example, emotions are extracted from facial expressions and tone of voice using a camera or microphone.

[1957] Step 9:

[1958] The server receives and analyzes the user's emotion data collected by the emotion engine.

[1959] Step 10:

[1960] The server uses the generative AI model to calculate the optimal route based on the user's characteristics and emotional data, for example, calculating a flat route or a route that efficiently visits tourist spots.

[1961] Step 11:

[1962] The server evaluates the calculated route to ensure safety, efficiency, and user comfort.

[1963] Step 12:

[1964] The server generates coordinate information for the optimal route and sends it to the terminal.

[1965] Step 13:

[1966] The terminal receives the optimal route information from the server and displays it on the screen to provide guidance to the user. Voice guidance is also provided at the same time.

[1967] Step 14:

[1968] The device tracks the user's current location in real time using GPS and sends that information to a server.

[1969] Step 15:

[1970] The server dynamically recalculates the route if necessary based on real-time location information and sends updated route information to the device.

[1971] Step 16:

[1972] The device continuously updates the guidance based on the latest route information, and adjusts the tone and content of the voice guidance based on the user's emotional state.

[1973] Specific examples

[1974] Example 1: Route for seniors

[1975] Step 1: An elderly user inputs, "I want to walk from my home to city hall, avoiding slopes."

[1976] Step 2: The terminal receives the user's input data and sends it to the server.

[1977] Step 3: The server receives the data and collects road data and slope gradient information from the geographic information database.

[1978] Step 4: The server analyzes the data and extracts information about flat roads.

[1979] Step 5: The device activates its emotion engine and recognizes anxiety from the user's facial expression.

[1980] Step 6: The server analyzes the emotion data and uses it to calculate the route.

[1981] Step 7: The server uses the generative AI model to calculate a flat route.

[1982] Step 8: The server evaluates the calculation results and sends the optimal route to the terminal.

[1983] Step 9: The device displays a flat route and provides voice directions in a friendly tone.

[1984] Example 2: Tourist Route

[1985] Step 1: The tourist enters, "I would like to visit tourist attractions in the area."

[1986] Step 2: The terminal receives the user's input data and sends it to the server.

[1987] Step 3: The server receives the data and collects the location information and business hours data of the tourist attractions.

[1988] Step 4: The server analyzes the data and extracts information for efficiently touring tourist attractions.

[1989] Step 5: The device activates its emotion engine and recognizes excitement from the user's tone of voice.

[1990] Step 6: The server analyzes the emotion data and uses it to calculate the route.

[1991] Step 7: The server uses the generative AI model to calculate an efficient route around the tourist attractions.

[1992] Step 8: The server evaluates the calculation results and sends the optimal route to the terminal.

[1993] Step 9: The device displays the optimal route and provides voice guidance in an energetic tone.

[1994] Example 2

[1995] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1996] Conventional navigation systems focus on simple route guidance based on a starting point and destination, making it difficult to provide personalized routes that take into account the user's specific needs and emotional state. Furthermore, they are unable to adequately adjust route guidance to reflect the user's current location and emotional data in real time, leaving the user experience open to improvement. Information analysis to address specific needs, such as avoiding slopes or visiting tourist attractions, is also limited.

[1997] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1998] In this invention, the server comprises means for receiving data from the user regarding the starting point, destination and specific needs;

[1999] means for analyzing the collected user data and collecting necessary data from related geographic information databases;

[2000] A means for analyzing the user's walking acceleration data and past movement history;

[2001] This allows for personalized routes that take into account the user's specific needs and emotional state.

[2002] The "starting point" is the location where the user starts their journey.

[2003] The "destination" is the final destination of the user's journey.

[2004] "Specific needs" are special requirements or desires that a user has when traveling.

[2005] "User data" refers to information such as starting point, destination, specific needs, walking acceleration data, past movement history, and emotional data.

[2006] A "geographic information database" is a collection of data that stores geographic information, including road width, slope gradient, and location information of tourist attractions.

[2007] "Walking acceleration data" is data obtained from an acceleration sensor while the user is walking.

[2008] "Past movement history" is data on the movement routes and movement patterns that the user has taken in the past.

[2009] "Emotion data" is information that indicates the user's current emotional state, and is obtained by facial expression and voice analysis, for example.

[2010] A "generative AI model" is an artificial intelligence model that makes route suggestions and predictions based on large amounts of data.

[2011] An "optimal route" is one that takes into maximum consideration the user's specific needs and emotional state, and provides an efficient, safe, and comfortable journey.

[2012] A "personalized route" is a route that is tailored based on a user's individual preferences and behavioral patterns.

[2013] "Voice guide" refers to guidance information provided by the navigation system through speech.

