System

Abstract

To provide a system that prepares a mountaineering schematic diagram suitable for a user.SOLUTION: The present system includes the means of: acquiring information on a departure point, and a destination point; acquiring topography information from a topographic map database; using an emotion engine to identify an emotion of a user; generating a prompt sentence instructing generation of mountaineering route information on the basis of information on the acquired destination point and destination point, and the topography information; generating the mountaineering route information, using the generated prompt sentence and a generative AI model; generating a prompt sentence instructing generation of a mountaineering schematic diagram on the basis of the generated mountaineering route information, and the identified emotion state of the user; using the generated prompt sentence and a generative AI model to generate the mountaineering schematic diagram; and suggesting the generated mountaineering schematic diagram to the user.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 a description and related instruction sentence regarding 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] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] It is very difficult for climbers (especially beginners) to read detailed information about the terrain from a topographical map. In addition, creating a simple mountain climbing map that includes climbing routes, terrain (ridges and valleys), and surrounding information (mountain huts), in other words, a mountain climbing concept map, requires a certain level of skill and experience. [Means for solving the problem]

[0005] The present invention uses AI that inputs climbing route information based on a topographical map and generates how to read and write topographical features based on the climbing route information. Then, using the how to read and write the topographical features generated by the AI, a climbing concept map is automatically created. This makes it possible to visualize the topographical map in a way that is easy for climbers to understand. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 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. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 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. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 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. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16] FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0011] 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.

[0012] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] 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. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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 wide area network (WAN) and / or a local area network (LAN).

[0018] 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.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. 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.

[0020] 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 (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Fig. 2, 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. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process 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 process program 56 executed on the RAM 30.

[0024] 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.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] In one embodiment of the present invention, a climber inputs climbing route information based on a topographical map into the system. This climbing route information includes, for example, the start and end points of the route planned by the climber, waypoints, and points requiring special attention. Next, an AI in the system generates how to read and write topographical features based on the climbing route information. This AI generates how to read and write topographical features by reading detailed information on the topographical map. Finally, the system automatically creates a climbing concept map using how to read and write topographical features generated by the AI. This climbing concept map is created including surrounding information other than the climbing route (mountain huts, etc.).

[0029] "Example 2"

[0030] As another embodiment of the present invention, when a climber inputs climbing route information based on a topographical map into the system, the climber can input the information in a format that is easy to understand intuitively. For example, climbing route information can be input by drawing the route directly on the topographical map. In addition, when the system automatically creates a climbing concept map using how to read and write the topographical features generated by AI, the system displays the climbing concept map in a visually easy-to-understand format that is easy for climbers to understand. For example, topographical features, climbing routes, and surrounding information are expressed using colors, line thicknesses, symbols, etc.

[0031] The process flow of each embodiment will be described below.

[0032] "Example 1"

[0033] Step 1: A climber inputs climbing route information based on a topographical map into the system. This climbing route information includes, for example, the start and end points of the climber's planned route, intermediate points, and points requiring special caution.

[0034] Step 2: The AI ​​in the system generates how to read and write the topographical features based on the climbing route information. This AI generates how to read and write the topographical features by reading the detailed information on the topographical map.

[0035] Step 3: The system automatically creates a mountain climbing concept map using the AI-generated reading and writing of terrain features. This mountain climbing concept map is created including surrounding information (mountain huts, etc.) other than the climbing route.

[0036] "Example 2"

[0037] Step 1: When climbers input climbing route information based on a topographical map into the system, the input should be in a format that is intuitive and easy for climbers to understand. For example, climbing route information can be input by drawing the route directly on a topographical map.

[0038] Step 2: The AI ​​in the system generates how to read and write the topographical features based on the climbing route information. This AI generates how to read and write the topographical features by reading the detailed information on the topographical map.

[0039] Step 3: The system uses the AI-generated methods for reading and writing terrain features to automatically create a mountaineering concept map, which is displayed in a visually easy-to-understand format for climbers to understand. For example, colors, line thicknesses, symbols, etc. are used to represent terrain features, climbing routes, and surrounding information.

[0040] Example 1

[0041] Next, a description will be given of Example 1 of the embodiment 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".

[0042] In conventional mountain climbing planning systems, when climbers input detailed climbing route information based on topographical maps, they had to understand how to read and write topographical features and enter them appropriately. This made it difficult for climbers without specialized knowledge of topographical maps to make accurate climbing plans, and also made it difficult to create comprehensive climbing concept maps that included surrounding information (such as accommodation facilities) other than the climbing route. This led to issues such as a decrease in the accuracy of climbing plans and difficulty in ensuring safety during climbing.

[0043] 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.

[0044] In this invention, the server includes a means for a climber to input climbing route information based on a topographical map, a means for acquiring topographical map data based on the climbing route information, a generation AI model means for analyzing the topographical map data and generating how to read and write topographical features, a means for automatically creating a climbing concept map using the how to read and write topographical features generated by the generation AI model means, and a means for displaying the climbing concept map on a user's terminal. This allows climbers to make accurate climbing plans even without specialized knowledge, and makes it easy to create a comprehensive climbing concept map that includes peripheral information other than the climbing route.

[0045] "Climber" refers to an individual or group engaged in mountaineering activities.

[0046] A "topographic map" is a map showing detailed information about a terrain, including contour lines and topographical features.

[0047] "Mountain climbing route information" refers to information such as the starting point, end point, waypoints, and points requiring caution on the mountain climbing route planned by the climber.

[0048] "Server" refers to a computer system that processes and stores data.

[0049] "Terminal" refers to a device that allows a user to input information and display results, including, for example, a smartphone or a personal computer.

[0050] "Topographical map data" means digital data based on a topographical map and includes detailed information on the topography.

[0051] "Generative AI model" refers to a model that uses artificial intelligence to perform a specific task, in this case, generating ways to read or write topographical features.

[0052] A "mountain climbing concept map" refers to a diagram that visually shows a mountain climbing route and the surrounding information.

[0053] "Accommodation" refers to facilities where climbers can stay overnight. Examples include mountain huts and campsites.

[0054] This invention is a system that allows a climber to input climbing route information based on a topographical map, generates how to read and write topographical features based on that information, and finally automatically creates a climbing concept map. A specific embodiment of this system will be described below.

[0055] First, the user uses the terminal to input climbing route information. The user inputs the start and end points of the planned route, intermediate points, and points requiring special caution. For example, the user opens a smartphone app and inputs into the input form, "From the fifth station of Mt. Fuji to the summit of Mt. Fuji, intermediate points are the sixth, seventh, and eighth stations, and points requiring caution are the steep slope at the seventh station."

[0056] Next, the server receives the climbing route information input by the user and acquires topographical map data. Specifically, the server acquires topographical map data related to the specified route using Google (registered trademark) Maps API or OpenStreetMap API. For example, the server sends a request to the API to "acquire topographical map data from the fifth station of Mt. Fuji to the summit of Mt. Fuji."

[0057] The generative AI model in the server then analyzes the acquired topographical map data. The generative AI model reads the topographical map data and analyzes the topographical features of each point. For example, the AI ​​identifies the "steep slope at the seventh station" and analyzes its features in detail.

[0058] Next, the generative AI model generates how to read and write the topographical features based on the analysis results. Specifically, the AI ​​generates information such as "The steep slope at the seventh station requires special caution." For example, the AI ​​generates instructions such as "Use specific icons and colors to highlight the steep slope feature."

[0059] The server then automatically creates a mountain climbing concept map using the reading and writing of the terrain features generated by the generative AI model. Specifically, the server combines the topographical map data with the generated information to create a visually easy-to-understand mountain climbing concept map. For example, the server performs a process such as "displaying the route from the fifth station of Mt. Fuji to the summit of Mt. Fuji in red, and displaying the steep slope at the seventh station with a yellow warning icon."

[0060] Finally, the server sends the created mountain climbing concept map to the user's terminal and displays it. Specifically, the mountain climbing concept map is displayed on the user's smartphone or PC. For example, the user checks on the screen of their smartphone "a mountain climbing concept map that visually displays the route from the fifth station of Mt. Fuji to the summit of Mt. Fuji, each waypoint, and points requiring caution."

[0061] Examples of concrete examples and prompts

[0062] Examples

[0063] The user opens the app on their smartphone and enters the following information:

[0064] Starting point: Mount Fuji 5th Station

[0065] End point: The summit of Mt. Fuji

[0066] Waypoints: 6th, 7th, 8th stations

[0067] Areas requiring caution: Steep slope at the seventh station

[0068] The server uses the Google Maps API to obtain topographical map data from the fifth station of Mt. Fuji to the summit. Next, a generative AI model in the server analyzes the topographical map data and identifies the characteristics of the steep slope at the seventh station. The AI ​​generates information such as "particular caution is required on steep slopes," and the server uses this information to create a conceptual map of the climb. Finally, the server sends the conceptual map created by the server to the user's smartphone, where the user can check it on the screen.

[0069] Examples of prompt statements

[0070] "I am planning a climbing route from the fifth station of Mt. Fuji to the summit of Mt. Fuji. I will include the sixth, seventh, and eighth stations as waypoints, and I must be careful of the steep slope of the seventh station. Please create a conceptual map of the climb based on this information."

[0071] The above is an embodiment of the invention.

[0072] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0073] Step 1:

[0074] A user inputs climbing route information using a terminal.

[0075] Specifically, the user opens the application on their smartphone or PC and enters the start point, end point, intermediate points, and points requiring caution of the planned route into an input form.

[0076] Input: Climbing route information (starting point, ending point, intermediate points, points requiring caution)

[0077] Output: Route information sent to the server

[0078] Step 2:

[0079] The server receives the climbing route information input by the user and obtains the topographical map data.

[0080] Specifically, the server uses the Google Maps API or the OpenStreetMap API to retrieve topographical map data related to the specified route.

[0081] Input: Climbing route information

[0082] Output: Topographic map data

[0083] Step 3:

[0084] A generative AI model on the server analyzes the acquired topographical map data.

[0085] Specifically, the generative AI model reads topographical map data and analyzes the terrain features of each location, identifying features such as steep slopes and cliffs.

[0086] Input: Topographic map data

[0087] Output: Analysis results of terrain features

[0088] Step 4:

[0089] A generative AI model generates readings and writings for topographical features based on the analysis results.

[0090] Specifically, the AI ​​generates information such as "particular caution is required on steep slopes" and generates instructions to use specific icons and colors.

[0091] Input: Topographic feature analysis results

[0092] Output: How to read and write topographical features

[0093] Step 5:

[0094] The server automatically creates a mountain climbing concept map using how to read and write the terrain features generated by the generative AI model.

[0095] Specifically, the server combines the topographical map data with the generated information to create a visually easy-to-understand mountain climbing concept map. For example, the route is displayed in red and steep slopes are displayed with a yellow warning icon.

[0096] Input: Topographic map data, how to read and write topographic features

[0097] Output: Mountain climbing concept diagram

[0098] Step 6:

[0099] The server transmits the created mountain climbing concept map to the user's terminal and displays it.

[0100] Specifically, a conceptual map of the climb is displayed on the user's smartphone or PC. The user can check the conceptual map on the screen, which visually displays the route, each waypoint, and points requiring caution.

[0101] Input: Mountain climbing concept diagram

[0102] Output: A conceptual diagram of the climb displayed on the user's device

[0103] (Application example 1)

[0104] Next, a description will be given of Application Example 1 of Form 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."

[0105] For autonomous vehicles, there is a need to generate optimal driving routes based on topographical maps and road information, and provide route maps that include points requiring special attention and surrounding information. However, current systems have the problem that it is difficult to efficiently analyze this information and display it visually.

[0106] The identification process by the identification processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for inputting route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the route information, a means for automatically creating a conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and a means for displaying the conceptual map. This makes it possible to generate an optimal driving route for an autonomous vehicle and efficiently provide a route map including points requiring special attention and surrounding information.

[0107] A "topographic map" is a map that contains detailed information about the terrain, visually showing the relief and characteristics of the terrain.

[0108] "Route information" refers to information about a route, such as a starting point, a destination point, and intermediate points.

[0109] An "artificial intelligence means" is a system that uses technologies such as machine learning and deep learning to analyze data and automatically perform specific tasks.

[0110] "Topographical features" refers to the relief and shape of the terrain shown on a topographical map, and the characteristics of a specific point.

[0111] "Reading and writing" refers to ways of understanding and visually representing topographical features.

[0112] A "conceptual map" is a diagram that visually simplifies specific information and includes routes and surrounding information.

[0113] The term "display means" refers to a device or system for visually displaying the generated conceptual diagram or other information.

[0114] "Nearby information" is information about points related to the route, including facilities such as rest areas and gas stations.

[0115] As an embodiment of the present invention, an "automated driving route optimization system" for automated driving vehicles will be described as an example. This system generates an optimal driving route based on topographical maps and road information, and provides a route map that includes points requiring special attention and surrounding information.

[0116] Hardware and Software Used

[0117] Hardware: On-board computer, GPS module, camera, LiDAR sensor for autonomous vehicles

[0118] Software: TENSORFLOW (registered trademark) (AI model training and inference), OpenStreetMap API (obtaining topographical maps and road information), Python (programming language)

[0119] Data processing and calculation

[0120] Data Entry

[0121] Users input start, destination and intermediate points into the autonomous vehicle's on-board computer, and the system then uses the OpenStreetMap API to retrieve topographical and road information for the specified route.

[0122] Analysis by AI model

[0123] The server uses TensorFlow to analyze the retrieved topographical map and road information and generate readings and writings of topographical features, which identify areas that require special attention (sharp curves, steep gradients, intersections, etc.).

[0124] Route Optimization

[0125] The server calculates the optimal driving route based on how the AI ​​model reads and writes the terrain features, taking into account surrounding information (gas stations, rest areas, etc.).

[0126] Generate route map

[0127] The server generates an optimized route map and displays it on the autonomous vehicle's display, along with visual indications of points of special interest and surrounding information.

[0128] Examples

[0129] Example prompts to be input to the generative AI model

[0130] Starting point: 35.6895, 139.6917

[0131] Destination point: 35.6586, 139.7454

[0132] Waypoint: 35.6733, 139.7100

[0133] Particular caution is required at: sharp curves, steep gradients, intersections

[0134] Based on this prompt, the server retrieves topographical maps and road information and performs analysis using an AI model. Based on the analysis results, it calculates the optimal driving route, generates a route map and displays it on the display of the autonomous vehicle, allowing the user to check a safe and efficient driving route.

[0135] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0136] Step 1:

[0137] The user inputs the starting point, destination point, and intermediate points into the on-board computer of the autonomous vehicle, and the system retrieves these points. The input includes latitude and longitude coordinates. The output is the coordinates that are passed to the next step.

[0138] Step 2:

[0139] The server uses the OpenStreetMap API to get the topographical map and road information for the specified route. As input, the coordinate information obtained in step 1 is used. The server sends an API request and receives data including the topographical map and road information. As output, the topographical map and road information are passed on to the next step.

[0140] Step 3:

[0141] The server uses TensorFlow to analyze the retrieved topographical map and road information and generate readings and writings of the topographical features. As input, the topographical map and road information retrieved in step 2 are used. Using an AI model, the server analyzes the topographical features and identifies points that require special attention (sharp curves, steep gradients, intersections, etc.). As output, the readings and writings of the topographical features are passed on to the next step.

[0142] Step 4:

[0143] The server calculates the optimal driving route based on the reading and writing of the terrain features generated by the AI ​​model. As input, the reading and writing of the terrain features generated in step 3 is used. The server also takes into account surrounding information (gas stations, rest areas, etc.) to calculate the optimal driving route. As output, the optimized driving route is passed to the next step.

[0144] Step 5:

[0145] The server generates an optimized route map and displays it on the autonomous vehicle's display. As input, the optimal driving route calculated in step 4 is used. The server generates the route map and also visually displays points of special interest and surrounding information. As output, the route map is displayed on the display for the user to review.

[0146] Through this series of processes, the user can check a safe and efficient driving route.

[0147] Example 2

[0148] Next, a second embodiment of the second embodiment will be described. 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."

[0149] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on a topographical map, and the generated mountain climbing concept map was visually difficult to understand. Furthermore, it was difficult to automatically create a detailed mountain climbing concept map that included surrounding information (such as accommodations) other than the mountain climbing route.

[0150] 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.

[0151] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, a means for transmitting the mountain climbing route information as digital data, a means for using a generative AI model for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and writings of the topographical features generated by the generative AI model, and a means for displaying the mountain climbing conceptual map in a visually easy-to-understand format. This allows the user to intuitively input mountain climbing route information, and makes it possible to automatically create a visually easy-to-understand mountain climbing conceptual map. It is also possible to provide a detailed mountain climbing conceptual map that includes surrounding information other than the mountain climbing route.

[0152] A "topographic map" is a map that visually represents detailed information about a terrain.

[0153] "Mountain climbing route information" is information about the route of a mountain climbing planned by a mountain climber.

[0154] The "means for inputting" is a device or software that provides an interface for a user to draw a climbing route on a topographical map.

[0155] The "means for transmitting as digital data" refers to a communication means for transmitting the climbing route information input by the user to the server in digital form.

[0156] A "generative AI model" is an artificial intelligence model that analyzes and generates how to read and write topographical features.

[0157] A "climbing concept map" is a visual representation of a climbing route and the topographical features of its surroundings.

[0158] "Means for automatic creation" refers to a device or software for automatically generating a mountain climbing concept map using a generative AI model.

[0159] The "means for displaying in a visually easy-to-understand format" refers to a device or software for displaying the generated mountain climbing concept map in a format that is easy for the user to understand.

[0160] "Local information" refers to information about accommodation and other important points related to the climbing route.

[0161] This invention is a system that allows climbers to intuitively input climbing route information based on a topographical map, analyzes topographical features using a generative AI model, and automatically creates a visually easy-to-understand climbing concept map. This system works in cooperation with the user, the terminal, and the server.

[0162] First, the user draws a climbing route on the topographical map displayed on the terminal screen using a mouse or a touch pen. The user can intuitively input route information by drawing a line on the topographical map or clicking points. For example, the user specifies a climbing route by dragging the mouse from the starting point to the goal point to draw a line.

[0163] Next, the terminal transmits the climbing route information drawn by the user to the server as digital data. This data includes the route coordinate information and drawing format (line color, thickness, etc.). For example, it includes the coordinates of the start and end points of the line, and information on the line color and thickness.

[0164] The server receives the climbing route information sent from the terminal and uses a generative AI model to analyze how to read and write the topographical features. The server automatically generates a climbing concept map based on the analysis results. The generated concept map displays the climbing route in a visually easy-to-understand format. Specifically, the topographical features, climbing route, and surrounding information are expressed using colors, line thickness, symbols, etc. For example, the climbing route is displayed with a thick red line, and the surrounding topographical features are expressed with blue dotted lines and green symbols.

[0165] The server then transmits the generated mountain climbing concept map to the terminal. The terminal receives this data and displays it to the user. The user can check the mountain climbing concept map displayed on the terminal screen and confirm the mountain climbing route and the characteristics of the terrain displayed in a visually easy-to-understand format. This allows the user to obtain information that is useful when making mountain climbing plans.

[0166] As a concrete example, consider the case where a user draws a mountain climbing route with a red line on a topographical map. When the user drags the mouse to draw a line from the starting point to the goal, the device sends that information to the server as digital data. The server uses a generative AI model to analyze the characteristics of the terrain, and generates a mountain climbing concept map that displays the climbing route with a thick red line and the surrounding topographical features with blue dotted lines and green symbols. The server sends this concept map to the device, where the user can view it on the device screen.

[0167] The following are examples of prompt sentences:

[0168] "Please draw your climbing route on the topographical map in red. The system will create a climbing concept map based on that information and display your climbing route in thick red."

[0169] "Click multiple points on the topographical map to specify a climbing route. The system will create a climbing concept map based on that information and display the climbing route with a yellow dashed line."

[0170] In this way, the user can intuitively input mountain climbing route information and obtain a visually easy-to-understand mountain climbing concept map, which improves the convenience when making mountain climbing plans.

[0171] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0172] Step 1:

[0173] The user inputs a climbing route.

[0174] The user draws a climbing route on the topographical map displayed on the terminal screen using a mouse or a touch pen. Specifically, the user draws a line by dragging the mouse from the starting point to the goal point. This operation inputs the coordinate information of the climbing route and the drawing format (such as the color and thickness of the line).

[0175] Step 2:

[0176] The terminal transmits the input data to the server.

[0177] The terminal sends the climbing route information drawn by the user to the server as digital data. The input includes the coordinates of the start and end points of the line, and information on the color and thickness of the line. The terminal puts this data into packets and sends them to the server.

[0178] Step 3:

[0179] The server receives and analyzes the data.

[0180] The server receives the climbing route information sent from the device. The input includes the climbing route's coordinate information and drawing format. The server uses a generative AI model to analyze how to read and write the terrain features. Specifically, it analyzes the elevation and slope of the terrain through which the route passes, and extracts detailed information about the climbing route.

[0181] Step 4:

[0182] The server generates a conceptual map of the mountain climb.

[0183] The server automatically generates a mountain climbing concept map based on the analysis results. The input includes the analyzed terrain feature information. The server uses the generative AI model to display the mountain climbing route in a visually easy-to-understand format. Specifically, the mountain climbing route is displayed as a thick red line, and the surrounding terrain features are represented by blue dotted lines and green symbols.

[0184] Step 5:

[0185] The server transmits the generated mountain climbing concept map to the terminal.

[0186] The server transmits the generated mountain climbing concept map to the terminal. The input includes the data of the generated mountain climbing concept map. The server assembles this data into packets and transmits them to the terminal.

[0187] Step 6:

[0188] The user checks the mountain climbing concept map.

[0189] The user checks the mountain climbing concept map displayed on the screen of the terminal. The input includes the data of the mountain climbing concept map sent from the server. The user checks the mountain climbing route and the topographical features displayed in a visually easy-to-understand format and makes a mountain climbing plan. Specifically, the user makes a mountain climbing plan by looking at the mountain climbing route and the surrounding topographical features.

[0190] (Application example 2)

[0191] Next, a description will be given of Application Example 2 of Form 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."

