system

Abstract

We provide the system. [Solution] A user registration means that allows a user to create an account by entering information, A data transmission means for sending uploaded data to an AI analysis engine, A feedback generation means that generates feedback based on the results of analysis by an AI analysis engine, A feedback notification method that notifies the user of feedback, A planning management system for saving and managing the generated final construction plan, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In construction work, there is a high possibility of an increase in rework man-hours, personal accidents due to insufficient consideration, and service disruptions. The causes lie in the complexity of laws, company regulations, and work-specific rules, and the fact that appropriate responses thereto depend on the skills of individual workers. In addition, there is a problem that efficient management is difficult because information such as order specifications, design considerations, estimated unit prices, construction precautions, and orderer's remarks covers a wide range.

Means for Solving the Problems

[0005] This invention solves these problems through a system that includes a user registration means for creating an account by inputting information by the user, a data transmission means for sending uploaded data to an AI analysis engine, a feedback generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, and a plan management means for saving and managing the generated final construction plan.

[0006] Furthermore, by including a means for users to re-upload their corrections to the system and a means for generating re-feedback that generates feedback based on the results of re-analysis and notifies the user, the correction and improvement process is streamlined, and compliance with laws, regulations, and company rules is systematically supported.

[0007] By including a data storage mechanism for temporarily storing user-uploaded data, the management of uploaded information is facilitated, and information necessary for analysis and re-analysis is appropriately maintained.

[0008] "User registration method" refers to the means by which a user enters their own information and creates an account within the system.

[0009] "Data transmission means" refers to the means by which data uploaded by the user is sent to the AI ​​analysis engine.

[0010] A "feedback generation method" is a means of generating feedback such as suggestions and warnings for the user based on the results analyzed by the AI ​​analysis engine.

[0011] A "feedback notification method" is a means of notifying the user of the generated feedback.

[0012] A "plan management system" is a means of saving the final construction plan created by the user and managing the progress of the project based on that plan.

[0013] The "method for submitting corrected data" is a means for users to re-upload data they have corrected based on feedback to the system.

[0014] A "re-feedback generation means" is a means for re-analyzing the corrected data and generating feedback again based on the results.

[0015] A "data storage method" is a means of temporarily storing data uploaded by a user. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Embodiments for Carrying out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the language used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the 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.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0030] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention relates to a system for improving the efficiency of operations in the construction industry. Specifically, it is a platform for efficiently carrying out construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules.

[0038] System Overview

[0039] First, the user accesses the system and creates an account. This involves entering basic information such as the company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[0040] Next, users can upload order specifications, design notes, estimated unit prices, construction precautions, and client comments to the system. The uploaded data is sent from the terminal to the server, which temporarily stores it before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[0041] The analysis results are generated as feedback and notified to the user from the server. The user can then make corrections based on this feedback and re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are also notified to the user as feedback.

[0042] Finally, after the user reviews all feedback and completes any necessary revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to support project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[0043] Specific example

[0044] The following is a specific scenario.

[0045] 1. User Registration

[0046] User: A representative from a construction company visits the system and creates an account. They enter the company name, contact person's name, email address, and password, and then press the submit button.

[0047] Server: Receives this information and stores it in the database. Sends a registration confirmation email to the user.

[0048] 2. Data Input

[0049] User: Upload the order specification document ("Order Specification.pdf") for a new construction project to the system.

[0050] Terminal: Sends uploaded data to the server.

[0051] Server: Temporarily stores data and sends it to the AI ​​analysis engine.

[0052] 3. AI analysis and feedback

[0053] Server: The AI ​​analysis engine analyzes the order specifications and determines, for example, that "the safety standards in Article 3 have not been met."

[0054] Server: Based on the analysis results, it generates a warning stating that "Article 3 of this order specification violates the latest safety standards."

[0055] Server: Sends the generated feedback to the user.

[0056] Device: Notifies the user of feedback.

[0057] 4. Project Management

[0058] User: Review the feedback and revise Article 3 of the order specification.

[0059] User: Re-upload the revised order specification to the system.

[0060] Terminal: Sends the corrected data to the server.

[0061] Server: Requests the AI ​​analysis engine to re-analyze the corrected data.

[0062] Server: Generates feedback again based on the re-analysis results.

[0063] Server: Sends further feedback to the user.

[0064] 5. Final confirmation and execution

[0065] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[0066] User: Upload the final construction plan to the system.

[0067] Terminal: Sends the final construction plan to the server.

[0068] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[0069] In this way, this invention supports the efficient progress of construction work. This system reduces rework, prevents personal injury and service disruptions, and improves the overall efficiency of operations.

[0070] The following describes the processing flow.

[0071] Step 1:

[0072] User: Access the system's website and view the registration form.

[0073] Step 2:

[0074] User: Enter company name, contact person's name, email address, and password, then submit.

[0075] Step 3:

[0076] Terminal: Sends the entered information to the server.

[0077] Step 4:

[0078] Server: Stores the received user information in the database.

[0079] Step 5:

[0080] Server: Sends a registration confirmation email to the user.

[0081] Step 6:

[0082] User: Opens a page to upload data files such as order specifications to the system.

[0083] Step 7:

[0084] User: Select the order specification document "Order Specification.pdf" and upload it.

[0085] Step 8:

[0086] Terminal: Sends uploaded data to the server.

[0087] Step 9:

[0088] Server: Temporarily stores data.

[0089] Step 10:

[0090] Server: Sends the stored data to the AI ​​analysis engine.

[0091] Step 11:

[0092] AI analysis engine: Performs analysis based on data and extracts important information based on laws, regulations, and company rules.

[0093] Step 12:

[0094] Server: Receives analysis results from the AI ​​analysis engine and generates feedback.

[0095] Step 13:

[0096] Server: Sends the generated feedback to the terminal.

[0097] Step 14:

[0098] Device: Notifies the user of feedback.

[0099] Step 15:

[0100] User: Review the feedback and make any necessary corrections.

[0101] Step 16:

[0102] User: Upload the revised order specification to the system again.

[0103] Step 17:

[0104] Terminal: Sends the corrected data to the server.

[0105] Step 18:

[0106] Server: Resends the corrected data to the AI ​​analysis engine.

[0107] Step 19:

[0108] AI analysis engine: Re-analyzes the corrected data and generates new feedback.

[0109] Step 20:

[0110] Server: Generates re-feedback based on the re-analysis results and sends it to the terminal.

[0111] Step 21:

[0112] Device: Notifies the user of further feedback.

[0113] Step 22:

[0114] User: Review all feedback and create the final construction plan.

[0115] Step 23:

[0116] User: Upload the final construction plan to the system.

[0117] Step 24:

[0118] Terminal: Sends the final construction plan to the server.

[0119] Step 25:

[0120] Server: Saves the final construction plan to the database.

[0121] Step 26:

[0122] Server: Manages project execution and progress, and notifies users as needed.

[0123] (Example 1)

[0124] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0125] In the construction industry, it is necessary to verify that many tasks comply with relevant laws, regulations, and unique work rules. This can lead to complexity, rework, and decreased efficiency. Furthermore, even during project execution, insufficient compliance with laws and regulations and inadequate progress management can lead to deviations from the plan and accidents. Therefore, there is a need for means to resolve these issues and achieve efficient and reliable work execution.

[0126] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0127] In this invention, the server includes a user registration means for creating an account by having the user input information, an information transmission means for transmitting uploaded data to an AI analysis engine, an evaluation generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, an evaluation notification means for notifying the user of the feedback, a plan management means for storing and managing the generated final plan, a legal compliance evaluation means for evaluating whether the plan complies with laws and regulations, and a progress monitoring means for managing the execution and tracking the progress of the project. This enables efficient and reliable planning and management of construction projects in compliance with laws and regulations, eliminates the complexity of the work, and simplifies progress management.

[0128] 1. "User registration method" refers to a means by which a user creates an account by entering information.

[0129] 2. "Information transmission means" refers to the means for transmitting uploaded data to the AI ​​analysis engine.

[0130] 3. "Evaluation generation means" refers to a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[0131] 4. "Evaluation notification means" refers to a means of notifying the user of the generated feedback.

[0132] 5. "Plan management means" refers to means for saving and managing the final plan that has been generated.

[0133] 6. "Methods for evaluating compliance with laws and regulations" are means for evaluating whether something complies with laws and regulations.

[0134] 7. "Progress monitoring means" refers to the means used for managing the execution and tracking the progress of a project.

[0135] This invention relates to a system for improving the efficiency of operations in the construction industry. Specifically, it is a platform for efficiently carrying out construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules.

[0136] The main components of this system include a server, terminals, and an AI analysis engine. The server includes means for user registration, information transmission, evaluation generation, evaluation notification, plan management, legal compliance evaluation, and progress monitoring.

[0137] The server manages user basic information and uploaded data using an SQL database. The AI ​​analysis engine analyzes data using machine learning libraries such as TENSORFLOW® and PyTorch. The terminal provides an interface for users to upload data and check feedback.

[0138] The following is a concrete example of the system.

[0139] User Registration

[0140] User: Access the system, enter the company name, contact person's name, email address, and password on the account creation screen, and click the register button.

[0141] Server: Receives the entered information and saves it to the database. It also generates and sends a registration confirmation email to the user.

[0142] Terminal: The user will receive a registration confirmation email.

[0143] Upload data

[0144] User: Drag and drop data such as order specifications, design notes, estimated unit prices, construction precautions, and client comments onto the system's upload screen, or select them using the file selection dialog.

[0145] Terminal: Sends the selected files to the server.

[0146] Server: Receives the file and stores it temporarily.

[0147] Temporary data storage and AI analysis request

[0148] Server: Sends temporarily stored data to the AI ​​analysis engine and requests analysis.

[0149] AI analysis and feedback generation

[0150] Server: The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and proprietary work rules.

[0151] Server: Receives analysis results and generates feedback based on them. For example, it might generate a warning such as, "Article 3 of this order specification violates the latest safety standards."

[0152] Server: Notifies the user of the feedback.

[0153] Reviewing feedback and correcting data

[0154] User: Check the feedback received from the server.

[0155] User: Based on feedback, revise data such as order specifications.

[0156] Request to re-upload corrected data and re-analyze it.

[0157] User: Re-upload the revised order specification to the system.

[0158] Terminal: Resend the corrected data to the server.

[0159] Server: Resubmits the corrected data to the AI ​​analysis engine and requests re-analysis.

[0160] Server: Receives re-analysis results and generates feedback again.

[0161] Server: Notifies the user of further feedback.

[0162] Uploading the final construction plan and project management

[0163] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[0164] User: Upload the final construction plan to the system.

[0165] Terminal: Sends files to the server.

[0166] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[0167] As a concrete example, the following prompt statement is shown:

[0168] Example of a prompt

[0169] 1. User Registration

[0170] I would like to create an account in the system. Please enter your company name, contact person's name, email address, and password.

[0171] 2. "Data Input

[0172] I have uploaded the order specifications for a new project. Please analyze this file.

[0173] 3. AI analysis and feedback

[0174] The analysis results for the order specifications are in. Article 3 violates safety standards and requires correction.

[0175] 4. "Further feedback"

[0176] I have reviewed the feedback and revised the order specifications. Please analyze it again.

[0177] 5. Final confirmation and execution

[0178] The final construction plan is complete. Uploading it to the system. Please begin project management.

[0179] In this way, this system supports the efficient progress of construction work. It enables efficient and reliable planning and management of construction projects in compliance with laws and regulations.

[0180] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0181] Step 1:

[0182] User Registration

[0183] User: Access the system, enter the company name, contact person's name, email address, and password on the account creation screen, and click the register button.

[0184] Server: Receives the entered information and saves it to the database. Executes the following SQL query: INSERT INTO users (company_name, contact_name, email, password) VALUES ('Company Name', 'Contact Person Name', 'Email Address', 'Password'). Generates a registration confirmation email and sends it to the user.

[0185] Input: Company name, contact person's name, email address, and password entered by the user.

[0186] Output: User information stored in the database, confirmation email sent to the user.

[0187] Terminal: The user's screen displays the message, "A registration confirmation email has been sent. Please check your email."

[0188] Step 2:

[0189] Upload data

[0190] User: Drag and drop data such as order specifications, design notes, estimated unit prices, construction precautions, and client comments onto the system's upload screen, or select them using the file selection dialog.

[0191] Terminal: Sends the file selected from the file selection dialog to the server using the multipart / form-data protocol.

[0192] Input: The file to be uploaded (e.g., "Order Specifications.pdf").

[0193] Output: File data sent to the server.

[0194] Server: Saves received file data to a temporary storage directory. For example, use the function store_temp_file('OrderSpecifications.pdf').

[0195] Input: File data sent from the terminal.

[0196] Output: Files saved in the temporary directory.

[0197] Step 3:

[0198] Temporary data storage and AI analysis request

[0199] Server: Sends temporarily stored data to the AI ​​analysis engine. Specifically, it uses the function `send_to_ai_engine('temp / order_specification_document.pdf')` to request analysis.

[0200] Input: Temporarily saved file data (e.g., "temp / order_specification.pdf").

[0201] Output: Analysis request sent to the AI ​​analysis engine.

[0202] Step 4:

[0203] AI analysis and feedback generation

[0204] Server: The AI ​​analysis engine analyzes the data and receives evaluation results on whether it complies with laws, company regulations, and proprietary work rules.

[0205] Input: Data sent to the AI ​​analysis engine.

[0206] Output: Evaluation results (e.g., feedback stating "Article 3 violates the latest safety standards").

[0207] Server: Generates feedback based on the analysis results and notifies the user. For example, it might generate a warning message stating, "Article 3 of this order specification violates the latest safety standards."

[0208] Input: Evaluation results from the AI ​​analysis engine.

[0209] Output: Feedback notified to the user.

[0210] Step 5:

[0211] Reviewing feedback and correcting data

[0212] User: Review the feedback received from the system and revise data such as order specifications.

[0213] Input: Feedback received from the system.

[0214] Output: Data such as the revised order specifications. Specifically, Article 3 of "Order Specifications.pdf" was modified in an editor to comply with the latest safety standards.

[0215] Step 6:

[0216] Request to re-upload corrected data and re-analyze it.

[0217] User: Upload the revised order specifications to the system again.

[0218] Input: Modified file (e.g., "Order Specification_v2.pdf").

[0219] Output: File data sent to the server.

[0220] Terminal: Sends modified data to the server using the multipart / form-data protocol.

[0221] Input: The modified file.

[0222] Output: File data sent to the server.

[0223] Server: Receives the modified data and saves it again to the temporary storage directory. For example, store_temp_file('Order Specification_v2.pdf').

[0224] Input: Modified file data sent from the terminal.

[0225] Output: The file has been resaved to the temporary directory.

[0226] Server: Resends the corrected data to the AI ​​analysis engine and requests re-analysis. Specifically, it calls send_to_ai_engine('temp / order_specification_v2.pdf').

[0227] Input: Re-saved modified file data.

[0228] Output: Analysis request resent to the AI ​​analysis engine.

[0229] Server: Receives the re-analysis results, generates feedback again, and notifies the user. For example, it might generate feedback stating, "All items comply with the latest safety standards."

[0230] Input: Re-evaluation results from the AI ​​analysis engine.

[0231] Output: Further feedback notified to the user.

[0232] Step 7:

[0233] Uploading the final construction plan and project management

[0234] User: Create the final construction plan based on the final feedback.

[0235] Input: Final feedback.

[0236] Output: Final Construction Plan (Example: "Final Construction Plan.pdf").

[0237] User: Upload the final construction plan to the system.

[0238] Input: Final construction plan.

[0239] Output: Sending plan data to the server.

[0240] Terminal: Sends the final construction plan to the server using the multipart / form-data protocol.

[0241] Input: Final construction plan.

[0242] Output: Sending plan data to the server.

[0243] Server: Receives the final construction plan and saves it to the plan management directory. For example, store_final_plan('final_construction_plan.pdf').

[0244] Input: Plan data sent from the terminal.

[0245] Output: The final construction plan saved in the save directory.

[0246] Server: Records necessary information and monitors project progress in order to initiate project execution management and progress tracking.

[0247] Input: Final construction plan.

[0248] Output: Progress monitoring data for project management.

[0249] (Application Example 1)

[0250] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0251] In traditional construction work, a major challenge has been the time-consuming and laborious process of manually verifying compliance with legal regulations, company rules, and unique work procedures. Furthermore, similar problems are more likely to occur during factory work, making it difficult to adhere to safety standards. As a result, there are challenges such as decreased work efficiency and an increased risk of personal injury and service disruptions.

[0252] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0253] In this invention, the server includes a user registration means for creating an account by having the user input information, a data transmission means for sending uploaded data to an AI analysis engine, a feedback display means for displaying feedback on a smart device in real time, a feedback generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, and a plan management means for saving and managing the generated final construction plan. As a result, the user can receive accurate feedback in real time that complies with laws and regulations, company rules, and unique work rules, enabling them to carry out their work safely and efficiently.

[0254] "User registration method" refers to a means by which a user creates an account by entering information.

[0255] "Data transmission means" refers to the means for transmitting uploaded data to the AI ​​analysis engine.

[0256] A "feedback display means" is a means for displaying feedback on a smart device in real time.

[0257] A "feedback generation method" is a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[0258] A "feedback notification method" is a means of notifying the user of the generated feedback.

[0259] "Planning management means" refers to means for saving and managing the generated final construction plan.

[0260] "Method for sending corrected data" refers to a means for users to re-upload their corrected content to the system.

[0261] A "re-feedback generation means" is a means for generating feedback again based on the results of re-analysis and notifying the user.

[0262] A "data storage method" is a means of temporarily storing data uploaded by a user.

[0263] A "smart device" is a device that has the capability to perform computer processing and provides information to the user. Examples include smart glasses and head-mounted displays.

[0264] This invention relates to a method for improving the efficiency and safety of construction work and factory operations using a certain system. Specific embodiments are described below.

[0265] First, users create an account by accessing the system and entering information. This includes basic information such as company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[0266] Next, the user uploads data related to construction work or factory operations (e.g., order specifications or work procedures) to the system. The terminal sends the uploaded data to the server, which temporarily stores the data before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[0267] The analysis results are generated as feedback and notified to the user from the server. Specifically, the feedback is displayed in real time on a smart device (such as smart glasses) using a feedback display means. The user can also review this feedback, make any necessary corrections, and then re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The results of the re-analysis are similarly notified to the user as feedback.

[0268] Finally, after the user reviews all feedback and completes the revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to assist with project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[0269] The hardware will include smart glasses (e.g., Google® Glass®, Microsoft® HoloLens®) and web servers that provide appropriate API endpoints. The software will utilize AI analysis engines such as NLP engines and rule-based systems.

[0270] For example, when factory workers assemble part A using smart glasses, they can immediately access a checklist based on the latest safety standards. An AI analysis engine audits all steps, and any violations detected are displayed instantly.

[0271] Examples of prompt statements are as follows:

[0272] When assembling part A in the factory, please review the following latest safety standards:

[0273] Component A is properly secured.

[0274] The correct tools are being used.

[0275] The operator is wearing protective gear

[0276] If there is a violation, please display the feedback on the smart glasses.

[0277] In this way, the user can receive accurate feedback in real time in accordance with laws and regulations, company regulations, and work-specific rules, and can proceed with work safely and efficiently.

[0278] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0279] Step 1:

[0280] The user accesses the system and creates an account. To do this, basic information such as company name, person in charge, email address, and password is entered. The entered information is sent to the server through the terminal. The server saves this information in the database and sends a registration confirmation email to the user. The input data is the company name and person in charge, and the output data is the registration confirmation email.

[0281] Step 2:

[0282] The user uploads a new construction project, order specification document, or work procedure document to the system. The terminal sends the uploaded data to the server. The server temporarily saves the data and sends it to the AI analysis engine. The input data is the uploaded specification document and procedure document, and the output data is the transmission data for AI analysis.

[0283] Step 3:

[0284] The server sends the data uploaded to the AI analysis engine. The AI analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and work-specific rules. The input data is the specification document and procedure document, and the output data is the analysis result for feedback.

[0285] Step 4:

[0286] The server receives the analysis result from the AI analysis engine and generates feedback. The feedback is generated using the feedback generation means. The input data is the AI analysis result, and the output data is the feedback message.

[0287] Step 5:

[0288] The server notifies the user of the generated feedback using the feedback notification means. The feedback display means displays the feedback on the smart device in real time. The input data is the generated feedback, and the output data is the feedback message displayed on the smart device.

[0289] Step 6:

[0290] The user makes corrections based on the feedback and uploads the corrected data to the system again. The terminal sends the corrected data to the server. The input data is the corrected specification or procedure document, and the output data is the transmission data for re-analysis.

