System

Abstract

A system is provided.SOLUTION: This system includes a means for receiving a drawing or a three dimensional model, a means for checking the received drawing or three dimensional model by collating it with a legal reference value, a means for generating and displaying a collation result, a means for generating advice on color arrangement and comfort, and a means for displaying the generated advice.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] During the proposal phase of a construction project, many drawings and 3D models are created, and they must be checked to see if they comply with regulations and are appropriate from the perspective of visual and comfort. However, these tasks require a lot of time and cost, so efficiency improvements are needed. The present invention aims to reduce the costs and man-hours involved in the proposal phase of construction by automating the checking of legal standards and providing advice on design color schemes and comfort. [Means for solving the problem]

[0005] The present invention solves the above problems by the following means. First, a means for receiving drawings and 3D models is provided. This means allows a user to upload files from a terminal to a server. Next, a means for checking the received drawings and 3D models against legal standards is provided. This means allows the server to analyze the drawing data and extract structural information such as walls and doors. Furthermore, a means for generating and displaying the matching results is provided. This allows the server to generate the matching results and show the user compliance with laws and regulations. Furthermore, a means for generating advice regarding color schemes and comfort is provided. The means for displaying the advice generated by the server allows the user to use it to improve the design. A system including the above means enables efficient legal checks and design improvements.

[0006] A "drawing" is a two- or three-dimensional visual representation of design information for a construction project.

[0007] A "3D model" is a three-dimensional data representation of the shape and layout of structures in a construction project.

[0008] "Statutory standards" refers to legal standards and regulatory values ​​that must be observed in construction projects.

[0009] "Checking" is the process of verifying whether drawings or three-dimensional models conform to specified standards.

[0010] "Analysis" is the process of extracting and evaluating necessary information from drawings and three-dimensional models.

[0011] "Matching results" refer to the results of comparing the legal standard values ​​with the actual values ​​of drawings or three-dimensional models.

[0012] "Color scheme" refers to the combination and arrangement of colors used in a construction project.

[0013] "Comfort" is a concept that indicates how comfortable and appropriate the living and usage environment within a building is.

[0014] "Advice" refers to suggestions and advice for improvements regarding color schemes and comfort.

[0015] A "server" is a computing device within the system that receives, analyzes, collates, generates and sends advice.

[0016] A "terminal" is a device operated by a user, which uploads drawings and three-dimensional models and displays analysis results and advice.

[0017] "User" refers to the end user who uses this system to check and receive advice on drawings and three-dimensional models. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The present invention relates to a system that receives drawings and 3D models, analyzes them, checks them for legal regulations, and generates advice on color schemes and comfort. Specific embodiments of the system are described below.

[0040] 1. Upload and analyze drawings

[0041] First, the user uploads a blueprint or 3D model from their device. The device generates a request to send the selected file to the server, and sends the file data to the server. The server analyzes the received blueprint or 3D model and extracts structural information such as walls and doors. At this time, the server checks whether each element complies with the standards set out in building regulations.

[0042] 2. Generate and send legal check results

[0043] The server generates a matching result based on the analysis results. For example, it checks whether the wall thickness is within legal limits, whether the door height is appropriate, etc. The matching result is generated in a way that clearly shows which parts comply with the law and which parts do not. The generated matching result is sent to the terminal so that the user can check it.

[0044] 3. Providing advice on color schemes and comfort

[0045] Based on the analysis results, the server generates advice on color schemes and comfort, including, for example, whether the room color is visually less tiring, whether the furniture arrangement is comfortable, etc. The generated advice is converted into a format for display to the user and sent to the terminal.

[0046] 4. User Presentation and Interaction

[0047] The terminal displays the received matching results and advice on the user interface. The user can review them and modify the drawings or 3D models as necessary. The modified drawings or 3D models are then uploaded back to the server, where they undergo the same process of checking and receiving advice.

[0048] Specific examples

[0049] A specific scenario is shown below.

[0050] Case 1: Wall Thickness Check

[0051] The user uploads a drawing file of a new building from their terminal to the system. The server receives the drawing file and performs an analysis. The analysis extracts the wall thickness. This is then compared with the legal standard, and the user is shown a message saying, "The wall thickness exceeds the legal standard. Corrections are required." The user can correct the wall thickness and upload it again to have it checked again.

[0052] Case 2: Color Advice

[0053] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color-scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." The user then adjusts the color scheme of the design accordingly.

[0054] The system of the present invention significantly reduces the time and cost involved in the proposal phase of a construction project by automatically checking regulatory standards and providing design advice, allowing users to efficiently improve regulatory compliance and design.

[0055] The processing flow will be explained below.

[0056] Step 1:

[0057] A user selects a drawing file or a 3D model on a terminal and presses an upload button. The terminal generates a request to send the selected file to the server. The request includes the file data and associated metadata.

[0058] Step 2:

[0059] The device sends the request to the server using the HTTP protocol, etc. The server receives the request and saves the uploaded file in local storage.

[0060] Step 3:

[0061] The server analyzes the received drawing file or 3D model using algorithms that read the file and identify and extract structural elements such as walls, doors, windows, etc. The extracted information is stored in a database.

[0062] Step 4:

[0063] The server compares the extracted structural information with legal standards, for example, checking whether the wall thickness is within legal standards and whether the door height is appropriate. These standards are stored in a database in advance and are compared with the extracted information.

[0064] Step 5:

[0065] The server generates a matching result, which clearly shows which parts of the document comply with the law and which parts do not. For non-compliant parts, the result includes specific corrections and recommended changes.

[0066] Step 6:

[0067] The server converts the results of the matching process into a display format, such as HTML or JSON, and prepares the results for transmission to the device. The converted data is then organized in a format that is easy for the user to understand.

[0068] Step 7:

[0069] The server sends the converted matching results to the terminal, which processes the received data to display it on the user interface. The user checks the displayed matching results and determines whether any inconsistencies need to be corrected.

[0070] Step 8:

[0071] The server generates color and comfort advice based on the analyzed design data, creating advice on color balance, furniture placement, and more. This includes algorithms that suggest color schemes that reduce visual fatigue and placement advice to provide a comfortable user environment.

[0072] Step 9:

[0073] The server converts the generated advice into a presentation format, organizing it in a user-friendly way and converting it into HTML or JSON.

[0074] Step 10:

[0075] The server sends the converted advice to the terminal, which processes the received advice to display it on the user interface. The user can use the displayed advice to improve the design.

[0076] Example 1

[0077] 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."

[0078] In architectural projects, it is important to efficiently check the legal compliance of drawings and 3D models and provide advice on the comfort of the design. However, manual checks and advice are time-consuming and costly. Furthermore, because specialized knowledge is required, it is often difficult to provide appropriate advice. The present invention aims to solve these problems and provide a system that automatically and efficiently checks legal compliance and provides advice on comfort.

[0079] 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.

[0080] In this invention, the server includes means for receiving drawings and 3D models, means for analyzing the received drawings and 3D models to extract structures such as walls and doors, means for checking the extracted structures against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, and means for displaying the generated advice. This automates the process of checking legal compliance and improving designs in architectural projects, reducing time and costs, and making it possible to obtain appropriate advice even without specialized knowledge.

[0081] "Drawings and three-dimensional models" refer to floor plans and three-dimensional drawings, as well as the digital data thereof, that represent the structure and layout of a building or design object.

[0082] "Means for receiving" refers to a mechanism or method for importing drawing or three-dimensional model data from a user into the server.

[0083] "Means of analysis" refers to the mechanisms and software used to process received drawings and three-dimensional model data and extract structural information such as walls and doors.

[0084] The "means for extraction" is a function for extracting and identifying specific elements (e.g., walls, doors, etc.) from the analyzed data.

[0085] The "means of matching" is a method for comparing the extracted structural information with legally defined standards to confirm the degree of agreement.

[0086] The "means of checking" is a system for evaluating the compliance of each element of a building based on legal standards.

[0087] "Means for generating" refers to the process for creating information and advice to be provided to the user based on the results of analysis and collation.

[0088] The "display means" refers to a device or interface for visually conveying the generated matching results and advice to the user.

[0089] "Color and comfort advice" means suggestions and instructions for improving the visual and functional comfort of a room's color and furniture arrangement.

[0090] A "user interface" is a screen or operating means through which a user interacts with a system and inputs and outputs information.

[0091] The "means for receiving again" refers to a mechanism or method for importing the data of drawings or three-dimensional models that have been modified into the server again.

[0092] "Means for rechecking" refers to the process of comparing revised drawings and three-dimensional models with the legal standards again to confirm compliance.

[0093] This invention relates to a system that automatically analyzes and evaluates compliance with regulations and design comfort using architectural drawings and 3D models, and provides the results to users. This system is composed of three entities: a server, a terminal, and a user. The overall system configuration and the role played by each entity are explained in detail below.

[0094] Hardware and Software Configuration

[0095] 1. Receiving drawings and 3D models

[0096] The user selects drawings or 3D models from the terminal and sends them to the server.

[0097] The terminal uploads the file selected by the user to the server using a protocol such as an HTTP request.

[0098] The server stores the received drawings and 3D models in storage (e.g., a disk drive or cloud storage).

[0099] 2. Analysis of drawings and 3D models

[0100] The server analyzes the stored data, for example, using AutoCAD API or BIM (Building Information Modeling) software.

[0101] An algorithm has been implemented to extract structural information such as walls and doors from the received data.

[0102] 3. Legal checks

[0103] The server checks the extracted structural information against the standard values ​​set by building regulations.

[0104] The check uses certain criteria (e.g. wall thickness, door height) and a matching algorithm evaluates whether the criteria are met.

[0105] 4. Generate and send legal check results

[0106] Based on the check results, the server generates a matching result that clearly indicates which parts comply with the law and which parts do not.

[0107] The generated matching results are converted into a user-viewable format (e.g., text report or graphical report) and sent to the terminal.

[0108] 5. Generate color and comfort advice

[0109] Based on the analysis results, the server generates advice on color schemes and comfort.

[0110] Advice can come in the form of, for example, a visual comfort rating or suggestions for furniture placement.

[0111] 6. Display and interaction on user devices

[0112] The terminal displays the received collation results and advice on a user interface.

[0113] The user can use this information to modify the drawings or 3D models and send them back to the server.

[0114] Specific examples

[0115] Case 1: Wall Thickness Check

[0116] A user uploads a drawing file of a new building to the system from their terminal. The server receives the drawing file and performs an analysis. The analysis extracts the wall thickness. This is then compared with the legal standard, and the user is shown a message such as, "The wall thickness does not meet the legal standard (current: 10cm, required: 12cm)." The user can then correct the wall thickness and upload it again to have it checked again.

[0117] Case 2: Color Advice

[0118] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color-scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." The user then adjusts the color scheme of the design accordingly.

[0119] Prompt Sentence Examples

[0120] "Please develop a system that analyzes the drawings of a new building and checks whether the wall thickness complies with regulations. Please also explain the specific check items and how to display the check results."

[0121] "Create a system that allows users to upload a room design model and provides color advice based on visual comfort. Explain how you would analyze the model and how you would provide the advice."

[0122] As described above, the present invention makes it possible to efficiently provide advice on legal compliance and design during the proposal phase of a construction project, thereby reducing time and costs.

[0123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0124] Step 1:

[0125] Upload drawings and 3D models

[0126] The user uses the terminal to select a drawing or 3D model file and perform the upload operation. The terminal sends the selected file to the server via an HTTP request. The input is the drawing or model file selected by the user, and the output is the file being sent to the server. Specifically, the user presses the "Select File" button, selects a file (e.g., building_plan.dwg) from local storage, and clicks the "Upload" button.

[0127] Step 2:

[0128] Receiving and storing drawings and 3D models

[0129] The server receives the file sent from the terminal and saves the data in storage. The input is the file data sent from the terminal, and the output is the file saved in storage. Specifically, the server receives the HTTP request and saves the file in the specified directory. For example, the save location is / uploads / building_plan.dwg.

[0130] Step 3:

[0131] Analysis of drawings and 3D models

[0132] The server analyzes the saved files and extracts structural information such as walls and doors. This analysis uses AutoCAD API and BIM software. The input is the saved file, and the output is the extracted structural information. Specifically, the server calls the AutoCAD API and analyzes and extracts the location of walls, doors, etc. from the file.

[0133] Step 4:

[0134] Legal checks

[0135] The server checks the extracted structural information against the standard values ​​set by building regulations. Examples of criteria for checking include "wall thickness" and "door height." The input is the extracted structural information, and the output is the result of the check. Specifically, the server compares the wall thickness (e.g., 10 cm) with the standard value (e.g., 12 cm) and determines whether it meets the criteria.

[0136] Step 5:

[0137] Generate and send legal check results

[0138] Based on the results of the legal check, the server generates a legal compliance matching result and sends it to the terminal in a format that the user can understand. The input is the matched information, and the output is a report of the generated matching result. Specifically, the server generates a message such as "The wall thickness does not meet the legal standards (current: 10 cm, required: 12 cm)" and sends it to the terminal.

[0139] Step 6:

[0140] Generate color and comfort advice

[0141] The server generates advice on color schemes and comfort based on the analysis results. The input is the analysis results, and the output is the generated advice. Specifically, the server detects that the color of the living room is too bright and generates the advice, "We recommend changing the color of the living room to a softer color (e.g., pastel green)."

[0142] Step 7:

[0143] Display and interaction on user devices

[0144] The terminal displays the matching results and advice received on the user interface. The user can check the displayed information and modify the drawing or 3D model as necessary. The input is the results and advice sent from the server, and the output is the displayed content and input from the user (modified drawing or model). Specifically, the terminal screen displays the areas that need to be modified and recommended advice, and the user modifies the drawing again based on this information and returns to step 1.

[0145] The above is the specific flow of the program processing of this system.

[0146] (Application example 1)

[0147] 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."

[0148] Currently, there are limited ways to efficiently check and provide advice on regulatory compliance, comfort, and color schemes in the interior design of autonomous vehicles. Designers must manually check regulations and repeatedly try and error interior designs. This results in significant time and cost involved in the design process. Furthermore, there is a lack of real-time feedback, which can delay design revisions.

[0149] 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.

[0150] In this invention, the server includes means for receiving drawings and 3D models, means for checking the received drawings and 3D models against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, means for displaying the generated advice, and means for displaying the legal check and the advice on comfort and color schemes on a 3D display device. This enables designers to receive checks and advice on legal compliance, comfort, and color schemes in real time in the interior design of autonomous vehicles through a 3D display device such as smart glasses, significantly improving the efficiency of the design process.

[0151] "Drawings and 3D models" means static or dynamic visual data used to represent the interior structure of a building or vehicle.

[0152] "Legal standard values" refer to specific numerical values ​​and standards set forth in laws, regulations, and standards related to construction and design.

[0153] The "matching result" is a report of the results of the evaluation of the received drawings or three-dimensional models based on the legal standards, and indicates whether or not they comply with the law.

[0154] "Advice on color schemes and comfort" refers to guidance and suggestions on whether the color scheme of a space is visually pleasing and whether the layout of furniture and interior décor ensures user comfort.

[0155] "Display means" refers to hardware and software for visually displaying analysis results and advice on a user interface.

[0156] A "three-dimensional display device" is a device that can display information in three-dimensional space, such as smart glasses or a head-mounted display.

[0157] The "server" is a computer system that analyzes drawings and three-dimensional models, checks legal compliance, generates matching results, and provides advice on color schemes and comfort.

[0158] This invention is a system that receives drawings and 3D models, performs analysis and legal checks, and generates advice on color schemes and comfort. Specifically, it uses a server, terminals, and a 3D display device to enable designers to efficiently check and improve the interior design of autonomous vehicles.

[0159] Program Overview

[0160] In this system, the server executes programs and processes various data. The programs are as follows:

[0161] 1. Receiving drawings and 3D models

[0162] The user uploads drawings or 3D models from their device, and the device sends this file data to the server.

[0163] 2. Analysis of drawings and 3D models

[0164] The server analyzes the received drawings and 3D models to extract structural information about walls, doors, etc. The results of the analysis are compared with legal standards to check whether each element complies with the regulations.

[0165] 3. Generate and send legal check results

[0166] The server generates a matching result based on the analysis results, clearly indicating which parts comply with the law and which parts do not. The matching result is sent to the terminal so that the user can check it.

[0167] 4. Providing advice on color and comfort

[0168] From the analysis results, the server generates color and comfort advice, including suggestions on the visual impact of colors and the comfort of furniture placement.

[0169] 5. Display on a 3D display device

[0170] The server sends the generated matching results and advice to a 3D display device, where the user can view the information in real time.The user can visually check the interior of the vehicle using smart glasses or a head-mounted display (e.g., Microsoft HoloLens or Google Glass).

[0171] Hardware and software used

[0172] Hardware

[0173] Device: PC or smartphone

[0174] 3D display devices: smart glasses, head-mounted displays

[0175] software

[0176] Server program: Python

[0177] Data transmission: REST API

[0178] 3D modeling software: Autodesk Revit, etc.

[0179] Specific examples

[0180] Example 1: Interior design check

[0181] After a designer finishes designing the interior of an autonomous vehicle, they upload the model file from their device to a server. The server analyzes the model and generates advice on compliance, comfort, and color schemes, which are then sent to the smart glasses. While wearing the smart glasses, the designer can visually confirm this information in real time while walking around the vehicle and make any necessary design changes.

[0182] Prompt Sentence Examples

[0183] To ensure that the interior design of an autonomous vehicle complies with regulations, please analyze the following models and provide advice on color schemes and comfort:

[0184] 1. / path / to / car_interior_model.obj

[0185] Check the thickness of the wall in accordance with regulations.

[0186] Rate the comfort of the seating arrangement.

[0187] Analyze the visual effects of room colors and recommend color schemes that reduce fatigue.

[0188] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0189] Specific processing steps of the program

[0190] Step 1:

[0191] The user uploads a drawing or 3D model from their device. To do this, the user uses a dedicated application to select the target drawing or 3D model file from a file dialog. Once the data is selected, the device generates a request to send it to the server. Input: Drawing or 3D model file. Output: A request is generated to send the file data to the server.

[0192] Step 2:

[0193] The server analyzes the received drawings and 3D models. When the server receives the files, it applies a specific analysis algorithm to extract structural information (walls, doors, etc.). Input: Uploaded drawings and 3D model files. Output: Extracted structural information.

[0194] Step 3:

[0195] The server compares the analyzed structural information with legal standards. Using a comparison algorithm, it evaluates whether each extracted element complies with the law. Input: Structural information, legal standard data. Output: Evaluation result of legal compliance.

[0196] Step 4:

[0197] The server generates a matching result report based on the evaluation results of the legal check. The report clearly shows which parts are compliant and which parts are not. Input: Legal compliance evaluation result. Output: Matching result report.

[0198] Step 5:

[0199] The server sends a matching result report to the terminal and the 3D display device, which visually presents this information to the user. Input: Matching result report. Output: Display data on the user interface and the 3D display device.

[0200] Step 6:

[0201] The server generates advice on color schemes and comfort based on the analysis results. It uses a generative AI model to provide detailed suggestions on visual impact and comfort. Input: Structural information, generative AI model. Output: Advice on color schemes and comfort.

[0202] Step 7:

[0203] The generated advice is sent from the server to the terminal and the 3D display device, which visually display the advice so that the user can check it in real time. Input: Advice on color scheme and comfort. Output: Display data on the user interface and the 3D display device.