[0192] In conventional climbing route information input systems, it was difficult for users to intuitively input climbing route information based on a topographical map, and the generated climbing concept map was visually difficult to understand. Furthermore, it was difficult to automatically create a detailed climbing concept map that included surrounding information other than the climbing route. This made it difficult for climbers to plan climbing routes safely and efficiently.

[0193] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0194] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an AI means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the AI ​​means, a means for inputting route information by drawing a route on a map, a means for analyzing the route information and converting it into a visually easy-to-understand format, and a means for displaying the converted route information. This makes it possible for a user to intuitively input mountain climbing route information and automatically generate a visually easy-to-understand mountain climbing concept map.

[0195] A "topographic map" is a map that shows detailed information about the terrain and is used to plan climbing routes and understand the characteristics of the terrain.

[0196] "Mountain climbing route information" refers to information about a mountain climbing route planned by a climber, including the route and points of the route depicted on a topographical map.

[0197] "AI means" means means for analyzing data and automatically performing specific tasks using artificial intelligence technology.

[0198] A "mountain climbing concept map" is a diagram that visually represents a mountain climbing route and surrounding information in an easy-to-understand manner, making it easier for climbers to understand the route.

[0199] The "means for inputting route information" refers to a means for a user to input climbing route information into the system by drawing the route directly on a map.

[0200] A "visually easy-to-understand format" is a format that expresses information using colors, line thicknesses, symbols, etc., making it easy for users to understand intuitively.

[0201] The "means for analyzing route information" refers to a means for analyzing input route information and converting it into a visually easy-to-understand format.

[0202] The "means for displaying route information" refers to a means for displaying the analyzed route information to the user in a visually easy-to-understand format.

[0203] A system for implementing this invention includes means for inputting mountain climbing route information based on a topographical map, AI means for generating how to read and write topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the how to read and write the topographical features generated by the AI ​​means, means for inputting route information by drawing a route on a map, means for analyzing the route information and converting it into a visually easy-to-understand format, and means for displaying the converted route information.

[0204] Program processing explanation

[0205] The server reads the topographical map data, and the user inputs the climbing route information by drawing the route on the map. Specifically, the user draws the route on the map using a touch screen or mouse input on a device such as a smartphone or a head-mounted display. This route information is sent to the server, and the AI ​​means analyzes it.

[0206] The AI ​​tool analyzes the input route information and generates readings and writings of topographical features. It uses Python and its libraries (matplotlib, numpy, sklearn, etc.). The analyzed data is converted into a visually easy-to-understand format. For example, the route is represented using colors, line thickness, symbols, etc.

[0207] The converted route information is sent from the server to the user's device and displayed in a visually easy-to-understand format, making it easier for users to intuitively understand the climbing route information.

[0208] Examples

[0209] For example, when a user uses a smartphone to draw a mountain climbing route on a map, the user draws the route on the map with his / her finger. The server receives this information, and the AI ​​means analyzes it to generate a visually easy-to-understand mountain climbing concept diagram. This mountain climbing concept diagram is expressed using colors, line thickness, symbols, etc., and is displayed on the smartphone screen.

[0210] Examples of prompt statements

[0211] Below are examples of prompts to be input to the generative AI model.

[0212] Please create an application where the user draws a route on a map, and the route is analyzed by AI and displayed in a visually easy-to-understand format. Please provide a Python program that includes the following steps: loading map data, inputting route information, analyzing the route by AI, and generating a route map.

[0213] It is expected that by using this prompt sentence, the generative AI model will generate an appropriate program.

[0214] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0215] Step 1:

[0216] The user loads map data using a smartphone or head-mounted display.

[0217] Input: Map data file (e.g. topographical map image file)

[0218] Output: Map data is displayed.

[0219] Specific operation: The user launches the application on the device, selects and loads a map data file, and the map data is displayed on the device screen.

[0220] Step 2:

[0221] The user draws a route on a map.

[0222] Input: Route drawing information from the user's touch screen or mouse input

[0223] Output: Rendered route information

[0224] How it works: A user draws a climbing route on a map using a finger or a stylus. The route information is stored on the device and sent to the server.

[0225] Step 3:

[0226] The server analyzes the received route information.

[0227] Input:Drawn route information

[0228] Output: Parsed route data

[0229] Specific operation: The server analyzes the received route information and generates reading and writing instructions for terrain features. It uses Python libraries (numpy, sklearn, etc.) to analyze the data and extract route features.

[0230] Step 4:

[0231] The server converts the parsed route data into a visually understandable format.

[0232] Input: Parsed route data

[0233] Output: Route data in a visually friendly format

[0234] Specific operation: The server converts the analyzed route data into a visually easy-to-understand format using colors, line thickness, symbols, etc. It uses matplotlib to draw the route and arrange it into a visually easy-to-understand format.

[0235] Step 5:

[0236] The server sends the converted route data to the user's device.

[0237] Input: Route data in a visually friendly format

[0238] Output: The route map as it appears on the user's device.

[0239] Specific operation: The server sends the converted route data to the user's device, which then displays the received data and provides the user with a visually easy-to-understand route map.

[0240] Step 6:

[0241] Users can view easy-to-understand route maps.

[0242] Input: A route map in a visually friendly format

[0243] Output: User understanding and confirmation

[0244] Specific operation: The user checks the route map displayed on the device screen and plans a mountain climbing route. Visual information using colors, line thickness, symbols, etc. allows the user to intuitively understand the route.

[0245] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0246] "Example 1"

[0247] As one embodiment of the present invention, a system is provided that combines an emotion engine that recognizes the emotions of a user. This system includes an AI means that receives mountain climbing route information based on a topographical map and generates how to read and write topographical features based on the mountain climbing route information, and a means that automatically creates a mountain climbing concept map using the how to read and write the topographical features generated by the AI ​​means. Furthermore, an emotion engine that recognizes the emotions of a user is also included. This emotion engine recognizes the emotional state of a user, for example, from the user's facial expression, tone of voice, text input, etc. Then, the reading and writing of the topographical features and the display method of the mountain climbing concept map are adjusted according to the emotional state. For example, if it is recognized that the user is nervous, more detailed topographical information is provided. Also, if it is recognized that the user is relaxed, only the minimum necessary information is provided, making it possible to provide optimal information according to the user's emotional state.

[0248] "Example 2"

[0249] As another embodiment of the present invention, a system is provided in which an emotion engine adjusts the display method of a mountain climbing concept map according to the emotional state of a user. As in the above-mentioned embodiment, this system includes an AI means for inputting mountain climbing route information based on a topographical map and generating a reading and writing method of topographical features based on the mountain climbing route information, and a means for automatically creating a mountain climbing concept map using the reading and writing method of the topographical features generated by the AI ​​means. Furthermore, an emotion engine for recognizing the emotion of a user is also included. This emotion engine adjusts the display method of the mountain climbing concept map according to the emotional state of the user. For example, if it is recognized that the user is feeling anxious, more detailed topographical information and safety information are displayed with emphasis. Also, if it is recognized that the user is excited, an optimal display method according to the emotional state of the user is provided, such as increasing the options of mountain climbing routes.

[0250] The process flow of each embodiment will be described below.

[0251] "Example 1"

[0252] Step 1: Receive climbing route information based on a topographical map from the user as input.

[0253] Step 2: Using AI means, generate readings and writings of terrain features based on the input climbing route information.

[0254] Step 3: Automatically create a mountaineering concept map using the generated reading and writing methods for the terrain features.

[0255] Step 4: Use the emotion engine to recognize the user's emotional state from their facial expressions, tone of voice, text input, etc.

[0256] Step 5: Adjust the way terrain features are read and written and the way mountain climbing concept maps are displayed according to the recognized emotional state of the user.

[0257] "Example 2"

[0258] Step 1: Receive climbing route information based on a topographical map from the user as input.

[0259] Step 2: Using AI means, generate readings and writings of terrain features based on the input climbing route information.

[0260] Step 3: Automatically create a mountaineering concept map using the generated reading and writing methods for the terrain features.

[0261] Step 4: Recognize the user's emotional state using the emotion engine.

[0262] Step 5: Adjust the way the mountain climbing concept diagram is displayed depending on the recognized emotional state of the user.

[0263] Example 1

[0264] Next, a description will be given of Example 1 of the embodiment 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".

[0265] In conventional mountain climbing support systems, the input of mountain climbing route information and the analysis of terrain characteristics are often done manually, which is inefficient. In addition, since information is not provided according to the user's emotional state, it is difficult to provide information optimal for the user's situation. This leads to the issue that safety and comfort during mountain climbing are not sufficiently ensured.

[0266] 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.

[0267] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the artificial intelligence means, an emotion recognition means for recognizing the emotion of the user, and a means for adjusting the information provided in accordance with the emotional state of the user recognized by the emotion recognition means. This makes it possible to automatically create a mountain climbing concept map based on the user's input, and further to provide optimal information in accordance with the emotional state of the user.

[0268] A "topographic map" is a map that shows detailed information about the terrain and is used to plan and analyze climbing routes.

[0269] "Mountain climbing route information" is information about the route planned by the climber, such as the starting point and end point of the climb, intermediate points, and points requiring special caution.

[0270] "Artificial intelligence means" means technology that includes algorithms or models to analyse input data and perform specific tasks automatically.

[0271] "How to read and write topographical features" refers to a method of analyzing information obtained from topographical maps and expressing it in a form that is easy for climbers to understand.

[0272] A "climbing concept map" is a diagram that visually shows a climbing route and the surrounding information, making it easier for climbers to understand the route.

[0273] "Emotion recognition means" is a technology that analyzes a user's emotional state from facial expressions, tone of voice, text input, etc.

[0274] "Means for adjusting information provision" refers to technology that changes the content and format of the information provided depending on the user's emotional state.

[0275] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0276] The present invention is a system in which a climber inputs climbing route information based on a topographical map, and an artificial intelligence generates how to read and write the topographical features based on that information, and finally creates a climbing concept map. In addition, by combining an emotion recognition means that recognizes the user's emotions, information is provided according to the user's emotional state.

[0277] System Configuration

[0278] 1. Enter climbing route information

[0279] The user inputs mountain climbing route information, specifically, the start and end points of the mountain climbing, intermediate points, points requiring special attention, etc.

[0280] Hardware used: PC, smartphone, tablet, etc.

[0281] Software used: Web browser, dedicated application

[0282] 2. Generating readings and writings of topographical features

[0283] The server receives the input climbing route information and generates readings and writings of topographical features using an AI model that analyzes detailed information on topographical maps.

[0284] Hardware used: Server (high performance CPU, GPU)

[0285] Software used: Artificial intelligence models (e.g. TensorFlow, PyTorch)

[0286] 3. Creating a mountain climbing concept map

[0287] The server automatically creates a mountain climbing concept map using the reading and writing of the terrain features generated by the artificial intelligence. This mountain climbing concept map includes surrounding information (mountain huts, etc.) other than the climbing route.

[0288] Hardware used: Server

[0289] Software used: Mapping software (e.g. QGIS)

[0290] 4. Emotion recognition using emotion recognition means

[0291] The terminal recognizes the user's emotional state from the user's facial expressions, tone of voice, text input, etc., which are then analyzed by the emotion recognition means.

[0292] Hardware used: PC, smartphone, tablet (camera, microphone)

[0293] Software used: Emotion recognition software (e.g. Microsoft® Azure® Emotion API)

[0294] 5. Coordination of information provision

[0295] The server adjusts how to read and write the terrain features and how to display the mountain climbing concept map according to the user's emotional state obtained from the emotion recognition means. For example, if the user is nervous, detailed terrain information is provided, and if the user is relaxed, only the minimum necessary information is provided.

[0296] Hardware used: Server

[0297] Software used: Customized information providing algorithms

[0298] Examples

[0299] The user opens a dedicated application on their smartphone and inputs climbing route information, for example, "Route from the fifth station to the summit of Mt. Fuji, stopping at mountain huts along the way."

[0300] The server receives this information and uses artificial intelligence models to generate readings and writings of the topographical features.

[0301] The server creates a mountain climbing concept map based on the generated information and displays it on the smartphone.

[0302] The terminal captures the user's facial expression with a camera, and the emotion recognition means recognizes that the user is nervous.

[0303] The server provides a conceptual map of a mountain climb including detailed topographical information.

[0304] Examples of prompt statements

[0305] "Please enter the route from the fifth station to the summit of Mt. Fuji. Please also enter any mountain huts you may need to stop at along the way and any points requiring caution."

[0306] In this way, the system automatically creates a mountain climbing concept map based on the user's input, and can provide optimal information according to the user's emotional state.

[0307] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0308] Step 1:

[0309] The user inputs the climbing route information. Specifically, the user opens a dedicated application on his / her smartphone and enters "Route from the fifth station of Mt. Fuji to the summit, stopping at mountain huts on the way" into the input form.

[0310] Input: Climbing route information such as the start and end points of the climb, intermediate points, and points requiring special attention

[0311] Output: The entered climbing route information is sent to the server.

[0312] Step 2:

[0313] The server receives the climbing route information sent by the user, then uses an artificial intelligence model to generate readings and writings of the terrain features.

[0314] Input: Climbing route information sent by the user

[0315] Data processing: The server analyzes the received data and uses artificial intelligence models (e.g. TensorFlow) to analyze detailed information on the topographical maps.

[0316] Output: How to read and write the topographical features is generated

[0317] Specific operation: The server analyzes the received data, analyzes the detailed information of the topographical map using TensorFlow, and generates how to read and write the topographical features.

[0318] Step 3:

[0319] The server automatically creates a mountain climbing concept map based on how to read and write the terrain features generated by the artificial intelligence. This mountain climbing concept map includes surrounding information (mountain huts, etc.) other than the climbing route.

[0320] Input: How to read and write terrain features generated by artificial intelligence

[0321] Data processing: The server uses QGIS to create a conceptual map of the climbing route and surrounding information.

[0322] Output: A mountain climbing concept map is generated and sent to the user's smartphone.

[0323] Specific operation: The server creates a mountain climbing concept map using QGIS and sends it to the user's smartphone.

[0324] Step 4:

[0325] The terminal recognizes the user's emotional state from the user's facial expressions, tone of voice, text input, etc., which are then analyzed by the emotion recognition means.

[0326] Input: User facial expressions, tone of voice, text input, etc.

[0327] Data processing: The device captures data using the camera and microphone and analyzes it using emotion recognition software (e.g. Microsoft Azure Emotion API).

[0328] Output: The user's emotional state is recognized.

[0329] How it works: The smartphone camera captures the user's facial expressions and analyzes their emotional state using the Microsoft Azure Emotion API.

[0330] Step 5:

[0331] The server adjusts how to read and write the terrain features and how to display the mountain climbing concept map according to the user's emotional state obtained from the emotion recognition means. For example, if the user is nervous, detailed terrain information is provided, and if the user is relaxed, only the minimum necessary information is provided.

[0332] Input: The user's emotional state obtained from an emotion recognition means

[0333] Data processing: The server receives the analysis results of the emotion recognition method and adjusts the display method using an information provision algorithm.

[0334] Output: The adjusted information is displayed on the user's smartphone.

[0335] Specific operation: The server receives the analysis results of the emotion recognition means, and if it determines that the user is nervous, it regenerates a mountain climbing concept map including detailed terrain information and sends it to the smartphone.

[0336] (Application example 1)

[0337] Next, a description will be given of Application Example 1 of Form 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."

[0338] Conventional mountain climbing route guidance systems provide uniform information without considering the user's emotional state, which means that they cannot provide appropriate information when the user is tense or relaxed. In addition, they lack the functionality to automatically generate how to read and write detailed topographical features based on topographical maps, making it difficult to provide the information users need quickly and accurately.

[0339] 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.

[0340] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an AI means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the AI ​​means, a means including an emotion engine for recognizing the user's emotions, and a means for adjusting the information provided according to the user's emotional state recognized by the emotion engine. This makes it possible to provide optimal information according to the user's emotional state.

[0341] A "topographic map" is a map that shows detailed information about a terrain, visually representing climbing routes and terrain features.

[0342] "Mountain climbing route information" includes information on the start point, end point, waypoints, points requiring special caution, and the like of the route the climber plans to take.

[0343] "AI Means" means a means for performing a specific task using artificial intelligence, and in this case refers to the ability to generate readings and / or writings of topographical features.

[0344] "Reading and writing topographic features" refers to the method of interpreting detailed information about a terrain based on a topographic map and expressing it in visual or textual form.

[0345] A "climbing concept map" is a visual representation of a climbing route and its surrounding information, intended to make it easier for climbers to understand the route.

[0346] An "emotion engine" is a system for recognizing a user's emotional state from their facial expressions, tone of voice, text input, etc.

[0347] The "means for adjusting the information provided" refers to a means for changing the level of detail and content of the information provided in accordance with the user's emotional state.

[0348] A system for implementing this invention includes means for inputting mountain climbing route information based on a topographical map, AI means for generating how to read and write topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the how to read and write the topographical features generated by the AI ​​means, means including an emotion engine for recognizing a user's emotions, and means for adjusting the provision of information in accordance with the user's emotional state recognized by the emotion engine.

[0349] Program processing explanation

[0350] Hardware and software used

[0351] Hardware: Smartphone (camera, microphone)

[0352] Software: Python, OpenCV, EmotionRecognizer library, RoutePlanner library, MapGenerator library

[0353] Processing flow

[0354] 1. User input: The user inputs the starting point, destination point, and intermediate points. This provides the climbing route information to the system.

[0355] 2. Route Planning: The server uses the RoutePlanner library to generate readings and writings of terrain features based on the input route information.

[0356] 3. Map generation: The server uses the MapGenerator library to create a driving concept map, which includes surrounding information (e.g. mountain huts) in addition to the climbing route.

[0357] 4. Emotion recognition: The device uses the EmotionRecognizer library to recognize the user's emotions based on data obtained from the camera and microphone.

[0358] 5. Adjustment of information provision: The server adjusts the level of detail of the information provided depending on the recognized emotional state. For example, if the user is nervous, detailed topographical information is provided, but if the user is relaxed, only the minimum necessary information is provided.

[0359] 6. Display: The device displays the adjusted information on the smartphone screen.

[0360] Examples

[0361] User input: Starting point "Tokyo Station", destination point "Mt. Fuji", intermediate point "Yokohama Station"

[0362] Emotion recognition: If the user is perceived as nervous, detailed terrain information (sharp turns, slope, etc.) is provided.

[0363] Display: Along with a detailed driving concept map, it also displays information on nearby gas stations and rest areas.

[0364] Examples of prompt statements

[0365] If a user inputs the starting point "Tokyo Station", the destination "Mt. Fuji", and the waypoint "Yokohama Station", and the emotion recognition engine recognizes the user's emotion as "nervous", please generate a program that provides detailed topographical and surrounding information.

[0366] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0367] Step 1:

[0368] The user inputs the starting point, destination, and intermediate points. Through the smartphone application, the user inputs the starting point "Tokyo Station," the destination point "Mt. Fuji," and the intermediate point "Yokohama Station." This provides the climbing route information to the system. The input data is sent to the server and proceeds to the next processing step.

[0369] Step 2:

[0370] The server uses the RoutePlanner library to generate readings and writings of terrain features based on the input route information. The server analyzes the received information of the starting point, destination point, and intermediate points, and retrieves the corresponding terrain information from the topographical map database. Based on the retrieved terrain information, the AI ​​model generates readings and writings of terrain features. The generated data is used in the next step.

[0371] Step 3:

[0372] The server creates a driving concept map using the MapGenerator library. The server generates a driving concept map including the climbing route and its surrounding information (e.g. mountain huts) based on the reading and writing of the topographical features generated in step 2. The generated driving concept map is used in the next step.

[0373] Step 4:

[0374] The device uses the EmotionRecognizer library to recognize the user's emotions based on data acquired from the camera and microphone. The device analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state. The determined emotional state is used in the next step.

[0375] Step 5:

[0376] The server adjusts the level of detail of the information to be provided according to the recognized emotional state. The server determines the level of detail of the information to be provided based on the emotional state determined in step 4. For example, if the user is nervous, detailed topographical information is provided, and if the user is relaxed, only the minimum necessary information is provided. The adjusted information is used in the next step.

[0377] Step 6:

[0378] The terminal displays the adjusted information on the smartphone screen. The terminal receives the adjusted driving concept map and surrounding information sent from the server and displays them on the smartphone screen. The user can check the mountain climbing route safely and efficiently based on the displayed information.

[0379] Example 2

[0380] Next, a second embodiment of the second embodiment will be described. 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."

[0381] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on a topographical map, and the generated mountain climbing concept map was not adjusted according to the user's emotional state, making it difficult to provide information that is easy for users to understand. Furthermore, it was also insufficient to create a detailed mountain climbing concept map that included surrounding information other than the mountain climbing route (such as evacuation sites).

[0382] 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.

[0383] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and an emotion recognition means for recognizing the emotional state of the user and adjusting the display method of the mountain climbing conceptual map according to the emotional state. This allows the user to intuitively input mountain climbing route information, and the generated mountain climbing conceptual map is adjusted according to the emotional state of the user, making it possible to provide information that is easy for the user to understand. It also makes it possible to create a detailed mountain climbing conceptual map that includes surrounding information other than the mountain climbing route.

[0384] A "topographic map" is a map that shows the terrain and the locations of landmarks, and is used for planning mountain climbing routes and navigation.

[0385] "Mountain climbing route information" refers to information about the mountain climbing route planned by a climber, including the route depicted on a topographical map and its details.

[0386] "Artificial intelligence means" refers to technology that uses machine learning or data analysis to automatically perform certain tasks, and is used in the present invention to generate readings and writings of topographical features.

[0387] "Topographical characteristics" refers to the characteristics of the terrain and features shown on a topographical map, and are used to evaluate the difficulty of climbing routes and dangerous areas.

[0388] A "climbing concept map" is a diagram that visually shows climbing routes and surrounding information in an easy-to-understand manner, and is created to make it easier for climbers to understand the route.

[0389] The "emotion recognition means" is a technology for analyzing and recognizing the user's emotional state, and in the present invention is used to adjust the display method of the mountain climbing concept map according to the user's emotional state.

