system

Abstract

Provide a system. [Solution] A means for a user to input new rules or modifications to existing rules; means for receiving the user-entered data and analyzing the text using a natural language processing engine; A means for searching for relevant laws and regulations based on the analysis results and verifying the conformity of the document; means for generating suggested modifications to the document based on the results of the conformance check; means for transmitting the generated revision suggestions to a user and accepting approval or further revisions from the user; means for editing and saving the final document based on said user's approval or further modifications; A system including:

Description

[Technical Field]

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

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

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

[0004] Corporate regulations are often managed by a small number of people without specialized knowledge, resulting in the risk of regulations not being updated or not being properly complied with. Furthermore, there are many regulations compared to the number of employees, and managing them is extremely time-consuming. This can lead to companies struggling to maintain compliance and potentially creating an unsuitable working environment for employees. This invention aims to solve these issues by efficiently managing the creation and revision of regulations, compliance inspections, proposal generation, and final document storage. [Means for solving the problem]

[0005] This invention provides a system in which a user inputs details for creating new rules or amending existing rules, a server receives the data, and analyzes the text using a natural language processing engine. Based on the analysis results, a database is searched for relevant laws and regulations, and it is confirmed whether the document complies with them. Based on the analysis results and the confirmation of compliance, a proposal for document amendments is generated and sent to the user for approval or additional amendments. By using a system in which the server edits the final document based on the user's approval or amendments and stores it in a database, it is possible to streamline management of rules and ensure compliance with laws and regulations.

[0006] A "user" is someone who uses the system to create new rules or modify existing rules.

[0007] A "regulation" is a document that lists the rules and procedures that employees must follow within a company.

[0008] "Data" refers to textual information entered into the system by a user.

[0009] A "natural language processing engine" is a computer program that analyzes input text data and understands its content.

[0010] "Text" refers to character string information entered by the user.

[0011] "Laws and regulations" refer to laws and regulations established by a country or region.

[0012] "Regulations" are rules that must be followed in a particular field or activity.

[0013] "Proposed corrections" are corrections that the system automatically generates to make a document compliant with laws and regulations.

[0014] "Transmission" is the act of moving data or information from one point to another.

[0015] "Accept" is an act that indicates the user's acceptance of the revision suggestions generated by the system.

[0016] "Additional correction" refers to the act of a user further correcting the correction suggestions made by the system.

[0017] "Final Document" refers to the final regulations document after user approval or additional amendments have been reflected.

[0018] "Saving" refers to the operation of retaining the final edited document in the database. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] ---

[0041] The present invention is a system for efficiently managing the creation and revision of regulations. This system analyzes regulation data entered by users and automatically generates revision suggestions to comply with relevant laws and regulations. The system can also edit and save the final regulation document.

[0042] Program processing

[0043] 1. Accepting user input

[0044] The user inputs the text of a new rule they want to create or an existing rule they want to modify from a terminal. For example, a user might input the text "Telecommuting, in principle, requires the approval of a supervisor" as the initial draft of a new "telecommuting rule."

[0045] 2. Server data reception and natural language processing

[0046] The terminal sends the user's input data to the server, which receives it. The server then uses a natural language processing engine to analyze the text. Specifically, it analyzes the sentence structure, extracts keywords, and understands the meaning. For example, it extracts keywords such as "telecommuting" and "supervisor's approval" and understands their meaning.

[0047] 3. Legal check

[0048] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches to see if Article 4 of the Industrial Safety and Health Act, which pertains to telecommuting, is a relevant law. This confirms whether the regulations document complies with that law.

[0049] 4. Correction proposal generation

[0050] Based on the results of the conformance check, the server generates a document revision proposal, such as "Telecommuting will be carried out with the approval of the supervisor, in principle. In addition, measures to ensure employee safety will be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0051] 5. Replying to the User

[0052] After the proposed revision is generated, the server sends it to the terminal and displays it to the user. The user reviews the proposed revision and, if necessary, approves it or makes additional revisions. For example, the user may type, "I approve the proposal."

[0053] 6. Edit and save

[0054] If the amendments are approved, the server edits the final document based on the user's approval or additional amendments. After the final policy document is completed, the server saves it in the database. For example, the completion is as follows: "The new 'Telework Policy' has been saved in the database."

[0055] Specific examples

[0056] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[0057] 1. Accepting user input

[0058] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[0059] 2. Server data reception and natural language processing

[0060] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[0061] 3. Legal check

[0062] Based on the analysis results, the server searches for "Article 4 of the Industrial Safety and Health Act" and checks it against related laws and regulations.

[0063] 4. Correction proposal generation

[0064] (Server) generates a revision proposal that reads, "In principle, teleworking will be carried out with the approval of a supervisor. In addition, measures will be taken to ensure the safety of employees in accordance with Article 4 of the Industrial Safety and Health Act."

[0065] 5. Replying to the User

[0066] The server sends the proposed revision to the terminal, which the user confirms. The user approves the proposal by typing "I approve the proposal."

[0067] 6. Edit and save

[0068] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[0069] The above is a specific embodiment of the present invention. This system allows efficient creation and revision of regulations, ensuring compliance with laws and regulations.

[0070] The processing flow will be explained below.

[0071] ---

[0072] Step 1:

[0073] The user inputs the text of the new rule they want to create or the text of the existing rule they want to modify from the terminal.

[0074] Step 2:

[0075] (Terminal) receives text data entered by the user.

[0076] Step 3:

[0077] (Terminal) sends the received text data to the server.

[0078] Step 4:

[0079] (Server) receives the text data sent from the terminal.

[0080] Step 5:

[0081] The server analyzes the received text using a natural language processing (NLP) engine, specifically analyzing sentence structure, extracting keywords, and understanding meaning.

[0082] Step 6:

[0083] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches for "laws related to telecommuting."

[0084] Step 7:

[0085] The server uses the legal information retrieved from the database to verify whether the text entered by the user complies with the legal information.

[0086] Step 8:

[0087] The server generates a correction proposal based on the results of the conformance check. For example, it generates a correction proposal such as, "Telecommuting must be performed with the approval of the supervisor, in principle. In addition, measures to ensure the safety of employees must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0088] Step 9:

[0089] The server sends the generated revision suggestions to the terminal.

[0090] Step 10:

[0091] (Terminal) receives the correction suggestions sent from the server and displays them to the user.

[0092] Step 11:

[0093] The user checks the displayed correction proposal and approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[0094] Step 12:

[0095] The (terminal) sends the user's approval or additional modification data to the server.

[0096] Step 13:

[0097] The (server) edits the final document based on the user's approval or additional modifications.

[0098] Step 14:

[0099] The (server) saves the final edited document in a database.

[0100] ---

[0101] This will streamline the process of creating and amending regulations and create a system that ensures compliance with laws and regulations.

[0102] Example 1

[0103] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0104] The creation and revision of existing regulations requires a lot of manual checking work, which means that verifying compliance with laws and regulations takes a very long time. Furthermore, creating proposed revisions after verifying compliance also requires a lot of work, which is inefficient. This can delay the entire process of creating and revising regulations and reduce the certainty of compliance with laws and regulations.

[0105] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0106] In this invention, the server includes: a means for a user to input details for creating new rules or amending existing rules; a means for receiving the data input by the user and analyzing the text using a natural language processing engine; a means for searching for relevant laws and regulations based on the analysis results and checking the conformance of the document; a means for generating proposed document amendments based on the conformance check results; a means for sending the generated proposed amendments to the user and accepting user approval or additional amendments; a means for editing and saving the final document based on the user approval or additional amendments; a means for the user to input via a terminal equipped with a rules creation form; a means for the server to identify grammatical elements using the natural language processing engine; a means for the server to extract keywords using the natural language processing engine; a means for the server to search a database for relevant laws and regulations; a means for the server to generate proposed amendments using a template engine; and a means for using a generative AI model to identify templates and amendments, thereby enabling automation of conformance checks and proposed amendments.

[0107] "User" refers to an individual or legal entity that uses the System to create new rules or amend existing rules.

[0108] "Terminal" refers to a device such as a computer, tablet, or smartphone that allows a user to enter input.

[0109] "Server" refers to a central control unit for receiving, analyzing, and processing data sent by users.

[0110] A "natural language processing engine" refers to a software tool or algorithm that analyzes text data entered by a user and understands its meaning.

[0111] "Structural analysis" refers to the process of identifying grammatical elements in input text data and analyzing the structure of sentences.

[0112] "Keyword extraction" refers to the process of extracting important words and phrases from input text data.

[0113] "Database" refers to a data management system for storing and retrieving information on relevant laws and regulations.

[0114] "Template engine" refers to a software tool for generating documents, such as revision suggestions, using templates.

[0115] "Generative AI model" refers to a machine learning model that uses artificial intelligence to generate natural language.

[0116] "Proposed amendments" refers to amendments generated by the server to bring the content of the regulations entered by the user into compliance with laws and regulations.

[0117] The present invention is a system for efficiently managing the creation and revision of regulations. This system analyzes regulation data entered by users and automatically generates revision suggestions to comply with relevant laws and regulations. The system also has the function of editing and saving the final regulation document.

[0118] Hardware and Software Configuration

[0119] 1. User input terminal

[0120] Hardware: Using devices such as computers, tablets, and smartphones.

[0121] Software: Use an internet browser or dedicated application software.

[0122] 2. Server

[0123] Hardware: Use a server with a powerful processor, sufficient memory, and plenty of storage.

[0124] software:

[0125] Use a natural language processing engine (e.g., Spacy or BERT).

[0126] Create a revision suggestion template using a template engine.

[0127] Uses a generative AI model (e.g., GPT-4 (registered trademark)).

[0128] Use a database that stores information on laws and regulations (e.g., LawDataDB).

[0129] Natural language processing and legal checks

[0130] 1. Data Reception and Analysis

[0131] (Terminal) sends the new regulations and amendments entered by the user to the server.

[0132] The server analyzes the received data, performs sentence structure analysis, keyword extraction, and semantic understanding using a natural language processing engine (Spacy or BERT).

[0133] 2. Legal check

[0134] Based on the analysis results, the server searches the database (LawDataDB) for relevant laws and regulations. Based on this search, it checks whether the regulations comply with the laws and regulations.

[0135] Generate correction suggestions and reply to the user

[0136] 1. Generate correction suggestions

[0137] The server generates a correction proposal based on the results of the compatibility check. It creates a template for the correction proposal using a template engine, and generates specific proposal sentences using a generative AI model.

[0138] 2. Reply to the user

[0139] The (server) sends the generated revision suggestions to the (terminal) so that the (user) can review them.

[0140] (User) reviews the proposed revisions and approves or makes additional revisions as necessary.

[0141] Edit and save the final document

[0142] 1. Edit and save

[0143] The (server) edits the final document based on the user's approval or additional modifications.

[0144] The final edited document is stored in a database (e.g., RegulationDB).

[0145] Specific examples

[0146] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[0147] 1. Accepting user input

[0148] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[0149] 2. Server data reception and natural language processing

[0150] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[0151] 3. Legal check

[0152] Based on the analysis results, the server searches for "Article 4 of the Industrial Safety and Health Act" and checks it against related laws and regulations.

[0153] 4. Correction proposal generation

[0154] (Server) generates a revision proposal that reads, "In principle, teleworking will be carried out with the approval of a supervisor. In addition, measures will be taken to ensure the safety of employees in accordance with Article 4 of the Industrial Safety and Health Act."

[0155] 5. Replying to the User

[0156] The server sends the proposed revision to the terminal, which the user confirms. The user approves the proposal by typing "I approve the proposal."

[0157] 6. Edit and save

[0158] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[0159] This system will enable efficient creation and revision of regulations and ensure compliance with the law.

[0160] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0161] Step 1: Accepting user input

[0162] The user creates new rules or enters the details of amendments to existing rules into the terminal. For example, the user might enter, "I would like to create a new 'telecommuting rules'. The initial draft is as follows: 'Telecommuting must, in principle, be approved by a supervisor.'"

[0163] Input: User-created policy text

[0164] Output: The input text data

[0165] Step 2: Server receives data and processes natural language

[0166] The terminal sends the input text data to the server. The server receives this data and analyzes the text using a natural language processing engine. The server analyzes the sentence structure, extracts keywords, and understands the meaning.

[0167] Input: Text data sent by the user

[0168] Output: Parsed grammatical structure, extracted keywords, semantic understanding results

[0169] Specific behavior:

[0170] The server receives the HTTP request and retrieves the content as text data.

[0171] A natural language processing engine (e.g., Spacy or BERT) is used to perform grammatical analysis, keyword extraction, and semantic analysis.

[0172] Step 3: Legal check

[0173] Based on the analysis results, the server searches for relevant laws and regulations in a database (LawDataDB). The server creates a database query using keywords from the analysis results and retrieves the search results.

[0174] Input: Parsed text data, extracted keywords

[0175] Output: Relevant statutory and regulatory data

[0176] Specific behavior:

[0177] The server runs SQL queries against a database (LawDataDB) to retrieve relevant laws and regulations.

[0178] Check compliance with regulations based on search results.

[0179] Step 4: Generate correction suggestions

[0180] The server generates revision suggestions based on the results of the legal check. It uses a template engine to create a revision suggestion template, and uses a generative AI model to generate specific suggested sentences.

[0181] Input: Legal check results, analyzed text data

[0182] Output: Suggested corrections

[0183] Specific behavior:

[0184] The server uses a template engine to prepare a template for the proposed revision.

[0185] Use a generative AI model (e.g., GPT-4) to generate suggested revisions.

[0186] Step 5: Respond to the user

[0187] The server sends the generated revision proposal to the terminal for the user to review. The user reviews the revision proposal and approves it or makes additional revisions as necessary.

[0188] Input: Generated suggested correction text

[0189] Output: User approval or further modifications

[0190] Specific behavior:

[0191] The server sends the proposed revisions to the terminal as an HTTP response.

[0192] The user checks the proposal via the terminal and inputs approval or additional corrections.

[0193] Step 6: Edit and save

[0194] The server edits the final document based on the user's approval or additional modifications, and the edited final document is stored in the database (RegulationDB).

[0195] Input: User approval or additional modifications

[0196] Output: The final completed document

[0197] Specific behavior:

[0198] The server edits the final document to reflect the user's input.

[0199] The final edited document is saved in the database (RegulationDB).

[0200] (Application example 1)

[0201] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0202] The management and revision of regulations in factories is complicated, and there is a problem that they are not updated in a timely manner based on the latest laws. There is also a high risk of human error or failure to update regulations, which increases the risk of legal violations. There are concerns that this situation will have a negative impact on worker safety and factory operations.

