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 an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

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

[0004] It is extremely difficult for climbers (especially beginners) to read detailed information about the terrain from a topographical map. It also requires a certain level of skill and experience to create a simple mountain climbing map that includes the climbing route, terrain (ridges and valleys), and surrounding information (mountain huts), i.e., a mountain climbing concept map. [Means for solving the problem]

[0005] This invention uses AI to input climbing route information based on a topographical map and generate readings and descriptions of topographical features based on the climbing route information. Then, using the readings and descriptions of topographical features generated by the AI, a climbing concept map is automatically created. This makes it possible to visualize topographical maps in a way that is easy for climbers to understand. [Brief explanation 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. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 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. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

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

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

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

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

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

[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. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[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 WAN (Wide Area Network) and / or a LAN (Local Area Network).

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

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

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

[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 climber's planned route, intermediate points, and points requiring special attention. Next, an AI within 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 by including surrounding information other than the climbing route (such as mountain huts).

[0029] "Example 2"

[0030] Another embodiment of the present invention allows climbers to input climbing route information based on a topographical map into the system in a format that is intuitively easy for them to understand. For example, climbing route information can be input by drawing the route directly on the topographical map. Furthermore, when the system automatically creates a climbing concept map using the reading and writing methods of topographical features generated by AI, it 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 represented using colors, line thicknesses, symbols, etc.

[0031] The processing 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 attention.

[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 detailed information from 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 includes surrounding information (such as mountain huts) in addition to 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 intuitively easy for climbers to understand. For example, climbing route information can be input by drawing the route directly on the 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 detailed information from the topographical map.

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

[0040] Example 1

[0041] 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 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 record them appropriately. This made it difficult for climbers without specialized knowledge of topographical maps to create accurate climbing plans, and also made it difficult to create comprehensive climbing concept maps that included surrounding information (such as accommodations) 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 means for a climber to input climbing route information based on a topographical map, means for acquiring topographical map data based on the climbing route information, generation AI model means for analyzing the topographical map data and generating how to read and write topographical features, 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 means for displaying the climbing concept map on the 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 information on the surrounding area 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 the terrain, including contour lines and topographic 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] "Topographic map data" refers to digital data based on topographic maps, and includes detailed information about the terrain.

[0051] A "generative AI model" refers to a model that uses artificial intelligence to perform a specific task, in this case, to generate 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 its surrounding information.

[0053] "Accommodation" refers to facilities where climbers can stay overnight, including 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 ways to read and write topographical features based on that information, and finally automatically creates a climbing concept map. A specific embodiment of this system is described below.

[0055] First, the user uses a device to input information about the mountain climbing route. 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 the following into the input form: "From the fifth station of Mt. Fuji to the summit, 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 entered by the user and obtains topographical map data. Specifically, the server uses the Google (registered trademark) 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."

[0057] The generative AI model on 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 readings and writings for 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 features."

[0059] The server then automatically creates a mountain climbing concept map using the reading and writing of the topographical 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 might perform a process such as "displaying the route from the fifth station of Mt. Fuji to the summit 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 device and displays it. Specifically, the mountain climbing concept map is displayed on the user's smartphone or PC. For example, the user can check on their smartphone screen "a mountain climbing concept map that visually displays the route from the fifth station to the summit of Mt. Fuji, along with each waypoint and points requiring caution."

[0061] Examples of concrete examples and prompts

[0062] Specific 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: Summit of Mt. Fuji

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

[0067] Points to be careful of: Steep slope at the seventh station

[0068] The server uses the Google Maps API to obtain topographical map data from the fifth station to the summit of Mount Fuji. Next, a generative AI model on 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 to the user's smartphone, where the user can view it on their screen.

[0069] Prompt Sentence Examples

[0070] "I am planning a climbing route from the fifth station of Mt. Fuji to the summit. I will include the sixth, seventh, and eighth stations as waypoints, and I need to be careful of the steep slope at 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] The user inputs the climbing route information using the 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 the input form.

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

[0077] Output: Climbing route information sent to the server

[0078] Step 2:

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

[0080] Specifically, the server uses the Google Maps API or OpenStreetMap API to retrieve topographic 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 reading and writing methods 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 using specific icons and colors.

[0091] Input: Analysis results of terrain features

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

[0093] Step 5:

[0094] The server automatically creates a mountain climbing concept map using the reading and writing methods of the terrain features generated by the 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 indicated with yellow warning icons.

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

[0097] Output: Mountain climbing concept diagram

[0098] Step 6:

[0099] The server sends 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 map on the screen, which visually displays the route, each waypoint, and points requiring caution.

[0101] Input: Mountain climbing concept diagram

[0102] Output: Mountain climbing concept diagram displayed on the user's device

[0103] (Application example 1)

[0104] Next, a description will be given of Application Example 1 of Embodiment 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] Autonomous vehicles are required to generate optimal driving routes based on topographical maps and road information, and to provide route maps that include points requiring special attention and surrounding information. However, current systems face the challenge of efficiently analyzing this information and visually displaying it.

[0106] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for receiving route information based on a topographical map as an input, artificial intelligence means for generating readings and writings of topographical features based on the route information, means for automatically creating a conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and 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 that includes points requiring particular attention and surrounding information.

[0107] A "topographic map" is a map that contains detailed information about the terrain, visually showing the undulations 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] "Artificial intelligence means" refers to 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, as well as the characteristics of specific points.

[0111] "Reading and writing" refers to methods for understanding and visually representing topographical features.

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

[0113] "Display means" refers to a device or system for visually displaying the generated conceptual diagram and 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 an automated driving vehicle 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 (acquisition of topographical maps and road information), Python (programming language)

[0119] Data processing and calculation

[0120] Data Entry

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

[0122] Analysis using AI models

[0123] The server uses TensorFlow to analyze the acquired topographical map and road information, generating readings and writings of terrain features, which in turn identify areas requiring special attention (such as sharp curves, steep gradients, and intersections).

[0124] Route Optimization

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

[0126] Generate a 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 requiring special attention and surrounding information.

[0128] Specific examples

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

[0130] Starting point: 35.6895, 139.6917

[0131] Destination point: 35.6586, 139.7454

[0132] Waypoints: 35.6733, 139.7100

[0133] Particular caution is required: 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, the server calculates the optimal driving route, generates a route map, and displays it on the autonomous vehicle's display, allowing the user to check a safe and efficient driving route.

[0135] The flow of the specific processing 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 autonomous vehicle's on-board computer, which then retrieves these points. The input includes latitude and longitude coordinates. The output is passed on to the next step.

[0138] Step 2:

[0139] The server uses the OpenStreetMap API to get the topographic 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 topographic map and road information. As output, the topographic map and road information are passed to the next step.

[0140] Step 3:

[0141] The server uses TensorFlow to analyze the acquired topographical map and road information and generate ways to read and write the topographical features. The topographical map and road information acquired in step 2 are used as input. The server uses an AI model to analyze the topographical features and identify points that require special attention (sharp curves, steep slopes, intersections, etc.). The output is the ways to read and write the topographical features, which 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. The input is the optimal driving route calculated in step 4. The server generates the route map and visually displays points requiring special attention and surrounding information. The output is a route map that the user can view on the display.

[0146] This series of processes allows the user to check a safe and efficient driving route.

[0147] Example 2

[0148] Next, a description will be given of 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."

[0149] Conventional mountain climbing route information input systems have had problems in that it is difficult for users to intuitively input mountain climbing route information based on topographical maps, and the generated mountain climbing concept maps are visually difficult to understand. Furthermore, it is difficult to automatically create detailed mountain climbing concept maps that include 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 to generate readings and descriptions of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and descriptions of 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 users to intuitively input mountain climbing route information and 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 information on the surrounding area in addition to the mountain climbing route.

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

[0153] "Mountain climbing route information" is information about the mountain climbing route planned by the 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] "Means for transmitting as digital data" refers to a communication means for transmitting the climbing route information entered 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 the climbing route and the surrounding terrain features.

[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 operates 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 device screen using a mouse or stylus. The user can intuitively input route information by drawing a line on the topographical map or clicking points. For example, the user can specify a climbing route by dragging the mouse from the starting point to the finish point and drawing a line.

[0163] Next, the device sends 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.), such as the coordinates of the line's start and end points, and information on the line's color and thickness.

[0164] The server receives the climbing route information sent from the device and uses a generative AI model to analyze how to read and write the topographical features. The server then 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 represented using colors, line thickness, symbols, etc. For example, the climbing route is displayed with a thick red line, and surrounding topographical features are represented with blue dotted lines and green symbols.

[0165] The server then sends 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 terrain features displayed in a visually easy-to-understand format. This allows the user to obtain information that is useful when planning a mountain climbing trip.

[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 finish point, the device sends that information as digital data to the server. The server uses a generative AI model to analyze the characteristics of the terrain and generates a conceptual map of the mountain climbing route, displaying it with a thick red line and surrounding topographical features with blue dotted lines and green symbols. The server sends this conceptual map to the device, where the user can view it on the device screen.

[0167] An example of a prompt is as follows:

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

[0169] "Click multiple points on the topographical map to specify your climbing route. The system will create a conceptual map of your climbing route based on that information and display it as 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 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 mountain climbing route on the topographical map displayed on the device screen using a mouse or stylus. Specifically, the user drags the mouse to draw a line from the starting point to the goal point. This operation inputs the coordinate information of the mountain climbing route and the drawing format (line color, thickness, etc.).

[0175] Step 2:

[0176] The terminal sends 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, as well as information on the color and thickness of the line. The terminal assembles 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 the route passes through and extracts detailed information about the climbing route.

[0181] Step 4:

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

[0183] The server automatically generates a mountain climbing concept map based on the analysis results. The input includes information on the analyzed terrain features. 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 surrounding terrain features are represented by blue dotted lines and green symbols.

[0184] Step 5:

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

[0186] The server sends 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 sends 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 device screen. The input includes the data of the mountain climbing concept map sent from the server. The user checks the mountain climbing route and the features of the terrain 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 features of the surrounding terrain.