[2014] "Continuously obtain in real time" refers to constantly updating and obtaining the user's current location information.

[2015] "Dynamic recalculation" refers to the process of optimizing an existing route on an ongoing basis based on newly acquired data.

[2016] This invention is a navigation system that responds to various user needs and provides optimal routes. This system also realizes more personalized services by combining it with an emotion engine that recognizes the user's emotions and reflects them in route guidance.

[2017] System Overview

[2018] This system mainly operates around three elements: the server, the terminal, and the user.

[2019] 1. User Input Processing:

[2020] Users launch a navigation app on their smartphone or tablet and input their starting point, destination, and specific needs (for example, "I want to avoid hills when getting from my house to city hall").

[2021] The terminal receives user input, formats it in an appropriate format, and sends the data to the server, typically using JSON as the transmission format.

[2022] 2. Data collection and analysis:

[2023] The terminal transmits user data to the server, which receives it.

[2024] The server accesses a geographic information database (e.g., Google Maps API) to collect road information, slope gradients, and location information of tourist attractions.

[2025] The server analyzes the collected data and extracts the necessary information to address the user's specific needs.

[2026] 3. User situation analysis:

[2027] The server analyzes the user's walking acceleration data and past movement history to identify the user's current status (elderly, large vehicle user, etc.).

[2028] 4. Emotion Recognition with Emotion Engine:

[2029] The device runs an emotion recognition engine and acquires the user's emotional data (facial expressions and voice analysis).

[2030] The server analyzes the emotion data and reflects it in route suggestions.

[2031] 5. Optimal route generation:

[2032] The server uses a generative AI model (such as GPT-4) to calculate the optimal route based on the collected and analyzed data.

[2033] The server evaluates the calculated route to ensure safety, efficiency and user comfort.

[2034] 6. Personalization and Delivery:

[2035] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions.

[2036] The server generates coordinate information for the optimal route and sends it to the terminal.

[2037] The device then provides users with directions based on the route information it receives, using map displays, voice guidance, and real-time location tracking.

[2038] 7. Improved user experience for route guidance:

[2039] Based on the emotional data, the device adjusts the tone and content of the voice guidance to match the user's emotional state, providing guidance in a friendly tone to users who are feeling anxious.

[2040] 8. Real-time updates:

[2041] The device tracks the user's current location in real time using GPS and sends that information to a server.

[2042] The server recalculates the route as needed based on the latest information and sends the updated route information to the terminal.

[2043] The device will continue to update the directions based on the latest route information it receives.

[2044] Specific examples

[2045] 1. Route for seniors:

[2046] User input: "I want to avoid hills when walking from my house to City Hall."

[2047] Data collection and analysis: The server collects and analyzes road data and slope gradient information.

[2048] Emotion recognition: The device recognizes anxiety from the user's facial expression.

[2049] Route generation: The server calculates and evaluates routes that prioritize flat roads.

[2050] Route guidance: The device displays a smooth, safe route and provides voice guidance in a friendly tone.

[2051] 2. Tourist Route:

[2052] User input: "I want to visit tourist attractions in the area."

[2053] Data collection and analysis: The server collects and analyzes information about the location and business hours of tourist attractions.

[2054] Emotion recognition: The device recognizes excitement from the user's tone of voice.

[2055] Route generation: The server calculates and evaluates routes that efficiently visit tourist spots.

[2056] Route guidance: The device displays a route to visit tourist attractions in the optimal order and provides guidance in an energetic tone.

[2057] As described above, this navigation system can provide a better user experience by providing routes tailored to the user's specific needs and utilizing emotion recognition to provide personalized guidance in real time.

[2058] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2059] Step 1:

[2060] User provides input (User)

[2061] A user launches a navigation app and inputs their starting point, destination, and specific needs (e.g., "I want to avoid hills"). The input is entered into text boxes in a form in the app. The input data is formatted as JSON and sent to the server.

[2062] Input: Starting point, Destination, Specific needs

[2063] Output: User input data in JSON format

[2064] Step 2:

[2065] Accepting user input (terminal)

[2066] The device receives the information entered by the user and sends the data to the server. Specifically, when a button is pressed, an HTTP request is generated and the input data is transferred to the server.

[2067] Input: User-supplied data in JSON format

[2068] Output: Forwarded to the server as an HTTP request

[2069] Step 3:

[2070] Data transmission and reception (terminal and server)

[2071] The device sends user input data to the server, which receives the data and passes it to the analysis module.

[2072] Input: User-supplied data as an HTTP request

[2073] Output: Data objects available on the server

[2074] Step 4:

[2075] Database access (server)

[2076] The server accesses the geographic information database to obtain the necessary road information, slope gradients, and location information for tourist attractions. Specifically, it sends an API request to the geographic information database and passes the data obtained in response to the analysis module.

