System

Abstract

A system is provided.SOLUTION: A system including means for a user to input a region, a means of transportation, a distance, and a theme to be drawn, means for transmitting input data to a server, means for analyzing map data based on the received data, means for generating a specific shape based on the theme, means for generating a route using an AI model in consideration of safety and traffic rules, means for verifying and adjusting the generated route, means for transmitting final course data to a terminal, and means for displaying the course data on the terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] When enjoying GPS art, users need to design their own courses or trace existing courses, which takes a lot of time and effort. There is also the possibility that safety may not be ensured. Therefore, there is a need for a system that allows users to easily create safe and efficient GPS art courses. [Means for solving the problem]

[0005] The system includes a means for a user to input the area, mode of transportation, distance, and theme to be drawn, a means for transmitting the input data to a server, a means for the server to analyze map data based on the received data, a means for generating a specific shape based on the theme, a means for generating a route using an AI model taking safety and traffic rules into consideration, a means for verifying and adjusting the generated route, a means for transmitting the final course data to a terminal, and a means for the terminal to display the course data.This allows users to easily create safe and efficient GPS art courses.By further including a means for generating a route that includes tourist attractions, the system can also be used as an activity in tourist destinations.

[0006] A "user" is an individual who intends to use the system to generate a course of GPS art.

[0007] "Region" refers to the broad or specific geographic area where a user wants to generate a GPS art course.

[0008] "Transportation" refers to the method or means (e.g., running, walking, biking, car) used by a user to travel the course of the GPS Art.

[0009] "Distance" refers to the total length of the generated GPS Art course, typically measured in kilometers or miles.

[0010] A "theme" refers to a specific shape or pattern (e.g., heart, star) that the user wants to express in GPS art.

[0011] A "server" is a computing device that receives input data from a user and returns the processed results, and is a device that performs central processing of the system.

[0012] "Map data" refers to digital map information that includes information on the topography, roads, facilities, etc. of a specified area.

[0013] A "specific shape based on a theme" is a specific pattern or shape that is generated according to a theme selected by the user.

[0014] An "AI model" is an algorithm that uses artificial intelligence technology to perform complex calculations and judgments, and is used to generate safe and efficient routes.

[0015] A "route" is a set of paths along which a user travels, forming a trajectory for forming a GPS map.

[0016] "Verification" is the process of checking whether the generated route complies with existing traffic rules and ensures safety.

[0017] A "terminal" is a device used by a user, such as a smartphone or PC, that is used to communicate with the server and display course data.

[0018] "Course data" refers to detailed information about the route of the generated GPS art, including information such as the route on the map, distance, and time.

[0019] "Tourist attractions" are famous places and sights that are included on the route generated by the user and that attract the user's interest. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] System Overview

[0042] This system automatically generates a GPS art course based on user input data. Users input their area, mode of transportation, distance, and the theme they want to draw, and a safe and efficient route is generated based on that information. It can also generate a course that takes into account traffic rules and includes tourist attractions.

[0043] composition

[0044] 1. User-entered data

[0045] region

[0046] Transportation

[0047] distance

[0048] Themes I want to draw

[0049] Safety priority or tourist attraction priority

[0050] 2. Server Functions

[0051] Receiving input data

[0052] Map data acquisition and analysis

[0053] Shape generation based on user themes

[0054] Route generation using AI models

[0055] Verifying route safety and traffic rules

[0056] Sending course data to your device

[0057] 3. Device Features

[0058] Providing an input interface

[0059] Receiving and displaying course data

[0060] Program processing

[0061] 1. Receiving user input

[0062] Device: The user opens the application on the device and inputs the area, mode of transportation, distance, theme to be drawn, safety priority or tourist attraction priority.

[0063] 2. Sending input information to the server

[0064] Terminal: When the user presses the "Generate" button, the input data is sent to the server.

[0065] 3. Server-side data processing

[0066] server:

[0067] Receives input data and retrieves map data for the specified area.

[0068] The acquired map data is analyzed and information such as major roads and intersections is extracted.

[0069] Generate specific shapes based on user themes.

[0070] An AI model is used to generate routes that take safety and traffic rules into consideration.

[0071] If you include a tourist attraction, incorporate its location into the route.

[0072] Verify that the generated route complies with traffic rules and is safe.

[0073] The verified course data is sent to the device.

[0074] 4. Receiving and Displaying Course Information

[0075] Terminal: Displays the course data received from the server to the user. The user can check information such as the course map, travel method, total distance, required time, and tourist attractions along the way.

[0076] Specific examples

[0077] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[0078] 1. Receiving user input

[0079] Device: The user enters the following information into the application: Shibuya Ward, Running, 5km, Heart, Safety First.

[0080] 2. Sending input information to the server

[0081] Terminal: Press the "Generate" button to send the information to the server.

[0082] 3. Data Processing

[0083] server:

[0084] Obtain map data for Shibuya Ward and analyze road information.

[0085] Generate a heart-shaped pattern and check if it is suitable for 5 kilometers.

[0086] Using AI models, routes that are safe and comply with traffic rules are generated.

[0087] The route will include tourist attractions such as the Hachiko statue and Yoyogi Park.

[0088] Simulate the generated route to ensure it is safe and adjust it if necessary.

[0089] The final course data is sent to the device.

[0090] 4. View course information

[0091] Terminal: Displays course information to the user, including course maps, transportation methods, distance, time required, and points of interest.

[0092] In this way, users can easily create safe and efficient GPS art courses.

[0093] The processing flow will be explained below.

[0094] Step 1:

[0095] User: Opens the application on the device. The user inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions.

[0096] Step 2:

[0097] Terminal: When the user presses the "Generate" button, the entered data is sent to the server, including the area, mode of transportation, distance, theme, and safety or tourist attraction priority.

[0098] Step 3:

[0099] Server: Analyzes the data received from the device. Specifically, it retrieves map data for the area specified by the user and obtains detailed information from a database, including road information, intersections, traffic lights, and other traffic infrastructure information.

[0100] Step 4:

[0101] Server: Performs thematic analysis. Based on a theme entered by the user (e.g., "heart"), it runs an algorithm to generate a specific shape and creates the patterns that form that shape.

[0102] Step 5:

[0103] Server: Generates a route using an AI model. This generates a route that matches the specified distance based on the acquired map data and thematic shape information. Route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[0104] Step 6:

[0105] Server: Adjust the route to include tourist attractions. If the user sets a high priority for a tourist attraction, the server will incorporate the tourist attraction (e.g., Hachiko Statue, Yoyogi Park, etc.) into the route and recalculate the route to reach that attraction.

[0106] Step 7:

[0107] Server: Validates the generated route, simulating whether it complies with traffic rules and ensures safety, and fine-tunes the route if necessary.

[0108] Step 8:

[0109] Server: Prepares the final course data after verification and sends it to the device.

[0110] Step 9:

[0111] Terminal: Displays the course data received from the server to the user. The displayed content includes the course map, travel method, total distance, estimated time required, and tourist attractions along the way.

[0112] Step 10:

[0113] User: Checks the provided course information, and if satisfied, prepares to actually exercise the course.

[0114] Example 1

[0115] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0116] Conventional route planning systems lack the ability to generate specific shapes based on user themes, and it is difficult to generate routes that fully consider safety and traffic rules. Furthermore, generating routes that include tourist attractions and verifying and adjusting the generated routes are time-consuming, making it difficult for users to easily obtain efficient and safe routes.

[0117] 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.

[0118] In this invention, the server includes means for acquiring and analyzing map data based on input data, means for generating a specific shape based on a theme, and means for inputting a prompt sentence to the AI ​​model to generate a route that takes safety and traffic rules into consideration, thereby enabling a user to easily generate a route with a specific shape based on a theme and obtain an efficient course that complies with safety and traffic rules.

[0119] A "region" is a particular geographic area that a user specifies when generating a route.

[0120] "Transportation" refers to the method or mode of transportation used by a user to travel a route, including, for example, walking, cycling, or driving.

[0121] "Distance" is the length of the route specified by the user, typically expressed in kilometers.

[0122] The "theme to be drawn" indicates the shape and purpose of the route that the user wants to generate, and includes a specific shape or pattern.

[0123] "Safety priority" is an index that indicates the priority of safety in route generation.

[0124] The "priority of tourist attractions" is an index that indicates the priority with which tourist attractions are emphasized in route generation.

[0125] "Map data" is a data set containing geographic information for a particular area, including information on roads, intersections, etc.

[0126] The "particular shape" refers to a particular pattern or shape that is generated based on a user's theme.

[0127] An "AI model" is a computational model that uses artificial intelligence to analyze data and perform specific tasks.

[0128] A "prompt sentence" is an input sentence used to prompt an AI model to perform a specific task.

[0129] "Generating a route" means calculating and determining a route that takes safety and traffic rules into consideration based on data input by the user.

[0130] "Validation" is the process of checking whether the generated route is correct and complies with certain conditions.

[0131] "Adjustment" means making necessary corrections based on the results of verification.

[0132] "Course data" is a detailed data set that includes the generated route, including route coordinates, distance traveled, time required, etc.

[0133] A "terminal" is a hardware device through which a user enters input data and receives final course information.

[0134] MODE FOR CARRYING OUT THE INVENTION

[0135] System Overview

[0136] This invention is a system that automatically generates routes based on user input data. Users input their area, mode of transportation, distance, and the theme they want to depict, and a safe and efficient route is generated based on that information. Furthermore, traffic rules are taken into account and tourist attractions can be included in the route. The operation of the system will be explained in detail using a specific example.

[0137] Hardware and software used

[0138] Device: User device such as a smartphone or tablet

[0139] Server: High-performance computing server

[0140] Map Data API: Google Maps API

[0141] Geographic information processing libraries: Geopy, Fiona

[0142] Shape manipulation library: Shapely

[0143] AI model: OpenAI GPT-3 model

[0144] Map display libraries: Mapbox, Leaflet

[0145] Program processing

[0146] 1. Receiving user input

[0147] Device: The user opens the application on their device and enters the area (e.g., Shibuya Ward), mode of transportation (e.g., running), distance (e.g., 5 kilometers), theme to draw (e.g., heart), and safety priority or tourist attraction priority (e.g., safety).

[0148] 2. Sending input information to the server

[0149] Terminal: When the user presses the "Generate" button, the input data is converted to JSON format and a POST request is sent to the server's API endpoint.

[0150] 3. Server-side data processing

[0151] Server: Receives input data and retrieves map data for the specified area (Shibuya Ward) using the Google Maps API.

[0152] Server: Analyzes the acquired map data and extracts information such as major roads and intersections using geographic information processing libraries such as Geopy and Fiona.

[0153] Specifically, the map data is parsed and the locations of road segments and intersections are stored in list format.

[0154] Server: Generates specific shapes (e.g., hearts) based on the user's theme. Shape manipulation libraries such as Shapely are used for shape generation.

[0155] Specifically, a heart-shaped Bezier curve is generated and a route is created along it.

[0156] Server: Enter a prompt into a generative AI model (e.g., OpenAI's GPT-3) to generate an optimal route. An example prompt is as follows:

[0157] Prompt statement:

[0158] The user is looking for a 5-kilometer running course in Shibuya, Tokyo. The course should be heart-shaped, and safety is a priority. Generate a route that passes by the Hachiko statue and Yoyogi Park as much as possible.

[0159] 4. The server verifies traffic rules and safety

[0160] Server: Simulates whether the generated route complies with traffic rules and is safe. The simulation uses traffic rule-related datasets and a rule engine.

[0161] As a specific example, check whether there are traffic lights at intersections or whether there are pedestrian-only roads.

[0162] Server: If necessary, fine-tune the output of the AI ​​model to align with safety and traffic rules.

[0163] 5. The generated route data is sent to the device.

[0164] Server: Once the final route is validated, it converts the route data into JSON format and sends it to the device, including route coordinates, distance traveled, travel time, and location information of tourist attractions.

[0165] 6. The device will display the route information.

[0166] Terminal: Analyzes the route data received from the server and displays it to the user. A map display library such as Mapbox or Leaflet is used for displaying the data.

[0167] For example, the system draws a route on a map, places pins at each tourist spot, and displays detailed information such as the mode of transportation, total distance, and required time on the screen.

[0168] Specific examples

[0169] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[0170] User: Enters "Shibuya Ward, running, 5km, heart, safety first" into the app.

[0171] Terminal: Press the "Generate" button and the data will be sent to the server in JSON format.

[0172] Server: Obtains Shibuya Ward map data via the Google Maps API and analyzes road information using the Geopy library. Shapely generates a heart-shaped pattern, and a GPT-3 model generates a safe route, taking into account routes that pass through the Hachiko statue and Yoyogi Park.

[0173] Server: Validates the generated route based on traffic rules and safety, and sends the final route data to the device.

[0174] Terminal: The received route is displayed on a map, and the user can check the course map, travel method, total distance, required time, and tourist attractions.

[0175] This process allows users to easily generate safe and efficient routes with thematic geometries.

[0176] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0177] Step 1:

[0178] User: Opens the application and enters the area (e.g. Shibuya Ward), mode of transportation (e.g. running), distance (e.g. 5 kilometers), theme to draw (e.g. heart), and safety priority or tourist attraction priority (e.g. safety).

[0179] Input: Region, mode of transport, distance, theme, safety or tourist attraction priority

[0180] Output: User input data (JSON format)

[0181] Step 2:

[0182] Terminal: Validates the entered data, and when the user presses the "Generate" button, converts the input data into JSON format and sends it to the server.

[0183] Input: User-entered data

[0184] Data processing: Convert user input data into JSON format

[0185] Output: POST request to the server

[0186] Step 3:

[0187] Server: Receives input data and retrieves map data for the specified area (Shibuya Ward) using the Google Maps API.

[0188] Input: User-entered data

[0189] Data processing: Retrieving and parsing map data

[0190] Output: Parsed map data (a list containing road and intersection information)

[0191] Step 4:

[0192] Server: Analyzes the acquired map data and extracts information on major roads and intersections.

[0193] Input: Map data

[0194] Data processing: Analysis of map data using Geopy and Fiona libraries

[0195] Output: A list of extracted road segments and intersections

[0196] Step 5:

[0197] Server: Generates a specific shape (e.g., heart) based on the user's theme.

[0198] Input: User theme, list of road segments and intersections

[0199] Data processing: Shape generation using the Shapely library

[0200] Output: Generated theme shape (e.g. heart-shaped route)

[0201] Step 6:

[0202] Server: Enters a prompt into a generative AI model (e.g., GPT-3) and generates a route that takes safety and traffic rules into consideration.

[0203] Input: Generated theme shapes

[0204] Data processing: Route generation using an AI model based on prompts

[0205] Output: Initial generated route

[0206] Example prompt sentence:

[0207] Prompt statement:

[0208] The user is looking for a 5-kilometer running course in Shibuya, Tokyo. The course should be heart-shaped, and safety is a priority. Generate a route that passes by the Hachiko statue and Yoyogi Park as much as possible.

[0209] Step 7:

[0210] Server: Simulates whether the generated route complies with traffic rules and is safe. Adjusts the route if necessary.

[0211] Input: Initial generated route, traffic rule dataset

[0212] Data processing: Verification and adjustment based on traffic rules and safety

[0213] Output: Final generated route

[0214] Step 8:

[0215] Server: Once the final route is validated, it converts the route data into JSON format and sends it to the device.

[0216] Input: Final generated route

[0217] Data processing: Converting route data to JSON format

[0218] Output: Send route data to the device

[0219] Step 9:

[0220] Terminal: Analyzes the route data received from the server and displays it to the user. A map display library such as Mapbox or Leaflet is used for displaying the data.

[0221] Input: Route data received from the server

[0222] Data processing: Route data analysis and mapping

[0223] Output: User-visible route map, detailed information such as travel methods, total distance, travel time, and points of interest

[0224] The system allows users to easily generate safe and efficient routes with specific geometries and view all the necessary details.

[0225] (Application example 1)

[0226] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0227] The problem that this invention aims to solve is to provide an optimal route for delivery staff to travel to multiple delivery destinations efficiently and safely in a food delivery service.The invention also aims to build a system that can provide added value by generating routes that include tourist attractions, allowing delivery staff to discover the charms of the area while performing delivery work.

[0228] 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.

[0229] In this invention, the server includes means for a user to input the area, mode of transportation, distance, and theme to be drawn, means for transmitting the input data to the server, means for analyzing map data based on the data received by the server, means for generating a specific shape based on the theme, means for generating a route using an AI model taking safety and traffic rules into consideration, means for verifying and adjusting the generated route, means for incorporating tourist attractions into the route, means for transmitting the final course data to the terminal, means for the terminal to display the course data, means for the user to use as an exercise plan, means for generating a round route for delivery destinations, means for generating a route that passes tourist attractions, and means for verifying traffic rules and safety. This enables delivery staff to deliver efficiently and safely, and also enables the provision of high-value-added routes that visit tourist attractions.

[0230] "User" refers to a customer or delivery staff member who uses this system.

[0231] "Area" refers to the specific geographic area in which delivery is made.

[0232] "Means of transportation" refers to the means of transportation used when making deliveries, including bicycles, walking, cars, etc.

[0233] "Distance" refers to the distance of travel specified by the user.

[0234] The "theme to be drawn" refers to instructions entered by the user regarding the shape and pattern of the route to be generated.

[0235] "Server" refers to a computer system that receives, analyzes, routes, and transmits data.

[0236] "Map data" refers to data that includes information on roads, intersections, buildings, etc. in a specific area.

[0237] "Specific Shape" refers to the geometric shape of the route that is generated based on a theme entered by the user.

[0238] An "AI model" is an algorithm that uses artificial intelligence technology and is used to take safety and traffic rules into consideration when generating routes.

[0239] "Traffic rules" refers to legal regulations that must be followed while traveling, such as the Road Traffic Act.

[0240] "Points of interest" refers to specific notable places or landmarks that are included in route generation.

[0241] "Course data" is digital information about the generated route that is ultimately sent to the terminal.

[0242] "Device" means a device used by a User to view and display course data, including, for example, a smartphone or tablet.

[0243] "Exercise planning" refers to a plan of movement or exercise that a user will undertake based on the generated route.

[0244] "Delivery destination" refers to the location where the food delivery service should deliver the item.

[0245] A "routes" refers to a specific route generated to efficiently visit multiple delivery destinations.

[0246] "Safety" refers to factors taken into consideration when generating a route to prevent accidents and dangers.

[0247] "Efficient" means that the route is optimized to achieve the goal with the least amount of time and effort.

[0248] "Added value" refers to additional benefits or value to the user that are provided in addition to basic functionality.

[0249] This invention is a system that generates optimal delivery routes based on information entered by the user and provides them to delivery staff. This system improves delivery efficiency, ensures safety, and provides added value such as routes that visit tourist attractions.

[0250] System Configuration

[0251] 1. User-entered data

[0252] Using a smartphone application, users input data such as the area, mode of transportation, distance, theme they want to depict, safety priority or tourist attraction priority.

[0253] 2. Data Transmission and Reception

[0254] The data entered by the user is sent to the server via the smartphone application, and the server receives the data and begins analyzing it.

[0255] 3. Map data acquisition and analysis

[0256] The server retrieves map data for the specified area using Google Maps API or similar, analyzes this data, extracts information on major roads, intersections, and buildings, and processes it as data necessary for route generation.

[0257] 4. Shape and Route Generation

[0258] The server generates a specific shape based on a theme specified by the user, and uses an AI model to generate a route that takes safety and traffic rules into account. The AI ​​model uses machine learning frameworks such as TensorFlow and PyTorch.

[0259] 5. Route verification and adjustment

[0260] The server verifies that the generated route complies with traffic rules and is safe. If necessary, it adjusts the route to determine the optimal delivery route. If the route includes tourist attractions, it also incorporates their locations into the route.

[0261] 6. Sending and displaying course data

[0262] The final course data is sent from the server to the user's smartphone. The smartphone application receives this course data and displays it to the user. The user can check information such as the course map, travel methods, total distance, required time, and tourist attractions along the way.

[0263] Specific examples

[0264] For example, let's consider a scenario where a delivery staff member wants to cycle around multiple delivery destinations in Shibuya Ward, Tokyo, and simultaneously generate a route that draws a heart shape. In this case, the user inputs the following information into the smartphone application: Shibuya Ward, bicycle, 5 kilometers, heart, and safety priority.

[0265] Example prompt sentence:

[0266] "Generate routes to three delivery destinations by bicycle within the Shibuya Ward area. Safety is the top priority and I would like the route to follow traffic rules."

[0267] In this way, users input the necessary information and the system automatically generates the optimal delivery route, which is safe and efficient, allowing delivery staff to visit tourist attractions and provide high-value-added services.

[0268] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0269] Step 1:

[0270] The user inputs the area, mode of transportation, distance, and theme they want to draw.

[0271] The user starts the smartphone application and inputs information such as the area, mode of transportation, distance, theme to be drawn, priority of safety or priority of tourist attractions into the specified interface. This input data is collected and sent to the server in the next step.

[0272] Step 2:

[0273] Sending input information to the server

[0274] When the user presses the "Generate Route" button, the device sends all the data entered, including information about the area, mode of transportation, distance, theme, and priority, to the server. The data is sent in JSON format to the server.

[0275] Step 3:

[0276] Map data acquisition and analysis

[0277] The server uses the received data to obtain map data for the specified area using the Google Maps API. The obtained map data is then analyzed to extract information on major roads, intersections, buildings, etc. The extracted information is then used to generate the route.

[0278] Step 4:

[0279] Theme-based specific shape generation

[0280] The server generates a specific shape based on a theme entered by the user (e.g., a heart shape), using a theme-specific path generation algorithm. The generated shape becomes the basis for the final route design.

[0281] Step 5:

[0282] Route generation using AI models

[0283] The server generates routes using an AI model, taking safety and traffic rules into consideration. This AI model uses machine learning frameworks such as TensorFlow and PyTorch. The optimal route is calculated based on input data (map information, specific shapes, and traffic rules).

[0284] Step 6:

[0285] Validate and adjust the generated route

[0286] The server verifies that the generated route complies with traffic rules and is safe. It runs a simulation to check for safety issues and adjusts the route as necessary. Once verified, the route data is prepared for transmission in the next step.

[0287] Step 7:

[0288] Include tourist attractions in your route

[0289] The server references tourist attraction data and incorporates tourist attractions into the generated route. If the user has set tourist attractions as a priority, the server adjusts the route to pass through the tourist attractions. The final route after adjustment is determined.

[0290] Step 8:

[0291] Submitting the final course data

[0292] The final course data is sent from the server to the user's smartphone, including a map of the route, travel methods, total distance, travel time, and information on tourist attractions.

[0293] Step 9:

[0294] Viewing course data

[0295] The device displays the received route data through a user interface, allowing the user to efficiently deliver the goods while checking the route map and understanding the travel method, total distance, required time, and tourist attractions.