[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] Conventional climbing route information input systems have had problems in that it is difficult for users to intuitively input climbing route information based on topographical maps, and the generated climbing concept maps are visually difficult to understand. Furthermore, it is difficult to automatically create detailed climbing concept maps that include surrounding information other than the climbing route. This makes 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 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 topographical features generated by the AI ​​means, means for inputting route information by drawing the 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. This enables users 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" is information about the mountain climbing route planned by the climber, and includes the route and points of the route drawn on a topographical map.

[0197] "AI means" means means that use artificial intelligence technology to analyze data and automatically perform specific tasks.

[0198] A "mountain climbing concept map" is a diagram that visually represents mountain climbing routes 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 by which a user can input mountain 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 uses colors, line thickness, symbols, etc. to express information and is easy for users to understand intuitively.

[0201] The "means for analyzing route information" is 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 how to read and write the topographical features generated by the AI ​​means; means for inputting route information by drawing the 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 head-mounted display. This route information is sent to the server, where it is analyzed by AI means.

[0206] The AI ​​tool analyzes the input route information and generates readings and writings of terrain features. This is done using 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 thicknesses, 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] Specific examples

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

[0210] Prompt Sentence Examples

[0211] Below are some example prompts to input to the generative AI model:

[0212] Please create an application where the user can draw a route on a map, and the route will be 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 with AI, and generating a route map.

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

[0214] The flow of the specific processing 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 device's application, selects and loads a map data file, and the map data is displayed on the device's screen.

[0220] Step 2:

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

[0222] Input: Route drawing information via user touchscreen or mouse input

[0223] Output: Rendered route information

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

[0225] Step 3:

[0226] The server analyzes the received route information.

[0227] Input: Route information drawn

[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 analyzes the data using Python libraries (numpy, sklearn, etc.) and extracts 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 plot 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: 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 displays the received data and provides the user with a visually easy-to-understand route map.

[0240] Step 6:

[0241] Users see a visually easy-to-understand route map.

[0242] Input: 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 user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0246] "Example 1"

[0247] One embodiment of the present invention provides a system incorporating an emotion engine that recognizes a user's emotions. This system includes an AI means that receives climbing route information based on a topographical map and generates readings and writings of topographical features based on the climbing route information, and a means for automatically creating a climbing concept map using the readings and writings of the topographical features generated by the AI ​​means. The system also includes an emotion engine that recognizes the user's emotions. This emotion engine recognizes the user's emotional state, for example, from the user's facial expression, tone of voice, text input, etc., and then adjusts the readings and writings of the topographical features and the display method of the climbing concept map according to the user's emotional state. For example, if the system recognizes that the user is nervous, it provides more detailed topographical information. Furthermore, if the system recognizes that the user is relaxed, it provides only the minimum necessary information, thereby providing optimal information according to the user's emotional state.

[0248] "Example 2"

[0249] Another embodiment of the present invention provides a system in which an emotion engine adjusts the display method of a mountain climbing conceptual map in accordance with a user's emotional state. Similar to the above-described embodiment, this system includes an AI means for inputting mountain climbing route information based on a topographical map and generating readings and descriptions of topographical features based on the mountain climbing route information, and a means for automatically creating a mountain climbing conceptual map using the readings and descriptions of topographical features generated by the AI ​​means. The system also includes an emotion engine that recognizes the user's emotions. The emotion engine adjusts the display method of the mountain climbing conceptual map in accordance with the user's emotional state. For example, if the emotion engine recognizes that the user is feeling anxious, it highlights and displays more detailed topographical information and safety information. Furthermore, if the emotion engine recognizes that the user is excited, it provides an optimal display method in accordance with the user's emotional state, such as by increasing the number of mountain climbing route options.

[0250] The processing 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 tools, generate readings and writings of topographical features based on the input climbing route information.

[0254] Step 3: Automatically create a mountain climbing concept map using the generated reading and writing methods for the topographical 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 tools, generate readings and writings of topographical features based on the input climbing route information.

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

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

[0262] Step 5: Adjust the display method of the mountain climbing concept diagram according to the recognized emotional state of the user.

[0263] Example 1

[0264] 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 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. Furthermore, since the system does not provide information based on the user's emotional state, it is difficult to provide information optimal for the user's situation. This leads to the issue of insufficient safety and comfort during mountain climbing.

[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 means for inputting mountain climbing route information based on a topographical map, artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the artificial intelligence means, emotion recognition means for recognizing the user's emotion, and means for adjusting the information provided in accordance with the user's emotional state 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 user's emotional state.

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

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

[0270] "Artificial intelligence means" means technology that includes algorithms or models for analyzing input data and automatically performing specific tasks.

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

[0272] A "climbing concept map" is a diagram that visually shows a climbing route and its 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 a technique for changing the content and format of information provided depending on the user's emotional state.

[0275] MODE FOR CARRYING OUT THE INVENTION

[0276] This system allows climbers to input climbing route information based on a topographical map, and then uses that information to generate readings and writings of topographical features, ultimately creating a climbing concept map. Furthermore, by combining it with an emotion recognition means that recognizes the user's emotions, the system provides information according to the user's emotional state.

[0277] System configuration

[0278] 1. Enter climbing route information

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

[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 descriptions 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 terrain features generated by AI. This mountain climbing concept map includes surrounding information (such as mountain huts) in addition to 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 device 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 delivery algorithms

[0298] Specific examples

[0299] The user opens a dedicated smartphone application and inputs information about the climbing route. For example, they input "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 the climb including detailed topographical information.

[0304] Prompt Sentence Examples

[0305] "Please enter your 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 climbing route information. Specifically, the user opens a dedicated smartphone application and enters "route from the fifth station of Mt. Fuji to the summit, stopping at mountain huts along the way" into the input form.

[0310] Input: Climbing route information such as the start and end points, 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 and 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 an artificial intelligence model (e.g., TensorFlow) to analyze detailed information on the topographic map.

[0316] Output: Generates readings and writings of topographical features

[0317] Specific operation: The server analyzes the received data, analyzes the detailed information of the topographic map using TensorFlow, and generates how to read and write the topographic 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 AI. This mountain climbing concept map includes information about the surrounding area (mountain huts, etc.) in addition to 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 area.

[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 device 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: User's emotional state obtained from 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 Embodiment 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 are unable to provide appropriate information when the user is tense or relaxed. Furthermore, 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: 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 topographical features generated by the AI ​​means; means including an emotion engine for recognizing the user's emotions; and means for adjusting the information provided in accordance with the user's emotional state recognized by the emotion engine. This makes it possible to provide optimal information in accordance with the user's emotional state.

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

[0342] "Mountain climbing route information" includes information such as the start point, end point, waypoints, and points requiring special attention on the route planned by the climber.

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

[0344] "Reading and writing topographic features" refers to the interpretation of detailed topographic information based on topographic maps and its representation in visual or textual form.

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

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

[0347] The "means for adjusting the information provided" is a means for changing the level of detail and content of the information provided depending on the emotional state of the user.

[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 how to read and write the topographical features generated by the AI ​​means; means including an emotion engine for recognizing the user's emotions; and means for adjusting the information provided 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 waypoints, which provides the climbing route information to the system.

[0355] 2. Route Planning: The server uses the RoutePlanner library to generate readings and writings of topographical 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 information about the surrounding area (e.g., mountain huts) in addition to the hiking 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, it provides detailed topographical information, but if the user is relaxed, it provides only the minimum necessary information.

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

[0360] Specific examples

[0361] User input: Departure point "Tokyo Station", destination point "Mount Fuji", intermediate point "Yokohama Station"

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

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

[0364] Prompt Sentence Examples

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

[0366] The flow of the specific processing 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 a smartphone application, the user inputs the starting point "Tokyo Station," the destination point "Mount 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 topographical features based on the input route information. The server analyzes the received information on the starting point, destination, and intermediate points, and retrieves the corresponding topographical information from a topographical map database. Based on the retrieved topographical information, an AI model generates readings and writings of topographical features. The generated data is used in the next step.

[0371] Step 3:

[0372] The server uses the MapGenerator library to create a driving concept map. The server generates a driving concept map including the climbing route and its surrounding information (mountain huts, etc.) based on how to read and write 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 their 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 it provides based on the recognized emotional state. The server determines the level of detail of the information it provides based on the emotional state determined in step 4. For example, if the user is nervous, it provides detailed topographical information, and if the user is relaxed, it provides only the minimum necessary information. 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. Based on the displayed information, the user can check the climbing route safely and efficiently.

[0379] Example 2

[0380] Next, a description will be given of 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."

[0381] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on topographical maps, and the generated mountain climbing concept map was not adjusted according to the user's emotional state, making it difficult to provide information that was easy for users to understand.Furthermore, it was also insufficient to create detailed mountain climbing concept maps 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 means for inputting mountain climbing route information based on a topographical map, artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the artificial intelligence means, and emotion recognition means for recognizing the user's emotional state and adjusting the display method of the mountain climbing concept map in accordance with the emotional state. This allows the user to intuitively input mountain climbing route information, and the generated mountain climbing concept map is adjusted according to the user's emotional state, 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 concept map that includes surrounding information other than the mountain climbing route.

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

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

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

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

[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 important information for climbers, such as evacuation sites and water sources.

[0391] This invention is a system that allows climbers to intuitively input climbing route information based on a topographical map, and the generated climbing concept map is adjusted according to the user's emotional state. Specific embodiments of this system are 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] The server then analyzes the received climbing route information. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate reading and writing instructions 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 the generated topographical features are read and written. 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 uses emotion recognition means (e.g., IBM Watson (registered trademark) or Microsoft Azure Cognitive Services) to recognize the user's emotional state. If the user feels anxious, the server will highlight and display detailed terrain information and safety information. If the user feels excited, the server will provide an optimal display method according to the user's emotional state, such as increasing the number of mountain climbing route options.

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

[0397] Example prompt sentence:

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

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

[0403] Step 2:

[0404] The server receives climbing route information sent from the terminal. The input is digitized climbing route information. The server analyzes this information and generates how to read and write the terrain features using a generative AI model (for example, TensorFlow or PyTorch). 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. The output is how to read and write the terrain features.

[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. Specifically, 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 an emotion recognition means. As input, it receives 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. Specifically, if the user feels anxious, the server highlights detailed topographical information and safety information. If the user feels excited, the server increases the number of mountain climbing route options. As output, it provides the optimal display method according to the user's emotional state.