[0291] Step 7:

[0292] The server sends the corrected data to the AI analysis engine again. The AI analysis engine re-analyzes the corrected data and outputs the re-analysis result. The input data is the corrected data, and the output data is the re-analysis result.

[0293] Step 8:

[0294] The server receives the result of the re-analysis, generates feedback again using the re-feedback generation means, and notifies the user. The input data is the re-analysis result, and the output data is the re-feedback message.

[0295] Step 9:

[0296] After the user reviews all feedback and completes any necessary corrections, they create the final construction plan and upload it to the system. The terminal then sends the final construction plan to the server. The input data is the final construction plan, and the output data is the plan data stored on the server.

[0297] Step 10:

[0298] The server stores the final construction plan and uses planning management tools to manage project execution and track progress. It monitors whether the project is progressing according to plan and notifies the user as needed. The input data is the final construction plan, and the output data is progress notifications.

[0299] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0300] This invention relates to a platform for improving the efficiency of operations in the construction industry by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules, and providing feedback that takes user sentiment into consideration.

[0301] System Overview

[0302] First, the user accesses the system and creates an account. To do this, they enter basic information such as company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[0303] The user can upload data files such as the order specification, design considerations, quotation unit price, construction precautions, and orderer's comments to the system. The uploaded data is sent from the terminal to the server, and the server temporarily stores it before sending it to the AI analysis engine. The AI analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and work-specific rules.

[0304] Furthermore, an emotion engine is used to recognize the user's emotions and generate feedback taking this into account. The analysis results are adjusted by the emotion engine based on the user's emotional state, and feedback tailored to individual needs and mental states is provided. The server sends the generated feedback to the user's terminal for notification.

[0305] The user can make corrections based on the feedback and upload the data to the system again. This corrected data is sent to the server again and re-analyzed by the AI analysis engine. The re-analysis results are also adjusted through the emotion engine and notified to the user as feedback.

[0306] Finally, after the user has confirmed all the feedback and completed the necessary corrections, the final construction plan is created and uploaded to the system. The final construction plan is stored on the server to assist in project execution management and progress tracking. The server monitors whether the project is progressing as planned based on this information and notifies the user if necessary.

[0307] Specific Example

[0308] The following is a specific scenario.

[0309] 1. User Registration

[0310] User: A person in charge of a construction company visits the system and creates an account. Enter the company name, person in charge's name, email address, password, and press the send button.

[0311] Server: Receives this information and stores it in the database. Sends a registration confirmation email to the user.

[0312] 2. Data Input

[0313] User: Upload the order specification document ("Order Specification.pdf") for a new construction project to the system.

[0314] Terminal: Sends uploaded data to the server.

[0315] Server: Temporarily stores data and sends it to the AI ​​analysis engine.

[0316] 3. AI analysis and emotional feedback

[0317] Server: The AI ​​analysis engine analyzes the order specifications and determines, for example, that "the safety standards in Article 3 have not been met."

[0318] Emotion Engine: Evaluates the user's current emotional state and adjusts feedback based on the analysis results.

[0319] Server: Based on the analysis results, it generates a warning stating that "Article 3 of this order specification violates the latest safety standards" and sends it to the user terminal as feedback via the emotion engine.

[0320] Device: Notifies the user of feedback.

[0321] 4. Project Management

[0322] User: Review the feedback and revise Article 3 of the order specification.

[0323] User: Re-upload the revised order specification to the system.

[0324] Terminal: Sends the corrected data to the server.

[0325] Server: Requests the AI ​​analysis engine to re-analyze the corrected data.

[0326] Emotion Engine: Re-analyzes the corrected data and considers the user's emotional state when generating new feedback.

[0327] Server: Generates feedback again based on the re-analysis results.

[0328] Server: Sends further feedback to the user.

[0329] 5. Final confirmation and execution

[0330] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[0331] User: Upload the final construction plan to the system.

[0332] Terminal: Sends the final construction plan to the server.

[0333] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[0334] This invention is a system that improves the efficiency and safety of construction work by providing more appropriate feedback by taking user emotions into consideration. Because the emotion engine provides feedback tailored to the user's state, more effective project management becomes possible.

[0335] The following describes the processing flow.

[0336] Step 1:

[0337] User: Access the system's website and view the registration form.

[0338] Step 2:

[0339] User: Enter company name, contact person's name, email address, and password, then submit.

[0340] Step 3:

[0341] Terminal: Sends the entered information to the server.

[0342] Step 4:

[0343] Server: Stores the received user information in the database.

[0344] Step 5:

[0345] Server: Sends a registration confirmation email to the user.

[0346] Step 6:

[0347] User: Opens a page to upload data files such as order specifications to the system.

[0348] Step 7:

[0349] User: Select the order specification document "Order Specification.pdf" and upload it.

[0350] Step 8:

[0351] Terminal: Sends uploaded data to the server.

[0352] Step 9:

[0353] Server: Temporarily stores data.

[0354] Step 10:

[0355] Server: Sends the stored data to the AI ​​analysis engine.

[0356] Step 11:

[0357] AI analysis engine: Performs analysis based on data and extracts important information based on laws, regulations, and company rules.

[0358] Step 12:

[0359] Emotion Engine: Analyzes the user's emotional state. For example, it considers the user's facial expressions while uploading and their typing speed.

[0360] Step 13:

[0361] Server: Integrates analysis results from the AI ​​analysis engine and the emotion engine to generate appropriate feedback.

[0362] Step 14:

[0363] Server: Sends the generated feedback to the terminal.

[0364] Step 15:

[0365] Device: Notifies the user of feedback.

[0366] Step 16:

[0367] User: Review the feedback and make any necessary corrections.

[0368] Step 17:

[0369] User: Upload the revised order specification to the system again.

[0370] Step 18:

[0371] Terminal: Sends the corrected data to the server.

[0372] Step 19:

[0373] Server: Resends the corrected data to the AI ​​analysis engine.

[0374] Step 20:

[0375] AI analysis engine: Re-analyzes the corrected data and generates new feedback.

[0376] Step 21:

[0377] Emotional Engine: Re-analyzes the user's emotional state and adjusts the feedback accordingly.

[0378] Step 22:

[0379] Server: Generates re-feedback based on the re-analysis results and the re-analysis results of the emotion engine, and sends it to the terminal.

[0380] Step 23:

[0381] Device: Notifies the user of further feedback.

[0382] Step 24:

[0383] User: Review all feedback and create the final construction plan.

[0384] Step 25:

[0385] User: Upload the final construction plan to the system.

[0386] Step 26:

[0387] Terminal: Sends the final construction plan to the server.

[0388] Step 27:

[0389] Server: Saves the final construction plan to the database.

[0390] Step 28:

[0391] Server: Manages project execution and progress, and notifies users as needed.

[0392] (Example 2)

[0393] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0394] In traditional construction work, it has been difficult to efficiently analyze information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments, and to provide feedback that complies with laws and company regulations. Furthermore, because feedback is provided only mechanically, without considering the user's feelings, there have been problems such as users feeling stressed or finding it difficult to accept the feedback. To solve these problems, there is a need for a system that generates more appropriate feedback that takes user feelings into account.

[0395] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user registration means for creating an account by inputting information by the user, a data transmission means for transmitting uploaded data to an AI analysis engine, a feedback generation means for generating feedback that takes into account the user's emotional state based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, and a plan management means for saving and managing the generated final construction plan. This makes it possible to improve efficiency and reliability in construction work by providing feedback that takes into account the user's emotions.

[0396] "User registration method" refers to the means by which a user enters information and creates an account.

[0397] "Data transmission means" refers to the means by which data uploaded by the user is sent to the AI ​​analysis engine.

[0398] A "feedback generation method" is a means of generating feedback that takes into account the user's emotional state based on the results analyzed by the AI ​​analysis engine.

[0399] A "feedback notification method" is a means of notifying the user of the generated feedback.

[0400] "Plan management means" refers to the means of saving and managing the final construction plan that has been generated.

[0401] "Method for sending corrected data" refers to a means for users to re-upload their corrected content to the system.

[0402] A "re-feedback generation method" is a means of generating feedback again, taking into account the user's emotional state based on the results of the re-analysis, and notifying the user.

[0403] A "data storage method" is a means of temporarily storing data uploaded by a user.

[0404] This invention aims to improve efficiency and reliability in construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules, and providing feedback that takes user sentiment into account.

[0405] System Overview

[0406] First, the user accesses the system and creates an account by entering basic information such as company name, contact person's name, email address, and password. The entered information is sent to the server and stored in the database. At the same time, a registration confirmation email is sent to the user.

[0407] Next, the user uploads data files such as order specifications and design notes to the system. The uploaded data is sent from the terminal to the server, temporarily stored, and then sent to the AI ​​analysis engine.

[0408] The AI ​​analysis engine analyzes uploaded data and evaluates whether it complies with laws, company regulations, and proprietary work rules. Furthermore, it uses an emotion engine to recognize the user's emotional state and reflect it in the feedback. The emotion engine analyzes the user's past operation logs and system usage history to assess the user's mental state.

[0409] The feedback is generated based on analysis results refined by the emotion engine and sent to the user terminal via the server. For example, feedback such as, "Article 3 of this order specification violates the latest safety standards, but we will provide detailed guidance on how to correct it," might be generated.

[0410] The user makes necessary corrections based on the feedback provided and re-uploads the data to the system. This corrected data is also sent to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are then adjusted again through the emotion engine and notified to the user as feedback.

[0411] Finally, after the user reviews all feedback and completes any necessary corrections, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to assist with project execution management and progress tracking. The server monitors whether the project is progressing according to plan and notifies the user as needed.

[0412] Hardware and software to be used

[0413] The following hardware and software are primarily used:

[0414] Server: Stores and processes data. Examples: Amazon Web Services (AWS®), Google Cloud Platform (GCP).

[0415] Device: Used for data input and display of results. Examples: PC, tablet.

[0416] AI analysis engine: Analyzes data based on laws, company regulations, and proprietary work rules. Example: GPT-4 (registered trademark).

[0417] Emotion engine: Evaluates the user's emotional state. Example: IBM Watson®.

[0418] Specific example

[0419] User Registration

[0420] Example prompt: "I would like to create a new account. Please enter your company name, contact person's name, email address, and password."

[0421] Data Input

[0422] Specific example: "Order Specification.pdf"

[0423] Example prompt: "I have uploaded the order specification. Please parse it."

[0424] AI analysis and emotional feedback

[0425] Example prompt: "Please analyze the uploaded order specification and provide feedback."

[0426] project management

[0427] Specific example: "Revised Order Specifications.pdf"

[0428] Example prompt: "I will re-upload the revised order specification. Please re-parse it."

[0429] Final confirmation and execution

[0430] Specific example: "Final Construction Plan.pdf"

[0431] Example prompt: "Uploading the final construction plan. Please track the project progress."

[0432] This system contributes to increased efficiency and reliability in construction work by providing more effective and user-friendly feedback that takes user emotions into consideration. Its key feature is the combination of an AI analysis engine and an emotion engine, which provides highly accurate feedback while taking the user's mental state into account.

[0433] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0434] Step 1:

[0435] The user accesses the system and is redirected to the account creation screen. The user enters the company name, contact person's name, email address, and password, then clicks the submit button.

[0436] Input: Company name, contact person's name, email address, password

[0437] Output: Registration confirmation request

[0438] Step 2:

[0439] The server receives the entered information and saves it to the database. The server then sends a registration confirmation email to the user.

[0440] Input: Registration confirmation request

[0441] Data processing: Saving input information, generating confirmation emails.

[0442] Output: Registration confirmation email

[0443] Step 3:

[0444] The user uploads the order specification document for a new construction project, "Order Specification Document.pdf". The user presses the upload button.

[0445] Input: Order specification "Order specification.pdf"

[0446] Output: Upload Request

[0447] Step 4:

[0448] The device sends the uploaded data to the server.

[0449] Input: Upload request

[0450] Output: Uploaded data

[0451] Step 5:

[0452] The server temporarily stores the received data and passes the destination path to the AI ​​analysis engine.

[0453] Input: Uploaded data

[0454] Data processing: Data storage, path generation

[0455] Output: Data path

[0456] Step 6:

[0457] The AI ​​analysis engine analyzes the order specifications based on the file paths provided by the server. It then evaluates whether the specifications comply with legal standards and company regulations.

[0458] Input: Data path

[0459] Data processing: Analysis of order specifications, comparison with reference points.

[0460] Output: Analysis results (Example: Safety standards under Article 3 are not met)

[0461] Step 7:

[0462] The server receives the analysis results from the AI ​​analysis engine.

[0463] Input: Analysis results

[0464] Output: Unadjusted analysis results

[0465] Step 8:

[0466] The emotion engine evaluates the user's emotional state and generates feedback based on the analysis results.

[0467] Input: Unadjusted analysis results, user's historical data

[0468] Data processing: Evaluating user emotional states, generating feedback.

[0469] Output: Adjustment feedback (e.g., Article 3 violates safety standards, but provides detailed guidance on how to correct it)

[0470] Step 9:

[0471] The server compiles feedback, refined by the emotion engine, and sends it to the user's terminal.

[0472] Input: Adjustment Feedback

[0473] Output: Feedback notification

[0474] Step 10:

[0475] Review the feedback provided by users and make any necessary corrections.

[0476] Input: Feedback notification

[0477] Output: Correction details

[0478] Step 11:

[0479] The user uploads the revised order specification file to the system again.

[0480] Input: Revised purchase order specification (Example: Revised purchase order specification.pdf)

[0481] Output: Re-upload request

[0482] Step 12:

[0483] The device is corrected and the uploaded files are sent back to the server.

[0484] Input: Re-upload request

[0485] Output: Re-uploaded data

[0486] Step 13:

[0487] The server sends the data back to the AI ​​analysis engine and requests a re-analysis.

[0488] Input: Re-uploaded data

[0489] Data processing: Data storage, re-analysis requests

[0490] Output: Reanalysis results

[0491] Step 14:

[0492] The emotion engine re-analyzes the results, taking into account the user's emotional state, and generates new feedback.

[0493] Input: Reanalysis results, user's historical data

[0494] Data processing: Sentiment evaluation, feedback generation

[0495] Output: Refeedback

[0496] Step 15:

[0497] The server compiles the re-analysis results and adjusted feedback, and then resends it to the user.

[0498] Input: Refeedback

[0499] Output: Re-feedback notification

[0500] Step 16:

[0501] The user confirms that all suggestions and warnings have been resolved, and then the final construction plan is created.

[0502] Input: Feedback notification

[0503] Output: Final construction plan

[0504] Step 17:

[0505] The user uploads the final construction plan to the system.

[0506] Input: Final Construction Plan (Example: Final Construction Plan.pdf)

[0507] Output: Final upload request

[0508] Step 18:

[0509] The terminal sends the final construction plan to the server.

[0510] Input: Final upload request

[0511] Output: Final Upload Data

[0512] Step 19:

[0513] The server saves the final construction plan to the database and begins project execution management and progress tracking.

[0514] Input: Last uploaded data

[0515] Data processing: Data storage, progress monitoring

[0516] Output: Progress notification

[0517] This clearly shows the overall system flow and the specific actions of each step, allowing users, terminals, and servers to understand the processes involved.

[0518] (Application Example 2)

[0519] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0520] In autonomous vehicles, safety and compliance with regulations are extremely important, but the driver's emotional state often influences these. Conventional systems have been unable to provide feedback that takes the driver's emotions into account, resulting in problems with ensuring driving safety and compliance with regulations. This invention aims to solve this problem by providing feedback that takes the driver's emotions into account, thereby improving the safety and compliance with regulations of autonomous vehicles.

[0521] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user registration means for creating an account by inputting information by the user, a data transmission means for transmitting uploaded data to an AI analysis engine, a feedback generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, a plan management means for saving and managing the generated final construction plan, an emotion recognition means for recognizing the driver's emotional state, and an emotion adjustment feedback generation means for adjusting the feedback based on the emotional state. This makes it possible to provide appropriate feedback that takes into account the driver's emotional state, thereby improving the safety of autonomous vehicles and compliance with legal regulations.

[0522] "User registration method" refers to a means by which a user creates an account by entering information.

[0523] "Data transmission means" refers to the means by which data uploaded by the user is sent to the AI ​​analysis engine.

[0524] A "feedback generation method" is a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[0525] A "feedback notification method" is a means of notifying the user of the generated feedback.

[0526] "Planning management means" refers to means for saving and managing the generated final construction plan.

[0527] "Means of emotional recognition" refers to means of recognizing the emotional state of the driver.

[0528] An "emotion adjustment feedback generation means" is a means for adjusting and generating feedback based on an emotional state.

[0529] This invention is a system for enhancing the safety and compliance with regulations of autonomous vehicles. Specifically, it improves the safety of operating autonomous vehicles by providing feedback that takes into account the driver's emotional state.

[0530] The system has the following functions:

[0531] User registration method

[0532] The server includes a means for users to create accounts by entering information. Users can access the system by entering basic information such as company name, contact person's name, email address, and password and submitting it to the server. The server stores the entered information in a database and sends a registration confirmation email to the user.

[0533] Data transmission means

[0534] When a user uploads data acquired from the vehicle's sensors and cameras to the system, the terminal sends this data to the server. The server temporarily stores the received data and then sends it to the AI ​​analysis engine.

[0535] Feedback generation means

[0536] The AI ​​analysis engine analyzes the received data and evaluates whether it complies with laws, regulations, and safety standards. It also detects whether the driver is engaging in specific behaviors (for example, exceeding the speed limit or entering a prohibited area).

[0537] emotion recognition means

[0538] The emotion recognition system uses an in-car camera to capture images of the driver's face and recognizes specific emotional states (e.g., anger, sadness, joy). Emotion recognition is performed using an emotion recognition library that evaluates the driver's facial microexpressions and overall facial movements.

[0539] Emotional regulation feedback generation method

[0540] The emotion-adjusted feedback generation method combines the analysis results of the AI ​​analysis engine with the driver's emotional state to generate adjusted feedback. For example, if the driver is angry, a warning such as "Please calm down and continue driving" can be added.

[0541] Feedback notification method

[0542] The generated feedback is sent from the server to the user's device. The device receives this notification and provides appropriate feedback to the driver.

[0543] Planning and management methods

[0544] The final construction plan and a history of important feedback are stored and managed on a server. This allows for continuous monitoring of project progress and safety assessments, and enables notifications to be sent to drivers and managers as needed.

[0545] Specific example

[0546] For example, if a vehicle is exceeding the speed limit, the AI ​​analysis engine will detect this and generate feedback warning it to "adjust your speed to the limit." Furthermore, if the emotion recognition system detects that the driver is angry, it will provide additional feedback such as "Please drive calmly."

[0547] Example of a prompt

[0548] "Evaluate compliance with legal regulations based on the detection results of road signs, vehicles, and pedestrians, and create feedback based on the driver's emotional state."

[0549] This will enable appropriate feedback that takes into account the driver's emotional state, thereby improving the safety and compliance with regulations of autonomous vehicles.

[0550] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0551] Step 1:

[0552] A user accesses the system and creates an account. Specifically, the user enters information such as company name, contact person's name, email address, and password, and sends this information to the server. The server stores the submitted information in a database and sends a registration confirmation email to the user. The input is user information, and the output is the storage in the database and the confirmation email.

[0553] Step 2:

[0554] The user uploads data acquired from the vehicle's sensors and cameras to the system. The terminal sends this data (e.g., camera footage and sensor information) to the server. The server temporarily stores the received data and then sends it to the AI ​​analysis engine. The input is sensor data, and the output is storage to the server and transmission to the AI ​​analysis engine.

[0555] Step 3:

[0556] The AI ​​analysis engine analyzes the received data. Specifically, it detects road signs, other vehicles, and pedestrians, and evaluates whether they comply with legal regulations and safety standards. The output of the analysis is a violation detection result, such as "exceeding the speed limit." The input is sensor data, and the output is the analysis result.

[0557] Step 4:

[0558] An emotion recognition system uses an in-car camera to recognize the driver's emotional state. An emotion recognition library analyzes the facial image to detect the driver's emotion (e.g., anger, sadness, joy). The input is facial image data, and the output is the emotional state.

[0559] Step 5:

[0560] The emotion-adjusted feedback generation mechanism combines the analysis results of the AI ​​analysis engine with the emotional state of the emotion recognition mechanism to generate feedback. Specifically, if the driver is angry, it generates additional feedback such as "Please calm down and continue driving." The input is the analysis results and emotional state, and the output is the adjusted feedback.

[0561] Step 6:

[0562] The server notifies the user terminal of the generated feedback. The terminal receives this notification and provides appropriate feedback to the driver. The input is the adjusted feedback, and the output is the notification to the user terminal.