[0296] 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.

[0297] System Overview

[0298] This invention is a system that automatically generates GPS art courses based on user input data. An emotion engine that recognizes the user's emotions is incorporated as an additional element, allowing the system to generate courses according to the user's emotional state. This system allows the user to input their area, mode of transportation, distance, and desired theme, and generates a safe and efficient route based on that information. It can also generate courses that take into account traffic rules and include tourist attractions.

[0299] composition

[0300] 1. User-entered data

[0301] region

[0302] Transportation

[0303] distance

[0304] Themes I want to draw

[0305] Safety priority or tourist attraction priority

[0306] 2. Server Functions

[0307] Receiving input data

[0308] Map data acquisition and analysis

[0309] Shape generation based on user themes

[0310] Route generation using AI models

[0311] Emotion data analysis and route adjustment using an emotion engine

[0312] Verifying route safety and traffic rules

[0313] Sending course data to your device

[0314] 3. Device Features

[0315] Providing an input interface

[0316] Receiving and displaying course data

[0317] Collecting and transmitting emotional states

[0318] Program processing

[0319] 1. Receiving user input

[0320] Device: The user opens the application on the device and inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions. In addition, an emotion engine that collects the user's emotional state operates and obtains emotion data from the device.

[0321] 2. Sending input information to the server

[0322] Terminal: When the user presses the "Generate" button, the input data and emotion data are sent to the server. The sent data includes the area, transportation method, distance, theme, priority of safety or tourist attractions, and emotion data.

[0323] 3. Server-side data processing

[0324] server:

[0325] Input data and emotion data are received.

[0326] Obtain map data for the specified area and retrieve detailed information from the database, including road information, intersections, traffic lights, and other transportation infrastructure.

[0327] It runs an algorithm to generate a specific shape based on the user's theme and creates a pattern to form that shape.

[0328] The system uses an AI model to generate routes that fit the specified distance based on the acquired map data and thematic shape information. The route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[0329] The emotion engine analyzes the emotional data and adjusts the route generation accordingly. For example, if the emotion is relaxation, it will select a route that passes through a quiet park, and if the emotion is excitement, it will select a route that includes active tourist attractions.

[0330] The generated route is simulated to check whether it is safe and complies with traffic rules, and the route is fine-tuned if necessary.

[0331] The final course data that has been verified is prepared and sent to the terminal.

[0332] 4. Receiving and Displaying Course Information

[0333] Device: Displays the route data received from the server to the user, including the route map, travel method, total distance, estimated travel time, points of interest along the way, and special route adjustment information based on emotional state.

[0334] Specific examples

[0335] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[0336] 1. Receiving user input

[0337] Device: The user enters information about Shibuya Ward, running, 5 kilometers, heart rate, and safety priority into the application. The emotion engine then recognizes the user's emotional state and determines that the user needs to relax.

[0338] 2. Sending input information to the server

[0339] Device: Press the "Generate" button to send the information to the server, along with the emotion data.

[0340] 3. Data Processing

[0341] server:

[0342] Obtain map data for Shibuya Ward and analyze road information.

[0343] Generate a heart-shaped pattern and check if it is suitable for 5 kilometers.

[0344] Using an AI model, the system generates a safe route that follows traffic rules. Because the user's emotional state indicates a desire for relaxation, the system selects routes that pass through parks and natural areas as much as possible.

[0345] The route will also include tourist attractions such as the Hachiko statue and Yoyogi Park.

[0346] Simulate the generated route to ensure it is safe and adjust it if necessary.

[0347] The final course data is sent to the device.

[0348] 4. View course information

[0349] Terminal: Displays to the user a course map, mode of travel, distance, time required, tourist attractions, and special route adjustment information based on emotional state.

[0350] In this way, users can generate safe and efficient GPS art courses tailored to their emotional state.

[0351] The processing flow will be explained below.

[0352] Step 1:

[0353] User: Opens the application on the device. The user inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions. Furthermore, the emotion engine collects the user's emotional state and analyzes the current emotional state.

[0354] Step 2:

[0355] Terminal: When the user presses the "Generate" button, the input data and emotion data are sent to the server. The sent data includes the area, transportation method, distance, theme, priority of safety or tourist attractions, and emotion data.

[0356] Step 3:

[0357] Server: Analyzes the data received from the device. Specifically, it retrieves map data for the area specified by the user and obtains detailed information from a database, including road information, intersections, traffic lights, and other traffic infrastructure information.

[0358] Step 4:

[0359] Server: Performs thematic analysis. Based on a theme entered by the user (e.g., "heart"), it runs an algorithm to generate a specific shape and creates the patterns that form that shape.

[0360] Step 5:

[0361] Server: Generates a route using an AI model. This generates a route that matches the specified distance based on the acquired map data and thematic shape information. Route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[0362] Step 6:

[0363] Server: Analyzes emotional data. The emotional state of the user recognized by the emotion engine (e.g., "I want to relax" or "I want an active experience") is analyzed and reflected in route generation.

[0364] Step 7:

[0365] Server: Adjusts the route based on emotional data. For example, if the emotional state is one of relaxation, it selects a route that passes through parks and quiet roads, and if the emotional state is active, it selects a route that includes tourist attractions and bustling places.

[0366] Step 8:

[0367] Server: Adjust the route to include tourist attractions. If the user sets a high priority for a tourist attraction, the server will incorporate the specified tourist attraction (e.g., Hachiko Statue, Yoyogi Park, etc.) into the route and recalculate the route to reach that attraction.

[0368] Step 9:

[0369] Server: Validates the generated route, simulating whether it complies with traffic rules and ensures safety, and fine-tunes the route if necessary.

[0370] Step 10:

[0371] Server: Prepares the final course data after verification and sends it to the device.

[0372] Step 11:

[0373] Device: Displays the route data received from the server to the user, including the route map, travel method, total distance, estimated travel time, points of interest along the way, and special route adjustment information based on emotional state.

[0374] Step 12:

[0375] User: Checks the provided course information, and if satisfied, prepares to actually exercise the course.

[0376] Example 2

[0377] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0378] Previous GPS Art route generation systems did not take the user's emotional state into account, making it difficult to provide routes that suited the user's mental and physical needs. Furthermore, they rarely guaranteed safety or compliance with traffic rules, making it difficult to generate appropriate routes for specific modes of transportation. Another problem was that they were unable to automatically generate routes that included tourist attractions, and lacked features that would increase the user's enjoyment.

[0379] 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.

[0380] In this invention, the server includes means for the user to input the area, mode of transportation, distance, and theme to be drawn, means for recognizing the user's emotional state and collecting relevant data, means for transmitting the input data and emotional data to the server, means for the server to analyze map data based on the data received, means for generating a specific shape based on the theme, means for generating a route using an AI model taking into account safety and traffic rules, means for adjusting the generated route based on the emotional data, means for verifying and adjusting the generated route, means for transmitting the final course data to the terminal, and means for the terminal to display the course data. This enables the generation of an optimal route that takes into account the user's emotional state, safety, and traffic rules, providing a safer and more enjoyable GPS art experience.

[0381] "Region" is data indicating the location or area where the user performs GPS art.

[0382] "Means of transportation" is data that indicates the method or tool (e.g., running, cycling, etc.) used by the user to create GPS art.

[0383] "Distance" is data indicating the total distance traveled by the user when drawing GPS art.

[0384] The "theme to be drawn" is data indicating a specific shape or figure (e.g., heart, star, etc.) that the user wants to draw in GPS Art.

[0385] "Emotional state" is data that indicates the mental or emotional state of a user.

[0386] An "emotion engine" refers to a function or system for recognizing a user's emotions and analyzing their state.

[0387] "Server" refers to a central computing system for receiving and processing data sent by users.

[0388] A "data packet" is a unit of information that includes user input data and emotion data and is sent to the server.

[0389] "Map Data" refers to a data set containing details of roads, intersections, traffic lights, etc. for a specified area.

[0390] A "theme shape" is data that indicates a shape that embodies a figure or pattern that the user wants to draw.

[0391] "AI Model" refers to the artificial intelligence algorithm used to generate the route.

[0392] "Route adjustment" is the process of making corrections and optimizations to the generated route based on the user's emotional data and other considerations.

[0393] "Course data" refers to data that indicates the final route information of the GPS Art that has been analyzed and generated.

[0394] "Terminal" refers to the device (e.g., smartphone, tablet, etc.) used by the user to enter and display the final course data.

[0395] "Tourist attractions" are data that indicate particular geographical locations or cultural facilities that may be of interest to users.

[0396] System Overview

[0397] This invention is a system that automatically generates GPS art courses based on user input and emotional data. The system generates a theme shape based on user-entered information and uses an AI model to generate a route that matches it. It also incorporates an emotion engine that recognizes the user's emotional state and adjusts the route accordingly. Users can input their area, mode of transportation, distance, theme they want to draw, and safety or tourist attraction priorities.

[0398] Hardware and software used

[0399] 1. User device (e.g. smartphone, tablet)

[0400] A device that allows users to input data and interact with the system, incorporating an input interface and emotion engine.

[0401] 2. Server

[0402] It is a central computing system for receiving and processing input data and emotion data, analyzing map data, generating theme shapes, generating routes using AI models, making adjustments based on emotion data, and transmitting the final course data.

[0403] Program processing explanation

[0404] Receiving user input

[0405] The user opens the application on their device and enters the following information: area (e.g., "Shibuya-ku, Tokyo"), mode of transportation (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and safety or tourist attraction priority. Furthermore, an emotion engine runs, collecting the user's emotional state using the camera and microphone.

[0406] Sending input information to the server

[0407] When the user presses the "Generate" button, the device sends this data to the server, including the area, mode of transportation, distance, theme, safety or tourist attraction priority, and emotion data.

[0408] Server-side data processing

[0409] The server does the following:

[0410] Receives input data and emotion data.

[0411] Obtain map data for the specified area and extract detailed information such as road information, intersections, and traffic lights from the database.

[0412] It runs an algorithm that generates a specific shape based on the user's theme, then creates a pattern to form that shape.

[0413] Routes are generated using AI models, taking safety and traffic rules into consideration during the process.

[0414] The generated route is adjusted based on the analysis results of the emotion engine. For example, if the user wants to "relax," the system will select a route that passes through parks and quiet places.

[0415] Simulate the generated route to ensure it is safe and make any necessary adjustments.

[0416] The final course data is sent to the device.

[0417] Receive and view course information

[0418] The device displays the course data received from the server to the user, including:

[0419] Course Map

[0420] How to move

[0421] Total distance

[0422] Estimated time required

[0423] Tourist attractions to visit

[0424] Special route adjustment information based on emotional state

[0425] Specific examples

[0426] If a user wants to generate a 5km course in Shibuya, Tokyo, where they will draw a heart shape while running:

[0427] 1. The user enters the following information into the application: Shibuya Ward, running, 5km, heart, safety first. The emotion engine recognizes that the user needs to relax.

[0428] 2. Press the "Generate" button to send the information to the server, along with the emotion data.

[0429] 3. The server retrieves map data for Shibuya Ward and analyzes road information. A heart-shaped pattern is generated, and an AI model is used to generate a safe route that takes traffic rules into account. Since the driver is looking for relaxation, parks and quiet routes are selected whenever possible. Tourist attractions are also included.

[0430] 4. Include tourist attractions such as the Hachiko statue and Yoyogi Park in your route.

[0431] 5. The generated route is simulated to check its safety, and fine-tuned if necessary. The final course data is sent to the device.

[0432] 6. The device displays the route map, travel method, distance, travel time, tourist attraction information, and special route adjustment information based on emotional state to the user.

[0433] Example prompt sentence:

[0434] "Generate a 5-kilometer course to trace a heart shape while running in Shibuya, Tokyo, prioritizing safety. I'm in the mood for relaxation right now."

[0435] In this way, users can generate safe and efficient GPS art courses tailored to their emotional state.

[0436] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0437] Step 1:

[0438] Receiving user input

[0439] The user opens the application on their device and inputs their "area" (e.g., "Shibuya-ku, Tokyo"), "mode of transportation" (e.g., "running"), "distance" (e.g., "5 kilometers"), "theme to draw" (e.g., "heart"), and "safety priority" or "tourist attraction priority." The emotion engine then operates, collecting the user's emotional state via the camera and microphone and converting it into digital data.

[0440] Input: Region, mode of transportation, distance, theme, priority, emotional state

[0441] Output: Collected user input data and emotion data

[0442] Step 2:

[0443] Preparing to send input information

[0444] The terminal assembles the collected user input data and emotion data into a single data packet, which includes the area, mode of transportation, distance, theme, priority of safety or tourist attractions, and emotion data.

[0445] Input: Collected user input data and emotion data

[0446] Output: Data packets

[0447] Step 3:

[0448] Sending data to the server

[0449] When the user presses the "Generate" button, the terminal sends a data packet to the server.

[0450] Input: Data packet

[0451] Output: Send data to the server

[0452] Step 4:

[0453] Receiving data

[0454] The server receives data packets sent from the terminal, which include region, mode of transportation, distance, theme, priority, and emotion data.

[0455] Input: Data packet

[0456] Output: Received data

[0457] Step 5:

[0458] Map data acquisition and analysis

[0459] The server retrieves map data for the area specified by the user and extracts detailed information from the database, such as road information, intersections, and traffic light locations. Through this analysis, it collects topographical and infrastructure information that will be the basis for route generation.

[0460] Input: Region data

[0461] Output: Map data (road information, intersections, traffic light locations, etc.)

[0462] Step 6:

[0463] Theme Shape Generation

[0464] The server runs an algorithm to generate a specific shape based on a user-specified theme (e.g., "heart"), which generates specific paths and segment patterns to form the theme shape.

[0465] Input: Theme data

[0466] Output: Theme Shape Pattern

[0467] Step 7:

[0468] Route Generation

[0469] The server uses an AI model to generate a route based on the acquired map data and the generated thematic shape patterns, taking into account safety and traffic rules (e.g., one-way streets, bicycle lanes, etc.) depending on the mode of travel.

[0470] Input: Map data and thematic shape patterns

[0471] Output: Generated routes

[0472] Step 8:

[0473] Route adjustment based on emotion data

[0474] The server then adjusts the generated route using the emotion data analyzed by the emotion engine. For example, if the user is looking to relax, the server may select a route that includes parks and plenty of nature.

[0475] Input: Generated route and emotion data

[0476] Output: Adjusted route

[0477] Step 9:

[0478] Safety and traffic rules verification

[0479] The server simulates the generated route to ensure safety and compliance with traffic rules, and fine-tunes the route if necessary.

[0480] Input: Adjusted Route

[0481] Output: Final route

[0482] Step 10:

[0483] Prepare and submit final course data

[0484] The server prepares the final course data and sends it to the device, which includes the course map, travel mode, distance, travel time, tourist attractions, and special route adjustment information based on emotional state.

[0485] Input: Final Route

[0486] Output: Send course data to the device

[0487] Step 11:

[0488] View course information

[0489] The device displays the course data received from the server to the user, including the course map, travel method, distance, travel time, tourist attractions along the way, and special route adjustment information based on emotional state.

[0490] Input: Course data

[0491] Output: Course information displayed to user

[0492] (Application example 2)

[0493] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0494] Conventional automated patrol systems within factories have the problem of not being able to fully consider safety and efficiency when generating routes. Furthermore, because the emotional state of the operator is not reflected in the patrol route, it is difficult to manage stress and ensure appropriate rest areas. The present invention aims to solve these problems and provide a system that achieves safe and efficient patrol within a factory.

[0495] 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.

[0496] In this invention, the server includes means for the user to input the area, means of transportation, distance, and theme to be drawn, means for transmitting the input data to the server, and means for collecting emotion data and adjusting the route based on the emotion data, thereby enabling route adjustment based on the emotion data and generation of work areas and process points for equipment maintenance.

[0497] A "region" is a geographical location specified by the user, and is the basic information for generating a route.

[0498] "Transportation" refers to the transportation method designated by the user, and includes running, cycling, car, etc.

[0499] "Distance" is the distance the user desires to travel, and is a parameter that specifies the length of the route.

[0500] The "theme" is the specific shape or pattern desired by the user, and serves as the basis for GPS art.

[0501] The "means for transmitting data to a server" is a function for sending information entered by a user to a server via a network.

[0502] The "means for analyzing map data based on data received by the server" is a function for extracting and analyzing detailed information on the map based on information received by the server from the user.

[0503] The "means for generating a specific shape based on a theme" is a function for generating a specific shape or pattern on a map based on a theme input by the user.

[0504] "Means for generating routes using AI models, taking into account safety and traffic rules" refers to a function that automatically generates optimal routes using AI models, taking into account the safety and traffic rules of each means of transportation.

[0505] "Means for verifying and adjusting the generated route" refers to a function that simulates whether the generated route complies with safety and traffic rules, and makes fine adjustments as necessary.

[0506] The "means for transmitting final course data to the terminal" is a function for transmitting the generated final route information to the terminal.

[0507] The "means for the terminal to display course data" refers to a function for visually displaying the course data received by the terminal to the user.

[0508] The "means for collecting emotional data and adjusting the route based on the emotional data" is a function that analyzes the user's emotional state using an emotional engine and optimizes the route based on that data.

[0509] The "means for generating patrol routes within a factory and supporting patrol by a robot" is a function that generates routes that allow a robot to patrol a factory efficiently and safely, and supports that patrol.

[0510] The "means for generating a route including tourist attractions" is a function for generating a route including tourist attractions within a specified area.

[0511] "Means for generating process points for work areas and equipment maintenance" is a function that includes specific work areas within a factory and points of equipment that require maintenance in the route.

[0512] "Means for providing the user with final course information and planning exercise based on that information" is a function that provides information for the user to plan exercise based on the generated route information.

[0513] The "means for planning patrol routes to improve work efficiency and safety within a factory" is a function for planning patrol routes within a factory and improving work efficiency and safety.

[0514] System Overview

[0515] The present invention is an automatic route generation system for a factory that generates an efficient and safe route based on user input data. The system is composed of the following elements:

[0516] System Configuration

[0517] 1. User-entered data

[0518] Area (e.g. Factory Zone A)

[0519] Means of transportation (e.g., patrol robot)

[0520] Distance (e.g. 5 kilometers)

[0521] The theme you want to draw (e.g., shortest route)

[0522] Prioritizing safety or patrol efficiency

[0523] Emotional data (e.g., stress level, preferred_break_spot)

[0524] 2. Server Functions

[0525] Receiving input data

[0526] Map data acquisition and analysis

[0527] Shape generation based on user themes

[0528] Route adjustment based on emotion data analysis

[0529] Route generation using AI models

[0530] Verifying route safety and traffic rules

[0531] Sending the final course data to the device

[0532] 3. Device Features

[0533] Providing an input interface

[0534] Receiving and displaying course data

[0535] Collecting and transmitting emotional states

[0536] Program processing explanation

[0537] 1. Receiving user input data

[0538] The terminal receives information from the user, such as area, mode of transportation, distance, theme, priority of safety or patrol efficiency, and emotion data. This input data is input by the user by opening an application on the terminal.

[0539] 2. Sending input information to the server

[0540] When the user presses the "generate" button, the terminal transmits the input data and emotion data to the server.

[0541] 3. Server-side data processing

[0542] The server analyzes the received data and retrieves map data for the specified area. It then uses an AI model to generate a route that takes safety and efficiency into account. It adjusts the route based on emotion data, prioritizing rest areas if stress levels are high, for example. Finally, the generated route is verified for safety and compliance with traffic rules, and fine-tuning is performed as needed.

[0543] Hardware and software used

[0544] Hardware: Servers (dedicated servers or cloud servers), user devices (smartphones, tablets, laptops, etc.)

[0545] Software: Application (to provide user interface), AI model (to generate routes), emotion engine (to analyze emotion data)

[0546] Specific examples

[0547] Let's take the example of a user wanting to generate a safe and efficient 5-kilometer patrol route for a patrol robot in factory zone A, which is experiencing a high stress level. The user opens the application, selects factory zone A, inputs the information for the patrol robot, 5 kilometers, shortest route, and safety priority, and sends emotional data indicating a high stress level.

[0548] The server acquires map data for Factory Zone A and analyzes road information. At the same time, it generates a route that prioritizes rest areas based on emotion data, and generates a final route that takes safety and traffic rules into consideration. This route data is sent to the terminal and displayed to the user.

[0549] Prompt Sentence Examples

[0550] Generate a safe patrol route that is optimal for workers with a stress level of 3 based on the user-specified factory zone A. In particular, create a route that prioritizes rest areas. The means of transportation is a "patrol robot." The generated route should include the locations of each waypoint and the actions to be taken at each point.

[0551] In this way, users can generate safe and efficient routes around the factory that are tailored to their emotional state.

[0552] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0553] Step 1:

[0554] The user opens the application on their device and inputs the area (e.g., factory zone A), the means of transportation (e.g., patrol robot), the distance (e.g., 5 kilometers), the theme they want to draw (e.g., the shortest route), the priority of safety (or the priority of patrol efficiency), and emotional data (e.g., stress level). The input data is formatted in JSON format.

[0555] Input: Region, mode of transportation, distance, theme, safety priority, sentiment data

[0556] Output: Input data in JSON format

[0557] Step 2:

[0558] When the user presses the "Generate" button, the terminal sends the formatted JSON input data to the server using an HTTP POST request.

[0559] Input: Input data in JSON format

[0560] Output: POST request to the server

[0561] Step 3:

[0562] The server analyzes the received JSON format data and obtains map data for the specified area (Factory Zone A). It also obtains data on traffic infrastructure such as road information, intersections, and traffic lights from a database.

[0563] Input: JSON format input data received via POST request

[0564] Output: Map data, road information, traffic infrastructure data

[0565] Step 4:

[0566] The server runs an algorithm that generates a particular shape based on the theme, and creates patterns to form that shape, for example, if the theme is "shortest path", it will generate patterns to form the shortest path.

[0567] Input: User's theme (e.g. shortest path)

[0568] Output: Specific shape pattern

[0569] Step 5:

[0570] The server generates a route using an AI model. It uses acquired map data and a shape pattern based on the theme to generate a route that fits the specified distance (5 kilometers). It generates the route while taking into account the safety and traffic rules of each mode of transportation.

[0571] Input: Map data, shape pattern, distance, means of transportation

[0572] Output: Generated routes

[0573] Step 6:

[0574] The server analyzes the emotion data and adjusts the route accordingly. For example, if the stress level is high, the server may select a route that prioritizes rest areas. The server processes the emotion data using an emotion engine and fine-tunes the route.

[0575] Input: Generated route, emotion data

[0576] Output: Adjusted route

[0577] Step 7:

[0578] The server simulates and verifies the generated route to ensure safety and compliance with traffic rules, and fine-tunes the route if there are any issues with safety or traffic rules.