[0390] "Area information" refers to information other than the climbing route, including information important to climbers, such as evacuation sites and water sources.

[0391] This invention is a system in which a climber intuitively inputs climbing route information based on a topographical map, and the generated climbing concept map is adjusted according to the user's emotional state. A specific embodiment of this system will be described below.

[0392] First, the user displays a topographical map using a terminal (PC or tablet). The user then draws a climbing route on the topographical map using a mouse or touch screen. For example, the user draws a climbing route by drawing a red line on the topographical map. This information is sent from the terminal to the server as digital data.

[0393] Next, the server analyzes the received climbing route information. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate readings and writings for terrain features. Specifically, the server analyzes the elevation data and terrain relief of the climbing route to evaluate the difficulty and dangerous areas of the climbing route.

[0394] The server then creates a mountain climbing concept map based on how to read and write the generated topographical features. The mountain climbing concept map is displayed in a visually easy-to-understand format using colors, line thickness, symbols, etc. For example, the mountain climbing route is displayed with a thick red line, and dangerous areas are indicated with yellow triangles. Nearby evacuation sites and water sources are also displayed with blue icons.

[0395] Furthermore, the server recognizes the user's emotional state using an emotion recognition means (e.g., IBM Watson (registered trademark) or Microsoft Azure Cognitive Services). If the user feels anxious, the server emphasizes and displays detailed terrain information and safety information. If the user feels excited, the server provides an optimal display method according to the user's emotional state, such as increasing the options for mountain climbing routes.

[0396] As a concrete example, the following prompt sentence is input into the generative AI model.

[0397] Example prompt:

[0398] Based on the climbing route information drawn by the user on the topographical map, use an AI model to generate reading and writing of the terrain features, and create a visually easy-to-understand climbing concept map. Also, use an emotion engine to recognize the user's emotional state and adjust the display method. For example, if the user is feeling anxious, highlight the detailed terrain information, and if the user is excited, increase the options of climbing routes.

[0399] In this way, a system is realized in which the server, terminal, and user work together to input mountain climbing route information, create a mountain climbing concept map, and adjust the display according to emotions.

[0400] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0401] Step 1:

[0402] A user uses a terminal to display a topographical map. The user draws a climbing route on the topographical map using a mouse or a touch screen. The climbing route information drawn by the user is input. The terminal transmits this information to a server as digital data. In concrete terms, the user draws a climbing route by drawing a red line on the topographical map.

[0403] Step 2:

[0404] The server receives climbing route information sent from the terminal. As input, there is digitized climbing route information. The server analyzes this information and generates how to read and write the topographical features using a generative AI model (e.g., TensorFlow or PyTorch). Specifically, the server analyzes the elevation data and topographical relief of the climbing route, and evaluates the difficulty and dangerous areas of the climbing route. As output, how to read and write the topographical features is generated.

[0405] Step 3:

[0406] The server creates a mountain climbing concept map based on how to read and write the generated topographical features. The input is how to read and write the topographical features. The server displays the mountain climbing concept map in a visually easy-to-understand format using colors, line thickness, symbols, etc. In concrete terms, the server displays the mountain climbing route with a thick red line and indicates dangerous areas with yellow triangles. It also displays nearby evacuation sites and water sources with blue icons. The output is a mountain climbing concept map.

[0407] Step 4:

[0408] The server recognizes the user's emotional state using the emotion recognition means. As an input, there is data on the user's emotional state. The server adjusts the display method of the mountain climbing concept map according to the user's emotional state. As a specific operation, if the user feels anxious, the server displays detailed topographical information and safety information with emphasis. If the user is excited, the server increases the options for mountain climbing routes. As an output, an optimal display method according to the user's emotional state is provided.

[0409] (Application example 2)

[0410] Next, a description will be given of Application Example 2 of Form 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."

[0411] Conventional mountain climbing navigation systems have the problem that it is difficult for climbers to intuitively input climbing route information based on topographical maps, and information is not provided according to the user's emotional state, so the safety and comfort of climbers is not sufficiently ensured. In addition, there is also the problem that automatic driving vehicles do not provide appropriate navigation to safely transport climbers to their destinations.

[0412] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0413] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an AI means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the AI ​​means, an emotion engine for recognizing the user's emotional state, a means for adjusting the display method of the mountain climbing concept map according to the emotional state recognized by the emotion engine, and a means for being installed in an autonomous vehicle. This allows mountain climbers to intuitively input mountain climbing route information, and makes it possible to provide optimal navigation information according to the user's emotional state.

[0414] A "topographic map" is a map that visually represents detailed information about a terrain.

[0415] "Mountain climbing route information" is information about the route that a climber plans to take when climbing a mountain.

[0416] "AI Means" means technical means for performing certain tasks using artificial intelligence.

[0417] "Topographic features" refers to topographical characteristics such as mountains, valleys, and rivers on a topographical map.

[0418] A "mountain climbing concept map" is a diagram that visually represents mountain climbing routes and surrounding information.

[0419] An "emotion engine" is a technology for recognizing a user's emotional state and adjusting the system's behavior based on that.

[0420] An "autonomous vehicle" is a vehicle that can drive autonomously using artificial intelligence and sensor technology.

[0421] A "display method" is the means or format by which information is visually presented to a user.

[0422] The following system configuration will be described as an embodiment of the present invention.

[0423] System Configuration

[0424] Hardware

[0425] Autonomous vehicle: A vehicle that can drive autonomously using artificial intelligence and sensor technology.

[0426] Cameras and sensors: devices to recognise the user's emotional state.

[0427] software

[0428] EmotionEngine: Technology for recognizing a user's emotional state and adjusting system behavior based on it.

[0429] AIGeography: Artificial intelligence techniques for generating terrain features and creating mountaineering concept maps.

[0430] Program processing explanation

[0431] Input of climbing route information based on topographical maps

[0432] The server provides a means for inputting climbing route information based on a topographical map. A user can input climbing route information by drawing the route directly on the topographical map. This information is sent to the server and used for the next process.

[0433] Generate terrain features

[0434] The server uses AIGeography to generate readings and writings of terrain features based on the input climbing route information. AIGeography reads detailed information of the topographical map and generates terrain features. The generated terrain features are used to create a climbing concept map.

[0435] Creating a mountain climbing concept map

[0436] The server automatically creates a mountaineering concept map using the reading and writing of the terrain features generated by AIGeography. This mountaineering concept map is displayed in a visually easy-to-understand format, including the climbing route and surrounding information (mountain huts, etc.).

[0437] Adjusting display method using emotion engine

[0438] The server recognizes the user's emotional state using the EmotionEngine. The EmotionEngine analyzes data obtained from cameras and sensors to determine the user's emotional state. For example, if the user feels anxious, the server will highlight safety information on the mountain climbing concept map. In addition, if the user feels excited, the server will provide the optimal display method according to the user's emotional state, such as increasing the number of mountain climbing route options.

[0439] Examples

[0440] For example, consider a climber getting into an autonomous vehicle and inputting a route to a destination. The user draws the route on a topographical map and sends it to the server. The server uses AI Geography to generate topographical features and create a mountain climbing concept map. Next, Emotion Engine recognizes the user's emotional state and adjusts the display method. If the user feels anxious, safety information is emphasized, and if the user is excited, the options for mountain climbing routes are increased.

[0441] Examples of prompt statements

[0442] "Design a mountain climbing navigation system that highlights safety information when the user feels anxious. Input mountain climbing route information based on a topographical map, and create a mountain climbing concept map using AI-generated topographical features. Use an emotion engine to adjust the navigation information according to the user's emotional state."

[0443] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0444] Step 1:

[0445] The user draws a climbing route on a topographical map.

[0446] Input: Topographical map, user-drawn climbing route information

[0447] Output: Climbing route information

[0448] Specific operation: A user draws a climbing route on a topographical map using a device such as a smartphone or tablet. This information is sent from the device to the server.

[0449] Step 2:

[0450] The server receives the climbing route information and generates topographical features using AIGenography.

[0451] Input: Climbing route information

[0452] Output: How to read and write topographical features

[0453] How it works: The server inputs the received climbing route information into AIGeography, and analyzes the detailed information of the topographical map to generate topographical features, including topographical characteristics such as mountains, valleys, and rivers.

[0454] Step 3:

[0455] The server creates a mountain climbing concept map using the generated topographical features.

[0456] Input: How to read and write topographical features

[0457] Output: Mountain climbing concept diagram

[0458] Specific operation: The server automatically creates a mountain climbing concept map including climbing routes and surrounding information (mountain huts, etc.) based on the topographical features generated by AIGenography.

[0459] Step 4:

[0460] The server uses the EmotionEngine to recognize the user's emotional state.

[0461] Input: User emotion data obtained from cameras and sensors

[0462] Output: The user's emotional state.

[0463] Specific operation: The server inputs data obtained from the camera and sensors into the EmotionEngine and analyzes the user's emotional state. For example, it determines whether the user is feeling anxious or excited based on data such as facial expressions and heart rate.

[0464] Step 5:

[0465] The server adjusts the display method of the mountain climbing concept diagram according to the user's emotional state.

[0466] Input: User's emotional state, mountain climbing concept

[0467] Output: Coordinated climbing concept map

[0468] Specific operation: The server adjusts the way the mountain climbing concept map is displayed based on the user's emotional state recognized by the Emotion Engine. For example, if the user feels anxious, the server emphasizes safety information and displays more options for mountain climbing routes if the user feels excited.

[0469] Step 6:

[0470] The server transmits the adjusted mountain climbing concept map to the terminal and displays it to the user.

[0471] Input: Coordinated climbing concept

[0472] Output: Mountain climbing concept diagram displayed on the user's device

[0473] Specific operation: The server sends the adjusted mountain climbing concept map to the user's terminal, which displays it. The user can check the mountain climbing route and safety information in a visually easy-to-understand format.

[0474] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice 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 voice data.

[0475] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[0476] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0477] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0478] [Second embodiment]

[0479] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0480] 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.

[0481] 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 wide area network (WAN) and / or a local area network (LAN).

[0482] 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.

[0483] 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 the voice according to instructions from the processor 46.

[0484] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0485] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0486] Fig. 4 shows an example of 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.

[0487] 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.

[0488] 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.

[0489] 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.

[0490] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0491] "Example 1"

[0492] In one embodiment of the present invention, a climber inputs climbing route information based on a topographical map into the system. This climbing route information includes, for example, the start and end points of the route planned by the climber, waypoints, and points requiring special attention. Next, an AI in the system generates how to read and write topographical features based on the climbing route information. This AI generates how to read and write topographical features by reading detailed information on the topographical map. Finally, the system automatically creates a climbing concept map using how to read and write topographical features generated by the AI. This climbing concept map is created including surrounding information other than the climbing route (mountain huts, etc.).

[0493] "Example 2"

[0494] As another embodiment of the present invention, when a climber inputs climbing route information based on a topographical map into the system, the climber can input the information in a format that is easy to understand intuitively. For example, climbing route information can be input by drawing the route directly on the topographical map. In addition, when the system automatically creates a climbing concept map using how to read and write the topographical features generated by AI, the system displays the climbing concept map in a visually easy-to-understand format that is easy for climbers to understand. For example, topographical features, climbing routes, and surrounding information are expressed using colors, line thicknesses, symbols, etc.

[0495] The process flow of each embodiment will be described below.

[0496] "Example 1"

[0497] Step 1: A climber inputs climbing route information based on a topographical map into the system. This climbing route information includes, for example, the start and end points of the climber's planned route, intermediate points, and points requiring special caution.

[0498] Step 2: The AI ​​in the system generates how to read and write the topographical features based on the climbing route information. This AI generates how to read and write the topographical features by reading the detailed information on the topographical map.

[0499] Step 3: The system automatically creates a mountain climbing concept map using the AI-generated reading and writing of terrain features. This mountain climbing concept map is created including surrounding information (mountain huts, etc.) other than the climbing route.

[0500] "Example 2"

[0501] Step 1: When climbers input climbing route information based on a topographical map into the system, the input should be in a format that is intuitive and easy for climbers to understand. For example, climbing route information can be input by drawing the route directly on a topographical map.

[0502] Step 2: The AI ​​in the system generates how to read and write the topographical features based on the climbing route information. This AI generates how to read and write the topographical features by reading the detailed information on the topographical map.

[0503] Step 3: The system uses the AI-generated methods for reading and writing terrain features to automatically create a mountaineering concept map, which is displayed in a visually easy-to-understand format for climbers to understand. For example, colors, line thicknesses, symbols, etc. are used to represent terrain features, climbing routes, and surrounding information.

[0504] Example 1

[0505] Next, a description will be given of Example 1 of Form 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".

[0506] In conventional mountain climbing planning systems, when climbers input detailed climbing route information based on topographical maps, they had to understand how to read and write topographical features and enter them appropriately. This made it difficult for climbers without specialized knowledge of topographical maps to make accurate climbing plans, and also made it difficult to create comprehensive climbing concept maps that included surrounding information (such as accommodation facilities) other than the climbing route. This led to issues such as a decrease in the accuracy of climbing plans and difficulty in ensuring safety during climbing.

[0507] 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.

[0508] In this invention, the server includes a means for a climber to input climbing route information based on a topographical map, a means for acquiring topographical map data based on the climbing route information, a generation AI model means for analyzing the topographical map data and generating how to read and write topographical features, a means for automatically creating a climbing concept map using the how to read and write topographical features generated by the generation AI model means, and a means for displaying the climbing concept map on a user's terminal. This allows climbers to make accurate climbing plans even without specialized knowledge, and makes it easy to create a comprehensive climbing concept map that includes peripheral information other than the climbing route.

[0509] "Climber" refers to an individual or group engaged in mountaineering activities.

[0510] A "topographic map" is a map showing detailed information about a terrain, including contour lines and topographical features.

[0511] "Mountain climbing route information" refers to information such as the starting point, end point, waypoints, and points requiring caution on the mountain climbing route planned by the climber.

[0512] "Server" refers to a computer system that processes and stores data.

[0513] "Terminal" refers to a device that allows a user to input information and display results, including, for example, a smartphone or a personal computer.

[0514] "Topographical map data" means digital data based on a topographical map and includes detailed information on the topography.

[0515] "Generative AI model" refers to a model that uses artificial intelligence to perform a specific task, in this case, generating ways to read or write topographical features.

[0516] A "mountain climbing concept map" refers to a diagram that visually shows a mountain climbing route and the surrounding information.

[0517] "Accommodation" refers to facilities where climbers can stay overnight. Examples include mountain huts and campsites.

[0518] This invention is a system that allows a climber to input climbing route information based on a topographical map, generates how to read and write topographical features based on that information, and finally automatically creates a climbing concept map. A specific embodiment of this system will be described below.

[0519] First, the user uses the terminal to input climbing route information. The user inputs the start and end points of the planned route, intermediate points, and points requiring special caution. For example, the user opens a smartphone app and inputs into the input form, "From the fifth station of Mt. Fuji to the summit of Mt. Fuji, intermediate points are the sixth, seventh, and eighth stations, and points requiring caution are the steep slope at the seventh station."

[0520] Next, the server receives the climbing route information entered by the user and obtains the topographical map data. Specifically, the server uses the Google Maps API or OpenStreetMap API to obtain topographical map data related to the specified route. For example, the server sends a request to the API to "obtain topographical map data from the fifth station of Mt. Fuji to the summit of Mt. Fuji."

[0521] The generative AI model in the server then analyzes the acquired topographical map data. The generative AI model reads the topographical map data and analyzes the topographical features of each point. For example, the AI ​​identifies the "steep slope at the seventh station" and analyzes its features in detail.

[0522] Next, the generative AI model generates how to read and write the topographical features based on the analysis results. Specifically, the AI ​​generates information such as "The steep slope at the seventh station requires special caution." For example, the AI ​​generates instructions such as "Use specific icons and colors to highlight the steep slope feature."

[0523] The server then automatically creates a mountain climbing concept map using the reading and writing of the terrain features generated by the generative AI model. Specifically, the server combines the topographical map data with the generated information to create a visually easy-to-understand mountain climbing concept map. For example, the server performs a process such as "displaying the route from the fifth station of Mt. Fuji to the summit of Mt. Fuji in red, and displaying the steep slope at the seventh station with a yellow warning icon."

[0524] Finally, the server sends the created mountain climbing concept map to the user's terminal and displays it. Specifically, the mountain climbing concept map is displayed on the user's smartphone or PC. For example, the user checks on the screen of their smartphone "a mountain climbing concept map that visually displays the route from the fifth station of Mt. Fuji to the summit of Mt. Fuji, each waypoint, and points requiring caution."

[0525] Examples of concrete examples and prompts

[0526] Examples

[0527] The user opens the app on their smartphone and enters the following information:

[0528] Starting point: Mount Fuji 5th Station

[0529] End point: The summit of Mt. Fuji

[0530] Waypoints: 6th, 7th, 8th stations

[0531] Areas requiring caution: Steep slope at the seventh station

[0532] The server uses the Google Maps API to obtain topographical map data from the fifth station of Mt. Fuji to the summit. Next, a generative AI model in the server analyzes the topographical map data and identifies the characteristics of the steep slope at the seventh station. The AI ​​generates information such as "particular caution is required on steep slopes," and the server uses this information to create a conceptual map of the climb. Finally, the server sends the conceptual map created by the server to the user's smartphone, where the user can check it on the screen.

[0533] Examples of prompt statements

[0534] "I am planning a climbing route from the 5th station of Mt. Fuji to the summit of Mt. Fuji. I will include the 6th, 7th, and 8th stations as waypoints, and I need to be careful of the steep slope of the 7th station. Please create a conceptual map of the climb based on this information."

[0535] The above is an embodiment of the invention.

[0536] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0537] Step 1:

[0538] A user inputs climbing route information using a terminal.

[0539] Specifically, the user opens the application on their smartphone or PC and enters the start point, end point, intermediate points, and points requiring caution of the planned route into an input form.

[0540] Input: Climbing route information (starting point, ending point, intermediate points, points requiring caution)

[0541] Output: Route information sent to the server

[0542] Step 2:

[0543] The server receives the climbing route information input by the user and obtains the topographical map data.

[0544] Specifically, the server uses the Google Maps API or the OpenStreetMap API to retrieve topographical map data related to the specified route.

[0545] Input: Climbing route information

[0546] Output: Topographical map data

[0547] Step 3:

[0548] A generative AI model on the server analyzes the acquired topographical map data.

[0549] Specifically, the generative AI model reads topographical map data and analyzes the terrain features of each location, identifying features such as steep slopes and cliffs.

[0550] Input: Topographic map data

[0551] Output: Analysis results of terrain features

[0552] Step 4:

[0553] A generative AI model generates readings and writings for topographical features based on the analysis results.

[0554] Specifically, the AI ​​generates information such as "particular caution is required on steep slopes" and generates instructions to use specific icons and colors.

[0555] Input: Topographic feature analysis results

[0556] Output: How to read and write topographical features

[0557] Step 5:

[0558] The server automatically creates a mountain climbing concept map using how to read and write the terrain features generated by the generative AI model.

[0559] Specifically, the server combines the topographical map data with the generated information to create a visually easy-to-understand mountain climbing concept map. For example, the route is displayed in red and steep slopes are displayed with a yellow warning icon.

[0560] Input: Topographic map data, how to read and write topographic features

[0561] Output: Mountain climbing concept diagram

[0562] Step 6:

[0563] The server transmits the created mountain climbing concept map to the user's terminal and displays it.

[0564] Specifically, a conceptual map of the climb is displayed on the user's smartphone or PC. The user can check the conceptual map on the screen, which visually displays the route, each waypoint, and points requiring caution.

[0565] Input: Mountain climbing concept diagram

[0566] Output: A conceptual diagram of the climb displayed on the user's device

[0567] (Application example 1)

[0568] Next, a description will be given of Application Example 1 of Form 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".

[0569] For autonomous vehicles, there is a need to generate optimal driving routes based on topographical maps and road information, and provide route maps that include points requiring special attention and surrounding information. However, current systems have the challenge of being unable to efficiently analyze and visually display this information.

[0570] The identification process by the identification processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for inputting route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the route information, a means for automatically creating a conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and a means for displaying the conceptual map. This makes it possible to generate an optimal driving route for an autonomous vehicle and efficiently provide a route map including points requiring special attention and surrounding information.

[0571] A "topographic map" is a map that contains detailed information about the terrain, visually showing the relief and characteristics of the terrain.

[0572] "Route information" refers to information about a route, such as a starting point, a destination point, and intermediate points.

[0573] An "artificial intelligence means" is a system that uses technologies such as machine learning and deep learning to analyze data and automatically perform specific tasks.

[0574] "Topographical features" refers to the relief and shape of the terrain shown on a topographical map, and the characteristics of a specific point.

[0575] "Reading and writing" refers to ways of understanding and visually representing topographical features.

[0576] A "conceptual map" is a diagram that visually simplifies specific information and includes routes and surrounding information.

[0577] The term "display means" refers to a device or system for visually displaying the generated conceptual diagram or other information.

[0578] "Nearby information" is information about points related to the route, including facilities such as rest areas and gas stations.

[0579] As an embodiment of the present invention, an "automated driving route optimization system" for automated driving vehicles will be described as an example. This system generates an optimal driving route based on topographical maps and road information, and provides a route map that includes points requiring special attention and surrounding information.

[0580] Hardware and Software Used

[0581] Hardware: On-board computer, GPS module, camera, LiDAR sensor for autonomous vehicles

[0582] Software: TensorFlow (training and inference of AI models), OpenStreetMap API (obtaining topographical maps and road information), Python (programming language)

[0583] Data processing and calculation

[0584] Data Entry

[0585] Users input start, destination and intermediate points into the autonomous vehicle's on-board computer, and the system then uses the OpenStreetMap API to retrieve topographical and road information for the specified route.

[0586] Analysis by AI model

[0587] The server uses TensorFlow to analyze the retrieved topographical map and road information and generate readings and writings of topographical features, which identify areas that require special attention (sharp curves, steep gradients, intersections, etc.).