[0203] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0204] In this invention, the server includes: means for a user to input details of creating new rules or amending existing rules; means for receiving the data input by the user and analyzing the text using a natural language processing engine; means for searching for relevant laws and regulations based on the analysis results and checking the document's compliance; means for generating document amendment suggestions based on the compliance check results; means for sending the generated amendment suggestions to the user and accepting user approval or additional amendments; means for editing and saving the final document based on the user approval or additional amendments; and means for automatically managing and amending factory rule data in accordance with laws and regulations to keep the rules up to date at all times. This improves the efficiency of factory rule management, ensures compliance with laws and regulations, and improves worker safety and the reliability of factory operations.

[0205] "User" means the person who creates or modifies a Policy.

[0206] "Input means" refers to an interface that allows a user to enter details of creating new rules or amending existing rules.

[0207] A "natural language processing engine" refers to software that analyzes text data entered by a user and performs sentence structure analysis, semantic understanding, and keyword extraction.

[0208] "Means for searching laws and regulations" refers to technology for searching relevant laws and regulations in a database and verifying the compliance of documents.

[0209] The "means for generating correction suggestions" refers to a technology for creating correction suggestions for a document based on the results of the conformance check.

[0210] "Means for sending to user" refers to an interface for notifying the user of generated revision suggestions and receiving feedback from the user.

[0211] "Means for editing and storing" refers to the technology for compiling the final document based on the user's approval or additional modifications and storing it in a database.

[0212] "Factory regulation data" refers to document data on regulations and guidelines necessary for factory operations.

[0213] "Means for automatically managing and correcting regulations and always maintaining the latest regulations" refers to technology that continuously updates and corrects regulation data in factories in response to changes in laws and regulations, and keeps it up to date.

[0214] This invention is a system that automatically manages and modifies factory regulation data in accordance with laws and regulations, and always keeps the regulations up to date.

[0215] The system includes a means for a user to input details for creating new regulations or amending existing regulations, a means for receiving the input data and analyzing the text using a natural language processing engine, a means for searching for relevant laws and regulations based on the analysis results and confirming the document's compliance, a means for generating suggested amendments to the document based on the results of the compliance confirmation, a means for sending the generated suggested amendments to the user and accepting the user's approval or additional amendments, and a means for editing and saving the final document based on the user's approval or additional amendments.

[0216] Hardware and software used

[0217] Hardware

[0218] Factory robots: Used for implementing and managing regulation data.

[0219] Server: Performs data analysis and stores results.

[0220] User terminal: An interface for entering regulations and reviewing and approving proposed amendments.

[0221] software

[0222] Python: A programming language used for the basic implementation of programs.

[0223] OpenAI® API: Used for text analysis using generative AI models.

[0224] SpaCy: A natural language processing engine for text analysis.

[0225] FuzzyWuzzy: Used for similarity searches with laws and regulations.

[0226] Data processing and calculation

[0227] The server receives new regulations or amendments from the user's device. The received data is first subjected to text analysis using a natural language processing engine (SpaCy). Text analysis involves analyzing the structure of the sentence, understanding its meaning, and extracting keywords, thereby obtaining the necessary information. Next, related laws and regulations are searched for based on the analysis results. This search uses a database of laws and regulations and a similarity search algorithm (FuzzyWuzzy).

[0228] The server then checks compliance with laws and regulations and automatically generates proposed revisions if necessary. The proposed revisions are sent to the user's device for review and approval. If the user approves or makes revisions, the final regulations document is edited based on the proposal and saved in the database.

[0229] Specific example explanation

[0230] As a concrete example, if a user enters, "I would like to create a new 'Safety Regulations'. Here is the initial draft: 'Helmets shall be worn while working.'", the system will automatically search the relevant legal database (e.g., the Industrial Safety and Health Act) and generate a proposed amendment: "In accordance with Article 4 of the Industrial Safety and Health Act, wearing helmets is mandatory to ensure safety while working." The user can then review the proposal and approve or make additional amendments. The final regulations document is saved in the database after approval.

[0231] Prompt Sentence Examples

[0232] The following are examples of prompts that users may enter into the system:

[0233] We want to create a new "safety rule." Here's an initial draft: 'Helmets must be worn while working.'

[0234] In this way, the present invention streamlines the management and revision of regulations within factories, enabling regulations to be maintained in strict compliance with relevant laws and regulations, which is expected to ensure compliance with laws and regulations and significantly improve worker safety and the reliability of factory operations.

[0235] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0236] Step 1:

[0237] A user uses a terminal to input the details of a new rule or an existing rule to be modified. For example, the user might input, "I would like to create a new 'Safety Rule'. Here is the initial draft: 'Helmets must be worn while working.'" This input data becomes a prompt for the system.

[0238] Step 2:

[0239] The terminal transmits the input data to the server, specifically, the text data input by the user.

[0240] Step 3:

[0241] The server analyzes the received text data using a natural language processing engine (SpaCy). It performs sentence structure analysis, semantic understanding, and keyword extraction to identify the meaning of keywords and sentences. For example, the keywords "helmet" and "working" are extracted.

[0242] Step 4:

[0243] The server then refers to the database of laws and regulations based on the analysis results and searches for relevant laws and regulations. Specifically, it uses FuzzyWuzzy to search for relevant laws and regulations in the database based on the extracted keywords, and identifies "Article 4 of the Industrial Safety and Health Act" as the result.

[0244] Step 5:

[0245] The server checks the document's relevance based on the search results. Specifically, it determines whether the current regulations comply with the applicable laws and regulations. For example, it checks whether "wearing a helmet" complies with Article 4 of the Industrial Safety and Health Act.

[0246] Step 6:

[0247] As a result of the conformance check, if necessary, a correction suggestion is generated. For example, a correction suggestion such as "In accordance with Article 4 of the Industrial Safety and Health Act, wearing a helmet is required to ensure safety during work" is automatically generated.

[0248] Step 7:

[0249] The server sends the generated revision proposal to the terminal and notifies the user, who then confirms the revision proposal through the terminal.

[0250] Step 8:

[0251] The user checks the proposed correction and approves it or makes additional corrections, for example, by typing "I approve the proposal."

[0252] Step 9:

[0253] The server edits the final document based on the user's approval or additional modifications, specifically by incorporating the approved modifications into the original document.

[0254] Step 10:

[0255] The server saves the final edited document in the database. As a result, the latest regulation data is accumulated in the database. For example, a message is displayed saying, "The new 'Safety Regulations' have been saved in the database."

[0256] The above are the specific processing steps for carrying out the present invention. This system allows for efficient management and revision of factory regulations, ensuring compliance with laws and regulations.

[0257] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0258] ---

[0259] The present invention is a system for efficiently managing the creation and revision of regulations, and furthermore, it enables more intuitive and effective regulation management by recognizing and reflecting user emotions. This system analyzes regulation data entered by the user, automatically generates revision suggestions to comply with relevant laws and regulations, and can edit and save the final regulation document. Another feature is that it collects and analyzes user emotions as they are entered and adjusts the revision suggestions based on them.

[0260] Program processing

[0261] 1. Accepting user input

[0262] The user inputs the text of a new rule they want to create or an existing rule they want to modify from a terminal. For example, a user might input the text "Telecommuting, in principle, requires the approval of a supervisor" as the initial draft of a new "telecommuting rule."

[0263] 2. Collecting Emotional Data

[0264] The device collects emotional data as users type, including keyboard typing speed, facial expression recognition, and tone of voice.

[0265] 3. Server data reception and natural language processing

[0266] (Terminal) transmits input text data and emotion data from the user to the server.

[0267] The server analyzes the received text data using a natural language processing (NLP) engine to analyze sentence structure, extract keywords, and understand meaning.

[0268] 4. Analysis by Emotion Engine

[0269] The server analyzes the emotion data with an emotion engine to identify the user's current emotional state, for example, detecting if the user is feeling stressed.

[0270] 5. Legal check and correction suggestion generation

[0271] Based on the analysis results, the server searches the database for relevant laws and regulations and checks whether the text entered by the user complies with the laws and regulations.

[0272] The server generates a correction suggestion based on the results of the compatibility check, but also reflects the results of the emotion engine and adjusts it to make it more acceptable to the user. For example, if the user is feeling stressed, the suggestion will be made more concise and easy to understand.

[0273] 6. Replying to the User

[0274] After the revision suggestions are generated, the (server) sends them to the (terminal) and displays them to the (user).

[0275] The device also reflects the results of the emotion engine and presents suggestions in a format that is easy for the user to understand. For example, suggestions may be presented in stages to reduce stress.

[0276] 7. User Authorization or Modification

[0277] The user checks the displayed correction proposal and accepts it or makes additional corrections as necessary. For example, the user may type "I accept the proposal."

[0278] 8. Edit and save

[0279] If the modifications are approved, the server edits the final document based on the user's approval or additional modifications.

[0280] The (server) saves the final edited document in a database.

[0281] Specific examples

[0282] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[0283] 1. Accepting user input

[0284] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[0285] 2. Collecting Emotional Data

[0286] The device monitors the user's typing speed and facial expressions to collect emotional data. For example, if the user is typing quickly, they may be feeling stressed.

[0287] 3. Server data reception and natural language processing

[0288] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[0289] 4. Analysis by Emotion Engine

[0290] (Server) analyzes the emotion data and determines that the user is feeling stressed.

[0291] 5. Legal check and correction suggestion generation

[0292] (Server) searches for "Article 4 of the Industrial Safety and Health Act" based on the analysis results and checks it against related laws and regulations.

[0293] The results of the emotion engine are reflected in the generation of concise and easy-to-understand revision suggestions: "Teleworking must, in principle, be carried out with the approval of the supervisor. In addition, measures to ensure employee safety must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0294] 6. Replying to the User

[0295] The server sends the proposed corrections to the device, which the user confirms. The suggestions may be displayed in stages to make them easier for the user to understand.

[0296] 7. User Authorization or Modification

[0297] (User) approves by typing "I approve the proposal."

[0298] 8. Edit and save

[0299] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[0300] The above is a specific embodiment of the present invention, which allows efficient policy creation and modification, ensures regulatory compliance, and provides a more intuitive and user-friendly process that takes into account the user's emotional state.

[0301] The processing flow will be explained below.

[0302] ---

[0303] Step 1:

[0304] The user inputs the text of the new rule they want to create or the existing rule they want to modify from the terminal. For example, they can input "Telecommuting must be performed with the approval of the supervisor as a general rule."

[0305] Step 2:

[0306] While the user types, the device collects emotional data such as keyboard typing speed, facial expression recognition, and tone of voice.

[0307] Step 3:

[0308] (Terminal) transmits the collected text data and emotion data to the server.

[0309] Step 4:

[0310] (Server) receives text data and emotion data sent from the terminal.

[0311] Step 5:

[0312] The server uses a natural language processing (NLP) engine to analyze the received text data, specifically analyzing the sentence structure, extracting keywords, and understanding the meaning.

[0313] Step 6:

[0314] The server uses an emotion engine to analyze the received emotion data and identify the user's emotional state, such as "feeling stressed."

[0315] Step 7:

[0316] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches for "laws regarding telecommuting."

[0317] Step 8:

[0318] The server uses the legal information retrieved from the database to verify whether the text entered by the user complies with the legal information.

[0319] Step 9:

[0320] The server generates a correction proposal based on the results of the conformance check. For example, it generates a correction proposal such as, "Telecommuting must be performed with the approval of the supervisor, in principle. In addition, measures to ensure the safety of employees must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0321] Step 10:

[0322] The server reflects the results of the emotion engine and adjusts the suggested corrections in an easy-to-understand manner that takes into account the user's emotional state. For example, if the user is feeling stressed, the suggested corrections will be concise and easy to understand.

[0323] Step 11:

[0324] The (server) sends the generated revision suggestions to the terminal and displays them to the (user).

[0325] Step 12:

[0326] The user checks the displayed correction proposal and accepts it or makes additional corrections as necessary. For example, the user enters "I accept the proposal."

[0327] Step 13:

[0328] The (terminal) sends the user's approval or additional modification data to the server.

[0329] Step 14:

[0330] The (server) edits the final document based on the user's approval or additional modifications.

[0331] Step 15:

[0332] The server saves the final edited document to the database. For example, the process is completed as follows: "The new 'Telecommuting Regulations' has been saved to the database."

[0333] ---

[0334] This will streamline the process of creating and amending regulations, ensuring compliance with laws and regulations. Furthermore, by taking into account the user's emotional state, the system will be more user-friendly and intuitive to use.

[0335] Example 2

[0336] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0337] In current policy management systems, when users create or modify policies, the process of checking compliance with laws and regulations is cumbersome, often resulting in a poor user experience. Furthermore, the system does not provide suggested modifications that reflect the user's feelings, often causing frustration for users. Therefore, there is a need for an efficient and user-friendly policy management system.

[0338] The identification process by the identification 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 means for a user to input details of creating new rules or amending existing rules; a means for collecting emotional data, including keyboard speed, facial expression recognition, and tone of voice, when the user inputs the rules; a means for receiving the user's input data and emotional data and analyzing the text using a natural language processing engine; a means for searching for relevant laws and regulations based on the analysis results and the emotional data and confirming the document's compliance; a means for generating document revision suggestions based on the compliance confirmation results and the emotional data; a means for sending the generated revision suggestions to the user and reflecting the emotional data to receive user approval or additional revisions; and a means for editing and saving the final document based on the user's approval or additional revisions. This realizes efficient and compliant rule creation and amendment, and also enables an intuitive and familiar process that takes the user's emotional state into consideration.

[0339] "User" means a person or entity that uses the System to create new rules or modify existing rules.

[0340] A "terminal" is a computer or digital device through which a user inputs regulatory data and collects emotional data.

[0341] "Emotional data" is data that indicates the user's emotional state, such as the user's keyboard speed, facial expression recognition, tone of voice, etc.

[0342] A "server" is a central computer system for analyzing received data and generating and sending correction suggestions.

[0343] A "natural language processing engine" is an algorithm or software that analyzes received text data and performs sentence structure analysis, semantic understanding, and keyword extraction.

[0344] A "legal database" is a database system that stores and makes searchable relevant laws and regulations.

[0345] A "revision proposal" is a proposed revision of a rule that is adjusted to comply with laws and regulations, and is a proposal that is generated taking into account the emotional state of the user.

[0346] "Final Document" means the completed version of the regulations document that has been edited based on the user's approval or additional modifications.

[0347] The present invention is a system for efficiently managing the creation and revision of regulations, and furthermore, it enables more intuitive and effective regulation management by recognizing and reflecting user emotions. This system analyzes regulation data entered by the user, automatically generates revision suggestions to comply with relevant laws and regulations, and can edit and save the final regulation document. Another feature is that it collects and analyzes user emotions as they are entered and adjusts the revision suggestions based on them.