[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 mountain climbing route information based on topographical maps, and the system does not provide information that reflects the user's emotional state, which means that the safety and comfort of the climber are not sufficiently ensured. Furthermore, autonomous vehicles also have the problem of not providing appropriate navigation to safely transport climbers to their destination.

[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 means for inputting mountain climbing route information based on a topographical map, AI means for generating readings and descriptions of topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the readings and descriptions of the topographical features generated by the AI ​​means, an emotion engine for recognizing the user's emotional state, means for adjusting the display method of the mountain climbing concept map in accordance with the emotional state recognized by the emotion engine, and means installed in the 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 the terrain.

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

[0416] "AI means" means technical means for performing a specific task using artificial intelligence.

[0417] "Topographic features" refer to topographical characteristics such as mountains, valleys, and rivers on a topographic 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 that recognize the user's emotional state.

[0427] software

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

[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. Users can input climbing route information by drawing the route directly on the topographical map. This information is sent to the server and used for further processing.

[0433] Generate terrain features

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

[0435] Creating a mountain climbing concept map

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

[0437] Adjusting display method using emotion engine

[0438] The server uses the Emotion Engine to recognize the user's emotional state. The Emotion Engine analyzes data obtained from cameras and sensors to determine the user's emotional state. For example, if the user is feeling anxious, the server will highlight safety information on the mountain climbing concept map. If the user is 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] Specific examples

[0440] For example, consider a climber getting into an autonomous vehicle and inputting a route to their 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 conceptual map of the climb. Next, Emotion Engine recognizes the user's emotional state and adjusts the display accordingly. If the user feels anxious, safety information is emphasized, and if the user feels excited, the options for the climbing route are increased.

[0441] Prompt Sentence Examples

[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 terrain features. Use an emotion engine to adjust the navigation information according to the user's emotional state."

[0443] The flow of the specific processing 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 hiking route information

[0447] Output: Climbing route information

[0448] Specific operation: The 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 terrain features using AI Geography.

[0451] Input: Climbing route information

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

[0453] Specific operation: The server inputs the received climbing route information into AI Geography and analyzes the detailed information of the topographic map to generate terrain 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 the climbing route and surrounding information (mountain huts, etc.) based on the topographical features generated by AI Geography.

[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: User's emotional state

[0463] How it works: The server inputs data acquired from cameras and sensors into the Emotion Engine 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 diagram

[0467] Output: Adjusted climbing concept map

[0468] Specific operation: The server adjusts the display method of the mountain climbing concept map based on the user's emotional state recognized by the Emotion Engine. For example, if the user feels anxious, it highlights safety information, and if the user feels excited, it increases the options for mountain climbing routes.

[0469] Step 6:

[0470] The server sends 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 device, 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 audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[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 engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

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

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

[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 WAN (Wide Area Network) and / or a LAN (Local Area Network).

[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 audio in accordance with instructions from the processor 46.

[0484] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0485] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0486] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[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 climber's planned route, intermediate points, and points requiring special attention. Next, an AI within 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 by including surrounding information other than the climbing route (such as mountain huts).

[0493] "Example 2"

[0494] Another embodiment of the present invention allows climbers to input climbing route information based on a topographical map into the system in a format that is intuitively easy for them to understand. For example, climbing route information can be input by drawing the route directly on the topographical map. Furthermore, when the system automatically creates a climbing concept map using the reading and writing methods of topographical features generated by AI, it 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 represented using colors, line thicknesses, symbols, etc.

[0495] The processing 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 attention.

[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 detailed information from 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 includes surrounding information (such as mountain huts) in addition to 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 intuitively easy for climbers to understand. For example, climbing route information can be input by drawing the route directly on the 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 detailed information from the topographical map.

[0503] Step 3: The system automatically creates a mountaineering concept map using the AI-generated methods for reading and writing terrain features, and displays the map in a visually easy-to-understand format for climbers to understand. For example, it uses colors, line thicknesses, symbols, etc. 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 record them appropriately. This made it difficult for climbers without specialized knowledge of topographical maps to create accurate climbing plans, and also made it difficult to create comprehensive climbing concept maps that included surrounding information (such as accommodations) 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 means for a climber to input climbing route information based on a topographical map, means for acquiring topographical map data based on the climbing route information, generation AI model means for analyzing the topographical map data and generating how to read and write topographical features, 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 means for displaying the climbing concept map on the 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 information on the surrounding area 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 the terrain, including contour lines and topographic 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] "Topographic map data" refers to digital data based on topographic maps, and includes detailed information about the terrain.

[0515] A "generative AI model" refers to a model that uses artificial intelligence to perform a specific task, in this case, to generate 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 its surrounding information.

[0517] "Accommodation" refers to facilities where climbers can stay overnight, including 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 ways to read and write topographical features based on that information, and finally automatically creates a climbing concept map. A specific embodiment of this system is described below.

[0519] First, the user uses a device to input information about the mountain climbing route. 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 the following into the input form: "From the fifth station of Mt. Fuji to the summit, 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 retrieves the topographical map data. Specifically, the server uses the Google Maps API or OpenStreetMap API to retrieve the topographical map data related to the specified route. For example, the server sends a request to the API to "retrieve topographical map data from the fifth station of Mt. Fuji to the summit of Mt. Fuji."

[0521] The generative AI model on 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 readings and writings for 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 features."

[0523] The server then automatically creates a mountain climbing concept map using the reading and writing of the topographical 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 might perform a process such as "displaying the route from the fifth station of Mt. Fuji to the summit 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 device and displays it. Specifically, the mountain climbing concept map is displayed on the user's smartphone or PC. For example, the user can check on their smartphone screen "a mountain climbing concept map that visually displays the route from the fifth station to the summit of Mt. Fuji, along with each waypoint and points requiring caution."

[0525] Examples of concrete examples and prompts

[0526] Specific 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: Summit of Mt. Fuji

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

[0531] Points to be careful of: Steep slope at the seventh station

[0532] The server uses the Google Maps API to obtain topographical map data from the fifth station to the summit of Mount Fuji. Next, a generative AI model on 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 to the user's smartphone, where the user can view it on their screen.

[0533] Prompt Sentence Examples

[0534] "I am planning a climbing route from the fifth station of Mt. Fuji to the summit. I will include the sixth, seventh, and eighth stations as waypoints, and I need to be careful of the steep slope at the seventh 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] The user inputs the climbing route information using the 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 the input form.

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

[0541] Output: Climbing route information sent to the server

[0542] Step 2:

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

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

[0545] Input: Climbing route information

[0546] Output: Topographic 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 reading and writing methods 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 using specific icons and colors.

[0555] Input: Analysis results of terrain features

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

[0557] Step 5:

[0558] The server automatically creates a mountain climbing concept map using the reading and writing methods of the terrain features generated by the 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 indicated with yellow warning icons.

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

[0561] Output: Mountain climbing concept diagram

[0562] Step 6:

[0563] The server sends 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 map on the screen, which visually displays the route, each waypoint, and points requiring caution.

[0565] Input: Mountain climbing concept diagram

[0566] Output: Mountain climbing concept diagram 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] Autonomous vehicles are required to generate optimal driving routes based on topographical maps and road information, and to provide route maps that include points requiring special attention and surrounding information. However, current systems face the challenge of efficiently analyzing this information and visually displaying it.

[0570] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for receiving route information based on a topographical map as an input, artificial intelligence means for generating readings and writings of topographical features based on the route information, means for automatically creating a conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and 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 that includes points requiring particular attention and surrounding information.

[0571] A "topographic map" is a map that contains detailed information about the terrain, visually showing the undulations 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] "Artificial intelligence means" refers to 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, as well as the characteristics of specific points.

[0575] "Reading and writing" refers to methods for understanding and visually representing topographical features.

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

[0577] "Display means" refers to a device or system for visually displaying the generated conceptual diagram and 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 an automated driving vehicle 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 (AI model training and inference), OpenStreetMap API (topographical map and road information acquisition), Python (programming language)

[0583] Data processing and calculation

[0584] Data Entry

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

[0586] Analysis using AI models

[0587] The server uses TensorFlow to analyze the acquired topographical map and road information, generating readings and writings of terrain features, which in turn identify areas requiring special attention (such as sharp curves, steep gradients, and intersections).

[0588] Route Optimization

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

[0590] Generate a 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 requiring special attention and surrounding information.

[0592] Specific examples

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

[0594] Starting point: 35.6895, 139.6917

[0595] Destination point: 35.6586, 139.7454

[0596] Waypoints: 35.6733, 139.7100

[0597] Particular caution is required: 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, the server calculates the optimal driving route, generates a route map, and displays it on the autonomous vehicle's display, allowing the user to check a safe and efficient driving route.

[0599] The flow of the specific processing 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 autonomous vehicle's on-board computer, which then retrieves these points. The input includes latitude and longitude coordinates. The output is passed on to the next step.

[0602] Step 2:

[0603] The server uses the OpenStreetMap API to get the topographic 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 topographic map and road information. As output, the topographic map and road information are passed to the next step.

[0604] Step 3:

[0605] The server uses TensorFlow to analyze the acquired topographical map and road information and generate ways to read and write the topographical features. The topographical map and road information acquired in step 2 are used as input. The server uses an AI model to analyze the topographical features and identify points that require special attention (sharp curves, steep slopes, intersections, etc.). The output is the ways to read and write the topographical features, which 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. The input is the optimal driving route calculated in step 4. The server generates the route map and visually displays points requiring special attention and surrounding information. The output is a route map that the user can view on the display.

[0610] This series of processes allows the user to check a safe and efficient driving route.

[0611] Example 2

[0612] Next, a description will be given of 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."

[0613] Conventional mountain climbing route information input systems have had problems in that it is difficult for users to intuitively input mountain climbing route information based on topographical maps, and the generated mountain climbing concept maps are visually difficult to understand. Furthermore, it is difficult to automatically create detailed mountain climbing concept maps that include 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 to generate readings and descriptions of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and descriptions of 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 users to intuitively input mountain climbing route information and 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 information on the surrounding area in addition to the mountain climbing route.

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

[0617] "Mountain climbing route information" is information about the mountain climbing route planned by the 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] "Means for transmitting as digital data" refers to a communication means for transmitting the climbing route information entered 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 the climbing route and the surrounding terrain features.