[0579] Input: Adjusted Route

[0580] Output: Final route

[0581] Step 8:

[0582] The server then sends the final course data to the device, which includes the location of each waypoint, the actions to be taken, the distance, and the estimated time required.

[0583] Input: Final route

[0584] Output: Course data to the device

[0585] Step 9:

[0586] The terminal displays the course data received from the server to the user, who can then check information such as the course map, travel method, total distance, estimated time required, and rest areas along the way.

[0587] Input: Course data received from the server

[0588] Output: Course information displayed on the user interface

[0589] 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.

[0590] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0591] 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.

[0592] [Second embodiment]

[0593] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0594] 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.

[0595] 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).

[0596] 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.

[0597] 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.

[0598] 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).

[0599] 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.

[0600] 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.

[0601] 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.

[0602] 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.

[0603] 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.

[0604] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0605] System Overview

[0606] This system automatically generates a GPS art course based on user input data. Users input their area, mode of transportation, distance, and the theme they want to draw, and a safe and efficient route is generated based on that information. It can also generate a course that takes into account traffic rules and includes tourist attractions.

[0607] composition

[0608] 1. User-entered data

[0609] region

[0610] Transportation

[0611] distance

[0612] Themes I want to draw

[0613] Safety priority or tourist attraction priority

[0614] 2. Server Functions

[0615] Receiving input data

[0616] Map data acquisition and analysis

[0617] Shape generation based on user themes

[0618] Route generation using AI models

[0619] Verifying route safety and traffic rules

[0620] Sending course data to your device

[0621] 3. Device Features

[0622] Providing an input interface

[0623] Receiving and displaying course data

[0624] Program processing

[0625] 1. Receiving user input

[0626] Device: The user opens the application on the device and inputs the area, mode of transportation, distance, theme to be drawn, safety priority or tourist attraction priority.

[0627] 2. Sending input information to the server

[0628] Terminal: When the user presses the "Generate" button, the input data is sent to the server.

[0629] 3. Server-side data processing

[0630] server:

[0631] Receives input data and retrieves map data for the specified area.

[0632] The acquired map data is analyzed and information such as major roads and intersections is extracted.

[0633] Generate specific shapes based on user themes.

[0634] An AI model is used to generate routes that take safety and traffic rules into consideration.

[0635] If you include a tourist attraction, incorporate its location into the route.

[0636] Verify that the generated route complies with traffic rules and is safe.

[0637] The verified course data is sent to the device.

[0638] 4. Receiving and Displaying Course Information

[0639] Terminal: Displays the course data received from the server to the user. The user can check information such as the course map, travel method, total distance, required time, and tourist attractions along the way.

[0640] Specific examples

[0641] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[0642] 1. Receiving user input

[0643] Device: The user enters the following information into the application: Shibuya Ward, Running, 5km, Heart, Safety First.

[0644] 2. Sending input information to the server

[0645] Terminal: Press the "Generate" button to send the information to the server.

[0646] 3. Data Processing

[0647] server:

[0648] Obtain map data for Shibuya Ward and analyze road information.

[0649] Generate a heart-shaped pattern and check if it is suitable for 5 kilometers.

[0650] Using AI models, routes that are safe and comply with traffic rules are generated.

[0651] The route will include tourist attractions such as the Hachiko statue and Yoyogi Park.

[0652] Simulate the generated route to ensure it is safe and adjust it if necessary.

[0653] The final course data is sent to the device.

[0654] 4. View course information

[0655] Terminal: Displays course information to the user, including course maps, transportation methods, distance, time required, and points of interest.

[0656] In this way, users can easily create safe and efficient GPS art courses.

[0657] The processing flow will be explained below.

[0658] Step 1:

[0659] User: Opens the application on the device. The user inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions.

[0660] Step 2:

[0661] Terminal: When the user presses the "Generate" button, the entered data is sent to the server, including the area, mode of transportation, distance, theme, and safety or tourist attraction priority.

[0662] Step 3:

[0663] Server: Analyzes the data received from the device. Specifically, it retrieves map data for the area specified by the user and obtains detailed information from a database, including road information, intersections, traffic lights, and other traffic infrastructure information.

[0664] Step 4:

[0665] Server: Performs thematic analysis. Based on a theme entered by the user (e.g., "heart"), it runs an algorithm to generate a specific shape and creates the patterns that form that shape.

[0666] Step 5:

[0667] Server: Generates a route using an AI model. This generates a route that matches the specified distance based on the acquired map data and thematic shape information. Route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[0668] Step 6:

[0669] Server: Adjust the route to include tourist attractions. If the user sets a high priority for a tourist attraction, the server will incorporate the tourist attraction (e.g., Hachiko Statue, Yoyogi Park, etc.) into the route and recalculate the route to reach that attraction.

[0670] Step 7:

[0671] Server: Validates the generated route, simulating whether it complies with traffic rules and ensures safety, and fine-tunes the route if necessary.

[0672] Step 8:

[0673] Server: Prepares the final course data after verification and sends it to the device.

[0674] Step 9:

[0675] Terminal: Displays the course data received from the server to the user. The displayed content includes the course map, travel method, total distance, estimated time required, and tourist attractions along the way.

[0676] Step 10:

[0677] User: Checks the provided course information, and if satisfied, prepares to actually exercise the course.

[0678] Example 1

[0679] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0680] Conventional route planning systems lack the ability to generate specific shapes based on user themes, and it is difficult to generate routes that fully consider safety and traffic rules. Furthermore, generating routes that include tourist attractions and verifying and adjusting the generated routes are time-consuming, making it difficult for users to easily obtain efficient and safe routes.

[0681] 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.

[0682] In this invention, the server includes means for acquiring and analyzing map data based on input data, means for generating a specific shape based on a theme, and means for inputting a prompt sentence to the AI ​​model to generate a route that takes safety and traffic rules into consideration, thereby enabling a user to easily generate a route with a specific shape based on a theme and obtain an efficient course that complies with safety and traffic rules.

[0683] A "region" is a particular geographic area that a user specifies when generating a route.

[0684] "Transportation" refers to the method or mode of transportation used by a user to travel a route, including, for example, walking, cycling, or driving.

[0685] "Distance" is the length of the route specified by the user, typically expressed in kilometers.

[0686] The "theme to be drawn" indicates the shape and purpose of the route that the user wants to generate, and includes a specific shape or pattern.

[0687] "Safety priority" is an index that indicates the priority of safety in route generation.

[0688] The "priority of tourist attractions" is an index that indicates the priority with which tourist attractions are emphasized in route generation.

[0689] "Map data" is a data set containing geographic information for a particular area, including information on roads, intersections, etc.

[0690] The "particular shape" refers to a particular pattern or shape that is generated based on a user's theme.

[0691] An "AI model" is a computational model that uses artificial intelligence to analyze data and perform specific tasks.

[0692] A "prompt sentence" is an input sentence used to prompt an AI model to perform a specific task.

[0693] "Generating a route" means calculating and determining a route that takes safety and traffic rules into consideration based on data input by the user.

[0694] "Validation" is the process of checking whether the generated route is correct and complies with certain conditions.

[0695] "Adjustment" means making necessary corrections based on the results of verification.

[0696] "Course data" is a detailed data set that includes the generated route, including route coordinates, distance traveled, time required, etc.

[0697] A "terminal" is a hardware device through which a user enters input data and receives final course information.

[0698] MODE FOR CARRYING OUT THE INVENTION

[0699] System Overview

[0700] This invention is a system that automatically generates routes based on user input data. Users input their area, mode of transportation, distance, and the theme they want to depict, and a safe and efficient route is generated based on that information. Furthermore, traffic rules are taken into account and tourist attractions can be included in the route. The operation of the system will be explained in detail using a specific example.

[0701] Hardware and software used

[0702] Device: User device such as a smartphone or tablet

[0703] Server: High-performance computing server

[0704] Map Data API: Google Maps API

[0705] Geographic information processing libraries: Geopy, Fiona

[0706] Shape manipulation library: Shapely

[0707] AI model: OpenAI GPT-3 model

[0708] Map display libraries: Mapbox, Leaflet

[0709] Program processing

[0710] 1. Receiving user input

[0711] Device: The user opens the application on their device and enters the area (e.g., Shibuya Ward), mode of transportation (e.g., running), distance (e.g., 5 kilometers), theme to draw (e.g., heart), and safety priority or tourist attraction priority (e.g., safety).

[0712] 2. Sending input information to the server

[0713] Terminal: When the user presses the "Generate" button, the input data is converted to JSON format and a POST request is sent to the server's API endpoint.

[0714] 3. Server-side data processing

[0715] Server: Receives input data and retrieves map data for the specified area (Shibuya Ward) using the Google Maps API.

[0716] Server: Analyzes the acquired map data and extracts information such as major roads and intersections using geographic information processing libraries such as Geopy and Fiona.

[0717] Specifically, the map data is parsed and the locations of road segments and intersections are stored in list format.

[0718] Server: Generates specific shapes (e.g., hearts) based on the user's theme. Shape manipulation libraries such as Shapely are used for shape generation.

[0719] Specifically, a heart-shaped Bezier curve is generated and a route is created along it.

[0720] Server: Enter a prompt into a generative AI model (e.g., OpenAI's GPT-3) to generate an optimal route. An example prompt is as follows:

[0721] Prompt statement:

[0722] The user is looking for a 5-kilometer running course in Shibuya, Tokyo. The course should be heart-shaped, and safety is a priority. Generate a route that passes by the Hachiko statue and Yoyogi Park as much as possible.

[0723] 4. The server verifies traffic rules and safety

[0724] Server: Simulates whether the generated route complies with traffic rules and is safe. The simulation uses traffic rule-related datasets and a rule engine.

[0725] As a specific example, check whether there are traffic lights at intersections or whether there are pedestrian-only roads.

[0726] Server: If necessary, fine-tune the output of the AI ​​model to align with safety and traffic rules.

[0727] 5. The generated route data is sent to the device.

[0728] Server: Once the final route is validated, it converts the route data into JSON format and sends it to the device, including route coordinates, distance traveled, travel time, and location information of tourist attractions.

[0729] 6. The device will display the route information.

[0730] Terminal: Analyzes the route data received from the server and displays it to the user. A map display library such as Mapbox or Leaflet is used for displaying the data.

[0731] For example, the system draws a route on a map, places pins at each tourist spot, and displays detailed information such as the mode of transportation, total distance, and required time on the screen.

[0732] Specific examples

[0733] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[0734] User: Enters "Shibuya Ward, running, 5km, heart, safety first" into the app.

[0735] Terminal: Press the "Generate" button and the data will be sent to the server in JSON format.

[0736] Server: Obtains Shibuya Ward map data via the Google Maps API and analyzes road information using the Geopy library. Shapely generates a heart-shaped pattern, and a GPT-3 model generates a safe route, taking into account routes that pass through the Hachiko statue and Yoyogi Park.

[0737] Server: Validates the generated route based on traffic rules and safety, and sends the final route data to the device.

[0738] Terminal: The received route is displayed on a map, and the user can check the course map, travel method, total distance, required time, and tourist attractions.

[0739] This process allows users to easily generate safe and efficient routes with thematic geometries.

[0740] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0741] Step 1:

[0742] User: Opens the application and enters the area (e.g. Shibuya Ward), mode of transportation (e.g. running), distance (e.g. 5 kilometers), theme to draw (e.g. heart), and safety priority or tourist attraction priority (e.g. safety).

[0743] Input: Region, mode of transport, distance, theme, safety or tourist attraction priority

[0744] Output: User input data (JSON format)

[0745] Step 2:

[0746] Terminal: Validates the entered data, and when the user presses the "Generate" button, converts the input data into JSON format and sends it to the server.

[0747] Input: User-entered data

[0748] Data processing: Convert user input data into JSON format

[0749] Output: POST request to the server

[0750] Step 3:

[0751] Server: Receives input data and retrieves map data for the specified area (Shibuya Ward) using the Google Maps API.

[0752] Input: User-entered data

[0753] Data processing: Retrieving and parsing map data

[0754] Output: Parsed map data (a list containing road and intersection information)

[0755] Step 4:

[0756] Server: Analyzes the acquired map data and extracts information on major roads and intersections.

[0757] Input: Map data

[0758] Data processing: Analysis of map data using Geopy and Fiona libraries

[0759] Output: A list of extracted road segments and intersections

[0760] Step 5:

[0761] Server: Generates a specific shape (e.g., heart) based on the user's theme.

[0762] Input: User theme, list of road segments and intersections

[0763] Data processing: Shape generation using the Shapely library

[0764] Output: Generated theme shape (e.g. heart-shaped route)

[0765] Step 6:

[0766] Server: Enters a prompt into a generative AI model (e.g., GPT-3) and generates a route that takes safety and traffic rules into consideration.

[0767] Input: Generated theme shapes

[0768] Data processing: Route generation using an AI model based on prompts

[0769] Output: Initial generated route

[0770] Example prompt sentence:

[0771] Prompt statement:

[0772] The user is looking for a 5-kilometer running course in Shibuya, Tokyo. The course should be heart-shaped, and safety is a priority. Generate a route that passes by the Hachiko statue and Yoyogi Park as much as possible.

[0773] Step 7:

[0774] Server: Simulates whether the generated route complies with traffic rules and is safe. Adjusts the route if necessary.

[0775] Input: Initial generated route, traffic rule dataset

[0776] Data processing: Verification and adjustment based on traffic rules and safety

[0777] Output: Final generated route

[0778] Step 8:

[0779] Server: Once the final route is validated, it converts the route data into JSON format and sends it to the device.

[0780] Input: Final generated route

[0781] Data processing: Converting route data to JSON format

[0782] Output: Send route data to the device

[0783] Step 9:

[0784] Terminal: Analyzes the route data received from the server and displays it to the user. A map display library such as Mapbox or Leaflet is used for displaying the data.

[0785] Input: Route data received from the server

[0786] Data processing: Route data analysis and mapping

[0787] Output: User-visible route map, detailed information such as travel methods, total distance, travel time, and points of interest

[0788] The system allows users to easily generate safe and efficient routes with specific geometries and view all the necessary details.

[0789] (Application example 1)

[0790] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0791] The problem that this invention aims to solve is to provide an optimal route for delivery staff to travel to multiple delivery destinations efficiently and safely in a food delivery service.The invention also aims to build a system that can provide added value by generating routes that include tourist attractions, allowing delivery staff to discover the charms of the area while performing delivery work.

[0792] 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.

[0793] In this invention, the server includes means for a user to input the area, mode of transportation, distance, and theme to be drawn, means for transmitting the input data to the server, means for analyzing map data based on the data received by the server, means for generating a specific shape based on the theme, means for generating a route using an AI model taking safety and traffic rules into consideration, means for verifying and adjusting the generated route, means for incorporating tourist attractions into the route, means for transmitting the final course data to the terminal, means for the terminal to display the course data, means for the user to use as an exercise plan, means for generating a round route for delivery destinations, means for generating a route that passes tourist attractions, and means for verifying traffic rules and safety. This enables delivery staff to deliver efficiently and safely, and also enables the provision of high-value-added routes that visit tourist attractions.

[0794] "User" refers to a customer or delivery staff member who uses this system.

[0795] "Area" refers to the specific geographic area in which delivery is made.

[0796] "Means of transportation" refers to the means of transportation used when making deliveries, including bicycles, walking, cars, etc.

[0797] "Distance" refers to the distance of travel specified by the user.

[0798] The "theme to be drawn" refers to instructions entered by the user regarding the shape and pattern of the route to be generated.

[0799] "Server" refers to a computer system that receives, analyzes, routes, and transmits data.

[0800] "Map data" refers to data that includes information on roads, intersections, buildings, etc. in a specific area.

[0801] "Specific Shape" refers to the geometric shape of the route that is generated based on a theme entered by the user.

[0802] An "AI model" is an algorithm that uses artificial intelligence technology and is used to take safety and traffic rules into consideration when generating routes.

[0803] "Traffic rules" refers to legal regulations that must be followed while traveling, such as the Road Traffic Act.

[0804] "Points of interest" refers to specific notable places or landmarks that are included in route generation.

[0805] "Course data" is digital information about the generated route that is ultimately sent to the terminal.

[0806] "Device" means a device used by a User to view and display course data, including, for example, a smartphone or tablet.

[0807] "Exercise planning" refers to a plan of movement or exercise that a user will undertake based on the generated route.

[0808] "Delivery destination" refers to the location where the food delivery service should deliver the item.

[0809] A "routes" refers to a specific route generated to efficiently visit multiple delivery destinations.

[0810] "Safety" refers to factors taken into consideration when generating a route to prevent accidents and dangers.

[0811] "Efficient" means that the route is optimized to achieve the goal with the least amount of time and effort.

[0812] "Added value" refers to additional benefits or value to the user that are provided in addition to basic functionality.

[0813] This invention is a system that generates optimal delivery routes based on information entered by the user and provides them to delivery staff. This system improves delivery efficiency, ensures safety, and provides added value such as routes that visit tourist attractions.

[0814] System Configuration

[0815] 1. User-entered data

[0816] Using a smartphone application, users input data such as the area, mode of transportation, distance, theme they want to depict, safety priority or tourist attraction priority.

[0817] 2. Data Transmission and Reception

[0818] The data entered by the user is sent to the server via the smartphone application, and the server receives the data and begins analyzing it.

[0819] 3. Map data acquisition and analysis

[0820] The server retrieves map data for the specified area using Google Maps API or similar, analyzes this data, extracts information on major roads, intersections, and buildings, and processes it as data necessary for route generation.

[0821] 4. Shape and Route Generation

[0822] The server generates a specific shape based on a theme specified by the user, and uses an AI model to generate a route that takes safety and traffic rules into account. The AI ​​model uses machine learning frameworks such as TensorFlow and PyTorch.

[0823] 5. Route verification and adjustment

[0824] The server verifies that the generated route complies with traffic rules and is safe. If necessary, it adjusts the route to determine the optimal delivery route. If the route includes tourist attractions, it also incorporates their locations into the route.

[0825] 6. Sending and displaying course data

[0826] The final course data is sent from the server to the user's smartphone. The smartphone application receives this course data and displays it to the user. The user can check information such as the course map, travel methods, total distance, required time, and tourist attractions along the way.

[0827] Specific examples

[0828] For example, let's consider a scenario where a delivery staff member wants to cycle around multiple delivery destinations in Shibuya Ward, Tokyo, and simultaneously generate a route that draws a heart shape. In this case, the user inputs the following information into the smartphone application: Shibuya Ward, bicycle, 5 kilometers, heart, and safety priority.

[0829] Example prompt sentence:

[0830] "Generate routes to three delivery destinations by bicycle within the Shibuya Ward area. Safety is the top priority and I would like the route to follow traffic rules."

[0831] In this way, users input the necessary information and the system automatically generates the optimal delivery route, which is safe and efficient, allowing delivery staff to visit tourist attractions and provide high-value-added services.

[0832] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0833] Step 1:

[0834] The user inputs the area, mode of transportation, distance, and theme they want to draw.

[0835] The user starts the smartphone application and inputs information such as the area, mode of transportation, distance, theme to be drawn, priority of safety or priority of tourist attractions into the specified interface. This input data is collected and sent to the server in the next step.

[0836] Step 2:

[0837] Sending input information to the server

[0838] When the user presses the "Generate Route" button, the device sends all the data entered, including information about the area, mode of transportation, distance, theme, and priority, to the server. The data is sent in JSON format to the server.

[0839] Step 3:

[0840] Map data acquisition and analysis

[0841] The server uses the received data to obtain map data for the specified area using the Google Maps API. The obtained map data is then analyzed to extract information on major roads, intersections, buildings, etc. The extracted information is then used to generate the route.

[0842] Step 4:

[0843] Theme-based specific shape generation

[0844] The server generates a specific shape based on a theme entered by the user (e.g., a heart shape), using a theme-specific path generation algorithm. The generated shape becomes the basis for the final route design.

[0845] Step 5:

[0846] Route generation using AI models

[0847] The server generates routes using an AI model, taking safety and traffic rules into consideration. This AI model uses machine learning frameworks such as TensorFlow and PyTorch. The optimal route is calculated based on input data (map information, specific shapes, and traffic rules).

[0848] Step 6:

[0849] Validate and adjust the generated route

[0850] The server verifies that the generated route complies with traffic rules and is safe. It runs a simulation to check for safety issues and adjusts the route as necessary. Once verified, the route data is prepared for transmission in the next step.

[0851] Step 7:

[0852] Include tourist attractions in your route

[0853] The server references tourist attraction data and incorporates tourist attractions into the generated route. If the user has set tourist attractions as a priority, the server adjusts the route to pass through the tourist attractions. The final route after adjustment is determined.

[0854] Step 8:

[0855] Submitting the final course data

[0856] The final course data is sent from the server to the user's smartphone, including a map of the route, travel methods, total distance, travel time, and information on tourist attractions.

[0857] Step 9:

[0858] Viewing course data

[0859] The device displays the received route data through a user interface, allowing the user to efficiently deliver the goods while checking the route map and understanding the travel method, total distance, required time, and tourist attractions.

[0860] 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.

[0861] System Overview

[0862] This invention is a system that automatically generates GPS art courses based on user input data. An emotion engine that recognizes the user's emotions is incorporated as an additional element, allowing the system to generate courses according to the user's emotional state. This system allows the user to input their area, mode of transportation, distance, and desired theme, and generates a safe and efficient route based on that information. It can also generate courses that take into account traffic rules and include tourist attractions.

[0863] composition

[0864] 1. User-entered data

[0865] region

[0866] Transportation

[0867] distance

[0868] Themes I want to draw

[0869] Safety priority or tourist attraction priority

[0870] 2. Server Functions

[0871] Receiving input data

[0872] Map data acquisition and analysis

[0873] Shape generation based on user themes

[0874] Route generation using AI models

[0875] Emotion data analysis and route adjustment using an emotion engine

[0876] Verifying route safety and traffic rules

[0877] Sending course data to your device

[0878] 3. Device Features

[0879] Providing an input interface

[0880] Receiving and displaying course data

[0881] Collecting and transmitting emotional states

[0882] Program processing

[0883] 1. Receiving user input

[0884] Device: The user opens the application on the device and inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions. In addition, an emotion engine that collects the user's emotional state operates and obtains emotion data from the device.

[0885] 2. Sending input information to the server

[0886] Terminal: When the user presses the "Generate" button, the input data and emotion data are sent to the server. The sent data includes the area, transportation method, distance, theme, priority of safety or tourist attractions, and emotion data.

[0887] 3. Server-side data processing

[0888] server:

[0889] Input data and emotion data are received.

[0890] Obtain map data for the specified area and retrieve detailed information from the database, including road information, intersections, traffic lights, and other transportation infrastructure.