[0563] Step 7:

[0564] The server stores and manages the final construction plan and feedback history. This allows for continuous monitoring of project progress and safety assessments, and enables notifications to drivers and managers as needed. Inputs are the final construction plan and feedback history, while outputs are the stored data and monitoring results.

[0565] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0566] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0567] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0568] [Second Embodiment]

[0569] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0570] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0571] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0572] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0573] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0574] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0575] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0576] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0577] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0578] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0579] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0580] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0581] This invention relates to a system for improving the efficiency of operations in the construction industry. Specifically, it is a platform for efficiently carrying out construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules.

[0582] System Overview

[0583] First, the user accesses the system and creates an account. This involves entering basic information such as the company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[0584] Next, users can upload order specifications, design notes, estimated unit prices, construction precautions, and client comments to the system. The uploaded data is sent from the terminal to the server, which temporarily stores it before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[0585] The analysis results are generated as feedback and notified to the user from the server. The user can then make corrections based on this feedback and re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are also notified to the user as feedback.

[0586] Finally, after the user reviews all feedback and completes any necessary revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to support project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[0587] Specific example

[0588] The following is a specific scenario.

[0589] 1. User Registration

[0590] User: A representative from a construction company visits the system and creates an account. They enter the company name, contact person's name, email address, and password, and then press the submit button.

[0591] Server: Receives this information and stores it in the database. Sends a registration confirmation email to the user.

[0592] 2. Data Input

[0593] User: Upload the order specification document ("Order Specification.pdf") for a new construction project to the system.

[0594] Terminal: Sends uploaded data to the server.

[0595] Server: Temporarily stores data and sends it to the AI ​​analysis engine.

[0596] 3. AI analysis and feedback

[0597] Server: The AI ​​analysis engine analyzes the order specifications and determines, for example, that "the safety standards in Article 3 have not been met."

[0598] Server: Based on the analysis results, it generates a warning stating that "Article 3 of this order specification violates the latest safety standards."

[0599] Server: Sends the generated feedback to the user.

[0600] Device: Notifies the user of feedback.

[0601] 4. Project Management

[0602] User: Review the feedback and revise Article 3 of the order specification.

[0603] User: Re-upload the revised order specification to the system.

[0604] Terminal: Sends the corrected data to the server.

[0605] Server: Requests the AI ​​analysis engine to re-analyze the corrected data.

[0606] Server: Generates feedback again based on the re-analysis results.

[0607] Server: Sends further feedback to the user.

[0608] 5. Final confirmation and execution

[0609] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[0610] User: Upload the final construction plan to the system.

[0611] Terminal: Sends the final construction plan to the server.

[0612] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[0613] In this way, this invention supports the efficient progress of construction work. This system reduces rework, prevents personal injury and service disruptions, and improves the overall efficiency of operations.

[0614] The following describes the processing flow.

[0615] Step 1:

[0616] User: Access the system's website and view the registration form.

[0617] Step 2:

[0618] User: Enter company name, contact person's name, email address, and password, then submit.

[0619] Step 3:

[0620] Terminal: Sends the entered information to the server.

[0621] Step 4:

[0622] Server: Stores the received user information in the database.

[0623] Step 5:

[0624] Server: Sends a registration confirmation email to the user.

[0625] Step 6:

[0626] User: Opens a page to upload data files such as order specifications to the system.

[0627] Step 7:

[0628] User: Select the order specification document "Order Specification.pdf" and upload it.

[0629] Step 8:

[0630] Terminal: Sends uploaded data to the server.

[0631] Step 9:

[0632] Server: Temporarily stores data.

[0633] Step 10:

[0634] Server: Sends the stored data to the AI ​​analysis engine.

[0635] Step 11:

[0636] AI analysis engine: Performs analysis based on data and extracts important information based on laws, regulations, and company rules.

[0637] Step 12:

[0638] Server: Receives analysis results from the AI ​​analysis engine and generates feedback.

[0639] Step 13:

[0640] Server: Sends the generated feedback to the terminal.

[0641] Step 14:

[0642] Device: Notifies the user of feedback.

[0643] Step 15:

[0644] User: Review the feedback and make any necessary corrections.

[0645] Step 16:

[0646] User: Upload the revised order specification to the system again.

[0647] Step 17:

[0648] Terminal: Sends the corrected data to the server.

[0649] Step 18:

[0650] Server: Resends the corrected data to the AI ​​analysis engine.

[0651] Step 19:

[0652] AI analysis engine: Re-analyzes the corrected data and generates new feedback.

[0653] Step 20:

[0654] Server: Generates re-feedback based on the re-analysis results and sends it to the terminal.

[0655] Step 21:

[0656] Device: Notifies the user of further feedback.

[0657] Step 22:

[0658] User: Review all feedback and create the final construction plan.

[0659] Step 23:

[0660] User: Upload the final construction plan to the system.

[0661] Step 24:

[0662] Terminal: Sends the final construction plan to the server.

[0663] Step 25:

[0664] Server: Saves the final construction plan to the database.

[0665] Step 26:

[0666] Server: Manages project execution and progress, and notifies users as needed.

[0667] (Example 1)

[0668] Next, we will describe Example 1. 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".

[0669] In the construction industry, it is necessary to verify that many tasks comply with relevant laws, regulations, and unique work rules. This can lead to complexity, rework, and decreased efficiency. Furthermore, even during project execution, insufficient compliance with laws and regulations and inadequate progress management can lead to deviations from the plan and accidents. Therefore, there is a need for means to resolve these issues and achieve efficient and reliable work execution.

[0670] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0671] In this invention, the server includes a user registration means for creating an account by having the user input information, an information transmission means for transmitting uploaded data to an AI analysis engine, an evaluation generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, an evaluation notification means for notifying the user of the feedback, a plan management means for storing and managing the generated final plan, a legal compliance evaluation means for evaluating whether the plan complies with laws and regulations, and a progress monitoring means for managing the execution and tracking the progress of the project. This enables efficient and reliable planning and management of construction projects in compliance with laws and regulations, eliminates the complexity of the work, and simplifies progress management.

[0672] 1. "User registration method" refers to a means by which a user creates an account by entering information.

[0673] 2. "Information transmission means" refers to the means for transmitting uploaded data to the AI ​​analysis engine.

[0674] 3. "Evaluation generation means" refers to a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[0675] 4. "Evaluation notification means" refers to a means of notifying the user of the generated feedback.

[0676] 5. "Plan management means" refers to means for saving and managing the final plan that has been generated.

[0677] 6. "Methods for evaluating compliance with laws and regulations" are means for evaluating whether something complies with laws and regulations.

[0678] 7. "Progress monitoring means" refers to the means used for managing the execution and tracking the progress of a project.

[0679] This invention relates to a system for improving the efficiency of operations in the construction industry. Specifically, it is a platform for efficiently carrying out construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules.

[0680] The main components of this system include a server, terminals, and an AI analysis engine. The server includes means for user registration, information transmission, evaluation generation, evaluation notification, plan management, legal compliance evaluation, and progress monitoring.

[0681] The server uses an SQL database to manage basic user information and uploaded data. The AI ​​analysis engine analyzes the data using machine learning libraries such as TensorFlow and PyTorch. The terminal provides an interface for users to upload data and check feedback.

[0682] The following is a concrete example of the system.

[0683] User Registration

[0684] User: Access the system, enter the company name, contact person's name, email address, and password on the account creation screen, and click the register button.

[0685] Server: Receives the entered information and saves it to the database. It also generates and sends a registration confirmation email to the user.

[0686] Terminal: The user will receive a registration confirmation email.

[0687] Upload data

[0688] User: Drag and drop data such as order specifications, design notes, estimated unit prices, construction precautions, and client comments onto the system's upload screen, or select them using the file selection dialog.

[0689] Terminal: Sends the selected files to the server.

[0690] Server: Receives the file and stores it temporarily.

[0691] Temporary data storage and AI analysis request

[0692] Server: Sends temporarily stored data to the AI ​​analysis engine and requests analysis.

[0693] AI analysis and feedback generation

[0694] Server: The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and proprietary work rules.

[0695] Server: Receives analysis results and generates feedback based on them. For example, it might generate a warning such as, "Article 3 of this order specification violates the latest safety standards."

[0696] Server: Notifies the user of the feedback.

[0697] Reviewing feedback and correcting data

[0698] User: Check the feedback received from the server.

[0699] User: Based on feedback, revise data such as order specifications.

[0700] Request to re-upload corrected data and re-analyze it.

[0701] User: Re-upload the revised order specification to the system.

[0702] Terminal: Resend the corrected data to the server.

[0703] Server: Resubmits the corrected data to the AI ​​analysis engine and requests re-analysis.

[0704] Server: Receives re-analysis results and generates feedback again.

[0705] Server: Notifies the user of further feedback.

[0706] Uploading the final construction plan and project management

[0707] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[0708] User: Upload the final construction plan to the system.

[0709] Terminal: Sends files to the server.

[0710] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[0711] As a concrete example, the following prompt statement is shown:

[0712] Example of a prompt

[0713] 1. User Registration

[0714] I would like to create an account in the system. Please enter your company name, contact person's name, email address, and password.

[0715] 2. "Data Input

[0716] I have uploaded the order specifications for a new project. Please analyze this file.

[0717] 3. AI analysis and feedback

[0718] The analysis results for the order specifications are in. Article 3 violates safety standards and requires correction.

[0719] 4. "Further feedback"

[0720] I have reviewed the feedback and revised the order specifications. Please analyze it again.

[0721] 5. Final confirmation and execution

[0722] The final construction plan is complete. Uploading it to the system. Please begin project management.

[0723] In this way, this system supports the efficient progress of construction work. It enables efficient and reliable planning and management of construction projects in compliance with laws and regulations.

[0724] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0725] Step 1:

[0726] User Registration

[0727] User: Access the system, enter the company name, contact person's name, email address, and password on the account creation screen, and click the register button.

[0728] Server: Receives the entered information and saves it to the database. Executes the following SQL query: INSERT INTO users (company_name, contact_name, email, password) VALUES ('Company Name', 'Contact Person Name', 'Email Address', 'Password'). Generates a registration confirmation email and sends it to the user.

[0729] Input: Company name, contact person's name, email address, and password entered by the user.

[0730] Output: User information stored in the database, confirmation email sent to the user.

[0731] Terminal: The user's screen displays the message, "A registration confirmation email has been sent. Please check your email."

[0732] Step 2:

[0733] Upload data

[0734] User: Drag and drop data such as order specifications, design notes, estimated unit prices, construction precautions, and client comments onto the system's upload screen, or select them using the file selection dialog.

[0735] Terminal: Sends the file selected from the file selection dialog to the server using the multipart / form-data protocol.

[0736] Input: The file to be uploaded (e.g., "Order Specifications.pdf").

[0737] Output: File data sent to the server.

[0738] Server: Saves received file data to a temporary storage directory. For example, use the function store_temp_file('OrderSpecifications.pdf').

[0739] Input: File data sent from the terminal.

[0740] Output: Files saved in the temporary directory.

[0741] Step 3:

[0742] Temporary data storage and AI analysis request

[0743] Server: Sends temporarily stored data to the AI ​​analysis engine. Specifically, it uses the function `send_to_ai_engine('temp / order_specification_document.pdf')` to request analysis.

[0744] Input: Temporarily saved file data (e.g., "temp / order_specification.pdf").

[0745] Output: Analysis request sent to the AI ​​analysis engine.

[0746] Step 4:

[0747] AI analysis and feedback generation

[0748] Server: The AI ​​analysis engine analyzes the data and receives evaluation results on whether it complies with laws, company regulations, and proprietary work rules.

[0749] Input: Data sent to the AI ​​analysis engine.

[0750] Output: Evaluation results (e.g., feedback stating "Article 3 violates the latest safety standards").

[0751] Server: Generates feedback based on the analysis results and notifies the user. For example, it might generate a warning message stating, "Article 3 of this order specification violates the latest safety standards."

[0752] Input: Evaluation results from the AI ​​analysis engine.

[0753] Output: Feedback notified to the user.

[0754] Step 5:

[0755] Reviewing feedback and correcting data

[0756] User: Review the feedback received from the system and revise data such as order specifications.

[0757] Input: Feedback received from the system.

[0758] Output: Data such as the revised order specifications. Specifically, Article 3 of "Order Specifications.pdf" was modified in an editor to comply with the latest safety standards.

[0759] Step 6:

[0760] Request to re-upload corrected data and re-analyze it.

[0761] User: Upload the revised order specifications to the system again.

[0762] Input: Modified file (e.g., "Order Specification_v2.pdf").

[0763] Output: File data sent to the server.

[0764] Terminal: Sends modified data to the server using the multipart / form-data protocol.

[0765] Input: The modified file.

[0766] Output: File data sent to the server.

[0767] Server: Receives the modified data and saves it again to the temporary storage directory. For example, store_temp_file('Order Specification_v2.pdf').

[0768] Input: Modified file data sent from the terminal.

[0769] Output: The file has been resaved to the temporary directory.

[0770] Server: Resends the corrected data to the AI ​​analysis engine and requests re-analysis. Specifically, it calls send_to_ai_engine('temp / order_specification_v2.pdf').

[0771] Input: Re-saved modified file data.

[0772] Output: Analysis request resent to the AI ​​analysis engine.

[0773] Server: Receives the re-analysis results, generates feedback again, and notifies the user. For example, it might generate feedback stating, "All items comply with the latest safety standards."

[0774] Input: Re-evaluation results from the AI ​​analysis engine.

[0775] Output: Further feedback notified to the user.

[0776] Step 7:

[0777] Uploading the final construction plan and project management

[0778] User: Create the final construction plan based on the final feedback.

[0779] Input: Final feedback.

[0780] Output: Final Construction Plan (Example: "Final Construction Plan.pdf").

[0781] User: Upload the final construction plan to the system.

[0782] Input: Final construction plan.

[0783] Output: Sending plan data to the server.

[0784] Terminal: Sends the final construction plan to the server using the multipart / form-data protocol.

[0785] Input: Final construction plan.

[0786] Output: Sending plan data to the server.

[0787] Server: Receives the final construction plan and saves it to the plan management directory. For example, store_final_plan('final_construction_plan.pdf').

[0788] Input: Plan data sent from the terminal.

[0789] Output: The final construction plan saved in the save directory.

[0790] Server: Records necessary information and monitors project progress in order to initiate project execution management and progress tracking.

[0791] Input: Final construction plan.

[0792] Output: Progress monitoring data for project management.

[0793] (Application Example 1)

[0794] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0795] In traditional construction work, a major challenge has been the time-consuming and laborious process of manually verifying compliance with legal regulations, company rules, and unique work procedures. Furthermore, similar problems are more likely to occur during factory work, making it difficult to adhere to safety standards. As a result, there are challenges such as decreased work efficiency and an increased risk of personal injury and service disruptions.

[0796] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0797] In this invention, the server includes a user registration means for creating an account by having the user input information, a data transmission means for sending uploaded data to an AI analysis engine, a feedback display means for displaying feedback on a smart device in real time, a feedback generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, and a plan management means for saving and managing the generated final construction plan. As a result, the user can receive accurate feedback in real time that complies with laws and regulations, company rules, and unique work rules, enabling them to carry out their work safely and efficiently.

[0798] "User registration method" refers to a means by which a user creates an account by entering information.

[0799] "Data transmission means" refers to the means for transmitting uploaded data to the AI ​​analysis engine.

[0800] A "feedback display means" is a means for displaying feedback on a smart device in real time.

[0801] A "feedback generation method" is a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[0802] A "feedback notification method" is a means of notifying the user of the generated feedback.

[0803] "Planning management means" refers to means for saving and managing the generated final construction plan.

[0804] "Method for sending corrected data" refers to a means for users to re-upload their corrected content to the system.

[0805] A "re-feedback generation means" is a means for generating feedback again based on the results of re-analysis and notifying the user.

[0806] A "data storage method" is a means of temporarily storing data uploaded by a user.

[0807] A "smart device" is a device that has the capability to perform computer processing and provides information to the user. Examples include smart glasses and head-mounted displays.

[0808] This invention relates to a method for improving the efficiency and safety of construction work and factory operations using a certain system. Specific embodiments are described below.

[0809] First, users create an account by accessing the system and entering information. This includes basic information such as company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[0810] Next, the user uploads data related to construction work or factory operations (e.g., order specifications or work procedures) to the system. The terminal sends the uploaded data to the server, which temporarily stores the data before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[0811] The analysis results are generated as feedback and notified to the user from the server. Specifically, the feedback is displayed in real time on a smart device (such as smart glasses) using a feedback display means. The user can also review this feedback, make any necessary corrections, and then re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The results of the re-analysis are similarly notified to the user as feedback.

[0812] Finally, after the user reviews all feedback and completes the revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to assist with project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[0813] The hardware will include smart glasses (e.g., Google Glass, Microsoft HoloLens) and web servers that provide appropriate API endpoints. The software will utilize AI analysis engines such as NLP engines and rule-based systems.

[0814] For example, when factory workers assemble part A using smart glasses, they can immediately access a checklist based on the latest safety standards. An AI analysis engine audits all steps, and any violations detected are displayed instantly.

[0815] Examples of prompt statements are as follows:

[0816] When assembling part A in the factory, please review the following latest safety standards:

[0817] Component A is properly secured.

[0818] The correct tools are being used.

[0819] Workers must wear protective equipment.

[0820] If there are any violations, please display the feedback on your smart glasses.

[0821] In this way, users can receive accurate feedback in real time that complies with legal regulations, company rules, and unique work rules, enabling them to carry out their work safely and efficiently.

[0822] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0823] Step 1:

[0824] The user accesses the system and creates an account. This involves entering basic information such as company name, contact person's name, email address, and password. The entered information is sent to the server via the terminal. The server stores this information in a database and sends a registration confirmation email to the user. The input data includes the company name and contact person's name, while the output data is the registration confirmation email.

[0825] Step 2:

[0826] Users upload specifications and work procedures for new construction projects or tasks to the system. The terminal sends the uploaded data to the server. The server temporarily stores the data and then sends it to the AI ​​analysis engine. The input data consists of the uploaded specifications and procedures, and the output data is the data sent for AI analysis.

[0827] Step 3:

[0828] The server sends the uploaded data to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and proprietary work rules. The input data consists of specifications and procedures, and the output data is the analysis results for feedback.

[0829] Step 4:

[0830] The server receives analysis results from the AI ​​analysis engine and generates feedback. Feedback is generated using a feedback generation method. The input data is the AI ​​analysis results, and the output data is the feedback message.

[0831] Step 5:

[0832] The server notifies the user of the generated feedback using a feedback notification means. The feedback display means displays the feedback on the smart device in real time. The input data is the generated feedback, and the output data is the feedback message displayed on the smart device.

[0833] Step 6:

[0834] The user makes corrections based on feedback and uploads the corrected data back to the system. The terminal sends the corrected data to the server. The input data is the corrected specifications or procedures, and the output data is the data to be sent for re-analysis.

[0835] Step 7:

[0836] The server sends the corrected data back to the AI ​​analysis engine. The AI ​​analysis engine re-analyzes the corrected data and outputs the analysis results again. The input data is the corrected data, and the output data is the re-analysis result.

[0837] Step 8:

[0838] The server receives the re-analysis results, generates feedback again using the re-feedback generation mechanism, and notifies the user. The input data is the re-analysis results, and the output data is the re-feedback message.

[0839] Step 9:

[0840] After the user reviews all feedback and completes any necessary corrections, they create the final construction plan and upload it to the system. The terminal then sends the final construction plan to the server. The input data is the final construction plan, and the output data is the plan data stored on the server.

[0841] Step 10:

[0842] The server stores the final construction plan and uses planning management tools to manage project execution and track progress. It monitors whether the project is progressing according to plan and notifies the user as needed. The input data is the final construction plan, and the output data is progress notifications.

[0843] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0844] This invention relates to a platform for improving the efficiency of operations in the construction industry by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules, and providing feedback that takes user sentiment into consideration.

[0845] System Overview

[0846] First, the user accesses the system and creates an account. To do this, they enter basic information such as company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[0847] Users can upload data files such as order specifications, design notes, estimated unit prices, construction precautions, and client comments to the system. The uploaded data is sent from the terminal to the server, which temporarily stores it before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[0848] Furthermore, an emotion engine is used to recognize the user's emotions and generate feedback that takes these emotions into account. The analysis results are adjusted by the emotion engine based on the user's emotional state, providing feedback tailored to individual needs and mental state. The server sends the generated feedback to the user's terminal for notification.

[0849] Users can make corrections based on feedback and re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are also adjusted through the emotion engine and notified to the user as feedback.

[0850] Finally, after the user reviews all feedback and completes any necessary revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to support project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[0851] Specific example

[0852] The following is a specific scenario.