[0588] Route Optimization

[0589] The server calculates the optimal driving route based on how the AI ​​model reads and writes the terrain features, taking into account surrounding information (gas stations, rest areas, etc.).

[0590] Generate route map

[0591] The server generates an optimized route map and displays it on the autonomous vehicle's display, along with visual indications of points of special interest and surrounding information.

[0592] Examples

[0593] Example prompts to be input to the generative AI model

[0594] Starting point: 35.6895, 139.6917

[0595] Destination point: 35.6586, 139.7454

[0596] Waypoint: 35.6733, 139.7100

[0597] Particular caution is required at: sharp curves, steep gradients, intersections

[0598] Based on this prompt, the server retrieves topographical maps and road information and performs analysis using an AI model. Based on the analysis results, it calculates the optimal driving route, generates a route map and displays it on the display of the autonomous vehicle, allowing the user to check a safe and efficient driving route.

[0599] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0600] Step 1:

[0601] The user inputs the starting point, destination point, and intermediate points into the on-board computer of the autonomous vehicle, and the system retrieves these points. The input includes latitude and longitude coordinates. The output is the coordinates that are passed to the next step.

[0602] Step 2:

[0603] The server uses the OpenStreetMap API to get the topographical map and road information for the specified route. As input, the coordinate information obtained in step 1 is used. The server sends an API request and receives data including the topographical map and road information. As output, the topographical map and road information are passed on to the next step.

[0604] Step 3:

[0605] The server uses TensorFlow to analyze the retrieved topographical map and road information and generate readings and writings of the topographical features. As input, the topographical map and road information retrieved in step 2 are used. Using an AI model, the server analyzes the topographical features and identifies points that require special attention (sharp curves, steep gradients, intersections, etc.). As output, the readings and writings of the topographical features are passed on to the next step.

[0606] Step 4:

[0607] The server calculates the optimal driving route based on the reading and writing of the terrain features generated by the AI ​​model. As input, the reading and writing of the terrain features generated in step 3 is used. The server also takes into account surrounding information (gas stations, rest areas, etc.) to calculate the optimal driving route. As output, the optimized driving route is passed to the next step.

[0608] Step 5:

[0609] The server generates an optimized route map and displays it on the autonomous vehicle's display. As input, the optimal driving route calculated in step 4 is used. The server generates the route map and also visually displays points of special interest and surrounding information. As output, the route map is displayed on the display for the user to review.

[0610] Through this series of processes, the user can check a safe and efficient driving route.

[0611] Example 2

[0612] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0613] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on a topographical map, and the generated mountain climbing concept map was visually difficult to understand. Furthermore, it was difficult to automatically create a detailed mountain climbing concept map that included surrounding information (such as accommodations) other than the mountain climbing route.

[0614] 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.

[0615] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, a means for transmitting the mountain climbing route information as digital data, a means for using a generative AI model for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and writings of the topographical features generated by the generative AI model, and a means for displaying the mountain climbing conceptual map in a visually easy-to-understand format. This allows the user to intuitively input mountain climbing route information, and makes it possible to automatically create a visually easy-to-understand mountain climbing conceptual map. It is also possible to provide a detailed mountain climbing conceptual map that includes surrounding information other than the mountain climbing route.

[0616] A "topographic map" is a map that visually represents detailed information about a terrain.

[0617] "Mountain climbing route information" is information about the route of a mountain climbing planned by a mountain climber.

[0618] The "means for inputting" is a device or software that provides an interface for a user to draw a climbing route on a topographical map.

[0619] The "means for transmitting as digital data" refers to a communication means for transmitting the climbing route information input by the user to the server in digital form.

[0620] A "generative AI model" is an artificial intelligence model that analyzes and generates how to read and write topographical features.

[0621] A "climbing concept map" is a visual representation of a climbing route and the topographical features of its surroundings.

[0622] "Means for automatic creation" refers to a device or software for automatically generating a mountain climbing concept map using a generative AI model.

[0623] The "means for displaying in a visually easy-to-understand format" refers to a device or software for displaying the generated mountain climbing concept map in a format that is easy for the user to understand.

[0624] "Local information" refers to information about accommodation and other important points related to the climbing route.

[0625] This invention is a system that allows climbers to intuitively input climbing route information based on a topographical map, analyzes topographical features using a generative AI model, and automatically creates a visually easy-to-understand climbing concept map. This system works in cooperation with the user, the terminal, and the server.

[0626] First, the user draws a climbing route on the topographical map displayed on the terminal screen using a mouse or a touch pen. The user can intuitively input route information by drawing a line on the topographical map or clicking points. For example, the user specifies a climbing route by dragging the mouse from the starting point to the goal point to draw a line.

[0627] Next, the terminal transmits the climbing route information drawn by the user to the server as digital data. This data includes the route coordinate information and drawing format (line color, thickness, etc.). For example, it includes the coordinates of the start and end points of the line, and information on the line color and thickness.

[0628] The server receives the climbing route information sent from the terminal and uses a generative AI model to analyze how to read and write the topographical features. The server automatically generates a climbing concept map based on the analysis results. The generated concept map displays the climbing route in a visually easy-to-understand format. Specifically, the topographical features, climbing route, and surrounding information are expressed using colors, line thickness, symbols, etc. For example, the climbing route is displayed with a thick red line, and the surrounding topographical features are expressed with blue dotted lines and green symbols.

[0629] The server then transmits the generated mountain climbing concept map to the terminal. The terminal receives this data and displays it to the user. The user can check the mountain climbing concept map displayed on the terminal screen and confirm the mountain climbing route and the characteristics of the terrain displayed in a visually easy-to-understand format. This allows the user to obtain information that is useful when making mountain climbing plans.

[0630] As a concrete example, consider the case where a user draws a mountain climbing route with a red line on a topographical map. When the user drags the mouse to draw a line from the starting point to the goal, the device sends that information to the server as digital data. The server uses a generative AI model to analyze the characteristics of the terrain, and generates a mountain climbing concept map that displays the climbing route with a thick red line and the surrounding topographical features with blue dotted lines and green symbols. The server sends this concept map to the device, where the user can view it on the device screen.

[0631] An example of a prompt is as follows:

[0632] "Please draw your climbing route on the topographical map in red. The system will create a climbing concept map based on that information and display your climbing route in thick red."

[0633] "Click multiple points on the topographical map to specify a climbing route. The system will create a climbing concept map based on that information and display the climbing route with a yellow dashed line."

[0634] In this way, the user can intuitively input mountain climbing route information and obtain a visually easy-to-understand mountain climbing concept map, which improves convenience when making mountain climbing plans.

[0635] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0636] Step 1:

[0637] The user inputs a climbing route.

[0638] The user draws a climbing route on the topographical map displayed on the terminal screen using a mouse or a touch pen. Specifically, the user draws a line by dragging the mouse from the starting point to the goal point. This operation inputs the coordinate information of the climbing route and the drawing format (such as the color and thickness of the line).

[0639] Step 2:

[0640] The terminal transmits the input data to the server.

[0641] The terminal sends the climbing route information drawn by the user to the server as digital data. The input includes the coordinates of the start and end points of the line, and information on the color and thickness of the line. The terminal assembles this data into packets and sends them to the server.

[0642] Step 3:

[0643] The server receives and analyzes the data.

[0644] The server receives the climbing route information sent from the device. The input includes the climbing route's coordinate information and drawing format. The server uses a generative AI model to analyze how to read and write the terrain features. Specifically, it analyzes the elevation and slope of the terrain through which the route passes, and extracts detailed information about the climbing route.

[0645] Step 4:

[0646] The server generates a conceptual map of the mountain climb.

[0647] The server automatically generates a mountain climbing concept map based on the analysis results. The input includes the analyzed terrain feature information. The server uses the generative AI model to display the mountain climbing route in a visually easy-to-understand format. Specifically, the mountain climbing route is displayed as a thick red line, and the surrounding terrain features are represented by blue dotted lines and green symbols.

[0648] Step 5:

[0649] The server transmits the generated mountain climbing concept map to the terminal.

[0650] The server transmits the generated mountain climbing concept map to the terminal. The input includes the data of the generated mountain climbing concept map. The server assembles this data into packets and transmits them to the terminal.

[0651] Step 6:

[0652] The user checks the mountain climbing concept map.

[0653] The user checks the mountain climbing concept map displayed on the screen of the terminal. The input includes the data of the mountain climbing concept map sent from the server. The user checks the mountain climbing route and the topographical features displayed in a visually easy-to-understand format and makes a mountain climbing plan. Specifically, the user makes a mountain climbing plan by looking at the mountain climbing route and the surrounding topographical features.

[0654] (Application example 2)

[0655] Next, a description will be given of Application Example 2 of Form 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".

[0656] In conventional climbing route information input systems, it was difficult for users to intuitively input climbing route information based on a topographical map, and the generated climbing concept map was visually difficult to understand. Furthermore, it was difficult to automatically create a detailed climbing concept map that included surrounding information other than the climbing route. This made it difficult for climbers to plan climbing routes safely and efficiently.

[0657] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0658] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an AI means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the AI ​​means, a means for inputting route information by drawing a route on a map, a means for analyzing the route information and converting it into a visually easy-to-understand format, and a means for displaying the converted route information. This makes it possible for a user to intuitively input mountain climbing route information and automatically generate a visually easy-to-understand mountain climbing concept map.

[0659] A "topographic map" is a map that shows detailed information about the terrain and is used to plan climbing routes and understand the characteristics of the terrain.

[0660] "Mountain climbing route information" refers to information about a mountain climbing route planned by a climber, including the route and points of the route depicted on a topographical map.

[0661] "AI means" means means for analyzing data and automatically performing specific tasks using artificial intelligence technology.

[0662] A "mountain climbing concept map" is a diagram that visually represents a mountain climbing route and surrounding information in an easy-to-understand manner, making it easier for climbers to understand the route.

[0663] The "means for inputting route information" refers to a means for a user to input climbing route information into the system by drawing the route directly on a map.

[0664] A "visually easy-to-understand format" is a format that expresses information using colors, line thicknesses, symbols, etc., making it easy for users to understand intuitively.

[0665] The "means for analyzing route information" refers to a means for analyzing input route information and converting it into a visually easy-to-understand format.

[0666] The "means for displaying route information" refers to a means for displaying the analyzed route information to the user in a visually easy-to-understand format.

[0667] A system for implementing this invention includes means for inputting mountain climbing route information based on a topographical map, AI means for generating how to read and write topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the how to read and write the topographical features generated by the AI ​​means, means for inputting route information by drawing a route on a map, means for analyzing the route information and converting it into a visually easy-to-understand format, and means for displaying the converted route information.

[0668] Program processing explanation

[0669] The server reads the topographical map data, and the user inputs the climbing route information by drawing the route on the map. Specifically, the user draws the route on the map using a touch screen or mouse input on a device such as a smartphone or a head-mounted display. This route information is sent to the server, and the AI ​​means analyzes it.

[0670] The AI ​​tool analyzes the input route information and generates readings and writings of topographical features. It uses Python and its libraries (matplotlib, numpy, sklearn, etc.). The analyzed data is converted into a visually easy-to-understand format. For example, the route is represented using colors, line thickness, symbols, etc.

[0671] The converted route information is sent from the server to the user's device and displayed in a visually easy-to-understand format, making it easier for users to intuitively understand the climbing route information.

[0672] Examples

[0673] For example, when a user uses a smartphone to draw a mountain climbing route on a map, the user draws the route on the map with his / her finger. The server receives this information, and the AI ​​means analyzes it to generate a visually easy-to-understand mountain climbing concept diagram. This mountain climbing concept diagram is expressed using colors, line thickness, symbols, etc., and is displayed on the smartphone screen.

[0674] Examples of prompt statements

[0675] Below are examples of prompts to be input to the generative AI model.

[0676] Please create an application where the user draws a route on a map, and the route is analyzed by AI and displayed in a visually easy-to-understand format. Please provide a Python program that includes the following steps: loading map data, inputting route information, analyzing the route by AI, and generating a route map.

[0677] It is expected that by using this prompt sentence, the generative AI model will generate an appropriate program.

[0678] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0679] Step 1:

[0680] The user loads map data using a smartphone or head-mounted display.

[0681] Input: Map data file (e.g. topographical map image file)

[0682] Output: Map data is displayed.

[0683] Specific operation: The user launches the application on the device, selects and loads a map data file, and the map data is displayed on the device screen.

[0684] Step 2:

[0685] The user draws a route on a map.

[0686] Input: Route drawing information from the user's touch screen or mouse input

[0687] Output: Rendered route information

[0688] How it works: A user draws a climbing route on a map using a finger or a stylus. The route information is stored on the device and sent to the server.

[0689] Step 3:

[0690] The server analyzes the received route information.

[0691] Input:Drawn route information

[0692] Output: Parsed route data

[0693] Specific operation: The server analyzes the received route information and generates reading and writing instructions for terrain features. It analyzes the data using Python libraries (numpy, sklearn, etc.) and extracts route features.

[0694] Step 4:

[0695] The server converts the parsed route data into a visually understandable format.

[0696] Input: Parsed route data

[0697] Output: Route data in a visually friendly format

[0698] Specific operation: The server converts the analyzed route data into a visually easy-to-understand format using colors, line thickness, symbols, etc. It uses matplotlib to draw the route and arrange it into a visually easy-to-understand format.

[0699] Step 5:

[0700] The server sends the converted route data to the user's device.

[0701] Input: Route data in a visually friendly format

[0702] Output: The route map as it appears on the user's device.

[0703] Specific operation: The server sends the converted route data to the user's device, which then displays the received data and provides the user with a visually easy-to-understand route map.

[0704] Step 6:

[0705] Users can view easy-to-understand route maps.

[0706] Input: Route map in a visually friendly format

[0707] Output: User understanding and confirmation

[0708] Specific operation: The user checks the route map displayed on the device screen and plans a mountain climbing route. Visual information using colors, line thickness, symbols, etc. allows the user to intuitively understand the route.

[0709] In addition, 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.

[0710] "Example 1"

[0711] As one embodiment of the present invention, a system is provided that combines an emotion engine that recognizes the emotions of a user. This system includes an AI means that receives mountain climbing route information based on a topographical map and generates how to read and write topographical features based on the mountain climbing route information, and a means that automatically creates a mountain climbing concept map using the how to read and write the topographical features generated by the AI ​​means. Furthermore, an emotion engine that recognizes the emotions of a user is also included. This emotion engine recognizes the emotional state of a user, for example, from the user's facial expression, tone of voice, text input, etc. Then, the reading and writing of the topographical features and the display method of the mountain climbing concept map are adjusted according to the emotional state. For example, if it is recognized that the user is nervous, more detailed topographical information is provided. Also, if it is recognized that the user is relaxed, only the minimum necessary information is provided, making it possible to provide optimal information according to the user's emotional state.

[0712] "Example 2"

[0713] As another embodiment of the present invention, a system is provided in which an emotion engine adjusts the display method of a mountain climbing concept map according to the emotional state of a user. As in the above-mentioned embodiment, this system includes an AI means for inputting mountain climbing route information based on a topographical map and generating a reading and writing method of topographical features based on the mountain climbing route information, and a means for automatically creating a mountain climbing concept map using the reading and writing method of the topographical features generated by the AI ​​means. Furthermore, an emotion engine for recognizing the emotion of a user is also included. This emotion engine adjusts the display method of the mountain climbing concept map according to the emotional state of the user. For example, if it is recognized that the user is feeling anxious, more detailed topographical information and safety information are displayed with emphasis. Also, if it is recognized that the user is excited, an optimal display method according to the emotional state of the user is provided, such as increasing the options of mountain climbing routes.

[0714] The process flow of each embodiment will be described below.

[0715] "Example 1"

[0716] Step 1: Receive climbing route information based on a topographical map from the user as input.

[0717] Step 2: Using AI means, generate readings and writings of terrain features based on the input climbing route information.

[0718] Step 3: Automatically create a mountaineering concept map using the generated reading and writing methods for the terrain features.

[0719] Step 4: Use the emotion engine to recognize the user's emotional state from their facial expressions, tone of voice, text input, etc.

[0720] Step 5: Adjust the way terrain features are read and written and the way mountain climbing concept maps are displayed according to the recognized emotional state of the user.

[0721] "Example 2"

[0722] Step 1: Receive climbing route information based on a topographical map from the user as input.

[0723] Step 2: Using AI means, generate readings and writings of terrain features based on the input climbing route information.

[0724] Step 3: Automatically create a mountaineering concept map using the generated reading and writing methods for the terrain features.

[0725] Step 4: Recognize the user's emotional state using the emotion engine.

[0726] Step 5: Adjust the way the mountain climbing concept diagram is displayed depending on the recognized emotional state of the user.

[0727] Example 1

[0728] Next, a description will be given of Example 1 of Form 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] In conventional mountain climbing support systems, the input of mountain climbing route information and the analysis of terrain characteristics are often done manually, which is inefficient. In addition, since information is not provided according to the user's emotional state, it is difficult to provide information optimal for the user's situation. This leads to the issue that safety and comfort during mountain climbing are not sufficiently ensured.

[0730] 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.

[0731] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the artificial intelligence means, an emotion recognition means for recognizing the emotion of the user, and a means for adjusting the information provided in accordance with the emotional state of the user recognized by the emotion recognition means. This makes it possible to automatically create a mountain climbing concept map based on the user's input, and to provide optimal information in accordance with the emotional state of the user.

[0732] A "topographic map" is a map that shows detailed information about the terrain and is used to plan and analyze climbing routes.

[0733] "Mountain climbing route information" is information about the route planned by the climber, such as the starting point and end point of the climb, intermediate points, and points requiring special caution.

[0734] "Artificial intelligence means" means technology that includes algorithms or models to analyse input data and perform specific tasks automatically.

[0735] "How to read and write topographic features" refers to a method of analyzing information obtained from topographic maps and expressing it in a form that is easy for climbers to understand.

[0736] A "climbing concept map" is a diagram that visually shows a climbing route and the surrounding information, making it easier for climbers to understand the route.

[0737] "Emotion recognition means" is a technology that analyzes a user's emotional state from facial expressions, tone of voice, text input, etc.

[0738] "Means for adjusting information provision" refers to technology that changes the content and format of the information provided depending on the user's emotional state.

[0739] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0740] The present invention is a system in which a climber inputs climbing route information based on a topographical map, and an artificial intelligence generates how to read and write the topographical features based on that information, and finally creates a climbing concept map. In addition, by combining an emotion recognition means that recognizes the user's emotions, information is provided according to the user's emotional state.

[0741] System Configuration

[0742] 1. Enter climbing route information

[0743] The user inputs mountain climbing route information, specifically, the start and end points of the mountain climbing, intermediate points, points requiring special attention, etc.

[0744] Hardware used: PC, smartphone, tablet, etc.

[0745] Software used: Web browser, dedicated application

[0746] 2. Generating readings and writings of topographical features

[0747] The server receives the input climbing route information and generates readings and writings of topographical features using an AI model that analyzes detailed information on topographical maps.

[0748] Hardware used: Server (high performance CPU, GPU)

[0749] Software used: Artificial intelligence models (e.g. TensorFlow, PyTorch)

[0750] 3. Creating a mountain climbing concept map

[0751] The server automatically creates a mountain climbing concept map using the reading and writing of the terrain features generated by the artificial intelligence. This mountain climbing concept map includes surrounding information (mountain huts, etc.) other than the climbing route.

[0752] Hardware used: Server

[0753] Software used: Mapping software (e.g. QGIS)

[0754] 4. Emotion recognition using emotion recognition means

[0755] The terminal recognizes the user's emotional state from the user's facial expressions, tone of voice, text input, etc., which are then analyzed by the emotion recognition means.

[0756] Hardware used: PC, smartphone, tablet (camera, microphone)

[0757] Software used: Emotion recognition software (e.g. Microsoft Azure Emotion API)

[0758] 5. Coordination of information provision

[0759] The server adjusts how to read and write the terrain features and how to display the mountain climbing concept map according to the user's emotional state obtained from the emotion recognition means. For example, if the user is nervous, detailed terrain information is provided, and if the user is relaxed, only the minimum necessary information is provided.

[0760] Hardware used: Server

[0761] Software used: Customized information providing algorithms

[0762] Examples

[0763] The user opens a dedicated smartphone application and inputs climbing route information. For example, the user inputs "route from the fifth station to the summit of Mt. Fuji, stopping at mountain huts along the way."

[0764] The server receives this information and uses artificial intelligence models to generate readings and writings of the topographical features.

[0765] The server creates a mountain climbing concept map based on the generated information and displays it on the smartphone.

[0766] The terminal captures the user's facial expression with a camera, and the emotion recognition means recognizes that the user is nervous.

[0767] The server provides a conceptual map of a mountain climb including detailed topographical information.

[0768] Examples of prompt statements

[0769] "Please enter the route from the fifth station to the summit of Mt. Fuji. Please also enter any mountain huts you may need to stop at along the way and any points requiring caution."

[0770] In this way, the system automatically creates a mountain climbing concept map based on the user's input, and can provide optimal information according to the user's emotional state.

[0771] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0772] Step 1:

[0773] The user inputs the climbing route information. Specifically, the user opens a dedicated application on his / her smartphone and enters "Route from the fifth station of Mt. Fuji to the summit, stopping at mountain huts on the way" into the input form.

[0774] Input: Climbing route information such as the start and end points of the climb, intermediate points, and points requiring special attention

[0775] Output: The entered climbing route information is sent to the server.

[0776] Step 2:

[0777] The server receives the climbing route information sent by the user, then uses an artificial intelligence model to generate readings and writings of the terrain features.

[0778] Input: Climbing route information sent by the user

[0779] Data processing: The server analyzes the received data and uses artificial intelligence models (e.g. TensorFlow) to analyze detailed information on the topographical maps.

[0780] Output: How to read and write the topographical features is generated

[0781] Specific operation: The server analyzes the received data, analyzes the detailed information of the topographical map using TensorFlow, and generates how to read and write the topographical features.

[0782] Step 3:

[0783] The server automatically creates a mountain climbing concept map based on how to read and write the terrain features generated by the artificial intelligence. This mountain climbing concept map includes surrounding information (mountain huts, etc.) other than the climbing route.