[0891] It runs an algorithm to generate a specific shape based on the user's theme and creates a pattern to form that shape.

[0892] The system uses an AI model to generate routes that fit the specified distance based on the acquired map data and thematic shape information. The route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[0893] The emotion engine analyzes the emotional data and adjusts the route generation accordingly. For example, if the emotion is relaxation, it will select a route that passes through a quiet park, and if the emotion is excitement, it will select a route that includes active tourist attractions.

[0894] The generated route is simulated to check whether it is safe and complies with traffic rules, and the route is fine-tuned if necessary.

[0895] The final course data that has been verified is prepared and sent to the terminal.

[0896] 4. Receiving and Displaying Course Information

[0897] Device: Displays the route data received from the server to the user, including the route map, travel method, total distance, estimated travel time, points of interest along the way, and special route adjustment information based on emotional state.

[0898] Specific examples

[0899] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[0900] 1. Receiving user input

[0901] Device: The user enters information about Shibuya Ward, running, 5 kilometers, heart rate, and safety priority into the application. The emotion engine then recognizes the user's emotional state and determines that the user needs to relax.

[0902] 2. Sending input information to the server

[0903] Device: Press the "Generate" button to send the information to the server, along with the emotion data.

[0904] 3. Data Processing

[0905] server:

[0906] Obtain map data for Shibuya Ward and analyze road information.

[0907] Generate a heart-shaped pattern and check if it is suitable for 5 kilometers.

[0908] Using an AI model, the system generates a safe route that follows traffic rules. Because the user's emotional state indicates a desire for relaxation, the system selects routes that pass through parks and natural areas as much as possible.

[0909] The route will also include tourist attractions such as the Hachiko statue and Yoyogi Park.

[0910] Simulate the generated route to ensure it is safe and adjust it if necessary.

[0911] The final course data is sent to the device.

[0912] 4. View course information

[0913] Terminal: Displays to the user a course map, mode of travel, distance, time required, tourist attractions, and special route adjustment information based on emotional state.

[0914] In this way, users can generate safe and efficient GPS art courses tailored to their emotional state.

[0915] The processing flow will be explained below.

[0916] Step 1:

[0917] User: Opens the application on the device. The user inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions. Furthermore, the emotion engine collects the user's emotional state and analyzes the current emotional state.

[0918] Step 2:

[0919] Terminal: When the user presses the "Generate" button, the input data and emotion data are sent to the server. The sent data includes the area, transportation method, distance, theme, priority of safety or tourist attractions, and emotion data.

[0920] Step 3:

[0921] Server: Analyzes the data received from the device. Specifically, it retrieves map data for the area specified by the user and obtains detailed information from a database, including road information, intersections, traffic lights, and other traffic infrastructure information.

[0922] Step 4:

[0923] Server: Performs thematic analysis. Based on a theme entered by the user (e.g., "heart"), it runs an algorithm to generate a specific shape and creates the patterns that form that shape.

[0924] Step 5:

[0925] Server: Generates a route using an AI model. This generates a route that matches the specified distance based on the acquired map data and thematic shape information. Route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[0926] Step 6:

[0927] Server: Analyzes emotional data. The emotional state of the user recognized by the emotion engine (e.g., "I want to relax" or "I want an active experience") is analyzed and reflected in route generation.

[0928] Step 7:

[0929] Server: Adjusts the route based on emotional data. For example, if the emotional state is one of relaxation, it selects a route that passes through parks and quiet roads, and if the emotional state is active, it selects a route that includes tourist attractions and bustling places.

[0930] Step 8:

[0931] Server: Adjust the route to include tourist attractions. If the user sets a high priority for a tourist attraction, the server will incorporate the specified tourist attraction (e.g., Hachiko Statue, Yoyogi Park, etc.) into the route and recalculate the route to reach that attraction.

[0932] Step 9:

[0933] Server: Validates the generated route, simulating whether it complies with traffic rules and ensures safety, and fine-tunes the route if necessary.

[0934] Step 10:

[0935] Server: Prepares the final course data after verification and sends it to the device.

[0936] Step 11:

[0937] Device: Displays the route data received from the server to the user, including the route map, travel method, total distance, estimated travel time, points of interest along the way, and special route adjustment information based on emotional state.

[0938] Step 12:

[0939] User: Checks the provided course information, and if satisfied, prepares to actually exercise the course.

[0940] Example 2

[0941] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0942] Previous GPS Art route generation systems did not take the user's emotional state into account, making it difficult to provide routes that suited the user's mental and physical needs. Furthermore, they rarely guaranteed safety or compliance with traffic rules, making it difficult to generate appropriate routes for specific modes of transportation. Another problem was that they were unable to automatically generate routes that included tourist attractions, and lacked features that would increase the user's enjoyment.

[0943] 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.

[0944] In this invention, the server includes means for the user to input the area, mode of transportation, distance, and theme to be drawn, means for recognizing the user's emotional state and collecting relevant data, means for transmitting the input data and emotional data to the server, means for the server to analyze map data based on the data received, means for generating a specific shape based on the theme, means for generating a route using an AI model taking into account safety and traffic rules, means for adjusting the generated route based on the emotional data, means for verifying and adjusting the generated route, means for transmitting the final course data to the terminal, and means for the terminal to display the course data. This enables the generation of an optimal route that takes into account the user's emotional state, safety, and traffic rules, providing a safer and more enjoyable GPS art experience.

[0945] "Region" is data indicating the location or area where the user performs GPS art.

[0946] "Means of transportation" is data that indicates the method or tool (e.g., running, cycling, etc.) used by the user to create GPS art.

[0947] "Distance" is data indicating the total distance traveled by the user when drawing GPS art.

[0948] The "theme to be drawn" is data indicating a specific shape or figure (e.g., heart, star, etc.) that the user wants to draw in GPS Art.

[0949] "Emotional state" is data that indicates the mental or emotional state of a user.

[0950] An "emotion engine" refers to a function or system for recognizing a user's emotions and analyzing their state.

[0951] "Server" refers to a central computing system for receiving and processing data sent by users.

[0952] A "data packet" is a unit of information that includes user input data and emotion data and is sent to the server.

[0953] "Map Data" refers to a data set containing details of roads, intersections, traffic lights, etc. for a specified area.

[0954] A "theme shape" is data that indicates a shape that embodies a figure or pattern that the user wants to draw.

[0955] "AI Model" refers to the artificial intelligence algorithm used to generate the route.

[0956] "Route adjustment" is the process of making corrections and optimizations to the generated route based on the user's emotional data and other considerations.

[0957] "Course data" refers to data that indicates the final route information of the GPS Art that has been analyzed and generated.

[0958] "Terminal" refers to the device (e.g., smartphone, tablet, etc.) used by the user to enter and display the final course data.

[0959] "Tourist attractions" are data that indicate particular geographical locations or cultural facilities that may be of interest to users.

[0960] System Overview

[0961] This invention is a system that automatically generates GPS art courses based on user input and emotional data. The system generates a theme shape based on user-entered information and uses an AI model to generate a route that matches it. It also incorporates an emotion engine that recognizes the user's emotional state and adjusts the route accordingly. Users can input their area, mode of transportation, distance, theme they want to draw, and safety or tourist attraction priorities.

[0962] Hardware and software used

[0963] 1. User device (e.g. smartphone, tablet)

[0964] A device that allows users to input data and interact with the system, incorporating an input interface and emotion engine.

[0965] 2. Server

[0966] It is a central computing system for receiving and processing input data and emotion data, analyzing map data, generating theme shapes, generating routes using AI models, making adjustments based on emotion data, and transmitting the final course data.

[0967] Program processing explanation

[0968] Receiving user input

[0969] The user opens the application on their device and enters the following information: area (e.g., "Shibuya-ku, Tokyo"), mode of transportation (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and safety or tourist attraction priority. Furthermore, an emotion engine runs, collecting the user's emotional state using the camera and microphone.

[0970] Sending input information to the server

[0971] When the user presses the "Generate" button, the device sends this data to the server, including the area, mode of transportation, distance, theme, safety or tourist attraction priority, and emotion data.

[0972] Server-side data processing

[0973] The server does the following:

[0974] Receives input data and emotion data.

[0975] Obtain map data for the specified area and extract detailed information such as road information, intersections, and traffic lights from the database.

[0976] It runs an algorithm that generates a specific shape based on the user's theme, then creates a pattern to form that shape.

[0977] Routes are generated using AI models, taking safety and traffic rules into consideration during the process.

[0978] The generated route is adjusted based on the analysis results of the emotion engine. For example, if the user wants to "relax," the system will select a route that passes through parks and quiet places.

[0979] Simulate the generated route to ensure it is safe and make any necessary adjustments.

[0980] The final course data is sent to the device.

[0981] Receive and view course information

[0982] The device displays the course data received from the server to the user, including:

[0983] Course Map

[0984] How to move

[0985] Total distance

[0986] Estimated time required

[0987] Tourist attractions to visit

[0988] Special route adjustment information based on emotional state

[0989] Specific examples

[0990] If a user wants to generate a 5km course in Shibuya, Tokyo, where they will draw a heart shape while running:

[0991] 1. The user enters the following information into the application: Shibuya Ward, running, 5km, heart, safety first. The emotion engine recognizes that the user needs to relax.

[0992] 2. Press the "Generate" button to send the information to the server, along with the emotion data.

[0993] 3. The server retrieves map data for Shibuya Ward and analyzes road information. A heart-shaped pattern is generated, and an AI model is used to generate a safe route that takes traffic rules into account. Since the driver is looking for relaxation, parks and quiet routes are selected whenever possible. Tourist attractions are also included.

[0994] 4. Include tourist attractions such as the Hachiko statue and Yoyogi Park in your route.

[0995] 5. The generated route is simulated to check its safety, and fine-tuned if necessary. The final course data is sent to the device.

[0996] 6. The device displays the route map, travel method, distance, travel time, tourist attraction information, and special route adjustment information based on emotional state to the user.

[0997] Example prompt sentence:

[0998] "Generate a 5-kilometer course to trace a heart shape while running in Shibuya, Tokyo, prioritizing safety. I'm in the mood for relaxation right now."

[0999] In this way, users can generate safe and efficient GPS art courses tailored to their emotional state.

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

[1001] Step 1:

[1002] Receiving user input

[1003] The user opens the application on their device and inputs their "area" (e.g., "Shibuya-ku, Tokyo"), "mode of transportation" (e.g., "running"), "distance" (e.g., "5 kilometers"), "theme to draw" (e.g., "heart"), and "safety priority" or "tourist attraction priority." The emotion engine then operates, collecting the user's emotional state via the camera and microphone and converting it into digital data.

[1004] Input: Region, mode of transportation, distance, theme, priority, emotional state

[1005] Output: Collected user input data and emotion data

[1006] Step 2:

[1007] Preparing to send input information

[1008] The terminal assembles the collected user input data and emotion data into a single data packet, which includes the area, mode of transportation, distance, theme, priority of safety or tourist attractions, and emotion data.

[1009] Input: Collected user input data and emotion data

[1010] Output: Data packets

[1011] Step 3:

[1012] Sending data to the server

[1013] When the user presses the "Generate" button, the terminal sends a data packet to the server.

[1014] Input: Data packet

[1015] Output: Send data to the server

[1016] Step 4:

[1017] Receiving data

[1018] The server receives data packets sent from the terminal, which include region, mode of transportation, distance, theme, priority, and emotion data.

[1019] Input: Data packet

[1020] Output: Received data

[1021] Step 5:

[1022] Map data acquisition and analysis

[1023] The server retrieves map data for the area specified by the user and extracts detailed information from the database, such as road information, intersections, and traffic light locations. Through this analysis, it collects topographical and infrastructure information that will be the basis for route generation.

[1024] Input: Region data

[1025] Output: Map data (road information, intersections, traffic light locations, etc.)

[1026] Step 6:

[1027] Theme Shape Generation

[1028] The server runs an algorithm to generate a specific shape based on a user-specified theme (e.g., "heart"), which generates specific paths and segment patterns to form the theme shape.

[1029] Input: Theme data

[1030] Output: Theme Shape Pattern

[1031] Step 7:

[1032] Route Generation

[1033] The server uses an AI model to generate a route based on the acquired map data and the generated thematic shape patterns, taking into account safety and traffic rules (e.g., one-way streets, bicycle lanes, etc.) depending on the mode of travel.

[1034] Input: Map data and thematic shape patterns

[1035] Output: Generated routes

[1036] Step 8:

[1037] Route adjustment based on emotion data

[1038] The server then adjusts the generated route using the emotion data analyzed by the emotion engine. For example, if the user is looking to relax, the server may select a route that includes parks and plenty of nature.

[1039] Input: Generated route and emotion data

[1040] Output: Adjusted route

[1041] Step 9:

[1042] Safety and traffic rules verification

[1043] The server simulates the generated route to ensure safety and compliance with traffic rules, and fine-tunes the route if necessary.

[1044] Input: Adjusted Route

[1045] Output: Final route

[1046] Step 10:

[1047] Prepare and submit final course data

[1048] The server prepares the final course data and sends it to the device, which includes the course map, travel mode, distance, travel time, tourist attractions, and special route adjustment information based on emotional state.

[1049] Input: Final Route

[1050] Output: Send course data to the device

[1051] Step 11:

[1052] View course information

[1053] The device displays the course data received from the server to the user, including the course map, travel method, distance, travel time, tourist attractions along the way, and special route adjustment information based on emotional state.

[1054] Input: Course data

[1055] Output: Course information displayed to user

[1056] (Application example 2)

[1057] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1058] Conventional automated patrol systems within factories have the problem of not being able to fully consider safety and efficiency when generating routes. Furthermore, because the emotional state of the operator is not reflected in the patrol route, it is difficult to manage stress and ensure appropriate rest areas. The present invention aims to solve these problems and provide a system that achieves safe and efficient patrol within a factory.

[1059] 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.

[1060] In this invention, the server includes means for the user to input the area, means of transportation, distance, and theme to be drawn, means for transmitting the input data to the server, and means for collecting emotion data and adjusting the route based on the emotion data, thereby enabling route adjustment based on the emotion data and generation of work areas and process points for equipment maintenance.

[1061] A "region" is a geographical location specified by the user, and is the basic information for generating a route.

[1062] "Transportation" refers to the transportation method designated by the user, and includes running, cycling, car, etc.

[1063] "Distance" is the distance the user desires to travel, and is a parameter that specifies the length of the route.

[1064] The "theme" is the specific shape or pattern desired by the user, and serves as the basis for GPS art.

[1065] The "means for transmitting data to a server" is a function for sending information entered by a user to a server via a network.

[1066] The "means for analyzing map data based on data received by the server" is a function for extracting and analyzing detailed information on the map based on information received by the server from the user.

[1067] The "means for generating a specific shape based on a theme" is a function for generating a specific shape or pattern on a map based on a theme input by the user.

[1068] "Means for generating routes using AI models, taking into account safety and traffic rules" refers to a function that automatically generates optimal routes using AI models, taking into account the safety and traffic rules of each means of transportation.

[1069] "Means for verifying and adjusting the generated route" refers to a function that simulates whether the generated route complies with safety and traffic rules, and makes fine adjustments as necessary.

[1070] The "means for transmitting final course data to the terminal" is a function for transmitting the generated final route information to the terminal.

[1071] The "means for the terminal to display course data" refers to a function for visually displaying the course data received by the terminal to the user.

[1072] The "means for collecting emotional data and adjusting the route based on the emotional data" is a function that analyzes the user's emotional state using an emotional engine and optimizes the route based on that data.

[1073] The "means for generating patrol routes within a factory and supporting patrol by a robot" is a function that generates routes that allow a robot to patrol a factory efficiently and safely, and supports that patrol.

[1074] The "means for generating a route including tourist attractions" is a function for generating a route including tourist attractions within a specified area.

[1075] "Means for generating process points for work areas and equipment maintenance" is a function that includes specific work areas within a factory and points of equipment that require maintenance in the route.

[1076] "Means for providing the user with final course information and planning exercise based on that information" is a function that provides information for the user to plan exercise based on the generated route information.

[1077] The "means for planning patrol routes to improve work efficiency and safety within a factory" is a function for planning patrol routes within a factory and improving work efficiency and safety.

[1078] System Overview

[1079] The present invention is an automatic route generation system for a factory that generates an efficient and safe route based on user input data. The system is composed of the following elements:

[1080] System Configuration

[1081] 1. User-entered data

[1082] Area (e.g. Factory Zone A)

[1083] Means of transportation (e.g., patrol robot)

[1084] Distance (e.g. 5 kilometers)

[1085] The theme you want to draw (e.g., shortest route)

[1086] Prioritizing safety or patrol efficiency

[1087] Emotional data (e.g., stress level, preferred_break_spot)

[1088] 2. Server Functions

[1089] Receiving input data

[1090] Map data acquisition and analysis

[1091] Shape generation based on user themes

[1092] Route adjustment based on emotion data analysis

[1093] Route generation using AI models

[1094] Verifying route safety and traffic rules

[1095] Sending the final course data to the device

[1096] 3. Device Features

[1097] Providing an input interface

[1098] Receiving and displaying course data

[1099] Collecting and transmitting emotional states

[1100] Program processing explanation

[1101] 1. Receiving user input data

[1102] The terminal receives information from the user, such as area, mode of transportation, distance, theme, priority of safety or patrol efficiency, and emotion data. This input data is input by the user by opening an application on the terminal.

[1103] 2. Sending input information to the server

[1104] When the user presses the "generate" button, the terminal transmits the input data and emotion data to the server.

[1105] 3. Server-side data processing

[1106] The server analyzes the received data and retrieves map data for the specified area. It then uses an AI model to generate a route that takes safety and efficiency into account. It adjusts the route based on emotion data, prioritizing rest areas if stress levels are high, for example. Finally, the generated route is verified for safety and compliance with traffic rules, and fine-tuning is performed as needed.

[1107] Hardware and software used

[1108] Hardware: Servers (dedicated servers or cloud servers), user devices (smartphones, tablets, laptops, etc.)

[1109] Software: Application (to provide user interface), AI model (to generate routes), emotion engine (to analyze emotion data)

[1110] Specific examples

[1111] Let's take the example of a user wanting to generate a safe and efficient 5-kilometer patrol route for a patrol robot in factory zone A, which is experiencing a high stress level. The user opens the application, selects factory zone A, inputs the information for the patrol robot, 5 kilometers, shortest route, and safety priority, and sends emotional data indicating a high stress level.

[1112] The server acquires map data for Factory Zone A and analyzes road information. At the same time, it generates a route that prioritizes rest areas based on emotion data, and generates a final route that takes safety and traffic rules into consideration. This route data is sent to the terminal and displayed to the user.

[1113] Prompt Sentence Examples

[1114] Generate a safe patrol route that is optimal for workers with a stress level of 3 based on the user-specified factory zone A. In particular, create a route that prioritizes rest areas. The means of transportation is a "patrol robot." The generated route should include the locations of each waypoint and the actions to be taken at each point.

[1115] In this way, users can generate safe and efficient routes around the factory that are tailored to their emotional state.

[1116] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1117] Step 1:

[1118] The user opens the application on their device and inputs the area (e.g., factory zone A), the means of transportation (e.g., patrol robot), the distance (e.g., 5 kilometers), the theme they want to draw (e.g., the shortest route), the priority of safety (or the priority of patrol efficiency), and emotional data (e.g., stress level). The input data is formatted in JSON format.

[1119] Input: Region, mode of transportation, distance, theme, safety priority, sentiment data

[1120] Output: Input data in JSON format

[1121] Step 2:

[1122] When the user presses the "Generate" button, the terminal sends the formatted JSON input data to the server using an HTTP POST request.

[1123] Input: Input data in JSON format

[1124] Output: POST request to the server

[1125] Step 3:

[1126] The server analyzes the received JSON format data and obtains map data for the specified area (Factory Zone A). It also obtains data on traffic infrastructure such as road information, intersections, and traffic lights from a database.

[1127] Input: JSON format input data received via POST request

[1128] Output: Map data, road information, traffic infrastructure data

[1129] Step 4:

[1130] The server runs an algorithm that generates a particular shape based on the theme, and creates patterns to form that shape, for example, if the theme is "shortest path", it will generate patterns to form the shortest path.

[1131] Input: User's theme (e.g. shortest path)

[1132] Output: Specific shape pattern

[1133] Step 5:

[1134] The server generates a route using an AI model. It uses acquired map data and a shape pattern based on the theme to generate a route that fits the specified distance (5 kilometers). It generates the route while taking into account the safety and traffic rules of each mode of transportation.

[1135] Input: Map data, shape pattern, distance, means of transportation

[1136] Output: Generated routes

[1137] Step 6:

[1138] The server analyzes the emotion data and adjusts the route accordingly. For example, if the stress level is high, the server may select a route that prioritizes rest areas. The server processes the emotion data using an emotion engine and fine-tunes the route.

[1139] Input: Generated route, emotion data

[1140] Output: Adjusted route

[1141] Step 7:

[1142] The server simulates and verifies the generated route to ensure safety and compliance with traffic rules, and fine-tunes the route if there are any issues with safety or traffic rules.

[1143] Input: Adjusted Route

[1144] Output: Final route

[1145] Step 8:

[1146] The server then sends the final course data to the device, which includes the location of each waypoint, the actions to be taken, the distance, and the estimated time required.

[1147] Input: Final route

[1148] Output: Course data to the device

[1149] Step 9:

[1150] The terminal displays the course data received from the server to the user, who can then check information such as the course map, travel method, total distance, estimated time required, and rest areas along the way.

[1151] Input: Course data received from the server

[1152] Output: Course information displayed on the user interface

[1153] 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.

[1154] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1155] 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.

[1156] [Third embodiment]

[1157] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1158] 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.

[1159] 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).

[1160] 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.

[1161] 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.

[1162] 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).

[1163] 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.

[1164] 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.

[1165] 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.

[1166] 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.

[1167] 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.

[1168] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1169] System Overview

[1170] This system automatically generates a GPS art course based on user input data. Users input their area, mode of transportation, distance, and the theme they want to draw, and a safe and efficient route is generated based on that information. It can also generate a course that takes into account traffic rules and includes tourist attractions.

[1171] composition

[1172] 1. User-entered data

[1173] region

[1174] Transportation

[1175] distance

[1176] Themes I want to draw

[1177] Safety priority or tourist attraction priority

[1178] 2. Server Functions

[1179] Receiving input data

[1180] Map data acquisition and analysis

[1181] Shape generation based on user themes

[1182] Route generation using AI models

[1183] Verifying route safety and traffic rules

[1184] Sending course data to your device

[1185] 3. Device Features

[1186] Providing an input interface

[1187] Receiving and displaying course data

[1188] Program processing

[1189] 1. Receiving user input

[1190] Device: The user opens the application on the device and inputs the area, mode of transportation, distance, theme to be drawn, safety priority or tourist attraction priority.