[0204] Step 8:

[0205] The user wears smart glasses and receives real-time feedback through a 3D display, allowing for immediate corrections for compliance, comfort, and color scheme. Input: Feedback information from the 3D display. Output: Real-time design corrections.

[0206] 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.

[0207] The present invention relates to a system that receives blueprints and 3D models, analyzes them, checks them for legal compliance, and generates advice on color schemes and comfort, in addition to a system that combines an emotion engine that recognizes the user's emotions. Specific embodiments of the system are described below.

[0208] 1. Upload and analyze drawings

[0209] First, the user uploads a blueprint or 3D model from their device. The device generates a request to send the selected file to the server, and sends the file data to the server. The server analyzes the received blueprint or 3D model and extracts structural information such as walls and doors. At this time, the server checks whether each element complies with the standards set out in building regulations.

[0210] 2. Generate and send legal check results

[0211] The server generates a matching result based on the analysis results. For example, it checks whether the wall thickness is within legal limits, whether the door height is appropriate, etc. The matching result is generated in a way that clearly shows which parts comply with the law and which parts do not. The generated matching result is sent to the terminal so that the user can check it.

[0212] 3. Providing advice on color schemes and comfort

[0213] Based on the analysis results, the server generates advice on color schemes and comfort, including, for example, whether the room color is visually less tiring, whether the furniture arrangement is comfortable, etc. The generated advice is converted into a format for display to the user and sent to the terminal.

[0214] 4. Emotion Engine for Recognizing and Adapting to User Emotions

[0215] The system incorporates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice. The emotion engine analyzes the user's current emotional state (e.g., stress, joy, surprise, etc.). The recognized emotions are sent to the server, and advice and user interface display content are dynamically adjusted.

[0216] 5. User Presentation and Interaction

[0217] The device displays the received matching results and advice on the user interface. If the user feels emotionally stressed, the emotion engine recognizes this and the server adjusts the content presented to allow the user to use the system comfortably. For example, a user feeling stressed may be presented with advice displayed in softer colors or with positive feedback. If the user modifies the drawing or 3D model based on the confirmation and advice, the modified data is uploaded back to the server and rechecked using the same process.

[0218] Specific examples

[0219] Case 1: Wall thickness check and user emotion adaptation

[0220] The user uploads a blueprint file of a new building to the system from their device. The server receives the blueprint file and analyzes it. The analysis extracts the wall thickness. This is then compared with the legal standard, and a message is displayed to the user, such as, "The wall thickness exceeds the legal standard. Correction is required." If the emotion engine detects stress from the user's facial expression, the server displays additional positive feedback, such as, "Don't worry, it's easy to correct."

[0221] Case 2: Color Advice and Emotional Adaptation

[0222] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." If the emotion engine recognizes the user's emotion of happiness, the server adds a positive message, such as "This color scheme will make your room look even better."

[0223] The system of the present invention improves the experience during the proposal phase of a construction project by automatically checking regulatory standards and providing design advice, as well as recognizing and responding to user emotions, allowing users to efficiently and comfortably improve regulatory compliance and design.

[0224] The processing flow will be explained below.

[0225] Step 1:

[0226] A user selects a drawing file or a 3D model on a terminal and presses an upload button. The terminal generates a request to send the selected file to the server. The request includes the file data and associated metadata.

[0227] Step 2:

[0228] The device sends the request to the server using the HTTP protocol, etc. The server receives the request and saves the uploaded file in local storage.

[0229] Step 3:

[0230] The server analyzes the received drawing file or 3D model using algorithms that read the file and identify and extract structural elements such as walls, doors, windows, etc. The extracted information is stored in a database.

[0231] Step 4:

[0232] The server compares the extracted structural information with legal standards, for example, checking whether the wall thickness is within legal standards and whether the door height is appropriate. These standards are stored in a database in advance and are compared with the extracted information.

[0233] Step 5:

[0234] The server generates a matching result, which clearly shows which parts of the document comply with the law and which parts do not. For non-compliant parts, the result includes specific corrections and recommended changes.

[0235] Step 6:

[0236] The server converts the results of the matching process into a display format, such as HTML or JSON, and prepares the results for transmission to the device. The converted data is then organized in a format that is easy for the user to understand.

[0237] Step 7:

[0238] The server sends the converted matching results to the terminal, which processes the received data to display it on the user interface. The user checks the displayed matching results and determines whether any inconsistencies need to be corrected.

[0239] Step 8:

[0240] The server generates color and comfort advice based on the analyzed design data, creating advice on color balance, furniture placement, and more. This includes algorithms that suggest color schemes that reduce visual fatigue and placement advice to provide a comfortable user environment.

[0241] Step 9:

[0242] The server converts the generated advice into a presentation format, organizing it in a user-friendly way and converting it into HTML or JSON.

[0243] Step 10:

[0244] The server sends the converted advice to the terminal, which processes the received advice to display it on the user interface. The user can use the displayed advice to improve the design.

[0245] Step 11:

[0246] The emotion engine installed in the device analyzes the user's facial expressions and tone of voice to recognize emotions. For example, the device uses a camera or microphone to capture the user's facial expressions and voice data.

[0247] Step 12:

[0248] The emotion engine analyzes the emotion data and sends it to the server. For example, if the user is feeling stressed, that information is sent to the server.

[0249] Step 13:

[0250] The server adjusts the advice and feedback it provides to users based on the emotion data it receives. For example, if a user is feeling stressed, it might display advice in softer colors and provide positive feedback messages.

[0251] Step 14:

[0252] The device displays the adjusted advice and feedback in the user interface, allowing the user to review the displayed content and modify the drawing or 3D model as needed.

[0253] Step 15:

[0254] If the user modifies the drawing or 3D model, the modified data is uploaded to the server again, where it is rechecked through the same process and the user is provided with new matching results and advice.

[0255] In this way, the system of the present invention not only automatically checks legal standards and provides design advice, but also improves the user experience by recognizing and responding appropriately to user emotions.

[0256] Example 2

[0257] 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."

[0258] Modern construction projects require rapid verification of design and construction compliance. However, doing this manually takes a significant amount of time and requires experts to provide advice on design comfort and color schemes. Furthermore, advice is often provided without taking into account the user's emotional state, resulting in a poor user experience.

[0259] 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.

[0260] In this invention, the server includes means for receiving drawings and 3D models, means for analyzing the received drawings and 3D models, means for checking the analyzed information against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, means for displaying the generated advice on a user interface, means for recognizing a user's emotion using an emotion engine, and means for adjusting the display content based on the recognized emotion. This makes it possible to check legal compliance in construction projects, automatically provide advice on the comfort of designs and color schemes, and provide feedback adapted to the user's emotions.

[0261] "Drawings and 3D models" are digital or analog information that represents a building or design in two or three dimensions.

[0262] The "receiving means" refers to a method or device for obtaining data transmitted from a terminal via a network.

[0263] "Means for analysis" refers to the process or software that deciphers the content of the received data and extracts structural information and various attributes.

[0264] "Means for checking against legal standards" refers to algorithms or programs that compare analyzed information with the standards of existing laws and regulations to confirm compliance.

[0265] The "means for generating and displaying the matching results" is a mechanism for compiling the check results into a format that is easy for the user to understand and displaying them on a display or the like.

[0266] The "means for generating color and comfort advice" refers to an algorithm or AI model that uses the user's design data to create suggestions for more comfortable and visually appealing color schemes and placements.

[0267] "Means for displaying on a user interface" refers to a method for presenting the generated advice and check results through an interface that can be viewed and operated by the user.

[0268] An "emotion engine" is software or hardware that analyzes a user's emotions from their facial expressions, tone of voice, etc., and identifies their state.

[0269] The "means for recognizing user emotions" is a process of detecting the user's emotions using an emotion engine and obtaining the analysis results.

[0270] The "means for adjusting the display content based on the recognized emotion" refers to an algorithm or program that flexibly changes the advice provided and the display method according to the user's emotional state.

[0271] This invention is a system that receives drawings and three-dimensional models, analyzes them, checks them for legal requirements, and generates advice on color schemes and comfort, in addition to a system that combines an emotion engine that recognizes the user's emotions.

[0272] Hardware and software used

[0273] Device: A PC or smartphone is typically used, which includes the ability to upload files and a display to show the user interface.

[0274] Server: A central processing unit that analyzes data, checks laws and regulations, generates advice, and analyzes emotions. It is equipped with CAD software, specialized analysis algorithms, and an emotion engine.

[0275] Emotion engine: Software that uses a camera and microphone to collect and analyze the user's facial expressions and tone of voice.

[0276] Specific processing flow

[0277] 1. Upload drawings and 3D models

[0278] A user uses a terminal to select a file of architectural drawings or a 3D model and clicks the upload button. The terminal generates an HTTP request and sends the file data to the server.

[0279] 2. Analysis of drawings and 3D models

[0280] The server analyzes the received file data using CAD software and specialized analysis algorithms. As a result of the analysis, structural information such as walls and doors is extracted, and measurements between endpoints and physical attributes (thickness, height, etc.) are identified.

[0281] 3. Legal checks

[0282] The server compares the extracted structural information with the building code standards. For example, it checks whether the wall thickness meets the legal standards and whether the door height is appropriate. The results of the legal check are summarized and displayed in a user-friendly format.

[0283] 4. Generate color and comfort advice

[0284] Based on the analysis results, the server generates advice on room colors and furniture placement. For example, it generates advice such as, "The color of the living room is too bright, so we recommend changing it to a softer color," and displays it to the user.

[0285] 5. Recognition of user emotions by emotion engine

[0286] The emotion engine uses a camera and microphone to collect and analyze the user's facial expressions and tone of voice, and sends the analysis results to a server to identify the user's emotions.

[0287] 6. Providing advice and feedback to users

[0288] The server adjusts the content and display of advice based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adds positive feedback such as "Don't worry, it's easy to fix." The information received by the device is displayed in the user interface.

[0289] Specific examples

[0290] Case 1: Wall thickness check and user emotion adaptation

[0291] The user uploads a blueprint file for a new building to the system from their device. The server receives the blueprint file and analyzes it. The analysis extracts the wall thickness. The result is compared with the legal standard value, and a message is displayed saying, "The wall thickness exceeds the legal standard. Corrections are required." If the emotion engine senses stress from the user's facial expression, the server adds positive feedback such as, "Don't worry, it's easy to correct."

[0292] Example prompt sentence:

[0293] Upload a new building drawing file into the system and receive a report with analysis results, including code checks on wall thickness, and feedback based on user sentiment.

[0294] Case 2: Color Advice and Emotional Adaptation

[0295] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. It generates color advice, such as "The colors in the living room are too bright, so we recommend changing them to softer colors." If the emotion engine recognizes the user's happy emotion, the server adds a positive message, such as "This color scheme will make your room look even better."

[0296] Example prompt sentence:

[0297] Upload a new room interior design model to the system, and receive analysis results that suggest color schemes for the room and provide feedback based on the user's emotions.

[0298] The system of the present invention is designed to support users in verifying compliance with regulations and improving the design of their construction projects efficiently and comfortably, and can enhance the user experience by responding flexibly to the user's emotional state.

[0299] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0300] Step 1: Upload your drawings or 3D models

[0301] Input: The user selects architectural drawings or 3D models from the terminal's file selection interface.

[0302] Process: The user clicks the "Upload" button. The device sends the selected file to the server as an HTTP request.

[0303] Output: The file sent from the terminal arrives at the server.

[0304] Step 2: Analyze drawings and 3D models

[0305] Input: Files of architectural drawings and 3D models received by the server from the terminal.

[0306] Processing: The server uses CAD software or specialized analysis algorithms to analyze the received file. The file data is parsed to extract structural information such as walls and doors. End-to-end measurements and physical attributes (thickness, height, etc.) are identified.

[0307] Output: Structural information based on the analysis is obtained.

[0308] Step 3: Conduct a legal check

[0309] Input: Structural information extracted by the server.

[0310] Processing: The server checks the extracted structural information against building code standards, for example, checking whether the wall thickness meets the code standards and whether the door height is appropriate.

[0311] Output: The compliance check results are generated, clearly indicating compliance and non-compliance.

[0312] Step 4: Generate color and comfort advice

[0313] Input: Room structural information and color data analyzed by the server.

[0314] Processing: Based on the analysis results, the server generates advice on the color scheme and furniture placement in the room. For example, it generates advice such as, "The color in the living room is too bright, so we recommend changing it to a softer color."

[0315] Output: Color and comfort advice is generated.

[0316] Step 5: Recognizing user emotions with the emotion engine

[0317] Input: Camera and microphone data to collect the user's facial expressions and tone of voice.

[0318] Processing: The emotion engine uses the camera and microphone to collect and analyze the user's facial expressions and tone of voice, which in turn identifies the user's emotional state (e.g., stress, joy, surprise, etc.).

[0319] Output: An analysis result about the user's emotional state is generated.

[0320] Step 6: Advise the user and provide feedback

[0321] Input: Server-generated legal check results, color and comfort advice, and the user's emotional state via the emotion engine.

[0322] Processing: The server adjusts the displayed advice based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adds positive feedback such as "Don't worry, it's easy to fix." The device then displays the adjusted check results and advice on the user interface.

[0323] Output: The adjusted legal check results and advice are displayed on the user interface.

[0324] Step 7: User corrections and recheck

[0325] Input: Drawings and 3D model data that users modify based on the advice and feedback provided.

[0326] Processing: The user modifies the drawing or model according to the provided advice. Once the modifications are complete, the file is uploaded back to the server, where it is analyzed and checked for legal compliance again.

[0327] Output: New regulatory check results and advice are generated based on the revised drawings and 3D models.

[0328] (Application example 2)

[0329] 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."

[0330] Conventional autonomous vehicles lack a system that can adjust in real time the impact of factors such as interior layout and color scheme on the comfort of the driver and passengers. Furthermore, there is a lack of means to improve comfort by providing feedback or advice based on the user's emotions while in the vehicle. This can easily lead to stressful situations for the user, resulting in a lower quality driving experience. Therefore, the present invention aims to solve these problems and provide a new system that can adapt to the user's emotions while maintaining a more comfortable environment inside an autonomous vehicle.

[0331] 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.

[0332] In this invention, the server includes means for receiving drawings and 3D models, means for checking the received drawings and 3D models against legal standards, means for generating and displaying the comparison results, means for generating advice regarding color schemes and comfort, means for displaying the generated advice, means including an emotion engine for recognizing the user's emotions, and means for dynamically adjusting the advice and display content based on the user's emotional state. This makes it possible to maintain a comfortable environment inside an autonomous vehicle in real time, reduce stress felt by the user, and provide a better driving experience.

[0333] "Drawings and 3D models" are digital data representing architectural or spatial design drawings and three-dimensional shapes that users provide to the system.

[0334] "Means for receiving" refers to devices and software that have the function of receiving data such as drawings and three-dimensional models uploaded by users.

[0335] "Means for checking" refers to equipment and software that compares received drawings and 3D models with existing standards and regulations to check for compliance.

[0336] "Means for generating and displaying" refers to devices and software that create information based on analysis results and advice and visually present it to users.

[0337] The "means for generating color and comfort advice" refers to devices and software that generate recommendations to users regarding the color and layout of a space based on the results of analysis of drawings and three-dimensional models.

[0338] An "emotion engine" is a device and software that identifies emotions from a user's facial expressions, voice, etc. and analyzes the data.

[0339] "Dynamic adjusting means" refers to devices and software for changing in real time the content and manner of advice or information presented based on the user's emotional state.

[0340] "Real-time" refers to data processing and information being provided immediately when a user uses the system.

[0341] An "autonomous vehicle" is a vehicle that is driven automatically by a system without the need for driver operation.

[0342] The present invention relates to a system that maintains a comfortable environment inside an autonomous vehicle while adapting based on the emotional state of the user. Specific embodiments of the system are described below.

[0343] 1. Receiving drawings and 3D models

[0344] The server receives images and 3D models of the interior of the autonomous vehicle in real time via smart glasses or a head-mounted display (HMD), which allows it to collect data on the interior layout and color scheme.

[0345] 2. Data analysis and legal checks

[0346] The server analyzes the received images and models to extract interior data for the vehicle. It uses the open-source libraries OpenCV and dlib for image analysis, and the DesignAnalysis library to analyze spatial layout and color data. The analysis results are compared with pre-set legal standards.

[0347] 3. Providing advice on color schemes and comfort

[0348] The server generates advice on color schemes and comfort based on the analysis results. For example, if the lighting is too bright, the server may provide advice such as "We recommend dimming the lights a little." If the seat position is inappropriate, the server may provide advice such as "We recommend moving your seat forward a little."

[0349] 4. Recognition of user emotions using an emotion engine

[0350] The server uses sensors built into the smart glasses or HMD to recognize emotions from the user's facial expressions and tone of voice. The EmotionRecognition library is used for this emotion recognition. The recognized emotion data is sent to the server for analysis.

[0351] 5. Emotional Adaptation

[0352] The server adjusts the generated advice and display content based on the user's emotional data. For example, it provides suggestions for stress reduction to a user who is feeling stressed, and includes positive feedback to a user who is feeling happy. This allows the user to continue driving in a comfortable state.

[0353] 6. Presenting the results to the user

[0354] The device displays the generated advice and tailored feedback in real time via smart glasses or an HMD, allowing the user to review the displayed content and implement the system's suggestions as needed.

[0355] Specific examples

[0356] Example 1: Adjusting the lighting

[0357] If the user feels that the lighting in the autonomous vehicle is too bright, the server generates and displays advice such as "We recommend that you dim the lights a little." If the user feels stressed, the server provides additional feedback such as "Dim the lights to relax."

[0358] Example 2: Seating arrangement

[0359] If the user is dissatisfied with the seating position in the car, the server will provide advice such as "If you move your seat a little forward, you will have more leg room." If the emotion engine recognizes the user's joy, the server will add a positive message such as "This positioning will make you even more comfortable."

[0360] Prompt Sentence Examples

[0361] "If I feel the colors in my car are too bright, can you suggest how I should change the settings?"

[0362] "How can I optimize my seat position to increase legroom?"

[0363] This enables the system to maintain a comfortable environment inside the autonomous vehicle while providing appropriate advice and feedback in real time based on the user's emotions.

[0364] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0365] Step 1:

[0366] The smart glasses or HMD captures images of the interior of the vehicle and sends the data to a server. The input is the image data captured by the smart glasses or HMD, and the output is the image data sent to the server. This image data includes the layout and color scheme of the interior of the vehicle.

[0367] Step 2:

[0368] The server analyzes the received image data. The OpenCV and dlib libraries are used for the analysis. Specifically, the necessary interior structural information is extracted from the image and color scheme data is identified. The input is the received image data, and the output is the analysis results.

[0369] Step 3:

[0370] The server uses the DesignAnalysis library to compare the extracted structural information with the legal standards. The comparison results clearly show which parts comply with the law and which do not. The input is the analysis result obtained in step 2, and the output is the result of the legal check.

[0371] Step 4:

[0372] The server generates color and comfort advice. A generative AI model is used to create recommendations based on interior color and layout. The input is the results of legal checks and analysis, and the output is specific advice.

[0373] Step 5:

[0374] The server uses the emotion engine to analyze the user's facial expressions and tone of voice received from the smart glasses or HMD and recognize the user's emotions. The input is the user's facial expression data and tone of voice data, and the output is the emotion recognition result.

[0375] Step 6:

[0376] The server dynamically adjusts the generated advice and display content based on the user's emotion recognition results. For example, it adds a recommendation to relax to a user who is feeling stressed, while adding positive feedback to a user who is feeling happy. The input is the emotion recognition results and the generated advice, and the output is the adjusted advice or notification.