[0853] 1. User Registration

[0854] User: A representative from a construction company visits the system and creates an account. They enter the company name, contact person's name, email address, and password, and then press the submit button.

[0855] Server: Receives this information and stores it in the database. Sends a registration confirmation email to the user.

[0856] 2. Data Input

[0857] User: Upload the order specification document ("Order Specification.pdf") for a new construction project to the system.

[0858] Terminal: Sends uploaded data to the server.

[0859] Server: Temporarily stores data and sends it to the AI ​​analysis engine.

[0860] 3. AI analysis and emotional feedback

[0861] Server: The AI ​​analysis engine analyzes the order specifications and determines, for example, that "the safety standards in Article 3 have not been met."

[0862] Emotion Engine: Evaluates the user's current emotional state and adjusts feedback based on the analysis results.

[0863] Server: Based on the analysis results, it generates a warning stating that "Article 3 of this order specification violates the latest safety standards" and sends it to the user terminal as feedback via the emotion engine.

[0864] Device: Notifies the user of feedback.

[0865] 4. Project Management

[0866] User: Review the feedback and revise Article 3 of the order specification.

[0867] User: Re-upload the revised order specification to the system.

[0868] Terminal: Sends the corrected data to the server.

[0869] Server: Requests the AI ​​analysis engine to re-analyze the corrected data.

[0870] Emotion Engine: Re-analyzes the corrected data and considers the user's emotional state when generating new feedback.

[0871] Server: Generates feedback again based on the re-analysis results.

[0872] Server: Sends further feedback to the user.

[0873] 5. Final confirmation and execution

[0874] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[0875] User: Upload the final construction plan to the system.

[0876] Terminal: Sends the final construction plan to the server.

[0877] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[0878] This invention is a system that improves the efficiency and safety of construction work by providing more appropriate feedback by taking user emotions into consideration. Because the emotion engine provides feedback tailored to the user's state, more effective project management becomes possible.

[0879] The following describes the processing flow.

[0880] Step 1:

[0881] User: Access the system's website and view the registration form.

[0882] Step 2:

[0883] User: Enter company name, contact person's name, email address, and password, then submit.

[0884] Step 3:

[0885] Terminal: Sends the entered information to the server.

[0886] Step 4:

[0887] Server: Stores the received user information in the database.

[0888] Step 5:

[0889] Server: Sends a registration confirmation email to the user.

[0890] Step 6:

[0891] User: Opens a page to upload data files such as order specifications to the system.

[0892] Step 7:

[0893] User: Select the order specification document "Order Specification.pdf" and upload it.

[0894] Step 8:

[0895] Terminal: Sends uploaded data to the server.

[0896] Step 9:

[0897] Server: Temporarily stores data.

[0898] Step 10:

[0899] Server: Sends the stored data to the AI ​​analysis engine.

[0900] Step 11:

[0901] AI analysis engine: Performs analysis based on data and extracts important information based on laws, regulations, and company rules.

[0902] Step 12:

[0903] Emotion Engine: Analyzes the user's emotional state. For example, it considers the user's facial expressions while uploading and their typing speed.

[0904] Step 13:

[0905] Server: Integrates analysis results from the AI ​​analysis engine and the emotion engine to generate appropriate feedback.

[0906] Step 14:

[0907] Server: Sends the generated feedback to the terminal.

[0908] Step 15:

[0909] Device: Notifies the user of feedback.

[0910] Step 16:

[0911] User: Review the feedback and make any necessary corrections.

[0912] Step 17:

[0913] User: Upload the revised order specification to the system again.

[0914] Step 18:

[0915] Terminal: Sends the corrected data to the server.

[0916] Step 19:

[0917] Server: Resends the corrected data to the AI ​​analysis engine.

[0918] Step 20:

[0919] AI analysis engine: Re-analyzes the corrected data and generates new feedback.

[0920] Step 21:

[0921] Emotional Engine: Re-analyzes the user's emotional state and adjusts the feedback accordingly.

[0922] Step 22:

[0923] Server: Generates re-feedback based on the re-analysis results and the re-analysis results of the emotion engine, and sends it to the terminal.

[0924] Step 23:

[0925] Device: Notifies the user of further feedback.

[0926] Step 24:

[0927] User: Review all feedback and create the final construction plan.

[0928] Step 25:

[0929] User: Upload the final construction plan to the system.

[0930] Step 26:

[0931] Terminal: Sends the final construction plan to the server.

[0932] Step 27:

[0933] Server: Saves the final construction plan to the database.

[0934] Step 28:

[0935] Server: Manages project execution and progress, and notifies users as needed.

[0936] (Example 2)

[0937] Next, we will describe Example 2. 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".

[0938] In traditional construction work, it has been difficult to efficiently analyze information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments, and to provide feedback that complies with laws and company regulations. Furthermore, because feedback is provided only mechanically, without considering the user's feelings, there have been problems such as users feeling stressed or finding it difficult to accept the feedback. To solve these problems, there is a need for a system that generates more appropriate feedback that takes user feelings into account.

[0939] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user registration means for creating an account by inputting information by the user, a data transmission means for transmitting uploaded data to an AI analysis engine, a feedback generation means for generating feedback that takes into account the user's emotional state based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, and a plan management means for saving and managing the generated final construction plan. This makes it possible to improve efficiency and reliability in construction work by providing feedback that takes into account the user's emotions.

[0940] "User registration method" refers to the means by which a user enters information and creates an account.

[0941] "Data transmission means" refers to the means by which data uploaded by the user is sent to the AI ​​analysis engine.

[0942] A "feedback generation method" is a means of generating feedback that takes into account the user's emotional state based on the results analyzed by the AI ​​analysis engine.

[0943] A "feedback notification method" is a means of notifying the user of the generated feedback.

[0944] "Plan management means" refers to the means of saving and managing the final construction plan that has been generated.

[0945] "Method for sending corrected data" refers to a means for users to re-upload their corrected content to the system.

[0946] A "re-feedback generation method" is a means of generating feedback again, taking into account the user's emotional state based on the results of the re-analysis, and notifying the user.

[0947] A "data storage method" is a means of temporarily storing data uploaded by a user.

[0948] This invention aims to improve efficiency and reliability in construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules, and providing feedback that takes user sentiment into account.

[0949] System Overview

[0950] First, the user accesses the system and creates an account by entering basic information such as company name, contact person's name, email address, and password. The entered information is sent to the server and stored in the database. At the same time, a registration confirmation email is sent to the user.

[0951] Next, the user uploads data files such as order specifications and design notes to the system. The uploaded data is sent from the terminal to the server, temporarily stored, and then sent to the AI ​​analysis engine.

[0952] The AI ​​analysis engine analyzes uploaded data and evaluates whether it complies with laws, company regulations, and proprietary work rules. Furthermore, it uses an emotion engine to recognize the user's emotional state and reflect it in the feedback. The emotion engine analyzes the user's past operation logs and system usage history to assess the user's mental state.

[0953] The feedback is generated based on analysis results refined by the emotion engine and sent to the user terminal via the server. For example, feedback such as, "Article 3 of this order specification violates the latest safety standards, but we will provide detailed guidance on how to correct it," might be generated.

[0954] The user makes necessary corrections based on the feedback provided and re-uploads the data to the system. This corrected data is also sent to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are then adjusted again through the emotion engine and notified to the user as feedback.

[0955] Finally, after the user reviews all feedback and completes any necessary corrections, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to assist with project execution management and progress tracking. The server monitors whether the project is progressing according to plan and notifies the user as needed.

[0956] Hardware and software to be used

[0957] The following hardware and software are primarily used:

[0958] Server: Stores and processes data. Examples: Amazon Web Services (AWS), Google Cloud Platform (GCP).

[0959] Device: Used for data input and display of results. Examples: PC, tablet.

[0960] AI analysis engine: Analyzes data based on laws, company regulations, and unique work rules. Example: GPT-4.

[0961] Emotion engine: Evaluates the user's emotional state. Example: IBM Watson.

[0962] Specific example

[0963] User Registration

[0964] Example prompt: "I would like to create a new account. Please enter your company name, contact person's name, email address, and password."

[0965] Data Input

[0966] Specific example: "Order Specification.pdf"

[0967] Example prompt: "I have uploaded the order specification. Please parse it."

[0968] AI analysis and emotional feedback

[0969] Example prompt: "Please analyze the uploaded order specification and provide feedback."

[0970] project management

[0971] Specific example: "Revised Order Specifications.pdf"

[0972] Example prompt message: "I will re-upload the revised order specification. Please re-parse it."

[0973] Final confirmation and execution

[0974] Specific example: "Final Construction Plan.pdf"

[0975] Example prompt: "Uploading the final construction plan. Please track the project progress."

[0976] This system contributes to increased efficiency and reliability in construction work by providing more effective and user-friendly feedback that takes user emotions into consideration. Its key feature is the combination of an AI analysis engine and an emotion engine, which provides highly accurate feedback while taking the user's mental state into account.

[0977] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0978] Step 1:

[0979] The user accesses the system and is redirected to the account creation screen. The user enters the company name, contact person's name, email address, and password, then clicks the submit button.

[0980] Input: Company name, contact person's name, email address, password

[0981] Output: Registration confirmation request

[0982] Step 2:

[0983] The server receives the entered information and saves it to the database. The server then sends a registration confirmation email to the user.

[0984] Input: Registration confirmation request

[0985] Data processing: Saving input information, generating confirmation emails.

[0986] Output: Registration confirmation email

[0987] Step 3:

[0988] The user uploads the order specification document for a new construction project, "Order Specification Document.pdf". The user presses the upload button.

[0989] Input: Order specification "Order specification.pdf"

[0990] Output: Upload Request

[0991] Step 4:

[0992] The device sends the uploaded data to the server.

[0993] Input: Upload request

[0994] Output: Uploaded data

[0995] Step 5:

[0996] The server temporarily stores the received data and passes the destination path to the AI ​​analysis engine.

[0997] Input: Uploaded data

[0998] Data processing: Data storage, path generation

[0999] Output: Data path

[1000] Step 6:

[1001] The AI ​​analysis engine analyzes the order specifications based on the file paths provided by the server. It then evaluates whether the specifications comply with legal standards and company regulations.

[1002] Input: Data path

[1003] Data processing: Analysis of order specifications, comparison with reference points.

[1004] Output: Analysis results (Example: Safety standards under Article 3 are not met)

[1005] Step 7:

[1006] The server receives the analysis results from the AI ​​analysis engine.

[1007] Input: Analysis results

[1008] Output: Unadjusted analysis results

[1009] Step 8:

[1010] The emotion engine evaluates the user's emotional state and generates feedback based on the analysis results.

[1011] Input: Unadjusted analysis results, user's historical data

[1012] Data processing: Evaluating user emotional states, generating feedback.

[1013] Output: Adjustment feedback (e.g., Article 3 violates safety standards, but provides detailed guidance on how to correct it)

[1014] Step 9:

[1015] The server compiles feedback, refined by the emotion engine, and sends it to the user's terminal.

[1016] Input: Adjustment Feedback

[1017] Output: Feedback notification

[1018] Step 10:

[1019] Review the feedback provided by users and make any necessary corrections.

[1020] Input: Feedback notification

[1021] Output: Correction details

[1022] Step 11:

[1023] The user uploads the revised order specification file to the system again.

[1024] Input: Revised purchase order specification (Example: Revised purchase order specification.pdf)

[1025] Output: Re-upload request

[1026] Step 12:

[1027] The device is corrected and the uploaded files are sent back to the server.

[1028] Input: Re-upload request

[1029] Output: Re-uploaded data

[1030] Step 13:

[1031] The server sends the data back to the AI ​​analysis engine and requests a re-analysis.

[1032] Input: Re-uploaded data

[1033] Data processing: Data storage, re-analysis requests

[1034] Output: Reanalysis results

[1035] Step 14:

[1036] The emotion engine re-analyzes the results, taking into account the user's emotional state, and generates new feedback.

[1037] Input: Reanalysis results, user's historical data

[1038] Data processing: Sentiment evaluation, feedback generation

[1039] Output: Refeedback

[1040] Step 15:

[1041] The server compiles the re-analysis results and adjusted feedback, and then resends it to the user.

[1042] Input: Refeedback

[1043] Output: Re-feedback notification

[1044] Step 16:

[1045] The user confirms that all suggestions and warnings have been resolved, and then the final construction plan is created.

[1046] Input: Feedback notification

[1047] Output: Final construction plan

[1048] Step 17:

[1049] The user uploads the final construction plan to the system.

[1050] Input: Final Construction Plan (Example: Final Construction Plan.pdf)

[1051] Output: Final upload request

[1052] Step 18:

[1053] The terminal sends the final construction plan to the server.

[1054] Input: Final upload request

[1055] Output: Final Upload Data

[1056] Step 19:

[1057] The server saves the final construction plan to the database and begins project execution management and progress tracking.

[1058] Input: Last uploaded data

[1059] Data processing: Data storage, progress monitoring

[1060] Output: Progress notification

[1061] This clearly shows the overall system flow and the specific actions of each step, allowing users, terminals, and servers to understand the processes involved.

[1062] (Application Example 2)

[1063] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1064] In autonomous vehicles, safety and compliance with regulations are extremely important, but the driver's emotional state often influences these. Conventional systems have been unable to provide feedback that takes the driver's emotions into account, resulting in problems with ensuring driving safety and compliance with regulations. This invention aims to solve this problem by providing feedback that takes the driver's emotions into account, thereby improving the safety and compliance with regulations of autonomous vehicles.

[1065] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user registration means for creating an account by inputting information by the user, a data transmission means for transmitting uploaded data to an AI analysis engine, a feedback generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, a plan management means for saving and managing the generated final construction plan, an emotion recognition means for recognizing the driver's emotional state, and an emotion adjustment feedback generation means for adjusting the feedback based on the emotional state. This makes it possible to provide appropriate feedback that takes into account the driver's emotional state, thereby improving the safety of autonomous vehicles and compliance with legal regulations.

[1066] "User registration method" refers to a means by which a user creates an account by entering information.

[1067] "Data transmission means" refers to the means by which data uploaded by the user is sent to the AI ​​analysis engine.

[1068] A "feedback generation method" is a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[1069] A "feedback notification method" is a means of notifying the user of the generated feedback.

[1070] "Planning management means" refers to means for saving and managing the generated final construction plan.

[1071] "Means of emotional recognition" refers to means of recognizing the emotional state of the driver.

[1072] An "emotion adjustment feedback generation means" is a means for adjusting and generating feedback based on an emotional state.

[1073] This invention is a system for enhancing the safety and compliance with regulations of autonomous vehicles. Specifically, it improves the safety of operating autonomous vehicles by providing feedback that takes into account the driver's emotional state.

[1074] The system has the following functions:

[1075] User registration method

[1076] The server includes a means for users to create accounts by entering information. Users can access the system by entering basic information such as company name, contact person's name, email address, and password and submitting it to the server. The server stores the entered information in a database and sends a registration confirmation email to the user.

[1077] Data transmission means

[1078] When a user uploads data acquired from the vehicle's sensors and cameras to the system, the terminal sends this data to the server. The server temporarily stores the received data and then sends it to the AI ​​analysis engine.

[1079] Feedback generation means

[1080] The AI ​​analysis engine analyzes the received data and evaluates whether it complies with laws, regulations, and safety standards. It also detects whether the driver is engaging in specific behaviors (for example, exceeding the speed limit or entering a prohibited area).

[1081] emotion recognition means

[1082] The emotion recognition system uses an in-car camera to capture images of the driver's face and recognizes specific emotional states (e.g., anger, sadness, joy). Emotion recognition is performed using an emotion recognition library that evaluates the driver's facial microexpressions and overall facial movements.

[1083] Emotional regulation feedback generation method

[1084] The emotion-adjusted feedback generation method combines the analysis results of the AI ​​analysis engine with the driver's emotional state to generate adjusted feedback. For example, if the driver is angry, a warning such as "Please calm down and continue driving" can be added.

[1085] Feedback notification method

[1086] The generated feedback is sent from the server to the user's device. The device receives this notification and provides appropriate feedback to the driver.

[1087] Planning and management methods

[1088] The final construction plan and a history of important feedback are stored and managed on a server. This allows for continuous monitoring of project progress and safety assessments, and enables notifications to be sent to drivers and managers as needed.

[1089] Specific example

[1090] For example, if a vehicle is exceeding the speed limit, the AI ​​analysis engine will detect this and generate feedback warning it to "adjust your speed to the limit." Furthermore, if the emotion recognition system detects that the driver is angry, it will provide additional feedback such as "Please drive calmly."

[1091] Example of a prompt

[1092] "Evaluate compliance with legal regulations based on the detection results of road signs, vehicles, and pedestrians, and create feedback based on the driver's emotional state."

[1093] This will enable appropriate feedback that takes into account the driver's emotional state, thereby improving the safety and compliance with regulations of autonomous vehicles.

[1094] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1095] Step 1:

[1096] A user accesses the system and creates an account. Specifically, the user enters information such as company name, contact person's name, email address, and password, and sends this information to the server. The server stores the submitted information in a database and sends a registration confirmation email to the user. The input is user information, and the output is the storage in the database and the confirmation email.

[1097] Step 2:

[1098] The user uploads data acquired from the vehicle's sensors and cameras to the system. The terminal sends this data (e.g., camera footage and sensor information) to the server. The server temporarily stores the received data and then sends it to the AI ​​analysis engine. The input is sensor data, and the output is storage to the server and transmission to the AI ​​analysis engine.

[1099] Step 3:

[1100] The AI ​​analysis engine analyzes the received data. Specifically, it detects road signs, other vehicles, and pedestrians, and evaluates whether they comply with legal regulations and safety standards. The output of the analysis is a violation detection result, such as "exceeding the speed limit." The input is sensor data, and the output is the analysis result.

[1101] Step 4:

[1102] An emotion recognition system uses an in-car camera to recognize the driver's emotional state. An emotion recognition library analyzes the facial image to detect the driver's emotion (e.g., anger, sadness, joy). The input is facial image data, and the output is the emotional state.

[1103] Step 5:

[1104] The emotion-adjusted feedback generation mechanism combines the analysis results of the AI ​​analysis engine with the emotional state of the emotion recognition mechanism to generate feedback. Specifically, if the driver is angry, it generates additional feedback such as "Please calm down and continue driving." The input is the analysis results and emotional state, and the output is the adjusted feedback.

[1105] Step 6:

[1106] The server notifies the user terminal of the generated feedback. The terminal receives this notification and provides appropriate feedback to the driver. The input is the adjusted feedback, and the output is the notification to the user terminal.

[1107] Step 7:

[1108] The server stores and manages the final construction plan and feedback history. This allows for continuous monitoring of project progress and safety assessments, and enables notifications to drivers and managers as needed. Inputs are the final construction plan and feedback history, while outputs are the stored data and monitoring results.

[1109] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1110] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1111] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1112] [Third Embodiment]

[1113] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1114] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1115] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1116] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1117] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1119] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1120] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1121] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1122] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1123] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1124] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1125] This invention relates to a system for improving the efficiency of operations in the construction industry. Specifically, it is a platform for efficiently carrying out construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules.

[1126] System Overview

[1127] First, the user accesses the system and creates an account. This involves entering basic information such as the company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[1128] Next, users can upload order specifications, design notes, estimated unit prices, construction precautions, and client comments to the system. The uploaded data is sent from the terminal to the server, which temporarily stores it before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[1129] The analysis results are generated as feedback and notified to the user from the server. The user can then make corrections based on this feedback and re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are also notified to the user as feedback.

[1130] Finally, after the user reviews all feedback and completes any necessary revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to support project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[1131] Specific example

[1132] The following is a specific scenario.

[1133] 1. User Registration

[1134] User: A representative from a construction company visits the system and creates an account. They enter the company name, contact person's name, email address, and password, and then press the submit button.

[1135] Server: Receives this information and stores it in the database. Sends a registration confirmation email to the user.

[1136] 2. Data Input

[1137] User: Upload the order specification document ("Order Specification.pdf") for a new construction project to the system.

[1138] Terminal: Sends uploaded data to the server.

[1139] Server: Temporarily stores data and sends it to the AI ​​analysis engine.

[1140] 3. AI analysis and feedback

[1141] Server: The AI ​​analysis engine analyzes the order specifications and determines, for example, that "the safety standards in Article 3 have not been met."

[1142] Server: Based on the analysis results, it generates a warning stating that "Article 3 of this order specification violates the latest safety standards."

[1143] Server: Sends the generated feedback to the user.

[1144] Device: Notifies the user of feedback.

[1145] 4. Project Management

[1146] User: Review the feedback and revise Article 3 of the order specification.

[1147] User: Re-upload the revised order specification to the system.

[1148] Terminal: Sends the corrected data to the server.