[1191] 2. Sending input information to the server

[1192] Terminal: When the user presses the "Generate" button, the input data is sent to the server.

[1193] 3. Server-side data processing

[1194] server:

[1195] Receives input data and retrieves map data for the specified area.

[1196] The acquired map data is analyzed and information such as major roads and intersections is extracted.

[1197] Generate specific shapes based on user themes.

[1198] An AI model is used to generate routes that take safety and traffic rules into consideration.

[1199] If you include a tourist attraction, incorporate its location into the route.

[1200] Verify that the generated route complies with traffic rules and is safe.

[1201] The verified course data is sent to the device.

[1202] 4. Receiving and Displaying Course Information

[1203] Terminal: Displays the course data received from the server to the user. The user can check information such as the course map, travel method, total distance, required time, and tourist attractions along the way.

[1204] Specific examples

[1205] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[1206] 1. Receiving user input

[1207] Device: The user enters the following information into the application: Shibuya Ward, Running, 5km, Heart, Safety First.

[1208] 2. Sending input information to the server

[1209] Terminal: Press the "Generate" button to send the information to the server.

[1210] 3. Data Processing

[1211] server:

[1212] Obtain map data for Shibuya Ward and analyze road information.

[1213] Generate a heart-shaped pattern and check if it is suitable for 5 kilometers.

[1214] Using AI models, routes that are safe and comply with traffic rules are generated.

[1215] The route will include tourist attractions such as the Hachiko statue and Yoyogi Park.

[1216] Simulate the generated route to ensure it is safe and adjust it if necessary.

[1217] The final course data is sent to the device.

[1218] 4. View course information

[1219] Terminal: Displays course information to the user, including course maps, transportation methods, distance, time required, and points of interest.

[1220] In this way, users can easily create safe and efficient GPS art courses.

[1221] The processing flow will be explained below.

[1222] Step 1:

[1223] User: Opens the application on the device. The user inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions.

[1224] Step 2:

[1225] Terminal: When the user presses the "Generate" button, the entered data is sent to the server, including the area, mode of transportation, distance, theme, and safety or tourist attraction priority.

[1226] Step 3:

[1227] Server: Analyzes the data received from the device. Specifically, it retrieves map data for the area specified by the user and obtains detailed information from a database, including road information, intersections, traffic lights, and other traffic infrastructure information.

[1228] Step 4:

[1229] Server: Performs thematic analysis. Based on a theme entered by the user (e.g., "heart"), it runs an algorithm to generate a specific shape and creates the patterns that form that shape.

[1230] Step 5:

[1231] Server: Generates a route using an AI model. This generates a route that matches the specified distance based on the acquired map data and thematic shape information. Route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[1232] Step 6:

[1233] Server: Adjust the route to include tourist attractions. If the user sets a high priority for a tourist attraction, the server will incorporate the tourist attraction (e.g., Hachiko Statue, Yoyogi Park, etc.) into the route and recalculate the route to reach that attraction.

[1234] Step 7:

[1235] Server: Validates the generated route, simulating whether it complies with traffic rules and ensures safety, and fine-tunes the route if necessary.

[1236] Step 8:

[1237] Server: Prepares the final course data after verification and sends it to the device.

[1238] Step 9:

[1239] Terminal: Displays the course data received from the server to the user. The displayed content includes the course map, travel method, total distance, estimated time required, and tourist attractions along the way.

[1240] Step 10:

[1241] User: Checks the provided course information, and if satisfied, prepares to actually exercise the course.

[1242] Example 1

[1243] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1244] Conventional route planning systems lack the ability to generate specific shapes based on user themes, and it is difficult to generate routes that fully consider safety and traffic rules. Furthermore, generating routes that include tourist attractions and verifying and adjusting the generated routes are time-consuming, making it difficult for users to easily obtain efficient and safe routes.

[1245] 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.

[1246] In this invention, the server includes means for acquiring and analyzing map data based on input data, means for generating a specific shape based on a theme, and means for inputting a prompt sentence to the AI ​​model to generate a route that takes safety and traffic rules into consideration, thereby enabling a user to easily generate a route with a specific shape based on a theme and obtain an efficient course that complies with safety and traffic rules.

[1247] A "region" is a particular geographic area that a user specifies when generating a route.

[1248] "Transportation" refers to the method or mode of transportation used by a user to travel a route, including, for example, walking, cycling, or driving.

[1249] "Distance" is the length of the route specified by the user, typically expressed in kilometers.

[1250] The "theme to be drawn" indicates the shape and purpose of the route that the user wants to generate, and includes a specific shape or pattern.

[1251] "Safety priority" is an index that indicates the priority of safety in route generation.

[1252] The "priority of tourist attractions" is an index that indicates the priority with which tourist attractions are emphasized in route generation.

[1253] "Map data" is a data set containing geographic information for a particular area, including information on roads, intersections, etc.

[1254] The "particular shape" refers to a particular pattern or shape that is generated based on a user's theme.

[1255] An "AI model" is a computational model that uses artificial intelligence to analyze data and perform specific tasks.

[1256] A "prompt sentence" is an input sentence used to prompt an AI model to perform a specific task.

[1257] "Generating a route" means calculating and determining a route that takes safety and traffic rules into consideration based on data input by the user.

[1258] "Validation" is the process of checking whether the generated route is correct and complies with certain conditions.

[1259] "Adjustment" means making necessary corrections based on the results of verification.

[1260] "Course data" is a detailed data set that includes the generated route, including route coordinates, distance traveled, time required, etc.

[1261] A "terminal" is a hardware device through which a user enters input data and receives final course information.

[1262] MODE FOR CARRYING OUT THE INVENTION

[1263] System Overview

[1264] This invention is a system that automatically generates routes based on user input data. Users input their area, mode of transportation, distance, and the theme they want to depict, and a safe and efficient route is generated based on that information. Furthermore, traffic rules are taken into account and tourist attractions can be included in the route. The operation of the system will be explained in detail using a specific example.

[1265] Hardware and software used

[1266] Device: User device such as a smartphone or tablet

[1267] Server: High-performance computing server

[1268] Map Data API: Google Maps API

[1269] Geographic information processing libraries: Geopy, Fiona

[1270] Shape manipulation library: Shapely

[1271] AI model: OpenAI GPT-3 model

[1272] Map display libraries: Mapbox, Leaflet

[1273] Program processing

[1274] 1. Receiving user input

[1275] Device: The user opens the application on their device and enters the area (e.g., Shibuya Ward), mode of transportation (e.g., running), distance (e.g., 5 kilometers), theme to draw (e.g., heart), and safety priority or tourist attraction priority (e.g., safety).

[1276] 2. Sending input information to the server

[1277] Terminal: When the user presses the "Generate" button, the input data is converted to JSON format and a POST request is sent to the server's API endpoint.

[1278] 3. Server-side data processing

[1279] Server: Receives input data and retrieves map data for the specified area (Shibuya Ward) using the Google Maps API.

[1280] Server: Analyzes the acquired map data and extracts information such as major roads and intersections using geographic information processing libraries such as Geopy and Fiona.

[1281] Specifically, the map data is parsed and the locations of road segments and intersections are stored in list format.

[1282] Server: Generates specific shapes (e.g., hearts) based on the user's theme. Shape manipulation libraries such as Shapely are used for shape generation.

[1283] Specifically, a heart-shaped Bezier curve is generated and a route is created along it.

[1284] Server: Enter a prompt into a generative AI model (e.g., OpenAI's GPT-3) to generate an optimal route. An example prompt is as follows:

[1285] Prompt statement:

[1286] The user is looking for a 5-kilometer running course in Shibuya, Tokyo. The course should be heart-shaped, and safety is a priority. Generate a route that passes by the Hachiko statue and Yoyogi Park as much as possible.

[1287] 4. The server verifies traffic rules and safety

[1288] Server: Simulates whether the generated route complies with traffic rules and is safe. The simulation uses traffic rule-related datasets and a rule engine.

[1289] As a specific example, check whether there are traffic lights at intersections or whether there are pedestrian-only roads.

[1290] Server: If necessary, fine-tune the output of the AI ​​model to align with safety and traffic rules.

[1291] 5. The generated route data is sent to the device.

[1292] Server: Once the final route is validated, it converts the route data into JSON format and sends it to the device, including route coordinates, distance traveled, travel time, and location information of tourist attractions.

[1293] 6. The device will display the route information.

[1294] Terminal: Analyzes the route data received from the server and displays it to the user. A map display library such as Mapbox or Leaflet is used for displaying the data.

[1295] For example, the system draws a route on a map, places pins at each tourist spot, and displays detailed information such as the mode of transportation, total distance, and required time on the screen.

[1296] Specific examples

[1297] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[1298] User: Enters "Shibuya Ward, running, 5km, heart, safety first" into the app.

[1299] Terminal: Press the "Generate" button and the data will be sent to the server in JSON format.

[1300] Server: Obtains Shibuya Ward map data via the Google Maps API and analyzes road information using the Geopy library. Shapely generates a heart-shaped pattern, and a GPT-3 model generates a safe route, taking into account routes that pass through the Hachiko statue and Yoyogi Park.

[1301] Server: Validates the generated route based on traffic rules and safety, and sends the final route data to the device.

[1302] Terminal: The received route is displayed on a map, and the user can check the course map, travel method, total distance, required time, and tourist attractions.

[1303] This process allows users to easily generate safe and efficient routes with thematic geometries.

[1304] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1305] Step 1:

[1306] User: Opens the application and enters the area (e.g. Shibuya Ward), mode of transportation (e.g. running), distance (e.g. 5 kilometers), theme to draw (e.g. heart), and safety priority or tourist attraction priority (e.g. safety).

[1307] Input: Region, mode of transport, distance, theme, safety or tourist attraction priority

[1308] Output: User input data (JSON format)

[1309] Step 2:

[1310] Terminal: Validates the entered data, and when the user presses the "Generate" button, converts the input data into JSON format and sends it to the server.

[1311] Input: User-entered data

[1312] Data processing: Convert user input data into JSON format

[1313] Output: POST request to the server

[1314] Step 3:

[1315] Server: Receives input data and retrieves map data for the specified area (Shibuya Ward) using the Google Maps API.

[1316] Input: User-entered data

[1317] Data processing: Retrieving and parsing map data

[1318] Output: Parsed map data (a list containing road and intersection information)

[1319] Step 4:

[1320] Server: Analyzes the acquired map data and extracts information on major roads and intersections.

[1321] Input: Map data

[1322] Data processing: Analysis of map data using Geopy and Fiona libraries

[1323] Output: A list of extracted road segments and intersections

[1324] Step 5:

[1325] Server: Generates a specific shape (e.g., heart) based on the user's theme.

[1326] Input: User theme, list of road segments and intersections

[1327] Data processing: Shape generation using the Shapely library

[1328] Output: Generated theme shape (e.g. heart-shaped route)

[1329] Step 6:

[1330] Server: Enters a prompt into a generative AI model (e.g., GPT-3) and generates a route that takes safety and traffic rules into consideration.

[1331] Input: Generated theme shapes

[1332] Data processing: Route generation using an AI model based on prompts

[1333] Output: Initial generated route

[1334] Example prompt sentence:

[1335] Prompt statement:

[1336] The user is looking for a 5-kilometer running course in Shibuya, Tokyo. The course should be heart-shaped, and safety is a priority. Generate a route that passes by the Hachiko statue and Yoyogi Park as much as possible.

[1337] Step 7:

[1338] Server: Simulates whether the generated route complies with traffic rules and is safe. Adjusts the route if necessary.

[1339] Input: Initial generated route, traffic rule dataset

[1340] Data processing: Verification and adjustment based on traffic rules and safety

[1341] Output: Final generated route

[1342] Step 8:

[1343] Server: Once the final route is validated, it converts the route data into JSON format and sends it to the device.

[1344] Input: Final generated route

[1345] Data processing: Converting route data to JSON format

[1346] Output: Send route data to the device

[1347] Step 9:

[1348] Terminal: Analyzes the route data received from the server and displays it to the user. A map display library such as Mapbox or Leaflet is used for displaying the data.

[1349] Input: Route data received from the server

[1350] Data processing: Route data analysis and mapping

[1351] Output: User-visible route map, detailed information such as travel methods, total distance, travel time, and points of interest

[1352] The system allows users to easily generate safe and efficient routes with specific geometries and view all the necessary details.

[1353] (Application example 1)

[1354] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1355] The problem that this invention aims to solve is to provide an optimal route for delivery staff to travel to multiple delivery destinations efficiently and safely in a food delivery service.The invention also aims to build a system that can provide added value by generating routes that include tourist attractions, allowing delivery staff to discover the charms of the area while performing delivery work.

[1356] 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.

[1357] In this invention, the server includes means for a user to input the area, mode of transportation, distance, and theme to be drawn, means for transmitting the input data to the server, means for analyzing map data based on the data received by the server, means for generating a specific shape based on the theme, means for generating a route using an AI model taking safety and traffic rules into consideration, means for verifying and adjusting the generated route, means for incorporating tourist attractions into the route, means for transmitting the final course data to the terminal, means for the terminal to display the course data, means for the user to use as an exercise plan, means for generating a round route for delivery destinations, means for generating a route that passes tourist attractions, and means for verifying traffic rules and safety. This enables delivery staff to deliver efficiently and safely, and also enables the provision of high-value-added routes that visit tourist attractions.

[1358] "User" refers to a customer or delivery staff member who uses this system.

[1359] "Area" refers to the specific geographic area in which delivery is made.

[1360] "Means of transportation" refers to the means of transportation used when making deliveries, including bicycles, walking, cars, etc.

[1361] "Distance" refers to the distance of travel specified by the user.

[1362] The "theme to be drawn" refers to instructions entered by the user regarding the shape and pattern of the route to be generated.

[1363] "Server" refers to a computer system that receives, analyzes, routes, and transmits data.

[1364] "Map data" refers to data that includes information on roads, intersections, buildings, etc. in a specific area.

[1365] "Specific Shape" refers to the geometric shape of the route that is generated based on a theme entered by the user.

[1366] An "AI model" is an algorithm that uses artificial intelligence technology and is used to take safety and traffic rules into consideration when generating routes.

[1367] "Traffic rules" refers to legal regulations that must be followed while traveling, such as the Road Traffic Act.

[1368] "Points of interest" refers to specific notable places or landmarks that are included in route generation.

[1369] "Course data" is digital information about the generated route that is ultimately sent to the terminal.

[1370] "Device" means a device used by a User to view and display course data, including, for example, a smartphone or tablet.

[1371] "Exercise planning" refers to a plan of movement or exercise that a user will undertake based on the generated route.

[1372] "Delivery destination" refers to the location where the food delivery service should deliver the item.

[1373] A "routes" refers to a specific route generated to efficiently visit multiple delivery destinations.

[1374] "Safety" refers to factors taken into consideration when generating a route to prevent accidents and dangers.

[1375] "Efficient" means that the route is optimized to achieve the goal with the least amount of time and effort.

[1376] "Added value" refers to additional benefits or value to the user that are provided in addition to basic functionality.

[1377] This invention is a system that generates optimal delivery routes based on information entered by the user and provides them to delivery staff. This system improves delivery efficiency, ensures safety, and provides added value such as routes that visit tourist attractions.

[1378] System Configuration

[1379] 1. User-entered data

[1380] Using a smartphone application, users input data such as the area, mode of transportation, distance, theme they want to depict, safety priority or tourist attraction priority.

[1381] 2. Data Transmission and Reception

[1382] The data entered by the user is sent to the server via the smartphone application, and the server receives the data and begins analyzing it.

[1383] 3. Map data acquisition and analysis

[1384] The server retrieves map data for the specified area using Google Maps API or similar, analyzes this data, extracts information on major roads, intersections, and buildings, and processes it as data necessary for route generation.

[1385] 4. Shape and Route Generation

[1386] The server generates a specific shape based on a theme specified by the user, and uses an AI model to generate a route that takes safety and traffic rules into account. The AI ​​model uses machine learning frameworks such as TensorFlow and PyTorch.

[1387] 5. Route verification and adjustment

[1388] The server verifies that the generated route complies with traffic rules and is safe. If necessary, it adjusts the route to determine the optimal delivery route. If the route includes tourist attractions, it also incorporates their locations into the route.

[1389] 6. Sending and displaying course data

[1390] The final course data is sent from the server to the user's smartphone. The smartphone application receives this course data and displays it to the user. The user can check information such as the course map, travel methods, total distance, required time, and tourist attractions along the way.

[1391] Specific examples

[1392] For example, let's consider a scenario where a delivery staff member wants to cycle around multiple delivery destinations in Shibuya Ward, Tokyo, and simultaneously generate a route that draws a heart shape. In this case, the user inputs the following information into the smartphone application: Shibuya Ward, bicycle, 5 kilometers, heart, and safety priority.

[1393] Example prompt sentence:

[1394] "Generate routes to three delivery destinations by bicycle within the Shibuya Ward area. Safety is the top priority and I would like the route to follow traffic rules."

[1395] In this way, users input the necessary information and the system automatically generates the optimal delivery route, which is safe and efficient, allowing delivery staff to visit tourist attractions and provide high-value-added services.

[1396] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1397] Step 1:

[1398] The user inputs the area, mode of transportation, distance, and theme they want to draw.

[1399] The user starts the smartphone application and inputs information such as the area, mode of transportation, distance, theme to be drawn, priority of safety or priority of tourist attractions into the specified interface. This input data is collected and sent to the server in the next step.

[1400] Step 2:

[1401] Sending input information to the server

[1402] When the user presses the "Generate Route" button, the device sends all the data entered, including information about the area, mode of transportation, distance, theme, and priority, to the server. The data is sent in JSON format to the server.

[1403] Step 3:

[1404] Map data acquisition and analysis

[1405] The server uses the received data to obtain map data for the specified area using the Google Maps API. The obtained map data is then analyzed to extract information on major roads, intersections, buildings, etc. The extracted information is then used to generate the route.

[1406] Step 4:

[1407] Theme-based specific shape generation

[1408] The server generates a specific shape based on a theme entered by the user (e.g., a heart shape), using a theme-specific path generation algorithm. The generated shape becomes the basis for the final route design.

[1409] Step 5:

[1410] Route generation using AI models

[1411] The server generates routes using an AI model, taking safety and traffic rules into consideration. This AI model uses machine learning frameworks such as TensorFlow and PyTorch. The optimal route is calculated based on input data (map information, specific shapes, and traffic rules).

[1412] Step 6:

[1413] Validate and adjust the generated route

[1414] The server verifies that the generated route complies with traffic rules and is safe. It runs a simulation to check for safety issues and adjusts the route as necessary. Once verified, the route data is prepared for transmission in the next step.

[1415] Step 7:

[1416] Include tourist attractions in your route

[1417] The server references tourist attraction data and incorporates tourist attractions into the generated route. If the user has set tourist attractions as a priority, the server adjusts the route to pass through the tourist attractions. The final route after adjustment is determined.

[1418] Step 8:

[1419] Submitting the final course data

[1420] The final course data is sent from the server to the user's smartphone, including a map of the route, travel methods, total distance, travel time, and information on tourist attractions.

[1421] Step 9:

[1422] Viewing course data

[1423] The device displays the received route data through a user interface, allowing the user to efficiently deliver the goods while checking the route map and understanding the travel method, total distance, required time, and tourist attractions.

[1424] 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.

[1425] System Overview

[1426] This invention is a system that automatically generates GPS art courses based on user input data. An emotion engine that recognizes the user's emotions is incorporated as an additional element, allowing the system to generate courses according to the user's emotional state. This system allows the user to input their area, mode of transportation, distance, and desired theme, and generates a safe and efficient route based on that information. It can also generate courses that take into account traffic rules and include tourist attractions.

[1427] composition

[1428] 1. User-entered data

[1429] region

[1430] Transportation

[1431] distance

[1432] Themes I want to draw

[1433] Safety priority or tourist attraction priority

[1434] 2. Server Functions

[1435] Receiving input data

[1436] Map data acquisition and analysis

[1437] Shape generation based on user themes

[1438] Route generation using AI models

[1439] Emotion data analysis and route adjustment using an emotion engine

[1440] Verifying route safety and traffic rules

[1441] Sending course data to your device

[1442] 3. Device Features

[1443] Providing an input interface

[1444] Receiving and displaying course data

[1445] Collecting and transmitting emotional states

[1446] Program processing

[1447] 1. Receiving user input

[1448] Device: The user opens the application on the device and inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions. In addition, an emotion engine that collects the user's emotional state operates and obtains emotion data from the device.

[1449] 2. Sending input information to the server

[1450] Terminal: When the user presses the "Generate" button, the input data and emotion data are sent to the server. The sent data includes the area, transportation method, distance, theme, priority of safety or tourist attractions, and emotion data.

[1451] 3. Server-side data processing

[1452] server:

[1453] Input data and emotion data are received.

[1454] Obtain map data for the specified area and retrieve detailed information from the database, including road information, intersections, traffic lights, and other transportation infrastructure.

[1455] It runs an algorithm to generate a specific shape based on the user's theme and creates a pattern to form that shape.

[1456] The system uses an AI model to generate routes that fit the specified distance based on the acquired map data and thematic shape information. The route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[1457] The emotion engine analyzes the emotional data and adjusts the route generation accordingly. For example, if the emotion is relaxation, it will select a route that passes through a quiet park, and if the emotion is excitement, it will select a route that includes active tourist attractions.

[1458] The generated route is simulated to check whether it is safe and complies with traffic rules, and the route is fine-tuned if necessary.

[1459] The final course data that has been verified is prepared and sent to the terminal.

[1460] 4. Receiving and Displaying Course Information

[1461] Device: Displays the route data received from the server to the user, including the route map, travel method, total distance, estimated travel time, points of interest along the way, and special route adjustment information based on emotional state.

[1462] Specific examples

[1463] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[1464] 1. Receiving user input

[1465] Device: The user enters information about Shibuya Ward, running, 5 kilometers, heart rate, and safety priority into the application. The emotion engine then recognizes the user's emotional state and determines that the user needs to relax.

[1466] 2. Sending input information to the server

[1467] Device: Press the "Generate" button to send the information to the server, along with the emotion data.

[1468] 3. Data Processing

[1469] server:

[1470] Obtain map data for Shibuya Ward and analyze road information.

[1471] Generate a heart-shaped pattern and check if it is suitable for 5 kilometers.

[1472] Using an AI model, the system generates a safe route that follows traffic rules. Because the user's emotional state indicates a desire for relaxation, the system selects routes that pass through parks and natural areas as much as possible.

[1473] The route will also include tourist attractions such as the Hachiko statue and Yoyogi Park.

[1474] Simulate the generated route to ensure it is safe and adjust it if necessary.