[0377] Step 7:

[0378] The device displays tailored advice and notifications to the user in real time through smart glasses or an HMD. The user reviews the displayed information and implements the system's suggestions as needed. The input is the tailored advice and notifications, and the output is a visual presentation to the user.

[0379] Through these processing steps, the system can provide appropriate advice and feedback according to the user's emotions while maintaining a comfortable environment inside the autonomous vehicle.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] [Second embodiment]

[0384] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0385] 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.

[0386] 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).

[0387] 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.

[0388] 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.

[0389] 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).

[0390] 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.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] 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.

[0395] 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."

[0396] The present invention relates to a system that receives drawings and 3D models, analyzes them, checks them for legal regulations, and generates advice on color schemes and comfort. Specific embodiments of the system are described below.

[0397] 1. Upload and analyze drawings

[0398] First, the user uploads a blueprint or 3D model from their device. The device generates a request to send the selected file to the server, and sends the file data to the server. The server analyzes the received blueprint or 3D model and extracts structural information such as walls and doors. At this time, the server checks whether each element complies with the standards set out in building regulations.

[0399] 2. Generate and send legal check results

[0400] The server generates a matching result based on the analysis results. For example, it checks whether the wall thickness is within legal limits, whether the door height is appropriate, etc. The matching result is generated in a way that clearly shows which parts comply with the law and which parts do not. The generated matching result is sent to the terminal so that the user can check it.

[0401] 3. Providing advice on color schemes and comfort

[0402] Based on the analysis results, the server generates advice on color schemes and comfort, including, for example, whether the room color is visually less tiring, whether the furniture arrangement is comfortable, etc. The generated advice is converted into a format for display to the user and sent to the terminal.

[0403] 4. User Presentation and Interaction

[0404] The terminal displays the received matching results and advice on the user interface. The user can review them and modify the drawings or 3D models as necessary. The modified drawings or 3D models are then uploaded back to the server, where they undergo the same process of checking and receiving advice.

[0405] Specific examples

[0406] A specific scenario is shown below.

[0407] Case 1: Wall Thickness Check

[0408] The user uploads a drawing file of a new building from their terminal to the system. The server receives the drawing file and performs an analysis. The analysis extracts the wall thickness. This is then compared with the legal standard, and the user is shown a message saying, "The wall thickness exceeds the legal standard. Corrections are required." The user can correct the wall thickness and upload it again to have it checked again.

[0409] Case 2: Color Advice

[0410] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color-scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." The user then adjusts the color scheme of the design accordingly.

[0411] The system of the present invention significantly reduces the time and cost involved in the proposal phase of a construction project by automatically checking regulatory standards and providing design advice, allowing users to efficiently improve regulatory compliance and design.

[0412] The processing flow will be explained below.

[0413] Step 1:

[0414] A user selects a drawing file or a 3D model on a terminal and presses an upload button. The terminal generates a request to send the selected file to the server. The request includes the file data and associated metadata.

[0415] Step 2:

[0416] The device sends the request to the server using the HTTP protocol, etc. The server receives the request and saves the uploaded file in local storage.

[0417] Step 3:

[0418] The server analyzes the received drawing file or 3D model using algorithms that read the file and identify and extract structural elements such as walls, doors, windows, etc. The extracted information is stored in a database.

[0419] Step 4:

[0420] The server compares the extracted structural information with legal standards, for example, checking whether the wall thickness is within legal standards and whether the door height is appropriate. These standards are stored in a database in advance and are compared with the extracted information.

[0421] Step 5:

[0422] The server generates a matching result, which clearly shows which parts of the document comply with the law and which parts do not. For non-compliant parts, the result includes specific corrections and recommended changes.

[0423] Step 6:

[0424] The server converts the results of the matching process into a display format, such as HTML or JSON, and prepares the results for transmission to the device. The converted data is then organized in a format that is easy for the user to understand.

[0425] Step 7:

[0426] The server sends the converted matching results to the terminal, which processes the received data to display it on the user interface. The user checks the displayed matching results and determines whether any inconsistencies need to be corrected.

[0427] Step 8:

[0428] The server generates color and comfort advice based on the analyzed design data, creating advice on color balance, furniture placement, and more. This includes algorithms that suggest color schemes that reduce visual fatigue and placement advice to provide a comfortable user environment.

[0429] Step 9:

[0430] The server converts the generated advice into a presentation format, organizing it in a user-friendly way and converting it into HTML or JSON.

[0431] Step 10:

[0432] The server sends the converted advice to the terminal, which processes the received advice to display it on the user interface. The user can use the displayed advice to improve the design.

[0433] Example 1

[0434] 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."

[0435] In architectural projects, it is important to efficiently check the legal compliance of drawings and 3D models and provide advice on the comfort of the design. However, manual checks and advice are time-consuming and costly. Furthermore, because specialized knowledge is required, it is often difficult to provide appropriate advice. The present invention aims to solve these problems and provide a system that automatically and efficiently checks legal compliance and provides advice on comfort.

[0436] 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.

[0437] In this invention, the server includes means for receiving drawings and 3D models, means for analyzing the received drawings and 3D models to extract structures such as walls and doors, means for checking the extracted structures against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, and means for displaying the generated advice. This automates the process of checking legal compliance and improving designs in architectural projects, reducing time and costs, and making it possible to obtain appropriate advice even without specialized knowledge.

[0438] "Drawings and three-dimensional models" refer to floor plans and three-dimensional drawings, as well as the digital data thereof, that represent the structure and layout of a building or design object.

[0439] "Means for receiving" refers to a mechanism or method for importing drawing or three-dimensional model data from a user into the server.

[0440] "Means of analysis" refers to the mechanisms and software used to process received drawings and three-dimensional model data and extract structural information such as walls and doors.

[0441] The "means for extraction" is a function for extracting and identifying specific elements (e.g., walls, doors, etc.) from the analyzed data.

[0442] The "means of matching" is a method for comparing the extracted structural information with legally defined standards to confirm the degree of agreement.

[0443] The "means of checking" is a system for evaluating the compliance of each element of a building based on legal standards.

[0444] "Means for generating" refers to the process for creating information and advice to be provided to the user based on the results of analysis and collation.

[0445] The "display means" refers to a device or interface for visually conveying the generated matching results and advice to the user.

[0446] "Color and comfort advice" means suggestions and instructions for improving the visual and functional comfort of a room's color and furniture arrangement.

[0447] A "user interface" is a screen or operating means through which a user interacts with a system and inputs and outputs information.

[0448] The "means for receiving again" refers to a mechanism or method for importing the data of drawings or three-dimensional models that have been modified into the server again.

[0449] "Means for rechecking" refers to the process of comparing revised drawings and three-dimensional models with the legal standards again to confirm compliance.

[0450] This invention relates to a system that automatically analyzes and evaluates compliance with regulations and design comfort using architectural drawings and 3D models, and provides the results to users. This system is composed of three entities: a server, a terminal, and a user. The overall system configuration and the role played by each entity are explained in detail below.

[0451] Hardware and Software Configuration

[0452] 1. Receiving drawings and 3D models

[0453] The user selects drawings or 3D models from the terminal and sends them to the server.

[0454] The terminal uploads the file selected by the user to the server using a protocol such as an HTTP request.

[0455] The server stores the received drawings and 3D models in storage (e.g., a disk drive or cloud storage).

[0456] 2. Analysis of drawings and 3D models

[0457] The server analyzes the stored data, for example, using AutoCAD API or BIM (Building Information Modeling) software.

[0458] An algorithm has been implemented to extract structural information such as walls and doors from the received data.

[0459] 3. Legal checks

[0460] The server checks the extracted structural information against the standard values ​​set by building regulations.

[0461] The check uses certain criteria (e.g. wall thickness, door height) and a matching algorithm evaluates whether the criteria are met.

[0462] 4. Generate and send legal check results

[0463] Based on the check results, the server generates a matching result that clearly indicates which parts comply with the law and which parts do not.

[0464] The generated matching results are converted into a user-viewable format (e.g., text report or graphical report) and sent to the terminal.

[0465] 5. Generate color and comfort advice

[0466] Based on the analysis results, the server generates advice on color schemes and comfort.

[0467] Advice can come in the form of, for example, a visual comfort rating or suggestions for furniture placement.

[0468] 6. Display and interaction on user devices

[0469] The terminal displays the received collation results and advice on a user interface.

[0470] The user can use this information to modify the drawings or 3D models and send them back to the server.

[0471] Specific examples

[0472] Case 1: Wall Thickness Check

[0473] A user uploads a drawing file of a new building to the system from their terminal. The server receives the drawing file and performs an analysis. The analysis extracts the wall thickness. This is then compared with the legal standard, and the user is shown a message such as, "The wall thickness does not meet the legal standard (current: 10cm, required: 12cm)." The user can then correct the wall thickness and upload it again to have it checked again.

[0474] Case 2: Color Advice

[0475] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color-scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." The user then adjusts the color scheme of the design accordingly.

[0476] Prompt Sentence Examples

[0477] "Please develop a system that analyzes the drawings of a new building and checks whether the wall thickness complies with regulations. Please also explain the specific check items and how to display the check results."

[0478] "Create a system that allows users to upload a room design model and provides color advice based on visual comfort. Explain how you would analyze the model and how you would provide the advice."

[0479] As described above, the present invention makes it possible to efficiently provide advice on legal compliance and design during the proposal phase of a construction project, thereby reducing time and costs.

[0480] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0481] Step 1:

[0482] Upload drawings and 3D models

[0483] The user uses the terminal to select a drawing or 3D model file and perform the upload operation. The terminal sends the selected file to the server via an HTTP request. The input is the drawing or model file selected by the user, and the output is the file being sent to the server. Specifically, the user presses the "Select File" button, selects a file (e.g., building_plan.dwg) from local storage, and clicks the "Upload" button.

[0484] Step 2:

[0485] Receiving and storing drawings and 3D models

[0486] The server receives the file sent from the terminal and saves the data in storage. The input is the file data sent from the terminal, and the output is the file saved in storage. Specifically, the server receives the HTTP request and saves the file in the specified directory. For example, the save location is / uploads / building_plan.dwg.

[0487] Step 3:

[0488] Analysis of drawings and 3D models

[0489] The server analyzes the saved files and extracts structural information such as walls and doors. This analysis uses AutoCAD API and BIM software. The input is the saved file, and the output is the extracted structural information. Specifically, the server calls the AutoCAD API and analyzes and extracts the location of walls, doors, etc. from the file.

[0490] Step 4:

[0491] Legal checks

[0492] The server checks the extracted structural information against the standard values ​​set by building regulations. Examples of criteria for checking include "wall thickness" and "door height." The input is the extracted structural information, and the output is the result of the check. Specifically, the server compares the wall thickness (e.g., 10 cm) with the standard value (e.g., 12 cm) and determines whether it meets the criteria.

[0493] Step 5:

[0494] Generate and send legal check results

[0495] Based on the results of the legal check, the server generates a legal compliance matching result and sends it to the terminal in a format that the user can understand. The input is the matched information, and the output is a report of the generated matching result. Specifically, the server generates a message such as "The wall thickness does not meet the legal standards (current: 10 cm, required: 12 cm)" and sends it to the terminal.

[0496] Step 6:

[0497] Generate color and comfort advice

[0498] The server generates advice on color schemes and comfort based on the analysis results. The input is the analysis results, and the output is the generated advice. Specifically, the server detects that the color of the living room is too bright and generates the advice, "We recommend changing the color of the living room to a softer color (e.g., pastel green)."

[0499] Step 7:

[0500] Display and interaction on user devices

[0501] The terminal displays the matching results and advice received on the user interface. The user can check the displayed information and modify the drawing or 3D model as necessary. The input is the results and advice sent from the server, and the output is the displayed content and input from the user (modified drawing or model). Specifically, the terminal screen displays the areas that need to be modified and recommended advice, and the user modifies the drawing again based on this information and returns to step 1.

[0502] The above is the specific flow of the program processing of this system.

[0503] (Application example 1)

[0504] 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."

[0505] Currently, there are limited ways to efficiently check and provide advice on regulatory compliance, comfort, and color schemes in the interior design of autonomous vehicles. Designers must manually check regulations and repeatedly try and error interior designs. This results in significant time and cost involved in the design process. Furthermore, there is a lack of real-time feedback, which can delay design revisions.

[0506] 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.

[0507] In this invention, the server includes means for receiving drawings and 3D models, means for checking the received drawings and 3D models against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, means for displaying the generated advice, and means for displaying the legal check and the advice on comfort and color schemes on a 3D display device. This enables designers to receive checks and advice on legal compliance, comfort, and color schemes in real time in the interior design of autonomous vehicles through a 3D display device such as smart glasses, significantly improving the efficiency of the design process.

[0508] "Drawings and 3D models" means static or dynamic visual data used to represent the interior structure of a building or vehicle.

[0509] "Legal standard values" refer to specific numerical values ​​and standards set forth in laws, regulations, and standards related to construction and design.

[0510] The "matching result" is a report of the results of the evaluation of the received drawings or three-dimensional models based on the legal standards, and indicates whether or not they comply with the law.

[0511] "Advice on color schemes and comfort" refers to guidance and suggestions on whether the color scheme of a space is visually pleasing and whether the layout of furniture and interior décor ensures user comfort.

[0512] "Display means" refers to hardware and software for visually displaying analysis results and advice on a user interface.

[0513] A "three-dimensional display device" is a device that can display information in three-dimensional space, such as smart glasses or a head-mounted display.

[0514] The "server" is a computer system that analyzes drawings and three-dimensional models, checks legal compliance, generates matching results, and provides advice on color schemes and comfort.

[0515] This invention is a system that receives drawings and 3D models, performs analysis and legal checks, and generates advice on color schemes and comfort. Specifically, it uses a server, terminals, and a 3D display device to enable designers to efficiently check and improve the interior design of autonomous vehicles.

[0516] Program Overview

[0517] In this system, the server executes programs and processes various data. The programs are as follows:

[0518] 1. Receiving drawings and 3D models

[0519] The user uploads drawings or 3D models from their device, and the device sends this file data to the server.

[0520] 2. Analysis of drawings and 3D models

[0521] The server analyzes the received drawings and 3D models to extract structural information about walls, doors, etc. The results of the analysis are compared with legal standards to check whether each element complies with the regulations.

[0522] 3. Generate and send legal check results

[0523] The server generates a matching result based on the analysis results, clearly indicating which parts comply with the law and which parts do not. The matching result is sent to the terminal so that the user can check it.

[0524] 4. Providing advice on color and comfort

[0525] From the analysis results, the server generates color and comfort advice, including suggestions on the visual impact of colors and the comfort of furniture placement.

[0526] 5. Display on a 3D display device

[0527] The server sends the generated matching results and advice to a 3D display device, where the user can view the information in real time.The user can visually check the interior of the vehicle using smart glasses or a head-mounted display (e.g., Microsoft HoloLens or Google Glass).

[0528] Hardware and software used

[0529] Hardware

[0530] Device: PC or smartphone

[0531] 3D display devices: smart glasses, head-mounted displays

[0532] software

[0533] Server program: Python

[0534] Data transmission: REST API

[0535] 3D modeling software: Autodesk Revit, etc.

[0536] Specific examples

[0537] Example 1: Interior design check

[0538] After a designer finishes designing the interior of an autonomous vehicle, they upload the model file from their device to a server. The server analyzes the model and generates advice on compliance, comfort, and color schemes, which are then sent to the smart glasses. While wearing the smart glasses, the designer can visually confirm this information in real time while walking around the vehicle and make any necessary design changes.

[0539] Prompt Sentence Examples

[0540] To ensure that the interior design of an autonomous vehicle complies with regulations, please analyze the following models and provide advice on color schemes and comfort:

[0541] 1. / path / to / car_interior_model.obj

[0542] Check the thickness of the wall in accordance with regulations.

[0543] Rate the comfort of the seating arrangement.

[0544] Analyze the visual effects of room colors and recommend color schemes that reduce fatigue.

[0545] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0546] Specific processing steps of the program

[0547] Step 1:

[0548] The user uploads a drawing or 3D model from their device. To do this, the user uses a dedicated application to select the target drawing or 3D model file from a file dialog. Once the data is selected, the device generates a request to send it to the server. Input: Drawing or 3D model file. Output: A request is generated to send the file data to the server.

[0549] Step 2:

[0550] The server analyzes the received drawings and 3D models. When the server receives the files, it applies a specific analysis algorithm to extract structural information (walls, doors, etc.). Input: Uploaded drawings and 3D model files. Output: Extracted structural information.

[0551] Step 3:

[0552] The server compares the analyzed structural information with legal standards. Using a comparison algorithm, it evaluates whether each extracted element complies with the law. Input: Structural information, legal standard data. Output: Evaluation result of legal compliance.

[0553] Step 4:

[0554] The server generates a matching result report based on the evaluation results of the legal check. The report clearly shows which parts are compliant and which parts are not. Input: Legal compliance evaluation result. Output: Matching result report.

[0555] Step 5:

[0556] The server sends a matching result report to the terminal and the 3D display device, which visually presents this information to the user. Input: Matching result report. Output: Display data on the user interface and the 3D display device.

[0557] Step 6:

[0558] The server generates advice on color schemes and comfort based on the analysis results. It uses a generative AI model to provide detailed suggestions on visual impact and comfort. Input: Structural information, generative AI model. Output: Advice on color schemes and comfort.

[0559] Step 7:

[0560] The generated advice is sent from the server to the terminal and the 3D display device, which visually display the advice so that the user can check it in real time. Input: Advice on color scheme and comfort. Output: Display data on the user interface and the 3D display device.

[0561] Step 8:

[0562] The user wears smart glasses and receives real-time feedback through a 3D display, allowing for immediate corrections for compliance, comfort, and color scheme. Input: Feedback information from the 3D display. Output: Real-time design corrections.

[0563] 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.

[0564] The present invention relates to a system that receives blueprints and 3D models, analyzes them, checks them for legal compliance, and generates advice on color schemes and comfort, in addition to a system that combines an emotion engine that recognizes the user's emotions. Specific embodiments of the system are described below.

[0565] 1. Upload and analyze drawings

[0566] First, the user uploads a blueprint or 3D model from their device. The device generates a request to send the selected file to the server, and sends the file data to the server. The server analyzes the received blueprint or 3D model and extracts structural information such as walls and doors. At this time, the server checks whether each element complies with the standards set out in building regulations.

[0567] 2. Generate and send legal check results

[0568] The server generates a matching result based on the analysis results. For example, it checks whether the wall thickness is within legal limits, whether the door height is appropriate, etc. The matching result is generated in a way that clearly shows which parts comply with the law and which parts do not. The generated matching result is sent to the terminal so that the user can check it.

[0569] 3. Providing advice on color schemes and comfort

[0570] Based on the analysis results, the server generates advice on color schemes and comfort, including, for example, whether the room color is visually less tiring, whether the furniture arrangement is comfortable, etc. The generated advice is converted into a format for display to the user and sent to the terminal.

[0571] 4. Emotion Engine for Recognizing and Adapting to User Emotions

[0572] The system incorporates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice. The emotion engine analyzes the user's current emotional state (e.g., stress, joy, surprise, etc.). The recognized emotions are sent to the server, and advice and user interface display content are dynamically adjusted.

[0573] 5. User Presentation and Interaction

[0574] The device displays the received matching results and advice on the user interface. If the user feels emotionally stressed, the emotion engine recognizes this and the server adjusts the content presented to allow the user to use the system comfortably. For example, a user feeling stressed may be presented with advice displayed in softer colors or with positive feedback. If the user modifies the drawing or 3D model based on the confirmation and advice, the modified data is uploaded back to the server and rechecked using the same process.