[0348] Hardware and Software Configuration

[0349] User terminal: A device through which a user inputs input data and emotion data. This includes a general personal computer, tablet, smartphone, etc.

[0350] Emotion data collection module: Software that collects keyboard speed, facial expression recognition, and voice tone in real time on the device. For example, it uses standard typing speed monitoring software to measure keyboard speed, OpenCV for facial expression recognition, and libraries such as Praat for voice tone recognition.

[0351] Communication protocol: A secure communication protocol (e.g., HTTPS) is used to transmit data from the device to the server.

[0352] Server: A central computer system that analyzes data and generates correction suggestions. It contains the following modules:

[0353] Natural language processing engine: Software for analyzing user input text, such as SpaCy or BERT, to analyze sentence structure, understand meaning, and extract keywords.

[0354] Emotion engine: Software for analyzing a user's emotional data, for example, using "IBM Watson (registered trademark) Tone Analyzer" to identify the user's emotional state.

[0355] Legal database: A database system that stores data on relevant laws and regulations.

[0356] Correction proposal generation module: Software that uses the analysis results of the NLP engine and emotion engine to generate correction proposals in a form that is easy for users to accept.

[0357] Specific examples

[0358] Here is an example of creating a new "telecommuting policy."

[0359] Example prompt sentence:

[0360] I'd like to create a new "telecommuting policy." Here's the initial draft: 'Telecommuting must be approved by a supervisor.'

[0361] 1. User input:

[0362] The user uses a terminal to input an initial draft of the new "telecommuting regulations." For example, the user might input "telecommuting must be performed with the approval of a supervisor, in principle."

[0363] 2. Collecting Emotional Data:

[0364] The device measures the user's keyboard input speed as they type, and also uses a camera to analyze the user's facial expressions and a microphone to analyze the tone of their voice.

[0365] 3. Data transmission:

[0366] The device sends the collected text data and emotion data to the server using a secure communication protocol such as HTTPS.

[0367] 4. Data Analysis and Natural Language Processing:

[0368] The server uses a natural language processing engine to analyze the received text data and extract important keywords (e.g., "telecommuting" and "supervisor's approval"), while simultaneously analyzing the syntax of the text and understanding the meaning of the sentence.

[0369] 5. Emotional Data Analysis:

[0370] The server analyzes the emotional data using an emotion engine and identifies that the user is feeling stressed.

[0371] 6. Legal check and correction suggestion generation:

[0372] Based on the analysis results, the server searches for relevant laws and regulations (e.g., Article 4 of the Industrial Safety and Health Act) in a legal database and checks whether the regulations comply with the laws and regulations.

[0373] Taking emotion data into consideration, the system generates revision suggestions that are easy for users to accept. For example, it generates a revision suggestion such as, "Teleworking must, in principle, be carried out with the approval of a supervisor. In addition, measures to ensure employee safety must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0374] 7. Submitting suggested revisions:

[0375] The server sends the generated revision suggestions to the user's device and presents them to the user. They may be presented in stages based on the results of the emotion engine.

[0376] 8. Approval or Amendment:

[0377] The user checks the proposal and either approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[0378] 9. Edit and save the final document:

[0379] The server edits the final document to reflect the user's approval and saves it to the database. Once the save is complete, a notification is sent stating, "The new 'Telecommuting Rules' has been saved to the database."

[0380] The system streamlines policy creation and modification, ensures regulatory compliance, and provides a more intuitive and friendly process that takes into account the user's emotional state.

[0381] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0382] Step 1: Accepting user input

[0383] The user opens a dedicated application (for example, a web browser or dedicated software) on the device and accesses the screen for creating or modifying regulations.

[0384] The user enters the text of the regulations they want to create or modify into the input form. For example, they might enter "Telecommuting must be approved by a supervisor as a general rule."

[0385] Input: The policy text entered by the user.

[0386] Data processing / calculation: None.

[0387] Output: The input text is passed to the next process as is.

[0388] Step 2: Collecting emotion data

[0389] (Terminal) measures the user's input speed (keyboard typing speed) and records it as a log.

[0390] The device uses the user's camera image to recognize facial expressions and analyze changes in facial expression. This is done using a facial recognition library (e.g., OpenCV).

[0391] The device captures the microphone data and analyzes the tone and pitch of the voice, for example using a voice analysis library (e.g., Praat).

[0392] Input: User keyboard typing speed, camera footage, microphone data.

[0393] Data processing / calculation: measuring input speed, analyzing facial expressions, analyzing voice tones.

[0394] Output: Measured and analyzed emotion data (keyboard speed, facial expression data, voice tone data).

[0395] Step 3: Sending data

[0396] (Device) compiles the collected text data and emotion data into a single dataset.

[0397] The device sends this dataset to the server using a secure communication protocol (e.g., HTTPS).

[0398] Input: Text data, emotion data.

[0399] Data processing / computation: Formation of data sets.

[0400] Output: The dataset that is sent to the server.

[0401] Step 4: Data analysis and natural language processing

[0402] The server inputs the received text data into a natural language processing engine, such as "SpaCy" or "BERT."

[0403] (Server) analyzes the text data and extracts important keywords (e.g., "telecommuting" and "supervisor's approval").

[0404] (Server) performs syntactic analysis of the sentence and understands its meaning.

[0405] Input: Text data.

[0406] Data processing / calculation: Keyword extraction and syntactic analysis using natural language processing.

[0407] Output: Analysis results (keywords, syntax information).

[0408] Step 5: Analyze the sentiment data

[0409] The (server) uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the received emotion data.

[0410] (Server) determines the user's current emotional state (e.g., stress, joy, frustration, etc.).

[0411] Input: Emotion data (keyboard speed, facial expression data, voice tone data).

[0412] Data processing / calculation: Emotion analysis using an emotion engine.

[0413] Output: Sentiment analysis results (user's emotional state).

[0414] Step 6: Legal check and correction proposal generation

[0415] (Server) combines the analysis results of the NLP engine (keywords, syntactic information) with the emotion analysis results (user's emotional state).

[0416] The server accesses its internal database of laws and regulations and searches for relevant laws and regulations, for example, "Article 4 of the Industrial Safety and Health Act."

[0417] The server checks whether the content of the regulations complies with the law and generates a revision proposal based on the results.

[0418] The system takes into account the results of sentiment analysis and tailors the suggestions to make them more acceptable to the user. For example, if the user is feeling stressed, the system makes the suggestions simpler and easier to understand.

[0419] Input: Analysis results (keywords, syntactic information), sentiment analysis results (user's emotional state).

[0420] Data processing / calculation: checking compliance with laws and regulations, generating correction suggestions.

[0421] Output: Fix suggestions.

[0422] Step 7: Present suggested revisions

[0423] The (server) sends the generated revision proposal to the (terminal).

[0424] The device displays suggested revisions to the user, reflecting emotional data and presenting them in a format that is easy for the user to understand. Suggestions may also be presented in stages.

[0425] Input: suggested fix.

[0426] Data processing / calculation: Proposals for corrections are presented to the user.

[0427] Output: Correction suggestions presented to the user.

[0428] Step 8: Approve or amend

[0429] The user checks the proposal and either approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[0430] The (terminal) sends the user's approval or modification to the server.

[0431] Input: User approval or correction.

[0432] Data processing / calculation: Approval or submission of corrections.

[0433] Output: The approval or correction sent to the server.

[0434] Step 9: Edit and save the final document

[0435] The (server) edits the final document based on the user's approval or modifications.

[0436] The server stores the final completed document in a database, along with its location and metadata.

[0437] Input: User approval or correction.

[0438] Data processing / calculation: Editing of final document.

[0439] Output: The final document stored in the database.

[0440] The above is the specific processing flow of the system's program. This process enables efficient creation and revision of regulations that comply with laws and regulations, and also enables intuitive operation that takes user feelings into consideration.

[0441] (Application example 2)

[0442] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0443] Creating and amending regulations manually takes a lot of time and effort, and verifying compliance with laws and regulations is cumbersome. There is also a need to reduce the stress and burden users feel when creating and amending regulations. Furthermore, there is a need for a system that allows workers to propose new work procedures and streamlines the process of amending regulations, proposing amendments in real time while ensuring legal compliance.

[0444] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input details of creating new rules or amending existing rules; means for receiving the data input by the user and analyzing the text using a natural language processing engine; means for searching for relevant laws and regulations based on the analysis results and confirming the document's compliance; means for generating proposed document amendments based on the results of the conformance check; means for sending the generated proposed amendments to the user and accepting user approval or additional amendments; means for editing and saving the final document based on the user's approval or additional amendments; means for accepting user voice and manual input; means for collecting and analyzing emotion data; and means for presenting proposed amendments in real time and confirming user approval. This enables the creation and amendment of rules to be performed quickly and reliably, facilitating compliance with laws and regulations, and enabling an intuitive and low-burden process for the user.

[0445] "User" means a person or organization that uses the system to create new rules or modify existing rules.

[0446] The "means for inputting" is a device or interface that allows a user to provide the content of new rules or amendments to existing rules as text to the system.

[0447] A "natural language processing engine" is software that analyzes text entered by a user and understands its meaning.

[0448] "Means for analyzing text" refers to the process of using a natural language processing engine to analyze the structure of text entered by a user and understand its meaning.

[0449] "Means for searching laws and regulations" is the process of searching a database for relevant laws and regulations and verifying whether the entered text complies with them.

[0450] "Means for verifying compliance" is a function that compares the searched laws and regulations with the input text and determines whether the text complies with the laws and regulations.

[0451] The "means for generating suggested corrections" is a process that, when text does not comply with the law, automatically generates suggested corrections to ensure compliance.

[0452] The "means for sending revision suggestions" is an interface for notifying the user of the generated revision suggestions and obtaining the user's approval.

[0453] A "means for accepting approval or further modifications" is an interface that supports the process by which a user can approve a proposed modification or make further modifications.

[0454] The "means for editing and saving the final document" is a process for creating a final document that reflects the user's approval and additional modifications, and saving it in a database.

[0455] "Means for accepting voice and manual input" refers to an interface that allows a user to create or modify rules by voice or keyboard input.

[0456] The "means for collecting and analyzing emotional data" is the process of collecting the user's emotional state and analyzing the input content based on that.

[0457] The "means for presenting revision suggestions in real time" is a function for instantly presenting generated revision suggestions to the user and receiving feedback in real time.

[0458] The present invention provides a system for efficiently managing the creation and modification of rules, and further enables more intuitive and effective rule management by recognizing and reflecting the user's emotions. Specific embodiments for implementing the present invention are described below.

[0459] The system uses smart glasses or tablets as a means for users to input new policies or modify existing policies, and has an interface that accepts voice and manual input, with user input transmitted to the system in real time.

[0460] The server receives the user's input data and analyzes the text using a natural language processing engine. Natural language processing includes sentence structure analysis, semantic understanding, and keyword extraction. For example, when the voice input system of the smart glasses recognizes "I would like to update the work procedure," the voice data is sent to the server, where the natural language processing engine analyzes it.

[0461] The server also has a means of collecting and analyzing emotional data. Using the camera in the smart glasses or the front-facing camera on the tablet, the system analyzes the user's facial expressions and vocal tone to identify their emotional state. The results of this emotional analysis are then reflected in the process of generating suggested revisions to the document.

[0462] Based on the analysis results, the server searches a database for relevant laws and regulations to verify whether the input text complies with them. This legal check includes, for example, the Industrial Safety and Health Act.

[0463] The proposed corrections are generated based on the results of the legal compliance check and sentiment analysis data. The suggestions are tailored to be easy to understand for the user. For example, if the user is feeling stressed, the suggestions will be made simple and easy to understand.

[0464] The generated correction suggestions are presented to the user in real time. The correction suggestions are displayed on the smart glasses display, and the user confirms the correction by replying "I accept" via voice input.

[0465] The final document is compiled by the server and stored in a database. This process makes creating and amending policies fast and efficient, and ensures compliance with regulations.

[0466] Specific examples

[0467] As a concrete example, we present a scenario in which a factory worker proposes a new work procedure.

[0468] 1. A factory worker uses voice input to propose a new work procedure: 'Handle parts safely and inspect equipment every Monday.'

[0469] 2. The camera in the smart glasses captures the worker's face and performs emotion analysis.

[0470] 3. The server receives the voice data and emotion data and performs text analysis and emotion analysis.

[0471] 4. Check compliance with the law and generate a correction proposal. The correction proposal is "Handle parts safely and inspect equipment every Monday in accordance with Article 4 of the Industrial Safety and Health Act."

[0472] 5. Correction suggestions are displayed in real time on the smart glasses.

[0473] 6. The worker responds by voice input, "I approve the proposal," and the correction is confirmed.

[0474] 7. The final document is edited and stored in the database.

[0475] Prompt Sentence Examples

[0476] (Voice input)

[0477] "Propose new work procedures: 'Handle parts safely and inspect equipment every Monday.'"

[0478] (Proposal from the system)

[0479] "Proposed amendment: 'Parts will be handled safely, and equipment will be inspected every Monday in accordance with Article 4 of the Industrial Safety and Health Act.'"

[0480] (Confirmation of workers)

[0481] "I accept the proposal."

[0482] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0483] Step 1:

[0484] Users can create new rules or modify existing rules by voice or manually. Input is done using smart glasses or a tablet device. For example, a worker can use smart glasses to input "I'm proposing a new work procedure. 'Parts will be handled safely and equipment will be inspected every Monday.'"

[0485] Input: User voice or text input

[0486] Output: Input audio or text data

[0487] Step 2:

[0488] The device converts the input voice data into text data. It then uses a voice recognition engine (e.g., the SpeechRecognition library) to analyze the voice data and generate text. This text data is then sent from the device to the server.

[0489] Input: Audio data

[0490] Output: Text data

[0491] Step 3:

[0492] The server sends the received text data to a natural language processing (NLP) engine for analysis. The NLP engine (for example, a model using the Transformers library) analyzes the sentence structure, understands its meaning, and extracts keywords. For example, keywords such as "work procedures," "parts handling," and "equipment inspection" are extracted.

[0493] Input: Text data

[0494] Output: Analysis results (sentence structure, meaning, keywords)

[0495] Step 4:

[0496] The device's camera is used to collect user emotion data. The camera captures facial expressions and uses an emotion analysis model (e.g., OpenCV or a specific emotion analysis library) to obtain analysis results. The user's emotional state (e.g., stress, joy, etc.) is identified.

[0497] Input: Video data (facial expression)

[0498] Output: Emotion analysis results

[0499] Step 5:

[0500] The server uses the results of NLP analysis and sentiment analysis to search a database for relevant laws and regulations and check the suitability of the entered text. For example, it searches for "Article 4 of the Industrial Safety and Health Act" and checks whether the regulations comply with the law.