[1475] The final course data is sent to the device.

[1476] 4. View course information

[1477] Terminal: Displays to the user a course map, mode of travel, distance, time required, tourist attractions, and special route adjustment information based on emotional state.

[1478] In this way, users can generate safe and efficient GPS art courses tailored to their emotional state.

[1479] The processing flow will be explained below.

[1480] Step 1:

[1481] User: Opens the application on the device. The user inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions. Furthermore, the emotion engine collects the user's emotional state and analyzes the current emotional state.

[1482] Step 2:

[1483] Terminal: When the user presses the "Generate" button, the input data and emotion data are sent to the server. The sent data includes the area, transportation method, distance, theme, priority of safety or tourist attractions, and emotion data.

[1484] Step 3:

[1485] Server: Analyzes the data received from the device. Specifically, it retrieves map data for the area specified by the user and obtains detailed information from a database, including road information, intersections, traffic lights, and other traffic infrastructure information.

[1486] Step 4:

[1487] Server: Performs thematic analysis. Based on a theme entered by the user (e.g., "heart"), it runs an algorithm to generate a specific shape and creates the patterns that form that shape.

[1488] Step 5:

[1489] Server: Generates a route using an AI model. This generates a route that matches the specified distance based on the acquired map data and thematic shape information. Route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[1490] Step 6:

[1491] Server: Analyzes emotional data. The emotional state of the user recognized by the emotion engine (e.g., "I want to relax" or "I want an active experience") is analyzed and reflected in route generation.

[1492] Step 7:

[1493] Server: Adjusts the route based on emotional data. For example, if the emotional state is one of relaxation, it selects a route that passes through parks and quiet roads, and if the emotional state is active, it selects a route that includes tourist attractions and bustling places.

[1494] Step 8:

[1495] Server: Adjust the route to include tourist attractions. If the user sets a high priority for a tourist attraction, the server will incorporate the specified tourist attraction (e.g., Hachiko Statue, Yoyogi Park, etc.) into the route and recalculate the route to reach that attraction.

[1496] Step 9:

[1497] Server: Validates the generated route, simulating whether it complies with traffic rules and ensures safety, and fine-tunes the route if necessary.

[1498] Step 10:

[1499] Server: Prepares the final course data after verification and sends it to the device.

[1500] Step 11:

[1501] Device: Displays the route data received from the server to the user, including the route map, travel method, total distance, estimated travel time, points of interest along the way, and special route adjustment information based on emotional state.

[1502] Step 12:

[1503] User: Checks the provided course information, and if satisfied, prepares to actually exercise the course.

[1504] Example 2

[1505] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1506] Previous GPS Art route generation systems did not take the user's emotional state into account, making it difficult to provide routes that suited the user's mental and physical needs. Furthermore, they rarely guaranteed safety or compliance with traffic rules, making it difficult to generate appropriate routes for specific modes of transportation. Another problem was that they were unable to automatically generate routes that included tourist attractions, and lacked features that would increase the user's enjoyment.

[1507] 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.

[1508] In this invention, the server includes means for the user to input the area, mode of transportation, distance, and theme to be drawn, means for recognizing the user's emotional state and collecting relevant data, means for transmitting the input data and emotional data to the server, means for the server to analyze map data based on the data received, means for generating a specific shape based on the theme, means for generating a route using an AI model taking into account safety and traffic rules, means for adjusting the generated route based on the emotional data, means for verifying and adjusting the generated route, means for transmitting the final course data to the terminal, and means for the terminal to display the course data. This enables the generation of an optimal route that takes into account the user's emotional state, safety, and traffic rules, providing a safer and more enjoyable GPS art experience.

[1509] "Region" is data indicating the location or area where the user performs GPS art.

[1510] "Means of transportation" is data that indicates the method or tool (e.g., running, cycling, etc.) used by the user to create GPS art.

[1511] "Distance" is data indicating the total distance traveled by the user when drawing GPS art.

[1512] The "theme to be drawn" is data indicating a specific shape or figure (e.g., heart, star, etc.) that the user wants to draw in GPS Art.

[1513] "Emotional state" is data that indicates the mental or emotional state of a user.

[1514] An "emotion engine" refers to a function or system for recognizing a user's emotions and analyzing their state.

[1515] "Server" refers to a central computing system for receiving and processing data sent by users.

[1516] A "data packet" is a unit of information that includes user input data and emotion data and is sent to the server.

[1517] "Map Data" refers to a data set containing details of roads, intersections, traffic lights, etc. for a specified area.

[1518] A "theme shape" is data that indicates a shape that embodies a figure or pattern that the user wants to draw.

[1519] "AI Model" refers to the artificial intelligence algorithm used to generate the route.

[1520] "Route adjustment" is the process of making corrections and optimizations to the generated route based on the user's emotional data and other considerations.

[1521] "Course data" refers to data that indicates the final route information of the GPS Art that has been analyzed and generated.

[1522] "Terminal" refers to the device (e.g., smartphone, tablet, etc.) used by the user to enter and display the final course data.

[1523] "Tourist attractions" are data that indicate particular geographical locations or cultural facilities that may be of interest to users.

[1524] System Overview

[1525] This invention is a system that automatically generates GPS art courses based on user input and emotional data. The system generates a theme shape based on user-entered information and uses an AI model to generate a route that matches it. It also incorporates an emotion engine that recognizes the user's emotional state and adjusts the route accordingly. Users can input their area, mode of transportation, distance, theme they want to draw, and safety or tourist attraction priorities.

[1526] Hardware and software used

[1527] 1. User device (e.g. smartphone, tablet)

[1528] A device that allows users to input data and interact with the system, incorporating an input interface and emotion engine.

[1529] 2. Server

[1530] It is a central computing system for receiving and processing input data and emotion data, analyzing map data, generating theme shapes, generating routes using AI models, making adjustments based on emotion data, and transmitting the final course data.

[1531] Program processing explanation

[1532] Receiving user input

[1533] The user opens the application on their device and enters the following information: area (e.g., "Shibuya-ku, Tokyo"), mode of transportation (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and safety or tourist attraction priority. Furthermore, an emotion engine runs, collecting the user's emotional state using the camera and microphone.

[1534] Sending input information to the server

[1535] When the user presses the "Generate" button, the device sends this data to the server, including the area, mode of transportation, distance, theme, safety or tourist attraction priority, and emotion data.

[1536] Server-side data processing

[1537] The server does the following:

[1538] Receives input data and emotion data.

[1539] Obtain map data for the specified area and extract detailed information such as road information, intersections, and traffic lights from the database.

[1540] It runs an algorithm that generates a specific shape based on the user's theme, then creates a pattern to form that shape.

[1541] Routes are generated using AI models, taking safety and traffic rules into consideration during the process.

[1542] The generated route is adjusted based on the analysis results of the emotion engine. For example, if the user wants to "relax," the system will select a route that passes through parks and quiet places.

[1543] Simulate the generated route to ensure it is safe and make any necessary adjustments.

[1544] The final course data is sent to the device.

[1545] Receive and view course information

[1546] The device displays the course data received from the server to the user, including:

[1547] Course Map

[1548] How to move

[1549] Total distance

[1550] Estimated time required

[1551] Tourist attractions to visit

[1552] Special route adjustment information based on emotional state

[1553] Specific examples

[1554] If a user wants to generate a 5km course in Shibuya, Tokyo, where they will draw a heart shape while running:

[1555] 1. The user enters the following information into the application: Shibuya Ward, running, 5km, heart, safety first. The emotion engine recognizes that the user needs to relax.

[1556] 2. Press the "Generate" button to send the information to the server, along with the emotion data.

[1557] 3. The server retrieves map data for Shibuya Ward and analyzes road information. A heart-shaped pattern is generated, and an AI model is used to generate a safe route that takes traffic rules into account. Since the driver is looking for relaxation, parks and quiet routes are selected whenever possible. Tourist attractions are also included.

[1558] 4. Include tourist attractions such as the Hachiko statue and Yoyogi Park in your route.

[1559] 5. The generated route is simulated to check its safety, and fine-tuned if necessary. The final course data is sent to the device.

[1560] 6. The device displays the route map, travel method, distance, travel time, tourist attraction information, and special route adjustment information based on emotional state to the user.

[1561] Example prompt sentence:

[1562] "Generate a 5-kilometer course to trace a heart shape while running in Shibuya, Tokyo, prioritizing safety. I'm in the mood for relaxation right now."

[1563] In this way, users can generate safe and efficient GPS art courses tailored to their emotional state.

[1564] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1565] Step 1:

[1566] Receiving user input

[1567] The user opens the application on their device and inputs their "area" (e.g., "Shibuya-ku, Tokyo"), "mode of transportation" (e.g., "running"), "distance" (e.g., "5 kilometers"), "theme to draw" (e.g., "heart"), and "safety priority" or "tourist attraction priority." The emotion engine then operates, collecting the user's emotional state via the camera and microphone and converting it into digital data.

[1568] Input: Region, mode of transportation, distance, theme, priority, emotional state

[1569] Output: Collected user input data and emotion data

[1570] Step 2:

[1571] Preparing to send input information

[1572] The terminal assembles the collected user input data and emotion data into a single data packet, which includes the area, mode of transportation, distance, theme, priority of safety or tourist attractions, and emotion data.

[1573] Input: Collected user input data and emotion data

[1574] Output: Data packets

[1575] Step 3:

[1576] Sending data to the server

[1577] When the user presses the "Generate" button, the terminal sends a data packet to the server.

[1578] Input: Data packet

[1579] Output: Send data to the server

[1580] Step 4:

[1581] Receiving data

[1582] The server receives data packets sent from the terminal, which include region, mode of transportation, distance, theme, priority, and emotion data.

[1583] Input: Data packet

[1584] Output: Received data

[1585] Step 5:

[1586] Map data acquisition and analysis

[1587] The server retrieves map data for the area specified by the user and extracts detailed information from the database, such as road information, intersections, and traffic light locations. Through this analysis, it collects topographical and infrastructure information that will be the basis for route generation.

[1588] Input: Region data

[1589] Output: Map data (road information, intersections, traffic light locations, etc.)

[1590] Step 6:

[1591] Theme Shape Generation

[1592] The server runs an algorithm to generate a specific shape based on a user-specified theme (e.g., "heart"), which generates specific paths and segment patterns to form the theme shape.

[1593] Input: Theme data

[1594] Output: Theme Shape Pattern

[1595] Step 7:

[1596] Route Generation

[1597] The server uses an AI model to generate a route based on the acquired map data and the generated thematic shape patterns, taking into account safety and traffic rules (e.g., one-way streets, bicycle lanes, etc.) depending on the mode of travel.

[1598] Input: Map data and thematic shape patterns

[1599] Output: Generated routes

[1600] Step 8:

[1601] Route adjustment based on emotion data

[1602] The server then adjusts the generated route using the emotion data analyzed by the emotion engine. For example, if the user is looking to relax, the server may select a route that includes parks and plenty of nature.

[1603] Input: Generated route and emotion data

[1604] Output: Adjusted route

[1605] Step 9:

[1606] Safety and traffic rules verification

[1607] The server simulates the generated route to ensure safety and compliance with traffic rules, and fine-tunes the route if necessary.

[1608] Input: Adjusted Route

[1609] Output: Final route

[1610] Step 10:

[1611] Prepare and submit final course data

[1612] The server prepares the final course data and sends it to the device, which includes the course map, travel mode, distance, travel time, tourist attractions, and special route adjustment information based on emotional state.

[1613] Input: Final Route

[1614] Output: Send course data to the device

[1615] Step 11:

[1616] View course information

[1617] The device displays the course data received from the server to the user, including the course map, travel method, distance, travel time, tourist attractions along the way, and special route adjustment information based on emotional state.

[1618] Input: Course data

[1619] Output: Course information displayed to user

[1620] (Application example 2)

[1621] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1622] Conventional automated patrol systems within factories have the problem of not being able to fully consider safety and efficiency when generating routes. Furthermore, because the emotional state of the operator is not reflected in the patrol route, it is difficult to manage stress and ensure appropriate rest areas. The present invention aims to solve these problems and provide a system that achieves safe and efficient patrol within a factory.

[1623] 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.

[1624] In this invention, the server includes means for the user to input the area, means of transportation, distance, and theme to be drawn, means for transmitting the input data to the server, and means for collecting emotion data and adjusting the route based on the emotion data, thereby enabling route adjustment based on the emotion data and generation of work areas and process points for equipment maintenance.

[1625] A "region" is a geographical location specified by the user, and is the basic information for generating a route.

[1626] "Transportation" refers to the transportation method designated by the user, and includes running, cycling, car, etc.

[1627] "Distance" is the distance the user desires to travel, and is a parameter that specifies the length of the route.

[1628] The "theme" is the specific shape or pattern desired by the user, and serves as the basis for GPS art.

[1629] The "means for transmitting data to a server" is a function for sending information entered by a user to a server via a network.

[1630] The "means for analyzing map data based on data received by the server" is a function for extracting and analyzing detailed information on the map based on information received by the server from the user.

[1631] The "means for generating a specific shape based on a theme" is a function for generating a specific shape or pattern on a map based on a theme input by the user.

[1632] "Means for generating routes using AI models, taking into account safety and traffic rules" refers to a function that automatically generates optimal routes using AI models, taking into account the safety and traffic rules of each means of transportation.

[1633] "Means for verifying and adjusting the generated route" refers to a function that simulates whether the generated route complies with safety and traffic rules, and makes fine adjustments as necessary.

[1634] The "means for transmitting final course data to the terminal" is a function for transmitting the generated final route information to the terminal.

[1635] The "means for the terminal to display course data" refers to a function for visually displaying the course data received by the terminal to the user.

[1636] The "means for collecting emotional data and adjusting the route based on the emotional data" is a function that analyzes the user's emotional state using an emotional engine and optimizes the route based on that data.

[1637] The "means for generating patrol routes within a factory and supporting patrol by a robot" is a function that generates routes that allow a robot to patrol a factory efficiently and safely, and supports that patrol.

[1638] The "means for generating a route including tourist attractions" is a function for generating a route including tourist attractions within a specified area.

[1639] "Means for generating process points for work areas and equipment maintenance" is a function that includes specific work areas within a factory and points of equipment that require maintenance in the route.

[1640] "Means for providing the user with final course information and planning exercise based on that information" is a function that provides information for the user to plan exercise based on the generated route information.

[1641] The "means for planning patrol routes to improve work efficiency and safety within a factory" is a function for planning patrol routes within a factory and improving work efficiency and safety.

[1642] System Overview

[1643] The present invention is an automatic route generation system for a factory that generates an efficient and safe route based on user input data. The system is composed of the following elements:

[1644] System Configuration

[1645] 1. User-entered data

[1646] Area (e.g. Factory Zone A)

[1647] Means of transportation (e.g., patrol robot)

[1648] Distance (e.g. 5 kilometers)

[1649] The theme you want to draw (e.g., shortest route)

[1650] Prioritizing safety or patrol efficiency

[1651] Emotional data (e.g., stress level, preferred_break_spot)

[1652] 2. Server Functions

[1653] Receiving input data

[1654] Map data acquisition and analysis

[1655] Shape generation based on user themes

[1656] Route adjustment based on emotion data analysis

[1657] Route generation using AI models

[1658] Verifying route safety and traffic rules

[1659] Sending the final course data to the device

[1660] 3. Device Features

[1661] Providing an input interface

[1662] Receiving and displaying course data

[1663] Collecting and transmitting emotional states

[1664] Program processing explanation

[1665] 1. Receiving user input data

[1666] The terminal receives information from the user, such as area, mode of transportation, distance, theme, priority of safety or patrol efficiency, and emotion data. This input data is input by the user by opening an application on the terminal.

[1667] 2. Sending input information to the server

[1668] When the user presses the "generate" button, the terminal transmits the input data and emotion data to the server.

[1669] 3. Server-side data processing

[1670] The server analyzes the received data and retrieves map data for the specified area. It then uses an AI model to generate a route that takes safety and efficiency into account. It adjusts the route based on emotion data, prioritizing rest areas if stress levels are high, for example. Finally, the generated route is verified for safety and compliance with traffic rules, and fine-tuning is performed as needed.

[1671] Hardware and software used

[1672] Hardware: Servers (dedicated servers or cloud servers), user devices (smartphones, tablets, laptops, etc.)

[1673] Software: Application (to provide user interface), AI model (to generate routes), emotion engine (to analyze emotion data)

[1674] Specific examples

[1675] Let's take the example of a user wanting to generate a safe and efficient 5-kilometer patrol route for a patrol robot in factory zone A, which is experiencing a high stress level. The user opens the application, selects factory zone A, inputs the information for the patrol robot, 5 kilometers, shortest route, and safety priority, and sends emotional data indicating a high stress level.

[1676] The server acquires map data for Factory Zone A and analyzes road information. At the same time, it generates a route that prioritizes rest areas based on emotion data, and generates a final route that takes safety and traffic rules into consideration. This route data is sent to the terminal and displayed to the user.

[1677] Prompt Sentence Examples

[1678] Generate a safe patrol route that is optimal for workers with a stress level of 3 based on the user-specified factory zone A. In particular, create a route that prioritizes rest areas. The means of transportation is a "patrol robot." The generated route should include the locations of each waypoint and the actions to be taken at each point.

[1679] In this way, users can generate safe and efficient routes around the factory that are tailored to their emotional state.

[1680] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1681] Step 1:

[1682] The user opens the application on their device and inputs the area (e.g., factory zone A), the means of transportation (e.g., patrol robot), the distance (e.g., 5 kilometers), the theme they want to draw (e.g., the shortest route), the priority of safety (or the priority of patrol efficiency), and emotional data (e.g., stress level). The input data is formatted in JSON format.

[1683] Input: Region, mode of transportation, distance, theme, safety priority, sentiment data

[1684] Output: Input data in JSON format

[1685] Step 2:

[1686] When the user presses the "Generate" button, the terminal sends the formatted JSON input data to the server using an HTTP POST request.

[1687] Input: Input data in JSON format

[1688] Output: POST request to the server

[1689] Step 3:

[1690] The server analyzes the received JSON format data and obtains map data for the specified area (Factory Zone A). It also obtains data on traffic infrastructure such as road information, intersections, and traffic lights from a database.

[1691] Input: JSON format input data received via POST request

[1692] Output: Map data, road information, traffic infrastructure data

[1693] Step 4:

[1694] The server runs an algorithm that generates a particular shape based on the theme, and creates patterns to form that shape, for example, if the theme is "shortest path", it will generate patterns to form the shortest path.

[1695] Input: User's theme (e.g. shortest path)

[1696] Output: Specific shape pattern

[1697] Step 5:

[1698] The server generates a route using an AI model. It uses acquired map data and a shape pattern based on the theme to generate a route that fits the specified distance (5 kilometers). It generates the route while taking into account the safety and traffic rules of each mode of transportation.

[1699] Input: Map data, shape pattern, distance, means of transportation

[1700] Output: Generated routes

[1701] Step 6:

[1702] The server analyzes the emotion data and adjusts the route accordingly. For example, if the stress level is high, the server may select a route that prioritizes rest areas. The server processes the emotion data using an emotion engine and fine-tunes the route.

[1703] Input: Generated route, emotion data

[1704] Output: Adjusted route

[1705] Step 7:

[1706] The server simulates and verifies the generated route to ensure safety and compliance with traffic rules, and fine-tunes the route if there are any issues with safety or traffic rules.

[1707] Input: Adjusted Route

[1708] Output: Final route

[1709] Step 8:

[1710] The server then sends the final course data to the device, which includes the location of each waypoint, the actions to be taken, the distance, and the estimated time required.

[1711] Input: Final route

[1712] Output: Course data to the device

[1713] Step 9:

[1714] The terminal displays the course data received from the server to the user, who can then check information such as the course map, travel method, total distance, estimated time required, and rest areas along the way.

[1715] Input: Course data received from the server

[1716] Output: Course information displayed on the user interface

[1717] 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.

[1718] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1719] 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.

[1720] [Fourth embodiment]

[1721] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1722] 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.

[1723] 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).

[1724] 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.

[1725] 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.

[1726] 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).

[1727] 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.

[1728] 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.

[1729] 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.

[1730] 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.

[1731] 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.

[1732] 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.

[1733] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1734] System Overview

[1735] This system automatically generates a GPS art course based on user input data. Users input their area, mode of transportation, distance, and the theme they want to draw, and a safe and efficient route is generated based on that information. It can also generate a course that takes into account traffic rules and includes tourist attractions.

[1736] composition

[1737] 1. User-entered data

[1738] region

[1739] Transportation

[1740] distance

[1741] Themes I want to draw

[1742] Safety priority or tourist attraction priority

[1743] 2. Server Functions

[1744] Receiving input data

[1745] Map data acquisition and analysis

[1746] Shape generation based on user themes

[1747] Route generation using AI models

[1748] Verifying route safety and traffic rules

[1749] Sending course data to your device

[1750] 3. Device Features

[1751] Providing an input interface

[1752] Receiving and displaying course data

[1753] Program processing

[1754] 1. Receiving user input

[1755] Device: The user opens the application on the device and inputs the area, mode of transportation, distance, theme to be drawn, safety priority or tourist attraction priority.

[1756] 2. Sending input information to the server

[1757] Terminal: When the user presses the "Generate" button, the input data is sent to the server.

[1758] 3. Server-side data processing

[1759] server:

[1760] Receives input data and retrieves map data for the specified area.

[1761] The acquired map data is analyzed and information such as major roads and intersections is extracted.

[1762] Generate specific shapes based on user themes.

[1763] An AI model is used to generate routes that take safety and traffic rules into consideration.

[1764] If you include a tourist attraction, incorporate its location into the route.

[1765] Verify that the generated route complies with traffic rules and is safe.

[1766] The verified course data is sent to the device.

[1767] 4. Receiving and Displaying Course Information

[1768] Terminal: Displays the course data received from the server to the user. The user can check information such as the course map, travel method, total distance, required time, and tourist attractions along the way.

[1769] Specific examples

[1770] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[1771] 1. Receiving user input

[1772] Device: The user enters the following information into the application: Shibuya Ward, Running, 5km, Heart, Safety First.

[1773] 2. Sending input information to the server

[1774] Terminal: Press the "Generate" button to send the information to the server.

[1775] 3. Data Processing

[1776] server:

[1777] Obtain map data for Shibuya Ward and analyze road information.

[1778] Generate a heart-shaped pattern and check if it is suitable for 5 kilometers.

[1779] Using AI models, routes that are safe and comply with traffic rules are generated.

[1780] The route will include tourist attractions such as the Hachiko statue and Yoyogi Park.

[1781] Simulate the generated route to ensure it is safe and adjust it if necessary.

[1782] The final course data is sent to the device.