[0575] Specific examples

[0576] Case 1: Wall thickness check and user emotion adaptation

[0577] The user uploads a blueprint file of a new building to the system from their device. The server receives the blueprint file and analyzes it. The analysis extracts the wall thickness. This is then compared with the legal standard, and a message is displayed to the user, such as, "The wall thickness exceeds the legal standard. Correction is required." If the emotion engine detects stress from the user's facial expression, the server displays additional positive feedback, such as, "Don't worry, it's easy to correct."

[0578] Case 2: Color Advice and Emotional Adaptation

[0579] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." If the emotion engine recognizes the user's emotion of happiness, the server adds a positive message, such as "This color scheme will make your room look even better."

[0580] The system of the present invention improves the experience during the proposal phase of a construction project by automatically checking regulatory standards and providing design advice, as well as recognizing and responding to user emotions, allowing users to efficiently and comfortably improve regulatory compliance and design.

[0581] The processing flow will be explained below.

[0582] Step 1:

[0583] A user selects a drawing file or a 3D model on a terminal and presses an upload button. The terminal generates a request to send the selected file to the server. The request includes the file data and associated metadata.

[0584] Step 2:

[0585] The device sends the request to the server using the HTTP protocol, etc. The server receives the request and saves the uploaded file in local storage.

[0586] Step 3:

[0587] The server analyzes the received drawing file or 3D model using algorithms that read the file and identify and extract structural elements such as walls, doors, windows, etc. The extracted information is stored in a database.

[0588] Step 4:

[0589] The server compares the extracted structural information with legal standards, for example, checking whether the wall thickness is within legal standards and whether the door height is appropriate. These standards are stored in a database in advance and are compared with the extracted information.

[0590] Step 5:

[0591] The server generates a matching result, which clearly shows which parts of the document comply with the law and which parts do not. For non-compliant parts, the result includes specific corrections and recommended changes.

[0592] Step 6:

[0593] The server converts the results of the matching process into a display format, such as HTML or JSON, and prepares the results for transmission to the device. The converted data is then organized in a format that is easy for the user to understand.

[0594] Step 7:

[0595] The server sends the converted matching results to the terminal, which processes the received data to display it on the user interface. The user checks the displayed matching results and determines whether any inconsistencies need to be corrected.

[0596] Step 8:

[0597] The server generates color and comfort advice based on the analyzed design data, creating advice on color balance, furniture placement, and more. This includes algorithms that suggest color schemes that reduce visual fatigue and placement advice to provide a comfortable user environment.

[0598] Step 9:

[0599] The server converts the generated advice into a presentation format, organizing it in a user-friendly way and converting it into HTML or JSON.

[0600] Step 10:

[0601] The server sends the converted advice to the terminal, which processes the received advice to display it on the user interface. The user can use the displayed advice to improve the design.

[0602] Step 11:

[0603] The emotion engine installed in the device analyzes the user's facial expressions and tone of voice to recognize emotions. For example, the device uses a camera or microphone to capture the user's facial expressions and voice data.

[0604] Step 12:

[0605] The emotion engine analyzes the emotion data and sends it to the server. For example, if the user is feeling stressed, that information is sent to the server.

[0606] Step 13:

[0607] The server adjusts the advice and feedback it provides to users based on the emotion data it receives. For example, if a user is feeling stressed, it might display advice in softer colors and provide positive feedback messages.

[0608] Step 14:

[0609] The device displays the adjusted advice and feedback in the user interface, allowing the user to review the displayed content and modify the drawing or 3D model as needed.

[0610] Step 15:

[0611] If the user modifies the drawing or 3D model, the modified data is uploaded to the server again, where it is rechecked through the same process and the user is provided with new matching results and advice.

[0612] In this way, the system of the present invention not only automatically checks legal standards and provides design advice, but also improves the user experience by recognizing and responding appropriately to user emotions.

[0613] Example 2

[0614] 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."

[0615] Modern construction projects require rapid verification of design and construction compliance. However, doing this manually takes a significant amount of time and requires experts to provide advice on design comfort and color schemes. Furthermore, advice is often provided without taking into account the user's emotional state, resulting in a poor user experience.

[0616] 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.

[0617] In this invention, the server includes means for receiving drawings and 3D models, means for analyzing the received drawings and 3D models, means for checking the analyzed information against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, means for displaying the generated advice on a user interface, means for recognizing a user's emotion using an emotion engine, and means for adjusting the display content based on the recognized emotion. This makes it possible to check legal compliance in construction projects, automatically provide advice on the comfort of designs and color schemes, and provide feedback adapted to the user's emotions.

[0618] "Drawings and 3D models" are digital or analog information that represents a building or design in two or three dimensions.

[0619] The "receiving means" refers to a method or device for obtaining data transmitted from a terminal via a network.

[0620] "Means for analysis" refers to the process or software that deciphers the content of the received data and extracts structural information and various attributes.

[0621] "Means for checking against legal standards" refers to algorithms or programs that compare analyzed information with the standards of existing laws and regulations to confirm compliance.

[0622] The "means for generating and displaying the matching results" is a mechanism for compiling the check results into a format that is easy for the user to understand and displaying them on a display or the like.

[0623] The "means for generating color and comfort advice" refers to an algorithm or AI model that uses the user's design data to create suggestions for more comfortable and visually appealing color schemes and placements.

[0624] "Means for displaying on a user interface" refers to a method for presenting the generated advice and check results through an interface that can be viewed and operated by the user.

[0625] An "emotion engine" is software or hardware that analyzes a user's emotions from their facial expressions, tone of voice, etc., and identifies their state.

[0626] The "means for recognizing user emotions" is a process of detecting the user's emotions using an emotion engine and obtaining the analysis results.

[0627] The "means for adjusting the display content based on the recognized emotion" refers to an algorithm or program that flexibly changes the advice provided and the display method according to the user's emotional state.

[0628] This invention is a system that receives drawings and three-dimensional models, analyzes them, checks them for legal requirements, and generates advice on color schemes and comfort, in addition to a system that combines an emotion engine that recognizes the user's emotions.

[0629] Hardware and software used

[0630] Device: A PC or smartphone is typically used, which includes the ability to upload files and a display to show the user interface.

[0631] Server: A central processing unit that analyzes data, checks laws and regulations, generates advice, and analyzes emotions. It is equipped with CAD software, specialized analysis algorithms, and an emotion engine.

[0632] Emotion engine: Software that uses a camera and microphone to collect and analyze the user's facial expressions and tone of voice.

[0633] Specific processing flow

[0634] 1. Upload drawings and 3D models

[0635] A user uses a terminal to select a file of architectural drawings or a 3D model and clicks the upload button. The terminal generates an HTTP request and sends the file data to the server.

[0636] 2. Analysis of drawings and 3D models

[0637] The server analyzes the received file data using CAD software and specialized analysis algorithms. As a result of the analysis, structural information such as walls and doors is extracted, and measurements between endpoints and physical attributes (thickness, height, etc.) are identified.

[0638] 3. Legal checks

[0639] The server compares the extracted structural information with the building code standards. For example, it checks whether the wall thickness meets the legal standards and whether the door height is appropriate. The results of the legal check are summarized and displayed in a user-friendly format.

[0640] 4. Generate color and comfort advice

[0641] Based on the analysis results, the server generates advice on room colors and furniture placement. For example, it generates advice such as, "The color of the living room is too bright, so we recommend changing it to a softer color," and displays it to the user.

[0642] 5. Recognition of user emotions using an emotion engine

[0643] The emotion engine uses a camera and microphone to collect and analyze the user's facial expressions and tone of voice, and sends the analysis results to a server to identify the user's emotions.

[0644] 6. Providing advice and feedback to users

[0645] The server adjusts the content and display of advice based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adds positive feedback such as "Don't worry, it's easy to fix." The information received by the device is displayed in the user interface.

[0646] Specific examples

[0647] Case 1: Wall thickness check and user emotion adaptation

[0648] The user uploads a blueprint file for a new building to the system from their device. The server receives the blueprint file and analyzes it. The analysis extracts the wall thickness. The result is compared with the legal standard value, and a message is displayed saying, "The wall thickness exceeds the legal standard. Corrections are required." If the emotion engine senses stress from the user's facial expression, the server adds positive feedback such as, "Don't worry, it's easy to correct."

[0649] Example prompt sentence:

[0650] Upload a new building drawing file into the system and receive a report with analysis results, including code checks on wall thickness, and feedback based on user sentiment.

[0651] Case 2: Color Advice and Emotional Adaptation

[0652] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. It generates color advice, such as "The colors in the living room are too bright, so we recommend changing them to softer colors." If the emotion engine recognizes the user's happy emotion, the server adds a positive message, such as "This color scheme will make your room look even better."

[0653] Example prompt sentence:

[0654] Upload a new room interior design model to the system, and receive analysis results that suggest color schemes for the room and provide feedback based on the user's emotions.

[0655] The system of the present invention is designed to support users in verifying compliance with regulations and improving the design of their construction projects efficiently and comfortably, and can enhance the user experience by responding flexibly to the user's emotional state.

[0656] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0657] Step 1: Upload your drawings or 3D models

[0658] Input: The user selects architectural drawings or 3D models from the terminal's file selection interface.

[0659] Process: The user clicks the "Upload" button. The device sends the selected file to the server as an HTTP request.

[0660] Output: The file sent from the terminal arrives at the server.

[0661] Step 2: Analyze drawings and 3D models

[0662] Input: Files of architectural drawings and 3D models received by the server from the terminal.

[0663] Processing: The server uses CAD software or specialized analysis algorithms to analyze the received file. The file data is parsed to extract structural information such as walls and doors. End-to-end measurements and physical attributes (thickness, height, etc.) are identified.

[0664] Output: Structural information based on the analysis is obtained.

[0665] Step 3: Conduct a legal check

[0666] Input: Structural information extracted by the server.

[0667] Processing: The server checks the extracted structural information against building code standards, for example, checking whether the wall thickness meets the code standards and whether the door height is appropriate.

[0668] Output: The compliance check results are generated, clearly indicating compliance and non-compliance.

[0669] Step 4: Generate color and comfort advice

[0670] Input: Room structural information and color data analyzed by the server.

[0671] Processing: Based on the analysis results, the server generates advice on the color scheme and furniture placement in the room. For example, it generates advice such as, "The color in the living room is too bright, so we recommend changing it to a softer color."

[0672] Output: Color and comfort advice is generated.

[0673] Step 5: Recognizing user emotions with the emotion engine

[0674] Input: Camera and microphone data to collect the user's facial expressions and tone of voice.

[0675] Processing: The emotion engine uses the camera and microphone to collect and analyze the user's facial expressions and tone of voice, which in turn identifies the user's emotional state (e.g., stress, joy, surprise, etc.).

[0676] Output: An analysis result about the user's emotional state is generated.

[0677] Step 6: Advise the user and provide feedback

[0678] Input: Server-generated legal check results, color and comfort advice, and the user's emotional state via the emotion engine.

[0679] Processing: The server adjusts the displayed advice based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adds positive feedback such as "Don't worry, it's easy to fix." The device then displays the adjusted check results and advice on the user interface.

[0680] Output: The adjusted legal check results and advice are displayed on the user interface.

[0681] Step 7: User corrections and recheck

[0682] Input: Drawings and 3D model data that users modify based on the advice and feedback provided.

[0683] Processing: The user modifies the drawing or model according to the provided advice. Once the modifications are complete, the file is uploaded back to the server, where it is analyzed and checked for legal compliance again.

[0684] Output: New regulatory check results and advice are generated based on the revised drawings and 3D models.

[0685] (Application example 2)

[0686] 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."

[0687] Conventional autonomous vehicles lack a system that can adjust in real time the impact of factors such as interior layout and color scheme on the comfort of the driver and passengers. Furthermore, there is a lack of means to improve comfort by providing feedback or advice based on the user's emotions while in the vehicle. This can easily lead to stressful situations for the user, resulting in a lower quality driving experience. Therefore, the present invention aims to solve these problems and provide a new system that can adapt to the user's emotions while maintaining a more comfortable environment inside an autonomous vehicle.

[0688] 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.

[0689] In this invention, the server includes means for receiving drawings and 3D models, means for checking the received drawings and 3D models against legal standards, means for generating and displaying the comparison results, means for generating advice regarding color schemes and comfort, means for displaying the generated advice, means including an emotion engine for recognizing the user's emotions, and means for dynamically adjusting the advice and display content based on the user's emotional state. This makes it possible to maintain a comfortable environment inside an autonomous vehicle in real time, reduce stress felt by the user, and provide a better driving experience.

[0690] "Drawings and 3D models" are digital data representing architectural or spatial design drawings and three-dimensional shapes that users provide to the system.

[0691] "Means for receiving" refers to devices and software that have the function of receiving data such as drawings and three-dimensional models uploaded by users.

[0692] "Means for checking" refers to equipment and software that compares received drawings and 3D models with existing standards and regulations to check for compliance.

[0693] "Means for generating and displaying" refers to devices and software that create information based on analysis results and advice and visually present it to users.

[0694] The "means for generating color and comfort advice" refers to devices and software that generate recommendations to users regarding the color and layout of a space based on the results of analysis of drawings and three-dimensional models.

[0695] An "emotion engine" is a device and software that identifies emotions from a user's facial expressions, voice, etc. and analyzes the data.

[0696] "Dynamic adjusting means" refers to devices and software for changing in real time the content and manner of advice or information presented based on the user's emotional state.

[0697] "Real-time" refers to data processing and information being provided immediately when a user uses the system.

[0698] An "autonomous vehicle" is a vehicle that is driven automatically by a system without the need for driver operation.

[0699] The present invention relates to a system that maintains a comfortable environment inside an autonomous vehicle while adapting based on the emotional state of the user. Specific embodiments of the system are described below.

[0700] 1. Receiving drawings and 3D models

[0701] The server receives images and 3D models of the interior of the autonomous vehicle in real time via smart glasses or a head-mounted display (HMD), which allows it to collect data on the interior layout and color scheme.

[0702] 2. Data analysis and legal checks

[0703] The server analyzes the received images and models to extract interior data for the vehicle. It uses the open-source libraries OpenCV and dlib for image analysis, and the DesignAnalysis library to analyze spatial layout and color data. The analysis results are compared with pre-set legal standards.

[0704] 3. Providing advice on color schemes and comfort

[0705] The server generates advice on color schemes and comfort based on the analysis results. For example, if the lighting is too bright, the server may provide advice such as "We recommend dimming the lights a little." If the seat position is inappropriate, the server may provide advice such as "We recommend moving your seat forward a little."

[0706] 4. Recognition of user emotions using an emotion engine

[0707] The server uses sensors built into the smart glasses or HMD to recognize emotions from the user's facial expressions and tone of voice. The EmotionRecognition library is used for this emotion recognition. The recognized emotion data is sent to the server for analysis.

[0708] 5. Emotional Adaptation

[0709] The server adjusts the generated advice and display content based on the user's emotional data. For example, it provides suggestions for stress reduction to a user who is feeling stressed, and includes positive feedback to a user who is feeling happy. This allows the user to continue driving in a comfortable state.

[0710] 6. Presenting the results to the user

[0711] The device displays the generated advice and tailored feedback in real time via smart glasses or an HMD, allowing the user to review the displayed content and implement the system's suggestions as needed.

[0712] Specific examples

[0713] Example 1: Adjusting the lighting

[0714] If the user feels that the lighting in the autonomous vehicle is too bright, the server generates and displays advice such as "We recommend that you dim the lights a little." If the user feels stressed, the server provides additional feedback such as "Dim the lights to relax."

[0715] Example 2: Seating arrangement

[0716] If the user is dissatisfied with the seating position in the car, the server will provide advice such as "If you move your seat a little forward, you will have more leg room." If the emotion engine recognizes the user's joy, the server will add a positive message such as "This positioning will make you even more comfortable."

[0717] Prompt Sentence Examples

[0718] "If I feel the colors in my car are too bright, can you suggest how I should change the settings?"

[0719] "How can I optimize my seat position to increase legroom?"

[0720] This enables the system to maintain a comfortable environment inside the autonomous vehicle while providing appropriate advice and feedback in real time based on the user's emotions.

[0721] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0722] Step 1:

[0723] The smart glasses or HMD captures images of the interior of the vehicle and sends the data to a server. The input is the image data captured by the smart glasses or HMD, and the output is the image data sent to the server. This image data includes the layout and color scheme of the interior of the vehicle.

[0724] Step 2:

[0725] The server analyzes the received image data. The OpenCV and dlib libraries are used for the analysis. Specifically, the necessary interior structural information is extracted from the image and color scheme data is identified. The input is the received image data, and the output is the analysis results.

[0726] Step 3:

[0727] The server uses the DesignAnalysis library to compare the extracted structural information with the legal standards. The comparison results clearly show which parts comply with the law and which do not. The input is the analysis result obtained in step 2, and the output is the result of the legal check.

[0728] Step 4:

[0729] The server generates color and comfort advice. A generative AI model is used to create recommendations based on interior color and layout. The input is the results of legal checks and analysis, and the output is specific advice.

[0730] Step 5:

[0731] The server uses the emotion engine to analyze the user's facial expressions and tone of voice received from the smart glasses or HMD and recognize the user's emotions. The input is the user's facial expression data and tone of voice data, and the output is the emotion recognition result.

[0732] Step 6:

[0733] The server dynamically adjusts the generated advice and display content based on the user's emotion recognition results. For example, it adds a recommendation to relax to a user who is feeling stressed, while adding positive feedback to a user who is feeling happy. The input is the emotion recognition results and the generated advice, and the output is the adjusted advice or notification.

[0734] Step 7:

[0735] The device displays tailored advice and notifications to the user in real time through smart glasses or an HMD. The user reviews the displayed information and implements the system's suggestions as needed. The input is the tailored advice and notifications, and the output is a visual presentation to the user.

[0736] Through these processing steps, the system can provide appropriate advice and feedback according to the user's emotions while maintaining a comfortable environment inside the autonomous vehicle.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] [Third embodiment]

[0741] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0742] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0743] 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).

[0744] 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.

[0745] 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.

[0746] 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).

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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.

[0752] 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."

[0753] The present invention relates to a system that receives drawings and 3D models, analyzes them, checks them for legal regulations, and generates advice on color schemes and comfort. Specific embodiments of the system are described below.

[0754] 1. Upload and analyze drawings

[0755] First, the user uploads a blueprint or 3D model from their device. The device generates a request to send the selected file to the server, and sends the file data to the server. The server analyzes the received blueprint or 3D model and extracts structural information such as walls and doors. At this time, the server checks whether each element complies with the standards set out in building regulations.

[0756] 2. Generate and send legal check results

[0757] The server generates a matching result based on the analysis results. For example, it checks whether the wall thickness is within legal limits, whether the door height is appropriate, etc. The matching result is generated in a way that clearly shows which parts comply with the law and which parts do not. The generated matching result is sent to the terminal so that the user can check it.

[0758] 3. Providing advice on color schemes and comfort

[0759] Based on the analysis results, the server generates advice on color schemes and comfort, including, for example, whether the room color is visually less tiring, whether the furniture arrangement is comfortable, etc. The generated advice is converted into a format for display to the user and sent to the terminal.

[0760] 4. User Presentation and Interaction

[0761] The terminal displays the received matching results and advice on the user interface. The user can review them and modify the drawings or 3D models as necessary. The modified drawings or 3D models are then uploaded back to the server, where they undergo the same process of checking and receiving advice.