[0784] Input: How to read and write terrain features generated by artificial intelligence

[0785] Data processing: The server uses QGIS to create a conceptual map of the climbing route and surrounding information.

[0786] Output: A mountain climbing concept map is generated and sent to the user's smartphone.

[0787] Specific operation: The server creates a mountain climbing concept map using QGIS and sends it to the user's smartphone.

[0788] Step 4:

[0789] The terminal recognizes the user's emotional state from the user's facial expressions, tone of voice, text input, etc., which are then analyzed by the emotion recognition means.

[0790] Input: User facial expressions, tone of voice, text input, etc.

[0791] Data processing: The device captures data using the camera and microphone and analyzes it using emotion recognition software (e.g. Microsoft Azure Emotion API).

[0792] Output: The user's emotional state is recognized.

[0793] How it works: The smartphone camera captures the user's facial expressions and analyzes their emotional state using the Microsoft Azure Emotion API.

[0794] Step 5:

[0795] The server adjusts how to read and write the terrain features and how to display the mountain climbing concept map according to the user's emotional state obtained from the emotion recognition means. For example, if the user is nervous, detailed terrain information is provided, and if the user is relaxed, only the minimum necessary information is provided.

[0796] Input: The user's emotional state obtained from an emotion recognition means

[0797] Data processing: The server receives the analysis results of the emotion recognition method and adjusts the display method using an information provision algorithm.

[0798] Output: The adjusted information is displayed on the user's smartphone.

[0799] Specific operation: The server receives the analysis results of the emotion recognition means, and if it determines that the user is nervous, it regenerates a mountain climbing concept map including detailed terrain information and sends it to the smartphone.

[0800] (Application example 1)

[0801] Next, a description will be given of Application Example 1 of Form 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".

[0802] Conventional mountain climbing route guidance systems provide uniform information without considering the user's emotional state, which means that they cannot provide appropriate information when the user is tense or relaxed. In addition, they lack the functionality to automatically generate how to read and write detailed topographical features based on topographical maps, making it difficult to provide the information users need quickly and accurately.

[0803] 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.

[0804] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an AI means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the AI ​​means, a means including an emotion engine for recognizing the user's emotions, and a means for adjusting the information provided according to the user's emotional state recognized by the emotion engine. This makes it possible to provide optimal information according to the user's emotional state.

[0805] A "topographic map" is a map that shows detailed information about a terrain, visually representing climbing routes and terrain features.

[0806] "Mountain climbing route information" includes information on the start point, end point, waypoints, points requiring special caution, and the like of the route the climber plans to take.

[0807] "AI Means" means a means for performing a specific task using artificial intelligence, and in this case refers to the ability to generate readings and / or writings of topographical features.

[0808] "Reading and writing topographic features" refers to the method of interpreting detailed information about a terrain based on a topographic map and expressing it in visual or textual form.

[0809] A "climbing concept map" is a visual representation of a climbing route and its surrounding information, intended to make it easier for climbers to understand the route.

[0810] An "emotion engine" is a system for recognizing a user's emotional state from their facial expressions, tone of voice, text input, etc.

[0811] The "means for adjusting the information provided" refers to a means for changing the level of detail and content of the information provided in accordance with the user's emotional state.

[0812] A system for implementing this invention includes means for inputting mountain climbing route information based on a topographical map, AI means for generating how to read and write topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the how to read and write the topographical features generated by the AI ​​means, means including an emotion engine for recognizing a user's emotions, and means for adjusting the provision of information in accordance with the user's emotional state recognized by the emotion engine.

[0813] Program processing explanation

[0814] Hardware and software used

[0815] Hardware: Smartphone (camera, microphone)

[0816] Software: Python, OpenCV, EmotionRecognizer library, RoutePlanner library, MapGenerator library

[0817] Processing flow

[0818] 1. User input: The user inputs the starting point, destination point, and intermediate points. This provides the climbing route information to the system.

[0819] 2. Route Planning: The server uses the RoutePlanner library to generate readings and writings of terrain features based on the input route information.

[0820] 3. Map generation: The server uses the MapGenerator library to create a driving concept map, which includes surrounding information (e.g. mountain huts) in addition to the climbing route.

[0821] 4. Emotion recognition: The device uses the EmotionRecognizer library to recognize the user's emotions based on data obtained from the camera and microphone.

[0822] 5. Adjustment of information provision: The server adjusts the level of detail of the information provided depending on the recognized emotional state. For example, if the user is nervous, detailed topographical information is provided, but if the user is relaxed, only the minimum necessary information is provided.

[0823] 6. Display: The device displays the adjusted information on the smartphone screen.

[0824] Examples

[0825] User input: Starting point "Tokyo Station", destination point "Mt. Fuji", intermediate point "Yokohama Station"

[0826] Emotion recognition: If the user is perceived as nervous, detailed terrain information (sharp turns, slope, etc.) is provided.

[0827] Display: Along with a detailed driving concept map, it also displays information on nearby gas stations and rest areas.

[0828] Examples of prompt statements

[0829] If a user inputs the starting point "Tokyo Station", the destination "Mt. Fuji", and the waypoint "Yokohama Station", and the emotion recognition engine recognizes the user's emotion as "nervous", please generate a program that provides detailed topographical and surrounding information.

[0830] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0831] Step 1:

[0832] The user inputs the starting point, destination, and intermediate points. Through the smartphone application, the user inputs the starting point "Tokyo Station," the destination point "Mt. Fuji," and the intermediate point "Yokohama Station." This provides the climbing route information to the system. The input data is sent to the server and proceeds to the next processing step.

[0833] Step 2:

[0834] The server uses the RoutePlanner library to generate readings and writings of terrain features based on the input route information. The server analyzes the received information of the starting point, destination point, and intermediate points, and retrieves the corresponding terrain information from the topographical map database. Based on the retrieved terrain information, the AI ​​model generates readings and writings of terrain features. The generated data is used in the next step.

[0835] Step 3:

[0836] The server creates a driving concept map using the MapGenerator library. The server generates a driving concept map including the climbing route and its surrounding information (e.g. mountain huts) based on the reading and writing of the topographical features generated in step 2. The generated driving concept map is used in the next step.

[0837] Step 4:

[0838] The device uses the EmotionRecognizer library to recognize the user's emotions based on data acquired from the camera and microphone. The device analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state. The determined emotional state is used in the next step.

[0839] Step 5:

[0840] The server adjusts the level of detail of the information to be provided according to the recognized emotional state. The server determines the level of detail of the information to be provided based on the emotional state determined in step 4. For example, if the user is nervous, detailed topographical information is provided, and if the user is relaxed, only the minimum necessary information is provided. The adjusted information is used in the next step.

[0841] Step 6:

[0842] The terminal displays the adjusted information on the smartphone screen. The terminal receives the adjusted driving concept map and surrounding information sent from the server and displays them on the smartphone screen. The user can check the mountain climbing route safely and efficiently based on the displayed information.

[0843] Example 2

[0844] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0845] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on a topographical map, and the generated mountain climbing concept map was not adjusted according to the user's emotional state, making it difficult to provide information that is easy for users to understand. Furthermore, it was also insufficient to create a detailed mountain climbing concept map that included surrounding information other than the mountain climbing route (such as evacuation sites).

[0846] 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.

[0847] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and an emotion recognition means for recognizing the emotional state of the user and adjusting the display method of the mountain climbing conceptual map according to the emotional state. This allows the user to intuitively input mountain climbing route information, and the generated mountain climbing conceptual map is adjusted according to the emotional state of the user, making it possible to provide information that is easy for the user to understand. It also makes it possible to create a detailed mountain climbing conceptual map that includes surrounding information other than the mountain climbing route.

[0848] A "topographic map" is a map that shows the terrain and the locations of landmarks, and is used for planning mountain climbing routes and navigation.

[0849] "Mountain climbing route information" refers to information about the mountain climbing route planned by a climber, including the route depicted on a topographical map and its details.

[0850] "Artificial intelligence means" refers to technology that uses machine learning or data analysis to automatically perform certain tasks, and is used in the present invention to generate readings and writings of topographical features.

[0851] "Topographical characteristics" refers to the characteristics of the terrain and features shown on a topographical map, and are used to evaluate the difficulty of climbing routes and dangerous areas.

[0852] A "climbing concept map" is a diagram that visually shows climbing routes and surrounding information in an easy-to-understand manner, and is created to make it easier for climbers to understand the route.

[0853] The "emotion recognition means" is a technology for analyzing and recognizing the user's emotional state, and in the present invention is used to adjust the display method of the mountain climbing concept map according to the user's emotional state.

[0854] "Area information" refers to information other than the climbing route, including information important to climbers, such as evacuation sites and water sources.

[0855] This invention is a system in which a climber intuitively inputs climbing route information based on a topographical map, and the generated climbing concept map is adjusted according to the user's emotional state. A specific embodiment of this system will be described below.

[0856] First, the user displays a topographical map using a terminal (PC or tablet). The user then draws a climbing route on the topographical map using a mouse or touch screen. For example, the user draws a climbing route by drawing a red line on the topographical map. This information is sent from the terminal to the server as digital data.

[0857] Next, the server analyzes the received climbing route information. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate readings and writings for terrain features. Specifically, the server analyzes the elevation data and terrain relief of the climbing route to evaluate the difficulty and dangerous areas of the climbing route.

[0858] The server then creates a mountain climbing concept map based on how to read and write the generated topographical features. The mountain climbing concept map is displayed in a visually easy-to-understand format using colors, line thickness, symbols, etc. For example, the mountain climbing route is displayed with a thick red line, and dangerous areas are indicated with yellow triangles. Nearby evacuation sites and water sources are also displayed with blue icons.

[0859] In addition, the server recognizes the user's emotional state using emotion recognition means (e.g., IBM Watson or Microsoft Azure Cognitive Services). If the user feels anxious, the server highlights and displays detailed terrain information and safety information. If the user feels excited, the server provides the optimal display method according to the user's emotional state, such as increasing the options for mountain climbing routes.

[0860] As a concrete example, the following prompt sentence is input into the generative AI model.

[0861] Example prompt:

[0862] Based on the climbing route information drawn by the user on the topographical map, use an AI model to generate reading and writing of the terrain features, and create a visually easy-to-understand climbing concept map. Also, use an emotion engine to recognize the user's emotional state and adjust the display method. For example, if the user is feeling anxious, highlight the detailed terrain information, and if the user is excited, increase the options of climbing routes.

[0863] In this way, a system is realized in which the server, terminal, and user work together to input mountain climbing route information, create a mountain climbing concept map, and adjust the display according to emotions.

[0864] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0865] Step 1:

[0866] A user uses a terminal to display a topographical map. The user draws a climbing route on the topographical map using a mouse or a touch screen. The climbing route information drawn by the user is input. The terminal transmits this information to a server as digital data. In concrete terms, the user draws a climbing route by drawing a red line on the topographical map.

[0867] Step 2:

[0868] The server receives climbing route information sent from the terminal. As input, there is digitized climbing route information. The server analyzes this information and generates how to read and write the topographical features using a generative AI model (e.g., TensorFlow or PyTorch). Specifically, the server analyzes the elevation data and topographical relief of the climbing route, and evaluates the difficulty and dangerous areas of the climbing route. As output, how to read and write the topographical features is generated.

[0869] Step 3:

[0870] The server creates a mountain climbing concept map based on how to read and write the generated topographical features. The input is how to read and write the topographical features. The server displays the mountain climbing concept map in a visually easy-to-understand format using colors, line thickness, symbols, etc. In concrete terms, the server displays the mountain climbing route with a thick red line and indicates dangerous areas with yellow triangles. It also displays nearby evacuation sites and water sources with blue icons. The output is a mountain climbing concept map.

[0871] Step 4:

[0872] The server recognizes the user's emotional state using the emotion recognition means. As an input, there is data on the user's emotional state. The server adjusts the display method of the mountain climbing concept map according to the user's emotional state. As a specific operation, if the user feels anxious, the server displays detailed topographical information and safety information with emphasis. If the user is excited, the server increases the options for mountain climbing routes. As an output, an optimal display method according to the user's emotional state is provided.

[0873] (Application example 2)

[0874] Next, a description will be given of Application Example 2 of Form 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".

[0875] Conventional mountain climbing navigation systems have the problem that it is difficult for climbers to intuitively input climbing route information based on topographical maps, and information is not provided according to the user's emotional state, so the safety and comfort of climbers is not sufficiently ensured. In addition, there is also the problem that automatic driving vehicles do not provide appropriate navigation to safely transport climbers to their destinations.

[0876] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0877] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an AI means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the AI ​​means, an emotion engine for recognizing the user's emotional state, a means for adjusting the display method of the mountain climbing concept map according to the emotional state recognized by the emotion engine, and a means for being installed in an autonomous vehicle. This allows mountain climbers to intuitively input mountain climbing route information, and makes it possible to provide optimal navigation information according to the user's emotional state.

[0878] A "topographic map" is a map that visually represents detailed information about a terrain.

[0879] "Mountain climbing route information" is information about the route that a climber plans to take when climbing a mountain.

[0880] "AI Means" means technical means for performing certain tasks using artificial intelligence.

[0881] "Topographic features" refers to topographical characteristics such as mountains, valleys, and rivers on a topographical map.

[0882] A "mountain climbing concept map" is a diagram that visually represents mountain climbing routes and surrounding information.

[0883] An "emotion engine" is a technology for recognizing a user's emotional state and adjusting the system's behavior based on that.

[0884] An "autonomous vehicle" is a vehicle that can drive autonomously using artificial intelligence and sensor technology.

[0885] A "display method" is the means or format by which information is visually presented to a user.

[0886] The following system configuration will be described as an embodiment of the present invention.

[0887] System Configuration

[0888] Hardware

[0889] Autonomous vehicle: A vehicle that can drive autonomously using artificial intelligence and sensor technology.

[0890] Cameras and sensors: devices to recognise the user's emotional state.

[0891] software

[0892] EmotionEngine: Technology for recognizing a user's emotional state and adjusting system behavior based on it.

[0893] AIGeography: Artificial intelligence techniques for generating terrain features and creating mountaineering concept maps.

[0894] Program processing explanation

[0895] Input of climbing route information based on topographical maps

[0896] The server provides a means for inputting climbing route information based on a topographical map. A user can input climbing route information by drawing the route directly on the topographical map. This information is sent to the server and used for the next process.

[0897] Generate terrain features

[0898] The server uses AIGeography to generate readings and writings of terrain features based on the input climbing route information. AIGeography reads detailed information of the topographical map and generates terrain features. The generated terrain features are used to create a climbing concept map.

[0899] Creating a mountain climbing concept map

[0900] The server automatically creates a mountaineering concept map using the reading and writing of the terrain features generated by AIGeography. This mountaineering concept map is displayed in a visually easy-to-understand format, including the climbing route and surrounding information (mountain huts, etc.).

[0901] Adjusting display method using emotion engine

[0902] The server recognizes the user's emotional state using the EmotionEngine. The EmotionEngine analyzes data obtained from cameras and sensors to determine the user's emotional state. For example, if the user feels anxious, the server will highlight safety information on the mountain climbing concept map. In addition, if the user feels excited, the server will provide the optimal display method according to the user's emotional state, such as increasing the number of mountain climbing route options.

[0903] Examples

[0904] For example, consider a climber getting into an autonomous vehicle and inputting a route to a destination. The user draws the route on a topographical map and sends it to the server. The server uses AI Geography to generate topographical features and create a mountain climbing concept map. Next, Emotion Engine recognizes the user's emotional state and adjusts the display method. If the user feels anxious, safety information is emphasized, and if the user is excited, the options for mountain climbing routes are increased.

[0905] Examples of prompt statements

[0906] "Design a mountain climbing navigation system that highlights safety information when the user feels anxious. Input mountain climbing route information based on a topographical map, and create a mountain climbing concept map using AI-generated topographical features. Use an emotion engine to adjust the navigation information according to the user's emotional state."

[0907] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0908] Step 1:

[0909] The user draws a climbing route on a topographical map.

[0910] Input: Topographical map, user-drawn climbing route information

[0911] Output: Climbing route information

[0912] Specific operation: A user draws a climbing route on a topographical map using a device such as a smartphone or tablet. This information is sent from the device to the server.

[0913] Step 2:

[0914] The server receives the climbing route information and generates topographical features using AIGenography.

[0915] Input: Climbing route information

[0916] Output: How to read and write topographical features

[0917] How it works: The server inputs the received climbing route information into AIGeography, and analyzes the detailed information of the topographical map to generate topographical features, including topographical characteristics such as mountains, valleys, and rivers.

[0918] Step 3:

[0919] The server creates a mountain climbing concept map using the generated topographical features.

[0920] Input: How to read and write topographical features

[0921] Output: Mountain climbing concept diagram

[0922] Specific operation: The server automatically creates a mountain climbing concept map including climbing routes and surrounding information (mountain huts, etc.) based on the topographical features generated by AIGenography.

[0923] Step 4:

[0924] The server uses the EmotionEngine to recognize the user's emotional state.

[0925] Input: User emotion data obtained from cameras and sensors

[0926] Output: The user's emotional state.

[0927] Specific operation: The server inputs data obtained from the camera and sensors into the EmotionEngine and analyzes the user's emotional state. For example, it determines whether the user is feeling anxious or excited based on data such as facial expressions and heart rate.

[0928] Step 5:

[0929] The server adjusts the display method of the mountain climbing concept diagram according to the user's emotional state.

[0930] Input: User's emotional state, mountain climbing concept

[0931] Output: Coordinated climbing concept map

[0932] Specific operation: The server adjusts the way the mountain climbing concept map is displayed based on the user's emotional state recognized by the Emotion Engine. For example, if the user feels anxious, the server emphasizes safety information and displays more options for mountain climbing routes if the user feels excited.

[0933] Step 6:

[0934] The server transmits the adjusted mountain climbing concept map to the terminal and displays it to the user.

[0935] Input: Coordinated climbing concept

[0936] Output: Mountain climbing concept diagram displayed on the user's device

[0937] Specific operation: The server sends the adjusted mountain climbing concept map to the user's terminal, which displays it. The user can check the mountain climbing route and safety information in a visually easy-to-understand format.

[0938] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice 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 voice data.

[0939] 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> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[0940] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0941] 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 smart glasses 214.

[0942] [Third embodiment]

[0943] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0944] 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.

[0945] 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 wide area network (WAN) and / or a local area network (LAN).

[0946] 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.

[0947] 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 the voice according to instructions from the processor 46.

[0948] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0949] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0950] 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.

[0951] 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.

[0952] 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.

[0953] In the headset type terminal 314, 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.

[0954] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0955] "Example 1"

[0956] In one embodiment of the present invention, a climber inputs climbing route information based on a topographical map into the system. This climbing route information includes, for example, the start and end points of the route planned by the climber, waypoints, and points requiring special attention. Next, an AI in the system generates how to read and write topographical features based on the climbing route information. This AI generates how to read and write topographical features by reading detailed information on the topographical map. Finally, the system automatically creates a climbing concept map using how to read and write topographical features generated by the AI. This climbing concept map is created including surrounding information other than the climbing route (mountain huts, etc.).

[0957] "Example 2"

[0958] As another embodiment of the present invention, when a climber inputs climbing route information based on a topographical map into the system, the climber can input the information in a format that is easy to understand intuitively. For example, climbing route information can be input by drawing the route directly on the topographical map. In addition, when the system automatically creates a climbing concept map using how to read and write the topographical features generated by AI, the system displays the climbing concept map in a visually easy-to-understand format that is easy for climbers to understand. For example, topographical features, climbing routes, and surrounding information are expressed using colors, line thicknesses, symbols, etc.

[0959] The process flow of each embodiment will be described below.

[0960] "Example 1"

[0961] Step 1: A climber inputs climbing route information based on a topographical map into the system. This climbing route information includes, for example, the start and end points of the climber's planned route, intermediate points, and points requiring special caution.

[0962] Step 2: The AI ​​in the system generates how to read and write the topographical features based on the climbing route information. This AI generates how to read and write the topographical features by reading the detailed information on the topographical map.

[0963] Step 3: The system automatically creates a mountain climbing concept map using the AI-generated reading and writing of terrain features. This mountain climbing concept map is created including surrounding information (mountain huts, etc.) other than the climbing route.

[0964] "Example 2"

[0965] Step 1: When climbers input climbing route information based on a topographical map into the system, the input should be in a format that is intuitive and easy for climbers to understand. For example, climbing route information can be input by drawing the route directly on a topographical map.

[0966] Step 2: The AI ​​in the system generates how to read and write the topographical features based on the climbing route information. This AI generates how to read and write the topographical features by reading the detailed information on the topographical map.

[0967] Step 3: The system uses the AI-generated methods for reading and writing terrain features to automatically create a mountaineering concept map, which is displayed in a visually easy-to-understand format for climbers to understand. For example, colors, line thicknesses, symbols, etc. are used to represent terrain features, climbing routes, and surrounding information.

[0968] Example 1

[0969] Next, a description will be given of Example 1 of the embodiment 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".

[0970] In conventional mountain climbing planning systems, when climbers input detailed climbing route information based on topographical maps, they had to understand how to read and write topographical features and enter them appropriately. This made it difficult for climbers without specialized knowledge of topographical maps to make accurate climbing plans, and also made it difficult to create comprehensive climbing concept maps that included surrounding information (such as accommodation facilities) other than the climbing route. This led to issues such as a decrease in the accuracy of climbing plans and difficulty in ensuring safety during climbing.

[0971] 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.

[0972] In this invention, the server includes a means for a climber to input climbing route information based on a topographical map, a means for acquiring topographical map data based on the climbing route information, a generation AI model means for analyzing the topographical map data and generating how to read and write topographical features, a means for automatically creating a climbing concept map using the how to read and write topographical features generated by the generation AI model means, and a means for displaying the climbing concept map on a user's terminal. This allows climbers to make accurate climbing plans even without specialized knowledge, and makes it easy to create a comprehensive climbing concept map that includes peripheral information other than the climbing route.

[0973] "Climber" refers to an individual or group engaged in mountaineering activities.

[0974] A "topographic map" is a map showing detailed information about a terrain, including contour lines and topographical features.