[1149] Server: Requests the AI ​​analysis engine to re-analyze the corrected data.

[1150] Server: Generates feedback again based on the re-analysis results.

[1151] Server: Sends further feedback to the user.

[1152] 5. Final confirmation and execution

[1153] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[1154] User: Upload the final construction plan to the system.

[1155] Terminal: Sends the final construction plan to the server.

[1156] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[1157] In this way, this invention supports the efficient progress of construction work. This system reduces rework, prevents personal injury and service disruptions, and improves the overall efficiency of operations.

[1158] The following describes the processing flow.

[1159] Step 1:

[1160] User: Access the system's website and view the registration form.

[1161] Step 2:

[1162] User: Enter company name, contact person's name, email address, and password, then submit.

[1163] Step 3:

[1164] Terminal: Sends the entered information to the server.

[1165] Step 4:

[1166] Server: Stores the received user information in the database.

[1167] Step 5:

[1168] Server: Sends a registration confirmation email to the user.

[1169] Step 6:

[1170] User: Opens a page to upload data files such as order specifications to the system.

[1171] Step 7:

[1172] User: Select the order specification document "Order Specification.pdf" and upload it.

[1173] Step 8:

[1174] Terminal: Sends uploaded data to the server.

[1175] Step 9:

[1176] Server: Temporarily stores data.

[1177] Step 10:

[1178] Server: Sends the stored data to the AI ​​analysis engine.

[1179] Step 11:

[1180] AI analysis engine: Performs analysis based on data and extracts important information based on laws, regulations, and company rules.

[1181] Step 12:

[1182] Server: Receives analysis results from the AI ​​analysis engine and generates feedback.

[1183] Step 13:

[1184] Server: Sends the generated feedback to the terminal.

[1185] Step 14:

[1186] Device: Notifies the user of feedback.

[1187] Step 15:

[1188] User: Review the feedback and make any necessary corrections.

[1189] Step 16:

[1190] User: Upload the revised order specification to the system again.

[1191] Step 17:

[1192] Terminal: Sends the corrected data to the server.

[1193] Step 18:

[1194] Server: Resends the corrected data to the AI ​​analysis engine.

[1195] Step 19:

[1196] AI analysis engine: Re-analyzes the corrected data and generates new feedback.

[1197] Step 20:

[1198] Server: Generates re-feedback based on the re-analysis results and sends it to the terminal.

[1199] Step 21:

[1200] Device: Notifies the user of further feedback.

[1201] Step 22:

[1202] User: Review all feedback and create the final construction plan.

[1203] Step 23:

[1204] User: Upload the final construction plan to the system.

[1205] Step 24:

[1206] Terminal: Sends the final construction plan to the server.

[1207] Step 25:

[1208] Server: Saves the final construction plan to the database.

[1209] Step 26:

[1210] Server: Manages project execution and progress, and notifies users as needed.

[1211] (Example 1)

[1212] Next, we will describe Example 1. 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."

[1213] In the construction industry, it is necessary to verify that many tasks comply with relevant laws, regulations, and unique work rules. This can lead to complexity, rework, and decreased efficiency. Furthermore, even during project execution, insufficient compliance with laws and regulations and inadequate progress management can lead to deviations from the plan and accidents. Therefore, there is a need for means to resolve these issues and achieve efficient and reliable work execution.

[1214] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1215] In this invention, the server includes a user registration means for creating an account by having the user input information, an information transmission means for transmitting uploaded data to an AI analysis engine, an evaluation generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, an evaluation notification means for notifying the user of the feedback, a plan management means for storing and managing the generated final plan, a legal compliance evaluation means for evaluating whether the plan complies with laws and regulations, and a progress monitoring means for managing the execution and tracking the progress of the project. This enables efficient and reliable planning and management of construction projects in compliance with laws and regulations, eliminates the complexity of the work, and simplifies progress management.

[1216] 1. "User registration method" refers to a means by which a user creates an account by entering information.

[1217] 2. "Information transmission means" refers to the means for transmitting uploaded data to the AI ​​analysis engine.

[1218] 3. "Evaluation generation means" refers to a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[1219] 4. "Evaluation notification means" refers to a means of notifying the user of the generated feedback.

[1220] 5. "Plan management means" refers to means for saving and managing the final plan that has been generated.

[1221] 6. "Methods for evaluating compliance with laws and regulations" are means for evaluating whether something complies with laws and regulations.

[1222] 7. "Progress monitoring means" refers to the means used for managing the execution and tracking the progress of a project.

[1223] This invention relates to a system for improving the efficiency of operations in the construction industry. Specifically, it is a platform for efficiently carrying out construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules.

[1224] The main components of this system include a server, terminals, and an AI analysis engine. The server includes means for user registration, information transmission, evaluation generation, evaluation notification, plan management, legal compliance evaluation, and progress monitoring.

[1225] The server uses an SQL database to manage basic user information and uploaded data. The AI ​​analysis engine analyzes the data using machine learning libraries such as TensorFlow and PyTorch. The terminal provides an interface for users to upload data and check feedback.

[1226] The following is a concrete example of the system.

[1227] User Registration

[1228] User: Access the system, enter the company name, contact person's name, email address, and password on the account creation screen, and click the register button.

[1229] Server: Receives the entered information and saves it to the database. It also generates and sends a registration confirmation email to the user.

[1230] Terminal: The user will receive a registration confirmation email.

[1231] Upload data

[1232] User: Drag and drop data such as order specifications, design notes, estimated unit prices, construction precautions, and client comments onto the system's upload screen, or select them using the file selection dialog.

[1233] Terminal: Sends the selected files to the server.

[1234] Server: Receives the file and stores it temporarily.

[1235] Temporary data storage and AI analysis request

[1236] Server: Sends temporarily stored data to the AI ​​analysis engine and requests analysis.

[1237] AI analysis and feedback generation

[1238] Server: The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and proprietary work rules.

[1239] Server: Receives analysis results and generates feedback based on them. For example, it might generate a warning such as, "Article 3 of this order specification violates the latest safety standards."

[1240] Server: Notifies the user of the feedback.

[1241] Reviewing feedback and correcting data

[1242] User: Check the feedback received from the server.

[1243] User: Based on feedback, revise data such as order specifications.

[1244] Request to re-upload corrected data and re-analyze it.

[1245] User: Re-upload the revised order specification to the system.

[1246] Terminal: Resend the corrected data to the server.

[1247] Server: Resubmits the corrected data to the AI ​​analysis engine and requests re-analysis.

[1248] Server: Receives re-analysis results and generates feedback again.

[1249] Server: Notifies the user of further feedback.

[1250] Uploading the final construction plan and project management

[1251] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[1252] User: Upload the final construction plan to the system.

[1253] Terminal: Sends files to the server.

[1254] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[1255] As a concrete example, the following prompt statement is shown:

[1256] Example of a prompt

[1257] 1. User Registration

[1258] I would like to create an account in the system. Please enter your company name, contact person's name, email address, and password.

[1259] 2. "Data Input

[1260] I have uploaded the order specifications for a new project. Please analyze this file.

[1261] 3. AI analysis and feedback

[1262] The analysis results for the order specifications are in. Article 3 violates safety standards and requires correction.

[1263] 4. "Further feedback"

[1264] I have reviewed the feedback and revised the order specifications. Please analyze it again.

[1265] 5. Final confirmation and execution

[1266] The final construction plan is complete. Uploading it to the system. Please begin project management.

[1267] In this way, this system supports the efficient progress of construction work. It enables efficient and reliable planning and management of construction projects in compliance with laws and regulations.

[1268] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1269] Step 1:

[1270] User Registration

[1271] User: Access the system, enter the company name, contact person's name, email address, and password on the account creation screen, and click the register button.

[1272] Server: Receives the entered information and saves it to the database. Executes the following SQL query: INSERT INTO users (company_name, contact_name, email, password) VALUES ('Company Name', 'Contact Person Name', 'Email Address', 'Password'). Generates a registration confirmation email and sends it to the user.

[1273] Input: Company name, contact person's name, email address, and password entered by the user.

[1274] Output: User information stored in the database, confirmation email sent to the user.

[1275] Terminal: The user's screen displays the message, "A registration confirmation email has been sent. Please check your email."

[1276] Step 2:

[1277] Upload data

[1278] User: Drag and drop data such as order specifications, design notes, estimated unit prices, construction precautions, and client comments onto the system's upload screen, or select them using the file selection dialog.

[1279] Terminal: Sends the file selected from the file selection dialog to the server using the multipart / form-data protocol.

[1280] Input: The file to be uploaded (e.g., "Order Specifications.pdf").

[1281] Output: File data sent to the server.

[1282] Server: Saves received file data to a temporary storage directory. For example, use the function store_temp_file('OrderSpecifications.pdf').

[1283] Input: File data sent from the terminal.

[1284] Output: Files saved in the temporary directory.

[1285] Step 3:

[1286] Temporary data storage and AI analysis request

[1287] Server: Sends temporarily stored data to the AI ​​analysis engine. Specifically, it uses the function `send_to_ai_engine('temp / order_specification_document.pdf')` to request analysis.

[1288] Input: Temporarily saved file data (e.g., "temp / order_specification.pdf").

[1289] Output: Analysis request sent to the AI ​​analysis engine.

[1290] Step 4:

[1291] AI analysis and feedback generation

[1292] Server: The AI ​​analysis engine analyzes the data and receives evaluation results on whether it complies with laws, company regulations, and proprietary work rules.

[1293] Input: Data sent to the AI ​​analysis engine.

[1294] Output: Evaluation results (e.g., feedback stating "Article 3 violates the latest safety standards").

[1295] Server: Generates feedback based on the analysis results and notifies the user. For example, it might generate a warning message stating, "Article 3 of this order specification violates the latest safety standards."

[1296] Input: Evaluation results from the AI ​​analysis engine.

[1297] Output: Feedback notified to the user.

[1298] Step 5:

[1299] Reviewing feedback and correcting data

[1300] User: Review the feedback received from the system and revise data such as order specifications.

[1301] Input: Feedback received from the system.

[1302] Output: Data such as the revised order specifications. Specifically, Article 3 of "Order Specifications.pdf" was modified in an editor to comply with the latest safety standards.

[1303] Step 6:

[1304] Request to re-upload corrected data and re-analyze it.

[1305] User: Upload the revised order specifications to the system again.

[1306] Input: Modified file (e.g., "Order Specification_v2.pdf").

[1307] Output: File data sent to the server.

[1308] Terminal: Sends modified data to the server using the multipart / form-data protocol.

[1309] Input: The modified file.

[1310] Output: File data sent to the server.

[1311] Server: Receives the modified data and saves it again to the temporary storage directory. For example, store_temp_file('Order Specification_v2.pdf').

[1312] Input: Modified file data sent from the terminal.

[1313] Output: The file has been resaved to the temporary directory.

[1314] Server: Resends the corrected data to the AI ​​analysis engine and requests re-analysis. Specifically, it calls send_to_ai_engine('temp / order_specification_v2.pdf').

[1315] Input: Re-saved modified file data.

[1316] Output: Analysis request resent to the AI ​​analysis engine.

[1317] Server: Receives the re-analysis results, generates feedback again, and notifies the user. For example, it might generate feedback stating, "All items comply with the latest safety standards."

[1318] Input: Re-evaluation results from the AI ​​analysis engine.

[1319] Output: Further feedback notified to the user.

[1320] Step 7:

[1321] Uploading the final construction plan and project management

[1322] User: Create the final construction plan based on the final feedback.

[1323] Input: Final feedback.

[1324] Output: Final Construction Plan (Example: "Final Construction Plan.pdf").

[1325] User: Upload the final construction plan to the system.

[1326] Input: Final construction plan.

[1327] Output: Sending plan data to the server.

[1328] Terminal: Sends the final construction plan to the server using the multipart / form-data protocol.

[1329] Input: Final construction plan.

[1330] Output: Sending plan data to the server.

[1331] Server: Receives the final construction plan and saves it to the plan management directory. For example, store_final_plan('final_construction_plan.pdf').

[1332] Input: Plan data sent from the terminal.

[1333] Output: The final construction plan saved in the save directory.

[1334] Server: Records necessary information and monitors project progress in order to initiate project execution management and progress tracking.

[1335] Input: Final construction plan.

[1336] Output: Progress monitoring data for project management.

[1337] (Application Example 1)

[1338] Next, we will explain Application Example 1. In the following explanation, 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."

[1339] In traditional construction work, a major challenge has been the time-consuming and laborious process of manually verifying compliance with legal regulations, company rules, and unique work procedures. Furthermore, similar problems are more likely to occur during factory work, making it difficult to adhere to safety standards. As a result, there are challenges such as decreased work efficiency and an increased risk of personal injury and service disruptions.

[1340] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1341] In this invention, the server includes a user registration means for creating an account by having the user input information, a data transmission means for sending uploaded data to an AI analysis engine, a feedback display means for displaying feedback on a smart device in real time, a feedback generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, and a plan management means for saving and managing the generated final construction plan. As a result, the user can receive accurate feedback in real time that complies with laws and regulations, company rules, and unique work rules, enabling them to carry out their work safely and efficiently.

[1342] "User registration method" refers to a means by which a user creates an account by entering information.

[1343] "Data transmission means" refers to the means for transmitting uploaded data to the AI ​​analysis engine.

[1344] A "feedback display means" is a means for displaying feedback on a smart device in real time.

[1345] A "feedback generation method" is a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[1346] A "feedback notification method" is a means of notifying the user of the generated feedback.

[1347] "Planning management means" refers to means for saving and managing the generated final construction plan.

[1348] "Method for sending corrected data" refers to a means for users to re-upload their corrected content to the system.

[1349] A "re-feedback generation means" is a means for generating feedback again based on the results of re-analysis and notifying the user.

[1350] A "data storage method" is a means of temporarily storing data uploaded by a user.

[1351] A "smart device" is a device that has the capability to perform computer processing and provides information to the user. Examples include smart glasses and head-mounted displays.

[1352] This invention relates to a method for improving the efficiency and safety of construction work and factory operations using a certain system. Specific embodiments are described below.

[1353] First, users create an account by accessing the system and entering information. This includes basic information such as company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[1354] Next, the user uploads data related to construction work or factory operations (e.g., order specifications or work procedures) to the system. The terminal sends the uploaded data to the server, which temporarily stores the data before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[1355] The analysis results are generated as feedback and notified to the user from the server. Specifically, the feedback is displayed in real time on a smart device (such as smart glasses) using a feedback display means. The user can also review this feedback, make any necessary corrections, and then re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The results of the re-analysis are similarly notified to the user as feedback.

[1356] Finally, after the user reviews all feedback and completes the revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to assist with project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[1357] The hardware will include smart glasses (e.g., Google Glass, Microsoft HoloLens) and web servers that provide appropriate API endpoints. The software will utilize AI analysis engines such as NLP engines and rule-based systems.

[1358] For example, when factory workers assemble part A using smart glasses, they can immediately access a checklist based on the latest safety standards. An AI analysis engine audits all steps, and any violations detected are displayed instantly.

[1359] Examples of prompt statements are as follows:

[1360] When assembling part A in the factory, please review the following latest safety standards:

[1361] Component A is properly secured.

[1362] The correct tools are being used.

[1363] Workers must wear protective equipment.

[1364] If there are any violations, please display the feedback on your smart glasses.

[1365] In this way, users can receive accurate feedback in real time that complies with legal regulations, company rules, and unique work rules, enabling them to carry out their work safely and efficiently.

[1366] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1367] Step 1:

[1368] The user accesses the system and creates an account. This involves entering basic information such as company name, contact person's name, email address, and password. The entered information is sent to the server via the terminal. The server stores this information in a database and sends a registration confirmation email to the user. The input data includes the company name and contact person's name, while the output data is the registration confirmation email.

[1369] Step 2:

[1370] Users upload specifications and work procedures for new construction projects or tasks to the system. The terminal sends the uploaded data to the server. The server temporarily stores the data and then sends it to the AI ​​analysis engine. The input data consists of the uploaded specifications and procedures, and the output data is the data sent for AI analysis.

[1371] Step 3:

[1372] The server sends the uploaded data to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and proprietary work rules. The input data consists of specifications and procedures, and the output data is the analysis results for feedback.

[1373] Step 4:

[1374] The server receives analysis results from the AI ​​analysis engine and generates feedback. Feedback is generated using a feedback generation method. The input data is the AI ​​analysis results, and the output data is the feedback message.

[1375] Step 5:

[1376] The server notifies the user of the generated feedback using a feedback notification means. The feedback display means displays the feedback on the smart device in real time. The input data is the generated feedback, and the output data is the feedback message displayed on the smart device.

[1377] Step 6:

[1378] The user makes corrections based on feedback and uploads the corrected data back to the system. The terminal sends the corrected data to the server. The input data is the corrected specifications or procedures, and the output data is the data to be sent for re-analysis.

[1379] Step 7:

[1380] The server sends the corrected data back to the AI ​​analysis engine. The AI ​​analysis engine re-analyzes the corrected data and outputs the analysis results again. The input data is the corrected data, and the output data is the re-analysis result.

[1381] Step 8:

[1382] The server receives the re-analysis results, generates feedback again using the re-feedback generation mechanism, and notifies the user. The input data is the re-analysis results, and the output data is the re-feedback message.

[1383] Step 9:

[1384] After the user reviews all feedback and completes any necessary corrections, they create the final construction plan and upload it to the system. The terminal then sends the final construction plan to the server. The input data is the final construction plan, and the output data is the plan data stored on the server.

[1385] Step 10:

[1386] The server stores the final construction plan and uses planning management tools to manage project execution and track progress. It monitors whether the project is progressing according to plan and notifies the user as needed. The input data is the final construction plan, and the output data is progress notifications.

[1387] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1388] This invention relates to a platform for improving the efficiency of operations in the construction industry by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules, and providing feedback that takes user sentiment into consideration.

[1389] System Overview

[1390] First, the user accesses the system and creates an account. To do this, they enter basic information such as company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[1391] Users can upload data files such as order specifications, design notes, estimated unit prices, construction precautions, and client comments to the system. The uploaded data is sent from the terminal to the server, which temporarily stores it before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[1392] Furthermore, an emotion engine is used to recognize the user's emotions and generate feedback that takes these emotions into account. The analysis results are adjusted by the emotion engine based on the user's emotional state, providing feedback tailored to individual needs and mental state. The server sends the generated feedback to the user's terminal for notification.

[1393] Users can make corrections based on feedback and re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are also adjusted through the emotion engine and notified to the user as feedback.

[1394] Finally, after the user reviews all feedback and completes any necessary revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to support project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[1395] Specific example

[1396] The following is a specific scenario.

[1397] 1. User Registration

[1398] User: A representative from a construction company visits the system and creates an account. They enter the company name, contact person's name, email address, and password, and then press the submit button.

[1399] Server: Receives this information and stores it in the database. Sends a registration confirmation email to the user.

[1400] 2. Data Input

[1401] User: Upload the order specification document ("Order Specification.pdf") for a new construction project to the system.

[1402] Terminal: Sends uploaded data to the server.

[1403] Server: Temporarily stores data and sends it to the AI ​​analysis engine.

[1404] 3. AI analysis and emotional feedback

[1405] Server: The AI ​​analysis engine analyzes the order specifications and determines, for example, that "the safety standards in Article 3 have not been met."

[1406] Emotion Engine: Evaluates the user's current emotional state and adjusts feedback based on the analysis results.

[1407] Server: Based on the analysis results, it generates a warning stating that "Article 3 of this order specification violates the latest safety standards" and sends it to the user terminal as feedback via the emotion engine.

[1408] Device: Notifies the user of feedback.

[1409] 4. Project Management

[1410] User: Review the feedback and revise Article 3 of the order specification.

[1411] User: Re-upload the revised order specification to the system.

[1412] Terminal: Sends the corrected data to the server.

[1413] Server: Requests the AI ​​analysis engine to re-analyze the corrected data.

[1414] Emotion Engine: Re-analyzes the corrected data and considers the user's emotional state when generating new feedback.

[1415] Server: Generates feedback again based on the re-analysis results.

[1416] Server: Sends further feedback to the user.

[1417] 5. Final confirmation and execution

[1418] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[1419] User: Upload the final construction plan to the system.

[1420] Terminal: Sends the final construction plan to the server.

[1421] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[1422] This invention is a system that improves the efficiency and safety of construction work by providing more appropriate feedback by taking user emotions into consideration. Because the emotion engine provides feedback tailored to the user's state, more effective project management becomes possible.

[1423] The following describes the processing flow.

[1424] Step 1:

[1425] User: Access the system's website and view the registration form.

[1426] Step 2:

[1427] User: Enter company name, contact person's name, email address, and password, then submit.

[1428] Step 3:

[1429] Terminal: Sends the entered information to the server.