[0762] Specific examples

[0763] A specific scenario is shown below.

[0764] Case 1: Wall Thickness Check

[0765] The user uploads a drawing file of a new building from their terminal to the system. The server receives the drawing file and performs an analysis. The analysis extracts the wall thickness. This is then compared with the legal standard, and the user is shown a message saying, "The wall thickness exceeds the legal standard. Corrections are required." The user can correct the wall thickness and upload it again to have it checked again.

[0766] Case 2: Color Advice

[0767] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color-scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." The user then adjusts the color scheme of the design accordingly.

[0768] The system of the present invention significantly reduces the time and cost involved in the proposal phase of a construction project by automatically checking regulatory standards and providing design advice, allowing users to efficiently improve regulatory compliance and design.

[0769] The processing flow will be explained below.

[0770] Step 1:

[0771] A user selects a drawing file or a 3D model on a terminal and presses an upload button. The terminal generates a request to send the selected file to the server. The request includes the file data and associated metadata.

[0772] Step 2:

[0773] The device sends the request to the server using the HTTP protocol, etc. The server receives the request and saves the uploaded file in local storage.

[0774] Step 3:

[0775] The server analyzes the received drawing file or 3D model using algorithms that read the file and identify and extract structural elements such as walls, doors, windows, etc. The extracted information is stored in a database.

[0776] Step 4:

[0777] The server compares the extracted structural information with legal standards, for example, checking whether the wall thickness is within legal standards and whether the door height is appropriate. These standards are stored in a database in advance and are compared with the extracted information.

[0778] Step 5:

[0779] The server generates a matching result, which clearly shows which parts of the document comply with the law and which parts do not. For non-compliant parts, the result includes specific corrections and recommended changes.

[0780] Step 6:

[0781] The server converts the results of the matching process into a display format, such as HTML or JSON, and prepares the results for transmission to the device. The converted data is then organized in a format that is easy for the user to understand.

[0782] Step 7:

[0783] The server sends the converted matching results to the terminal, which processes the received data to display it on the user interface. The user checks the displayed matching results and determines whether any inconsistencies need to be corrected.

[0784] Step 8:

[0785] The server generates color and comfort advice based on the analyzed design data, creating advice on color balance, furniture placement, and more. This includes algorithms that suggest color schemes that reduce visual fatigue and placement advice to provide a comfortable user environment.

[0786] Step 9:

[0787] The server converts the generated advice into a presentation format, organizing it in a user-friendly way and converting it into HTML or JSON.

[0788] Step 10:

[0789] The server sends the converted advice to the terminal, which processes the received advice to display it on the user interface. The user can use the displayed advice to improve the design.

[0790] Example 1

[0791] 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."

[0792] In architectural projects, it is important to efficiently check the legal compliance of drawings and 3D models and provide advice on the comfort of the design. However, manual checks and advice are time-consuming and costly. Furthermore, because specialized knowledge is required, it is often difficult to provide appropriate advice. The present invention aims to solve these problems and provide a system that automatically and efficiently checks legal compliance and provides advice on comfort.

[0793] 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.

[0794] In this invention, the server includes means for receiving drawings and 3D models, means for analyzing the received drawings and 3D models to extract structures such as walls and doors, means for checking the extracted structures against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, and means for displaying the generated advice. This automates the process of checking legal compliance and improving designs in architectural projects, reducing time and costs, and making it possible to obtain appropriate advice even without specialized knowledge.

[0795] "Drawings and three-dimensional models" refer to floor plans and three-dimensional drawings, as well as the digital data thereof, that represent the structure and layout of a building or design object.

[0796] "Means for receiving" refers to a mechanism or method for importing drawing or three-dimensional model data from a user into the server.

[0797] "Means of analysis" refers to the mechanisms and software used to process received drawings and three-dimensional model data and extract structural information such as walls and doors.

[0798] The "means for extraction" is a function for extracting and identifying specific elements (e.g., walls, doors, etc.) from the analyzed data.

[0799] The "means of matching" is a method for comparing the extracted structural information with legally defined standards to confirm the degree of agreement.

[0800] The "means of checking" is a system for evaluating the compliance of each element of a building based on legal standards.

[0801] "Means for generating" refers to the process for creating information and advice to be provided to the user based on the results of analysis and collation.

[0802] The "display means" refers to a device or interface for visually conveying the generated matching results and advice to the user.

[0803] "Color and comfort advice" means suggestions and instructions for improving the visual and functional comfort of a room's color and furniture arrangement.

[0804] A "user interface" is a screen or operating means through which a user interacts with a system and inputs and outputs information.

[0805] The "means for receiving again" refers to a mechanism or method for importing the data of drawings or three-dimensional models that have been modified into the server again.

[0806] "Means for rechecking" refers to the process of comparing revised drawings and three-dimensional models with the legal standards again to confirm compliance.

[0807] This invention relates to a system that automatically analyzes and evaluates compliance with regulations and design comfort using architectural drawings and 3D models, and provides the results to users. This system is composed of three entities: a server, a terminal, and a user. The overall system configuration and the role played by each entity are explained in detail below.

[0808] Hardware and Software Configuration

[0809] 1. Receiving drawings and 3D models

[0810] The user selects drawings or 3D models from the terminal and sends them to the server.

[0811] The terminal uploads the file selected by the user to the server using a protocol such as an HTTP request.

[0812] The server stores the received drawings and 3D models in storage (e.g., a disk drive or cloud storage).

[0813] 2. Analysis of drawings and 3D models

[0814] The server analyzes the stored data, for example, using AutoCAD API or BIM (Building Information Modeling) software.

[0815] An algorithm has been implemented to extract structural information such as walls and doors from the received data.

[0816] 3. Legal checks

[0817] The server checks the extracted structural information against the standard values ​​set by building regulations.

[0818] The check uses certain criteria (e.g. wall thickness, door height) and a matching algorithm evaluates whether the criteria are met.

[0819] 4. Generate and send legal check results

[0820] Based on the check results, the server generates a matching result that clearly indicates which parts comply with the law and which parts do not.

[0821] The generated matching results are converted into a user-viewable format (e.g., text report or graphical report) and sent to the terminal.

[0822] 5. Generate color and comfort advice

[0823] Based on the analysis results, the server generates advice on color schemes and comfort.

[0824] Advice can come in the form of, for example, a visual comfort rating or suggestions for furniture placement.

[0825] 6. Display and interaction on user devices

[0826] The terminal displays the received collation results and advice on a user interface.

[0827] The user can use this information to modify the drawings or 3D models and send them back to the server.

[0828] Specific examples

[0829] Case 1: Wall Thickness Check

[0830] A user uploads a drawing file of a new building to the system from their terminal. The server receives the drawing file and performs an analysis. The analysis extracts the wall thickness. This is then compared with the legal standard, and the user is shown a message such as, "The wall thickness does not meet the legal standard (current: 10cm, required: 12cm)." The user can then correct the wall thickness and upload it again to have it checked again.

[0831] Case 2: Color Advice

[0832] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color-scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." The user then adjusts the color scheme of the design accordingly.

[0833] Prompt Sentence Examples

[0834] "Please develop a system that analyzes the drawings of a new building and checks whether the wall thickness complies with regulations. Please also explain the specific check items and how to display the check results."

[0835] "Create a system that allows users to upload a room design model and provides color advice based on visual comfort. Explain how you would analyze the model and how you would provide the advice."

[0836] As described above, the present invention makes it possible to efficiently provide advice on legal compliance and design during the proposal phase of a construction project, thereby reducing time and costs.

[0837] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0838] Step 1:

[0839] Upload drawings and 3D models

[0840] The user uses the terminal to select a drawing or 3D model file and perform the upload operation. The terminal sends the selected file to the server via an HTTP request. The input is the drawing or model file selected by the user, and the output is the file being sent to the server. Specifically, the user presses the "Select File" button, selects a file (e.g., building_plan.dwg) from local storage, and clicks the "Upload" button.

[0841] Step 2:

[0842] Receiving and storing drawings and 3D models

[0843] The server receives the file sent from the terminal and saves the data in storage. The input is the file data sent from the terminal, and the output is the file saved in storage. Specifically, the server receives the HTTP request and saves the file in the specified directory. For example, the save location is / uploads / building_plan.dwg.

[0844] Step 3:

[0845] Analysis of drawings and 3D models

[0846] The server analyzes the saved files and extracts structural information such as walls and doors. This analysis uses AutoCAD API and BIM software. The input is the saved file, and the output is the extracted structural information. Specifically, the server calls the AutoCAD API and analyzes and extracts the location of walls, doors, etc. from the file.

[0847] Step 4:

[0848] Legal checks

[0849] The server checks the extracted structural information against the standard values ​​set by building regulations. Examples of criteria for checking include "wall thickness" and "door height." The input is the extracted structural information, and the output is the result of the check. Specifically, the server compares the wall thickness (e.g., 10 cm) with the standard value (e.g., 12 cm) and determines whether it meets the criteria.

[0850] Step 5:

[0851] Generate and send legal check results

[0852] Based on the results of the legal check, the server generates a legal compliance matching result and sends it to the terminal in a format that the user can understand. The input is the matched information, and the output is a report of the generated matching result. Specifically, the server generates a message such as "The wall thickness does not meet the legal standards (current: 10 cm, required: 12 cm)" and sends it to the terminal.

[0853] Step 6:

[0854] Generate color and comfort advice

[0855] The server generates advice on color schemes and comfort based on the analysis results. The input is the analysis results, and the output is the generated advice. Specifically, the server detects that the color of the living room is too bright and generates the advice, "We recommend changing the color of the living room to a softer color (e.g., pastel green)."

[0856] Step 7:

[0857] Display and interaction on user devices

[0858] The terminal displays the matching results and advice received on the user interface. The user can check the displayed information and modify the drawing or 3D model as necessary. The input is the results and advice sent from the server, and the output is the displayed content and input from the user (modified drawing or model). Specifically, the terminal screen displays the areas that need to be modified and recommended advice, and the user modifies the drawing again based on this information and returns to step 1.

[0859] The above is the specific flow of the program processing of this system.

[0860] (Application example 1)

[0861] 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."

[0862] Currently, there are limited ways to efficiently check and provide advice on regulatory compliance, comfort, and color schemes in the interior design of autonomous vehicles. Designers must manually check regulations and repeatedly try and error interior designs. This results in significant time and cost involved in the design process. Furthermore, there is a lack of real-time feedback, which can delay design revisions.

[0863] 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.

[0864] In this invention, the server includes means for receiving drawings and 3D models, means for checking the received drawings and 3D models against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, means for displaying the generated advice, and means for displaying the legal check and the advice on comfort and color schemes on a 3D display device. This enables designers to receive checks and advice on legal compliance, comfort, and color schemes in real time in the interior design of autonomous vehicles through a 3D display device such as smart glasses, significantly improving the efficiency of the design process.

[0865] "Drawings and 3D models" means static or dynamic visual data used to represent the interior structure of a building or vehicle.

[0866] "Legal standard values" refer to specific numerical values ​​and standards set forth in laws, regulations, and standards related to construction and design.

[0867] The "matching result" is a report of the results of the evaluation of the received drawings or three-dimensional models based on the legal standards, and indicates whether or not they comply with the law.

[0868] "Advice on color schemes and comfort" refers to guidance and suggestions on whether the color scheme of a space is visually pleasing and whether the layout of furniture and interior décor ensures user comfort.

[0869] "Display means" refers to hardware and software for visually displaying analysis results and advice on a user interface.

[0870] A "three-dimensional display device" is a device that can display information in three-dimensional space, such as smart glasses or a head-mounted display.

[0871] The "server" is a computer system that analyzes drawings and three-dimensional models, checks legal compliance, generates matching results, and provides advice on color schemes and comfort.

[0872] This invention is a system that receives drawings and 3D models, performs analysis and legal checks, and generates advice on color schemes and comfort. Specifically, it uses a server, terminals, and a 3D display device to enable designers to efficiently check and improve the interior design of autonomous vehicles.

[0873] Program Overview

[0874] In this system, the server executes programs and processes various data. The programs are as follows:

[0875] 1. Receiving drawings and 3D models

[0876] The user uploads drawings or 3D models from their device, and the device sends this file data to the server.

[0877] 2. Analysis of drawings and 3D models

[0878] The server analyzes the received drawings and 3D models to extract structural information about walls, doors, etc. The results of the analysis are compared with legal standards to check whether each element complies with the regulations.

[0879] 3. Generate and send legal check results

[0880] The server generates a matching result based on the analysis results, clearly indicating which parts comply with the law and which parts do not. The matching result is sent to the terminal so that the user can check it.

[0881] 4. Providing advice on color and comfort

[0882] From the analysis results, the server generates color and comfort advice, including suggestions on the visual impact of colors and the comfort of furniture placement.

[0883] 5. Display on a 3D display device

[0884] The server sends the generated matching results and advice to a 3D display device, where the user can view the information in real time.The user can visually check the interior of the vehicle using smart glasses or a head-mounted display (e.g., Microsoft HoloLens or Google Glass).

[0885] Hardware and software used

[0886] Hardware

[0887] Device: PC or smartphone

[0888] 3D display devices: smart glasses, head-mounted displays

[0889] software

[0890] Server program: Python

[0891] Data transmission: REST API

[0892] 3D modeling software: Autodesk Revit, etc.

[0893] Specific examples

[0894] Example 1: Interior design check

[0895] After a designer finishes designing the interior of an autonomous vehicle, they upload the model file from their device to a server. The server analyzes the model and generates advice on compliance, comfort, and color schemes, which are then sent to the smart glasses. While wearing the smart glasses, the designer can visually confirm this information in real time while walking around the vehicle and make any necessary design changes.

[0896] Prompt Sentence Examples

[0897] To ensure that the interior design of an autonomous vehicle complies with regulations, please analyze the following models and provide advice on color schemes and comfort:

[0898] 1. / path / to / car_interior_model.obj

[0899] Check the thickness of the wall in accordance with regulations.

[0900] Rate the comfort of the seating arrangement.

[0901] Analyze the visual effects of room colors and recommend color schemes that reduce fatigue.

[0902] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0903] Specific processing steps of the program

[0904] Step 1:

[0905] The user uploads a drawing or 3D model from their device. To do this, the user uses a dedicated application to select the target drawing or 3D model file from a file dialog. Once the data is selected, the device generates a request to send it to the server. Input: Drawing or 3D model file. Output: A request is generated to send the file data to the server.

[0906] Step 2:

[0907] The server analyzes the received drawings and 3D models. When the server receives the files, it applies a specific analysis algorithm to extract structural information (walls, doors, etc.). Input: Uploaded drawings and 3D model files. Output: Extracted structural information.

[0908] Step 3:

[0909] The server compares the analyzed structural information with legal standards. Using a comparison algorithm, it evaluates whether each extracted element complies with the law. Input: Structural information, legal standard data. Output: Evaluation result of legal compliance.

[0910] Step 4:

[0911] The server generates a matching result report based on the evaluation results of the legal check. The report clearly shows which parts are compliant and which parts are not. Input: Legal compliance evaluation result. Output: Matching result report.

[0912] Step 5:

[0913] The server sends a matching result report to the terminal and the 3D display device, which visually presents this information to the user. Input: Matching result report. Output: Display data on the user interface and the 3D display device.

[0914] Step 6:

[0915] The server generates advice on color schemes and comfort based on the analysis results. It uses a generative AI model to provide detailed suggestions on visual impact and comfort. Input: Structural information, generative AI model. Output: Advice on color schemes and comfort.

[0916] Step 7:

[0917] The generated advice is sent from the server to the terminal and the 3D display device, which visually display the advice so that the user can check it in real time. Input: Advice on color scheme and comfort. Output: Display data on the user interface and the 3D display device.

[0918] Step 8:

[0919] The user wears smart glasses and receives real-time feedback through a 3D display, allowing for immediate corrections for compliance, comfort, and color scheme. Input: Feedback information from the 3D display. Output: Real-time design corrections.

[0920] 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.

[0921] The present invention relates to a system that receives blueprints and 3D models, analyzes them, checks them for legal compliance, and generates advice on color schemes and comfort, in addition to a system that combines an emotion engine that recognizes the user's emotions. Specific embodiments of the system are described below.

[0922] 1. Upload and analyze drawings

[0923] First, the user uploads a blueprint or 3D model from their device. The device generates a request to send the selected file to the server, and sends the file data to the server. The server analyzes the received blueprint or 3D model and extracts structural information such as walls and doors. At this time, the server checks whether each element complies with the standards set out in building regulations.

[0924] 2. Generate and send legal check results

[0925] The server generates a matching result based on the analysis results. For example, it checks whether the wall thickness is within legal limits, whether the door height is appropriate, etc. The matching result is generated in a way that clearly shows which parts comply with the law and which parts do not. The generated matching result is sent to the terminal so that the user can check it.

[0926] 3. Providing advice on color schemes and comfort

[0927] Based on the analysis results, the server generates advice on color schemes and comfort, including, for example, whether the room color is visually less tiring, whether the furniture arrangement is comfortable, etc. The generated advice is converted into a format for display to the user and sent to the terminal.

[0928] 4. Emotion Engine for Recognizing and Adapting to User Emotions

[0929] The system incorporates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice. The emotion engine analyzes the user's current emotional state (e.g., stress, joy, surprise, etc.). The recognized emotions are sent to the server, and advice and user interface display content are dynamically adjusted.

[0930] 5. User Presentation and Interaction

[0931] The device displays the received matching results and advice on the user interface. If the user feels emotionally stressed, the emotion engine recognizes this and the server adjusts the content presented to allow the user to use the system comfortably. For example, a user feeling stressed may be presented with advice displayed in softer colors or with positive feedback. If the user modifies the drawing or 3D model based on the confirmation and advice, the modified data is uploaded back to the server and rechecked using the same process.

[0932] Specific examples

[0933] Case 1: Wall thickness check and user emotion adaptation

[0934] The user uploads a blueprint file of a new building to the system from their device. The server receives the blueprint file and analyzes it. The analysis extracts the wall thickness. This is then compared with the legal standard, and a message is displayed to the user, such as, "The wall thickness exceeds the legal standard. Correction is required." If the emotion engine detects stress from the user's facial expression, the server displays additional positive feedback, such as, "Don't worry, it's easy to correct."

[0935] Case 2: Color Advice and Emotional Adaptation

[0936] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." If the emotion engine recognizes the user's emotion of happiness, the server adds a positive message, such as "This color scheme will make your room look even better."

[0937] The system of the present invention improves the experience during the proposal phase of a construction project by automatically checking regulatory standards and providing design advice, as well as recognizing and responding to user emotions, allowing users to efficiently and comfortably improve regulatory compliance and design.

[0938] The processing flow will be explained below.

[0939] Step 1:

[0940] A user selects a drawing file or a 3D model on a terminal and presses an upload button. The terminal generates a request to send the selected file to the server. The request includes the file data and associated metadata.

[0941] Step 2:

[0942] The device sends the request to the server using the HTTP protocol, etc. The server receives the request and saves the uploaded file in local storage.

[0943] Step 3:

[0944] The server analyzes the received drawing file or 3D model using algorithms that read the file and identify and extract structural elements such as walls, doors, windows, etc. The extracted information is stored in a database.

[0945] Step 4:

[0946] The server compares the extracted structural information with legal standards, for example, checking whether the wall thickness is within legal standards and whether the door height is appropriate. These standards are stored in a database in advance and are compared with the extracted information.