[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 operates 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 device screen using a mouse or stylus. The user can intuitively input route information by drawing a line on the topographical map or clicking points. For example, the user can specify a climbing route by dragging the mouse from the starting point to the finish point and drawing a line.

[0627] Next, the device sends 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.), such as the coordinates of the line's start and end points, and information on the line's color and thickness.

[0628] The server receives the climbing route information sent from the device and uses a generative AI model to analyze how to read and write the topographical features. The server then 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 represented using colors, line thickness, symbols, etc. For example, the climbing route is displayed with a thick red line, and surrounding topographical features are represented with blue dotted lines and green symbols.

[0629] The server then sends 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 terrain features displayed in a visually easy-to-understand format. This allows the user to obtain information that is useful when planning a mountain climbing trip.

[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 finish point, the device sends that information as digital data to the server. The server uses a generative AI model to analyze the characteristics of the terrain and generates a conceptual map of the mountain climbing route, displaying it with a thick red line and surrounding topographical features with blue dotted lines and green symbols. The server sends this conceptual 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 in red on the topographical map. The system will create a conceptual map of the climb based on that information and display your climbing route in thick red."

[0633] "Click multiple points on the topographical map to specify your climbing route. The system will create a conceptual map of your climbing route based on that information and display it as 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 mountain climbing route on the topographical map displayed on the device screen using a mouse or stylus. Specifically, the user drags the mouse to draw a line from the starting point to the goal point. This operation inputs the coordinate information of the mountain climbing route and the drawing format (line color, thickness, etc.).

[0639] Step 2:

[0640] The terminal sends 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, as well as 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 the route passes through and extracts detailed information about the climbing route.

[0645] Step 4:

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

[0647] The server automatically generates a mountain climbing concept map based on the analysis results. The input includes information on the analyzed terrain features. 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 surrounding terrain features are represented by blue dotted lines and green symbols.

[0648] Step 5:

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

[0650] The server sends 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 sends 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 device screen. The input includes the data of the mountain climbing concept map sent from the server. The user checks the mountain climbing route and the features of the terrain 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 features of the surrounding terrain.

[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] Conventional climbing route information input systems have had problems in that it is difficult for users to intuitively input climbing route information based on topographical maps, and the generated climbing concept maps are visually difficult to understand. Furthermore, it is difficult to automatically create detailed climbing concept maps that include surrounding information other than the climbing route. This makes 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 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 topographical features generated by the AI ​​means, means for inputting route information by drawing the 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. This enables users 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" is information about the mountain climbing route planned by the climber, and includes the route and points of the route drawn on a topographical map.

[0661] "AI means" means means that use artificial intelligence technology to analyze data and automatically perform specific tasks.

[0662] A "mountain climbing concept map" is a diagram that visually represents mountain climbing routes 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 by which a user can input mountain 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 uses colors, line thickness, symbols, etc. to express information and is easy for users to understand intuitively.

[0665] The "means for analyzing route information" is 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 how to read and write the topographical features generated by the AI ​​means; means for inputting route information by drawing the 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 head-mounted display. This route information is sent to the server, where it is analyzed by AI means.

[0670] The AI ​​tool analyzes the input route information and generates readings and writings of terrain features. This is done using 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 thicknesses, 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] Specific examples

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

[0674] Prompt Sentence Examples

[0675] Below are some example prompts to input to the generative AI model:

[0676] Please create an application where the user can draw a route on a map, and the route will be 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 with AI, and generating a route map.

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

[0678] The flow of the specific processing 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 device's application, selects and loads a map data file, and the map data is displayed on the device's screen.

[0684] Step 2:

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

[0686] Input: Route drawing information via user touchscreen or mouse input

[0687] Output: Rendered route information

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

[0689] Step 3:

[0690] The server analyzes the received route information.

[0691] Input: Route information drawn

[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 plot 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: 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 displays the received data and provides the user with a visually easy-to-understand route map.

[0704] Step 6:

[0705] Users see a visually easy-to-understand route map.

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

[0710] "Example 1"

[0711] One embodiment of the present invention provides a system incorporating an emotion engine that recognizes a user's emotions. This system includes an AI means that receives climbing route information based on a topographical map and generates readings and writings of topographical features based on the climbing route information, and a means for automatically creating a climbing concept map using the readings and writings of the topographical features generated by the AI ​​means. The system also includes an emotion engine that recognizes the user's emotions. This emotion engine recognizes the user's emotional state, for example, from the user's facial expression, tone of voice, text input, etc., and then adjusts the readings and writings of the topographical features and the display method of the climbing concept map according to the user's emotional state. For example, if the system recognizes that the user is nervous, it provides more detailed topographical information. Furthermore, if the system recognizes that the user is relaxed, it provides only the minimum necessary information, thereby providing optimal information according to the user's emotional state.

[0712] "Example 2"

[0713] Another embodiment of the present invention provides a system in which an emotion engine adjusts the display method of a mountain climbing conceptual map in accordance with a user's emotional state. Similar to the above-described embodiment, this system includes an AI means for inputting mountain climbing route information based on a topographical map and generating readings and descriptions of topographical features based on the mountain climbing route information, and a means for automatically creating a mountain climbing conceptual map using the readings and descriptions of topographical features generated by the AI ​​means. The system also includes an emotion engine that recognizes the user's emotions. The emotion engine adjusts the display method of the mountain climbing conceptual map in accordance with the user's emotional state. For example, if the emotion engine recognizes that the user is feeling anxious, it highlights and displays more detailed topographical information and safety information. Furthermore, if the emotion engine recognizes that the user is excited, it provides an optimal display method in accordance with the user's emotional state, such as by increasing the number of mountain climbing route options.

[0714] The processing 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 tools, generate readings and writings of topographical features based on the input climbing route information.

[0718] Step 3: Automatically create a mountain climbing concept map using the generated reading and writing methods for the topographical 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 tools, generate readings and writings of topographical features based on the input climbing route information.

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

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

[0726] Step 5: Adjust the display method of the mountain climbing concept diagram according to 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. Furthermore, since the system does not provide information based on the user's emotional state, it is difficult to provide information optimal for the user's situation. This leads to the issue of insufficient safety and comfort during mountain climbing.

[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 means for inputting mountain climbing route information based on a topographical map, artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the artificial intelligence means, emotion recognition means for recognizing the user's emotion, and means for adjusting the information provided in accordance with the user's emotional state 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 user's emotional state.

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

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

[0734] "Artificial intelligence means" means technology that includes algorithms or models for analyzing input data and automatically performing specific tasks.

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

[0736] A "climbing concept map" is a diagram that visually shows a climbing route and its 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 a technique for changing the content and format of information provided depending on the user's emotional state.

[0739] MODE FOR CARRYING OUT THE INVENTION

[0740] This system allows climbers to input climbing route information based on a topographical map, and then uses that information to generate readings and writings of topographical features, ultimately creating a climbing concept map. Furthermore, by combining it with an emotion recognition means that recognizes the user's emotions, the system provides information according to the user's emotional state.

[0741] System configuration

[0742] 1. Enter climbing route information

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

[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 descriptions 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 terrain features generated by AI. This mountain climbing concept map includes surrounding information (such as mountain huts) in addition to 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 device 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 delivery algorithms

[0762] Specific examples

[0763] The user opens a dedicated smartphone application and inputs information about the climbing route. For example, they input "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 the climb including detailed topographical information.

[0768] Prompt Sentence Examples

[0769] "Please enter your 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 climbing route information. Specifically, the user opens a dedicated smartphone application and enters "route from the fifth station of Mt. Fuji to the summit, stopping at mountain huts along the way" into the input form.

[0774] Input: Climbing route information such as the start and end points, 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 and 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 an artificial intelligence model (e.g., TensorFlow) to analyze detailed information on the topographic map.

[0780] Output: Generates readings and writings of topographical features

[0781] Specific operation: The server analyzes the received data, analyzes the detailed information of the topographic map using TensorFlow, and generates how to read and write the topographic 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 AI. This mountain climbing concept map includes information about the surrounding area (mountain huts, etc.) in addition to 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 area.

[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 device 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: User's emotional state obtained from 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 are unable to provide appropriate information when the user is tense or relaxed. Furthermore, 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: 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 topographical features generated by the AI ​​means; means including an emotion engine for recognizing the user's emotions; and means for adjusting the information provided in accordance with the user's emotional state recognized by the emotion engine. This makes it possible to provide optimal information in accordance with the user's emotional state.

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

[0806] "Mountain climbing route information" includes information such as the start point, end point, waypoints, and points requiring special attention on the route planned by the climber.

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

[0808] "Reading and writing topographic features" refers to the interpretation of detailed topographic information based on topographic maps and its representation in visual or textual form.

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

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

[0811] The "means for adjusting the information provided" is a means for changing the level of detail and content of the information provided depending on the emotional state of the user.

[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 how to read and write the topographical features generated by the AI ​​means; means including an emotion engine for recognizing the user's emotions; and means for adjusting the information provided 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 waypoints, which provides the climbing route information to the system.

[0819] 2. Route Planning: The server uses the RoutePlanner library to generate readings and writings of topographical 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 information about the surrounding area (e.g., mountain huts) in addition to the hiking 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, it provides detailed topographical information, but if the user is relaxed, it provides only the minimum necessary information.

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

[0824] Specific examples

[0825] User input: Departure point "Tokyo Station", destination point "Mount Fuji", intermediate point "Yokohama Station"

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

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

[0828] Prompt Sentence Examples

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

[0830] The flow of the specific processing 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 a smartphone application, the user inputs the starting point "Tokyo Station," the destination point "Mount 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 topographical features based on the input route information. The server analyzes the received information on the starting point, destination, and intermediate points, and retrieves the corresponding topographical information from a topographical map database. Based on the retrieved topographical information, an AI model generates readings and writings of topographical features. The generated data is used in the next step.

[0835] Step 3:

[0836] The server uses the MapGenerator library to create a driving concept map. The server generates a driving concept map including the climbing route and its surrounding information (mountain huts, etc.) based on how to read and write 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 their 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 it provides based on the recognized emotional state. The server determines the level of detail of the information it provides based on the emotional state determined in step 4. For example, if the user is nervous, it provides detailed topographical information, and if the user is relaxed, it provides only the minimum necessary information. 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. Based on the displayed information, the user can check the climbing route safely and efficiently.