[1783] 4. View course information

[1784] Terminal: Displays course information to the user, including course maps, transportation methods, distance, time required, and points of interest.

[1785] In this way, users can easily create safe and efficient GPS art courses.

[1786] The processing flow will be explained below.

[1787] Step 1:

[1788] User: Opens the application on the device. The user inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions.

[1789] Step 2:

[1790] Terminal: When the user presses the "Generate" button, the entered data is sent to the server, including the area, mode of transportation, distance, theme, and safety or tourist attraction priority.

[1791] Step 3:

[1792] Server: Analyzes the data received from the device. Specifically, it retrieves map data for the area specified by the user and obtains detailed information from a database, including road information, intersections, traffic lights, and other traffic infrastructure information.

[1793] Step 4:

[1794] Server: Performs thematic analysis. Based on a theme entered by the user (e.g., "heart"), it runs an algorithm to generate a specific shape and creates the patterns that form that shape.

[1795] Step 5:

[1796] Server: Generates a route using an AI model. This generates a route that matches the specified distance based on the acquired map data and thematic shape information. Route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[1797] Step 6:

[1798] Server: Adjust the route to include tourist attractions. If the user sets a high priority for a tourist attraction, the server will incorporate the tourist attraction (e.g., Hachiko Statue, Yoyogi Park, etc.) into the route and recalculate the route to reach that attraction.

[1799] Step 7:

[1800] Server: Validates the generated route, simulating whether it complies with traffic rules and ensures safety, and fine-tunes the route if necessary.

[1801] Step 8:

[1802] Server: Prepares the final course data after verification and sends it to the device.

[1803] Step 9:

[1804] Terminal: Displays the course data received from the server to the user. The displayed content includes the course map, travel method, total distance, estimated time required, and tourist attractions along the way.

[1805] Step 10:

[1806] User: Checks the provided course information, and if satisfied, prepares to actually exercise the course.

[1807] Example 1

[1808] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1809] Conventional route planning systems lack the ability to generate specific shapes based on user themes, and it is difficult to generate routes that fully consider safety and traffic rules. Furthermore, generating routes that include tourist attractions and verifying and adjusting the generated routes are time-consuming, making it difficult for users to easily obtain efficient and safe routes.

[1810] 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.

[1811] In this invention, the server includes means for acquiring and analyzing map data based on input data, means for generating a specific shape based on a theme, and means for inputting a prompt sentence to the AI ​​model to generate a route that takes safety and traffic rules into consideration, thereby enabling a user to easily generate a route with a specific shape based on a theme and obtain an efficient course that complies with safety and traffic rules.

[1812] A "region" is a particular geographic area that a user specifies when generating a route.

[1813] "Transportation" refers to the method or mode of transportation used by a user to travel a route, including, for example, walking, cycling, or driving.

[1814] "Distance" is the length of the route specified by the user, typically expressed in kilometers.

[1815] The "theme to be drawn" indicates the shape and purpose of the route that the user wants to generate, and includes a specific shape or pattern.

[1816] "Safety priority" is an index that indicates the priority of safety in route generation.

[1817] The "priority of tourist attractions" is an index that indicates the priority with which tourist attractions are emphasized in route generation.

[1818] "Map data" is a data set containing geographic information for a particular area, including information on roads, intersections, etc.

[1819] The "particular shape" refers to a particular pattern or shape that is generated based on a user's theme.

[1820] An "AI model" is a computational model that uses artificial intelligence to analyze data and perform specific tasks.

[1821] A "prompt sentence" is an input sentence used to prompt an AI model to perform a specific task.

[1822] "Generating a route" means calculating and determining a route that takes safety and traffic rules into consideration based on data input by the user.

[1823] "Validation" is the process of checking whether the generated route is correct and complies with certain conditions.

[1824] "Adjustment" means making necessary corrections based on the results of verification.

[1825] "Course data" is a detailed data set that includes the generated route, including route coordinates, distance traveled, time required, etc.

[1826] A "terminal" is a hardware device through which a user enters input data and receives final course information.

[1827] MODE FOR CARRYING OUT THE INVENTION

[1828] System Overview

[1829] This invention is a system that automatically generates routes based on user input data. Users input their area, mode of transportation, distance, and the theme they want to depict, and a safe and efficient route is generated based on that information. Furthermore, traffic rules are taken into account and tourist attractions can be included in the route. The operation of the system will be explained in detail using a specific example.

[1830] Hardware and software used

[1831] Device: User device such as a smartphone or tablet

[1832] Server: High-performance computing server

[1833] Map Data API: Google Maps API

[1834] Geographic information processing libraries: Geopy, Fiona

[1835] Shape manipulation library: Shapely

[1836] AI model: OpenAI GPT-3 model

[1837] Map display libraries: Mapbox, Leaflet

[1838] Program processing

[1839] 1. Receiving user input

[1840] Device: The user opens the application on their device and enters the area (e.g., Shibuya Ward), mode of transportation (e.g., running), distance (e.g., 5 kilometers), theme to draw (e.g., heart), and safety priority or tourist attraction priority (e.g., safety).

[1841] 2. Sending input information to the server

[1842] Terminal: When the user presses the "Generate" button, the input data is converted to JSON format and a POST request is sent to the server's API endpoint.

[1843] 3. Server-side data processing

[1844] Server: Receives input data and retrieves map data for the specified area (Shibuya Ward) using the Google Maps API.

[1845] Server: Analyzes the acquired map data and extracts information such as major roads and intersections using geographic information processing libraries such as Geopy and Fiona.

[1846] Specifically, the map data is parsed and the locations of road segments and intersections are stored in list format.

[1847] Server: Generates specific shapes (e.g., hearts) based on the user's theme. Shape manipulation libraries such as Shapely are used for shape generation.

[1848] Specifically, a heart-shaped Bezier curve is generated and a route is created along it.

[1849] Server: Enter a prompt into a generative AI model (e.g., OpenAI's GPT-3) to generate an optimal route. An example prompt is as follows:

[1850] Prompt statement:

[1851] The user is looking for a 5-kilometer running course in Shibuya, Tokyo. The course should be heart-shaped, and safety is a priority. Generate a route that passes by the Hachiko statue and Yoyogi Park as much as possible.

[1852] 4. The server verifies traffic rules and safety

[1853] Server: Simulates whether the generated route complies with traffic rules and is safe. The simulation uses traffic rule-related datasets and a rule engine.

[1854] As a specific example, check whether there are traffic lights at intersections or whether there are pedestrian-only roads.

[1855] Server: If necessary, fine-tune the output of the AI ​​model to align with safety and traffic rules.

[1856] 5. The generated route data is sent to the device.

[1857] Server: Once the final route is validated, it converts the route data into JSON format and sends it to the device, including route coordinates, distance traveled, travel time, and location information of tourist attractions.

[1858] 6. The device will display the route information.

[1859] Terminal: Analyzes the route data received from the server and displays it to the user. A map display library such as Mapbox or Leaflet is used for displaying the data.

[1860] For example, the system draws a route on a map, places pins at each tourist spot, and displays detailed information such as the mode of transportation, total distance, and required time on the screen.

[1861] Specific examples

[1862] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[1863] User: Enters "Shibuya Ward, running, 5km, heart, safety first" into the app.

[1864] Terminal: Press the "Generate" button and the data will be sent to the server in JSON format.

[1865] Server: Obtains Shibuya Ward map data via the Google Maps API and analyzes road information using the Geopy library. Shapely generates a heart-shaped pattern, and a GPT-3 model generates a safe route, taking into account routes that pass through the Hachiko statue and Yoyogi Park.

[1866] Server: Validates the generated route based on traffic rules and safety, and sends the final route data to the device.

[1867] Terminal: The received route is displayed on a map, and the user can check the course map, travel method, total distance, required time, and tourist attractions.

[1868] This process allows users to easily generate safe and efficient routes with thematic geometries.

[1869] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1870] Step 1:

[1871] User: Opens the application and enters the area (e.g. Shibuya Ward), mode of transportation (e.g. running), distance (e.g. 5 kilometers), theme to draw (e.g. heart), and safety priority or tourist attraction priority (e.g. safety).

[1872] Input: Region, mode of transport, distance, theme, safety or tourist attraction priority

[1873] Output: User input data (JSON format)

[1874] Step 2:

[1875] Terminal: Validates the entered data, and when the user presses the "Generate" button, converts the input data into JSON format and sends it to the server.

[1876] Input: User-entered data

[1877] Data processing: Convert user input data into JSON format

[1878] Output: POST request to the server

[1879] Step 3:

[1880] Server: Receives input data and retrieves map data for the specified area (Shibuya Ward) using the Google Maps API.

[1881] Input: User-entered data

[1882] Data processing: Retrieving and parsing map data

[1883] Output: Parsed map data (a list containing road and intersection information)

[1884] Step 4:

[1885] Server: Analyzes the acquired map data and extracts information on major roads and intersections.

[1886] Input: Map data

[1887] Data processing: Analysis of map data using Geopy and Fiona libraries

[1888] Output: A list of extracted road segments and intersections

[1889] Step 5:

[1890] Server: Generates a specific shape (e.g., heart) based on the user's theme.

[1891] Input: User theme, list of road segments and intersections

[1892] Data processing: Shape generation using the Shapely library

[1893] Output: Generated theme shape (e.g. heart-shaped route)

[1894] Step 6:

[1895] Server: Enters a prompt into a generative AI model (e.g., GPT-3) and generates a route that takes safety and traffic rules into consideration.

[1896] Input: Generated theme shapes

[1897] Data processing: Route generation using an AI model based on prompts

[1898] Output: Initial generated route

[1899] Example prompt sentence:

[1900] Prompt statement:

[1901] The user is looking for a 5-kilometer running course in Shibuya, Tokyo. The course should be heart-shaped, and safety is a priority. Generate a route that passes by the Hachiko statue and Yoyogi Park as much as possible.

[1902] Step 7:

[1903] Server: Simulates whether the generated route complies with traffic rules and is safe. Adjusts the route if necessary.

[1904] Input: Initial generated route, traffic rule dataset

[1905] Data processing: Verification and adjustment based on traffic rules and safety

[1906] Output: Final generated route

[1907] Step 8:

[1908] Server: Once the final route is validated, it converts the route data into JSON format and sends it to the device.

[1909] Input: Final generated route

[1910] Data processing: Converting route data to JSON format

[1911] Output: Send route data to the device

[1912] Step 9:

[1913] Terminal: Analyzes the route data received from the server and displays it to the user. A map display library such as Mapbox or Leaflet is used for displaying the data.

[1914] Input: Route data received from the server

[1915] Data processing: Route data analysis and mapping

[1916] Output: User-visible route map, detailed information such as travel methods, total distance, travel time, and points of interest

[1917] The system allows users to easily generate safe and efficient routes with specific geometries and view all the necessary details.

[1918] (Application example 1)

[1919] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1920] The problem that this invention aims to solve is to provide an optimal route for delivery staff to travel to multiple delivery destinations efficiently and safely in a food delivery service.The invention also aims to build a system that can provide added value by generating routes that include tourist attractions, allowing delivery staff to discover the charms of the area while performing delivery work.

[1921] 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.

[1922] In this invention, the server includes means for a user to input the area, mode of transportation, distance, and theme to be drawn, means for transmitting the input data to the server, means for analyzing map data based on the data received by the server, means for generating a specific shape based on the theme, means for generating a route using an AI model taking safety and traffic rules into consideration, means for verifying and adjusting the generated route, means for incorporating tourist attractions into the route, means for transmitting the final course data to the terminal, means for the terminal to display the course data, means for the user to use as an exercise plan, means for generating a round route for delivery destinations, means for generating a route that passes tourist attractions, and means for verifying traffic rules and safety. This enables delivery staff to deliver efficiently and safely, and also enables the provision of high-value-added routes that visit tourist attractions.

[1923] "User" refers to a customer or delivery staff member who uses this system.

[1924] "Area" refers to the specific geographic area in which delivery is made.

[1925] "Means of transportation" refers to the means of transportation used when making deliveries, including bicycles, walking, cars, etc.

[1926] "Distance" refers to the distance of travel specified by the user.

[1927] The "theme to be drawn" refers to instructions entered by the user regarding the shape and pattern of the route to be generated.

[1928] "Server" refers to a computer system that receives, analyzes, routes, and transmits data.

[1929] "Map data" refers to data that includes information on roads, intersections, buildings, etc. in a specific area.

[1930] "Specific Shape" refers to the geometric shape of the route that is generated based on a theme entered by the user.

[1931] An "AI model" is an algorithm that uses artificial intelligence technology and is used to take safety and traffic rules into consideration when generating routes.

[1932] "Traffic rules" refers to legal regulations that must be followed while traveling, such as the Road Traffic Act.

[1933] "Points of interest" refers to specific notable places or landmarks that are included in route generation.

[1934] "Course data" is digital information about the generated route that is ultimately sent to the terminal.

[1935] "Device" means a device used by a User to view and display course data, including, for example, a smartphone or tablet.

[1936] "Exercise planning" refers to a plan of movement or exercise that a user will undertake based on the generated route.

[1937] "Delivery destination" refers to the location where the food delivery service should deliver the item.

[1938] A "routes" refers to a specific route generated to efficiently visit multiple delivery destinations.

[1939] "Safety" refers to factors taken into consideration when generating a route to prevent accidents and dangers.

[1940] "Efficient" means that the route is optimized to achieve the goal with the least amount of time and effort.

[1941] "Added value" refers to additional benefits or value to the user that are provided in addition to basic functionality.

[1942] This invention is a system that generates optimal delivery routes based on information entered by the user and provides them to delivery staff. This system improves delivery efficiency, ensures safety, and provides added value such as routes that visit tourist attractions.

[1943] System Configuration

[1944] 1. User-entered data

[1945] Using a smartphone application, users input data such as the area, mode of transportation, distance, theme they want to depict, safety priority or tourist attraction priority.

[1946] 2. Data Transmission and Reception

[1947] The data entered by the user is sent to the server via the smartphone application, and the server receives the data and begins analyzing it.

[1948] 3. Map data acquisition and analysis

[1949] The server retrieves map data for the specified area using Google Maps API or similar, analyzes this data, extracts information on major roads, intersections, and buildings, and processes it as data necessary for route generation.

[1950] 4. Shape and Route Generation

[1951] The server generates a specific shape based on a theme specified by the user, and uses an AI model to generate a route that takes safety and traffic rules into account. The AI ​​model uses machine learning frameworks such as TensorFlow and PyTorch.

[1952] 5. Route verification and adjustment

[1953] The server verifies that the generated route complies with traffic rules and is safe. If necessary, it adjusts the route to determine the optimal delivery route. If the route includes tourist attractions, it also incorporates their locations into the route.

[1954] 6. Sending and displaying course data

[1955] The final course data is sent from the server to the user's smartphone. The smartphone application receives this course data and displays it to the user. The user can check information such as the course map, travel methods, total distance, required time, and tourist attractions along the way.

[1956] Specific examples

[1957] For example, let's consider a scenario where a delivery staff member wants to cycle around multiple delivery destinations in Shibuya Ward, Tokyo, and simultaneously generate a route that draws a heart shape. In this case, the user inputs the following information into the smartphone application: Shibuya Ward, bicycle, 5 kilometers, heart, and safety priority.

[1958] Example prompt sentence:

[1959] "Generate routes to three delivery destinations by bicycle within the Shibuya Ward area. Safety is the top priority and I would like the route to follow traffic rules."

[1960] In this way, users input the necessary information and the system automatically generates the optimal delivery route, which is safe and efficient, allowing delivery staff to visit tourist attractions and provide high-value-added services.

[1961] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1962] Step 1:

[1963] The user inputs the area, mode of transportation, distance, and theme they want to draw.

[1964] The user starts the smartphone application and inputs information such as the area, mode of transportation, distance, theme to be drawn, priority of safety or priority of tourist attractions into the specified interface. This input data is collected and sent to the server in the next step.

[1965] Step 2:

[1966] Sending input information to the server

[1967] When the user presses the "Generate Route" button, the device sends all the data entered, including information about the area, mode of transportation, distance, theme, and priority, to the server. The data is sent in JSON format to the server.

[1968] Step 3:

[1969] Map data acquisition and analysis

[1970] The server uses the received data to obtain map data for the specified area using the Google Maps API. The obtained map data is then analyzed to extract information on major roads, intersections, buildings, etc. The extracted information is then used to generate the route.

[1971] Step 4:

[1972] Theme-based specific shape generation

[1973] The server generates a specific shape based on a theme entered by the user (e.g., a heart shape), using a theme-specific path generation algorithm. The generated shape becomes the basis for the final route design.

[1974] Step 5:

[1975] Route generation using AI models

[1976] The server generates routes using an AI model, taking safety and traffic rules into consideration. This AI model uses machine learning frameworks such as TensorFlow and PyTorch. The optimal route is calculated based on input data (map information, specific shapes, and traffic rules).

[1977] Step 6:

[1978] Validate and adjust the generated route

[1979] The server verifies that the generated route complies with traffic rules and is safe. It runs a simulation to check for safety issues and adjusts the route as necessary. Once verified, the route data is prepared for transmission in the next step.

[1980] Step 7:

[1981] Include tourist attractions in your route

[1982] The server references tourist attraction data and incorporates tourist attractions into the generated route. If the user has set tourist attractions as a priority, the server adjusts the route to pass through the tourist attractions. The final route after adjustment is determined.

[1983] Step 8:

[1984] Submitting the final course data

[1985] The final course data is sent from the server to the user's smartphone, including a map of the route, travel methods, total distance, travel time, and information on tourist attractions.

[1986] Step 9:

[1987] Viewing course data

[1988] The device displays the received route data through a user interface, allowing the user to efficiently deliver the goods while checking the route map and understanding the travel method, total distance, required time, and tourist attractions.

[1989] 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.

[1990] System Overview

[1991] This invention is a system that automatically generates GPS art courses based on user input data. An emotion engine that recognizes the user's emotions is incorporated as an additional element, allowing the system to generate courses according to the user's emotional state. This system allows the user to input their area, mode of transportation, distance, and desired theme, and generates a safe and efficient route based on that information. It can also generate courses that take into account traffic rules and include tourist attractions.

[1992] composition

[1993] 1. User-entered data

[1994] region

[1995] Transportation

[1996] distance

[1997] Themes I want to draw

[1998] Safety priority or tourist attraction priority

[1999] 2. Server Functions

[2000] Receiving input data

[2001] Map data acquisition and analysis

[2002] Shape generation based on user themes

[2003] Route generation using AI models

[2004] Emotion data analysis and route adjustment using an emotion engine

[2005] Verifying route safety and traffic rules

[2006] Sending course data to your device

[2007] 3. Device Features

[2008] Providing an input interface

[2009] Receiving and displaying course data

[2010] Collecting and transmitting emotional states

[2011] Program processing

[2012] 1. Receiving user input

[2013] Device: The user opens the application on the device and inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions. In addition, an emotion engine that collects the user's emotional state operates and obtains emotion data from the device.

[2014] 2. Sending input information to the server

[2015] Terminal: When the user presses the "Generate" button, the input data and emotion data are sent to the server. The sent data includes the area, transportation method, distance, theme, priority of safety or tourist attractions, and emotion data.

[2016] 3. Server-side data processing

[2017] server:

[2018] Input data and emotion data are received.

[2019] Obtain map data for the specified area and retrieve detailed information from the database, including road information, intersections, traffic lights, and other transportation infrastructure.

[2020] It runs an algorithm to generate a specific shape based on the user's theme and creates a pattern to form that shape.

[2021] The system uses an AI model to generate routes that fit the specified distance based on the acquired map data and thematic shape information. The route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[2022] The emotion engine analyzes the emotional data and adjusts the route generation accordingly. For example, if the emotion is relaxation, it will select a route that passes through a quiet park, and if the emotion is excitement, it will select a route that includes active tourist attractions.

[2023] The generated route is simulated to check whether it is safe and complies with traffic rules, and the route is fine-tuned if necessary.

[2024] The final course data that has been verified is prepared and sent to the terminal.

[2025] 4. Receiving and Displaying Course Information

[2026] Device: Displays the route data received from the server to the user, including the route map, travel method, total distance, estimated travel time, points of interest along the way, and special route adjustment information based on emotional state.

[2027] Specific examples

[2028] An example will be described in which a user wants to generate a 5-kilometer course in which he or she will draw a heart shape while running in Shibuya Ward, Tokyo.

[2029] 1. Receiving user input

[2030] Device: The user enters information about Shibuya Ward, running, 5 kilometers, heart rate, and safety priority into the application. The emotion engine then recognizes the user's emotional state and determines that the user needs to relax.

[2031] 2. Sending input information to the server

[2032] Device: Press the "Generate" button to send the information to the server, along with the emotion data.

[2033] 3. Data Processing

[2034] server:

[2035] Obtain map data for Shibuya Ward and analyze road information.

[2036] Generate a heart-shaped pattern and check if it is suitable for 5 kilometers.

[2037] Using an AI model, the system generates a safe route that follows traffic rules. Because the user's emotional state indicates a desire for relaxation, the system selects routes that pass through parks and natural areas as much as possible.

[2038] The route will also include tourist attractions such as the Hachiko statue and Yoyogi Park.

[2039] Simulate the generated route to ensure it is safe and adjust it if necessary.

[2040] The final course data is sent to the device.

[2041] 4. View course information

[2042] Terminal: Displays to the user a course map, mode of travel, distance, time required, tourist attractions, and special route adjustment information based on emotional state.

[2043] In this way, users can generate safe and efficient GPS art courses tailored to their emotional state.

[2044] The processing flow will be explained below.

[2045] Step 1:

[2046] User: Opens the application on the device. The user inputs the area (e.g., "Shibuya-ku, Tokyo"), transportation method (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and priority of safety or tourist attractions. Furthermore, the emotion engine collects the user's emotional state and analyzes the current emotional state.

[2047] Step 2:

[2048] Terminal: When the user presses the "Generate" button, the input data and emotion data are sent to the server. The sent data includes the area, transportation method, distance, theme, priority of safety or tourist attractions, and emotion data.

[2049] Step 3:

[2050] Server: Analyzes the data received from the device. Specifically, it retrieves map data for the area specified by the user and obtains detailed information from a database, including road information, intersections, traffic lights, and other traffic infrastructure information.

[2051] Step 4:

[2052] Server: Performs thematic analysis. Based on a theme entered by the user (e.g., "heart"), it runs an algorithm to generate a specific shape and creates the patterns that form that shape.

[2053] Step 5:

[2054] Server: Generates a route using an AI model. This generates a route that matches the specified distance based on the acquired map data and thematic shape information. Route generation also takes into account the safety of each mode of transportation and traffic rules (e.g., one-way streets, bicycle-only lanes, etc.).