[0501] Input: NLP analysis results, sentiment analysis results

[0502] Output: Compliance check results

[0503] Step 6:

[0504] The server generates correction suggestions based on the results of the legal compliance check and the emotion analysis. The suggestions are adjusted to be easy to understand, taking into account the user's emotional state. For example, a correction suggestion might be generated such as, "Handle parts safely, and in accordance with Article 4 of the Industrial Safety and Health Act, inspect equipment every Monday."

[0505] Input: Legal compliance check results, sentiment analysis results

[0506] Output: suggested fixes

[0507] Step 7:

[0508] The server sends the generated correction suggestions to the terminal and presents them to the user, who can then see the correction suggestions on the smart glasses display and accept or make additional corrections.

[0509] Input: Suggested correction

[0510] Output: Proposal for corrections presented to the user

[0511] Step 8:

[0512] The user checks the proposed corrections and approves them by voice or manually. For example, the user can say "I approve the proposal" through the smart glasses. The device accepts this input and sends it to the server.

[0513] Input: Voice or text input of user approval or further correction

[0514] Output: Approval or correction data

[0515] Step 9:

[0516] The server edits and saves the final document based on the user's approval or additional modifications. The edited final document is saved in a database and can be referenced and used when needed, ensuring compliance with regulations.

[0517] Input: Approval or correction data

[0518] Output: Final document saved in database

[0519] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0520] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0521] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0522] [Second embodiment]

[0523] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0524] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0525] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0526] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0527] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0528] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0529] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0530] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0531] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0532] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0533] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0534] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0535] ---

[0536] The present invention is a system for efficiently managing the creation and revision of regulations. This system analyzes regulation data entered by users and automatically generates revision suggestions to comply with relevant laws and regulations. The system can also edit and save the final regulation document.

[0537] Program processing

[0538] 1. Accepting user input

[0539] The user inputs the text of a new rule they want to create or an existing rule they want to modify from a terminal. For example, a user might input the text "Telecommuting, in principle, requires the approval of a supervisor" as the initial draft of a new "telecommuting rule."

[0540] 2. Server data reception and natural language processing

[0541] The terminal sends the user's input data to the server, which receives it. The server then uses a natural language processing engine to analyze the text. Specifically, it analyzes the sentence structure, extracts keywords, and understands the meaning. For example, it extracts keywords such as "telecommuting" and "supervisor's approval" and understands their meaning.

[0542] 3. Legal check

[0543] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches to see if Article 4 of the Industrial Safety and Health Act, which pertains to telecommuting, is a relevant law. This confirms whether the regulations document complies with that law.

[0544] 4. Correction proposal generation

[0545] Based on the results of the conformance check, the server generates a document revision proposal, such as "Telecommuting will be carried out with the approval of the supervisor, in principle. In addition, measures to ensure employee safety will be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0546] 5. Replying to the User

[0547] After the proposed revision is generated, the server sends it to the terminal and displays it to the user. The user reviews the proposed revision and, if necessary, approves it or makes additional revisions. For example, the user may type, "I approve the proposal."

[0548] 6. Edit and save

[0549] If the amendments are approved, the server edits the final document based on the user's approval or additional amendments. After the final policy document is completed, the server saves it in the database. For example, the completion is as follows: "The new 'Telework Policy' has been saved in the database."

[0550] Specific examples

[0551] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[0552] 1. Accepting user input

[0553] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[0554] 2. Server data reception and natural language processing

[0555] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[0556] 3. Legal check

[0557] Based on the analysis results, the server searches for "Article 4 of the Industrial Safety and Health Act" and checks it against related laws and regulations.

[0558] 4. Correction proposal generation

[0559] (Server) generates a revision proposal that reads, "In principle, teleworking will be carried out with the approval of a supervisor. In addition, measures will be taken to ensure the safety of employees in accordance with Article 4 of the Industrial Safety and Health Act."

[0560] 5. Replying to the User

[0561] The server sends the proposed revision to the terminal, which the user confirms. The user approves the proposal by typing "I approve the proposal."

[0562] 6. Edit and save

[0563] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[0564] The above is a specific embodiment of the present invention. This system allows efficient creation and revision of regulations, ensuring compliance with laws and regulations.

[0565] The processing flow will be explained below.

[0566] ---

[0567] Step 1:

[0568] The user inputs the text of the new rule they want to create or the text of the existing rule they want to modify from the terminal.

[0569] Step 2:

[0570] (Terminal) receives text data entered by the user.

[0571] Step 3:

[0572] (Terminal) sends the received text data to the server.

[0573] Step 4:

[0574] (Server) receives the text data sent from the terminal.

[0575] Step 5:

[0576] The server analyzes the received text using a natural language processing (NLP) engine, specifically analyzing sentence structure, extracting keywords, and understanding meaning.

[0577] Step 6:

[0578] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches for "laws related to telecommuting."

[0579] Step 7:

[0580] The server uses the legal information retrieved from the database to verify whether the text entered by the user complies with the legal information.

[0581] Step 8:

[0582] The server generates a correction proposal based on the results of the conformance check. For example, it generates a correction proposal such as, "Telecommuting must be performed with the approval of the supervisor, in principle. In addition, measures to ensure the safety of employees must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0583] Step 9:

[0584] The server sends the generated revision suggestions to the terminal.

[0585] Step 10:

[0586] (Terminal) receives the correction suggestions sent from the server and displays them to the user.

[0587] Step 11:

[0588] The user checks the displayed correction proposal and approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[0589] Step 12:

[0590] The (terminal) sends the user's approval or additional modification data to the server.

[0591] Step 13:

[0592] The (server) edits the final document based on the user's approval or additional modifications.

[0593] Step 14:

[0594] The (server) saves the final edited document in a database.

[0595] ---

[0596] This will streamline the process of creating and amending regulations and create a system that ensures compliance with laws and regulations.

[0597] Example 1

[0598] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0599] The creation and revision of existing regulations requires a lot of manual checking work, which means that verifying compliance with laws and regulations takes a very long time. Furthermore, creating proposed revisions after verifying compliance also requires a lot of work, which is inefficient. This can delay the entire process of creating and revising regulations and reduce the certainty of compliance with laws and regulations.

[0600] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0601] In this invention, the server includes: a means for a user to input details for creating new rules or amending existing rules; a means for receiving the data input by the user and analyzing the text using a natural language processing engine; a means for searching for relevant laws and regulations based on the analysis results and checking the conformance of the document; a means for generating proposed document amendments based on the conformance check results; a means for sending the generated proposed amendments to the user and accepting user approval or additional amendments; a means for editing and saving the final document based on the user approval or additional amendments; a means for the user to input via a terminal equipped with a rules creation form; a means for the server to identify grammatical elements using the natural language processing engine; a means for the server to extract keywords using the natural language processing engine; a means for the server to search a database for relevant laws and regulations; a means for the server to generate proposed amendments using a template engine; and a means for using a generative AI model to identify templates and amendments, thereby enabling automation of conformance checks and proposed amendments.

[0602] "User" refers to an individual or legal entity that uses the System to create new rules or amend existing rules.

[0603] "Terminal" refers to a device such as a computer, tablet, or smartphone that allows a user to enter input.

[0604] "Server" refers to a central control unit for receiving, analyzing, and processing data sent by users.

[0605] A "natural language processing engine" refers to a software tool or algorithm that analyzes text data entered by a user and understands its meaning.

[0606] "Structural analysis" refers to the process of identifying grammatical elements in input text data and analyzing the structure of sentences.

[0607] "Keyword extraction" refers to the process of extracting important words and phrases from input text data.

[0608] "Database" refers to a data management system for storing and retrieving information on relevant laws and regulations.

[0609] "Template engine" refers to a software tool for generating documents, such as revision suggestions, using templates.

[0610] "Generative AI model" refers to a machine learning model that uses artificial intelligence to generate natural language.

[0611] "Proposed amendments" refers to amendments generated by the server to bring the content of the regulations entered by the user into compliance with laws and regulations.

[0612] The present invention is a system for efficiently managing the creation and revision of regulations. This system analyzes regulation data entered by users and automatically generates revision suggestions to comply with relevant laws and regulations. The system also has the function of editing and saving the final regulation document.

[0613] Hardware and Software Configuration

[0614] 1. User input terminal

[0615] Hardware: Using devices such as computers, tablets, and smartphones.

[0616] Software: Use an internet browser or dedicated application software.

[0617] 2. Server

[0618] Hardware: Use a server with a powerful processor, sufficient memory, and plenty of storage.

[0619] software:

[0620] Use a natural language processing engine (e.g., Spacy or BERT).

[0621] Create a revision suggestion template using a template engine.

[0622] Use a generative AI model (e.g., GPT-4).

[0623] Use a database that stores information on laws and regulations (e.g., LawDataDB).

[0624] Natural language processing and legal checks

[0625] 1. Data Reception and Analysis

[0626] (Terminal) sends the new regulations and amendments entered by the user to the server.

[0627] The server analyzes the received data, performs sentence structure analysis, keyword extraction, and semantic understanding using a natural language processing engine (Spacy or BERT).

[0628] 2. Legal check

[0629] Based on the analysis results, the server searches the database (LawDataDB) for relevant laws and regulations. Based on this search, it checks whether the regulations comply with the laws and regulations.

[0630] Generate correction suggestions and reply to the user

[0631] 1. Generate correction suggestions

[0632] The server generates a correction proposal based on the results of the compatibility check. It creates a template for the correction proposal using a template engine, and generates specific proposal sentences using a generative AI model.

[0633] 2. Reply to the user

[0634] The (server) sends the generated revision suggestions to the (terminal) so that the (user) can review them.

[0635] (User) reviews the proposed revisions and approves or makes additional revisions as necessary.

[0636] Edit and save the final document

[0637] 1. Edit and save

[0638] The (server) edits the final document based on the user's approval or additional modifications.

[0639] The final edited document is stored in a database (e.g., RegulationDB).

[0640] Specific examples

[0641] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[0642] 1. Accepting user input

[0643] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[0644] 2. Server data reception and natural language processing

[0645] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[0646] 3. Legal check

[0647] Based on the analysis results, the server searches for "Article 4 of the Industrial Safety and Health Act" and checks it against related laws and regulations.

[0648] 4. Correction proposal generation

[0649] (Server) generates a revision proposal that reads, "In principle, teleworking will be carried out with the approval of a supervisor. In addition, measures will be taken to ensure the safety of employees in accordance with Article 4 of the Industrial Safety and Health Act."

[0650] 5. Replying to the User

[0651] The server sends the proposed revision to the terminal, which the user confirms. The user approves the proposal by typing "I approve the proposal."

[0652] 6. Edit and save

[0653] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[0654] This system will enable efficient creation and revision of regulations and ensure compliance with the law.

[0655] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0656] Step 1: Accepting user input

[0657] The user creates new rules or enters the details of amendments to existing rules into the terminal. For example, the user might enter, "I would like to create a new 'telecommuting rules'. The initial draft is as follows: 'Telecommuting must, in principle, be approved by a supervisor.'"

[0658] Input: User-created policy text

[0659] Output: The input text data

[0660] Step 2: Server receives data and processes natural language

[0661] The terminal sends the input text data to the server. The server receives this data and analyzes the text using a natural language processing engine. The server analyzes the sentence structure, extracts keywords, and understands the meaning.

[0662] Input: Text data sent by the user

[0663] Output: Parsed grammatical structure, extracted keywords, semantic understanding results

[0664] Specific behavior:

[0665] The server receives the HTTP request and retrieves the content as text data.

[0666] A natural language processing engine (e.g., Spacy or BERT) is used to perform grammatical analysis, keyword extraction, and semantic analysis.

[0667] Step 3: Legal check

[0668] Based on the analysis results, the server searches for relevant laws and regulations in a database (LawDataDB). The server creates a database query using keywords from the analysis results and retrieves the search results.

[0669] Input: Parsed text data, extracted keywords

[0670] Output: Relevant statutory and regulatory data

[0671] Specific behavior:

[0672] The server runs SQL queries against a database (LawDataDB) to retrieve relevant laws and regulations.

[0673] Check compliance with regulations based on search results.

[0674] Step 4: Generate correction suggestions

[0675] The server generates revision suggestions based on the results of the legal check. It uses a template engine to create a revision suggestion template, and uses a generative AI model to generate specific suggested sentences.

[0676] Input: Legal check results, analyzed text data

[0677] Output: Suggested corrections

[0678] Specific behavior:

[0679] The server uses a template engine to prepare a template for the proposed revision.

[0680] Use a generative AI model (e.g., GPT-4) to generate suggested revisions.

[0681] Step 5: Respond to the user

[0682] The server sends the generated revision proposal to the terminal for the user to review. The user reviews the revision proposal and approves it or makes additional revisions as necessary.

[0683] Input: Generated suggested correction text

[0684] Output: User approval or further modifications

[0685] Specific behavior:

[0686] The server sends the proposed revisions to the terminal as an HTTP response.

[0687] The user checks the proposal via the terminal and inputs approval or additional corrections.

[0688] Step 6: Edit and save

[0689] The server edits the final document based on the user's approval or additional modifications, and the edited final document is stored in the database (RegulationDB).

[0690] Input: User approval or additional modifications

[0691] Output: The final completed document

[0692] Specific behavior:

[0693] The server edits the final document to reflect the user's input.

[0694] The final edited document is saved in the database (RegulationDB).

[0695] (Application example 1)

[0696] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0697] The management and revision of regulations in factories is complicated, and there is a problem that they are not updated in a timely manner based on the latest laws. There is also a high risk of human error or failure to update regulations, which increases the risk of legal violations. There are concerns that this situation will have a negative impact on worker safety and factory operations.

[0698] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0699] In this invention, the server includes: means for a user to input details of creating new rules or amending existing rules; means for receiving the data input by the user and analyzing the text using a natural language processing engine; means for searching for relevant laws and regulations based on the analysis results and checking the document's compliance; means for generating document amendment suggestions based on the compliance check results; means for sending the generated amendment suggestions to the user and accepting user approval or additional amendments; means for editing and saving the final document based on the user approval or additional amendments; and means for automatically managing and amending factory rule data in accordance with laws and regulations to keep the rules up to date at all times. This improves the efficiency of factory rule management, ensures compliance with laws and regulations, and improves worker safety and the reliability of factory operations.

[0700] "User" means the person who creates or modifies a Policy.

[0701] "Input means" refers to an interface that allows a user to enter details of creating new rules or amending existing rules.

[0702] A "natural language processing engine" refers to software that analyzes text data entered by a user and performs sentence structure analysis, semantic understanding, and keyword extraction.

[0703] "Means for searching laws and regulations" refers to technology for searching relevant laws and regulations in a database and verifying the compliance of documents.

[0704] The "means for generating correction suggestions" refers to a technology for creating correction suggestions for a document based on the results of the conformance check.