[0843] Example 2

[0844] Next, a description will be given of 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."

[0845] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on topographical maps, and the generated mountain climbing concept map was not adjusted according to the user's emotional state, making it difficult to provide information that was easy for users to understand.Furthermore, it was also insufficient to create detailed mountain climbing concept maps 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 means for inputting mountain climbing route information based on a topographical map, artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the artificial intelligence means, and emotion recognition means for recognizing the user's emotional state and adjusting the display method of the mountain climbing concept map in accordance with the emotional state. This allows the user to intuitively input mountain climbing route information, and the generated mountain climbing concept map is adjusted according to the user's emotional state, 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 concept map that includes surrounding information other than the mountain climbing route.

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

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

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

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

[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 important information for climbers, such as evacuation sites and water sources.

[0855] This invention is a system that allows climbers to intuitively input climbing route information based on a topographical map, and the generated climbing concept map is adjusted according to the user's emotional state. Specific embodiments of this system are 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] The server then analyzes the received climbing route information. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate reading and writing instructions 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 the generated topographical features are read and written. 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] Furthermore, the server uses emotion recognition tools (e.g., IBM Watson or Microsoft Azure Cognitive Services) to recognize the user's emotional state. If the user feels anxious, the server will highlight and display detailed terrain information and safety information. 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 hiking route options.

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

[0861] Example prompt sentence:

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

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

[0867] Step 2:

[0868] The server receives climbing route information sent from the terminal. The input is digitized climbing route information. The server analyzes this information and generates how to read and write the terrain features using a generative AI model (for example, TensorFlow or PyTorch). 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. The output is how to read and write the terrain features.

[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. Specifically, 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 an emotion recognition means. As input, it receives 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. Specifically, if the user feels anxious, the server highlights detailed topographical information and safety information. If the user feels excited, the server increases the number of mountain climbing route options. As output, it provides the optimal display method according to the user's emotional state.

[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 mountain climbing route information based on topographical maps, and the system does not provide information that reflects the user's emotional state, which means that the safety and comfort of the climber are not sufficiently ensured. Furthermore, autonomous vehicles also have the problem of not providing appropriate navigation to safely transport climbers to their destination.

[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 means for inputting mountain climbing route information based on a topographical map, AI means for generating readings and descriptions of topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the readings and descriptions of the topographical features generated by the AI ​​means, an emotion engine for recognizing the user's emotional state, means for adjusting the display method of the mountain climbing concept map in accordance with the emotional state recognized by the emotion engine, and means installed in the 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 the terrain.

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

[0880] "AI means" means technical means for performing a specific task using artificial intelligence.

[0881] "Topographic features" refer to topographical characteristics such as mountains, valleys, and rivers on a topographic 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 that recognize the user's emotional state.

[0891] software

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

[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. Users can input climbing route information by drawing the route directly on the topographical map. This information is sent to the server and used for further processing.

[0897] Generate terrain features

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

[0899] Creating a mountain climbing concept map

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

[0901] Adjusting display method using emotion engine

[0902] The server uses the Emotion Engine to recognize the user's emotional state. The Emotion Engine analyzes data obtained from cameras and sensors to determine the user's emotional state. For example, if the user is feeling anxious, the server will highlight safety information on the mountain climbing concept map. If the user is 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] Specific examples

[0904] For example, consider a climber getting into an autonomous vehicle and inputting a route to their 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 conceptual map of the climb. Next, Emotion Engine recognizes the user's emotional state and adjusts the display accordingly. If the user feels anxious, safety information is emphasized, and if the user feels excited, the options for the climbing route are increased.

[0905] Prompt Sentence Examples

[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 terrain features. Use an emotion engine to adjust the navigation information according to the user's emotional state."

[0907] The flow of the specific processing 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 hiking route information

[0911] Output: Climbing route information

[0912] Specific operation: The 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 terrain features using AI Geography.

[0915] Input: Climbing route information

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

[0917] Specific operation: The server inputs the received climbing route information into AI Geography and analyzes the detailed information of the topographic map to generate terrain 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 the climbing route and surrounding information (mountain huts, etc.) based on the topographical features generated by AI Geography.

[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: User's emotional state

[0927] How it works: The server inputs data acquired from cameras and sensors into the Emotion Engine 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 diagram

[0931] Output: Adjusted climbing concept map

[0932] Specific operation: The server adjusts the display method of the mountain climbing concept map based on the user's emotional state recognized by the Emotion Engine. For example, if the user feels anxious, it highlights safety information, and if the user feels excited, it increases the options for mountain climbing routes.

[0933] Step 6:

[0934] The server sends 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 device, 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 audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[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 performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

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

[0941] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[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 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 WAN (Wide Area Network) and / or a LAN (Local Area Network).

[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 audio in accordance with instructions from the processor 46.

[0948] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0949] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

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

[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 climber's planned route, intermediate points, and points requiring special attention. Next, an AI within 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 by including surrounding information other than the climbing route (such as mountain huts).

[0957] "Example 2"

[0958] Another embodiment of the present invention allows climbers to input climbing route information based on a topographical map into the system in a format that is intuitively easy for them to understand. For example, climbing route information can be input by drawing the route directly on the topographical map. Furthermore, when the system automatically creates a climbing concept map using the reading and writing methods of topographical features generated by AI, it 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 represented using colors, line thicknesses, symbols, etc.

[0959] The processing 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 attention.

[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 detailed information from 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 includes surrounding information (such as mountain huts) in addition to 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 intuitively easy for climbers to understand. For example, climbing route information can be input by drawing the route directly on the 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 detailed information from the topographical map.

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

[0968] Example 1

[0969] 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 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 record them appropriately. This made it difficult for climbers without specialized knowledge of topographical maps to create accurate climbing plans, and also made it difficult to create comprehensive climbing concept maps that included surrounding information (such as accommodations) 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 means for a climber to input climbing route information based on a topographical map, means for acquiring topographical map data based on the climbing route information, generation AI model means for analyzing the topographical map data and generating how to read and write topographical features, 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 means for displaying the climbing concept map on the 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 information on the surrounding area 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 the terrain, including contour lines and topographic 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] "Topographic map data" refers to digital data based on topographic maps, and includes detailed information about the terrain.

[0979] A "generative AI model" refers to a model that uses artificial intelligence to perform a specific task, in this case, to generate 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 its surrounding information.

[0981] "Accommodation" refers to facilities where climbers can stay overnight, including 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 ways to read and write topographical features based on that information, and finally automatically creates a climbing concept map. A specific embodiment of this system is described below.

[0983] First, the user uses a device to input information about the mountain climbing route. 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 the following into the input form: "From the fifth station of Mt. Fuji to the summit, 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 retrieves the topographical map data. Specifically, the server uses the Google Maps API or OpenStreetMap API to retrieve the topographical map data related to the specified route. For example, the server sends a request to the API to "retrieve topographical map data from the fifth station of Mt. Fuji to the summit of Mt. Fuji."

[0985] The generative AI model on 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 readings and writings for 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 features."

[0987] The server then automatically creates a mountain climbing concept map using the reading and writing of the topographical 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 might perform a process such as "displaying the route from the fifth station of Mt. Fuji to the summit 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 device and displays it. Specifically, the mountain climbing concept map is displayed on the user's smartphone or PC. For example, the user can check on their smartphone screen "a mountain climbing concept map that visually displays the route from the fifth station to the summit of Mt. Fuji, along with each waypoint and points requiring caution."

[0989] Examples of concrete examples and prompts

[0990] Specific 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: Summit of Mt. Fuji

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

[0995] Points to be careful of: Steep slope at the seventh station

[0996] The server uses the Google Maps API to obtain topographical map data from the fifth station to the summit of Mount Fuji. Next, a generative AI model on 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 to the user's smartphone, where the user can view it on their screen.

[0997] Prompt Sentence Examples

[0998] "I am planning a climbing route from the fifth station of Mt. Fuji to the summit. I will include the sixth, seventh, and eighth stations as waypoints, and I need to be careful of the steep slope at the seventh 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] The user inputs the climbing route information using the 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 the input form.

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

[1005] Output: Climbing route information sent to the server

[1006] Step 2:

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

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

[1009] Input: Climbing route information

[1010] Output: Topographic 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 reading and writing methods 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 using specific icons and colors.

[1019] Input: Analysis results of terrain features

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

[1021] Step 5:

[1022] The server automatically creates a mountain climbing concept map using the reading and writing methods of the terrain features generated by the 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 indicated with yellow warning icons.

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

[1025] Output: Mountain climbing concept diagram

[1026] Step 6:

[1027] The server sends 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 map on the screen, which visually displays the route, each waypoint, and points requiring caution.

[1029] Input: Mountain climbing concept diagram

[1030] Output: Mountain climbing concept diagram 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] Autonomous vehicles are required to generate optimal driving routes based on topographical maps and road information, and to provide route maps that include points requiring special attention and surrounding information. However, current systems face the challenge of efficiently analyzing this information and visually displaying it.

[1034] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for receiving route information based on a topographical map as an input, artificial intelligence means for generating readings and writings of topographical features based on the route information, means for automatically creating a conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and 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 that includes points requiring particular attention and surrounding information.

[1035] A "topographic map" is a map that contains detailed information about the terrain, visually showing the undulations 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] "Artificial intelligence means" refers to 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, as well as the characteristics of specific points.

[1039] "Reading and writing" refers to methods for understanding and visually representing topographical features.

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

[1041] "Display means" refers to a device or system for visually displaying the generated conceptual diagram and 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 an automated driving vehicle 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 (AI model training and inference), OpenStreetMap API (topographical map and road information acquisition), Python (programming language)

[1047] Data processing and calculation

[1048] Data Entry

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

[1050] Analysis using AI models

[1051] The server uses TensorFlow to analyze the acquired topographical map and road information, generating readings and writings of terrain features, which in turn identify areas requiring special attention (such as sharp curves, steep gradients, and intersections).

[1052] Route Optimization

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

[1054] Generate a 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 requiring special attention and surrounding information.