[0947] Step 5:

[0948] The server generates a matching result, which clearly shows which parts of the document comply with the law and which parts do not. For non-compliant parts, the result includes specific corrections and recommended changes.

[0949] Step 6:

[0950] The server converts the results of the matching process into a display format, such as HTML or JSON, and prepares the results for transmission to the device. The converted data is then organized in a format that is easy for the user to understand.

[0951] Step 7:

[0952] The server sends the converted matching results to the terminal, which processes the received data to display it on the user interface. The user checks the displayed matching results and determines whether any inconsistencies need to be corrected.

[0953] Step 8:

[0954] The server generates color and comfort advice based on the analyzed design data, creating advice on color balance, furniture placement, and more. This includes algorithms that suggest color schemes that reduce visual fatigue and placement advice to provide a comfortable user environment.

[0955] Step 9:

[0956] The server converts the generated advice into a presentation format, organizing it in a user-friendly way and converting it into HTML or JSON.

[0957] Step 10:

[0958] The server sends the converted advice to the terminal, which processes the received advice to display it on the user interface. The user can use the displayed advice to improve the design.

[0959] Step 11:

[0960] The emotion engine installed in the device analyzes the user's facial expressions and tone of voice to recognize emotions. For example, the device uses a camera or microphone to capture the user's facial expressions and voice data.

[0961] Step 12:

[0962] The emotion engine analyzes the emotion data and sends it to the server. For example, if the user is feeling stressed, that information is sent to the server.

[0963] Step 13:

[0964] The server adjusts the advice and feedback it provides to users based on the emotion data it receives. For example, if a user is feeling stressed, it might display advice in softer colors and provide positive feedback messages.

[0965] Step 14:

[0966] The device displays the adjusted advice and feedback in the user interface, allowing the user to review the displayed content and modify the drawing or 3D model as needed.

[0967] Step 15:

[0968] If the user modifies the drawing or 3D model, the modified data is uploaded to the server again, where it is rechecked through the same process and the user is provided with new matching results and advice.

[0969] In this way, the system of the present invention not only automatically checks legal standards and provides design advice, but also improves the user experience by recognizing and responding appropriately to user emotions.

[0970] Example 2

[0971] 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."

[0972] Modern construction projects require rapid verification of design and construction compliance. However, doing this manually takes a significant amount of time and requires experts to provide advice on design comfort and color schemes. Furthermore, advice is often provided without taking into account the user's emotional state, resulting in a poor user experience.

[0973] 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.

[0974] In this invention, the server includes means for receiving drawings and 3D models, means for analyzing the received drawings and 3D models, means for checking the analyzed information against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, means for displaying the generated advice on a user interface, means for recognizing a user's emotion using an emotion engine, and means for adjusting the display content based on the recognized emotion. This makes it possible to check legal compliance in construction projects, automatically provide advice on the comfort of designs and color schemes, and provide feedback adapted to the user's emotions.

[0975] "Drawings and 3D models" are digital or analog information that represents a building or design in two or three dimensions.

[0976] The "receiving means" refers to a method or device for obtaining data transmitted from a terminal via a network.

[0977] "Means for analysis" refers to the process or software that deciphers the content of the received data and extracts structural information and various attributes.

[0978] "Means for checking against legal standards" refers to algorithms or programs that compare analyzed information with the standards of existing laws and regulations to confirm compliance.

[0979] The "means for generating and displaying the matching results" is a mechanism for compiling the check results into a format that is easy for the user to understand and displaying them on a display or the like.

[0980] The "means for generating color and comfort advice" refers to an algorithm or AI model that uses the user's design data to create suggestions for more comfortable and visually appealing color schemes and placements.

[0981] "Means for displaying on a user interface" refers to a method for presenting the generated advice and check results through an interface that can be viewed and operated by the user.

[0982] An "emotion engine" is software or hardware that analyzes a user's emotions from their facial expressions, tone of voice, etc., and identifies their state.

[0983] The "means for recognizing user emotions" is a process of detecting the user's emotions using an emotion engine and obtaining the analysis results.

[0984] The "means for adjusting the display content based on the recognized emotion" refers to an algorithm or program that flexibly changes the advice provided and the display method according to the user's emotional state.

[0985] This invention is a system that receives drawings and three-dimensional models, analyzes them, checks them for legal requirements, and generates advice on color schemes and comfort, in addition to a system that combines an emotion engine that recognizes the user's emotions.

[0986] Hardware and software used

[0987] Device: A PC or smartphone is typically used, which includes the ability to upload files and a display to show the user interface.

[0988] Server: A central processing unit that analyzes data, checks laws and regulations, generates advice, and analyzes emotions. It is equipped with CAD software, specialized analysis algorithms, and an emotion engine.

[0989] Emotion engine: Software that uses a camera and microphone to collect and analyze the user's facial expressions and tone of voice.

[0990] Specific processing flow

[0991] 1. Upload drawings and 3D models

[0992] A user uses a terminal to select a file of architectural drawings or a 3D model and clicks the upload button. The terminal generates an HTTP request and sends the file data to the server.

[0993] 2. Analysis of drawings and 3D models

[0994] The server analyzes the received file data using CAD software and specialized analysis algorithms. As a result of the analysis, structural information such as walls and doors is extracted, and measurements between endpoints and physical attributes (thickness, height, etc.) are identified.

[0995] 3. Legal checks

[0996] The server compares the extracted structural information with the building code standards. For example, it checks whether the wall thickness meets the legal standards and whether the door height is appropriate. The results of the legal check are summarized and displayed in a user-friendly format.

[0997] 4. Generate color and comfort advice

[0998] Based on the analysis results, the server generates advice on room colors and furniture placement. For example, it generates advice such as, "The color of the living room is too bright, so we recommend changing it to a softer color," and displays it to the user.

[0999] 5. Recognition of user emotions by emotion engine

[1000] The emotion engine uses a camera and microphone to collect and analyze the user's facial expressions and tone of voice, and sends the analysis results to a server to identify the user's emotions.

[1001] 6. Providing advice and feedback to users

[1002] The server adjusts the content and display of advice based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adds positive feedback such as "Don't worry, it's easy to fix." The information received by the device is displayed in the user interface.

[1003] Specific examples

[1004] Case 1: Wall thickness check and user emotion adaptation

[1005] The user uploads a blueprint file for a new building to the system from their device. The server receives the blueprint file and analyzes it. The analysis extracts the wall thickness. The result is compared with the legal standard value, and a message is displayed saying, "The wall thickness exceeds the legal standard. Corrections are required." If the emotion engine senses stress from the user's facial expression, the server adds positive feedback such as, "Don't worry, it's easy to correct."

[1006] Example prompt sentence:

[1007] Upload a new building drawing file into the system and receive a report with analysis results, including code checks on wall thickness, and feedback based on user sentiment.

[1008] Case 2: Color Advice and Emotional Adaptation

[1009] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. It generates color advice, such as "The colors in the living room are too bright, so we recommend changing them to softer colors." If the emotion engine recognizes the user's happy emotion, the server adds a positive message, such as "This color scheme will make your room look even better."

[1010] Example prompt sentence:

[1011] Upload a new room interior design model to the system, and receive analysis results that suggest color schemes for the room and provide feedback based on the user's emotions.

[1012] The system of the present invention is designed to support users in verifying compliance with regulations and improving the design of their construction projects efficiently and comfortably, and can enhance the user experience by responding flexibly to the user's emotional state.

[1013] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1014] Step 1: Upload your drawings or 3D models

[1015] Input: The user selects architectural drawings or 3D models from the terminal's file selection interface.

[1016] Process: The user clicks the "Upload" button. The device sends the selected file to the server as an HTTP request.

[1017] Output: The file sent from the terminal arrives at the server.

[1018] Step 2: Analyze drawings and 3D models

[1019] Input: Files of architectural drawings and 3D models received by the server from the terminal.

[1020] Processing: The server uses CAD software or specialized analysis algorithms to analyze the received file. The file data is parsed to extract structural information such as walls and doors. End-to-end measurements and physical attributes (thickness, height, etc.) are identified.

[1021] Output: Structural information based on the analysis is obtained.

[1022] Step 3: Conduct a legal check

[1023] Input: Structural information extracted by the server.

[1024] Processing: The server checks the extracted structural information against building code standards, for example, checking whether the wall thickness meets the code standards and whether the door height is appropriate.

[1025] Output: The compliance check results are generated, clearly indicating compliance and non-compliance.

[1026] Step 4: Generate color and comfort advice

[1027] Input: Room structural information and color data analyzed by the server.

[1028] Processing: Based on the analysis results, the server generates advice on the color scheme and furniture placement in the room. For example, it generates advice such as, "The color in the living room is too bright, so we recommend changing it to a softer color."

[1029] Output: Color and comfort advice is generated.

[1030] Step 5: Recognizing user emotions with the emotion engine

[1031] Input: Camera and microphone data to collect the user's facial expressions and tone of voice.

[1032] Processing: The emotion engine uses the camera and microphone to collect and analyze the user's facial expressions and tone of voice, which in turn identifies the user's emotional state (e.g., stress, joy, surprise, etc.).

[1033] Output: An analysis result about the user's emotional state is generated.

[1034] Step 6: Advise the user and provide feedback

[1035] Input: Server-generated legal check results, color and comfort advice, and the user's emotional state via the emotion engine.

[1036] Processing: The server adjusts the displayed advice based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adds positive feedback such as "Don't worry, it's easy to fix." The device then displays the adjusted check results and advice on the user interface.

[1037] Output: The adjusted legal check results and advice are displayed on the user interface.

[1038] Step 7: User corrections and recheck

[1039] Input: Drawings and 3D model data that users modify based on the advice and feedback provided.

[1040] Processing: The user modifies the drawing or model according to the provided advice. Once the modifications are complete, the file is uploaded back to the server, where it is analyzed and checked for legal compliance again.

[1041] Output: New regulatory check results and advice are generated based on the revised drawings and 3D models.

[1042] (Application example 2)

[1043] 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."

[1044] Conventional autonomous vehicles lack a system that can adjust in real time the impact of factors such as interior layout and color scheme on the comfort of the driver and passengers. Furthermore, there is a lack of means to improve comfort by providing feedback or advice based on the user's emotions while in the vehicle. This can easily lead to stressful situations for the user, resulting in a lower quality driving experience. Therefore, the present invention aims to solve these problems and provide a new system that can adapt to the user's emotions while maintaining a more comfortable environment inside an autonomous vehicle.

[1045] 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.

[1046] In this invention, the server includes means for receiving drawings and 3D models, means for checking the received drawings and 3D models against legal standards, means for generating and displaying the comparison results, means for generating advice regarding color schemes and comfort, means for displaying the generated advice, means including an emotion engine for recognizing the user's emotions, and means for dynamically adjusting the advice and display content based on the user's emotional state. This makes it possible to maintain a comfortable environment inside an autonomous vehicle in real time, reduce stress felt by the user, and provide a better driving experience.

[1047] "Drawings and 3D models" are digital data representing architectural or spatial design drawings and three-dimensional shapes that users provide to the system.

[1048] "Means for receiving" refers to devices and software that have the function of receiving data such as drawings and three-dimensional models uploaded by users.

[1049] "Means for checking" refers to equipment and software that compares received drawings and 3D models with existing standards and regulations to check for compliance.

[1050] "Means for generating and displaying" refers to devices and software that create information based on analysis results and advice and visually present it to users.

[1051] The "means for generating color and comfort advice" refers to devices and software that generate recommendations to users regarding the color and layout of a space based on the results of analysis of drawings and three-dimensional models.

[1052] An "emotion engine" is a device and software that identifies emotions from a user's facial expressions, voice, etc. and analyzes the data.

[1053] "Dynamic adjusting means" refers to devices and software for changing in real time the content and manner of advice or information presented based on the user's emotional state.

[1054] "Real-time" refers to data processing and information being provided immediately when a user uses the system.

[1055] An "autonomous vehicle" is a vehicle that is driven automatically by a system without the need for driver operation.

[1056] The present invention relates to a system that maintains a comfortable environment inside an autonomous vehicle while adapting based on the emotional state of the user. Specific embodiments of the system are described below.

[1057] 1. Receiving drawings and 3D models

[1058] The server receives images and 3D models of the interior of the autonomous vehicle in real time via smart glasses or a head-mounted display (HMD), which allows it to collect data on the interior layout and color scheme.

[1059] 2. Data analysis and legal checks

[1060] The server analyzes the received images and models to extract interior data for the vehicle. It uses the open-source libraries OpenCV and dlib for image analysis, and the DesignAnalysis library to analyze spatial layout and color data. The analysis results are compared with pre-set legal standards.

[1061] 3. Providing advice on color schemes and comfort

[1062] The server generates advice on color schemes and comfort based on the analysis results. For example, if the lighting is too bright, the server may provide advice such as "We recommend dimming the lights a little." If the seat position is inappropriate, the server may provide advice such as "We recommend moving your seat forward a little."

[1063] 4. Recognition of user emotions using an emotion engine

[1064] The server uses sensors built into the smart glasses or HMD to recognize emotions from the user's facial expressions and tone of voice. The EmotionRecognition library is used for this emotion recognition. The recognized emotion data is sent to the server for analysis.

[1065] 5. Emotional Adaptation

[1066] The server adjusts the generated advice and display content based on the user's emotional data. For example, it provides suggestions for stress reduction to a user who is feeling stressed, and includes positive feedback to a user who is feeling happy. This allows the user to continue driving in a comfortable state.

[1067] 6. Presenting the results to the user

[1068] The device displays the generated advice and tailored feedback in real time via smart glasses or an HMD, allowing the user to review the displayed content and implement the system's suggestions as needed.

[1069] Specific examples

[1070] Example 1: Adjusting the lighting

[1071] If the user feels that the lighting in the autonomous vehicle is too bright, the server generates and displays advice such as "We recommend that you dim the lights a little." If the user feels stressed, the server provides additional feedback such as "Dim the lights to relax."

[1072] Example 2: Seating arrangement

[1073] If the user is dissatisfied with the seating position in the car, the server will provide advice such as "If you move your seat a little forward, you will have more leg room." If the emotion engine recognizes the user's joy, the server will add a positive message such as "This positioning will make you even more comfortable."

[1074] Prompt Sentence Examples

[1075] "If I feel the colors in my car are too bright, can you suggest how I should change the settings?"

[1076] "How can I optimize my seat position to increase legroom?"

[1077] This enables the system to maintain a comfortable environment inside the autonomous vehicle while providing appropriate advice and feedback in real time based on the user's emotions.

[1078] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1079] Step 1:

[1080] The smart glasses or HMD captures images of the interior of the vehicle and sends the data to a server. The input is the image data captured by the smart glasses or HMD, and the output is the image data sent to the server. This image data includes the layout and color scheme of the interior of the vehicle.

[1081] Step 2:

[1082] The server analyzes the received image data. The OpenCV and dlib libraries are used for the analysis. Specifically, the necessary interior structural information is extracted from the image and color scheme data is identified. The input is the received image data, and the output is the analysis results.

[1083] Step 3:

[1084] The server uses the DesignAnalysis library to compare the extracted structural information with the legal standards. The comparison results clearly show which parts comply with the law and which do not. The input is the analysis result obtained in step 2, and the output is the result of the legal check.

[1085] Step 4:

[1086] The server generates color and comfort advice. A generative AI model is used to create recommendations based on interior color and layout. The input is the results of legal checks and analysis, and the output is specific advice.

[1087] Step 5:

[1088] The server uses the emotion engine to analyze the user's facial expressions and tone of voice received from the smart glasses or HMD and recognize the user's emotions. The input is the user's facial expression data and tone of voice data, and the output is the emotion recognition result.

[1089] Step 6:

[1090] The server dynamically adjusts the generated advice and display content based on the user's emotion recognition results. For example, it adds a recommendation to relax to a user who is feeling stressed, while adding positive feedback to a user who is feeling happy. The input is the emotion recognition results and the generated advice, and the output is the adjusted advice or notification.

[1091] Step 7:

[1092] The device displays tailored advice and notifications to the user in real time through smart glasses or an HMD. The user reviews the displayed information and implements the system's suggestions as needed. The input is the tailored advice and notifications, and the output is a visual presentation to the user.

[1093] Through these processing steps, the system can provide appropriate advice and feedback according to the user's emotions while maintaining a comfortable environment inside the autonomous vehicle.

[1094] 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.

[1095] 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.

[1096] 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.

[1097] [Fourth embodiment]

[1098] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1099] 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.

[1100] 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).

[1101] 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.

[1102] 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.

[1103] 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).

[1104] 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.

[1105] 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.

[1106] 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.

[1107] 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.

[1108] 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.

[1109] 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.

[1110] 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."

[1111] The present invention relates to a system that receives drawings and 3D models, analyzes them, checks them for legal regulations, and generates advice on color schemes and comfort. Specific embodiments of the system are described below.

[1112] 1. Upload and analyze drawings

[1113] First, the user uploads a blueprint or 3D model from their device. The device generates a request to send the selected file to the server, and sends the file data to the server. The server analyzes the received blueprint or 3D model and extracts structural information such as walls and doors. At this time, the server checks whether each element complies with the standards set out in building regulations.

[1114] 2. Generate and send legal check results

[1115] The server generates a matching result based on the analysis results. For example, it checks whether the wall thickness is within legal limits, whether the door height is appropriate, etc. The matching result is generated in a way that clearly shows which parts comply with the law and which parts do not. The generated matching result is sent to the terminal so that the user can check it.

[1116] 3. Providing advice on color schemes and comfort

[1117] Based on the analysis results, the server generates advice on color schemes and comfort, including, for example, whether the room color is visually less tiring, whether the furniture arrangement is comfortable, etc. The generated advice is converted into a format for display to the user and sent to the terminal.

[1118] 4. User Presentation and Interaction

[1119] The terminal displays the received matching results and advice on the user interface. The user can review them and modify the drawings or 3D models as necessary. The modified drawings or 3D models are then uploaded back to the server, where they undergo the same process of checking and receiving advice.

[1120] Specific examples

[1121] A specific scenario is shown below.

[1122] Case 1: Wall Thickness Check

[1123] The user uploads a drawing file of a new building from their terminal to the system. The server receives the drawing file and performs an analysis. The analysis extracts the wall thickness. This is then compared with the legal standard, and the user is shown a message saying, "The wall thickness exceeds the legal standard. Corrections are required." The user can correct the wall thickness and upload it again to have it checked again.

[1124] Case 2: Color Advice

[1125] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color-scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." The user then adjusts the color scheme of the design accordingly.

[1126] The system of the present invention significantly reduces the time and cost involved in the proposal phase of a construction project by automatically checking regulatory standards and providing design advice, allowing users to efficiently improve regulatory compliance and design.

[1127] The processing flow will be explained below.

[1128] Step 1:

[1129] A user selects a drawing file or a 3D model on a terminal and presses an upload button. The terminal generates a request to send the selected file to the server. The request includes the file data and associated metadata.

[1130] Step 2:

[1131] The device sends the request to the server using the HTTP protocol, etc. The server receives the request and saves the uploaded file in local storage.

[1132] Step 3:

[1133] The server analyzes the received drawing file or 3D model using algorithms that read the file and identify and extract structural elements such as walls, doors, windows, etc. The extracted information is stored in a database.

[1134] Step 4:

[1135] The server compares the extracted structural information with legal standards, for example, checking whether the wall thickness is within legal standards and whether the door height is appropriate. These standards are stored in a database in advance and are compared with the extracted information.