[0705] "Means for sending to user" refers to an interface for notifying the user of generated revision suggestions and receiving feedback from the user.

[0706] "Means for editing and storing" refers to the technology for compiling the final document based on the user's approval or additional modifications and storing it in a database.

[0707] "Factory regulation data" refers to document data on regulations and guidelines necessary for factory operations.

[0708] "Means for automatically managing and correcting regulations and always maintaining the latest regulations" refers to technology that continuously updates and corrects regulation data in factories in response to changes in laws and regulations, and keeps it up to date.

[0709] This invention is a system that automatically manages and modifies factory regulation data in accordance with laws and regulations, and always keeps the regulations up to date.

[0710] The system includes a means for a user to input details for creating new regulations or amending existing regulations, a means for receiving the input data and analyzing the text using a natural language processing engine, a means for searching for relevant laws and regulations based on the analysis results and confirming the document's compliance, a means for generating suggested amendments to the document based on the results of the compliance confirmation, a means for sending the generated suggested amendments to the user and accepting the user's approval or additional amendments, and a means for editing and saving the final document based on the user's approval or additional amendments.

[0711] Hardware and software used

[0712] Hardware

[0713] Factory robots: Used for implementing and managing regulation data.

[0714] Server: Performs data analysis and stores results.

[0715] User terminal: An interface for entering regulations and reviewing and approving proposed amendments.

[0716] software

[0717] Python: A programming language used for the basic implementation of programs.

[0718] OpenAI API: Used for text analysis using generative AI models.

[0719] SpaCy: A natural language processing engine for text analysis.

[0720] FuzzyWuzzy: Used for similarity searches with laws and regulations.

[0721] Data processing and calculation

[0722] The server receives new regulations or amendments from the user's device. The received data is first subjected to text analysis using a natural language processing engine (SpaCy). Text analysis involves analyzing the structure of the sentence, understanding its meaning, and extracting keywords, thereby obtaining the necessary information. Next, related laws and regulations are searched for based on the analysis results. This search uses a database of laws and regulations and a similarity search algorithm (FuzzyWuzzy).

[0723] The server then checks compliance with laws and regulations and automatically generates proposed revisions if necessary. The proposed revisions are sent to the user's device for review and approval. If the user approves or makes revisions, the final regulations document is edited based on the proposal and saved in the database.

[0724] Specific example explanation

[0725] As a concrete example, if a user enters, "I would like to create a new 'Safety Regulations'. Here is the initial draft: 'Helmets shall be worn while working.'", the system will automatically search the relevant legal database (e.g., the Industrial Safety and Health Act) and generate a proposed amendment: "In accordance with Article 4 of the Industrial Safety and Health Act, wearing helmets is mandatory to ensure safety while working." The user can then review the proposal and approve or make additional amendments. The final regulations document is saved in the database after approval.

[0726] Prompt Sentence Examples

[0727] The following are examples of prompts that users may enter into the system:

[0728] We want to create a new "safety rule." Here's an initial draft: 'Helmets must be worn while working.'

[0729] In this way, the present invention streamlines the management and revision of regulations within factories, enabling regulations to be maintained in strict compliance with relevant laws and regulations, which is expected to ensure compliance with laws and regulations and significantly improve worker safety and the reliability of factory operations.

[0730] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0731] Step 1:

[0732] A user uses a terminal to input the details of a new rule or an existing rule to be modified. For example, the user might input, "I would like to create a new 'Safety Rule'. Here is the initial draft: 'Helmets must be worn while working.'" This input data becomes a prompt for the system.

[0733] Step 2:

[0734] The terminal transmits the input data to the server, specifically, the text data input by the user.

[0735] Step 3:

[0736] The server analyzes the received text data using a natural language processing engine (SpaCy). It performs sentence structure analysis, semantic understanding, and keyword extraction to identify the meaning of keywords and sentences. For example, the keywords "helmet" and "working" are extracted.

[0737] Step 4:

[0738] The server then refers to the database of laws and regulations based on the analysis results and searches for relevant laws and regulations. Specifically, it uses FuzzyWuzzy to search for relevant laws and regulations in the database based on the extracted keywords, and identifies "Article 4 of the Industrial Safety and Health Act" as the result.

[0739] Step 5:

[0740] The server checks the document's relevance based on the search results. Specifically, it determines whether the current regulations comply with the applicable laws and regulations. For example, it checks whether "wearing a helmet" complies with Article 4 of the Industrial Safety and Health Act.

[0741] Step 6:

[0742] As a result of the conformance check, if necessary, a correction suggestion is generated. For example, a correction suggestion such as "In accordance with Article 4 of the Industrial Safety and Health Act, wearing a helmet is required to ensure safety during work" is automatically generated.

[0743] Step 7:

[0744] The server sends the generated revision proposal to the terminal and notifies the user, who then confirms the revision proposal through the terminal.

[0745] Step 8:

[0746] The user checks the proposed correction and approves it or makes additional corrections, for example, by typing "I approve the proposal."

[0747] Step 9:

[0748] The server edits the final document based on the user's approval or additional modifications, specifically by incorporating the approved modifications into the original document.

[0749] Step 10:

[0750] The server saves the final edited document in the database. As a result, the latest regulation data is accumulated in the database. For example, a message is displayed saying, "The new 'Safety Regulations' have been saved in the database."

[0751] The above are the specific processing steps for carrying out the present invention. This system allows for efficient management and revision of factory regulations, ensuring compliance with laws and regulations.

[0752] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0753] ---

[0754] The present invention is a system for efficiently managing the creation and revision of regulations, and furthermore, it enables more intuitive and effective regulation management by recognizing and reflecting user emotions. This system analyzes regulation data entered by the user, automatically generates revision suggestions to comply with relevant laws and regulations, and can edit and save the final regulation document. Another feature is that it collects and analyzes user emotions as they are entered and adjusts the revision suggestions based on them.

[0755] Program processing

[0756] 1. Accepting user input

[0757] The user inputs the text of a new rule they want to create or an existing rule they want to modify from a terminal. For example, a user might input the text "Telecommuting, in principle, requires the approval of a supervisor" as the initial draft of a new "telecommuting rule."

[0758] 2. Collecting Emotional Data

[0759] The device collects emotional data as users type, including keyboard typing speed, facial expression recognition, and tone of voice.

[0760] 3. Server data reception and natural language processing

[0761] (Terminal) transmits input text data and emotion data from the user to the server.

[0762] The server analyzes the received text data using a natural language processing (NLP) engine to analyze sentence structure, extract keywords, and understand meaning.

[0763] 4. Analysis by Emotion Engine

[0764] The server analyzes the emotion data with an emotion engine to identify the user's current emotional state, for example, detecting if the user is feeling stressed.

[0765] 5. Legal check and correction suggestion generation

[0766] Based on the analysis results, the server searches the database for relevant laws and regulations and checks whether the text entered by the user complies with the laws and regulations.

[0767] The server generates a correction suggestion based on the results of the compatibility check, but also reflects the results of the emotion engine and adjusts it to make it more acceptable to the user. For example, if the user is feeling stressed, the suggestion will be made more concise and easy to understand.

[0768] 6. Replying to the User

[0769] After the revision suggestions are generated, the (server) sends them to the (terminal) and displays them to the (user).

[0770] The device also reflects the results of the emotion engine and presents suggestions in a format that is easy for the user to understand. For example, suggestions may be presented in stages to reduce stress.

[0771] 7. User Authorization or Modification

[0772] The user checks the displayed correction proposal and accepts it or makes additional corrections as necessary. For example, the user may type "I accept the proposal."

[0773] 8. Edit and save

[0774] If the modifications are approved, the server edits the final document based on the user's approval or additional modifications.

[0775] The (server) saves the final edited document in a database.

[0776] Specific examples

[0777] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[0778] 1. Accepting user input

[0779] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[0780] 2. Collecting Emotional Data

[0781] The device monitors the user's typing speed and facial expressions to collect emotional data. For example, if the user is typing quickly, they may be feeling stressed.

[0782] 3. Server data reception and natural language processing

[0783] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[0784] 4. Analysis by Emotion Engine

[0785] (Server) analyzes the emotion data and determines that the user is feeling stressed.

[0786] 5. Legal check and correction suggestion generation

[0787] (Server) searches for "Article 4 of the Industrial Safety and Health Act" based on the analysis results and checks it against related laws and regulations.

[0788] The results of the emotion engine are reflected in the generation of concise and easy-to-understand revision suggestions: "Teleworking must, in principle, be carried out with the approval of the supervisor. In addition, measures to ensure employee safety must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0789] 6. Replying to the User

[0790] The server sends the proposed corrections to the device, which the user confirms. The suggestions may be displayed in stages to make them easier for the user to understand.

[0791] 7. User Authorization or Modification

[0792] (User) approves by typing "I approve the proposal."

[0793] 8. Edit and save

[0794] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[0795] The above is a specific embodiment of the present invention, which allows efficient policy creation and modification, ensures regulatory compliance, and provides a more intuitive and user-friendly process that takes into account the user's emotional state.

[0796] The processing flow will be explained below.

[0797] ---

[0798] Step 1:

[0799] The user inputs the text of the new rule they want to create or the existing rule they want to modify from the terminal. For example, they can input "Telecommuting must be performed with the approval of the supervisor as a general rule."

[0800] Step 2:

[0801] While the user types, the device collects emotional data such as keyboard typing speed, facial expression recognition, and tone of voice.

[0802] Step 3:

[0803] (Terminal) transmits the collected text data and emotion data to the server.

[0804] Step 4:

[0805] (Server) receives text data and emotion data sent from the terminal.

[0806] Step 5:

[0807] The server uses a natural language processing (NLP) engine to analyze the received text data, specifically analyzing the sentence structure, extracting keywords, and understanding the meaning.

[0808] Step 6:

[0809] The server uses an emotion engine to analyze the received emotion data and identify the user's emotional state, such as "feeling stressed."

[0810] Step 7:

[0811] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches for "laws regarding telecommuting."

[0812] Step 8:

[0813] The server uses the legal information retrieved from the database to verify whether the text entered by the user complies with the legal information.

[0814] Step 9:

[0815] The server generates a correction proposal based on the results of the conformance check. For example, it generates a correction proposal such as, "Telecommuting must be performed with the approval of the supervisor, in principle. In addition, measures to ensure the safety of employees must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0816] Step 10:

[0817] The server reflects the results of the emotion engine and adjusts the suggested corrections in an easy-to-understand manner that takes into account the user's emotional state. For example, if the user is feeling stressed, the suggested corrections will be concise and easy to understand.

[0818] Step 11:

[0819] The (server) sends the generated revision suggestions to the terminal and displays them to the (user).

[0820] Step 12:

[0821] The user checks the displayed correction proposal and accepts it or makes additional corrections as necessary. For example, the user enters "I accept the proposal."

[0822] Step 13:

[0823] The (terminal) sends the user's approval or additional modification data to the server.

[0824] Step 14:

[0825] The (server) edits the final document based on the user's approval or additional modifications.

[0826] Step 15:

[0827] The server saves the final edited document to the database. For example, the process is completed as follows: "The new 'Telecommuting Regulations' has been saved to the database."

[0828] ---

[0829] This will streamline the process of creating and amending regulations, ensuring compliance with laws and regulations. Furthermore, by taking into account the user's emotional state, the system will be more user-friendly and intuitive to use.

[0830] Example 2

[0831] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0832] In current policy management systems, when users create or modify policies, the process of checking compliance with laws and regulations is cumbersome, often resulting in a poor user experience. Furthermore, the system does not provide suggested modifications that reflect the user's feelings, often causing frustration for users. Therefore, there is a need for an efficient and user-friendly policy management system.

[0833] The identification process by the identification 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 means for a user to input details of creating new rules or amending existing rules; a means for collecting emotional data, including keyboard speed, facial expression recognition, and tone of voice, when the user inputs the rules; a means for receiving the user's input data and emotional data and analyzing the text using a natural language processing engine; a means for searching for relevant laws and regulations based on the analysis results and the emotional data and confirming the document's compliance; a means for generating document revision suggestions based on the compliance confirmation results and the emotional data; a means for sending the generated revision suggestions to the user and reflecting the emotional data to receive user approval or additional revisions; and a means for editing and saving the final document based on the user's approval or additional revisions. This realizes efficient and compliant rule creation and amendment, and also enables an intuitive and familiar process that takes the user's emotional state into consideration.

[0834] "User" means a person or entity that uses the System to create new rules or modify existing rules.

[0835] A "terminal" is a computer or digital device through which a user inputs regulatory data and collects emotional data.

[0836] "Emotional data" is data that indicates the user's emotional state, such as the user's keyboard speed, facial expression recognition, tone of voice, etc.

[0837] A "server" is a central computer system for analyzing received data and generating and sending correction suggestions.

[0838] A "natural language processing engine" is an algorithm or software that analyzes received text data and performs sentence structure analysis, semantic understanding, and keyword extraction.

[0839] A "legal database" is a database system that stores and makes searchable relevant laws and regulations.

[0840] A "revision proposal" is a proposed revision of a rule that is adjusted to comply with laws and regulations, and is a proposal that is generated taking into account the emotional state of the user.

[0841] "Final Document" means the completed version of the regulations document that has been edited based on the user's approval or additional modifications.

[0842] The present invention is a system for efficiently managing the creation and revision of regulations, and furthermore, it enables more intuitive and effective regulation management by recognizing and reflecting user emotions. This system analyzes regulation data entered by the user, automatically generates revision suggestions to comply with relevant laws and regulations, and can edit and save the final regulation document. Another feature is that it collects and analyzes user emotions as they are entered and adjusts the revision suggestions based on them.

[0843] Hardware and Software Configuration

[0844] User terminal: A device through which a user inputs input data and emotion data. This includes a general personal computer, tablet, smartphone, etc.

[0845] Emotion data collection module: Software that collects keyboard speed, facial expression recognition, and voice tone in real time on the device. For example, it uses standard typing speed monitoring software to measure keyboard speed, OpenCV for facial expression recognition, and libraries such as Praat for voice tone recognition.

[0846] Communication protocol: A secure communication protocol (e.g., HTTPS) is used to transmit data from the device to the server.

[0847] Server: A central computer system that analyzes data and generates correction suggestions. It contains the following modules:

[0848] Natural language processing engine: Software for analyzing user input text, such as SpaCy or BERT, to analyze sentence structure, understand meaning, and extract keywords.

[0849] Emotion engine: Software for analyzing user emotional data. For example, it uses the IBM Watson Tone Analyzer to identify the user's emotional state.

[0850] Legal database: A database system that stores data on relevant laws and regulations.

[0851] Correction proposal generation module: Software that uses the analysis results of the NLP engine and emotion engine to generate correction proposals in a form that is easy for users to accept.