[1056] Specific examples

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

[1058] Starting point: 35.6895, 139.6917

[1059] Destination point: 35.6586, 139.7454

[1060] Waypoints: 35.6733, 139.7100

[1061] Particular caution is required: 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, the server calculates the optimal driving route, generates a route map, and displays it on the autonomous vehicle's display, allowing the user to check a safe and efficient driving route.

[1063] The flow of the specific processing 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 autonomous vehicle's on-board computer, which then retrieves these points. The input includes latitude and longitude coordinates. The output is passed on to the next step.

[1066] Step 2:

[1067] The server uses the OpenStreetMap API to get the topographic 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 topographic map and road information. As output, the topographic map and road information are passed to the next step.

[1068] Step 3:

[1069] The server uses TensorFlow to analyze the acquired topographical map and road information and generate ways to read and write the topographical features. The topographical map and road information acquired in step 2 are used as input. The server uses an AI model to analyze the topographical features and identify points that require special attention (sharp curves, steep slopes, intersections, etc.). The output is the ways to read and write the topographical features, which 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. The input is the optimal driving route calculated in step 4. The server generates the route map and visually displays points requiring special attention and surrounding information. The output is a route map that the user can view on the display.

[1074] This series of processes allows the user to check a safe and efficient driving route.

[1075] Example 2

[1076] Next, a description will be given of 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."

[1077] Conventional mountain climbing route information input systems have had problems in that it is difficult for users to intuitively input mountain climbing route information based on topographical maps, and the generated mountain climbing concept maps are visually difficult to understand. Furthermore, it is difficult to automatically create detailed mountain climbing concept maps that include 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 to generate readings and descriptions of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and descriptions of 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 users to intuitively input mountain climbing route information and 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 information on the surrounding area in addition to the mountain climbing route.

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

[1081] "Mountain climbing route information" is information about the mountain climbing route planned by the 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] "Means for transmitting as digital data" refers to a communication means for transmitting the climbing route information entered 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 the climbing route and the surrounding terrain features.

[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 operates 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 device screen using a mouse or stylus. The user can intuitively input route information by drawing a line on the topographical map or clicking points. For example, the user can specify a climbing route by dragging the mouse from the starting point to the finish point and drawing a line.

[1091] Next, the device sends 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.), such as the coordinates of the line's start and end points, and information on the line's color and thickness.

[1092] The server receives the climbing route information sent from the device and uses a generative AI model to analyze how to read and write the topographical features. The server then 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 represented using colors, line thickness, symbols, etc. For example, the climbing route is displayed with a thick red line, and surrounding topographical features are represented with blue dotted lines and green symbols.

[1093] The server then sends 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 terrain features displayed in a visually easy-to-understand format. This allows the user to obtain information that is useful when planning a mountain climbing trip.

[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 finish point, the device sends that information as digital data to the server. The server uses a generative AI model to analyze the characteristics of the terrain and generates a conceptual map of the mountain climbing route, displaying it with a thick red line and surrounding topographical features with blue dotted lines and green symbols. The server sends this conceptual 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 in red on the topographical map. The system will create a conceptual map of the climb based on that information and display your climbing route in thick red."

[1097] "Click multiple points on the topographical map to specify your climbing route. The system will create a conceptual map of your climbing route based on that information and display it as 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 mountain climbing route on the topographical map displayed on the device screen using a mouse or stylus. Specifically, the user drags the mouse to draw a line from the starting point to the goal point. This operation inputs the coordinate information of the mountain climbing route and the drawing format (line color, thickness, etc.).

[1103] Step 2:

[1104] The terminal sends 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, as well as 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 the route passes through and extracts detailed information about the climbing route.

[1109] Step 4:

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

[1111] The server automatically generates a mountain climbing concept map based on the analysis results. The input includes information on the analyzed terrain features. 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 surrounding terrain features are represented by blue dotted lines and green symbols.

[1112] Step 5:

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

[1114] The server sends 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 sends 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 device screen. The input includes the data of the mountain climbing concept map sent from the server. The user checks the mountain climbing route and the features of the terrain 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 features of the surrounding terrain.

[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] Conventional climbing route information input systems have had problems in that it is difficult for users to intuitively input climbing route information based on topographical maps, and the generated climbing concept maps are visually difficult to understand. Furthermore, it is difficult to automatically create detailed climbing concept maps that include surrounding information other than the climbing route. This makes 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 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 topographical features generated by the AI ​​means, means for inputting route information by drawing the 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. This enables users 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" is information about the mountain climbing route planned by the climber, and includes the route and points of the route drawn on a topographical map.

[1125] "AI means" means means that use artificial intelligence technology to analyze data and automatically perform specific tasks.

[1126] A "mountain climbing concept map" is a diagram that visually represents mountain climbing routes 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 by which a user can input mountain 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 uses colors, line thickness, symbols, etc. to express information and is easy for users to understand intuitively.

[1129] The "means for analyzing route information" is 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 how to read and write the topographical features generated by the AI ​​means; means for inputting route information by drawing the 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 head-mounted display. This route information is sent to the server, where it is analyzed by AI means.

[1134] The AI ​​tool analyzes the input route information and generates readings and writings of terrain features. This is done using 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 thicknesses, 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] Specific examples

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

[1138] Prompt Sentence Examples

[1139] Below are some example prompts to input to the generative AI model:

[1140] Please create an application where the user can draw a route on a map, and the route will be 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 with AI, and generating a route map.

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

[1142] The flow of the specific processing 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 device's application, selects and loads a map data file, and the map data is displayed on the device's screen.

[1148] Step 2:

[1149] The user draws a route on a map.

[1150] Input: Route drawing information via user touchscreen or mouse input

[1151] Output: Rendered route information

[1152] How it works: The user draws a climbing route on a map using a finger or a stylus. The route information is saved on the device and sent to the server.

[1153] Step 3:

[1154] The server analyzes the received route information.

[1155] Input: Route information drawn

[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 plot 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: 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 displays the received data and provides the user with a visually easy-to-understand route map.

[1168] Step 6:

[1169] Users see a visually easy-to-understand route map.

[1170] Input: 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] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1174] "Example 1"

[1175] One embodiment of the present invention provides a system incorporating an emotion engine that recognizes a user's emotions. This system includes an AI means that receives climbing route information based on a topographical map and generates readings and writings of topographical features based on the climbing route information, and a means for automatically creating a climbing concept map using the readings and writings of the topographical features generated by the AI ​​means. The system also includes an emotion engine that recognizes the user's emotions. This emotion engine recognizes the user's emotional state, for example, from the user's facial expression, tone of voice, text input, etc., and then adjusts the readings and writings of the topographical features and the display method of the climbing concept map according to the user's emotional state. For example, if the system recognizes that the user is nervous, it provides more detailed topographical information. Furthermore, if the system recognizes that the user is relaxed, it provides only the minimum necessary information, thereby providing optimal information according to the user's emotional state.

[1176] "Example 2"

[1177] Another embodiment of the present invention provides a system in which an emotion engine adjusts the display method of a mountain climbing conceptual map in accordance with a user's emotional state. Similar to the above-described embodiment, this system includes an AI means for inputting mountain climbing route information based on a topographical map and generating readings and descriptions of topographical features based on the mountain climbing route information, and a means for automatically creating a mountain climbing conceptual map using the readings and descriptions of topographical features generated by the AI ​​means. The system also includes an emotion engine that recognizes the user's emotions. The emotion engine adjusts the display method of the mountain climbing conceptual map in accordance with the user's emotional state. For example, if the emotion engine recognizes that the user is feeling anxious, it highlights and displays more detailed topographical information and safety information. Furthermore, if the emotion engine recognizes that the user is excited, it provides an optimal display method in accordance with the user's emotional state, such as by increasing the number of mountain climbing route options.

[1178] The processing 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 tools, generate readings and writings of topographical features based on the input climbing route information.

[1182] Step 3: Automatically create a mountain climbing concept map using the generated reading and writing methods for the topographical 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 tools, generate readings and writings of topographical features based on the input climbing route information.

[1188] Step 3: Automatically create a mountain climbing concept map using the generated reading and writing methods for the topographical features.

[1189] Step 4: Recognize the user's emotional state using the emotion engine.

[1190] Step 5: Adjust the display method of the mountain climbing concept diagram according to the recognized emotional state of the user.

[1191] Example 1

[1192] 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 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. Furthermore, since the system does not provide information based on the user's emotional state, it is difficult to provide information optimal for the user's situation. This leads to the issue of insufficient safety and comfort during mountain climbing.

[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 means for inputting mountain climbing route information based on a topographical map, artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the artificial intelligence means, emotion recognition means for recognizing the user's emotion, and means for adjusting the information provided in accordance with the user's emotional state 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 user's emotional state.

[1196] A "topographic map" is a map that shows detailed information about the terrain and is used to plan and analyze mountain climbing routes.

[1197] "Mountain climbing route information" is information about the route planned by the climber, such as the starting point and ending point of the mountain climbing, intermediate points, and points requiring special caution.

[1198] "Artificial intelligence means" means technology that includes algorithms or models for analyzing input data and automatically performing specific tasks.

[1199] "How to read and write topographical features" is a method of analyzing information obtained from topographical maps and expressing it in a format that is easy for climbers to understand.

[1200] A "climbing concept map" is a diagram that visually shows a climbing route and its 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 a technique for changing the content and format of information provided depending on the user's emotional state.

[1203] MODE FOR CARRYING OUT THE INVENTION

[1204] This system allows climbers to input climbing route information based on a topographical map, and then uses that information to generate readings and writings of topographical features, ultimately creating a climbing concept map. Furthermore, by combining it with an emotion recognition means that recognizes the user's emotions, the system provides information according to the user's emotional state.

[1205] System configuration

[1206] 1. Enter climbing route information

[1207] The user inputs information about the mountain climbing route, including the start and end points of the climb, intermediate points, and points requiring special attention.

[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 descriptions 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 terrain features generated by AI. This mountain climbing concept map includes surrounding information (such as mountain huts) in addition to 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 device 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 delivery algorithms

[1226] Specific examples

[1227] The user opens a dedicated smartphone application and inputs information about the climbing route. For example, they input "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 the climb including detailed topographical information.