[1136] Step 5:

[1137] The server generates a matching result, which clearly shows which parts of the document comply with the law and which parts do not. For non-compliant parts, the result includes specific corrections and recommended changes.

[1138] Step 6:

[1139] The server converts the results of the matching process into a display format, such as HTML or JSON, and prepares the results for transmission to the device. The converted data is then organized in a format that is easy for the user to understand.

[1140] Step 7:

[1141] The server sends the converted matching results to the terminal, which processes the received data to display it on the user interface. The user checks the displayed matching results and determines whether any inconsistencies need to be corrected.

[1142] Step 8:

[1143] The server generates color and comfort advice based on the analyzed design data, creating advice on color balance, furniture placement, and more. This includes algorithms that suggest color schemes that reduce visual fatigue and placement advice to provide a comfortable user environment.

[1144] Step 9:

[1145] The server converts the generated advice into a presentation format, organizing it in a user-friendly way and converting it into HTML or JSON.

[1146] Step 10:

[1147] The server sends the converted advice to the terminal, which processes the received advice to display it on the user interface. The user can use the displayed advice to improve the design.

[1148] Example 1

[1149] 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."

[1150] In architectural projects, it is important to efficiently check the legal compliance of drawings and 3D models and provide advice on the comfort of the design. However, manual checks and advice are time-consuming and costly. Furthermore, because specialized knowledge is required, it is often difficult to provide appropriate advice. The present invention aims to solve these problems and provide a system that automatically and efficiently checks legal compliance and provides advice on comfort.

[1151] 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.

[1152] In this invention, the server includes means for receiving drawings and 3D models, means for analyzing the received drawings and 3D models to extract structures such as walls and doors, means for checking the extracted structures against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, and means for displaying the generated advice. This automates the process of checking legal compliance and improving designs in architectural projects, reducing time and costs, and making it possible to obtain appropriate advice even without specialized knowledge.

[1153] "Drawings and three-dimensional models" refer to floor plans and three-dimensional drawings, as well as the digital data thereof, that represent the structure and layout of a building or design object.

[1154] "Means for receiving" refers to a mechanism or method for importing drawing or three-dimensional model data from a user into the server.

[1155] "Means of analysis" refers to the mechanisms and software used to process received drawings and three-dimensional model data and extract structural information such as walls and doors.

[1156] The "means for extraction" is a function for extracting and identifying specific elements (e.g., walls, doors, etc.) from the analyzed data.

[1157] The "means of matching" is a method for comparing the extracted structural information with legally defined standards to confirm the degree of agreement.

[1158] The "means of checking" is a system for evaluating the compliance of each element of a building based on legal standards.

[1159] "Means for generating" refers to the process for creating information and advice to be provided to the user based on the results of analysis and collation.

[1160] The "display means" refers to a device or interface for visually conveying the generated matching results and advice to the user.

[1161] "Color and comfort advice" means suggestions and instructions for improving the visual and functional comfort of a room's color and furniture arrangement.

[1162] A "user interface" is a screen or operating means through which a user interacts with a system and inputs and outputs information.

[1163] The "means for receiving again" refers to a mechanism or method for importing the data of drawings or three-dimensional models that have been modified into the server again.

[1164] "Means for rechecking" refers to the process of comparing revised drawings and three-dimensional models with the legal standards again to confirm compliance.

[1165] This invention relates to a system that automatically analyzes and evaluates compliance with regulations and design comfort using architectural drawings and 3D models, and provides the results to users. This system is composed of three entities: a server, a terminal, and a user. The overall system configuration and the role played by each entity are explained in detail below.

[1166] Hardware and Software Configuration

[1167] 1. Receiving drawings and 3D models

[1168] The user selects drawings or 3D models from the terminal and sends them to the server.

[1169] The terminal uploads the file selected by the user to the server using a protocol such as an HTTP request.

[1170] The server stores the received drawings and 3D models in storage (e.g., a disk drive or cloud storage).

[1171] 2. Analysis of drawings and 3D models

[1172] The server analyzes the stored data, for example, using AutoCAD API or BIM (Building Information Modeling) software.

[1173] An algorithm has been implemented to extract structural information such as walls and doors from the received data.

[1174] 3. Legal checks

[1175] The server checks the extracted structural information against the standard values ​​set by building regulations.

[1176] The check uses certain criteria (e.g. wall thickness, door height) and a matching algorithm evaluates whether the criteria are met.

[1177] 4. Generate and send legal check results

[1178] Based on the check results, the server generates a matching result that clearly indicates which parts comply with the law and which parts do not.

[1179] The generated matching results are converted into a user-viewable format (e.g., text report or graphical report) and sent to the terminal.

[1180] 5. Generate color and comfort advice

[1181] Based on the analysis results, the server generates advice on color schemes and comfort.

[1182] Advice can come in the form of, for example, a visual comfort rating or suggestions for furniture placement.

[1183] 6. Display and interaction on user devices

[1184] The terminal displays the received collation results and advice on a user interface.

[1185] The user can use this information to modify the drawings or 3D models and send them back to the server.

[1186] Specific examples

[1187] Case 1: Wall Thickness Check

[1188] A user uploads a drawing file of a new building to the system from their terminal. The server receives the drawing file and performs an analysis. The analysis extracts the wall thickness. This is then compared with the legal standard, and the user is shown a message such as, "The wall thickness does not meet the legal standard (current: 10cm, required: 12cm)." The user can then correct the wall thickness and upload it again to have it checked again.

[1189] Case 2: Color Advice

[1190] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color-scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." The user then adjusts the color scheme of the design accordingly.

[1191] Prompt Sentence Examples

[1192] "Please develop a system that analyzes the drawings of a new building and checks whether the wall thickness complies with regulations. Please also explain the specific check items and how to display the check results."

[1193] "Create a system that allows users to upload a room design model and provides color advice based on visual comfort. Explain how you would analyze the model and how you would provide the advice."

[1194] As described above, the present invention makes it possible to efficiently provide advice on legal compliance and design during the proposal phase of a construction project, thereby reducing time and costs.

[1195] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1196] Step 1:

[1197] Upload drawings and 3D models

[1198] The user uses the terminal to select a drawing or 3D model file and perform the upload operation. The terminal sends the selected file to the server via an HTTP request. The input is the drawing or model file selected by the user, and the output is the file being sent to the server. Specifically, the user presses the "Select File" button, selects a file (e.g., building_plan.dwg) from local storage, and clicks the "Upload" button.

[1199] Step 2:

[1200] Receiving and storing drawings and 3D models

[1201] The server receives the file sent from the terminal and saves the data in storage. The input is the file data sent from the terminal, and the output is the file saved in storage. Specifically, the server receives the HTTP request and saves the file in the specified directory. For example, the save location is / uploads / building_plan.dwg.

[1202] Step 3:

[1203] Analysis of drawings and 3D models

[1204] The server analyzes the saved files and extracts structural information such as walls and doors. This analysis uses AutoCAD API and BIM software. The input is the saved file, and the output is the extracted structural information. Specifically, the server calls the AutoCAD API and analyzes and extracts the location of walls, doors, etc. from the file.

[1205] Step 4:

[1206] Legal checks

[1207] The server checks the extracted structural information against the standard values ​​set by building regulations. Examples of criteria for checking include "wall thickness" and "door height." The input is the extracted structural information, and the output is the result of the check. Specifically, the server compares the wall thickness (e.g., 10 cm) with the standard value (e.g., 12 cm) and determines whether it meets the criteria.

[1208] Step 5:

[1209] Generate and send legal check results

[1210] Based on the results of the legal check, the server generates a legal compliance matching result and sends it to the terminal in a format that the user can understand. The input is the matched information, and the output is a report of the generated matching result. Specifically, the server generates a message such as "The wall thickness does not meet the legal standards (current: 10 cm, required: 12 cm)" and sends it to the terminal.

[1211] Step 6:

[1212] Generate color and comfort advice

[1213] The server generates advice on color schemes and comfort based on the analysis results. The input is the analysis results, and the output is the generated advice. Specifically, the server detects that the color of the living room is too bright and generates the advice, "We recommend changing the color of the living room to a softer color (e.g., pastel green)."

[1214] Step 7:

[1215] Display and interaction on user devices

[1216] The terminal displays the matching results and advice received on the user interface. The user can check the displayed information and modify the drawing or 3D model as necessary. The input is the results and advice sent from the server, and the output is the displayed content and input from the user (modified drawing or model). Specifically, the terminal screen displays the areas that need to be modified and recommended advice, and the user modifies the drawing again based on this information and returns to step 1.

[1217] The above is the specific flow of the program processing of this system.

[1218] (Application example 1)

[1219] 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."

[1220] Currently, there are limited ways to efficiently check and provide advice on regulatory compliance, comfort, and color schemes in the interior design of autonomous vehicles. Designers must manually check regulations and repeatedly try and error interior designs. This results in significant time and cost involved in the design process. Furthermore, there is a lack of real-time feedback, which can delay design revisions.

[1221] 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.

[1222] In this invention, the server includes means for receiving drawings and 3D models, means for checking the received drawings and 3D models against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, means for displaying the generated advice, and means for displaying the legal check and the advice on comfort and color schemes on a 3D display device. This enables designers to receive checks and advice on legal compliance, comfort, and color schemes in real time in the interior design of autonomous vehicles through a 3D display device such as smart glasses, significantly improving the efficiency of the design process.

[1223] "Drawings and 3D models" means static or dynamic visual data used to represent the interior structure of a building or vehicle.

[1224] "Legal standard values" refer to specific numerical values ​​and standards set forth in laws, regulations, and standards related to construction and design.

[1225] The "matching result" is a report of the results of the evaluation of the received drawings or three-dimensional models based on the legal standards, and indicates whether or not they comply with the law.

[1226] "Advice on color schemes and comfort" refers to guidance and suggestions on whether the color scheme of a space is visually pleasing and whether the layout of furniture and interior décor ensures user comfort.

[1227] "Display means" refers to hardware and software for visually displaying analysis results and advice on a user interface.

[1228] A "three-dimensional display device" is a device that can display information in three-dimensional space, such as smart glasses or a head-mounted display.

[1229] The "server" is a computer system that analyzes drawings and three-dimensional models, checks legal compliance, generates matching results, and provides advice on color schemes and comfort.

[1230] This invention is a system that receives drawings and 3D models, performs analysis and legal checks, and generates advice on color schemes and comfort. Specifically, it uses a server, terminals, and a 3D display device to enable designers to efficiently check and improve the interior design of autonomous vehicles.

[1231] Program Overview

[1232] In this system, the server executes programs and processes various data. The programs are as follows:

[1233] 1. Receiving drawings and 3D models

[1234] The user uploads drawings or 3D models from their device, and the device sends this file data to the server.

[1235] 2. Analysis of drawings and 3D models

[1236] The server analyzes the received drawings and 3D models to extract structural information about walls, doors, etc. The results of the analysis are compared with legal standards to check whether each element complies with the regulations.

[1237] 3. Generate and send legal check results

[1238] The server generates a matching result based on the analysis results, clearly indicating which parts comply with the law and which parts do not. The matching result is sent to the terminal so that the user can check it.

[1239] 4. Providing advice on color and comfort

[1240] From the analysis results, the server generates color and comfort advice, including suggestions on the visual impact of colors and the comfort of furniture placement.

[1241] 5. Display on a 3D display device

[1242] The server sends the generated matching results and advice to a 3D display device, where the user can view the information in real time.The user can visually check the interior of the vehicle using smart glasses or a head-mounted display (e.g., Microsoft HoloLens or Google Glass).

[1243] Hardware and software used

[1244] Hardware

[1245] Device: PC or smartphone

[1246] 3D display devices: smart glasses, head-mounted displays

[1247] software

[1248] Server program: Python

[1249] Data transmission: REST API

[1250] 3D modeling software: Autodesk Revit, etc.

[1251] Specific examples

[1252] Example 1: Interior design check

[1253] After a designer finishes designing the interior of an autonomous vehicle, they upload the model file from their device to a server. The server analyzes the model and generates advice on compliance, comfort, and color schemes, which are then sent to the smart glasses. While wearing the smart glasses, the designer can visually confirm this information in real time while walking around the vehicle and make any necessary design changes.

[1254] Prompt Sentence Examples

[1255] To ensure that the interior design of an autonomous vehicle complies with regulations, please analyze the following models and provide advice on color schemes and comfort:

[1256] 1. / path / to / car_interior_model.obj

[1257] Check the thickness of the wall in accordance with regulations.

[1258] Rate the comfort of the seating arrangement.

[1259] Analyze the visual effects of room colors and recommend color schemes that reduce fatigue.

[1260] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1261] Specific processing steps of the program

[1262] Step 1:

[1263] The user uploads a drawing or 3D model from their device. To do this, the user uses a dedicated application to select the target drawing or 3D model file from a file dialog. Once the data is selected, the device generates a request to send it to the server. Input: Drawing or 3D model file. Output: A request is generated to send the file data to the server.

[1264] Step 2:

[1265] The server analyzes the received drawings and 3D models. When the server receives the files, it applies a specific analysis algorithm to extract structural information (walls, doors, etc.). Input: Uploaded drawings and 3D model files. Output: Extracted structural information.

[1266] Step 3:

[1267] The server compares the analyzed structural information with legal standards. Using a comparison algorithm, it evaluates whether each extracted element complies with the law. Input: Structural information, legal standard data. Output: Evaluation result of legal compliance.

[1268] Step 4:

[1269] The server generates a matching result report based on the evaluation results of the legal check. The report clearly shows which parts are compliant and which parts are not. Input: Legal compliance evaluation result. Output: Matching result report.

[1270] Step 5:

[1271] The server sends a matching result report to the terminal and the 3D display device, which visually presents this information to the user. Input: Matching result report. Output: Display data on the user interface and the 3D display device.

[1272] Step 6:

[1273] The server generates advice on color schemes and comfort based on the analysis results. It uses a generative AI model to provide detailed suggestions on visual impact and comfort. Input: Structural information, generative AI model. Output: Advice on color schemes and comfort.

[1274] Step 7:

[1275] The generated advice is sent from the server to the terminal and the 3D display device, which visually display the advice so that the user can check it in real time. Input: Advice on color scheme and comfort. Output: Display data on the user interface and the 3D display device.

[1276] Step 8:

[1277] The user wears smart glasses and receives real-time feedback through a 3D display, allowing for immediate corrections for compliance, comfort, and color scheme. Input: Feedback information from the 3D display. Output: Real-time design corrections.

[1278] 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.

[1279] The present invention relates to a system that receives blueprints and 3D models, analyzes them, checks them for legal compliance, and generates advice on color schemes and comfort, in addition to a system that combines an emotion engine that recognizes the user's emotions. Specific embodiments of the system are described below.

[1280] 1. Upload and analyze drawings

[1281] First, the user uploads a blueprint or 3D model from their device. The device generates a request to send the selected file to the server, and sends the file data to the server. The server analyzes the received blueprint or 3D model and extracts structural information such as walls and doors. At this time, the server checks whether each element complies with the standards set out in building regulations.

[1282] 2. Generate and send legal check results

[1283] The server generates a matching result based on the analysis results. For example, it checks whether the wall thickness is within legal limits, whether the door height is appropriate, etc. The matching result is generated in a way that clearly shows which parts comply with the law and which parts do not. The generated matching result is sent to the terminal so that the user can check it.

[1284] 3. Providing advice on color schemes and comfort

[1285] Based on the analysis results, the server generates advice on color schemes and comfort, including, for example, whether the room color is visually less tiring, whether the furniture arrangement is comfortable, etc. The generated advice is converted into a format for display to the user and sent to the terminal.

[1286] 4. Emotion Engine for Recognizing and Adapting to User Emotions

[1287] The system incorporates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice. The emotion engine analyzes the user's current emotional state (e.g., stress, joy, surprise, etc.). The recognized emotions are sent to the server, and advice and user interface display content are dynamically adjusted.

[1288] 5. User Presentation and Interaction

[1289] The device displays the received matching results and advice on the user interface. If the user feels emotionally stressed, the emotion engine recognizes this and the server adjusts the content presented to allow the user to use the system comfortably. For example, a user feeling stressed may be presented with advice displayed in softer colors or with positive feedback. If the user modifies the drawing or 3D model based on the confirmation and advice, the modified data is uploaded back to the server and rechecked using the same process.

[1290] Specific examples

[1291] Case 1: Wall thickness check and user emotion adaptation

[1292] The user uploads a blueprint file of a new building to the system from their device. The server receives the blueprint file and analyzes it. The analysis extracts the wall thickness. This is then compared with the legal standard, and a message is displayed to the user, such as, "The wall thickness exceeds the legal standard. Correction is required." If the emotion engine detects stress from the user's facial expression, the server displays additional positive feedback, such as, "Don't worry, it's easy to correct."

[1293] Case 2: Color Advice and Emotional Adaptation

[1294] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. The server generates color scheme advice and provides it to the user, such as "The color in the living room is too bright, so we recommend changing it to a softer color." If the emotion engine recognizes the user's emotion of happiness, the server adds a positive message, such as "This color scheme will make your room look even better."

[1295] The system of the present invention improves the experience during the proposal phase of a construction project by automatically checking regulatory standards and providing design advice, as well as recognizing and responding to user emotions, allowing users to efficiently and comfortably improve regulatory compliance and design.

[1296] The processing flow will be explained below.

[1297] Step 1:

[1298] A user selects a drawing file or a 3D model on a terminal and presses an upload button. The terminal generates a request to send the selected file to the server. The request includes the file data and associated metadata.

[1299] Step 2:

[1300] The device sends the request to the server using the HTTP protocol, etc. The server receives the request and saves the uploaded file in local storage.

[1301] Step 3:

[1302] The server analyzes the received drawing file or 3D model using algorithms that read the file and identify and extract structural elements such as walls, doors, windows, etc. The extracted information is stored in a database.

[1303] Step 4:

[1304] The server compares the extracted structural information with legal standards, for example, checking whether the wall thickness is within legal standards and whether the door height is appropriate. These standards are stored in a database in advance and are compared with the extracted information.

[1305] Step 5:

[1306] The server generates a matching result, which clearly shows which parts of the document comply with the law and which parts do not. For non-compliant parts, the result includes specific corrections and recommended changes.

[1307] Step 6:

[1308] The server converts the results of the matching process into a display format, such as HTML or JSON, and prepares the results for transmission to the device. The converted data is then organized in a format that is easy for the user to understand.

[1309] Step 7:

[1310] The server sends the converted matching results to the terminal, which processes the received data to display it on the user interface. The user checks the displayed matching results and determines whether any inconsistencies need to be corrected.

[1311] Step 8:

[1312] The server generates color and comfort advice based on the analyzed design data, creating advice on color balance, furniture placement, and more. This includes algorithms that suggest color schemes that reduce visual fatigue and placement advice to provide a comfortable user environment.

[1313] Step 9:

[1314] The server converts the generated advice into a presentation format, organizing it in a user-friendly way and converting it into HTML or JSON.

[1315] Step 10:

[1316] The server sends the converted advice to the terminal, which processes the received advice to display it on the user interface. The user can use the displayed advice to improve the design.

[1317] Step 11:

[1318] The emotion engine installed in the device analyzes the user's facial expressions and tone of voice to recognize emotions. For example, the device uses a camera or microphone to capture the user's facial expressions and voice data.

[1319] Step 12:

[1320] The emotion engine analyzes the emotion data and sends it to the server. For example, if the user is feeling stressed, that information is sent to the server.

[1321] Step 13:

[1322] The server adjusts the advice and feedback it provides to users based on the emotion data it receives. For example, if a user is feeling stressed, it might display advice in softer colors and provide positive feedback messages.