[0852] Specific examples

[0853] Here is an example of creating a new "telecommuting policy."

[0854] Example prompt sentence:

[0855] I'd like to create a new "telecommuting policy." Here's the initial draft: 'Telecommuting must be approved by a supervisor.'

[0856] 1. User input:

[0857] The user uses a terminal to input an initial draft of the new "telecommuting regulations." For example, the user might input "telecommuting must be performed with the approval of a supervisor, in principle."

[0858] 2. Collecting Emotional Data:

[0859] The device measures the user's keyboard input speed as they type, and also uses a camera to analyze the user's facial expressions and a microphone to analyze the tone of their voice.

[0860] 3. Data transmission:

[0861] The device sends the collected text data and emotion data to the server using a secure communication protocol such as HTTPS.

[0862] 4. Data Analysis and Natural Language Processing:

[0863] The server uses a natural language processing engine to analyze the received text data and extract important keywords (e.g., "telecommuting" and "supervisor's approval"), while simultaneously analyzing the syntax of the text and understanding the meaning of the sentence.

[0864] 5. Emotional Data Analysis:

[0865] The server analyzes the emotional data using an emotion engine and identifies that the user is feeling stressed.

[0866] 6. Legal check and correction suggestion generation:

[0867] Based on the analysis results, the server searches for relevant laws and regulations (e.g., Article 4 of the Industrial Safety and Health Act) in a legal database and checks whether the regulations comply with the laws and regulations.

[0868] Taking emotion data into consideration, the system generates revision suggestions that are easy for users to accept. For example, it generates a revision suggestion such as, "Teleworking must, in principle, be carried out with the approval of a supervisor. In addition, measures to ensure employee safety must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[0869] 7. Submitting suggested revisions:

[0870] The server sends the generated revision suggestions to the user's device and presents them to the user. They may be presented in stages based on the results of the emotion engine.

[0871] 8. Approval or Amendment:

[0872] The user checks the proposal and either approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[0873] 9. Edit and save the final document:

[0874] The server edits the final document to reflect the user's approval and saves it to the database. Once the save is complete, a notification is sent stating, "The new 'Telecommuting Rules' has been saved to the database."

[0875] The system streamlines policy creation and modification, ensures regulatory compliance, and provides a more intuitive and friendly process that takes into account the user's emotional state.

[0876] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0877] Step 1: Accepting user input

[0878] The user opens a dedicated application (for example, a web browser or dedicated software) on the device and accesses the screen for creating or modifying regulations.

[0879] The user enters the text of the regulations they want to create or modify into the input form. For example, they might enter "Telecommuting must be approved by a supervisor as a general rule."

[0880] Input: The policy text entered by the user.

[0881] Data processing / calculation: None.

[0882] Output: The input text is passed to the next process as is.

[0883] Step 2: Collecting emotion data

[0884] (Terminal) measures the user's input speed (keyboard typing speed) and records it as a log.

[0885] The device uses the user's camera image to recognize facial expressions and analyze changes in facial expression. This is done using a facial recognition library (e.g., OpenCV).

[0886] The device captures the microphone data and analyzes the tone and pitch of the voice, for example using a voice analysis library (e.g., Praat).

[0887] Input: User keyboard typing speed, camera footage, microphone data.

[0888] Data processing / calculation: measuring input speed, analyzing facial expressions, analyzing voice tones.

[0889] Output: Measured and analyzed emotion data (keyboard speed, facial expression data, voice tone data).

[0890] Step 3: Sending data

[0891] (Device) compiles the collected text data and emotion data into a single dataset.

[0892] The device sends this dataset to the server using a secure communication protocol (e.g., HTTPS).

[0893] Input: Text data, emotion data.

[0894] Data processing / computation: Formation of data sets.

[0895] Output: The dataset that is sent to the server.

[0896] Step 4: Data analysis and natural language processing

[0897] The server inputs the received text data into a natural language processing engine, such as "SpaCy" or "BERT."

[0898] (Server) analyzes the text data and extracts important keywords (e.g., "telecommuting" and "supervisor's approval").

[0899] (Server) performs syntactic analysis of the sentence and understands its meaning.

[0900] Input: Text data.

[0901] Data processing / calculation: Keyword extraction and syntactic analysis using natural language processing.

[0902] Output: Analysis results (keywords, syntax information).

[0903] Step 5: Analyze the sentiment data

[0904] The (server) uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the received emotion data.

[0905] (Server) determines the user's current emotional state (e.g., stress, joy, frustration, etc.).

[0906] Input: Emotion data (keyboard speed, facial expression data, voice tone data).

[0907] Data processing / calculation: Emotion analysis using an emotion engine.

[0908] Output: Sentiment analysis results (user's emotional state).

[0909] Step 6: Legal check and correction proposal generation

[0910] (Server) combines the analysis results of the NLP engine (keywords, syntactic information) with the emotion analysis results (user's emotional state).

[0911] The server accesses its internal database of laws and regulations and searches for relevant laws and regulations, for example, "Article 4 of the Industrial Safety and Health Act."

[0912] The server checks whether the content of the regulations complies with the law and generates a revision proposal based on the results.

[0913] The system takes into account the results of sentiment analysis and tailors the suggestions to make them more acceptable to the user. For example, if the user is feeling stressed, the system makes the suggestions simpler and easier to understand.

[0914] Input: Analysis results (keywords, syntactic information), sentiment analysis results (user's emotional state).

[0915] Data processing / calculation: checking compliance with laws and regulations, generating correction suggestions.

[0916] Output: Fix suggestions.

[0917] Step 7: Present suggested revisions

[0918] The (server) sends the generated revision proposal to the (terminal).

[0919] The device displays suggested revisions to the user, reflecting emotional data and presenting them in a format that is easy for the user to understand. Suggestions may also be presented in stages.

[0920] Input: suggested fix.

[0921] Data processing / calculation: Proposals for corrections are presented to the user.

[0922] Output: Correction suggestions presented to the user.

[0923] Step 8: Approve or amend

[0924] The user checks the proposal and either approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[0925] The (terminal) sends the user's approval or modification to the server.

[0926] Input: User approval or correction.

[0927] Data processing / calculation: Approval or submission of corrections.

[0928] Output: The approval or correction sent to the server.

[0929] Step 9: Edit and save the final document

[0930] The (server) edits the final document based on the user's approval or modifications.

[0931] The server stores the final completed document in a database, along with its location and metadata.

[0932] Input: User approval or correction.

[0933] Data processing / calculation: Editing of final document.

[0934] Output: The final document stored in the database.

[0935] The above is the specific processing flow of the system's program. This process enables efficient creation and revision of regulations that comply with laws and regulations, and also enables intuitive operation that takes user feelings into consideration.

[0936] (Application example 2)

[0937] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0938] Creating and amending regulations manually takes a lot of time and effort, and verifying compliance with laws and regulations is cumbersome. There is also a need to reduce the stress and burden users feel when creating and amending regulations. Furthermore, there is a need for a system that allows workers to propose new work procedures and streamlines the process of amending regulations, proposing amendments in real time while ensuring legal compliance.

[0939] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input details of creating new rules or amending existing rules; means for receiving the data input by the user and analyzing the text using a natural language processing engine; means for searching for relevant laws and regulations based on the analysis results and confirming the document's compliance; means for generating proposed document amendments based on the results of the conformance check; means for sending the generated proposed amendments to the user and accepting user approval or additional amendments; means for editing and saving the final document based on the user's approval or additional amendments; means for accepting user voice and manual input; means for collecting and analyzing emotion data; and means for presenting proposed amendments in real time and confirming user approval. This enables the creation and amendment of rules to be performed quickly and reliably, facilitating compliance with laws and regulations, and enabling an intuitive and low-burden process for the user.

[0940] "User" means a person or organization that uses the system to create new rules or modify existing rules.

[0941] The "means for inputting" is a device or interface that allows a user to provide the content of new rules or amendments to existing rules as text to the system.

[0942] A "natural language processing engine" is software that analyzes text entered by a user and understands its meaning.

[0943] "Means for analyzing text" refers to the process of using a natural language processing engine to analyze the structure of text entered by a user and understand its meaning.

[0944] "Means for searching laws and regulations" is the process of searching a database for relevant laws and regulations and verifying whether the entered text complies with them.

[0945] "Means for verifying compliance" is a function that compares the searched laws and regulations with the input text and determines whether the text complies with the laws and regulations.

[0946] The "means for generating suggested corrections" is a process that, when text does not comply with the law, automatically generates suggested corrections to ensure compliance.

[0947] The "means for sending revision suggestions" is an interface for notifying the user of the generated revision suggestions and obtaining the user's approval.

[0948] A "means for accepting approval or further modifications" is an interface that supports the process by which a user can approve a proposed modification or make further modifications.

[0949] The "means for editing and saving the final document" is a process for creating a final document that reflects the user's approval and additional modifications, and saving it in a database.

[0950] "Means for accepting voice and manual input" refers to an interface that allows a user to create or modify rules by voice or keyboard input.

[0951] The "means for collecting and analyzing emotional data" is the process of collecting the user's emotional state and analyzing the input content based on that.

[0952] The "means for presenting revision suggestions in real time" is a function for instantly presenting generated revision suggestions to the user and receiving feedback in real time.

[0953] The present invention provides a system for efficiently managing the creation and modification of rules, and further enables more intuitive and effective rule management by recognizing and reflecting the user's emotions. Specific embodiments for implementing the present invention are described below.

[0954] The system uses smart glasses or tablets as a means for users to input new policies or modify existing policies, and has an interface that accepts voice and manual input, with user input transmitted to the system in real time.

[0955] The server receives the user's input data and analyzes the text using a natural language processing engine. Natural language processing includes sentence structure analysis, semantic understanding, and keyword extraction. For example, when the voice input system of the smart glasses recognizes "I would like to update the work procedure," the voice data is sent to the server, where the natural language processing engine analyzes it.

[0956] The server also has a means of collecting and analyzing emotional data. Using the camera in the smart glasses or the front-facing camera on the tablet, the system analyzes the user's facial expressions and vocal tone to identify their emotional state. The results of this emotional analysis are then reflected in the process of generating suggested revisions to the document.

[0957] Based on the analysis results, the server searches a database for relevant laws and regulations to verify whether the input text complies with them. This legal check includes, for example, the Industrial Safety and Health Act.

[0958] The proposed corrections are generated based on the results of the legal compliance check and sentiment analysis data. The suggestions are tailored to be easy to understand for the user. For example, if the user is feeling stressed, the suggestions will be made simple and easy to understand.

[0959] The generated correction suggestions are presented to the user in real time. The correction suggestions are displayed on the smart glasses display, and the user confirms the correction by replying "I accept" via voice input.

[0960] The final document is compiled by the server and stored in a database. This process makes creating and amending policies fast and efficient, and ensures compliance with regulations.

[0961] Specific examples

[0962] As a concrete example, we present a scenario in which a factory worker proposes a new work procedure.

[0963] 1. A factory worker uses voice input to propose a new work procedure: 'Handle parts safely and inspect equipment every Monday.'

[0964] 2. The camera in the smart glasses captures the worker's face and performs emotion analysis.

[0965] 3. The server receives the voice data and emotion data and performs text analysis and emotion analysis.

[0966] 4. Check compliance with the law and generate a correction proposal. The correction proposal is "Handle parts safely and inspect equipment every Monday in accordance with Article 4 of the Industrial Safety and Health Act."

[0967] 5. Correction suggestions are displayed in real time on the smart glasses.

[0968] 6. The worker responds by voice input, "I approve the proposal," and the correction is confirmed.

[0969] 7. The final document is edited and stored in the database.

[0970] Prompt Sentence Examples

[0971] (Voice input)

[0972] "Propose new work procedures: 'Handle parts safely and inspect equipment every Monday.'"

[0973] (Proposal from the system)

[0974] "Proposed amendment: 'Parts will be handled safely, and equipment will be inspected every Monday in accordance with Article 4 of the Industrial Safety and Health Act.'"

[0975] (Confirmation of workers)

[0976] "I accept the proposal."

[0977] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0978] Step 1:

[0979] Users can create new rules or modify existing rules by voice or manually. Input is done using smart glasses or a tablet device. For example, a worker can use smart glasses to input "I'm proposing a new work procedure. 'Parts will be handled safely and equipment will be inspected every Monday.'"

[0980] Input: User voice or text input

[0981] Output: Input audio or text data

[0982] Step 2:

[0983] The device converts the input voice data into text data. It then uses a voice recognition engine (e.g., the SpeechRecognition library) to analyze the voice data and generate text. This text data is then sent from the device to the server.

[0984] Input: Audio data

[0985] Output: Text data

[0986] Step 3:

[0987] The server sends the received text data to a natural language processing (NLP) engine for analysis. The NLP engine (for example, a model using the Transformers library) analyzes the sentence structure, understands its meaning, and extracts keywords. For example, keywords such as "work procedures," "parts handling," and "equipment inspection" are extracted.

[0988] Input: Text data

[0989] Output: Analysis results (sentence structure, meaning, keywords)

[0990] Step 4:

[0991] The device's camera is used to collect user emotion data. The camera captures facial expressions and uses an emotion analysis model (e.g., OpenCV or a specific emotion analysis library) to obtain analysis results. The user's emotional state (e.g., stress, joy, etc.) is identified.

[0992] Input: Video data (facial expression)

[0993] Output: Emotion analysis results

[0994] Step 5:

[0995] The server uses the results of NLP analysis and sentiment analysis to search a database for relevant laws and regulations and check the suitability of the entered text. For example, it searches for "Article 4 of the Industrial Safety and Health Act" and checks whether the regulations comply with the law.

[0996] Input: NLP analysis results, sentiment analysis results

[0997] Output: Compliance check results

[0998] Step 6:

[0999] The server generates correction suggestions based on the results of the legal compliance check and the emotion analysis. The suggestions are adjusted to be easy to understand, taking into account the user's emotional state. For example, a correction suggestion might be generated such as, "Handle parts safely, and in accordance with Article 4 of the Industrial Safety and Health Act, inspect equipment every Monday."

[1000] Input: Legal compliance check results, sentiment analysis results

[1001] Output: suggested fixes

[1002] Step 7:

[1003] The server sends the generated correction suggestions to the terminal and presents them to the user, who can then see the correction suggestions on the smart glasses display and accept or make additional corrections.

[1004] Input: Suggested correction

[1005] Output: Proposal for corrections presented to the user

[1006] Step 8:

[1007] The user checks the proposed corrections and approves them by voice or manually. For example, the user can say "I approve the proposal" through the smart glasses. The device accepts this input and sends it to the server.