[1430] Step 4:

[1431] Server: Stores the received user information in the database.

[1432] Step 5:

[1433] Server: Sends a registration confirmation email to the user.

[1434] Step 6:

[1435] User: Opens a page to upload data files such as order specifications to the system.

[1436] Step 7:

[1437] User: Select the order specification document "Order Specification.pdf" and upload it.

[1438] Step 8:

[1439] Terminal: Sends uploaded data to the server.

[1440] Step 9:

[1441] Server: Temporarily stores data.

[1442] Step 10:

[1443] Server: Sends the stored data to the AI ​​analysis engine.

[1444] Step 11:

[1445] AI analysis engine: Performs analysis based on data and extracts important information based on laws, regulations, and company rules.

[1446] Step 12:

[1447] Emotion Engine: Analyzes the user's emotional state. For example, it considers the user's facial expressions while uploading and their typing speed.

[1448] Step 13:

[1449] Server: Integrates analysis results from the AI ​​analysis engine and the emotion engine to generate appropriate feedback.

[1450] Step 14:

[1451] Server: Sends the generated feedback to the terminal.

[1452] Step 15:

[1453] Device: Notifies the user of feedback.

[1454] Step 16:

[1455] User: Review the feedback and make any necessary corrections.

[1456] Step 17:

[1457] User: Upload the revised order specification to the system again.

[1458] Step 18:

[1459] Terminal: Sends the corrected data to the server.

[1460] Step 19:

[1461] Server: Resends the corrected data to the AI ​​analysis engine.

[1462] Step 20:

[1463] AI analysis engine: Re-analyzes the corrected data and generates new feedback.

[1464] Step 21:

[1465] Emotional Engine: Re-analyzes the user's emotional state and adjusts the feedback accordingly.

[1466] Step 22:

[1467] Server: Generates new feedback based on the re-analysis results and the re-analysis results of the emotion engine, and sends it to the terminal.

[1468] Step 23:

[1469] Device: Notifies the user of further feedback.

[1470] Step 24:

[1471] User: Review all feedback and create the final construction plan.

[1472] Step 25:

[1473] User: Upload the final construction plan to the system.

[1474] Step 26:

[1475] Terminal: Sends the final construction plan to the server.

[1476] Step 27:

[1477] Server: Saves the final construction plan to the database.

[1478] Step 28:

[1479] Server: Manages project execution and progress, and notifies users as needed.

[1480] (Example 2)

[1481] Next, we will describe Example 2. 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."

[1482] In traditional construction work, it has been difficult to efficiently analyze information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments, and to provide feedback that complies with laws and company regulations. Furthermore, because feedback is provided only mechanically, without considering the user's feelings, there have been problems such as users feeling stressed or finding it difficult to accept the feedback. To solve these problems, there is a need for a system that generates more appropriate feedback that takes user feelings into account.

[1483] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user registration means for creating an account by inputting information by the user, a data transmission means for transmitting uploaded data to an AI analysis engine, a feedback generation means for generating feedback that takes into account the user's emotional state based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, and a plan management means for saving and managing the generated final construction plan. This makes it possible to improve efficiency and reliability in construction work by providing feedback that takes into account the user's emotions.

[1484] "User registration method" refers to the means by which a user enters information and creates an account.

[1485] "Data transmission means" refers to the means by which data uploaded by the user is sent to the AI ​​analysis engine.

[1486] A "feedback generation method" is a means of generating feedback that takes into account the user's emotional state based on the results analyzed by the AI ​​analysis engine.

[1487] A "feedback notification method" is a means of notifying the user of the generated feedback.

[1488] "Plan management means" refers to the means of saving and managing the final construction plan that has been generated.

[1489] "Method for sending corrected data" refers to a means for users to re-upload their corrected content to the system.

[1490] A "re-feedback generation method" is a means of generating feedback again, taking into account the user's emotional state based on the results of the re-analysis, and notifying the user.

[1491] A "data storage method" is a means of temporarily storing data uploaded by a user.

[1492] This invention aims to improve efficiency and reliability in construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules, and providing feedback that takes user sentiment into account.

[1493] System Overview

[1494] First, the user accesses the system and creates an account by entering basic information such as company name, contact person's name, email address, and password. The entered information is sent to the server and stored in the database. At the same time, a registration confirmation email is sent to the user.

[1495] Next, the user uploads data files such as order specifications and design notes to the system. The uploaded data is sent from the terminal to the server, temporarily stored, and then sent to the AI ​​analysis engine.

[1496] The AI ​​analysis engine analyzes uploaded data and evaluates whether it complies with laws, company regulations, and proprietary work rules. Furthermore, it uses an emotion engine to recognize the user's emotional state and reflect it in the feedback. The emotion engine analyzes the user's past operation logs and system usage history to assess the user's mental state.

[1497] The feedback is generated based on analysis results refined by the emotion engine and sent to the user terminal via the server. For example, feedback such as, "Article 3 of this order specification violates the latest safety standards, but we will provide detailed guidance on how to correct it," might be generated.

[1498] The user makes necessary corrections based on the feedback provided and re-uploads the data to the system. This corrected data is also sent to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are then adjusted again through the emotion engine and notified to the user as feedback.

[1499] Finally, after the user reviews all feedback and completes any necessary corrections, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to assist with project execution management and progress tracking. The server monitors whether the project is progressing according to plan and notifies the user as needed.

[1500] Hardware and software to be used

[1501] The following hardware and software are primarily used:

[1502] Server: Stores and processes data. Examples: Amazon Web Services (AWS), Google Cloud Platform (GCP).

[1503] Device: Used for data input and display of results. Examples: PC, tablet.

[1504] AI analysis engine: Analyzes data based on laws, company regulations, and unique work rules. Example: GPT-4.

[1505] Emotion engine: Evaluates the user's emotional state. Example: IBM Watson.

[1506] Specific example

[1507] User Registration

[1508] Example prompt: "I would like to create a new account. Please enter your company name, contact person's name, email address, and password."

[1509] Data Input

[1510] Specific example: "Order Specification.pdf"

[1511] Example prompt: "I have uploaded the order specification. Please parse it."

[1512] AI analysis and emotional feedback

[1513] Example prompt: "Please analyze the uploaded order specification and provide feedback."

[1514] project management

[1515] Specific example: "Revised Order Specifications.pdf"

[1516] Example prompt message: "I will re-upload the revised order specification. Please re-parse it."

[1517] Final confirmation and execution

[1518] Specific example: "Final Construction Plan.pdf"

[1519] Example prompt: "Uploading the final construction plan. Please track the project progress."

[1520] This system contributes to increased efficiency and reliability in construction work by providing more effective and user-friendly feedback that takes user emotions into consideration. Its key feature is the combination of an AI analysis engine and an emotion engine, which provides highly accurate feedback while taking the user's mental state into account.

[1521] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1522] Step 1:

[1523] The user accesses the system and is redirected to the account creation screen. The user enters the company name, contact person's name, email address, and password, then clicks the submit button.

[1524] Input: Company name, contact person's name, email address, password

[1525] Output: Registration confirmation request

[1526] Step 2:

[1527] The server receives the entered information and saves it to the database. The server then sends a registration confirmation email to the user.

[1528] Input: Registration confirmation request

[1529] Data processing: Saving input information, generating confirmation emails.

[1530] Output: Registration confirmation email

[1531] Step 3:

[1532] The user uploads the order specification document for a new construction project, "Order Specification Document.pdf". The user presses the upload button.

[1533] Input: Order specification "Order specification.pdf"

[1534] Output: Upload Request

[1535] Step 4:

[1536] The device sends the uploaded data to the server.

[1537] Input: Upload request

[1538] Output: Uploaded data

[1539] Step 5:

[1540] The server temporarily stores the received data and passes the destination path to the AI ​​analysis engine.

[1541] Input: Uploaded data

[1542] Data processing: Data storage, path generation

[1543] Output: Data path

[1544] Step 6:

[1545] The AI ​​analysis engine analyzes the order specifications based on the file paths provided by the server. It then evaluates whether the specifications comply with legal standards and company regulations.

[1546] Input: Data path

[1547] Data processing: Analysis of order specifications, comparison with reference points.

[1548] Output: Analysis results (Example: Safety standards under Article 3 are not met)

[1549] Step 7:

[1550] The server receives the analysis results from the AI ​​analysis engine.

[1551] Input: Analysis results

[1552] Output: Unadjusted analysis results

[1553] Step 8:

[1554] The emotion engine evaluates the user's emotional state and generates feedback based on the analysis results.

[1555] Input: Unadjusted analysis results, user's historical data

[1556] Data processing: Evaluating user emotional states, generating feedback.

[1557] Output: Adjustment feedback (e.g., Article 3 violates safety standards, but provides detailed guidance on how to correct it)

[1558] Step 9:

[1559] The server compiles feedback, refined by the emotion engine, and sends it to the user's terminal.

[1560] Input: Adjustment Feedback

[1561] Output: Feedback notification

[1562] Step 10:

[1563] Review the feedback provided by users and make any necessary corrections.

[1564] Input: Feedback notification

[1565] Output: Correction details

[1566] Step 11:

[1567] The user uploads the revised order specification file to the system again.

[1568] Input: Revised purchase order specification (Example: Revised purchase order specification.pdf)

[1569] Output: Re-upload request

[1570] Step 12:

[1571] The device is corrected and the uploaded files are sent back to the server.

[1572] Input: Re-upload request

[1573] Output: Re-uploaded data

[1574] Step 13:

[1575] The server sends the data back to the AI ​​analysis engine and requests a re-analysis.

[1576] Input: Re-uploaded data

[1577] Data processing: Data storage, re-analysis requests

[1578] Output: Reanalysis results

[1579] Step 14:

[1580] The emotion engine re-analyzes the results, taking into account the user's emotional state, and generates new feedback.

[1581] Input: Reanalysis results, user's historical data

[1582] Data processing: Sentiment evaluation, feedback generation

[1583] Output: Refeedback

[1584] Step 15:

[1585] The server compiles the re-analysis results and adjusted feedback, and then resends it to the user.

[1586] Input: Refeedback

[1587] Output: Re-feedback notification

[1588] Step 16:

[1589] The user confirms that all suggestions and warnings have been resolved, and then the final construction plan is created.

[1590] Input: Feedback notification

[1591] Output: Final construction plan

[1592] Step 17:

[1593] The user uploads the final construction plan to the system.

[1594] Input: Final Construction Plan (Example: Final Construction Plan.pdf)

[1595] Output: Final upload request

[1596] Step 18:

[1597] The terminal sends the final construction plan to the server.

[1598] Input: Final upload request

[1599] Output: Final Upload Data

[1600] Step 19:

[1601] The server saves the final construction plan to the database and begins project execution management and progress tracking.

[1602] Input: Last uploaded data

[1603] Data processing: Data storage, progress monitoring

[1604] Output: Progress notification

[1605] This clearly shows the overall system flow and the specific actions of each step, allowing users, terminals, and servers to understand the processes involved.

[1606] (Application Example 2)

[1607] Next, we will explain application example 2. In the following explanation, 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."

[1608] In autonomous vehicles, safety and compliance with regulations are extremely important, but the driver's emotional state often influences these. Conventional systems have been unable to provide feedback that takes the driver's emotions into account, resulting in problems with ensuring driving safety and compliance with regulations. This invention aims to solve this problem by providing feedback that takes the driver's emotions into account, thereby improving the safety and compliance with regulations of autonomous vehicles.

[1609] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user registration means for creating an account by inputting information by the user, a data transmission means for transmitting uploaded data to an AI analysis engine, a feedback generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, a plan management means for saving and managing the generated final construction plan, an emotion recognition means for recognizing the driver's emotional state, and an emotion adjustment feedback generation means for adjusting the feedback based on the emotional state. This makes it possible to provide appropriate feedback that takes into account the driver's emotional state, thereby improving the safety of autonomous vehicles and compliance with legal regulations.

[1610] "User registration method" refers to a means by which a user creates an account by entering information.

[1611] "Data transmission means" refers to the means by which data uploaded by the user is sent to the AI ​​analysis engine.

[1612] A "feedback generation method" is a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[1613] A "feedback notification method" is a means of notifying the user of the generated feedback.

[1614] "Planning management means" refers to means for saving and managing the generated final construction plan.

[1615] "Means of emotional recognition" refers to means of recognizing the emotional state of the driver.

[1616] An "emotion adjustment feedback generation means" is a means for adjusting and generating feedback based on an emotional state.

[1617] This invention is a system for enhancing the safety and compliance with regulations of autonomous vehicles. Specifically, it improves the safety of operating autonomous vehicles by providing feedback that takes into account the driver's emotional state.

[1618] The system has the following functions:

[1619] User registration method

[1620] The server includes a means for users to create accounts by entering information. Users can access the system by entering basic information such as company name, contact person's name, email address, and password and submitting it to the server. The server stores the entered information in a database and sends a registration confirmation email to the user.

[1621] Data transmission means

[1622] When a user uploads data acquired from the vehicle's sensors and cameras to the system, the terminal sends this data to the server. The server temporarily stores the received data and then sends it to the AI ​​analysis engine.

[1623] Feedback generation means

[1624] The AI ​​analysis engine analyzes the received data and evaluates whether it complies with laws, regulations, and safety standards. It also detects whether the driver is engaging in specific behaviors (for example, exceeding the speed limit or entering a prohibited area).

[1625] emotion recognition means

[1626] The emotion recognition system uses an in-car camera to capture images of the driver's face and recognizes specific emotional states (e.g., anger, sadness, joy). Emotion recognition is performed using an emotion recognition library that evaluates the driver's facial microexpressions and overall facial movements.

[1627] Emotional regulation feedback generation method

[1628] The emotion-adjusted feedback generation method combines the analysis results of the AI ​​analysis engine with the driver's emotional state to generate adjusted feedback. For example, if the driver is angry, a warning such as "Please calm down and continue driving" can be added.

[1629] Feedback notification method

[1630] The generated feedback is sent from the server to the user's device. The device receives this notification and provides appropriate feedback to the driver.

[1631] Planning and management methods

[1632] The final construction plan and a history of important feedback are stored and managed on a server. This allows for continuous monitoring of project progress and safety assessments, and enables notifications to be sent to drivers and managers as needed.

[1633] Specific example

[1634] For example, if a vehicle is exceeding the speed limit, the AI ​​analysis engine will detect this and generate feedback warning it to "adjust your speed to the limit." Furthermore, if the emotion recognition system detects that the driver is angry, it will provide additional feedback such as "Please drive calmly."

[1635] Example of a prompt

[1636] "Evaluate compliance with legal regulations based on the detection results of road signs, vehicles, and pedestrians, and create feedback based on the driver's emotional state."

[1637] This will enable appropriate feedback that takes into account the driver's emotional state, thereby improving the safety and compliance with regulations of autonomous vehicles.

[1638] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1639] Step 1:

[1640] A user accesses the system and creates an account. Specifically, the user enters information such as company name, contact person's name, email address, and password, and sends this information to the server. The server stores the submitted information in a database and sends a registration confirmation email to the user. The input is user information, and the output is the storage in the database and the confirmation email.

[1641] Step 2:

[1642] The user uploads data acquired from the vehicle's sensors and cameras to the system. The terminal sends this data (e.g., camera footage and sensor information) to the server. The server temporarily stores the received data and then sends it to the AI ​​analysis engine. The input is sensor data, and the output is storage to the server and transmission to the AI ​​analysis engine.

[1643] Step 3:

[1644] The AI ​​analysis engine analyzes the received data. Specifically, it detects road signs, other vehicles, and pedestrians, and evaluates whether they comply with legal regulations and safety standards. The output of the analysis is a violation detection result, such as "exceeding the speed limit." The input is sensor data, and the output is the analysis result.

[1645] Step 4:

[1646] An emotion recognition system uses an in-car camera to recognize the driver's emotional state. An emotion recognition library analyzes the facial image to detect the driver's emotion (e.g., anger, sadness, joy). The input is facial image data, and the output is the emotional state.

[1647] Step 5:

[1648] The emotion-adjusted feedback generation mechanism combines the analysis results of the AI ​​analysis engine with the emotional state of the emotion recognition mechanism to generate feedback. Specifically, if the driver is angry, it generates additional feedback such as "Please calm down and continue driving." The input is the analysis results and emotional state, and the output is the adjusted feedback.

[1649] Step 6:

[1650] The server notifies the user terminal of the generated feedback. The terminal receives this notification and provides appropriate feedback to the driver. The input is the adjusted feedback, and the output is the notification to the user terminal.

[1651] Step 7:

[1652] The server stores and manages the final construction plan and feedback history. This allows for continuous monitoring of project progress and safety assessments, and enables notifications to drivers and managers as needed. Inputs are the final construction plan and feedback history, while outputs are the stored data and monitoring results.

[1653] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1654] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1655] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1656] [Fourth Embodiment]

[1657] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1658] As shown in Figure 7, the 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.

[1659] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1660] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1661] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1662] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1663] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1664] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1665] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1666] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1667] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1668] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1669] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1670] This invention relates to a system for improving the efficiency of operations in the construction industry. Specifically, it is a platform for efficiently carrying out construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules.

[1671] System Overview

[1672] First, the user accesses the system and creates an account. This involves entering basic information such as the company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[1673] Next, users can upload order specifications, design notes, estimated unit prices, construction precautions, and client comments to the system. The uploaded data is sent from the terminal to the server, which temporarily stores it before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[1674] The analysis results are generated as feedback and notified to the user from the server. The user can then make corrections based on this feedback and re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are also notified to the user as feedback.

[1675] Finally, after the user reviews all feedback and completes any necessary revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to support project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[1676] Specific example

[1677] The following is a specific scenario.

[1678] 1. User Registration

[1679] User: A representative from a construction company visits the system and creates an account. They enter the company name, contact person's name, email address, and password, and then press the submit button.

[1680] Server: Receives this information and stores it in the database. Sends a registration confirmation email to the user.

[1681] 2. Data Input

[1682] User: Upload the order specification document ("Order Specification.pdf") for a new construction project to the system.

[1683] Terminal: Sends uploaded data to the server.

[1684] Server: Temporarily stores data and sends it to the AI ​​analysis engine.

[1685] 3. AI analysis and feedback

[1686] Server: The AI ​​analysis engine analyzes the order specifications and determines, for example, that "the safety standards in Article 3 have not been met."

[1687] Server: Based on the analysis results, it generates a warning stating that "Article 3 of this order specification violates the latest safety standards."

[1688] Server: Sends the generated feedback to the user.

[1689] Device: Notifies the user of feedback.

[1690] 4. Project Management

[1691] User: Review the feedback and revise Article 3 of the order specification.

[1692] User: Re-upload the revised order specification to the system.

[1693] Terminal: Sends the corrected data to the server.

[1694] Server: Requests the AI ​​analysis engine to re-analyze the corrected data.

[1695] Server: Generates feedback again based on the re-analysis results.

[1696] Server: Sends further feedback to the user.

[1697] 5. Final confirmation and execution

[1698] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[1699] User: Upload the final construction plan to the system.

[1700] Terminal: Sends the final construction plan to the server.

[1701] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[1702] In this way, this invention supports the efficient progress of construction work. This system reduces rework, prevents personal injury and service disruptions, and improves the overall efficiency of operations.

[1703] The following describes the processing flow.

[1704] Step 1:

[1705] User: Access the system's website and view the registration form.

[1706] Step 2:

[1707] User: Enter company name, contact person's name, email address, and password, then submit.

[1708] Step 3:

[1709] Terminal: Sends the entered information to the server.

[1710] Step 4:

[1711] Server: Stores the received user information in the database.

[1712] Step 5:

[1713] Server: Sends a registration confirmation email to the user.

[1714] Step 6:

[1715] User: Opens a page to upload data files such as order specifications to the system.

[1716] Step 7:

[1717] User: Select the order specification document "Order Specification.pdf" and upload it.

[1718] Step 8:

[1719] Terminal: Sends uploaded data to the server.

[1720] Step 9:

[1721] Server: Temporarily stores data.

[1722] Step 10:

[1723] Server: Sends the stored data to the AI ​​analysis engine.

[1724] Step 11:

[1725] AI analysis engine: Performs analysis based on data and extracts important information based on laws, regulations, and company rules.

[1726] Step 12:

[1727] Server: Receives analysis results from the AI ​​analysis engine and generates feedback.

[1728] Step 13:

[1729] Server: Sends the generated feedback to the terminal.

[1730] Step 14:

[1731] Device: Notifies the user of feedback.

[1732] Step 15:

[1733] User: Review the feedback and make any necessary corrections.

[1734] Step 16:

[1735] User: Upload the revised order specification to the system again.

[1736] Step 17:

[1737] Terminal: Sends the corrected data to the server.