[1232] Prompt Sentence Examples

[1233] "Please enter your 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 climbing route information. Specifically, the user opens a dedicated smartphone application and enters "route from the fifth station of Mt. Fuji to the summit, stopping at mountain huts along the way" into the input form.

[1238] Input: Climbing route information such as the start and end points, 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 and 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 an artificial intelligence model (e.g., TensorFlow) to analyze detailed information on the topographic map.

[1244] Output: Generates readings and writings of topographical features

[1245] Specific operation: The server analyzes the received data, analyzes the detailed information of the topographic map using TensorFlow, and generates how to read and write the topographic 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 AI. This mountain climbing concept map includes information about the surrounding area (mountain huts, etc.) in addition to 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 area.

[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 device 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: User's emotional state obtained from 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 are unable to provide appropriate information when the user is tense or relaxed. Furthermore, 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: 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 topographical features generated by the AI ​​means; means including an emotion engine for recognizing the user's emotions; and means for adjusting the information provided in accordance with the user's emotional state recognized by the emotion engine. This makes it possible to provide optimal information in accordance with the user's emotional state.

[1269] A "topographic map" is a map that shows detailed information about the terrain, visually representing hiking routes and topographical features.

[1270] "Mountain climbing route information" includes information such as the start point, end point, waypoints, and points requiring special attention on the route planned by the climber.

[1271] "AI means" refers to means for performing a specific task using artificial intelligence, and in this case refers to the ability to generate readings and writings of topographical features.

[1272] "Reading and writing topographic features" refers to the interpretation of detailed topographic information based on topographic maps and its representation in visual or textual form.

[1273] A "climbing concept map" is a visual representation of a climbing route and its surrounding information, making it easier for climbers to understand the route.

[1274] An "emotion engine" is a system that recognizes a user's emotional state from facial expressions, tone of voice, text input, etc.

[1275] The "means for adjusting the information provided" is a means for changing the level of detail and content of the information provided depending on the emotional state of the user.

[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 how to read and write the topographical features generated by the AI ​​means; means including an emotion engine for recognizing the user's emotions; and means for adjusting the information provided 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 waypoints, which provides the climbing route information to the system.

[1283] 2. Route Planning: The server uses the RoutePlanner library to generate readings and writings of topographical 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 information about the surrounding area (e.g., mountain huts) in addition to the hiking 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, it provides detailed topographical information, but if the user is relaxed, it provides only the minimum necessary information.

[1287] 6. Display: The device displays the adjusted information on the smartphone screen.

[1288] Specific examples

[1289] User input: Departure point "Tokyo Station", destination point "Mount Fuji", intermediate point "Yokohama Station"

[1290] Emotion recognition: If the user is perceived as nervous, detailed terrain information (sharp curves, slopes, etc.) is provided.

[1291] Display: Along with a detailed driving concept map, information on nearby gas stations and rest areas is also displayed.

[1292] Prompt Sentence Examples

[1293] If a user inputs the starting point "Tokyo Station," the destination "Mount Fuji," and the waypoint "Yokohama Station," and the emotion recognition engine recognizes the user's emotion as "tension," generate a program that provides detailed topographical and surrounding information.

[1294] The flow of the specific processing 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 a smartphone application, the user inputs the starting point "Tokyo Station," the destination point "Mount 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 topographical features based on the input route information. The server analyzes the received information on the starting point, destination, and intermediate points, and retrieves the corresponding topographical information from a topographical map database. Based on the retrieved topographical information, an AI model generates readings and writings of topographical features. The generated data is used in the next step.

[1299] Step 3:

[1300] The server uses the MapGenerator library to create a driving concept map. The server generates a driving concept map including the climbing route and its surrounding information (mountain huts, etc.) based on how to read and write 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 their 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 it provides based on the recognized emotional state. The server determines the level of detail of the information it provides based on the emotional state determined in step 4. For example, if the user is nervous, it provides detailed topographical information, and if the user is relaxed, it provides only the minimum necessary information. 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. Based on the displayed information, the user can check the climbing route safely and efficiently.

[1307] Example 2

[1308] Next, a description will be given of 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."

[1309] In conventional mountain climbing route information input systems, it was difficult for users to intuitively input mountain climbing route information based on topographical maps, and the generated mountain climbing concept map was not adjusted according to the user's emotional state, making it difficult to provide information that was easy for users to understand.Furthermore, it was also insufficient to create detailed mountain climbing concept maps 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 means for inputting mountain climbing route information based on a topographical map, artificial intelligence means for generating readings and writings of topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the readings and writings of the topographical features generated by the artificial intelligence means, and emotion recognition means for recognizing the user's emotional state and adjusting the display method of the mountain climbing concept map in accordance with the emotional state. This allows the user to intuitively input mountain climbing route information, and the generated mountain climbing concept map is adjusted according to the user's emotional state, 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 concept map that includes surrounding information other than the mountain climbing route.

[1312] A "topographic map" is a map that shows the terrain and the location of features, and is used for planning mountain climbing routes and navigation.

[1313] "Mountain climbing route information" is information about the mountain climbing route planned by the climber, including the route drawn on a topographical map and its details.

[1314] "Artificial intelligence means" refers to technology that uses machine learning and data analysis to automatically perform specific tasks, and is used in the present invention to generate readings and writings of topographical features.

[1315] "Topographical features" refer to the undulations and features of the terrain shown on a topographical map, and are used to evaluate the difficulty and dangerous areas of a climbing route.

[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 important information for climbers, such as evacuation sites and water sources.

[1319] This invention is a system that allows climbers to intuitively input climbing route information based on a topographical map, and the generated climbing concept map is adjusted according to the user's emotional state. Specific embodiments of this system are 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] The server then analyzes the received climbing route information. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate reading and writing instructions 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 the generated topographical features are read and written. 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] Furthermore, the server uses emotion recognition tools (e.g., IBM Watson or Microsoft Azure Cognitive Services) to recognize the user's emotional state. If the user feels anxious, the server will highlight and display detailed terrain information and safety information. 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 hiking route options.

[1324] As a concrete example, the following prompt sentence is input into the generative AI model:

[1325] Example prompt sentence:

[1326] Based on the climbing route information drawn by the user on a topographical map, use an AI model to generate reading and writing instructions for terrain features, creating a visually easy-to-understand climbing concept map. Also, use an emotion engine to recognize the user's emotional state and adjust the display accordingly. For example, if the user is feeling anxious, emphasize detailed terrain information, and if they are excited, increase the number of climbing route options.

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

[1331] Step 2:

[1332] The server receives climbing route information sent from the terminal. The input is digitized climbing route information. The server analyzes this information and generates how to read and write the terrain features using a generative AI model (for example, TensorFlow or PyTorch). 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. The output is how to read and write the terrain features.

[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. Specifically, 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 an emotion recognition means. As input, it receives 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. Specifically, if the user feels anxious, the server highlights detailed topographical information and safety information. If the user feels excited, the server increases the number of mountain climbing route options. As output, it provides the optimal display method according to the user's emotional state.

[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 mountain climbing route information based on topographical maps, and the system does not provide information that reflects the user's emotional state, which means that the safety and comfort of the climber are not sufficiently ensured. Furthermore, autonomous vehicles also have the problem of not providing appropriate navigation to safely transport climbers to their destination.

[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 means for inputting mountain climbing route information based on a topographical map, AI means for generating readings and descriptions of topographical features based on the mountain climbing route information, means for automatically creating a mountain climbing concept map using the readings and descriptions of the topographical features generated by the AI ​​means, an emotion engine for recognizing the user's emotional state, means for adjusting the display method of the mountain climbing concept map in accordance with the emotional state recognized by the emotion engine, and means installed in the 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 the terrain.

[1343] "Mountain climbing route information" is information about the route that a mountain climber plans to take when climbing a mountain.

[1344] "AI means" means technical means for performing a specific task using artificial intelligence.

[1345] "Topographic features" refer to topographical characteristics such as mountains, valleys, and rivers on a topographic 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 that recognize the user's emotional state.

[1355] software

[1356] EmotionEngine: Technology for recognizing a user's emotional state and adjusting system behavior accordingly.

[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. Users can input climbing route information by drawing the route directly on the topographical map. This information is sent to the server and used for further processing.

[1361] Generate terrain features

[1362] The server uses AI Geography to generate readings and writings of terrain features based on the input climbing route information. AI Geography reads detailed information from the topographic map and generates terrain features. These 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 methods of the terrain features generated by AI Geography. 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 uses the Emotion Engine to recognize the user's emotional state. The Emotion Engine analyzes data obtained from cameras and sensors to determine the user's emotional state. For example, if the user is feeling anxious, the server will highlight safety information on the mountain climbing concept map. If the user is 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] Specific examples

[1368] For example, consider a climber getting into an autonomous vehicle and inputting a route to their 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 conceptual map of the climb. Next, Emotion Engine recognizes the user's emotional state and adjusts the display accordingly. If the user feels anxious, safety information is emphasized, and if the user feels excited, the options for the climbing route are increased.

[1369] Prompt Sentence Examples

[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 terrain features. Use an emotion engine to adjust the navigation information according to the user's emotional state."

[1371] The flow of the specific processing 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 hiking route information

[1375] Output: Climbing route information

[1376] Specific operation: The 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 terrain features using AI Geography.

[1379] Input: Climbing route information

[1380] Output: How to read and write topographic features

[1381] Specific operation: The server inputs the received climbing route information into AI Geography and analyzes the detailed information of the topographic map to generate terrain 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 the climbing route and surrounding information (mountain huts, etc.) based on the topographical features generated by AI Geography.

[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: User's emotional state

[1391] How it works: The server inputs data acquired from cameras and sensors into the Emotion Engine 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 diagram

[1395] Output: Adjusted climbing concept map

[1396] Specific operation: The server adjusts the display method of the mountain climbing concept map based on the user's emotional state recognized by the Emotion Engine. For example, if the user feels anxious, it highlights safety information, and if the user feels excited, it increases the options for mountain climbing routes.

[1397] Step 6:

[1398] The server sends 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 device, 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 audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[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 performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1404] Another example of generative AI is Gemini (internet search engine). <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 WAN (Wide Area Network) and / or a LAN (Local Area Network).