[0975] "Mountain climbing route information" refers to information such as the starting point, end point, waypoints, and points requiring caution on the mountain climbing route planned by the climber.

[0976] "Server" refers to a computer system that processes and stores data.

[0977] "Terminal" refers to a device that allows a user to input information and display results, including, for example, a smartphone or a personal computer.

[0978] "Topographical map data" means digital data based on a topographical map and includes detailed information on the topography.

[0979] "Generative AI model" refers to a model that uses artificial intelligence to perform a specific task, in this case, generating ways to read or write topographical features.

[0980] A "mountain climbing concept map" refers to a diagram that visually shows a mountain climbing route and the surrounding information.

[0981] "Accommodation" refers to facilities where climbers can stay overnight. Examples include mountain huts and campsites.

[0982] This invention is a system that allows a climber to input climbing route information based on a topographical map, generates how to read and write topographical features based on that information, and finally automatically creates a climbing concept map. A specific embodiment of this system will be described below.

[0983] First, the user uses the terminal to input climbing route information. The user inputs the start and end points of the planned route, intermediate points, and points requiring special caution. For example, the user opens a smartphone app and inputs into the input form, "From the fifth station of Mt. Fuji to the summit of Mt. Fuji, intermediate points are the sixth, seventh, and eighth stations, and points requiring caution are the steep slope at the seventh station."

[0984] Next, the server receives the climbing route information entered by the user and obtains the topographical map data. Specifically, the server uses the Google Maps API or OpenStreetMap API to obtain topographical map data related to the specified route. For example, the server sends a request to the API to "obtain topographical map data from the fifth station of Mt. Fuji to the summit of Mt. Fuji."

[0985] The generative AI model in the server then analyzes the acquired topographical map data. The generative AI model reads the topographical map data and analyzes the topographical features of each point. For example, the AI ​​identifies the "steep slope at the seventh station" and analyzes its features in detail.

[0986] Next, the generative AI model generates how to read and write the topographical features based on the analysis results. Specifically, the AI ​​generates information such as "The steep slope at the seventh station requires special caution." For example, the AI ​​generates instructions such as "Use specific icons and colors to highlight the steep slope feature."

[0987] The server then automatically creates a mountain climbing concept map using the reading and writing of the terrain features generated by the generative AI model. Specifically, the server combines the topographical map data with the generated information to create a visually easy-to-understand mountain climbing concept map. For example, the server performs a process such as "displaying the route from the fifth station of Mt. Fuji to the summit of Mt. Fuji in red, and displaying the steep slope at the seventh station with a yellow warning icon."

[0988] Finally, the server sends the created mountain climbing concept map to the user's terminal and displays it. Specifically, the mountain climbing concept map is displayed on the user's smartphone or PC. For example, the user checks on the screen of their smartphone "a mountain climbing concept map that visually displays the route from the fifth station of Mt. Fuji to the summit of Mt. Fuji, each waypoint, and points requiring caution."

[0989] Examples of concrete examples and prompts

[0990] Examples

[0991] The user opens the app on their smartphone and enters the following information:

[0992] Starting point: Mount Fuji 5th Station

[0993] End point: The summit of Mt. Fuji

[0994] Waypoints: 6th, 7th, 8th stations

[0995] Areas requiring caution: Steep slope at the seventh station

[0996] The server uses the Google Maps API to obtain topographical map data from the fifth station of Mt. Fuji to the summit. Next, a generative AI model in the server analyzes the topographical map data and identifies the characteristics of the steep slope at the seventh station. The AI ​​generates information such as "particular caution is required on steep slopes," and the server uses this information to create a conceptual map of the climb. Finally, the server sends the conceptual map created by the server to the user's smartphone, where the user can check it on the screen.

[0997] Examples of prompt statements

[0998] "I am planning a climbing route from the 5th station of Mt. Fuji to the summit of Mt. Fuji. I will include the 6th, 7th, and 8th stations as waypoints, and I need to be careful of the steep slope of the 7th station. Please create a conceptual map of the climb based on this information."

[0999] The above is an embodiment of the invention.

[1000] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1001] Step 1:

[1002] A user inputs climbing route information using a terminal.

[1003] Specifically, the user opens the application on their smartphone or PC and enters the start point, end point, intermediate points, and points requiring caution of the planned route into an input form.

[1004] Input: Climbing route information (starting point, ending point, intermediate points, points requiring caution)

[1005] Output: Route information sent to the server

[1006] Step 2:

[1007] The server receives the climbing route information input by the user and obtains the topographical map data.

[1008] Specifically, the server uses the Google Maps API or the OpenStreetMap API to retrieve topographical map data related to the specified route.

[1009] Input: Climbing route information

[1010] Output: Topographical map data

[1011] Step 3:

[1012] A generative AI model on the server analyzes the acquired topographical map data.

[1013] Specifically, the generative AI model reads topographical map data and analyzes the terrain features of each location, identifying features such as steep slopes and cliffs.

[1014] Input: Topographic map data

[1015] Output: Analysis results of terrain features

[1016] Step 4:

[1017] A generative AI model generates readings and writings for topographical features based on the analysis results.

[1018] Specifically, the AI ​​generates information such as "particular caution is required on steep slopes" and generates instructions to use specific icons and colors.

[1019] Input: Topographic feature analysis results

[1020] Output: How to read and write topographical features

[1021] Step 5:

[1022] The server automatically creates a mountain climbing concept map using how to read and write the terrain features generated by the generative AI model.

[1023] Specifically, the server combines the topographical map data with the generated information to create a visually easy-to-understand mountain climbing concept map. For example, the route is displayed in red and steep slopes are displayed with a yellow warning icon.

[1024] Input: Topographic map data, how to read and write topographic features

[1025] Output: Mountain climbing concept diagram

[1026] Step 6:

[1027] The server transmits the created mountain climbing concept map to the user's terminal and displays it.

[1028] Specifically, a conceptual map of the climb is displayed on the user's smartphone or PC. The user can check the conceptual map on the screen, which visually displays the route, each waypoint, and points requiring caution.

[1029] Input: Mountain climbing concept diagram

[1030] Output: A conceptual diagram of the climb displayed on the user's device

[1031] (Application example 1)

[1032] Next, a description will be given of Application Example 1 of Form 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".

[1033] For autonomous vehicles, there is a need to generate optimal driving routes based on topographical maps and road information, and provide route maps that include points requiring special attention and surrounding information. However, current systems have the challenge of being unable to efficiently analyze and visually display this information.

[1034] The identification process by the identification processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for inputting route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the route information, a means for automatically creating a conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and a means for displaying the conceptual map. This makes it possible to generate an optimal driving route for an autonomous vehicle and efficiently provide a route map including points requiring special attention and surrounding information.

[1035] A "topographic map" is a map that contains detailed information about the terrain, visually showing the relief and characteristics of the terrain.

[1036] "Route information" refers to information about a route, such as a starting point, a destination point, and intermediate points.

[1037] An "artificial intelligence means" is a system that uses technologies such as machine learning and deep learning to analyze data and automatically perform specific tasks.

[1038] "Topographical features" refers to the relief and shape of the terrain shown on a topographical map, and the characteristics of a specific point.

[1039] "Reading and writing" refers to ways of understanding and visually representing topographical features.

[1040] A "conceptual map" is a diagram that visually simplifies specific information and includes routes and surrounding information.

[1041] The term "display means" refers to a device or system for visually displaying the generated conceptual diagram or other information.

[1042] "Nearby information" is information about points related to the route, including facilities such as rest areas and gas stations.

[1043] As an embodiment of the present invention, an "automated driving route optimization system" for automated driving vehicles will be described as an example. This system generates an optimal driving route based on topographical maps and road information, and provides a route map that includes points requiring special attention and surrounding information.

[1044] Hardware and Software Used

[1045] Hardware: On-board computer, GPS module, camera, LiDAR sensor for autonomous vehicles

[1046] Software: TensorFlow (training and inference of AI models), OpenStreetMap API (obtaining topographical maps and road information), Python (programming language)

[1047] Data processing and calculation

[1048] Data Entry

[1049] Users input start, destination and intermediate points into the autonomous vehicle's on-board computer, and the system then uses the OpenStreetMap API to retrieve topographical and road information for the specified route.

[1050] Analysis by AI model

[1051] The server uses TensorFlow to analyze the retrieved topographical map and road information and generate readings and writings of topographical features, which identify areas that require special attention (sharp curves, steep gradients, intersections, etc.).

[1052] Route Optimization

[1053] The server calculates the optimal driving route based on how the AI ​​model reads and writes the terrain features, taking into account surrounding information (gas stations, rest areas, etc.).

[1054] Generate route map

[1055] The server generates an optimized route map and displays it on the autonomous vehicle's display, along with visual indications of points of special interest and surrounding information.

[1056] Examples

[1057] Example prompts to be input to the generative AI model

[1058] Starting point: 35.6895, 139.6917

[1059] Destination point: 35.6586, 139.7454

[1060] Waypoint: 35.6733, 139.7100

[1061] Particular caution is required at: sharp curves, steep gradients, intersections

[1062] Based on this prompt, the server retrieves topographical maps and road information and performs analysis using an AI model. Based on the analysis results, it calculates the optimal driving route, generates a route map and displays it on the display of the autonomous vehicle, allowing the user to check a safe and efficient driving route.

[1063] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1064] Step 1:

[1065] The user inputs the starting point, destination point, and intermediate points into the on-board computer of the autonomous vehicle, and the system retrieves these points. The input includes latitude and longitude coordinates. The output is the coordinates that are passed to the next step.

[1066] Step 2:

[1067] The server uses the OpenStreetMap API to get the topographical map and road information for the specified route. As input, the coordinate information obtained in step 1 is used. The server sends an API request and receives data including the topographical map and road information. As output, the topographical map and road information are passed on to the next step.

[1068] Step 3:

[1069] The server uses TensorFlow to analyze the retrieved topographical map and road information and generate readings and writings of the topographical features. As input, the topographical map and road information retrieved in step 2 are used. Using an AI model, the server analyzes the topographical features and identifies points that require special attention (sharp curves, steep gradients, intersections, etc.). As output, the readings and writings of the topographical features are passed on to the next step.

[1070] Step 4:

[1071] The server calculates the optimal driving route based on the reading and writing of the terrain features generated by the AI ​​model. As input, the reading and writing of the terrain features generated in step 3 is used. The server also takes into account surrounding information (gas stations, rest areas, etc.) to calculate the optimal driving route. As output, the optimized driving route is passed to the next step.

[1072] Step 5:

[1073] The server generates an optimized route map and displays it on the autonomous vehicle's display. As input, the optimal driving route calculated in step 4 is used. The server generates the route map and also visually displays points of special interest and surrounding information. As output, the route map is displayed on the display for the user to review.

[1074] Through this series of processes, the user can check a safe and efficient driving route.

[1075] Example 2

[1076] Next, a second embodiment of the second form will be described. 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".

[1077] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on a topographical map, and the generated mountain climbing concept map was visually difficult to understand. Furthermore, it was difficult to automatically create a detailed mountain climbing concept map that included surrounding information (such as accommodations) other than the mountain climbing route.

[1078] 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.

[1079] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, a means for transmitting the mountain climbing route information as digital data, a means for using a generative AI model for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and writings of the topographical features generated by the generative AI model, and a means for displaying the mountain climbing conceptual map in a visually easy-to-understand format. This allows the user to intuitively input mountain climbing route information, and makes it possible to automatically create a visually easy-to-understand mountain climbing conceptual map. It is also possible to provide a detailed mountain climbing conceptual map that includes surrounding information other than the mountain climbing route.

[1080] A "topographic map" is a map that visually represents detailed information about a terrain.

[1081] "Mountain climbing route information" is information about the route of a mountain climbing planned by a mountain climber.

[1082] The "means for inputting" is a device or software that provides an interface for a user to draw a climbing route on a topographical map.

[1083] The "means for transmitting as digital data" refers to a communication means for transmitting the climbing route information input by the user to the server in digital form.

[1084] A "generative AI model" is an artificial intelligence model that analyzes and generates how to read and write topographical features.

[1085] A "climbing concept map" is a visual representation of a climbing route and the topographical features of its surroundings.

[1086] "Means for automatic creation" refers to a device or software for automatically generating a mountain climbing concept map using a generative AI model.

[1087] The "means for displaying in a visually easy-to-understand format" refers to a device or software for displaying the generated mountain climbing concept map in a format that is easy for the user to understand.

[1088] "Local information" refers to information about accommodation and other important points related to the climbing route.

[1089] This invention is a system that allows climbers to intuitively input climbing route information based on a topographical map, analyzes topographical features using a generative AI model, and automatically creates a visually easy-to-understand climbing concept map. This system works in cooperation with the user, the terminal, and the server.

[1090] First, the user draws a climbing route on the topographical map displayed on the terminal screen using a mouse or a touch pen. The user can intuitively input route information by drawing a line on the topographical map or clicking points. For example, the user specifies a climbing route by dragging the mouse from the starting point to the goal point to draw a line.

[1091] Next, the terminal transmits the climbing route information drawn by the user to the server as digital data. This data includes the route coordinate information and drawing format (line color, thickness, etc.). For example, it includes the coordinates of the start and end points of the line, and information on the line color and thickness.

[1092] The server receives the climbing route information sent from the terminal and uses a generative AI model to analyze how to read and write the topographical features. The server automatically generates a climbing concept map based on the analysis results. The generated concept map displays the climbing route in a visually easy-to-understand format. Specifically, the topographical features, climbing route, and surrounding information are expressed using colors, line thickness, symbols, etc. For example, the climbing route is displayed with a thick red line, and the surrounding topographical features are expressed with blue dotted lines and green symbols.

[1093] The server then transmits the generated mountain climbing concept map to the terminal. The terminal receives this data and displays it to the user. The user can check the mountain climbing concept map displayed on the terminal screen and confirm the mountain climbing route and the characteristics of the terrain displayed in a visually easy-to-understand format. This allows the user to obtain information that is useful when making mountain climbing plans.

[1094] As a concrete example, consider the case where a user draws a mountain climbing route with a red line on a topographical map. When the user drags the mouse to draw a line from the starting point to the goal, the device sends that information to the server as digital data. The server uses a generative AI model to analyze the characteristics of the terrain, and generates a mountain climbing concept map that displays the climbing route with a thick red line and the surrounding topographical features with blue dotted lines and green symbols. The server sends this concept map to the device, where the user can view it on the device screen.

[1095] An example of a prompt is as follows:

[1096] "Please draw your climbing route on the topographical map in red. The system will create a climbing concept map based on that information and display your climbing route in thick red."

[1097] "Click multiple points on the topographical map to specify a climbing route. The system will create a climbing concept map based on that information and display the climbing route with a yellow dashed line."

[1098] In this way, the user can intuitively input mountain climbing route information and obtain a visually easy-to-understand mountain climbing concept map, which improves convenience when making mountain climbing plans.

[1099] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1100] Step 1:

[1101] The user inputs a climbing route.

[1102] The user draws a climbing route on the topographical map displayed on the terminal screen using a mouse or a touch pen. Specifically, the user draws a line by dragging the mouse from the starting point to the goal point. This operation inputs the coordinate information of the climbing route and the drawing format (such as the color and thickness of the line).

[1103] Step 2:

[1104] The terminal transmits the input data to the server.

[1105] The terminal sends the climbing route information drawn by the user to the server as digital data. The input includes the coordinates of the start and end points of the line, and information on the color and thickness of the line. The terminal assembles this data into packets and sends them to the server.

[1106] Step 3:

[1107] The server receives and analyzes the data.

[1108] The server receives the climbing route information sent from the device. The input includes the climbing route's coordinate information and drawing format. The server uses a generative AI model to analyze how to read and write the terrain features. Specifically, it analyzes the elevation and slope of the terrain through which the route passes, and extracts detailed information about the climbing route.

[1109] Step 4:

[1110] The server generates a conceptual map of the mountain climb.

[1111] The server automatically generates a mountain climbing concept map based on the analysis results. The input includes the analyzed terrain feature information. The server uses the generative AI model to display the mountain climbing route in a visually easy-to-understand format. Specifically, the mountain climbing route is displayed as a thick red line, and the surrounding terrain features are represented by blue dotted lines and green symbols.

[1112] Step 5:

[1113] The server transmits the generated mountain climbing concept map to the terminal.

[1114] The server transmits the generated mountain climbing concept map to the terminal. The input includes the data of the generated mountain climbing concept map. The server assembles this data into packets and transmits them to the terminal.

[1115] Step 6:

[1116] The user checks the mountain climbing concept map.

[1117] The user checks the mountain climbing concept map displayed on the screen of the terminal. The input includes the data of the mountain climbing concept map sent from the server. The user checks the mountain climbing route and the topographical features displayed in a visually easy-to-understand format and makes a mountain climbing plan. Specifically, the user makes a mountain climbing plan by looking at the mountain climbing route and the surrounding topographical features.

[1118] (Application example 2)

[1119] Next, a description will be given of Application Example 2 of Form 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".

[1120] In conventional climbing route information input systems, it was difficult for users to intuitively input climbing route information based on a topographical map, and the generated climbing concept map was visually difficult to understand. Furthermore, it was difficult to automatically create a detailed climbing concept map that included surrounding information other than the climbing route. This made it difficult for climbers to plan climbing routes safely and efficiently.

[1121] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1122] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an AI means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the AI ​​means, a means for inputting route information by drawing a route on a map, a means for analyzing the route information and converting it into a visually easy-to-understand format, and a means for displaying the converted route information. This makes it possible for a user to intuitively input mountain climbing route information and automatically generate a visually easy-to-understand mountain climbing concept map.

[1123] A "topographic map" is a map that shows detailed information about the terrain and is used to plan climbing routes and understand the characteristics of the terrain.

[1124] "Mountain climbing route information" refers to information about a mountain climbing route planned by a climber, including the route and points of the route depicted on a topographical map.

[1125] "AI means" means means for analyzing data and automatically performing specific tasks using artificial intelligence technology.

[1126] A "mountain climbing concept map" is a diagram that visually represents a mountain climbing route and surrounding information in an easy-to-understand manner, making it easier for climbers to understand the route.

[1127] The "means for inputting route information" refers to a means for a user to input climbing route information into the system by drawing the route directly on a map.

[1128] A "visually easy-to-understand format" is a format that expresses information using colors, line thicknesses, symbols, etc., making it easy for users to understand intuitively.

[1129] The "means for analyzing route information" refers to a means for analyzing input route information and converting it into a visually easy-to-understand format.

[1130] The "means for displaying route information" refers to a means for displaying the analyzed route information to the user in a visually easy-to-understand format.

[1131] A system for implementing this invention includes means for inputting mountain climbing route information based on a topographical map, AI means for generating how to read and write topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the how to read and write the topographical features generated by the AI ​​means, means for inputting route information by drawing a route on a map, means for analyzing the route information and converting it into a visually easy-to-understand format, and means for displaying the converted route information.

[1132] Program processing explanation

[1133] The server reads the topographical map data, and the user inputs the climbing route information by drawing the route on the map. Specifically, the user draws the route on the map using a touch screen or mouse input on a device such as a smartphone or a head-mounted display. This route information is sent to the server, and the AI ​​means analyzes it.

[1134] The AI ​​tool analyzes the input route information and generates readings and writings of topographical features. It uses Python and its libraries (matplotlib, numpy, sklearn, etc.). The analyzed data is converted into a visually easy-to-understand format. For example, the route is represented using colors, line thickness, symbols, etc.

[1135] The converted route information is sent from the server to the user's device and displayed in a visually easy-to-understand format, making it easier for users to intuitively understand the climbing route information.

[1136] Examples

[1137] For example, when a user uses a smartphone to draw a mountain climbing route on a map, the user draws the route on the map with his / her finger. The server receives this information, and the AI ​​means analyzes it to generate a visually easy-to-understand mountain climbing concept diagram. This mountain climbing concept diagram is expressed using colors, line thickness, symbols, etc., and is displayed on the smartphone screen.

[1138] Examples of prompt statements

[1139] Below are examples of prompts to be input to the generative AI model.

[1140] Please create an application where the user draws a route on a map, and the route is analyzed by AI and displayed in a visually easy-to-understand format. Please provide a Python program that includes the following steps: loading map data, inputting route information, analyzing the route by AI, and generating a route map.

[1141] It is expected that by using this prompt sentence, the generative AI model will generate an appropriate program.

[1142] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1143] Step 1:

[1144] The user loads map data using a smartphone or head-mounted display.

[1145] Input: Map data file (e.g. topographical map image file)

[1146] Output: Map data is displayed.

[1147] Specific operation: The user launches the application on the device, selects and loads a map data file, and the map data is displayed on the device screen.

[1148] Step 2:

[1149] The user draws a route on a map.

[1150] Input: Route drawing information from the user's touch screen or mouse input

[1151] Output: Rendered route information

[1152] How it works: A user draws a climbing route on a map using a finger or a stylus. The route information is stored on the device and sent to the server.

[1153] Step 3:

[1154] The server analyzes the received route information.

[1155] Input:Drawn route information

[1156] Output: Parsed route data

[1157] Specific operation: The server analyzes the received route information and generates reading and writing instructions for terrain features. It analyzes the data using Python libraries (numpy, sklearn, etc.) and extracts route features.

[1158] Step 4:

[1159] The server converts the parsed route data into a visually understandable format.

[1160] Input: Parsed route data

[1161] Output: Route data in a visually friendly format

[1162] Specific operation: The server converts the analyzed route data into a visually easy-to-understand format using colors, line thickness, symbols, etc. It uses matplotlib to draw the route and arrange it into a visually easy-to-understand format.

[1163] Step 5:

[1164] The server sends the converted route data to the user's device.

[1165] Input: Route data in a visually friendly format

[1166] Output: The route map as it appears on the user's device.

[1167] Specific operation: The server sends the converted route data to the user's device, which then displays the received data and provides the user with a visually easy-to-understand route map.

[1168] Step 6:

[1169] Users can view easy-to-understand route maps.