[1008] Input: Voice or text input of user approval or further correction

[1009] Output: Approval or correction data

[1010] Step 9:

[1011] The server edits and saves the final document based on the user's approval or additional modifications. The edited final document is saved in a database and can be referenced and used when needed, ensuring compliance with regulations.

[1012] Input: Approval or correction data

[1013] Output: Final document saved in database

[1014] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1015] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1016] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1017] [Third embodiment]

[1018] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1019] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1020] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1021] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1022] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1023] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1024] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1025] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1026] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1027] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1028] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1029] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1030] ---

[1031] The present invention is a system for efficiently managing the creation and revision of regulations. This system analyzes regulation data entered by users and automatically generates revision suggestions to comply with relevant laws and regulations. The system can also edit and save the final regulation document.

[1032] Program processing

[1033] 1. Accepting user input

[1034] The user inputs the text of a new rule they want to create or an existing rule they want to modify from a terminal. For example, a user might input the text "Telecommuting, in principle, requires the approval of a supervisor" as the initial draft of a new "telecommuting rule."

[1035] 2. Server data reception and natural language processing

[1036] The terminal sends the user's input data to the server, which receives it. The server then uses a natural language processing engine to analyze the text. Specifically, it analyzes the sentence structure, extracts keywords, and understands the meaning. For example, it extracts keywords such as "telecommuting" and "supervisor's approval" and understands their meaning.

[1037] 3. Legal check

[1038] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches to see if Article 4 of the Industrial Safety and Health Act, which pertains to telecommuting, is a relevant law. This confirms whether the regulations document complies with that law.

[1039] 4. Correction proposal generation

[1040] Based on the results of the conformance check, the server generates a document revision proposal, such as "Telecommuting will be carried out with the approval of the supervisor, in principle. In addition, measures to ensure employee safety will be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1041] 5. Replying to the User

[1042] After the proposed revision is generated, the server sends it to the terminal and displays it to the user. The user reviews the proposed revision and, if necessary, approves it or makes additional revisions. For example, the user may type, "I approve the proposal."

[1043] 6. Edit and save

[1044] If the amendments are approved, the server edits the final document based on the user's approval or additional amendments. After the final policy document is completed, the server saves it in the database. For example, the completion is as follows: "The new 'Telework Policy' has been saved in the database."

[1045] Specific examples

[1046] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[1047] 1. Accepting user input

[1048] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[1049] 2. Server data reception and natural language processing

[1050] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[1051] 3. Legal check

[1052] Based on the analysis results, the server searches for "Article 4 of the Industrial Safety and Health Act" and checks it against related laws and regulations.

[1053] 4. Correction proposal generation

[1054] (Server) generates a revision proposal that reads, "In principle, teleworking will be carried out with the approval of a supervisor. In addition, measures will be taken to ensure the safety of employees in accordance with Article 4 of the Industrial Safety and Health Act."

[1055] 5. Replying to the User

[1056] The server sends the proposed revision to the terminal, which the user confirms. The user approves the proposal by typing "I approve the proposal."

[1057] 6. Edit and save

[1058] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[1059] The above is a specific embodiment of the present invention. This system allows efficient creation and revision of regulations, ensuring compliance with laws and regulations.

[1060] The processing flow will be explained below.

[1061] ---

[1062] Step 1:

[1063] The user inputs the text of the new rule they want to create or the text of the existing rule they want to modify from the terminal.

[1064] Step 2:

[1065] (Terminal) receives text data entered by the user.

[1066] Step 3:

[1067] (Terminal) sends the received text data to the server.

[1068] Step 4:

[1069] (Server) receives the text data sent from the terminal.

[1070] Step 5:

[1071] The server analyzes the received text using a natural language processing (NLP) engine, specifically analyzing sentence structure, extracting keywords, and understanding meaning.

[1072] Step 6:

[1073] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches for "laws related to telecommuting."

[1074] Step 7:

[1075] The server uses the legal information retrieved from the database to verify whether the text entered by the user complies with the legal information.

[1076] Step 8:

[1077] The server generates a correction proposal based on the results of the conformance check. For example, it generates a correction proposal such as, "Telecommuting must be performed with the approval of the supervisor, in principle. In addition, measures to ensure the safety of employees must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1078] Step 9:

[1079] The server sends the generated revision suggestions to the terminal.

[1080] Step 10:

[1081] (Terminal) receives the correction suggestions sent from the server and displays them to the user.

[1082] Step 11:

[1083] The user checks the displayed correction proposal and approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[1084] Step 12:

[1085] The (terminal) sends the user's approval or additional modification data to the server.

[1086] Step 13:

[1087] The (server) edits the final document based on the user's approval or additional modifications.

[1088] Step 14:

[1089] The (server) saves the final edited document in a database.

[1090] ---

[1091] This will streamline the process of creating and amending regulations and create a system that ensures compliance with laws and regulations.

[1092] Example 1

[1093] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1094] The creation and revision of existing regulations requires a lot of manual checking work, which means that verifying compliance with laws and regulations takes a very long time. Furthermore, creating proposed revisions after verifying compliance also requires a lot of work, which is inefficient. This can delay the entire process of creating and revising regulations and reduce the certainty of compliance with laws and regulations.

[1095] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1096] In this invention, the server includes: a means for a user to input details for creating new rules or amending existing rules; a means for receiving the data input by the user and analyzing the text using a natural language processing engine; a means for searching for relevant laws and regulations based on the analysis results and checking the conformance of the document; a means for generating proposed document amendments based on the conformance check results; a means for sending the generated proposed amendments to the user and accepting user approval or additional amendments; a means for editing and saving the final document based on the user approval or additional amendments; a means for the user to input via a terminal equipped with a rules creation form; a means for the server to identify grammatical elements using the natural language processing engine; a means for the server to extract keywords using the natural language processing engine; a means for the server to search a database for relevant laws and regulations; a means for the server to generate proposed amendments using a template engine; and a means for using a generative AI model to identify templates and amendments, thereby enabling automation of conformance checks and proposed amendments.

[1097] "User" refers to an individual or legal entity that uses the System to create new rules or amend existing rules.

[1098] "Terminal" refers to a device such as a computer, tablet, or smartphone that allows a user to enter input.

[1099] "Server" refers to a central control unit for receiving, analyzing, and processing data sent by users.

[1100] A "natural language processing engine" refers to a software tool or algorithm that analyzes text data entered by a user and understands its meaning.

[1101] "Structural analysis" refers to the process of identifying grammatical elements in input text data and analyzing the structure of sentences.

[1102] "Keyword extraction" refers to the process of extracting important words and phrases from input text data.

[1103] "Database" refers to a data management system for storing and retrieving information on relevant laws and regulations.

[1104] "Template engine" refers to a software tool for generating documents, such as revision suggestions, using templates.

[1105] "Generative AI model" refers to a machine learning model that uses artificial intelligence to generate natural language.

[1106] "Proposed amendments" refers to amendments generated by the server to bring the content of the regulations entered by the user into compliance with laws and regulations.

[1107] The present invention is a system for efficiently managing the creation and revision of regulations. This system analyzes regulation data entered by users and automatically generates revision suggestions to comply with relevant laws and regulations. The system also has the function of editing and saving the final regulation document.

[1108] Hardware and Software Configuration

[1109] 1. User input terminal

[1110] Hardware: Using devices such as computers, tablets, and smartphones.

[1111] Software: Use an internet browser or dedicated application software.

[1112] 2. Server

[1113] Hardware: Use a server with a powerful processor, sufficient memory, and plenty of storage.

[1114] software:

[1115] Use a natural language processing engine (e.g., Spacy or BERT).

[1116] Create a revision suggestion template using a template engine.

[1117] Use a generative AI model (e.g., GPT-4).

[1118] Use a database that stores information on laws and regulations (e.g., LawDataDB).

[1119] Natural language processing and legal checks

[1120] 1. Data Reception and Analysis

[1121] (Terminal) sends the new regulations and amendments entered by the user to the server.

[1122] The server analyzes the received data, performs sentence structure analysis, keyword extraction, and semantic understanding using a natural language processing engine (Spacy or BERT).

[1123] 2. Legal check

[1124] Based on the analysis results, the server searches the database (LawDataDB) for relevant laws and regulations. Based on this search, it checks whether the regulations comply with the laws and regulations.

[1125] Generate correction suggestions and reply to the user

[1126] 1. Generate correction suggestions

[1127] The server generates a correction proposal based on the results of the compatibility check. It creates a template for the correction proposal using a template engine, and generates specific proposal sentences using a generative AI model.

[1128] 2. Reply to the user

[1129] The (server) sends the generated revision suggestions to the (terminal) so that the (user) can review them.

[1130] (User) reviews the proposed revisions and approves or makes additional revisions as necessary.

[1131] Edit and save the final document

[1132] 1. Edit and save

[1133] The (server) edits the final document based on the user's approval or additional modifications.

[1134] The final edited document is stored in a database (e.g., RegulationDB).

[1135] Specific examples

[1136] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[1137] 1. Accepting user input

[1138] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[1139] 2. Server data reception and natural language processing

[1140] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[1141] 3. Legal check

[1142] Based on the analysis results, the server searches for "Article 4 of the Industrial Safety and Health Act" and checks it against related laws and regulations.

[1143] 4. Correction proposal generation

[1144] (Server) generates a revision proposal that reads, "In principle, teleworking will be carried out with the approval of a supervisor. In addition, measures will be taken to ensure the safety of employees in accordance with Article 4 of the Industrial Safety and Health Act."

[1145] 5. Replying to the User

[1146] The server sends the proposed revision to the terminal, which the user confirms. The user approves the proposal by typing "I approve the proposal."

[1147] 6. Edit and save

[1148] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[1149] This system will enable efficient creation and revision of regulations and ensure compliance with the law.

[1150] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1151] Step 1: Accepting user input

[1152] The user creates new rules or enters the details of amendments to existing rules into the terminal. For example, the user might enter, "I would like to create a new 'telecommuting rules'. The initial draft is as follows: 'Telecommuting must, in principle, be approved by a supervisor.'"

[1153] Input: User-created policy text

[1154] Output: The input text data

[1155] Step 2: Server receives data and processes natural language

[1156] The terminal sends the input text data to the server. The server receives this data and analyzes the text using a natural language processing engine. The server analyzes the sentence structure, extracts keywords, and understands the meaning.

[1157] Input: Text data sent by the user

[1158] Output: Parsed grammatical structure, extracted keywords, semantic understanding results

[1159] Specific behavior:

[1160] The server receives the HTTP request and retrieves the content as text data.

[1161] A natural language processing engine (e.g., Spacy or BERT) is used to perform grammatical analysis, keyword extraction, and semantic analysis.

[1162] Step 3: Legal check

[1163] Based on the analysis results, the server searches for relevant laws and regulations in a database (LawDataDB). The server creates a database query using keywords from the analysis results and retrieves the search results.

[1164] Input: Parsed text data, extracted keywords

[1165] Output: Relevant statutory and regulatory data

[1166] Specific behavior:

[1167] The server runs SQL queries against a database (LawDataDB) to retrieve relevant laws and regulations.

[1168] Check compliance with regulations based on search results.

[1169] Step 4: Generate correction suggestions

[1170] The server generates revision suggestions based on the results of the legal check. It uses a template engine to create a revision suggestion template, and uses a generative AI model to generate specific suggested sentences.

[1171] Input: Legal check results, analyzed text data

[1172] Output: Suggested corrections

[1173] Specific behavior:

[1174] The server uses a template engine to prepare a template for the proposed revision.

[1175] Use a generative AI model (e.g., GPT-4) to generate suggested revisions.

[1176] Step 5: Respond to the user

[1177] The server sends the generated revision proposal to the terminal for the user to review. The user reviews the revision proposal and approves it or makes additional revisions as necessary.

[1178] Input: Generated suggested correction text

[1179] Output: User approval or further modifications

[1180] Specific behavior:

[1181] The server sends the proposed revisions to the terminal as an HTTP response.

[1182] The user checks the proposal via the terminal and inputs approval or additional corrections.

[1183] Step 6: Edit and save

[1184] The server edits the final document based on the user's approval or additional modifications, and the edited final document is stored in the database (RegulationDB).

[1185] Input: User approval or additional modifications

[1186] Output: The final completed document

[1187] Specific behavior:

[1188] The server edits the final document to reflect the user's input.

[1189] The final edited document is saved in the database (RegulationDB).

[1190] (Application example 1)

[1191] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1192] The management and revision of regulations in factories is complicated, and there is a problem that they are not updated in a timely manner based on the latest laws. There is also a high risk of human error or failure to update regulations, which increases the risk of legal violations. There are concerns that this situation will have a negative impact on worker safety and factory operations.

[1193] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1194] In this invention, the server includes: means for a user to input details of creating new rules or amending existing rules; means for receiving the data input by the user and analyzing the text using a natural language processing engine; means for searching for relevant laws and regulations based on the analysis results and checking the document's compliance; means for generating document amendment suggestions based on the compliance check results; means for sending the generated amendment suggestions to the user and accepting user approval or additional amendments; means for editing and saving the final document based on the user approval or additional amendments; and means for automatically managing and amending factory rule data in accordance with laws and regulations to keep the rules up to date at all times. This improves the efficiency of factory rule management, ensures compliance with laws and regulations, and improves worker safety and the reliability of factory operations.

[1195] "User" means the person who creates or modifies a Policy.

[1196] "Input means" refers to an interface that allows a user to enter details of creating new rules or amending existing rules.

[1197] A "natural language processing engine" refers to software that analyzes text data entered by a user and performs sentence structure analysis, semantic understanding, and keyword extraction.

[1198] "Means for searching laws and regulations" refers to technology for searching relevant laws and regulations in a database and verifying the compliance of documents.

[1199] The "means for generating correction suggestions" refers to a technology for creating correction suggestions for a document based on the results of the conformance check.

[1200] "Means for sending to user" refers to an interface for notifying the user of generated revision suggestions and receiving feedback from the user.

[1201] "Means for editing and storing" refers to the technology for compiling the final document based on the user's approval or additional modifications and storing it in a database.

[1202] "Factory regulation data" refers to document data on regulations and guidelines necessary for factory operations.

[1203] "Means for automatically managing and correcting regulations and always maintaining the latest regulations" refers to technology that continuously updates and corrects regulation data in factories in response to changes in laws and regulations, and keeps it up to date.

[1204] This invention is a system that automatically manages and modifies factory regulation data in accordance with laws and regulations, and always keeps the regulations up to date.

[1205] The system includes a means for a user to input details for creating new regulations or amending existing regulations, a means for receiving the input data and analyzing the text using a natural language processing engine, a means for searching for relevant laws and regulations based on the analysis results and confirming the document's compliance, a means for generating suggested amendments to the document based on the results of the compliance confirmation, a means for sending the generated suggested amendments to the user and accepting the user's approval or additional amendments, and a means for editing and saving the final document based on the user's approval or additional amendments.