[1738] Step 18:

[1739] Server: Resends the corrected data to the AI ​​analysis engine.

[1740] Step 19:

[1741] AI analysis engine: Re-analyzes the corrected data and generates new feedback.

[1742] Step 20:

[1743] Server: Generates re-feedback based on the re-analysis results and sends it to the terminal.

[1744] Step 21:

[1745] Device: Notifies the user of further feedback.

[1746] Step 22:

[1747] User: Review all feedback and create the final construction plan.

[1748] Step 23:

[1749] User: Upload the final construction plan to the system.

[1750] Step 24:

[1751] Terminal: Sends the final construction plan to the server.

[1752] Step 25:

[1753] Server: Saves the final construction plan to the database.

[1754] Step 26:

[1755] Server: Manages project execution and progress, and notifies users as needed.

[1756] (Example 1)

[1757] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1758] In the construction industry, it is necessary to verify that many tasks comply with relevant laws, regulations, and unique work rules. This can lead to complexity, rework, and decreased efficiency. Furthermore, even during project execution, insufficient compliance with laws and regulations and inadequate progress management can lead to deviations from the plan and accidents. Therefore, there is a need for means to resolve these issues and achieve efficient and reliable work execution.

[1759] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1760] In this invention, the server includes a user registration means for creating an account by having the user input information, an information transmission means for transmitting uploaded data to an AI analysis engine, an evaluation generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, an evaluation notification means for notifying the user of the feedback, a plan management means for storing and managing the generated final plan, a legal compliance evaluation means for evaluating whether the plan complies with laws and regulations, and a progress monitoring means for managing the execution and tracking the progress of the project. This enables efficient and reliable planning and management of construction projects in compliance with laws and regulations, eliminates the complexity of the work, and simplifies progress management.

[1761] 1. "User registration method" refers to a means by which a user creates an account by entering information.

[1762] 2. "Information transmission means" refers to the means for transmitting uploaded data to the AI ​​analysis engine.

[1763] 3. "Evaluation generation means" refers to a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[1764] 4. "Evaluation notification means" refers to a means of notifying the user of the generated feedback.

[1765] 5. "Plan management means" refers to means for saving and managing the final plan that has been generated.

[1766] 6. "Methods for evaluating compliance with laws and regulations" are means for evaluating whether something complies with laws and regulations.

[1767] 7. "Progress monitoring means" refers to the means used for managing the execution and tracking the progress of a project.

[1768] This invention relates to a system for improving the efficiency of operations in the construction industry. Specifically, it is a platform for efficiently carrying out construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules.

[1769] The main components of this system include a server, terminals, and an AI analysis engine. The server includes means for user registration, information transmission, evaluation generation, evaluation notification, plan management, legal compliance evaluation, and progress monitoring.

[1770] The server uses an SQL database to manage basic user information and uploaded data. The AI ​​analysis engine analyzes the data using machine learning libraries such as TensorFlow and PyTorch. The terminal provides an interface for users to upload data and check feedback.

[1771] The following is a concrete example of the system.

[1772] User Registration

[1773] User: Access the system, enter the company name, contact person's name, email address, and password on the account creation screen, and click the register button.

[1774] Server: Receives the entered information and saves it to the database. It also generates and sends a registration confirmation email to the user.

[1775] Terminal: The user will receive a registration confirmation email.

[1776] Upload data

[1777] User: Drag and drop data such as order specifications, design notes, estimated unit prices, construction precautions, and client comments onto the system's upload screen, or select them using the file selection dialog.

[1778] Terminal: Sends the selected files to the server.

[1779] Server: Receives the file and stores it temporarily.

[1780] Temporary data storage and AI analysis request

[1781] Server: Sends temporarily stored data to the AI ​​analysis engine and requests analysis.

[1782] AI analysis and feedback generation

[1783] Server: The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and proprietary work rules.

[1784] Server: Receives analysis results and generates feedback based on them. For example, it might generate a warning such as, "Article 3 of this order specification violates the latest safety standards."

[1785] Server: Notifies the user of the feedback.

[1786] Reviewing feedback and correcting data

[1787] User: Check the feedback received from the server.

[1788] User: Based on feedback, revise data such as order specifications.

[1789] Request to re-upload corrected data and re-analyze it.

[1790] User: Re-upload the revised order specification to the system.

[1791] Terminal: Resend the corrected data to the server.

[1792] Server: Resubmits the corrected data to the AI ​​analysis engine and requests re-analysis.

[1793] Server: Receives re-analysis results and generates feedback again.

[1794] Server: Notifies the user of further feedback.

[1795] Uploading the final construction plan and project management

[1796] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[1797] User: Upload the final construction plan to the system.

[1798] Terminal: Sends files to the server.

[1799] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[1800] As a concrete example, the following prompt statement is shown:

[1801] Example of a prompt

[1802] 1. User Registration

[1803] I would like to create an account in the system. Please enter your company name, contact person's name, email address, and password.

[1804] 2. "Data Input

[1805] I have uploaded the order specifications for a new project. Please analyze this file.

[1806] 3. AI analysis and feedback

[1807] The analysis results for the order specifications are in. Article 3 violates safety standards and requires correction.

[1808] 4. "Further feedback"

[1809] I have reviewed the feedback and revised the order specifications. Please analyze it again.

[1810] 5. Final confirmation and execution

[1811] The final construction plan is complete. Uploading it to the system. Please begin project management.

[1812] In this way, this system supports the efficient progress of construction work. It enables efficient and reliable planning and management of construction projects in compliance with laws and regulations.

[1813] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1814] Step 1:

[1815] User Registration

[1816] User: Access the system, enter the company name, contact person's name, email address, and password on the account creation screen, and click the register button.

[1817] Server: Receives the entered information and saves it to the database. Executes the following SQL query: INSERT INTO users (company_name, contact_name, email, password) VALUES ('Company Name', 'Contact Person Name', 'Email Address', 'Password'). Generates a registration confirmation email and sends it to the user.

[1818] Input: Company name, contact person's name, email address, and password entered by the user.

[1819] Output: User information stored in the database, confirmation email sent to the user.

[1820] Terminal: The user's screen displays the message, "A registration confirmation email has been sent. Please check your email."

[1821] Step 2:

[1822] Upload data

[1823] User: Drag and drop data such as order specifications, design notes, estimated unit prices, construction precautions, and client comments onto the system's upload screen, or select them using the file selection dialog.

[1824] Terminal: Sends the file selected from the file selection dialog to the server using the multipart / form-data protocol.

[1825] Input: The file to be uploaded (e.g., "Order Specifications.pdf").

[1826] Output: File data sent to the server.

[1827] Server: Saves received file data to a temporary storage directory. For example, use the function store_temp_file('OrderSpecifications.pdf').

[1828] Input: File data sent from the terminal.

[1829] Output: Files saved in the temporary directory.

[1830] Step 3:

[1831] Temporary data storage and AI analysis request

[1832] Server: Sends temporarily stored data to the AI ​​analysis engine. Specifically, it uses the function `send_to_ai_engine('temp / order_specification_document.pdf')` to request analysis.

[1833] Input: Temporarily saved file data (e.g., "temp / order_specification.pdf").

[1834] Output: Analysis request sent to the AI ​​analysis engine.

[1835] Step 4:

[1836] AI analysis and feedback generation

[1837] Server: The AI ​​analysis engine analyzes the data and receives evaluation results on whether it complies with laws, company regulations, and proprietary work rules.

[1838] Input: Data sent to the AI ​​analysis engine.

[1839] Output: Evaluation results (e.g., feedback stating "Article 3 violates the latest safety standards").

[1840] Server: Generates feedback based on the analysis results and notifies the user. For example, it might generate a warning message stating, "Article 3 of this order specification violates the latest safety standards."

[1841] Input: Evaluation results from the AI ​​analysis engine.

[1842] Output: Feedback notified to the user.

[1843] Step 5:

[1844] Reviewing feedback and correcting data

[1845] User: Review the feedback received from the system and revise data such as order specifications.

[1846] Input: Feedback received from the system.

[1847] Output: Data such as the revised order specifications. Specifically, Article 3 of "Order Specifications.pdf" was modified in an editor to comply with the latest safety standards.

[1848] Step 6:

[1849] Request to re-upload corrected data and re-analyze it.

[1850] User: Upload the revised order specifications to the system again.

[1851] Input: Modified file (e.g., "Order Specification_v2.pdf").

[1852] Output: File data sent to the server.

[1853] Terminal: Sends modified data to the server using the multipart / form-data protocol.

[1854] Input: The modified file.

[1855] Output: File data sent to the server.

[1856] Server: Receives the modified data and saves it again to the temporary storage directory. For example, store_temp_file('Order Specification_v2.pdf').

[1857] Input: Modified file data sent from the terminal.

[1858] Output: The file has been resaved to the temporary directory.

[1859] Server: Resends the corrected data to the AI ​​analysis engine and requests re-analysis. Specifically, it calls send_to_ai_engine('temp / order_specification_v2.pdf').

[1860] Input: Re-saved modified file data.

[1861] Output: Analysis request resent to the AI ​​analysis engine.

[1862] Server: Receives the re-analysis results, generates feedback again, and notifies the user. For example, it might generate feedback stating, "All items comply with the latest safety standards."

[1863] Input: Re-evaluation results from the AI ​​analysis engine.

[1864] Output: Further feedback notified to the user.

[1865] Step 7:

[1866] Uploading the final construction plan and project management

[1867] User: Create the final construction plan based on the final feedback.

[1868] Input: Final feedback.

[1869] Output: Final Construction Plan (Example: "Final Construction Plan.pdf").

[1870] User: Upload the final construction plan to the system.

[1871] Input: Final construction plan.

[1872] Output: Sending plan data to the server.

[1873] Terminal: Sends the final construction plan to the server using the multipart / form-data protocol.

[1874] Input: Final construction plan.

[1875] Output: Sending plan data to the server.

[1876] Server: Receives the final construction plan and saves it to the plan management directory. For example, store_final_plan('final_construction_plan.pdf').

[1877] Input: Plan data sent from the terminal.

[1878] Output: The final construction plan saved in the save directory.

[1879] Server: Records necessary information and monitors project progress in order to initiate project execution management and progress tracking.

[1880] Input: Final construction plan.

[1881] Output: Progress monitoring data for project management.

[1882] (Application Example 1)

[1883] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1884] In traditional construction work, a major challenge has been the time-consuming and laborious process of manually verifying compliance with legal regulations, company rules, and unique work procedures. Furthermore, similar problems are more likely to occur during factory work, making it difficult to adhere to safety standards. As a result, there are challenges such as decreased work efficiency and an increased risk of personal injury and service disruptions.

[1885] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1886] In this invention, the server includes a user registration means for creating an account by having the user input information, a data transmission means for sending uploaded data to an AI analysis engine, a feedback display means for displaying feedback on a smart device in real time, a feedback generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, and a plan management means for saving and managing the generated final construction plan. As a result, the user can receive accurate feedback in real time that complies with laws and regulations, company rules, and unique work rules, enabling them to carry out their work safely and efficiently.

[1887] "User registration method" refers to a means by which a user creates an account by entering information.

[1888] "Data transmission means" refers to the means for transmitting uploaded data to the AI ​​analysis engine.

[1889] A "feedback display means" is a means for displaying feedback on a smart device in real time.

[1890] A "feedback generation method" is a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[1891] A "feedback notification method" is a means of notifying the user of the generated feedback.

[1892] "Planning management means" refers to means for saving and managing the generated final construction plan.

[1893] "Method for sending corrected data" refers to a means for users to re-upload their corrected content to the system.

[1894] A "re-feedback generation means" is a means for generating feedback again based on the results of re-analysis and notifying the user.

[1895] A "data storage method" is a means of temporarily storing data uploaded by a user.

[1896] A "smart device" is a device that has the capability to perform computer processing and provides information to the user. Examples include smart glasses and head-mounted displays.

[1897] This invention relates to a method for improving the efficiency and safety of construction work and factory operations using a certain system. Specific embodiments are described below.

[1898] First, users create an account by accessing the system and entering information. This includes basic information such as company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[1899] Next, the user uploads data related to construction work or factory operations (e.g., order specifications or work procedures) to the system. The terminal sends the uploaded data to the server, which temporarily stores the data before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[1900] The analysis results are generated as feedback and notified to the user from the server. Specifically, the feedback is displayed in real time on a smart device (such as smart glasses) using a feedback display means. The user can also review this feedback, make any necessary corrections, and then re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The results of the re-analysis are similarly notified to the user as feedback.

[1901] Finally, after the user reviews all feedback and completes the revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to assist with project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[1902] The hardware will include smart glasses (e.g., Google Glass, Microsoft HoloLens) and web servers that provide appropriate API endpoints. The software will utilize AI analysis engines such as NLP engines and rule-based systems.

[1903] For example, when factory workers assemble part A using smart glasses, they can immediately access a checklist based on the latest safety standards. An AI analysis engine audits all steps, and any violations detected are displayed instantly.

[1904] Examples of prompt statements are as follows:

[1905] When assembling part A in the factory, please review the following latest safety standards:

[1906] Component A is properly secured.

[1907] The correct tools are being used.

[1908] Workers must wear protective equipment.

[1909] If there are any violations, please display the feedback on your smart glasses.

[1910] In this way, users can receive accurate feedback in real time that complies with legal regulations, company rules, and unique work rules, enabling them to carry out their work safely and efficiently.

[1911] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1912] Step 1:

[1913] The user accesses the system and creates an account. This involves entering basic information such as company name, contact person's name, email address, and password. The entered information is sent to the server via the terminal. The server stores this information in a database and sends a registration confirmation email to the user. The input data includes the company name and contact person's name, while the output data is the registration confirmation email.

[1914] Step 2:

[1915] Users upload specifications and work procedures for new construction projects or tasks to the system. The terminal sends the uploaded data to the server. The server temporarily stores the data and then sends it to the AI ​​analysis engine. The input data consists of the uploaded specifications and procedures, and the output data is the data sent for AI analysis.

[1916] Step 3:

[1917] The server sends the uploaded data to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and proprietary work rules. The input data consists of specifications and procedures, and the output data is the analysis results for feedback.

[1918] Step 4:

[1919] The server receives analysis results from the AI ​​analysis engine and generates feedback. Feedback is generated using a feedback generation method. The input data is the AI ​​analysis results, and the output data is the feedback message.

[1920] Step 5:

[1921] The server notifies the user of the generated feedback using a feedback notification means. The feedback display means displays the feedback on the smart device in real time. The input data is the generated feedback, and the output data is the feedback message displayed on the smart device.

[1922] Step 6:

[1923] The user makes corrections based on feedback and uploads the corrected data back to the system. The terminal sends the corrected data to the server. The input data is the corrected specifications or procedures, and the output data is the data to be sent for re-analysis.

[1924] Step 7:

[1925] The server sends the corrected data back to the AI ​​analysis engine. The AI ​​analysis engine re-analyzes the corrected data and outputs the analysis results again. The input data is the corrected data, and the output data is the re-analysis result.

[1926] Step 8:

[1927] The server receives the re-analysis results, generates feedback again using the re-feedback generation mechanism, and notifies the user. The input data is the re-analysis results, and the output data is the re-feedback message.

[1928] Step 9:

[1929] After the user reviews all feedback and completes any necessary corrections, they create the final construction plan and upload it to the system. The terminal then sends the final construction plan to the server. The input data is the final construction plan, and the output data is the plan data stored on the server.

[1930] Step 10:

[1931] The server stores the final construction plan and uses planning management tools to manage project execution and track progress. It monitors whether the project is progressing according to plan and notifies the user as needed. The input data is the final construction plan, and the output data is progress notifications.

[1932] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1933] This invention relates to a platform for improving the efficiency of operations in the construction industry by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules, and providing feedback that takes user sentiment into consideration.

[1934] System Overview

[1935] First, the user accesses the system and creates an account. To do this, they enter basic information such as company name, contact person's name, email address, and password. Once the user enters and submits this information, the server saves this information in its database and sends a registration confirmation email to the user.

[1936] Users can upload data files such as order specifications, design notes, estimated unit prices, construction precautions, and client comments to the system. The uploaded data is sent from the terminal to the server, which temporarily stores it before sending it to the AI ​​analysis engine. The AI ​​analysis engine analyzes the data and evaluates whether it complies with laws, company regulations, and unique work rules.

[1937] Furthermore, an emotion engine is used to recognize the user's emotions and generate feedback that takes these emotions into account. The analysis results are adjusted by the emotion engine based on the user's emotional state, providing feedback tailored to individual needs and mental state. The server sends the generated feedback to the user's terminal for notification.

[1938] Users can make corrections based on feedback and re-upload the data to the system. This corrected data is sent back to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are also adjusted through the emotion engine and notified to the user as feedback.

[1939] Finally, after the user reviews all feedback and completes any necessary revisions, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to support project execution management and progress tracking. Based on this information, the server monitors whether the project is progressing as planned and notifies the user as needed.

[1940] Specific example

[1941] The following is a specific scenario.

[1942] 1. User Registration

[1943] User: A representative from a construction company visits the system and creates an account. They enter the company name, contact person's name, email address, and password, and then press the submit button.

[1944] Server: Receives this information and stores it in the database. Sends a registration confirmation email to the user.

[1945] 2. Data Input

[1946] User: Upload the order specification document ("Order Specification.pdf") for a new construction project to the system.

[1947] Terminal: Sends uploaded data to the server.

[1948] Server: Temporarily stores data and sends it to the AI ​​analysis engine.

[1949] 3. AI analysis and emotional feedback

[1950] Server: The AI ​​analysis engine analyzes the order specifications and determines, for example, that "the safety standards in Article 3 have not been met."

[1951] Emotion Engine: Evaluates the user's current emotional state and adjusts feedback based on the analysis results.

[1952] Server: Based on the analysis results, it generates a warning stating that "Article 3 of this order specification violates the latest safety standards" and sends it to the user terminal as feedback via the emotion engine.

[1953] Device: Notifies the user of feedback.

[1954] 4. Project Management

[1955] User: Review the feedback and revise Article 3 of the order specification.

[1956] User: Re-upload the revised order specification to the system.

[1957] Terminal: Sends the corrected data to the server.

[1958] Server: Requests the AI ​​analysis engine to re-analyze the corrected data.

[1959] Emotion Engine: Re-analyzes the corrected data and considers the user's emotional state when generating new feedback.

[1960] Server: Generates feedback again based on the re-analysis results.

[1961] Server: Sends further feedback to the user.

[1962] 5. Final confirmation and execution

[1963] User: Confirm that all suggestions and warnings have been resolved, and then create the final construction plan.

[1964] User: Upload the final construction plan to the system.

[1965] Terminal: Sends the final construction plan to the server.

[1966] Server: Saves the final construction plan and initiates project execution management and progress tracking.

[1967] This invention is a system that improves the efficiency and safety of construction work by providing more appropriate feedback by taking user emotions into consideration. Because the emotion engine provides feedback tailored to the user's state, more effective project management becomes possible.

[1968] The following describes the processing flow.

[1969] Step 1:

[1970] User: Access the system's website and view the registration form.

[1971] Step 2:

[1972] User: Enter company name, contact person's name, email address, and password, then submit.

[1973] Step 3:

[1974] Terminal: Sends the entered information to the server.

[1975] Step 4:

[1976] Server: Stores the received user information in the database.

[1977] Step 5:

[1978] Server: Sends a registration confirmation email to the user.

[1979] Step 6:

[1980] User: Opens a page to upload data files such as order specifications to the system.

[1981] Step 7:

[1982] User: Select the order specification document "Order Specification.pdf" and upload it.

[1983] Step 8:

[1984] Terminal: Sends uploaded data to the server.

[1985] Step 9:

[1986] Server: Temporarily stores data.

[1987] Step 10:

[1988] Server: Sends the stored data to the AI ​​analysis engine.

[1989] Step 11:

[1990] AI analysis engine: Performs analysis based on data and extracts important information based on laws, regulations, and company rules.

[1991] Step 12:

[1992] Emotion Engine: Analyzes the user's emotional state. For example, it considers the user's facial expressions while uploading and their typing speed.

[1993] Step 13:

[1994] Server: Integrates analysis results from the AI ​​analysis engine and the emotion engine to generate appropriate feedback.

[1995] Step 14:

[1996] Server: Sends the generated feedback to the terminal.

[1997] Step 15:

[1998] Device: Notifies the user of feedback.

[1999] Step 16:

[2000] User: Review the feedback and make any necessary corrections.

[2001] Step 17:

[2002] User: Upload the revised order specification to the system again.

[2003] Step 18:

[2004] Terminal: Sends the corrected data to the server.

[2005] Step 19:

[2006] Server: Resends the corrected data to the AI ​​analysis engine.