[1170] Input: A route map in a visually friendly format

[1171] Output: User understanding and confirmation

[1172] Specific operation: The user checks the route map displayed on the device screen and plans a mountain climbing route. Visual information using colors, line thickness, symbols, etc. allows the user to intuitively understand the route.

[1173] In addition, 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.

[1174] "Example 1"

[1175] As one embodiment of the present invention, a system is provided that combines an emotion engine that recognizes the emotions of a user. This system includes an AI means that receives mountain climbing route information based on a topographical map and generates how to read and write topographical features based on the mountain climbing route information, and a means that automatically creates a mountain climbing concept map using the how to read and write the topographical features generated by the AI ​​means. Furthermore, an emotion engine that recognizes the emotions of a user is also included. This emotion engine recognizes the emotional state of a user, for example, from the user's facial expression, tone of voice, text input, etc. Then, the reading and writing of the topographical features and the display method of the mountain climbing concept map are adjusted according to the emotional state. For example, if it is recognized that the user is nervous, more detailed topographical information is provided. Also, if it is recognized that the user is relaxed, only the minimum necessary information is provided, making it possible to provide optimal information according to the user's emotional state.

[1176] "Example 2"

[1177] As another embodiment of the present invention, a system is provided in which an emotion engine adjusts the display method of a mountain climbing concept map according to the emotional state of a user. As in the above-mentioned embodiment, this system includes an AI means for inputting mountain climbing route information based on a topographical map and generating a reading and writing method of topographical features based on the mountain climbing route information, and a means for automatically creating a mountain climbing concept map using the reading and writing method of the topographical features generated by the AI ​​means. Furthermore, an emotion engine for recognizing the emotion of a user is also included. This emotion engine adjusts the display method of the mountain climbing concept map according to the emotional state of the user. For example, if it is recognized that the user is feeling anxious, more detailed topographical information and safety information are displayed with emphasis. Also, if it is recognized that the user is excited, an optimal display method according to the emotional state of the user is provided, such as increasing the options of mountain climbing routes.

[1178] The process flow of each embodiment will be described below.

[1179] "Example 1"

[1180] Step 1: Receive climbing route information based on a topographical map from the user as input.

[1181] Step 2: Using AI means, generate readings and writings of terrain features based on the input climbing route information.

[1182] Step 3: Automatically create a mountaineering concept map using the generated reading and writing methods for the terrain features.

[1183] Step 4: Use the emotion engine to recognize the user's emotional state from their facial expressions, tone of voice, text input, etc.

[1184] Step 5: Adjust the way terrain features are read and written and the way mountain climbing concept maps are displayed according to the recognized emotional state of the user.

[1185] "Example 2"

[1186] Step 1: Receive climbing route information based on a topographical map from the user as input.

[1187] Step 2: Using AI means, generate readings and writings of terrain features based on the input climbing route information.

[1188] Step 3: Automatically create a mountaineering concept map using the generated reading and writing methods for the terrain features.

[1189] Step 4: Recognize the user's emotional state using the emotion engine.

[1190] Step 5: Adjust the way the mountain climbing concept diagram is displayed depending on the recognized emotional state of the user.

[1191] Example 1

[1192] Next, a description will be given of Example 1 of the embodiment 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".

[1193] In conventional mountain climbing support systems, the input of mountain climbing route information and the analysis of terrain characteristics are often done manually, which is inefficient. In addition, since information is not provided according to the user's emotional state, it is difficult to provide information optimal for the user's situation. This leads to the issue that safety and comfort during mountain climbing are not sufficiently ensured.

[1194] 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.

[1195] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the artificial intelligence means, an emotion recognition means for recognizing the emotion of the user, and a means for adjusting the information provided in accordance with the emotional state of the user recognized by the emotion recognition means. This makes it possible to automatically create a mountain climbing concept map based on the user's input, and to provide optimal information in accordance with the emotional state of the user.

[1196] A "topographic map" is a map that shows detailed information about the terrain and is used to plan and analyze climbing routes.

[1197] "Mountain climbing route information" is information about the route planned by the climber, such as the starting point and end point of the climb, intermediate points, and points requiring special caution.

[1198] "Artificial intelligence means" means technology that includes algorithms or models to analyse input data and perform specific tasks automatically.

[1199] "How to read and write topographic features" refers to a method of analyzing information obtained from topographic maps and expressing it in a form that is easy for climbers to understand.

[1200] A "climbing concept map" is a diagram that visually shows a climbing route and the surrounding information, making it easier for climbers to understand the route.

[1201] "Emotion recognition means" is a technology that analyzes a user's emotional state from facial expressions, tone of voice, text input, etc.

[1202] "Means for adjusting information provision" refers to technology that changes the content and format of the information provided depending on the user's emotional state.

[1203] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1204] The present invention is a system in which a climber inputs climbing route information based on a topographical map, and an artificial intelligence generates how to read and write the topographical features based on that information, and finally creates a climbing concept map. In addition, by combining an emotion recognition means that recognizes the user's emotions, information is provided according to the user's emotional state.

[1205] System Configuration

[1206] 1. Enter climbing route information

[1207] The user inputs mountain climbing route information, specifically, the start and end points of the mountain climbing, intermediate points, points requiring special attention, etc.

[1208] Hardware used: PC, smartphone, tablet, etc.

[1209] Software used: Web browser, dedicated application

[1210] 2. Generating readings and writings of topographical features

[1211] The server receives the input climbing route information and generates readings and writings of topographical features using an AI model that analyzes detailed information on topographical maps.

[1212] Hardware used: Server (high performance CPU, GPU)

[1213] Software used: Artificial intelligence models (e.g. TensorFlow, PyTorch)

[1214] 3. Creating a mountain climbing concept map

[1215] The server automatically creates a mountain climbing concept map using the reading and writing of the terrain features generated by the artificial intelligence. This mountain climbing concept map includes surrounding information (mountain huts, etc.) other than the climbing route.

[1216] Hardware used: Server

[1217] Software used: Mapping software (e.g. QGIS)

[1218] 4. Emotion recognition using emotion recognition means

[1219] The terminal recognizes the user's emotional state from the user's facial expressions, tone of voice, text input, etc., which are then analyzed by the emotion recognition means.

[1220] Hardware used: PC, smartphone, tablet (camera, microphone)

[1221] Software used: Emotion recognition software (e.g. Microsoft Azure Emotion API)

[1222] 5. Coordination of information provision

[1223] The server adjusts how to read and write the terrain features and how to display the mountain climbing concept map according to the user's emotional state obtained from the emotion recognition means. For example, if the user is nervous, detailed terrain information is provided, and if the user is relaxed, only the minimum necessary information is provided.

[1224] Hardware used: Server

[1225] Software used: Customized information providing algorithms

[1226] Examples

[1227] The user opens a dedicated smartphone application and inputs climbing route information. For example, the user inputs "route from the fifth station to the summit of Mt. Fuji, stopping at mountain huts along the way."

[1228] The server receives this information and uses artificial intelligence models to generate readings and writings of the topographical features.

[1229] The server creates a mountain climbing concept map based on the generated information and displays it on the smartphone.

[1230] The terminal captures the user's facial expression with a camera, and the emotion recognition means recognizes that the user is nervous.

[1231] The server provides a conceptual map of a mountain climb including detailed topographical information.

[1232] Examples of prompt statements

[1233] "Please enter the route from the fifth station to the summit of Mt. Fuji. Please also enter any mountain huts you may need to stop at along the way and any points requiring caution."

[1234] In this way, the system automatically creates a mountain climbing concept map based on the user's input, and can provide optimal information according to the user's emotional state.

[1235] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1236] Step 1:

[1237] The user inputs the climbing route information. Specifically, the user opens a dedicated application on his / her smartphone and enters "Route from the fifth station of Mt. Fuji to the summit, stopping at mountain huts on the way" into the input form.

[1238] Input: Climbing route information such as the start and end points of the climb, intermediate points, and points requiring special attention

[1239] Output: The entered climbing route information is sent to the server.

[1240] Step 2:

[1241] The server receives the climbing route information sent by the user, then uses an artificial intelligence model to generate readings and writings of the terrain features.

[1242] Input: Climbing route information sent by the user

[1243] Data processing: The server analyzes the received data and uses artificial intelligence models (e.g. TensorFlow) to analyze detailed information on the topographical maps.

[1244] Output: How to read and write the topographical features is generated

[1245] Specific operation: The server analyzes the received data, analyzes the detailed information of the topographical map using TensorFlow, and generates how to read and write the topographical features.

[1246] Step 3:

[1247] The server automatically creates a mountain climbing concept map based on how to read and write the terrain features generated by the artificial intelligence. This mountain climbing concept map includes surrounding information (mountain huts, etc.) other than the climbing route.

[1248] Input: How to read and write terrain features generated by artificial intelligence

[1249] Data processing: The server uses QGIS to create a conceptual map of the climbing route and surrounding information.

[1250] Output: A mountain climbing concept map is generated and sent to the user's smartphone.

[1251] Specific operation: The server creates a mountain climbing concept map using QGIS and sends it to the user's smartphone.

[1252] Step 4:

[1253] The terminal recognizes the user's emotional state from the user's facial expressions, tone of voice, text input, etc., which are then analyzed by the emotion recognition means.

[1254] Input: User facial expressions, tone of voice, text input, etc.

[1255] Data processing: The device captures data using the camera and microphone and analyzes it using emotion recognition software (e.g. Microsoft Azure Emotion API).

[1256] Output: The user's emotional state is recognized.

[1257] How it works: The smartphone camera captures the user's facial expressions and analyzes their emotional state using the Microsoft Azure Emotion API.

[1258] Step 5:

[1259] The server adjusts how to read and write the terrain features and how to display the mountain climbing concept map according to the user's emotional state obtained from the emotion recognition means. For example, if the user is nervous, detailed terrain information is provided, and if the user is relaxed, only the minimum necessary information is provided.

[1260] Input: The user's emotional state obtained from an emotion recognition means

[1261] Data processing: The server receives the analysis results of the emotion recognition method and adjusts the display method using an information provision algorithm.

[1262] Output: The adjusted information is displayed on the user's smartphone.

[1263] Specific operation: The server receives the analysis results of the emotion recognition means, and if it determines that the user is nervous, it regenerates a mountain climbing concept map including detailed terrain information and sends it to the smartphone.

[1264] (Application example 1)

[1265] Next, a description will be given of Application Example 1 of Form 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".

[1266] Conventional mountain climbing route guidance systems provide uniform information without considering the user's emotional state, which means that they cannot provide appropriate information when the user is tense or relaxed. In addition, they lack the functionality to automatically generate how to read and write detailed topographical features based on topographical maps, making it difficult to provide the information users need quickly and accurately.

[1267] 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.

[1268] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an AI means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the AI ​​means, a means including an emotion engine for recognizing the user's emotions, and a means for adjusting the information provided according to the user's emotional state recognized by the emotion engine. This makes it possible to provide optimal information according to the user's emotional state.

[1269] A "topographic map" is a map that shows detailed information about a terrain, visually representing climbing routes and terrain features.

[1270] "Mountain climbing route information" includes information on the start point, end point, waypoints, points requiring special caution, and the like of the route the climber plans to take.

[1271] "AI Means" means a means for performing a specific task using artificial intelligence, and in this case refers to the ability to generate readings and / or writings of topographical features.

[1272] "Reading and writing topographic features" refers to the method of interpreting detailed information about a terrain based on a topographic map and expressing it in visual or textual form.

[1273] A "climbing concept map" is a visual representation of a climbing route and its surrounding information, intended to make it easier for climbers to understand the route.

[1274] An "emotion engine" is a system for recognizing a user's emotional state from their facial expressions, tone of voice, text input, etc.

[1275] The "means for adjusting the information provided" refers to a means for changing the level of detail and content of the information provided in accordance with the user's emotional state.

[1276] A system for implementing this invention includes means for inputting mountain climbing route information based on a topographical map, AI means for generating how to read and write topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the how to read and write the topographical features generated by the AI ​​means, means including an emotion engine for recognizing a user's emotions, and means for adjusting the provision of information in accordance with the user's emotional state recognized by the emotion engine.

[1277] Program processing explanation

[1278] Hardware and software used

[1279] Hardware: Smartphone (camera, microphone)

[1280] Software: Python, OpenCV, EmotionRecognizer library, RoutePlanner library, MapGenerator library

[1281] Processing flow

[1282] 1. User input: The user inputs the starting point, destination point, and intermediate points. This provides the climbing route information to the system.

[1283] 2. Route Planning: The server uses the RoutePlanner library to generate readings and writings of terrain features based on the input route information.

[1284] 3. Map generation: The server uses the MapGenerator library to create a driving concept map, which includes surrounding information (e.g. mountain huts) in addition to the climbing route.

[1285] 4. Emotion recognition: The device uses the EmotionRecognizer library to recognize the user's emotions based on data obtained from the camera and microphone.

[1286] 5. Adjustment of information provision: The server adjusts the level of detail of the information provided depending on the recognized emotional state. For example, if the user is nervous, detailed topographical information is provided, but if the user is relaxed, only the minimum necessary information is provided.

[1287] 6. Display: The device displays the adjusted information on the smartphone screen.

[1288] Examples

[1289] User input: Starting point "Tokyo Station", destination point "Mt. Fuji", intermediate point "Yokohama Station"

[1290] Emotion recognition: If the user is perceived as nervous, detailed terrain information (sharp turns, slope, etc.) is provided.

[1291] Display: Along with a detailed driving concept map, it also displays information on nearby gas stations and rest areas.

[1292] Examples of prompt statements

[1293] If a user inputs the starting point "Tokyo Station", the destination "Mt. Fuji", and the waypoint "Yokohama Station", and the emotion recognition engine recognizes the user's emotion as "nervous", please generate a program that provides detailed topographical and surrounding information.

[1294] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1295] Step 1:

[1296] The user inputs the starting point, destination, and intermediate points. Through the smartphone application, the user inputs the starting point "Tokyo Station," the destination point "Mt. Fuji," and the intermediate point "Yokohama Station." This provides the climbing route information to the system. The input data is sent to the server and proceeds to the next processing step.

[1297] Step 2:

[1298] The server uses the RoutePlanner library to generate readings and writings of terrain features based on the input route information. The server analyzes the received information of the starting point, destination point, and intermediate points, and retrieves the corresponding terrain information from the topographical map database. Based on the retrieved terrain information, the AI ​​model generates readings and writings of terrain features. The generated data is used in the next step.

[1299] Step 3:

[1300] The server creates a driving concept map using the MapGenerator library. The server generates a driving concept map including the climbing route and its surrounding information (e.g. mountain huts) based on the reading and writing of the topographical features generated in step 2. The generated driving concept map is used in the next step.

[1301] Step 4:

[1302] The device uses the EmotionRecognizer library to recognize the user's emotions based on data acquired from the camera and microphone. The device analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state. The determined emotional state is used in the next step.

[1303] Step 5:

[1304] The server adjusts the level of detail of the information to be provided according to the recognized emotional state. The server determines the level of detail of the information to be provided based on the emotional state determined in step 4. For example, if the user is nervous, detailed topographical information is provided, and if the user is relaxed, only the minimum necessary information is provided. The adjusted information is used in the next step.

[1305] Step 6:

[1306] The terminal displays the adjusted information on the smartphone screen. The terminal receives the adjusted driving concept map and surrounding information sent from the server and displays them on the smartphone screen. The user can check the mountain climbing route safely and efficiently based on the displayed information.

[1307] Example 2

[1308] Next, a second embodiment of the second form will be described. 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".

[1309] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on a topographical map, and the generated mountain climbing concept map was not adjusted according to the user's emotional state, making it difficult to provide information that is easy for users to understand. Furthermore, it was also insufficient to create a detailed mountain climbing concept map that included surrounding information other than the mountain climbing route (such as evacuation sites).

[1310] 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.

[1311] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and an emotion recognition means for recognizing the emotional state of the user and adjusting the display method of the mountain climbing conceptual map according to the emotional state. This allows the user to intuitively input mountain climbing route information, and the generated mountain climbing conceptual map is adjusted according to the emotional state of the user, making it possible to provide information that is easy for the user to understand. It also makes it possible to create a detailed mountain climbing conceptual map that includes surrounding information other than the mountain climbing route.

[1312] A "topographic map" is a map that shows the terrain and the locations of landmarks, and is used for planning mountain climbing routes and navigation.

[1313] "Mountain climbing route information" refers to information about the mountain climbing route planned by a climber, including the route depicted on a topographical map and its details.

[1314] "Artificial intelligence means" refers to technology that uses machine learning or data analysis to automatically perform certain tasks, and is used in the present invention to generate readings and writings of topographical features.

[1315] "Topographical characteristics" refers to the characteristics of the terrain and features shown on a topographical map, and are used to evaluate the difficulty of climbing routes and dangerous areas.

[1316] A "climbing concept map" is a diagram that visually shows climbing routes and surrounding information in an easy-to-understand manner, and is created to make it easier for climbers to understand the route.

[1317] The "emotion recognition means" is a technology for analyzing and recognizing the user's emotional state, and in the present invention is used to adjust the display method of the mountain climbing concept map according to the user's emotional state.

[1318] "Area information" refers to information other than the climbing route, including information important to climbers, such as evacuation sites and water sources.

[1319] This invention is a system in which a climber intuitively inputs climbing route information based on a topographical map, and the generated climbing concept map is adjusted according to the user's emotional state. A specific embodiment of this system will be described below.

[1320] First, the user displays a topographical map using a terminal (PC or tablet). The user then draws a climbing route on the topographical map using a mouse or touch screen. For example, the user draws a climbing route by drawing a red line on the topographical map. This information is sent from the terminal to the server as digital data.

[1321] Next, the server analyzes the received climbing route information. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate readings and writings for terrain features. Specifically, the server analyzes the elevation data and terrain relief of the climbing route to evaluate the difficulty and dangerous areas of the climbing route.

[1322] The server then creates a mountain climbing concept map based on how to read and write the generated topographical features. The mountain climbing concept map is displayed in a visually easy-to-understand format using colors, line thickness, symbols, etc. For example, the mountain climbing route is displayed with a thick red line, and dangerous areas are indicated with yellow triangles. Nearby evacuation sites and water sources are also displayed with blue icons.

[1323] In addition, the server recognizes the user's emotional state using emotion recognition means (e.g., IBM Watson or Microsoft Azure Cognitive Services). If the user feels anxious, the server highlights and displays detailed terrain information and safety information. If the user feels excited, the server provides the optimal display method according to the user's emotional state, such as increasing the options for mountain climbing routes.

[1324] As a concrete example, the following prompt sentence is input into the generative AI model.

[1325] Example prompt:

[1326] Based on the climbing route information drawn by the user on the topographical map, use an AI model to generate reading and writing of the terrain features, and create a visually easy-to-understand climbing concept map. Also, use an emotion engine to recognize the user's emotional state and adjust the display method. For example, if the user is feeling anxious, highlight the detailed terrain information, and if the user is excited, increase the options of climbing routes.

[1327] In this way, a system is realized in which the server, terminal, and user work together to input mountain climbing route information, create a mountain climbing concept map, and adjust the display according to emotions.

[1328] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1329] Step 1:

[1330] A user uses a terminal to display a topographical map. The user draws a climbing route on the topographical map using a mouse or a touch screen. The climbing route information drawn by the user is input. The terminal transmits this information to a server as digital data. In concrete terms, the user draws a climbing route by drawing a red line on the topographical map.

[1331] Step 2:

[1332] The server receives climbing route information sent from the terminal. As input, there is digitized climbing route information. The server analyzes this information and generates how to read and write the topographical features using a generative AI model (e.g., TensorFlow or PyTorch). Specifically, the server analyzes the elevation data and topographical relief of the climbing route, and evaluates the difficulty and dangerous areas of the climbing route. As output, how to read and write the topographical features is generated.

[1333] Step 3:

[1334] The server creates a mountain climbing concept map based on how to read and write the generated topographical features. The input is how to read and write the topographical features. The server displays the mountain climbing concept map in a visually easy-to-understand format using colors, line thickness, symbols, etc. In concrete terms, the server displays the mountain climbing route with a thick red line and indicates dangerous areas with yellow triangles. It also displays nearby evacuation sites and water sources with blue icons. The output is a mountain climbing concept map.

[1335] Step 4:

[1336] The server recognizes the user's emotional state using the emotion recognition means. As an input, there is data on the user's emotional state. The server adjusts the display method of the mountain climbing concept map according to the user's emotional state. As a specific operation, if the user feels anxious, the server displays detailed topographical information and safety information with emphasis. If the user is excited, the server increases the options for mountain climbing routes. As an output, an optimal display method according to the user's emotional state is provided.

[1337] (Application example 2)

[1338] Next, a description will be given of Application Example 2 of Form 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".

[1339] Conventional mountain climbing navigation systems have the problem that it is difficult for climbers to intuitively input climbing route information based on topographical maps, and information is not provided according to the user's emotional state, so the safety and comfort of climbers is not sufficiently ensured. In addition, there is also the problem that automatic driving vehicles do not provide appropriate navigation to safely transport climbers to their destinations.

[1340] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1341] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, an AI means for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the AI ​​means, an emotion engine for recognizing the user's emotional state, a means for adjusting the display method of the mountain climbing concept map according to the emotional state recognized by the emotion engine, and a means for being installed in an autonomous vehicle. This allows mountain climbers to intuitively input mountain climbing route information, and makes it possible to provide optimal navigation information according to the user's emotional state.

[1342] A "topographic map" is a map that visually represents detailed information about a terrain.

[1343] "Mountain climbing route information" is information about the route that a climber plans to take when climbing a mountain.

[1344] "AI means" means technical means for performing certain tasks using artificial intelligence.

[1345] "Topographic features" refers to topographical characteristics such as mountains, valleys, and rivers on a topographical map.

[1346] A "mountain climbing concept map" is a diagram that visually represents mountain climbing routes and surrounding information.

[1347] An "emotion engine" is a technology for recognizing a user's emotional state and adjusting the system's behavior based on that.

[1348] An "autonomous vehicle" is a vehicle that can drive autonomously using artificial intelligence and sensor technology.

[1349] A "display method" is the means or format by which information is visually presented to a user.

[1350] The following system configuration will be described as an embodiment of the present invention.