[2077] Input: User's starting and destination information

[2078] Output: Geographical information (road information, slope gradient, location information of tourist attractions)

[2079] Step 5:

[2080] Data analysis (server)

[2081] The server analyzes the collected geographical information and extracts information to meet the user's specific needs, for example, filtering road gradient information to calculate routes that avoid hills.

[2082] Input: Geographical information data

[2083] Output: Parsed route information

[2084] Step 6:

[2085] User status analysis (server)

[2086] The server analyzes the user's walking acceleration data and past movement history to determine the user's current state, and inputs this data into a machine learning model to determine whether the user is elderly or a wheelchair user.

[2087] Input: Acceleration data during walking, past movement history

[2088] Output: User characteristics data (elderly, wheelchair users, etc.)

[2089] Step 7:

[2090] Emotion recognition data acquisition (device)

[2091] The device activates an emotion recognition engine to obtain user emotional data through facial expression and voice analysis, and uses the camera and microphone to capture the user's emotional state in real time.

[2092] Input: The user's current facial expression and voice data

[2093] Output: Retrieved emotion data

[2094] Step 8:

[2095] Emotion data analysis (server)

[2096] The server analyzes the acquired emotion data to identify the user's current emotional state. The emotion engine inputs the acquired data into multiple emotion models and identifies the user's emotion based on the results.

[2097] Input: Emotion data

[2098] Output: Parsed emotional state

[2099] Step 9:

[2100] Route calculation (server)

[2101] The server uses the generative AI model to calculate the optimal route based on the analyzed data. Specifically, the server inputs the prompt "Please provide the optimal route if the user wants to go from home to city hall while avoiding slopes" into the generative AI model and obtains the calculation result.

[2102] Input: Parsed user data and prompt statements

[2103] Output: Optimal route

[2104] Step 10:

[2105] Route Evaluation (Server)

[2106] The server evaluates the calculated routes to check safety, efficiency, and user comfort, assigns a score based on the evaluation criteria, and selects the best route.

[2107] Input: Optimal route suggestions

[2108] Output: Evaluated route

[2109] Step 11:

[2110] Personalization (Server)

[2111] The server learns the user's preferences and behavioral patterns and reflects them in future route suggestions. The learning module analyzes the user's past data and updates the personalized model.

[2112] Input: User's past behavior data

[2113] Output: A trained personalized model

[2114] Step 12:

[2115] Route information generation and transmission (server)

[2116] The server generates coordinate information for the optimal route and sends it to the device. The route data is converted to JSON format and transferred to the device as an HTTP response.

[2117] Input: Evaluated route information

[2118] Output: Route data in JSON format

[2119] Step 13:

[2120] Route guidance (terminal)

[2121] The device provides the user with directions based on the received route information, using map display and voice guidance to provide real-time location tracking and guidance to the user.

[2122] Input: Route data in JSON format

[2123] Output: Map display, voice guidance

[2124] Step 14:

[2125] Audio guide adjustments (device)

[2126] The device adjusts the tone and content of the voice guidance to match the user's emotional state based on the emotion data, providing guidance in a friendly tone to an anxious user and guidance in an energetic tone to an excited user.

[2127] Input: Parsed emotional state data

[2128] Output: Adjusted voice prompts

[2129] Step 15:

[2130] Real-time data reception and updates (terminal and server)

[2131] The device tracks the user's current location in real time using GPS and sends that information to the server, which then recalculates the route as needed based on the latest information and sends the updated route information to the device.

[2132] Input: Real-time location of the user

[2133] Output: Updated route information

[2134] Step 16:

[2135] Latest route guidance (terminal)

[2136] The device continuously updates its guidance based on the latest route information received, providing users with the latest information and helping them reach their destination safely and efficiently.

[2137] Input: Updated route information

[2138] Output: Updated map display, voice guidance

[2139] (Application example 2)

[2140] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2141] Conventional navigation systems have difficulty providing optimal route guidance to users because they are unable to fully reflect the user's specific needs and real-time emotional state. Furthermore, existing systems do not adapt voice guidance to reflect the user's emotions, and personalized services are not provided. This creates a need for reducing stress during travel and increasing user satisfaction.

[2142] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving data regarding the starting point, destination, and specific needs from the user, means for analyzing the collected user data and collecting necessary data from a related geographic information database, means for calculating an optimal route using a generative AI model, means for acquiring the user's emotional state through facial expression recognition and voice analysis, and means for adjusting the tone and content of audio guidance to suit the user based on the emotional state. This enables optimal route guidance based on the user's specific needs and emotional state, and allows for the provision of personalized, advanced navigation services.