[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. 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 audio in accordance with instructions from the processor 46.

[1412] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1413] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1414] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1415] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[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 processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[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 climber's planned route, intermediate points, and points requiring special attention. Next, an AI within 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 by including surrounding information other than the climbing route (such as mountain huts).

[1422] "Example 2"

[1423] Another embodiment of the present invention allows climbers to input climbing route information based on a topographical map into the system in a format that is intuitively easy for them to understand. For example, climbing route information can be input by drawing the route directly on the topographical map. Furthermore, when the system automatically creates a climbing concept map using the reading and writing methods of topographical features generated by AI, it 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 represented using colors, line thicknesses, symbols, etc.

[1424] The processing 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 attention.

[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 detailed information from 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 includes surrounding information (such as mountain huts) in addition to 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 intuitively easy for climbers to understand. For example, climbing route information can be input by drawing the route directly on the 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 detailed information from the topographical map.

[1432] Step 3: The system automatically creates a mountaineering concept map using the AI-generated methods for reading and writing terrain features, and displays the map in a visually easy-to-understand format for climbers to understand. For example, it uses colors, line thicknesses, symbols, etc. to represent terrain features, climbing routes, and surrounding information.

[1433] Example 1

[1434] 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 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 record them appropriately. This made it difficult for climbers without specialized knowledge of topographical maps to create accurate climbing plans, and also made it difficult to create comprehensive climbing concept maps that included surrounding information (such as accommodations) 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 means for a climber to input climbing route information based on a topographical map, means for acquiring topographical map data based on the climbing route information, generation AI model means for analyzing the topographical map data and generating how to read and write topographical features, 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 means for displaying the climbing concept map on the 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 information on the surrounding area 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 the terrain, including contour lines and topographic 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] "Topographic map data" refers to digital data based on topographic maps, and includes detailed information about the terrain.

[1444] A "generative AI model" refers to a model that uses artificial intelligence to perform a specific task, in this case, to generate 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 its surrounding information.

[1446] "Accommodation" refers to facilities where climbers can stay overnight, including 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 ways to read and write topographical features based on that information, and finally automatically creates a climbing concept map. A specific embodiment of this system is described below.

[1448] First, the user uses a device to input information about the mountain climbing route. 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 the following into the input form: "From the fifth station of Mt. Fuji to the summit, 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 retrieves the topographical map data. Specifically, the server uses the Google Maps API or OpenStreetMap API to retrieve the topographical map data related to the specified route. For example, the server sends a request to the API to "retrieve topographical map data from the fifth station of Mt. Fuji to the summit of Mt. Fuji."

[1450] The generative AI model on 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 readings and writings for 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 features."

[1452] The server then automatically creates a mountain climbing concept map using the reading and writing of the topographical 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 might perform a process such as "displaying the route from the fifth station of Mt. Fuji to the summit 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 device and displays it. Specifically, the mountain climbing concept map is displayed on the user's smartphone or PC. For example, the user can check on their smartphone screen "a mountain climbing concept map that visually displays the route from the fifth station to the summit of Mt. Fuji, along with each waypoint and points requiring caution."

[1454] Examples of concrete examples and prompts

[1455] Specific 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: Summit of Mt. Fuji

[1459] Waypoints: 6th, 7th, 8th stations

[1460] Points to be careful of: Steep slope at the seventh station

[1461] The server uses the Google Maps API to obtain topographical map data from the fifth station to the summit of Mount Fuji. Next, a generative AI model on 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 to the user's smartphone, where the user can view it on their screen.

[1462] Prompt Sentence Examples

[1463] "I am planning a climbing route from the fifth station of Mt. Fuji to the summit. I will include the sixth, seventh, and eighth stations as waypoints, and I need to be careful of the steep slope at the seventh 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] The user inputs the climbing route information using the 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 the input form.

[1469] Input: Climbing route information (starting point, ending point, intermediate points, points requiring caution)

[1470] Output: Climbing route information sent to the server

[1471] Step 2:

[1472] The server receives the climbing route information input by the user and acquires topographical map data.

[1473] Specifically, the server uses the Google Maps API or OpenStreetMap API to retrieve topographic 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 reading and writing methods 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 using specific icons and colors.

[1484] Input: Analysis results of terrain features

[1485] Output: How to read and write topographical features

[1486] Step 5:

[1487] The server automatically creates a mountain climbing concept map using the reading and writing methods of the terrain features generated by the 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 indicated with yellow warning icons.

[1489] Input: Topographic map data, how to read and write topographic features

[1490] Output: Mountain climbing concept diagram

[1491] Step 6:

[1492] The server sends 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 map on the screen, which visually displays the route, each waypoint, and points requiring caution.

[1494] Input: Mountain climbing concept diagram

[1495] Output: Mountain climbing concept diagram displayed on the user's device

[1496] (Application example 1)

[1497] Next, a description will be given of Application Example 1 of Embodiment 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] Autonomous vehicles are required to generate optimal driving routes based on topographical maps and road information, and to provide route maps that include points requiring special attention and surrounding information. However, current systems face the challenge of efficiently analyzing this information and visually displaying it.

[1499] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for receiving route information based on a topographical map as an input, artificial intelligence means for generating readings and writings of topographical features based on the route information, means for automatically creating a conceptual map using the readings and writings of the topographical features generated by the artificial intelligence means, and 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 that includes points requiring particular attention and surrounding information.

[1500] A "topographic map" is a map that contains detailed information about the terrain, visually showing the undulations 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] "Artificial intelligence means" refers to 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, as well as the characteristics of specific points.

[1504] "Reading and writing" refers to methods for understanding and visually representing topographical features.

[1505] A "conceptual map" is a diagram that visually simplifies specific information and includes route and surrounding information.

[1506] "Display means" refers to a device or system for visually displaying the generated conceptual diagram and 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 an automated driving vehicle 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 (AI model training and inference), OpenStreetMap API (topographical map and road information acquisition), Python (programming language)

[1512] Data processing and calculation

[1513] Data Entry

[1514] Users input their starting point, destination, and intermediate points into the autonomous vehicle's on-board computer, which then uses the OpenStreetMap API to retrieve topographical and road information for the specified route.

[1515] Analysis using AI models

[1516] The server uses TensorFlow to analyze the acquired topographical map and road information, generating readings and writings of terrain features, which in turn identify areas requiring special attention (such as sharp curves, steep gradients, and intersections).

[1517] Route Optimization

[1518] The server calculates the optimal driving route based on the reading and writing of the terrain features generated by the AI ​​model, taking into account surrounding information (gas stations, rest areas, etc.).

[1519] Generate a 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 requiring special attention and surrounding information.

[1521] Specific examples

[1522] Example prompts to input to the generative AI model

[1523] Starting point: 35.6895, 139.6917

[1524] Destination point: 35.6586, 139.7454

[1525] Waypoints: 35.6733, 139.7100

[1526] Particular caution is required: 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, the server calculates the optimal driving route, generates a route map, and displays it on the autonomous vehicle's display, allowing the user to check a safe and efficient driving route.

[1528] The flow of the specific processing 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 autonomous vehicle's on-board computer, which then retrieves these points. The input includes latitude and longitude coordinates. The output is passed on to the next step.

[1531] Step 2:

[1532] The server uses the OpenStreetMap API to get the topographic 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 topographic map and road information. As output, the topographic map and road information are passed to the next step.

[1533] Step 3:

[1534] The server uses TensorFlow to analyze the acquired topographical map and road information and generate ways to read and write the topographical features. The topographical map and road information acquired in step 2 are used as input. The server uses an AI model to analyze the topographical features and identify points that require special attention (sharp curves, steep slopes, intersections, etc.). The output is the ways to read and write the topographical features, which 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. The input is the optimal driving route calculated in step 4. The server generates the route map and visually displays points requiring special attention and surrounding information. The output is a route map that the user can view on the display.

[1539] This series of processes allows the user to check a safe and efficient driving route.

[1540] Example 2

[1541] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1542] Conventional mountain climbing route information input systems have had problems in that it is difficult for users to intuitively input mountain climbing route information based on topographical maps, and the generated mountain climbing concept maps are visually difficult to understand. Furthermore, it is difficult to automatically create detailed mountain climbing concept maps that include 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 to generate readings and descriptions of topographical features based on the mountain climbing route information, a means for automatically creating a mountain climbing conceptual map using the readings and descriptions of 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 users to intuitively input mountain climbing route information and 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 information on the surrounding area in addition to the mountain climbing route.

[1545] A "topographic map" is a map that visually represents detailed information about the terrain.

[1546] "Mountain climbing route information" is information about the mountain climbing route planned by the 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] "Means for transmitting as digital data" refers to a communication means for transmitting the climbing route information entered 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 the climbing route and the surrounding terrain features.

[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.

[1553] "Local information" refers to information about accommodation and other important points related to the climbing route.

[1554] 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 operates in cooperation with the user, the terminal, and the server.

[1555] First, the user draws a climbing route on the topographical map displayed on the device screen using a mouse or stylus. The user can intuitively input route information by drawing a line on the topographical map or clicking points. For example, the user can specify a climbing route by dragging the mouse from the starting point to the finish point and drawing a line.

[1556] Next, the device sends the climbing route information drawn by the user to the server as digital data. This data includes the route coo...

Claims

[Claim 1] A means for acquiring mountain climbing route information including information on the start point, end point, and waypoints of a mountain climbing route planned by a mountain climber, as well as information on points where the mountain climber determines caution is necessary; means for acquiring topographical map data related to the climbing route from a topographical map database based on the climbing route information; a means for using a generative AI model to analyze topographical features at each point along the climbing route based on the topographical map data to identify steep slopes, and generating instructions for how to depict the topographical features, which specify a display method including an icon or color to be used to highlight the steep slope features; a means for creating a mountain climbing concept map related to the mountain climbing route based on the instructions; means for determining an emotional state of the climber using an emotion engine; a means for adjusting a display method of the mountain climbing conceptual map so that, when the emotional state indicates tension, the level of detail of topographical information provided in the mountain climbing conceptual map is increased, and, when the emotional state indicates anxiety, the safety information provided in the mountain climbing conceptual map is emphasized; and a means for transmitting the mountain climbing concept map to a climber's terminal. system.

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