[2055] Step 6:

[2056] Server: Analyzes emotional data. The emotional state of the user recognized by the emotion engine (e.g., "I want to relax" or "I want an active experience") is analyzed and reflected in route generation.

[2057] Step 7:

[2058] Server: Adjusts the route based on emotional data. For example, if the emotional state is one of relaxation, it selects a route that passes through parks and quiet roads, and if the emotional state is active, it selects a route that includes tourist attractions and bustling places.

[2059] Step 8:

[2060] Server: Adjust the route to include tourist attractions. If the user sets a high priority for a tourist attraction, the server will incorporate the specified tourist attraction (e.g., Hachiko Statue, Yoyogi Park, etc.) into the route and recalculate the route to reach that attraction.

[2061] Step 9:

[2062] Server: Validates the generated route, simulating whether it complies with traffic rules and ensures safety, and fine-tunes the route if necessary.

[2063] Step 10:

[2064] Server: Prepares the final course data after verification and sends it to the device.

[2065] Step 11:

[2066] Device: Displays the route data received from the server to the user, including the route map, travel method, total distance, estimated travel time, points of interest along the way, and special route adjustment information based on emotional state.

[2067] Step 12:

[2068] User: Checks the provided course information, and if satisfied, prepares to actually exercise the course.

[2069] Example 2

[2070] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2071] Previous GPS Art route generation systems did not take the user's emotional state into account, making it difficult to provide routes that suited the user's mental and physical needs. Furthermore, they rarely guaranteed safety or compliance with traffic rules, making it difficult to generate appropriate routes for specific modes of transportation. Another problem was that they were unable to automatically generate routes that included tourist attractions, and lacked features that would increase the user's enjoyment.

[2072] 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.

[2073] In this invention, the server includes means for the user to input the area, mode of transportation, distance, and theme to be drawn, means for recognizing the user's emotional state and collecting relevant data, means for transmitting the input data and emotional data to the server, means for the server to analyze map data based on the data received, means for generating a specific shape based on the theme, means for generating a route using an AI model taking into account safety and traffic rules, means for adjusting the generated route based on the emotional data, means for verifying and adjusting the generated route, means for transmitting the final course data to the terminal, and means for the terminal to display the course data. This enables the generation of an optimal route that takes into account the user's emotional state, safety, and traffic rules, providing a safer and more enjoyable GPS art experience.

[2074] "Region" is data indicating the location or area where the user performs GPS art.

[2075] "Means of transportation" is data that indicates the method or tool (e.g., running, cycling, etc.) used by the user to create GPS art.

[2076] "Distance" is data indicating the total distance traveled by the user when drawing GPS art.

[2077] The "theme to be drawn" is data indicating a specific shape or figure (e.g., heart, star, etc.) that the user wants to draw in GPS Art.

[2078] "Emotional state" is data that indicates the mental or emotional state of a user.

[2079] An "emotion engine" refers to a function or system for recognizing a user's emotions and analyzing their state.

[2080] "Server" refers to a central computing system for receiving and processing data sent by users.

[2081] A "data packet" is a unit of information that includes user input data and emotion data and is sent to the server.

[2082] "Map Data" refers to a data set containing details of roads, intersections, traffic lights, etc. for a specified area.

[2083] A "theme shape" is data that indicates a shape that embodies a figure or pattern that the user wants to draw.

[2084] "AI Model" refers to the artificial intelligence algorithm used to generate the route.

[2085] "Route adjustment" is the process of making corrections and optimizations to the generated route based on the user's emotional data and other considerations.

[2086] "Course data" refers to data that indicates the final route information of the GPS Art that has been analyzed and generated.

[2087] "Terminal" refers to the device (e.g., smartphone, tablet, etc.) used by the user to enter and display the final course data.

[2088] "Tourist attractions" are data that indicate particular geographical locations or cultural facilities that may be of interest to users.

[2089] System Overview

[2090] This invention is a system that automatically generates GPS art courses based on user input and emotional data. The system generates a theme shape based on user-entered information and uses an AI model to generate a route that matches it. It also incorporates an emotion engine that recognizes the user's emotional state and adjusts the route accordingly. Users can input their area, mode of transportation, distance, theme they want to draw, and safety or tourist attraction priorities.

[2091] Hardware and software used

[2092] 1. User device (e.g. smartphone, tablet)

[2093] A device that allows users to input data and interact with the system, incorporating an input interface and emotion engine.

[2094] 2. Server

[2095] It is a central computing system for receiving and processing input data and emotion data, analyzing map data, generating theme shapes, generating routes using AI models, making adjustments based on emotion data, and transmitting the final course data.

[2096] Program processing explanation

[2097] Receiving user input

[2098] The user opens the application on their device and enters the following information: area (e.g., "Shibuya-ku, Tokyo"), mode of transportation (e.g., "running"), distance (e.g., "5 kilometers"), theme to draw (e.g., "heart"), and safety or tourist attraction priority. Furthermore, an emotion engine runs, collecting the user's emotional state using the camera and microphone.

[2099] Sending input information to the server

[2100] When the user presses the "Generate" button, the device sends this data to the server, including the area, mode of transportation, distance, theme, safety or tourist attraction priority, and emotion data.

[2101] Server-side data processing

[2102] The server does the following:

[2103] Receives input data and emotion data.

[2104] Obtain map data for the specified area and extract detailed information such as road information, intersections, and traffic lights from the database.

[2105] It runs an algorithm that generates a specific shape based on the user's theme, then creates a pattern to form that shape.

[2106] Routes are generated using AI models, taking safety and traffic rules into consideration during the process.

[2107] The generated route is adjusted based on the analysis results of the emotion engine. For example, if the user wants to "relax," the system will select a route that passes through parks and quiet places.

[2108] Simulate the generated route to ensure it is safe and make any necessary adjustments.

[2109] The final course data is sent to the device.

[2110] Receive and view course information

[2111] The device displays the course data received from the server to the user, including:

[2112] Course Map

[2113] How to move

[2114] Total distance

[2115] Estimated time required

[2116] Tourist attractions to visit

[2117] Special route adjustment information based on emotional state

[2118] Specific examples

[2119] If a user wants to generate a 5km course in Shibuya, Tokyo, where they will draw a heart shape while running:

[2120] 1. The user enters the following information into the application: Shibuya Ward, running, 5km, heart, safety first. The emotion engine recognizes that the user needs to relax.

[2121] 2. Press the "Generate" button to send the information to the server, along with the emotion data.

[2122] 3. The server retrieves map data for Shibuya Ward and analyzes road information. A heart-shaped pattern is generated, and an AI model is used to generate a safe route that takes traffic rules into account. Since the driver is looking for relaxation, parks and quiet routes are selected whenever possible. Tourist attractions are also included.

[2123] 4. Include tourist attractions such as the Hachiko statue and Yoyogi Park in your route.

[2124] 5. The generated route is simulated to check its safety, and fine-tuned if necessary. The final course data is sent to the device.

[2125] 6. The device displays the route map, travel method, distance, travel time, tourist attraction information, and special route adjustment information based on emotional state to the user.

[2126] Example prompt sentence:

[2127] "Generate a 5-kilometer course to trace a heart shape while running in Shibuya, Tokyo, prioritizing safety. I'm in the mood for relaxation right now."

[2128] In this way, users can generate safe and efficient GPS art courses tailored to their emotional state.

[2129] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2130] Step 1:

[2131] Receiving user input

[2132] The user opens the application on their device and inputs their "area" (e.g., "Shibuya-ku, Tokyo"), "mode of transportation" (e.g., "running"), "distance" (e.g., "5 kilometers"), "theme to draw" (e.g., "heart"), and "safety priority" or "tourist attraction priority." The emotion engine then operates, collecting the user's emotional state via the camera and microphone and converting it into digital data.

[2133] Input: Region, mode of transportation, distance, theme, priority, emotional state

[2134] Output: Collected user input data and emotion data

[2135] Step 2:

[2136] Preparing to send input information

[2137] The terminal assembles the collected user input data and emotion data into a single data packet, which includes the area, mode of transportation, distance, theme, priority of safety or tourist attractions, and emotion data.

[2138] Input: Collected user input data and emotion data

[2139] Output: Data packets

[2140] Step 3:

[2141] Sending data to the server

[2142] When the user presses the "Generate" button, the terminal sends a data packet to the server.

[2143] Input: Data packet

[2144] Output: Send data to the server

[2145] Step 4:

[2146] Receiving data

[2147] The server receives data packets sent from the terminal, which include region, mode of transportation, distance, theme, priority, and emotion data.

[2148] Input: Data packet

[2149] Output: Received data

[2150] Step 5:

[2151] Map data acquisition and analysis

[2152] The server retrieves map data for the area specified by the user and extracts detailed information from the database, such as road information, intersections, and traffic light locations. Through this analysis, it collects topographical and infrastructure information that will be the basis for route generation.

[2153] Input: Region data

[2154] Output: Map data (road information, intersections, traffic light locations, etc.)

[2155] Step 6:

[2156] Theme Shape Generation

[2157] The server runs an algorithm to generate a specific shape based on a user-specified theme (e.g., "heart"), which generates specific paths and segment patterns to form the theme shape.

[2158] Input: Theme data

[2159] Output: Theme Shape Pattern

[2160] Step 7:

[2161] Route Generation

[2162] The server uses an AI model to generate a route based on the acquired map data and the generated thematic shape patterns, taking into account safety and traffic rules (e.g., one-way streets, bicycle lanes, etc.) depending on the mode of travel.

[2163] Input: Map data and thematic shape patterns

[2164] Output: Generated routes

[2165] Step 8:

[2166] Route adjustment based on emotion data

[2167] The server then adjusts the generated route using the emotion data analyzed by the emotion engine. For example, if the user is looking to relax, the server may select a route that includes parks and plenty of nature.

[2168] Input: Generated route and emotion data

[2169] Output: Adjusted route

[2170] Step 9:

[2171] Safety and traffic rules verification

[2172] The server simulates the generated route to ensure safety and compliance with traffic rules, and fine-tunes the route if necessary.

[2173] Input: Adjusted Route

[2174] Output: Final route

[2175] Step 10:

[2176] Prepare and submit final course data

[2177] The server prepares the final course data and sends it to the device, which includes the course map, travel mode, distance, travel time, tourist attractions, and special route adjustment information based on emotional state.

[2178] Input: Final Route

[2179] Output: Send course data to the device

[2180] Step 11:

[2181] View course information

[2182] The device displays the course data received from the server to the user, including the course map, travel method, distance, travel time, tourist attractions along the way, and special route adjustment information based on emotional state.

[2183] Input: Course data

[2184] Output: Course information displayed to user

[2185] (Application example 2)

[2186] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2187] Conventional automated patrol systems within factories have the problem of not being able to fully consider safety and efficiency when generating routes. Furthermore, because the emotional state of the operator is not reflected in the patrol route, it is difficult to manage stress and ensure appropriate rest areas. The present invention aims to solve these problems and provide a system that achieves safe and efficient patrol within a factory.

[2188] 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.

[2189] In this invention, the server includes means for the user to input the area, means of transportation, distance, and theme to be drawn, means for transmitting the input data to the server, and means for collecting emotion data and adjusting the route based on the emotion data, thereby enabling route adjustment based on the emotion data and generation of work areas and process points for equipment maintenance.

[2190] A "region" is a geographical location specified by the user, and is the basic information for generating a route.

[2191] "Transportation" refers to the transportation method designated by the user, and includes running, cycling, car, etc.

[2192] "Distance" is the distance the user desires to travel, and is a parameter that specifies the length of the route.

[2193] The "theme" is the specific shape or pattern desired by the user, and serves as the basis for GPS art.

[2194] The "means for transmitting data to a server" is a function for sending information entered by a user to a server via a network.

[2195] The "means for analyzing map data based on data received by the server" is a function for extracting and analyzing detailed information on the map based on information received by the server from the user.

[2196] The "means for generating a specific shape based on a theme" is a function for generating a specific shape or pattern on a map based on a theme input by the user.

[2197] "Means for generating routes using AI models, taking into account safety and traffic rules" refers to a function that automatically generates optimal routes using AI models, taking into account the safety and traffic rules of each means of transportation.

[2198] "Means for verifying and adjusting the generated route" refers to a function that simulates whether the generated route complies with safety and traffic rules, and makes fine adjustments as necessary.

[2199] The "means for transmitting final course data to the terminal" is a function for transmitting the generated final route information to the terminal.

[2200] The "means for the terminal to display course data" refers to a function for visually displaying the course data received by the terminal to the user.

[2201] The "means for collecting emotional data and adjusting the route based on the emotional data" is a function that analyzes the user's emotional state using an emotional engine and optimizes the route based on that data.

[2202] The "means for generating patrol routes within a factory and supporting patrol by a robot" is a function that generates routes that allow a robot to patrol a factory efficiently and safely, and supports that patrol.

[2203] The "means for generating a route including tourist attractions" is a function for generating a route including tourist attractions within a specified area.

[2204] "Means for generating process points for work areas and equipment maintenance" is a function that includes specific work areas within a factory and points of equipment that require maintenance in the route.

[2205] "Means for providing the user with final course information and planning exercise based on that information" is a function that provides information for the user to plan exercise based on the generated route information.

[2206] The "means for planning patrol routes to improve work efficiency and safety within a factory" is a function for planning patrol routes within a factory and improving work efficiency and safety.

[2207] System Overview

[2208] The present invention is an automatic route generation system for a factory that generates an efficient and safe route based on user input data. The system is composed of the following elements:

[2209] System Configuration

[2210] 1. User-entered data

[2211] Area (e.g. Factory Zone A)

[2212] Means of transportation (e.g., patrol robot)

[2213] Distance (e.g. 5 kilometers)

[2214] The theme you want to draw (e.g., shortest route)

[2215] Prioritizing safety or patrol efficiency

[2216] Emotional data (e.g., stress level, preferred_break_spot)

[2217] 2. Server Functions

[2218] Receiving input data

[2219] Map data acquisition and analysis

[2220] Shape generation based on user themes

[2221] Route adjustment based on emotion data analysis

[2222] Route generation using AI models

[2223] Verifying route safety and traffic rules

[2224] Sending the final course data to the device

[2225] 3. Device Features

[2226] Providing an input interface

[2227] Receiving and displaying course data

[2228] Collecting and transmitting emotional states

[2229] Program processing explanation

[2230] 1. Receiving user input data

[2231] The terminal receives information from the user, such as area, mode of transportation, distance, theme, priority of safety or patrol efficiency, and emotion data. This input data is input by the user by opening an application on the terminal.

[2232] 2. Sending input information to the server

[2233] When the user presses the "generate" button, the terminal transmits the input data and emotion data to the server.

[2234] 3. Server-side data processing

[2235] The server analyzes the received data and retrieves map data for the specified area. It then uses an AI model to generate a route that takes safety and efficiency into account. It adjusts the route based on emotion data, prioritizing rest areas if stress levels are high, for example. Finally, the generated route is verified for safety and compliance with traffic rules, and fine-tuning is performed as needed.

[2236] Hardware and software used

[2237] Hardware: Servers (dedicated servers or cloud servers), user devices (smartphones, tablets, laptops, etc.)

[2238] Software: Application (to provide user interface), AI model (to generate routes), emotion engine (to analyze emotion data)

[2239] Specific examples

[2240] Let's take the example of a user wanting to generate a safe and efficient 5-kilometer patrol route for a patrol robot in factory zone A, which is experiencing a high stress level. The user opens the application, selects factory zone A, inputs the information for the patrol robot, 5 kilometers, shortest route, and safety priority, and sends emotional data indicating a high stress level.

[2241] The server acquires map data for Factory Zone A and analyzes road information. At the same time, it generates a route that prioritizes rest areas based on emotion data, and generates a final route that takes safety and traffic rules into consideration. This route data is sent to the terminal and displayed to the user.

[2242] Prompt Sentence Examples

[2243] Generate a safe patrol route that is optimal for workers with a stress level of 3 based on the user-specified factory zone A. In particular, create a route that prioritizes rest areas. The means of transportation is a "patrol robot." The generated route should include the locations of each waypoint and the actions to be taken at each point.

[2244] In this way, users can generate safe and efficient routes around the factory that are tailored to their emotional state.

[2245] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2246] Step 1:

[2247] The user opens the application on their device and inputs the area (e.g., factory zone A), the means of transportation (e.g., patrol robot), the distance (e.g., 5 kilometers), the theme they want to draw (e.g., the shortest route), the priority of safety (or the priority of patrol efficiency), and emotional data (e.g., stress level). The input data is formatted in JSON format.

[2248] Input: Region, mode of transportation, distance, theme, safety priority, sentiment data

[2249] Output: Input data in JSON format

[2250] Step 2:

[2251] When the user presses the "Generate" button, the terminal sends the formatted JSON input data to the server using an HTTP POST request.

[2252] Input: Input data in JSON format

[2253] Output: POST request to the server

[2254] Step 3:

[2255] The server analyzes the received JSON format data and obtains map data for the specified area (Factory Zone A). It also obtains data on traffic infrastructure such as road information, intersections, and traffic lights from a database.

[2256] Input: JSON format input data received via POST request

[2257] Output: Map data, road information, traffic infrastructure data

[2258] Step 4:

[2259] The server runs an algorithm that generates a particular shape based on the theme, and creates patterns to form that shape, for example, if the theme is "shortest path", it will generate patterns to form the shortest path.

[2260] Input: User's theme (e.g. shortest path)

[2261] Output: Specific shape pattern

[2262] Step 5:

[2263] The server generates a route using an AI model. It uses acquired map data and a shape pattern based on the theme to generate a route that fits the specified distance (5 kilometers). It generates the route while taking into account the safety and traffic rules of each mode of transportation.

[2264] Input: Map data, shape pattern, distance, means of transportation

[2265] Output: Generated routes

[2266] Step 6:

[2267] The server analyzes the emotion data and adjusts the route accordingly. For example, if the stress level is high, the server may select a route that prioritizes rest areas. The server processes the emotion data using an emotion engine and fine-tunes the route.

[2268] Input: Generated route, emotion data

[2269] Output: Adjusted route

[2270] Step 7:

[2271] The server simulates and verifies the generated route to ensure safety and compliance with traffic rules, and fine-tunes the route if there are any issues with safety or traffic rules.

[2272] Input: Adjusted Route

[2273] Output: Final route

[2274] Step 8:

[2275] The server then sends the final course data to the device, which includes the location of each waypoint, the actions to be taken, the distance, and the estimated time required.

[2276] Input: Final route

[2277] Output: Course data to the device

[2278] Step 9:

[2279] The terminal displays the course data received from the server to the user, who can then check information such as the course map, travel method, total distance, estimated time required, and rest areas along the way.

[2280] Input: Course data received from the server

[2281] Output: Course information displayed on the user interface

[2282] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2283] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2284] 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 robot 414.

[2285] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2286] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2287] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2288] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2289] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2290] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2291] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2292] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2293] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2294] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2295] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2296] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2297] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2298] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2299] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2300] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2301] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2302] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2303] The following is further disclosed regarding the above embodiment.

[2304] (Claim 1)

[2305] A way for users to input the area, mode of transportation, distance, and theme they want to draw;

[2306] means for transmitting the input data to a server;

[2307] means for analyzing map data based on the data received by the server;

[2308] a means for generating specific shapes based on a theme;

[2309] A means of generating routes using AI models that take safety and traffic rules into account;

[2310] a means for validating and adjusting the generated route;

[2311] means for transmitting the final course data to the terminal;

[2312] The system includes a means for displaying course data on the terminal.

[2313] (Claim 2)

[2314] 10. The system of claim 1, further comprising means for generating a route including tourist attractions.

[2315] (Claim 3)

[2316] 10. The system of claim 1, further comprising means for providing the user with final course information and planning an exercise based thereon.

[2317] "Example 1"

[2318] (Claim 1)

[2319] A means for the user to input the area, mode of transportation, distance, theme to be depicted, safety priority or tourist attraction priority;

[2320] means for transmitting the input data to a server;

[2321] means for acquiring and analyzing map data based on the data received by the server;

[2322] a means for generating specific shapes based on a theme;

[2323] A means to input prompts into the AI ​​model to generate a route that takes safety and traffic rules into consideration;

[2324] A means to validate the generated route and adjust it if necessary;

[2325] means for transmitting the final course data to the terminal;

[2326] The system includes a means for displaying course data on the terminal.

[2327] (Claim 2)

[2328] 10. The system of claim 1, further comprising means for generating a route including tourist attractions.

[2329] (Claim 3)

[2330] 10. The system of claim 1, further comprising means for providing the user with final course information and planning an exercise based thereon.

[2331] "Application Example 1"

[2332] (Claim 1)

[2333] A way for users to input the area, mode of transportation, distance, and theme they want to draw;

[2334] means for transmitting the input data to a server;

[2335] means for analyzing map data based on the data received by the server;

[2336] a means for generating specific shapes based on a theme;

[2337] A means of generating routes using AI models that take safety and traffic rules into account;

[2338] a means for validating and adjusting the generated route;

[2339] A way to incorporate tourist attractions into the route,

[2340] means for transmitting the final course data to the terminal;

[2341] a means for the terminal to display course data;

[2342] A means for the user to use as an exercise plan;

[2343] A means for generating a route for visiting delivery destinations;

[2344] a means for generating a route through tourist attractions;

[2345] A system that includes means to verify traffic rules and safety.

[2346] (Claim 2)

[2347] 10. The system of claim 1, further comprising means for generating a route including tourist attractions.

[2348] (Claim 3)

[2349] 10. The system according to claim 1, further comprising means for providing an efficient round route for a plurality of delivery destinations in a food delivery service.

[2350] "Example 2: Combining Emotion Engines"

[2351] (Claim 1)

[2352] A way for users to input the area, mode of transportation, distance, and theme they want to draw;

[2353] means for recognizing emotional states and collecting corresponding data;

[2354] means for transmitting the input data and emotion data to a server;

[2355] means for analyzing map data based on the data received by the server;

[2356] a means for generating specific shapes based on a theme;

[2357] A means of generating routes using AI models that take safety and traffic rules into account;

[2358] means for adjusting the generated route based on the emotion data;

[2359] a means for validating and adjusting the generated route;

[2360] means for transmitting the final course data to the terminal;

[2361] The system includes a means for displaying course data on the terminal.

[2362] (Claim 2)

[2363] ...

Claims

1. A way for users to input the area, mode of transportation, distance, and theme they want to draw; means for transmitting the input data to a server; means for analyzing map data based on the data received by the server; a means for generating specific shapes based on a theme; A means of generating routes using AI models that take safety and traffic rules into account; a means for validating and adjusting the generated route; means for transmitting the final course data to the terminal; The system includes a means for displaying course data on the terminal.

2. The system of claim 1 further comprising means for generating a route including tourist attractions.

3. 10. The system of claim 1, further comprising means for providing the user with final course information and planning an exercise based thereon.

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