[2143] A "user" is a person who uses the navigation system.

[2144] The "starting point" is the location where the user begins their journey.

[2145] A "destination" is a location that a user wishes to reach.

[2146] "Specific needs" refers to special requirements or desires that a user has while traveling.

[2147] "Means" refers to a method or apparatus for achieving a specific function or operation.

[2148] "Walking acceleration data" is acceleration information acquired while the user is walking.

[2149] "Past travel history" is a record of the routes and places the user has traveled to so far.

[2150] A "generative AI model" is an artificial intelligence model that calculates optimal routes based on large amounts of data.

[2151] "User preferences and behavioral patterns" is data that indicates the movement and preference trends that the user has shown in the past.

[2152] "Transmit" is the act of sending data to another device or system.

[2153] A "user terminal" is a device that can be directly operated by a user.

[2154] "Guidance" refers to providing information to guide the user in a specific direction.

[2155] "Facial expression recognition" is a technology that uses cameras and sensors to analyze a user's facial expressions.

[2156] "Voice analysis" is a technology that analyzes voice data to identify a user's emotions and intentions.

[2157] "Emotional state" refers to the emotional state that the user is currently feeling.

[2158] "Audio guidance" is a method of providing instructions and information to a user using audio.

[2159] "Tone" refers to the pitch and texture of a voice.

[2160] The present invention is a navigation system that provides an optimal route taking into account the specific needs and emotional state of the user. The system is composed of a server and a user terminal.

[2161] User device capabilities:

[2162] The user terminal has the function of receiving data from the user regarding the starting point, destination, and specific needs. It also has the function of obtaining the user's emotional state through facial expression recognition and voice analysis. The user terminal appropriately formats this data and transmits it to the server. At the same time, the user terminal receives the optimal route information transmitted from the server and provides guidance to the user. The guidance also includes the function of changing the tone and content of the voice guidance according to the user's emotional state.

[2163] Server capabilities:

[2164] The server receives and analyzes the data sent from the user's device. First, it accesses a geographic information database to collect the necessary data. Then, it uses a generative AI model to calculate the optimal route, taking into account the user's specific needs and emotional state. It also has the ability to learn the user's preferences and behavioral patterns and reflect them in future route suggestions. The calculated optimal route information is then sent back to the user's device.

[2165] Examples of hardware and software used:

[2166] Smartphones and tablets: Used for user input and display.

[2167] Camera and microphone: Used for facial expression recognition and voice analysis to capture emotional state.

[2168] GPS system: Used to track your location and update your route in real time.

[2169] Python-based application: Used to execute the entire program logic.

[2170] HTTP Requests library (requests): Used to send and receive data.

[2171] Generative AI models: used to calculate optimal routes and generate personalized suggestions.

[2172] Examples:

[2173] The user (driver) opens a smartphone app and inputs the "optimal route from home to work," as well as specific needs and emotions such as "wanting to avoid traffic jams" or "wanting to relax." The app sends this data to a server, which uses a generative AI model to calculate the optimal route. The server then selects the optimal route and an appropriate voice guide (relaxing tone) and provides it to the self-driving vehicle.

[2174] Example prompt sentence:

[2175] "Write Python code for a navigation system for a self-driving car that recognizes emotions and suggests the best route. The user inputs their starting point, destination, specific needs, and emotion. Provide a safe and efficient route, including voice guidance based on the emotion."

[2176] This allows for optimal route guidance based on the user's specific needs and emotional state, providing a highly personalized navigation service.

[2177] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2178] Step 1:

[2179] The user enters the starting point, destination, and specific needs into the text input fields and launches the terminal application. The user then inputs their current location, destination, and specific needs, such as "I want to avoid traffic jams and relax," into the application. The input data is saved in the application as starting point, destination, and specific needs data.

[2180] Step 2:

[2181] The device u...

Claims

1. means for receiving data from a user regarding origin, destination, and specific needs; means for analyzing the collected user data and collecting necessary data from related geographic information databases; A means for analyzing the user's walking acceleration data and past movement history; A means to calculate the optimal route using a generative AI model; and A means to learn user preferences and behavioral patterns and reflect them in future route suggestions; means for transmitting the generated optimum route information to a user terminal; means for guiding a user to an optimum route in a user terminal; A system including:

2. 10. The system of claim 1, further comprising means for continuously obtaining the user's current location in real time and dynamically recalculating the route as needed.

3. 2. The system according to claim 1, further comprising means for extracting information on road widths, slope gradients, and location information of tourist attractions when analyzing the collected geographic information data.

Images