[1351] System Configuration

[1352] Hardware

[1353] Autonomous vehicle: A vehicle that can drive autonomously using artificial intelligence and sensor technology.

[1354] Cameras and sensors: devices to recognise the user's emotional state.

[1355] software

[1356] EmotionEngine: Technology for recognizing a user's emotional state and adjusting system behavior based on it.

[1357] AIGeography: Artificial intelligence techniques for generating terrain features and creating mountaineering concept maps.

[1358] Program processing explanation

[1359] Input of climbing route information based on topographical maps

[1360] The server provides a means for inputting climbing route information based on a topographical map. A user can input climbing route information by drawing the route directly on the topographical map. This information is sent to the server and used for the next process.

[1361] Generate terrain features

[1362] The server uses AIGeography to generate readings and writings of terrain features based on the input climbing route information. AIGeography reads detailed information of the topographical map and generates terrain features. The generated terrain features are used to create a climbing concept map.

[1363] Creating a mountain climbing concept map

[1364] The server automatically creates a mountain climbing concept map using the reading and writing of the terrain features generated by AIGeography. This mountain climbing concept map is displayed in a visually easy-to-understand format, including climbing routes and surrounding information (mountain huts, etc.).

[1365] Adjusting display method using emotion engine

[1366] The server recognizes the user's emotional state using the EmotionEngine. The EmotionEngine analyzes data obtained from cameras and sensors to determine the user's emotional state. For example, if the user feels anxious, the server will highlight safety information on the mountain climbing concept map. In addition, if the user feels excited, the server will provide the optimal display method according to the user's emotional state, such as increasing the number of mountain climbing route options.

[1367] Examples

[1368] For example, consider a climber getting into an autonomous vehicle and inputting a route to a destination. The user draws the route on a topographical map and sends it to the server. The server uses AI Geography to generate topographical features and create a mountain climbing concept map. Next, Emotion Engine recognizes the user's emotional state and adjusts the display method. If the user feels anxious, safety information is emphasized, and if the user is excited, the options for mountain climbing routes are increased.

[1369] Examples of prompt statements

[1370] "Design a mountain climbing navigation system that highlights safety information when the user feels anxious. Input mountain climbing route information based on a topographical map, and create a mountain climbing concept map using AI-generated topographical features. Use an emotion engine to adjust the navigation information according to the user's emotional state."

[1371] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1372] Step 1:

[1373] The user draws a climbing route on a topographical map.

[1374] Input: Topographical map, user-drawn climbing route information

[1375] Output: Climbing route information

[1376] Specific operation: A user draws a climbing route on a topographical map using a device such as a smartphone or tablet. This information is sent from the device to the server.

[1377] Step 2:

[1378] The server receives the climbing route information and generates topographical features using AIGenography.

[1379] Input: Climbing route information

[1380] Output: How to read and write topographical features

[1381] How it works: The server inputs the received climbing route information into AIGeography, and analyzes the detailed information of the topographical map to generate topographical features, including topographical characteristics such as mountains, valleys, and rivers.

[1382] Step 3:

[1383] The server creates a mountain climbing concept map using the generated topographical features.

[1384] Input: How to read and write topographical features

[1385] Output: Mountain climbing concept diagram

[1386] Specific operation: The server automatically creates a mountain climbing concept map including climbing routes and surrounding information (mountain huts, etc.) based on the topographical features generated by AIGenography.

[1387] Step 4:

[1388] The server uses the EmotionEngine to recognize the user's emotional state.

[1389] Input: User emotion data obtained from cameras and sensors

[1390] Output: The user's emotional state.

[1391] Specific operation: The server inputs data obtained from the camera and sensors into the EmotionEngine and analyzes the user's emotional state. For example, it determines whether the user is feeling anxious or excited based on data such as facial expressions and heart rate.

[1392] Step 5:

[1393] The server adjusts the display method of the mountain climbing concept diagram according to the user's emotional state.

[1394] Input: User's emotional state, mountain climbing concept

[1395] Output: Coordinated climbing concept map

[1396] Specific operation: The server adjusts the way the mountain climbing concept map is displayed based on the user's emotional state recognized by the Emotion Engine. For example, if the user feels anxious, the server emphasizes safety information and displays more options for mountain climbing routes if the user feels excited.

[1397] Step 6:

[1398] The server transmits the adjusted mountain climbing concept map to the terminal and displays it to the user.

[1399] Input: Coordinated climbing concept

[1400] Output: Mountain climbing concept diagram displayed on the user's device

[1401] Specific operation: The server sends the adjusted mountain climbing concept map to the user's terminal, which displays it. The user can check the mountain climbing route and safety information in a visually easy-to-understand format.

[1402] 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 voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1403] 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> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[1404] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1405] 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.

[1406] [Fourth embodiment]

[1407] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1408] 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.

[1409] 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 wide area network (WAN) and / or a local area network (LAN).

[1410] 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. In addition, the microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1411] 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 the voice according to instructions from the processor 46.

[1412] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1413] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1414] The control target 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, legs, etc. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, legs, etc. 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.

[1415] Fig. 8 shows an example of 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.

[1416] 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.

[1417] 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.

[1418] In the robot 414, 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.

[1419] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1420] "Example 1"

[1421] In one embodiment of the present invention, a climber inputs climbing route information based on a topographical map into the system. This climbing route information includes, for example, the start and end points of the route planned by the climber, waypoints, and points requiring special attention. Next, an AI in the system generates how to read and write topographical features based on the climbing route information. This AI generates how to read and write topographical features by reading detailed information on the topographical map. Finally, the system automatically creates a climbing concept map using how to read and write topographical features generated by the AI. This climbing concept map is created including surrounding information other than the climbing route (mountain huts, etc.).

[1422] "Example 2"

[1423] As another embodiment of the present invention, when a climber inputs climbing route information based on a topographical map into the system, the climber can input the information in a format that is easy to understand intuitively. For example, climbing route information can be input by drawing the route directly on the topographical map. In addition, when the system automatically creates a climbing concept map using how to read and write the topographical features generated by AI, the system displays the climbing concept map in a visually easy-to-understand format that is easy for climbers to understand. For example, topographical features, climbing routes, and surrounding information are expressed using colors, line thicknesses, symbols, etc.

[1424] The process flow of each embodiment will be described below.

[1425] "Example 1"

[1426] Step 1: A climber inputs climbing route information based on a topographical map into the system. This climbing route information includes, for example, the start and end points of the climber's planned route, intermediate points, and points requiring special caution.

[1427] Step 2: The AI ​​in the system generates how to read and write the topographical features based on the climbing route information. This AI generates how to read and write the topographical features by reading the detailed information on the topographical map.

[1428] Step 3: The system automatically creates a mountain climbing concept map using the AI-generated reading and writing of terrain features. This mountain climbing concept map is created including surrounding information (mountain huts, etc.) other than the climbing route.

[1429] "Example 2"

[1430] Step 1: When climbers input climbing route information based on a topographical map into the system, the input should be in a format that is intuitive and easy for climbers to understand. For example, climbing route information can be input by drawing the route directly on a topographical map.

[1431] Step 2: The AI ​​in the system generates how to read and write the topographical features based on the climbing route information. This AI generates how to read and write the topographical features by reading the detailed information on the topographical map.

[1432] Step 3: The system uses the AI-generated methods for reading and writing terrain features to automatically create a mountaineering concept map, which is displayed in a visually easy-to-understand format for climbers to understand. For example, colors, line thicknesses, symbols, etc. are used to represent terrain features, climbing routes, and surrounding information.

[1433] Example 1

[1434] Next, a description will be given of Example 1 of the embodiment 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".

[1435] In conventional mountain climbing planning systems, when climbers input detailed climbing route information based on topographical maps, they had to understand how to read and write topographical features and enter them appropriately. This made it difficult for climbers without specialized knowledge of topographical maps to make accurate climbing plans, and also made it difficult to create comprehensive climbing concept maps that included surrounding information (such as accommodation facilities) other than the climbing route. This led to issues such as a decrease in the accuracy of climbing plans and difficulty in ensuring safety during climbing.

[1436] 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.

[1437] In this invention, the server includes a means for a climber to input climbing route information based on a topographical map, a means for acquiring topographical map data based on the climbing route information, a generation AI model means for analyzing the topographical map data and generating how to read and write topographical features, a means for automatically creating a climbing concept map using the how to read and write topographical features generated by the generation AI model means, and a means for displaying the climbing concept map on a user's terminal. This allows climbers to make accurate climbing plans even without specialized knowledge, and makes it easy to create a comprehensive climbing concept map that includes peripheral information other than the climbing route.

[1438] "Climber" refers to an individual or group engaged in mountaineering activities.

[1439] A "topographic map" is a map showing detailed information about a terrain, including contour lines and topographical features.

[1440] "Mountain climbing route information" refers to information such as the starting point, end point, waypoints, and points requiring caution on the mountain climbing route planned by the climber.

[1441] "Server" refers to a computer system that processes and stores data.

[1442] "Terminal" refers to a device that allows a user to input information and display results, including, for example, a smartphone or a personal computer.

[1443] "Topographical map data" means digital data based on a topographical map and includes detailed information on the topography.

[1444] "Generative AI model" refers to a model that uses artificial intelligence to perform a specific task, in this case, generating ways to read or write topographical features.

[1445] A "mountain climbing concept map" refers to a diagram that visually shows a mountain climbing route and the surrounding information.

[1446] "Accommodation" refers to facilities where climbers can stay overnight. Examples include mountain huts and campsites.

[1447] This invention is a system that allows a climber to input climbing route information based on a topographical map, generates how to read and write topographical features based on that information, and finally automatically creates a climbing concept map. A specific embodiment of this system will be described below.

[1448] First, the user uses the terminal to input climbing route information. The user inputs the start and end points of the planned route, intermediate points, and points requiring special caution. For example, the user opens a smartphone app and inputs into the input form, "From the fifth station of Mt. Fuji to the summit of Mt. Fuji, intermediate points are the sixth, seventh, and eighth stations, and points requiring caution are the steep slope at the seventh station."

[1449] Next, the server receives the climbing route information entered by the user and obtains the topographical map data. Specifically, the server uses the Google Maps API or OpenStreetMap API to obtain topographical map data related to the specified route. For example, the server sends a request to the API to "obtain topographical map data from the fifth station of Mt. Fuji to the summit of Mt. Fuji."

[1450] The generative AI model in the server then analyzes the acquired topographical map data. The generative AI model reads the topographical map data and analyzes the topographical features of each point. For example, the AI ​​identifies the "steep slope at the seventh station" and analyzes its features in detail.

[1451] Next, the generative AI model generates how to read and write the topographical features based on the analysis results. Specifically, the AI ​​generates information such as "The steep slope at the seventh station requires special caution." For example, the AI ​​generates instructions such as "Use specific icons and colors to highlight the steep slope feature."

[1452] The server then automatically creates a mountain climbing concept map using the reading and writing of the terrain features generated by the generative AI model. Specifically, the server combines the topographical map data with the generated information to create a visually easy-to-understand mountain climbing concept map. For example, the server performs a process such as "displaying the route from the fifth station of Mt. Fuji to the summit of Mt. Fuji in red, and displaying the steep slope at the seventh station with a yellow warning icon."

[1453] Finally, the server sends the created mountain climbing concept map to the user's terminal and displays it. Specifically, the mountain climbing concept map is displayed on the user's smartphone or PC. For example, the user checks on the screen of their smartphone "a mountain climbing concept map that visually displays the route from the fifth station of Mt. Fuji to the summit of Mt. Fuji, each waypoint, and points requiring caution."

[1454] Examples of concrete examples and prompts

[1455] Examples

[1456] The user opens the app on their smartphone and enters the following information:

[1457] Starting point: Mount Fuji 5th Station

[1458] End point: The summit of Mt. Fuji

[1459] Waypoints: 6th, 7th, 8th stations

[1460] Areas requiring caution: Steep slope at the seventh station

[1461] The server uses the Google Maps API to obtain topographical map data from the fifth station of Mt. Fuji to the summit. Next, a generative AI model in the server analyzes the topographical map data and identifies the characteristics of the steep slope at the seventh station. The AI ​​generates information such as "particular caution is required on steep slopes," and the server uses this information to create a conceptual map of the climb. Finally, the server sends the conceptual map created by the server to the user's smartphone, where the user can check it on the screen.

[1462] Examples of prompt statements

[1463] "I am planning a climbing route from the 5th station of Mt. Fuji to the summit of Mt. Fuji. I will include the 6th, 7th, and 8th stations as waypoints, and I need to be careful of the steep slope of the 7th station. Please create a conceptual map of the climb based on this information."

[1464] The above is an embodiment of the invention.

[1465] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1466] Step 1:

[1467] A user inputs climbing route information using a terminal.

[1468] Specifically, the user opens the application on their smartphone or PC and enters the start point, end point, intermediate points, and points requiring caution of the planned route into an input form.

[1469] Input: Climbing route information (starting point, ending point, intermediate points, points requiring caution)

[1470] Output: Route information sent to the server

[1471] Step 2:

[1472] The server receives the climbing route information input by the user and obtains the topographical map data.

[1473] Specifically, the server uses the Google Maps API or the OpenStreetMap API to retrieve topographical map data related to the specified route.

[1474] Input: Climbing route information

[1475] Output: Topographic map data

[1476] Step 3:

[1477] A generative AI model on the server analyzes the acquired topographical map data.

[1478] Specifically, the generative AI model reads topographical map data and analyzes the terrain features of each location, identifying features such as steep slopes and cliffs.

[1479] Input: Topographic map data

[1480] Output: Analysis results of terrain features

[1481] Step 4:

[1482] A generative AI model generates readings and writings for topographical features based on the analysis results.

[1483] Specifically, the AI ​​generates information such as "particular caution is required on steep slopes" and generates instructions to use specific icons and colors.

[1484] Input: Topographic feature analysis results

[1485] Output: How to read and write topographical features

[1486] Step 5:

[1487] The server automatically creates a mountain climbing concept map using how to read and write the terrain features generated by the generative AI model.

[1488] Specifically, the server combines the topographical map data with the generated information to create a visually easy-to-understand mountain climbing concept map. For example, the route is displayed in red and steep slopes are displayed with a yellow warning icon.

[1489] Input: Topographic map data, how to read and write topographic features

[1490] Output: Mountain climbing concept diagram

[1491] Step 6:

[1492] The server transmits the created mountain climbing concept map to the user's terminal and displays it.

[1493] Specifically, a conceptual map of the climb is displayed on the user's smartphone or PC. The user can check the conceptual map on the screen, which visually displays the route, each waypoint, and points requiring caution.

[1494] Input: Mountain climbing concept diagram

[1495] Output: A conceptual diagram of the climb displayed on the user's device

[1496] (Application example 1)

[1497] Next, a description will be given of Application Example 1 of Form 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".

[1498] For autonomous vehicles, there is a need to generate optimal driving routes based on topographical maps and road information, and provide route maps that include points requiring special attention and surrounding information. However, current systems have the problem that it is difficult to efficiently analyze this information and display it visually.

[1499] The identification process by the identification processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for inputting route information based on a topographical map, an artificial intelligence means for generating readings and writings of topographical features based on the route information, a means for automatically creating a conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and a means for displaying the conceptual map. This makes it possible to generate an optimal driving route for an autonomous vehicle and efficiently provide a route map including points requiring special attention and surrounding information.

[1500] A "topographic map" is a map that contains detailed information about the terrain, visually showing the relief and characteristics of the terrain.

[1501] "Route information" refers to information about a route, such as a starting point, a destination point, and intermediate points.

[1502] An "artificial intelligence means" is a system that uses technologies such as machine learning and deep learning to analyze data and automatically perform specific tasks.

[1503] "Topographical features" refers to the relief and shape of the terrain shown on a topographical map, and the characteristics of a specific point.

[1504] "Reading and writing" refers to ways of understanding and visually representing topographical features.

[1505] A "conceptual map" is a diagram that visually simplifies specific information and includes routes and surrounding information.

[1506] The term "display means" refers to a device or system for visually displaying the generated conceptual diagram or other information.

[1507] "Nearby information" is information about points related to the route, including facilities such as rest areas and gas stations.

[1508] As an embodiment of the present invention, an "automated driving route optimization system" for automated driving vehicles will be described as an example. This system generates an optimal driving route based on topographical maps and road information, and provides a route map that includes points requiring special attention and surrounding information.

[1509] Hardware and Software Used

[1510] Hardware: On-board computer, GPS module, camera, LiDAR sensor for autonomous vehicles

[1511] Software: TensorFlow (training and inference of AI models), OpenStreetMap API (obtaining topographical maps and road information), Python (programming language)

[1512] Data processing and calculation

[1513] Data Entry

[1514] Users input start, destination and intermediate points into the autonomous vehicle's on-board computer, and the system then uses the OpenStreetMap API to retrieve topographical and road information for the specified route.

[1515] Analysis by AI model

[1516] The server uses TensorFlow to analyze the retrieved topographical map and road information and generate readings and writings of topographical features, which identify areas that require special attention (sharp curves, steep gradients, intersections, etc.).

[1517] Route Optimization

[1518] The server calculates the optimal driving route based on how the AI ​​model reads and writes the terrain features, taking into account surrounding information (gas stations, rest areas, etc.).

[1519] Generate route map

[1520] The server generates an optimized route map and displays it on the autonomous vehicle's display, along with visual indications of points of special interest and surrounding information.

[1521] Examples

[1522] Example prompts to be input to the generative AI model

[1523] Starting point: 35.6895, 139.6917

[1524] Destination point: 35.6586, 139.7454

[1525] Waypoint: 35.6733, 139.7100

[1526] Particular caution is required at: sharp curves, steep gradients, intersections

[1527] Based on this prompt, the server retrieves topographical maps and road information and performs analysis using an AI model. Based on the analysis results, it calculates the optimal driving route, generates a route map and displays it on the display of the autonomous vehicle, allowing the user to check a safe and efficient driving route.

[1528] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1529] Step 1:

[1530] The user inputs the starting point, destination point, and intermediate points into the on-board computer of the autonomous vehicle, and the system retrieves these points. The input includes latitude and longitude coordinates. The output is the coordinates that are passed to the next step.

[1531] Step 2:

[1532] The server uses the OpenStreetMap API to get the topographical map and road information for the specified route. As input, the coordinate information obtained in step 1 is used. The server sends an API request and receives data including the topographical map and road information. As output, the topographical map and road information are passed on to the next step.

[1533] Step 3:

[1534] The server uses TensorFlow to analyze the retrieved topographical map and road information and generate readings and writings of the topographical features. As input, the topographical map and road information retrieved in step 2 are used. Using an AI model, the server analyzes the topographical features and identifies points that require special attention (sharp curves, steep gradients, intersections, etc.). As output, the readings and writings of the topographical features are passed on to the next step.

[1535] Step 4:

[1536] The server calculates the optimal driving route based on the reading and writing of the terrain features generated by the AI ​​model. As input, the reading and writing of the terrain features generated in step 3 is used. The server also takes into account surrounding information (gas stations, rest areas, etc.) to calculate the optimal driving route. As output, the optimized driving route is passed to the next step.

[1537] Step 5:

[1538] The server generates an optimized route map and displays it on the autonomous vehicle's display. As input, the optimal driving route calculated in step 4 is used. The server generates the route map and also visually displays points of special interest and surrounding information. As output, the route map is displayed on the display for the user to review.

[1539] Through this series of processes, the user can check a safe and efficient driving route.

[1540] Example 2

[1541] Next, a second embodiment of the second embodiment will be described. 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".

[1542] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on a topographical map, and the generated mountain climbing concept map was visually difficult to understand. Furthermore, it was difficult to automatically create a detailed mountain climbing concept map that included surrounding information (such as accommodations) other than the mountain climbing route.

[1543] 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.

[1544] In this invention, the server includes a means for inputting mountain climbing route information based on a topographical map, a means for transmitting the mountain climbing route information as digital data, a means for using a generative AI model for generating readings and writings of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and writings of the topographical features generated by the generative AI model, and a means for displaying the mountain climbing conceptual map in a visually easy-to-understand format. This allows the user to intuitively input mountain climbing route information, and makes it possible to automatically create a visually easy-to-understand mountain climbing conceptual map. It is also possible to provide a detailed mountain climbing conceptual map that includes surrounding information other than the mountain climbing route.

[1545] A "topographic map" is a map that visually represents detailed information about a terrain.

[1546] "Mountain climbing route information" is information about the route of a mountain climbing planned by a mountain climber.

[1547] The "means for inputting" is a device or software that provides an interface for a user to draw a climbing route on a topographical map.

[1548] The "means for transmitting as digital data" refers to a communication means for transmitting the climbing route information input by the user to the server in digital form.

[1549] A "generative AI model" is an artificial intelligence model that analyzes and generates how to read and write topographical features.

[1550] A "climbing concept map" is a visual representation of a climbing route and the topographical features of its surroundings.

[1551] "Means for automatic creation" refers to a device or software for automatically generating a mountain climbing concept map using a generative AI model.

[1552] The "means for displaying in a visually easy-to-understand format" refers to a device or software for displaying the generated mountain climbing concept map in a format that is easy for the user to understand. ...

Claims

1. A means for acquiring information on a departure point and a destination point; means for acquiring topographical information from a topographical map database; means for identifying a user's emotion using an emotion engine; a means for generating a prompt sentence for instructing the generation of mountain climbing route information based on the acquired information on the starting point, the destination point, and the topographical information; A means for generating mountain climbing route information using the generated prompt sentence and the generative AI model; a means for generating a prompt sentence for instructing the user to generate a mountain climbing concept map based on the generated mountain climbing route information and the identified user's emotion; A means for generating a mountain climbing concept map using the generated prompt sentence and the generative AI model; A system including a means for presenting the generated mountain climbing concept map to a user.

2. 2. The system according to claim 1, wherein the means for generating the mountain climbing concept map displays predetermined topographical features in a visually easily distinguishable format based on the mountain climbing route information.

3. 2. The system according to claim 1, wherein the means for generating the mountain climbing concept map generates a mountain climbing concept map including peripheral information other than mountain climbing route information.

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