[2007] Step 20:

[2008] AI analysis engine: Re-analyzes the corrected data and generates new feedback.

[2009] Step 21:

[2010] Emotional Engine: Re-analyzes the user's emotional state and adjusts the feedback accordingly.

[2011] Step 22:

[2012] Server: Generates new feedback based on the re-analysis results and the re-analysis results of the emotion engine, and sends it to the terminal.

[2013] Step 23:

[2014] Device: Notifies the user of further feedback.

[2015] Step 24:

[2016] User: Review all feedback and create the final construction plan.

[2017] Step 25:

[2018] User: Upload the final construction plan to the system.

[2019] Step 26:

[2020] Terminal: Sends the final construction plan to the server.

[2021] Step 27:

[2022] Server: Saves the final construction plan to the database.

[2023] Step 28:

[2024] Server: Manages project execution and progress, and notifies users as needed.

[2025] (Example 2)

[2026] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2027] In traditional construction work, it has been difficult to efficiently analyze information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments, and to provide feedback that complies with laws and company regulations. Furthermore, because feedback is provided only mechanically, without considering the user's feelings, there have been problems such as users feeling stressed or finding it difficult to accept the feedback. To solve these problems, there is a need for a system that generates more appropriate feedback that takes user feelings into account.

[2028] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user registration means for creating an account by inputting information by the user, a data transmission means for transmitting uploaded data to an AI analysis engine, a feedback generation means for generating feedback that takes into account the user's emotional state based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, and a plan management means for saving and managing the generated final construction plan. This makes it possible to improve efficiency and reliability in construction work by providing feedback that takes into account the user's emotions.

[2029] "User registration method" refers to the means by which a user enters information and creates an account.

[2030] "Data transmission means" refers to the means by which data uploaded by the user is sent to the AI ​​analysis engine.

[2031] A "feedback generation method" is a means of generating feedback that takes into account the user's emotional state based on the results analyzed by the AI ​​analysis engine.

[2032] A "feedback notification method" is a means of notifying the user of the generated feedback.

[2033] "Plan management means" refers to the means of saving and managing the final construction plan that has been generated.

[2034] "Method for sending corrected data" refers to a means for users to re-upload their corrected content to the system.

[2035] A "re-feedback generation method" is a means of generating feedback again, taking into account the user's emotional state based on the results of the re-analysis, and notifying the user.

[2036] A "data storage method" is a means of temporarily storing data uploaded by a user.

[2037] This invention aims to improve efficiency and reliability in construction work by inputting information such as order specifications, design notes, estimated unit prices, construction precautions, and client comments into an AI analysis engine, while complying with laws, company regulations, and unique work rules, and providing feedback that takes user sentiment into account.

[2038] System Overview

[2039] First, the user accesses the system and creates an account by entering basic information such as company name, contact person's name, email address, and password. The entered information is sent to the server and stored in the database. At the same time, a registration confirmation email is sent to the user.

[2040] Next, the user uploads data files such as order specifications and design notes to the system. The uploaded data is sent from the terminal to the server, temporarily stored, and then sent to the AI ​​analysis engine.

[2041] The AI ​​analysis engine analyzes uploaded data and evaluates whether it complies with laws, company regulations, and proprietary work rules. Furthermore, it uses an emotion engine to recognize the user's emotional state and reflect it in the feedback. The emotion engine analyzes the user's past operation logs and system usage history to assess the user's mental state.

[2042] The feedback is generated based on analysis results refined by the emotion engine and sent to the user terminal via the server. For example, feedback such as, "Article 3 of this order specification violates the latest safety standards, but we will provide detailed guidance on how to correct it," might be generated.

[2043] The user makes necessary corrections based on the feedback provided and re-uploads the data to the system. This corrected data is also sent to the server and re-analyzed by the AI ​​analysis engine. The re-analysis results are then adjusted again through the emotion engine and notified to the user as feedback.

[2044] Finally, after the user reviews all feedback and completes any necessary corrections, they create a final construction plan and upload it to the system. The final construction plan is stored on the server to assist with project execution management and progress tracking. The server monitors whether the project is progressing according to plan and notifies the user as needed.

[2045] Hardware and software to be used

[2046] The following hardware and software are primarily used:

[2047] Server: Stores and processes data. Examples: Amazon Web Services (AWS), Google Cloud Platform (GCP).

[2048] Device: Used for data input and display of results. Examples: PC, tablet.

[2049] AI analysis engine: Analyzes data based on laws, company regulations, and unique work rules. Example: GPT-4.

[2050] Emotion engine: Evaluates the user's emotional state. Example: IBM Watson.

[2051] Specific example

[2052] User Registration

[2053] Example prompt: "I would like to create a new account. Please enter your company name, contact person's name, email address, and password."

[2054] Data Input

[2055] Specific example: "Order Specification.pdf"

[2056] Example prompt: "I have uploaded the order specification. Please parse it."

[2057] AI analysis and emotional feedback

[2058] Example prompt: "Please analyze the uploaded order specification and provide feedback."

[2059] project management

[2060] Specific example: "Revised Order Specifications.pdf"

[2061] Example prompt message: "I will re-upload the revised order specification. Please re-parse it."

[2062] Final confirmation and execution

[2063] Specific example: "Final Construction Plan.pdf"

[2064] Example prompt: "Uploading the final construction plan. Please track the project progress."

[2065] This system contributes to increased efficiency and reliability in construction work by providing more effective and user-friendly feedback that takes user emotions into consideration. Its key feature is the combination of an AI analysis engine and an emotion engine, which provides highly accurate feedback while taking the user's mental state into account.

[2066] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2067] Step 1:

[2068] The user accesses the system and is redirected to the account creation screen. The user enters the company name, contact person's name, email address, and password, then clicks the submit button.

[2069] Input: Company name, contact person's name, email address, password

[2070] Output: Registration confirmation request

[2071] Step 2:

[2072] The server receives the entered information and saves it to the database. The server then sends a registration confirmation email to the user.

[2073] Input: Registration confirmation request

[2074] Data processing: Saving input information, generating confirmation emails.

[2075] Output: Registration confirmation email

[2076] Step 3:

[2077] The user uploads the order specification document for a new construction project, "Order Specification Document.pdf". The user presses the upload button.

[2078] Input: Order specification "Order specification.pdf"

[2079] Output: Upload Request

[2080] Step 4:

[2081] The device sends the uploaded data to the server.

[2082] Input: Upload request

[2083] Output: Uploaded data

[2084] Step 5:

[2085] The server temporarily stores the received data and passes the destination path to the AI ​​analysis engine.

[2086] Input: Uploaded data

[2087] Data processing: Data storage, path generation

[2088] Output: Data path

[2089] Step 6:

[2090] The AI ​​analysis engine analyzes the order specifications based on the file paths provided by the server. It then evaluates whether the specifications comply with legal standards and company regulations.

[2091] Input: Data path

[2092] Data processing: Analysis of order specifications, comparison with reference points.

[2093] Output: Analysis results (Example: Safety standards under Article 3 are not met)

[2094] Step 7:

[2095] The server receives the analysis results from the AI ​​analysis engine.

[2096] Input: Analysis results

[2097] Output: Unadjusted analysis results

[2098] Step 8:

[2099] The emotion engine evaluates the user's emotional state and generates feedback based on the analysis results.

[2100] Input: Unadjusted analysis results, user's historical data

[2101] Data processing: Evaluating user emotional states, generating feedback.

[2102] Output: Adjustment feedback (e.g., Article 3 violates safety standards, but provides detailed guidance on how to correct it)

[2103] Step 9:

[2104] The server compiles feedback, refined by the emotion engine, and sends it to the user's terminal.

[2105] Input: Adjustment Feedback

[2106] Output: Feedback notification

[2107] Step 10:

[2108] Review the feedback provided by users and make any necessary corrections.

[2109] Input: Feedback notification

[2110] Output: Correction details

[2111] Step 11:

[2112] The user uploads the revised order specification file to the system again.

[2113] Input: Revised purchase order specification (Example: Revised purchase order specification.pdf)

[2114] Output: Re-upload request

[2115] Step 12:

[2116] The device is corrected and the uploaded files are sent back to the server.

[2117] Input: Re-upload request

[2118] Output: Re-uploaded data

[2119] Step 13:

[2120] The server sends the data back to the AI ​​analysis engine and requests a re-analysis.

[2121] Input: Re-uploaded data

[2122] Data processing: Data storage, re-analysis requests

[2123] Output: Reanalysis results

[2124] Step 14:

[2125] The emotion engine re-analyzes the results, taking into account the user's emotional state, and generates new feedback.

[2126] Input: Reanalysis results, user's historical data

[2127] Data processing: Sentiment evaluation, feedback generation

[2128] Output: Refeedback

[2129] Step 15:

[2130] The server compiles the re-analysis results and adjusted feedback, and then resends it to the user.

[2131] Input: Refeedback

[2132] Output: Re-feedback notification

[2133] Step 16:

[2134] The user confirms that all suggestions and warnings have been resolved, and then the final construction plan is created.

[2135] Input: Feedback notification

[2136] Output: Final construction plan

[2137] Step 17:

[2138] The user uploads the final construction plan to the system.

[2139] Input: Final Construction Plan (Example: Final Construction Plan.pdf)

[2140] Output: Final upload request

[2141] Step 18:

[2142] The terminal sends the final construction plan to the server.

[2143] Input: Final upload request

[2144] Output: Final Upload Data

[2145] Step 19:

[2146] The server saves the final construction plan to the database and begins project execution management and progress tracking.

[2147] Input: Last uploaded data

[2148] Data processing: Data storage, progress monitoring

[2149] Output: Progress notification

[2150] This clearly shows the overall system flow and the specific actions of each step, allowing users, terminals, and servers to understand the processes involved.

[2151] (Application Example 2)

[2152] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2153] In autonomous vehicles, safety and compliance with regulations are extremely important, but the driver's emotional state often influences these. Conventional systems have been unable to provide feedback that takes the driver's emotions into account, resulting in problems with ensuring driving safety and compliance with regulations. This invention aims to solve this problem by providing feedback that takes the driver's emotions into account, thereby improving the safety and compliance with regulations of autonomous vehicles.

[2154] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user registration means for creating an account by inputting information by the user, a data transmission means for transmitting uploaded data to an AI analysis engine, a feedback generation means for generating feedback based on the results of analysis by the AI ​​analysis engine, a feedback notification means for notifying the user of the feedback, a plan management means for saving and managing the generated final construction plan, an emotion recognition means for recognizing the driver's emotional state, and an emotion adjustment feedback generation means for adjusting the feedback based on the emotional state. This makes it possible to provide appropriate feedback that takes into account the driver's emotional state, thereby improving the safety of autonomous vehicles and compliance with legal regulations.

[2155] "User registration method" refers to a means by which a user creates an account by entering information.

[2156] "Data transmission means" refers to the means by which data uploaded by the user is sent to the AI ​​analysis engine.

[2157] A "feedback generation method" is a means for generating feedback based on the results analyzed by the AI ​​analysis engine.

[2158] A "feedback notification method" is a means of notifying the user of the generated feedback.

[2159] "Planning management means" refers to means for saving and managing the generated final construction plan.

[2160] "Means of emotional recognition" refers to means of recognizing the emotional state of the driver.

[2161] An "emotion adjustment feedback generation means" is a means for adjusting and generating feedback based on an emotional state.

[2162] This invention is a system for enhancing the safety and compliance with regulations of autonomous vehicles. Specifically, it improves the safety of operating autonomous vehicles by providing feedback that takes into account the driver's emotional state.

[2163] The system has the following functions:

[2164] User registration method

[2165] The server includes a means for users to create accounts by entering information. Users can access the system by entering basic information such as company name, contact person's name, email address, and password and submitting it to the server. The server stores the entered information in a database and sends a registration confirmation email to the user.

[2166] Data transmission means

[2167] When a user uploads data acquired from the vehicle's sensors and cameras to the system, the terminal sends this data to the server. The server temporarily stores the received data and then sends it to the AI ​​analysis engine.

[2168] Feedback generation means

[2169] The AI ​​analysis engine analyzes the received data and evaluates whether it complies with laws, regulations, and safety standards. It also detects whether the driver is engaging in specific behaviors (for example, exceeding the speed limit or entering a prohibited area).

[2170] emotion recognition means

[2171] The emotion recognition system uses an in-car camera to capture images of the driver's face and recognizes specific emotional states (e.g., anger, sadness, joy). Emotion recognition is performed using an emotion recognition library that evaluates the driver's facial microexpressions and overall facial movements.

[2172] Emotional regulation feedback generation method

[2173] The emotion-adjusted feedback generation method combines the analysis results of the AI ​​analysis engine with the driver's emotional state to generate adjusted feedback. For example, if the driver is angry, a warning such as "Please calm down and continue driving" can be added.

[2174] Feedback notification method

[2175] The generated feedback is sent from the server to the user's device. The device receives this notification and provides appropriate feedback to the driver.

[2176] Planning and management methods

[2177] The final construction plan and a history of important feedback are stored and managed on a server. This allows for continuous monitoring of project progress and safety assessments, and enables notifications to be sent to drivers and managers as needed.

[2178] Specific example

[2179] For example, if a vehicle is exceeding the speed limit, the AI ​​analysis engine will detect this and generate feedback warning it to "adjust your speed to the limit." Furthermore, if the emotion recognition system detects that the driver is angry, it will provide additional feedback such as "Please drive calmly."

[2180] Example of a prompt

[2181] "Evaluate compliance with legal regulations based on the detection results of road signs, vehicles, and pedestrians, and create feedback based on the driver's emotional state."

[2182] This will enable appropriate feedback that takes into account the driver's emotional state, thereby improving the safety and compliance with regulations of autonomous vehicles.

[2183] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2184] Step 1:

[2185] A user accesses the system and creates an account. Specifically, the user enters information such as company name, contact person's name, email address, and password, and sends this information to the server. The server stores the submitted information in a database and sends a registration confirmation email to the user. The input is user information, and the output is the storage in the database and the confirmation email.

[2186] Step 2:

[2187] The user uploads data acquired from the vehicle's sensors and cameras to the system. The terminal sends this data (e.g., camera footage and sensor information) to the server. The server temporarily stores the received data and then sends it to the AI ​​analysis engine. The input is sensor data, and the output is storage to the server and transmission to the AI ​​analysis engine.

[2188] Step 3:

[2189] The AI ​​analysis engine analyzes the received data. Specifically, it detects road signs, other vehicles, and pedestrians, and evaluates whether they comply with legal regulations and safety standards. The output of the analysis is a violation detection result, such as "exceeding the speed limit." The input is sensor data, and the output is the analysis result.

[2190] Step 4:

[2191] An emotion recognition system uses an in-car camera to recognize the driver's emotional state. An emotion recognition library analyzes the facial image to detect the driver's emotion (e.g., anger, sadness, joy). The input is facial image data, and the output is the emotional state.

[2192] Step 5:

[2193] The emotion-adjusted feedback generation mechanism combines the analysis results of the AI ​​analysis engine with the emotional state of the emotion recognition mechanism to generate feedback. Specifically, if the driver is angry, it generates additional feedback such as "Please calm down and continue driving." The input is the analysis results and emotional state, and the output is the adjusted feedback.

[2194] Step 6:

[2195] The server notifies the user terminal of the generated feedback. The terminal receives this notification and provides appropriate feedback to the driver. The input is the adjusted feedback, and the output is the notification to the user terminal.

[2196] Step 7:

[2197] The server stores and manages the final construction plan and feedback history. This allows for continuous monitoring of project progress and safety assessments, and enables notifications to drivers and managers as needed. Inputs are the final construction plan and feedback history, while outputs are the stored data and monitoring results.

[2198] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2199] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2200] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2201] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2202] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2203] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2204] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2205] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2206] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2207] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2208] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2209] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2210] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2211] 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.

[2212] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2213] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[2214] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[2215] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[2216] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[2217] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2218] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[2219] The following is further disclosed regarding the embodiments described above.

[2220] (Claim 1)

[2221] A user registration method in which users create an account by entering information,

[2222] A data transmission means for sending uploaded data to an AI analysis engine,

[2223] A feedback generation means that generates feedback based on the results of analysis by an AI analysis engine,

[2224] A feedback notification method that notifies the user of feedback,

[2225] A planning management system for saving and managing the generated final construction plan,

[2226] A system that includes this.

[2227] (Claim 2)

[2228] The system according to claim 1, further comprising: a means for transmitting corrected data for the user to re-upload the corrected content to the system; and a means for generating re-feedback based on the results of re-analysis and notifying the user of the re-feedback.

[2229] (Claim 3)

[2230] The system according to claim 1, further comprising a data storage means for temporarily storing data uploaded by a user.

[2231] "Example 1"

[2232] (Claim 1)

[2233] A user registration method in which users create an account by entering information,

[2234] An information transmission means for sending uploaded data to an AI analysis engine,

[2235] An evaluation generation means that generates feedback based on the results of analysis by an AI analysis engine,

[2236] A means of notifying users of feedback,

[2237] A plan management system for saving and managing the generated final plan,

[2238] Legal compliance assessment tools for evaluating whether something complies with laws and regulations,

[2239] A progress monitoring system for managing and tracking the execution of a project,

[2240] A system that includes this.

[2241] (Claim 2)

[2242] The system according to claim 1, further comprising: a means for transmitting correction information for the user to re-upload the corrections to the system; and a means for generating re-evaluation feedback based on the results of re-analysis and notifying the user.

[2243] (Claim 3)

[2244] The system according to claim 1, further comprising a data storage means for temporarily storing data uploaded by a user.

[2245] "Application Example 1"

[2246] (Claim 1)

[2247] A user registration method in which users create an account by entering information,

[2248] A data transmission means for sending uploaded data to an AI analysis engine,

[2249] A feedback display means that displays feedback in real time on a smart device,

[2250] A feedback generation means that generates feedback based on the results of analysis by an AI analysis engine,

[2251] A feedback notification method that notifies the user of feedback,

[2252] A planning management system for saving and managing the generated final construction plan,

[2253] A system that includes this.

[2254] (Claim 2)

[2255] The system according to claim 1, further comprising: a means for transmitting corrected data for the user to re-upload the corrected content to the system; and a means for generating re-feedback based on the results of re-analysis and notifying the user of the re-feedback.

[2256] (Claim 3)

[2257] The system according to claim 1, further comprising a data storage means for temporarily storing data uploaded by a user.

[2258] "Example 2 of combining an emotion engine"

[2259] (Claim 1)

[2260] A user registration method in which users create an account by entering information,

[2261] A data transmission means for sending uploaded data to an AI analysis engine,

[2262] A feedback generation means that generates feedback that takes into account the user's emotional state based on the results of analysis by an AI analysis engine,

[2263] A feedback notification method that notifies the user of feedback,

[2264] A planning management system for saving and managing the generated final construction plan,

[2265] A system that includes this.

[2266] (Claim 2)

[2267] A means for the user to re-upload the corrected data to the system,

[2268] The system according to claim 1, further comprising a re-feedback generation means that generates new feedback based on the results of re-analysis, taking into account the user's emotional state, and notifies the user.

[2269] (Claim 3)

[2270] The system according to claim 1, further comprising a data storage means for temporarily storing data uploaded by a user.

[2271] "Application example 2 of combining emotional engines"

[2272] (Claim 1)

[2273] A user registration method in which users create an account by entering information,

[2274] A data transmission means for sending uploaded data to an AI analysis engine,

[2275] A feedback generation means that generates feedback based on the results of analysis by an AI analysis engine,

[2276] A feedback notification method that notifies the user of feedback,

[2277] A planning management system for saving and managing the generated final construction plan,

[2278] An emotion recognition means for recognizing the driver's emotional state,

[2279] An emotion-adjusting feedback generation means that adjusts feedback based on emotional state,

[2280] A system that includes this.

[2281] (Claim 2)

[2282] The system according to claim 1, further comprising: a means for transmitting corrected data for the user to re-upload the corrected content to the system; and a means for generating re-feedback based on the results of re-analysis and notifying the user of the re-feedback.

[2283] (Claim 3)

[2284] The system according to claim 1, further comprising a data storage means for temporarily storing data uploaded by a user. [Explanation of Symbols]

[2285] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A user registration method in which users create an account by entering information, A data transmission means for sending uploaded data to an AI analysis engine, A feedback generation means that generates feedback based on the results of analysis by an AI analysis engine, A feedback notification method that notifies the user of feedback, A planning management system for saving and managing the generated final construction plan, A system that includes this.

2. The system according to claim 1, further comprising: a means for transmitting corrected data for the user to re-upload the corrected content to the system; and a means for generating re-feedback for generating feedback again based on the results of re-analysis and notifying the user.

3. The system according to claim 1, further comprising a data storage means for temporarily storing data uploaded by a user.

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