[1323] Step 14:

[1324] The device displays the adjusted advice and feedback in the user interface, allowing the user to review the displayed content and modify the drawing or 3D model as needed.

[1325] Step 15:

[1326] If the user modifies the drawing or 3D model, the modified data is uploaded to the server again, where it is rechecked through the same process and the user is provided with new matching results and advice.

[1327] In this way, the system of the present invention not only automatically checks legal standards and provides design advice, but also improves the user experience by recognizing and responding appropriately to user emotions.

[1328] Example 2

[1329] 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."

[1330] Modern construction projects require rapid verification of design and construction compliance. However, doing this manually takes a significant amount of time and requires experts to provide advice on design comfort and color schemes. Furthermore, advice is often provided without taking into account the user's emotional state, resulting in a poor user experience.

[1331] 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.

[1332] In this invention, the server includes means for receiving drawings and 3D models, means for analyzing the received drawings and 3D models, means for checking the analyzed information against legal standards, means for generating and displaying the comparison results, means for generating advice on color schemes and comfort, means for displaying the generated advice on a user interface, means for recognizing a user's emotion using an emotion engine, and means for adjusting the display content based on the recognized emotion. This makes it possible to check legal compliance in construction projects, automatically provide advice on the comfort of designs and color schemes, and provide feedback adapted to the user's emotions.

[1333] "Drawings and 3D models" are digital or analog information that represents a building or design in two or three dimensions.

[1334] The "receiving means" refers to a method or device for obtaining data transmitted from a terminal via a network.

[1335] "Means for analysis" refers to the process or software that deciphers the content of the received data and extracts structural information and various attributes.

[1336] "Means for checking against legal standards" refers to algorithms or programs that compare analyzed information with the standards of existing laws and regulations to confirm compliance.

[1337] The "means for generating and displaying the matching results" is a mechanism for compiling the check results into a format that is easy for the user to understand and displaying them on a display or the like.

[1338] The "means for generating color and comfort advice" refers to an algorithm or AI model that uses the user's design data to create suggestions for more comfortable and visually appealing color schemes and placements.

[1339] "Means for displaying on a user interface" refers to a method for presenting the generated advice and check results through an interface that can be viewed and operated by the user.

[1340] An "emotion engine" is software or hardware that analyzes a user's emotions from their facial expressions, tone of voice, etc., and identifies their state.

[1341] The "means for recognizing user emotions" is a process of detecting the user's emotions using an emotion engine and obtaining the analysis results.

[1342] The "means for adjusting the display content based on the recognized emotion" refers to an algorithm or program that flexibly changes the advice provided and the display method according to the user's emotional state.

[1343] This invention is a system that receives drawings and three-dimensional models, analyzes them, checks them for legal requirements, and generates advice on color schemes and comfort, in addition to a system that combines an emotion engine that recognizes the user's emotions.

[1344] Hardware and software used

[1345] Device: A PC or smartphone is typically used, which includes the ability to upload files and a display to show the user interface.

[1346] Server: A central processing unit that analyzes data, checks laws and regulations, generates advice, and analyzes emotions. It is equipped with CAD software, specialized analysis algorithms, and an emotion engine.

[1347] Emotion engine: Software that uses a camera and microphone to collect and analyze the user's facial expressions and tone of voice.

[1348] Specific processing flow

[1349] 1. Upload drawings and 3D models

[1350] A user uses a terminal to select a file of architectural drawings or a 3D model and clicks the upload button. The terminal generates an HTTP request and sends the file data to the server.

[1351] 2. Analysis of drawings and 3D models

[1352] The server analyzes the received file data using CAD software and specialized analysis algorithms. As a result of the analysis, structural information such as walls and doors is extracted, and measurements between endpoints and physical attributes (thickness, height, etc.) are identified.

[1353] 3. Legal checks

[1354] The server compares the extracted structural information with the building code standards. For example, it checks whether the wall thickness meets the legal standards and whether the door height is appropriate. The results of the legal check are summarized and displayed in a user-friendly format.

[1355] 4. Generate color and comfort advice

[1356] Based on the analysis results, the server generates advice on room colors and furniture placement. For example, it generates advice such as, "The color of the living room is too bright, so we recommend changing it to a softer color," and displays it to the user.

[1357] 5. Recognition of user emotions by emotion engine

[1358] The emotion engine uses a camera and microphone to collect and analyze the user's facial expressions and tone of voice, and sends the analysis results to a server to identify the user's emotions.

[1359] 6. Providing advice and feedback to users

[1360] The server adjusts the content and display of advice based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adds positive feedback such as "Don't worry, it's easy to fix." The information received by the device is displayed in the user interface.

[1361] Specific examples

[1362] Case 1: Wall thickness check and user emotion adaptation

[1363] The user uploads a blueprint file for a new building to the system from their device. The server receives the blueprint file and analyzes it. The analysis extracts the wall thickness. The result is compared with the legal standard value, and a message is displayed saying, "The wall thickness exceeds the legal standard. Corrections are required." If the emotion engine senses stress from the user's facial expression, the server adds positive feedback such as, "Don't worry, it's easy to correct."

[1364] Example prompt sentence:

[1365] Upload a new building drawing file into the system and receive a report with analysis results, including code checks on wall thickness, and feedback based on user sentiment.

[1366] Case 2: Color Advice and Emotional Adaptation

[1367] A user uploads a new room interior design model to the system. The server analyzes the model and extracts color data for each room. It generates color advice, such as "The colors in the living room are too bright, so we recommend changing them to softer colors." If the emotion engine recognizes the user's happy emotion, the server adds a positive message, such as "This color scheme will make your room look even better."

[1368] Example prompt sentence:

[1369] Upload a new room interior design model to the system, and receive analysis results that suggest color schemes for the room and provide feedback based on the user's emotions.

[1370] The system of the present invention is designed to help users check the compliance of their construction projects and improve their designs efficiently and comfortably, and it can enhance the user experience by responding flexibly to the user's emotional state.

[1371] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1372] Step 1: Upload your drawings or 3D models

[1373] Input: The user selects architectural drawings or 3D models from the terminal's file selection interface.

[1374] Process: The user clicks the "Upload" button. The device sends the selected file to the server as an HTTP request.

[1375] Output: The file sent from the terminal arrives at the server.

[1376] Step 2: Analyze drawings and 3D models

[1377] Input: Files of architectural drawings and 3D models received by the server from the terminal.

[1378] Processing: The server uses CAD software or specialized analysis algorithms to analyze the received file. The file data is parsed to extract structural information such as walls and doors. End-to-end measurements and physical attributes (thickness, height, etc.) are identified.

[1379] Output: Structural information based on the analysis is obtained.

[1380] Step 3: Conduct a legal check

[1381] Input: Structural information extracted by the server.

[1382] Processing: The server checks the extracted structural information against building code standards, for example, checking whether the wall thickness meets the code standards and whether the door height is appropriate.

[1383] Output: The compliance check results are generated, clearly indicating compliance and non-compliance.

[1384] Step 4: Generate color and comfort advice

[1385] Input: Room structural information and color data analyzed by the server.

[1386] Processing: Based on the analysis results, the server generates advice on the color scheme and furniture placement in the room. For example, it generates advice such as, "The color in the living room is too bright, so we recommend changing it to a softer color."

[1387] Output: Color and comfort advice is generated.

[1388] Step 5: Recognizing user emotions with the emotion engine

[1389] Input: Camera and microphone data to collect the user's facial expressions and tone of voice.

[1390] Processing: The emotion engine uses the camera and microphone to collect and analyze the user's facial expressions and tone of voice, which in turn identifies the user's emotional state (e.g., stress, joy, surprise, etc.).

[1391] Output: An analysis result about the user's emotional state is generated.

[1392] Step 6: Advise the user and provide feedback

[1393] Input: Server-generated legal check results, color and comfort advice, and the user's emotional state via the emotion engine.

[1394] Processing: The server adjusts the displayed advice based on the analysis results of the emotion engine. For example, if the user is feeling stressed, the server adds positive feedback such as "Don't worry, it's easy to fix." The device then displays the adjusted check results and advice on the user interface.

[1395] Output: The adjusted legal check results and advice are displayed on the user interface.

[1396] Step 7: User corrections and recheck

[1397] Input: Drawings and 3D model data that users modify based on the advice and feedback provided.

[1398] Processing: The user modifies the drawing or model according to the provided advice. Once the modifications are complete, the file is uploaded back to the server, where it is analyzed and checked for legal compliance again.

[1399] Output: New regulatory check results and advice are generated based on the revised drawings and 3D models.

[1400] (Application example 2)

[1401] 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."

[1402] Conventional autonomous vehicles lack a system that can adjust in real time the impact of factors such as interior layout and color scheme on the comfort of the driver and passengers. Furthermore, there is a lack of means to improve comfort by providing feedback or advice based on the user's emotions while in the vehicle. This can easily lead to stressful situations for the user, resulting in a lower quality driving experience. Therefore, the present invention aims to solve these problems and provide a new system that can adapt to the user's emotions while maintaining a more comfortable environment inside an autonomous vehicle.

[1403] 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.

[1404] In this invention, the server includes means for receiving drawings and 3D models, means for checking the received drawings and 3D models against legal standards, means for generating and displaying the comparison results, means for generating advice regarding color schemes and comfort, means for displaying the generated advice, means including an emotion engine for recognizing the user's emotions, and means for dynamically adjusting the advice and display content based on the user's emotional state. This makes it possible to maintain a comfortable environment inside an autonomous vehicle in real time, reduce stress felt by the user, and provide a better driving experience.

[1405] "Drawings and 3D models" are digital data representing architectural or spatial design drawings and three-dimensional shapes that users provide to the system.

[1406] "Means for receiving" refers to devices and software that have the function of receiving data such as drawings and three-dimensional models uploaded by users.

[1407] "Means for checking" refers to equipment and software that compares received drawings and 3D models with existing standards and regulations to check for compliance.

[1408] "Means for generating and displaying" refers to devices and software that create information based on analysis results and advice and visually present it to users.

[1409] The "means for generating color and comfort advice" refers to devices and software that generate recommendations to users regarding the color and layout of a space based on the results of analysis of drawings and three-dimensional models.

[1410] An "emotion engine" is a device and software that identifies emotions from a user's facial expressions, voice, etc. and analyzes the data.

[1411] "Dynamic adjusting means" refers to devices and software for changing in real time the content and manner of advice or information presented based on the user's emotional state.

[1412] "Real-time" refers to data processing and information being provided immediately when a user uses the system.

[1413] An "autonomous vehicle" is a vehicle that is driven automatically by a system without the need for driver operation.

[1414] The present invention relates to a system that maintains a comfortable environment inside an autonomous vehicle while adapting based on the emotional state of the user. Specific embodiments of the system are described below.

[1415] 1. Receiving drawings and 3D models

[1416] The server receives images and 3D models of the interior of the autonomous vehicle in real time via smart glasses or a head-mounted display (HMD), which allows it to collect data on the interior layout and color scheme.

[1417] 2. Data analysis and legal checks

[1418] The server analyzes the received images and models to extract interior data for the vehicle. It uses the open-source libraries OpenCV and dlib for image analysis, and the DesignAnalysis library to analyze spatial layout and color data. The analysis results are compared with pre-set legal standards.

[1419] 3. Providing advice on color schemes and comfort

[1420] The server generates advice on color schemes and comfort based on the analysis results. For example, if the lighting is too bright, the server may provide advice such as "We recommend dimming the lights a little." If the seat position is inappropriate, the server may provide advice such as "We recommend moving your seat forward a little."

[1421] 4. Recognition of user emotions using an emotion engine

[1422] The server uses sensors built into the smart glasses or HMD to recognize emotions from the user's facial expressions and tone of voice. The EmotionRecognition library is used for this emotion recognition. The recognized emotion data is sent to the server for analysis.

[1423] 5. Emotional Adaptation

[1424] The server adjusts the generated advice and display content based on the user's emotional data. For example, it provides suggestions for stress reduction to a user who is feeling stressed, and includes positive feedback to a user who is feeling happy. This allows the user to continue driving in a comfortable state.

[1425] 6. Presenting the results to the user

[1426] The device displays the generated advice and tailored feedback in real time via smart glasses or an HMD, allowing the user to review the displayed content and implement the system's suggestions as needed.

[1427] Specific examples

[1428] Example 1: Adjusting the lighting

[1429] If the user feels that the lighting in the autonomous vehicle is too bright, the server generates and displays advice such as "We recommend that you dim the lights a little." If the user feels stressed, the server provides additional feedback such as "Dim the lights to relax."

[1430] Example 2: Seating arrangement

[1431] If the user is dissatisfied with the seating position in the car, the server will provide advice such as "If you move your seat a little forward, you will have more leg room." If the emotion engine recognizes the user's joy, the server will add a positive message such as "This positioning will make you even more comfortable."

[1432] Prompt Sentence Examples

[1433] "If I feel the colors in my car are too bright, can you suggest how I should change the settings?"

[1434] "How can I optimize my seat position to increase legroom?"

[1435] This enables the system to maintain a comfortable environment inside the autonomous vehicle while providing appropriate advice and feedback in real time based on the user's emotions.

[1436] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1437] Step 1:

[1438] The smart glasses or HMD captures images of the interior of the vehicle and sends the data to a server. The input is the image data captured by the smart glasses or HMD, and the output is the image data sent to the server. This image data includes the layout and color scheme of the interior of the vehicle.

[1439] Step 2:

[1440] The server analyzes the received image data. The OpenCV and dlib libraries are used for the analysis. Specifically, the necessary interior structural information is extracted from the image and color scheme data is identified. The input is the received image data, and the output is the analysis results.

[1441] Step 3:

[1442] The server uses the DesignAnalysis library to compare the extracted structural information with the legal standards. The comparison results clearly show which parts comply with the law and which do not. The input is the analysis result obtained in step 2, and the output is the result of the legal check.

[1443] Step 4:

[1444] The server generates color and comfort advice. A generative AI model is used to create recommendations based on interior color and layout. The input is the results of legal checks and analysis, and the output is specific advice.

[1445] Step 5:

[1446] The server uses the emotion engine to analyze the user's facial expressions and tone of voice received from the smart glasses or HMD and recognize the user's emotions. The input is the user's facial expression data and tone of voice data, and the output is the emotion recognition result.

[1447] Step 6:

[1448] The server dynamically adjusts the generated advice and display content based on the user's emotion recognition results. For example, it adds a recommendation to relax to a user who is feeling stressed, while adding positive feedback to a user who is feeling happy. The input is the emotion recognition results and the generated advice, and the output is the adjusted advice or notification.

[1449] Step 7:

[1450] The device displays tailored advice and notifications to the user in real time through smart glasses or an HMD. The user reviews the displayed information and implements the system's suggestions as needed. The input is the tailored advice and notifications, and the output is a visual presentation to the user.

[1451] Through these processing steps, the system can provide appropriate advice and feedback according to the user's emotions while maintaining a comfortable environment inside the autonomous vehicle.

[1452] 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.

[1453] 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.

[1454] 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 robot 414.

[1455] 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.

[1456] 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.

[1457] 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.

[1458] 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).

[1459] 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.

[1460] 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."

[1461] 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.

[1462] 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).

[1463] 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.

[1464] 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.

[1465] 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.

[1466] 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.

[1467] 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.

[1468] 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.

[1469] 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.

[1470] 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.

[1471] 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.

[1472] 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.

[1473] The following is further disclosed regarding the above embodiment.

[1474] (Claim 1)

[1475] means for receiving drawings or three-dimensional models;

[1476] A means of checking received drawings and 3D models against legal standards,

[1477] means for generating and displaying a match result;

[1478] means for generating color and comfort advice;

[1479] a means for displaying the generated advice;

[1480] A system including:

[1481] (Claim 2)

[1482] 10. The system of claim 1, further comprising means for analyzing drawings or three-dimensional models to extract structural information such as walls and doors.

[1483] (Claim 3)

[1484] 10. The system of claim 1, further comprising means for displaying the analysis results and advice in a user interface.

[1485] "Example 1"

[1486] (Claim 1)

[1487] means for receiving drawings or three-dimensional models;

[1488] A means to analyze received drawings and 3D models and extract structures such as walls and doors,

[1489] A means for checking the extracted structure against legal standards;

[1490] means for generating and displaying a match result;

[1491] means for generating color and comfort advice;

[1492] a means for displaying the generated advice;

[1493] A system including:

[1494] (Claim 2)

[1495] 10. The system of claim 1, further comprising means for displaying the analysis results and the legal check results on a user interface.

[1496] (Claim 3)

[1497] 2. The system according to claim 1, further comprising means for receiving drawings or three-dimensional models modified by a user and rechecking the drawings or three-dimensional models.

[1498] "Application Example 1"

[1499] (Claim 1)

[1500] means for receiving drawings or three-dimensional models;

[1501] A means of checking received drawings and 3D models against legal standards,

[1502] means for generating and displaying a match result;

[1503] means for generating color and comfort advice;

[1504] a means for displaying the generated advice;

[1505] a means for displaying legal checks and advice on comfort and color schemes on a three-dimensional display device;

[1506] A system including:

[1507] (Claim 2)

[1508] 10. The system of claim 1, further comprising means for analyzing drawings or three-dimensional models to extract structural information such as walls and doors.

[1509] (Claim 3)

[1510] 10. The system of claim 1, further comprising means for displaying the analysis results and advice on a user interface, and means for displaying the compliance, comfort, and color scheme of the three-dimensional model in real time on a three-dimensional display device.

[1511] "Example 2: Combining Emotion Engines"

[1512] (Claim 1)

[1513] means for receiving drawings or three-dimensional models;

[1514] means for analyzing received drawings and three-dimensional models;

[1515] A means of checking the analyzed information against legal standards,

[1516] means for generating and displaying a match result;

[1517] means for generating color and comfort advice;

[1518] means for displaying the generated advice on a user interface;

[1519] a means for recognizing a user's emotion with an emotion engine;

[1520] means for adjusting the displayed content based on the recognized emotion;

[1521] A system including:

[1522] (Claim 2)

[1523] 10. The system of claim 1, further comprising means for analyzing drawings or three-dimensional models to extract structural information such as walls and doors.

[1524] (Claim 3)

[1525] 10. The system of claim 1, further comprising means for displaying the analysis results and advice in a user interface.

[1526] "Application example 2 when combining emotion engines"

[1527] (Claim 1)

[1528] means for receiving drawings or three-dimensional models;

[1529] A means of checking received drawings and 3D models against legal standards,

[1530] means for generating and displaying a match result;

[1531] means for generating color and comfort advice;

[1532] a means for displaying the generated advice;

[1533] means including an emotion engine for recognizing an emotion of a user;

[1534] means for dynamically adjusting advice and display content based on the user's emotional state;

[1535] A system including:

[1536] (Claim 2)

[1537] 10. The system of claim 1, further comprising means for analyzing drawings or three-dimensional models to extract structural information such as walls and doors.

[1538] (Claim 3)

[1539] 10. The system of claim 1, further comprising means for displaying the analysis results and advice in a user interface. [Explanation of symbols]

[1540] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving drawings or three-dimensional models; A means of checking received drawings and 3D models against legal standards, means for generating and displaying a match result; means for generating color and comfort advice; a means for displaying the generated advice; A system including:

2. 10. The system of claim 1, further comprising means for analyzing drawings or three-dimensional models to extract structural information such as walls and doors.

3. The system of claim 1 further comprising means for displaying the analysis results and advice in a user interface.

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