[1206] Hardware and software used

[1207] Hardware

[1208] Factory robots: Used for implementing and managing regulation data.

[1209] Server: Performs data analysis and stores results.

[1210] User terminal: An interface for entering regulations and reviewing and approving proposed amendments.

[1211] software

[1212] Python: A programming language used for the basic implementation of programs.

[1213] OpenAI API: Used for text analysis using generative AI models.

[1214] SpaCy: A natural language processing engine for text analysis.

[1215] FuzzyWuzzy: Used for similarity searches with laws and regulations.

[1216] Data processing and calculation

[1217] The server receives new regulations or amendments from the user's device. The received data is first subjected to text analysis using a natural language processing engine (SpaCy). Text analysis involves analyzing the structure of the sentence, understanding its meaning, and extracting keywords, thereby obtaining the necessary information. Next, related laws and regulations are searched for based on the analysis results. This search uses a database of laws and regulations and a similarity search algorithm (FuzzyWuzzy).

[1218] The server then checks compliance with laws and regulations and automatically generates proposed revisions if necessary. The proposed revisions are sent to the user's device for review and approval. If the user approves or makes revisions, the final regulations document is edited based on the proposal and saved in the database.

[1219] Specific example explanation

[1220] As a concrete example, if a user enters, "I would like to create a new 'Safety Regulations'. Here is the initial draft: 'Helmets shall be worn while working.'", the system will automatically search the relevant legal database (e.g., the Industrial Safety and Health Act) and generate a proposed amendment: "In accordance with Article 4 of the Industrial Safety and Health Act, wearing helmets is mandatory to ensure safety while working." The user can then review the proposal and approve or make additional amendments. The final regulations document is saved in the database after approval.

[1221] Prompt Sentence Examples

[1222] The following are examples of prompts that users may enter into the system:

[1223] We want to create a new "safety rule." Here's an initial draft: 'Helmets must be worn while working.'

[1224] In this way, the present invention streamlines the management and revision of regulations within factories, enabling regulations to be maintained in strict compliance with relevant laws and regulations, which is expected to ensure compliance with laws and regulations and significantly improve worker safety and the reliability of factory operations.

[1225] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1226] Step 1:

[1227] A user uses a terminal to input the details of a new rule or an existing rule to be modified. For example, the user might input, "I would like to create a new 'Safety Rule'. Here is the initial draft: 'Helmets must be worn while working.'" This input data becomes a prompt for the system.

[1228] Step 2:

[1229] The terminal transmits the input data to the server, specifically, the text data input by the user.

[1230] Step 3:

[1231] The server analyzes the received text data using a natural language processing engine (SpaCy). It performs sentence structure analysis, semantic understanding, and keyword extraction to identify the meaning of keywords and sentences. For example, the keywords "helmet" and "working" are extracted.

[1232] Step 4:

[1233] The server then refers to the database of laws and regulations based on the analysis results and searches for relevant laws and regulations. Specifically, it uses FuzzyWuzzy to search for relevant laws and regulations in the database based on the extracted keywords, and identifies "Article 4 of the Industrial Safety and Health Act" as the result.

[1234] Step 5:

[1235] The server checks the document's relevance based on the search results. Specifically, it determines whether the current regulations comply with the applicable laws and regulations. For example, it checks whether "wearing a helmet" complies with Article 4 of the Industrial Safety and Health Act.

[1236] Step 6:

[1237] As a result of the conformance check, if necessary, a correction suggestion is generated. For example, a correction suggestion such as "In accordance with Article 4 of the Industrial Safety and Health Act, wearing a helmet is required to ensure safety during work" is automatically generated.

[1238] Step 7:

[1239] The server sends the generated revision proposal to the terminal and notifies the user, who then confirms the revision proposal through the terminal.

[1240] Step 8:

[1241] The user checks the proposed correction and approves it or makes additional corrections, for example, by typing "I approve the proposal."

[1242] Step 9:

[1243] The server edits the final document based on the user's approval or additional modifications, specifically by incorporating the approved modifications into the original document.

[1244] Step 10:

[1245] The server saves the final edited document in the database. As a result, the latest regulation data is accumulated in the database. For example, a message is displayed saying, "The new 'Safety Regulations' have been saved in the database."

[1246] The above are the specific processing steps for carrying out the present invention. This system allows for efficient management and revision of factory regulations, ensuring compliance with laws and regulations.

[1247] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1248] ---

[1249] The present invention is a system for efficiently managing the creation and revision of regulations, and furthermore, it enables more intuitive and effective regulation management by recognizing and reflecting user emotions. This system analyzes regulation data entered by the user, automatically generates revision suggestions to comply with relevant laws and regulations, and can edit and save the final regulation document. Another feature is that it collects and analyzes user emotions as they are entered and adjusts the revision suggestions based on them.

[1250] Program processing

[1251] 1. Accepting user input

[1252] The user inputs the text of a new rule they want to create or an existing rule they want to modify from a terminal. For example, a user might input the text "Telecommuting, in principle, requires the approval of a supervisor" as the initial draft of a new "telecommuting rule."

[1253] 2. Collecting Emotional Data

[1254] The device collects emotional data as users type, including keyboard typing speed, facial expression recognition, and tone of voice.

[1255] 3. Server data reception and natural language processing

[1256] (Terminal) transmits input text data and emotion data from the user to the server.

[1257] The server analyzes the received text data using a natural language processing (NLP) engine to analyze sentence structure, extract keywords, and understand meaning.

[1258] 4. Analysis by Emotion Engine

[1259] The server analyzes the emotion data with an emotion engine to identify the user's current emotional state, for example, detecting if the user is feeling stressed.

[1260] 5. Legal check and correction suggestion generation

[1261] Based on the analysis results, the server searches the database for relevant laws and regulations and checks whether the text entered by the user complies with the laws and regulations.

[1262] The server generates a correction suggestion based on the results of the compatibility check, but also reflects the results of the emotion engine and adjusts it to make it more acceptable to the user. For example, if the user is feeling stressed, the suggestion will be made more concise and easy to understand.

[1263] 6. Replying to the User

[1264] After the revision suggestions are generated, the (server) sends them to the (terminal) and displays them to the (user).

[1265] The device also reflects the results of the emotion engine and presents suggestions in a format that is easy for the user to understand. For example, suggestions may be presented in stages to reduce stress.

[1266] 7. User Authorization or Modification

[1267] The user checks the displayed correction proposal and accepts it or makes additional corrections as necessary. For example, the user may type "I accept the proposal."

[1268] 8. Edit and save

[1269] If the modifications are approved, the server edits the final document based on the user's approval or additional modifications.

[1270] The (server) saves the final edited document in a database.

[1271] Specific examples

[1272] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[1273] 1. Accepting user input

[1274] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[1275] 2. Collecting Emotional Data

[1276] The device monitors the user's typing speed and facial expressions to collect emotional data. For example, if the user is typing quickly, they may be feeling stressed.

[1277] 3. Server data reception and natural language processing

[1278] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[1279] 4. Analysis by Emotion Engine

[1280] (Server) analyzes the emotion data and determines that the user is feeling stressed.

[1281] 5. Legal check and correction suggestion generation

[1282] (Server) searches for "Article 4 of the Industrial Safety and Health Act" based on the analysis results and checks it against related laws and regulations.

[1283] The results of the emotion engine are reflected in the generation of concise and easy-to-understand revision suggestions: "Teleworking must, in principle, be carried out with the approval of the supervisor. In addition, measures to ensure employee safety must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1284] 6. Replying to the User

[1285] The server sends the proposed corrections to the device, which the user confirms. The suggestions may be displayed in stages to make them easier for the user to understand.

[1286] 7. User Authorization or Modification

[1287] (User) approves by typing "I approve the proposal."

[1288] 8. Edit and save

[1289] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[1290] The above is a specific embodiment of the present invention, which allows efficient policy creation and modification, ensures regulatory compliance, and provides a more intuitive and user-friendly process that takes into account the user's emotional state.

[1291] The processing flow will be explained below.

[1292] ---

[1293] Step 1:

[1294] The user inputs the text of the new rule they want to create or the existing rule they want to modify from the terminal. For example, they can input "Telecommuting must be performed with the approval of the supervisor as a general rule."

[1295] Step 2:

[1296] While the user types, the device collects emotional data such as keyboard typing speed, facial expression recognition, and tone of voice.

[1297] Step 3:

[1298] (Terminal) transmits the collected text data and emotion data to the server.

[1299] Step 4:

[1300] (Server) receives text data and emotion data sent from the terminal.

[1301] Step 5:

[1302] The server uses a natural language processing (NLP) engine to analyze the received text data, specifically analyzing the sentence structure, extracting keywords, and understanding the meaning.

[1303] Step 6:

[1304] The server uses an emotion engine to analyze the received emotion data and identify the user's emotional state, such as "feeling stressed."

[1305] Step 7:

[1306] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches for "laws regarding telecommuting."

[1307] Step 8:

[1308] The server uses the legal information retrieved from the database to verify whether the text entered by the user complies with the legal information.

[1309] Step 9:

[1310] The server generates a correction proposal based on the results of the conformance check. For example, it generates a correction proposal such as, "Telecommuting must be performed with the approval of the supervisor, in principle. In addition, measures to ensure the safety of employees must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1311] Step 10:

[1312] The server reflects the results of the emotion engine and adjusts the suggested corrections in an easy-to-understand manner that takes into account the user's emotional state. For example, if the user is feeling stressed, the suggested corrections will be concise and easy to understand.

[1313] Step 11:

[1314] The (server) sends the generated revision suggestions to the terminal and displays them to the (user).

[1315] Step 12:

[1316] The user checks the displayed correction proposal and accepts it or makes additional corrections as necessary. For example, the user enters "I accept the proposal."

[1317] Step 13:

[1318] The (terminal) sends the user's approval or additional modification data to the server.

[1319] Step 14:

[1320] The (server) edits the final document based on the user's approval or additional modifications.

[1321] Step 15:

[1322] The server saves the final edited document to the database. For example, the process is completed as follows: "The new 'Telecommuting Regulations' has been saved to the database."

[1323] ---

[1324] This will streamline the process of creating and amending regulations, ensuring compliance with laws and regulations. Furthermore, by taking into account the user's emotional state, the system will be more user-friendly and intuitive to use.

[1325] Example 2

[1326] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1327] In current policy management systems, when users create or modify policies, the process of checking compliance with laws and regulations is cumbersome, often resulting in a poor user experience. Furthermore, the system does not provide suggested modifications that reflect the user's feelings, often causing frustration for users. Therefore, there is a need for an efficient and user-friendly policy management system.

[1328] The identification process by the identification 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 means for a user to input details of creating new rules or amending existing rules; a means for collecting emotional data, including keyboard speed, facial expression recognition, and tone of voice, when the user inputs the rules; a means for receiving the user's input data and emotional data and analyzing the text using a natural language processing engine; a means for searching for relevant laws and regulations based on the analysis results and the emotional data and confirming the document's compliance; a means for generating document revision suggestions based on the compliance confirmation results and the emotional data; a means for sending the generated revision suggestions to the user and reflecting the emotional data to receive user approval or additional revisions; and a means for editing and saving the final document based on the user's approval or additional revisions. This realizes efficient and compliant rule creation and amendment, and also enables an intuitive and familiar process that takes the user's emotional state into consideration.

[1329] "User" means a person or entity that uses the System to create new rules or modify existing rules.

[1330] A "terminal" is a computer or digital device through which a user inputs regulatory data and collects emotional data.

[1331] "Emotional data" is data that indicates the user's emotional state, such as the user's keyboard speed, facial expression recognition, tone of voice, etc.

[1332] A "server" is a central computer system for analyzing received data and generating and sending correction suggestions.

[1333] A "natural language processing engine" is an algorithm or software that analyzes received text data and performs sentence structure analysis, semantic understanding, and keyword extraction.

[1334] A "legal database" is a database system that stores and makes searchable relevant laws and regulations.

[1335] A "revision proposal" is a proposed revision of a rule that is adjusted to comply with laws and regulations, and is a proposal that is generated taking into account the emotional state of the user.

[1336] "Final Document" means the completed version of the regulations document that has been edited based on the user's approval or additional modifications.

[1337] The present invention is a system for efficiently managing the creation and revision of regulations, and furthermore, it enables more intuitive and effective regulation management by recognizing and reflecting user emotions. This system analyzes regulation data entered by the user, automatically generates revision suggestions to comply with relevant laws and regulations, and can edit and save the final regulation document. Another feature is that it collects and analyzes user emotions as they are entered and adjusts the revision suggestions based on them.

[1338] Hardware and Software Configuration

[1339] User terminal: A device through which a user inputs input data and emotion data. This includes a general personal computer, tablet, smartphone, etc.

[1340] Emotion data collection module: Software that collects keyboard speed, facial expression recognition, and voice tone in real time on the device. For example, it uses standard typing speed monitoring software to measure keyboard speed, OpenCV for facial expression recognition, and libraries such as Praat for voice tone recognition.

[1341] Communication protocol: A secure communication protocol (e.g., HTTPS) is used to transmit data from the device to the server.

[1342] Server: A central computer system that analyzes data and generates correction suggestions. It contains the following modules:

[1343] Natural language processing engine: Software for analyzing user input text, such as SpaCy or BERT, to analyze sentence structure, understand meaning, and extract keywords.

[1344] Emotion engine: Software for analyzing user emotional data. For example, it uses the IBM Watson Tone Analyzer to identify the user's emotional state.

[1345] Legal database: A database system that stores data on relevant laws and regulations.

[1346] Correction proposal generation module: Software that uses the analysis results of the NLP engine and emotion engine to generate correction proposals in a form that is easy for users to accept.

[1347] Specific examples

[1348] Here is an example of creating a new "telecommuting policy."

[1349] Example prompt sentence:

[1350] I'd like to create a new "telecommuting policy." Here's the initial draft: 'Telecommuting must be approved by a supervisor.'

[1351] 1. User input:

[1352] The user uses a terminal to input an initial draft of the new "telecommuting regulations." For example, the user might input "telecommuting must be performed with the approval of a supervisor, in principle."

[1353] 2. Collecting Emotional Data:

[1354] The device measures the user's keyboard input speed as they type, and also uses a camera to analyze the user's facial expressions and a microphone to analyze the tone of their voice.

[1355] 3. Data transmission:

[1356] The device sends the collected text data and emotion data to the server using a secure communication protocol such as HTTPS.

[1357] 4. Data Analysis and Natural Language Processing:

[1358] The server uses a natural language processing engine to analyze the received text data and extract important keywords (e.g., "telecommuting" and "supervisor's approval"), while simultaneously analyzing the syntax of the text and understanding the meaning of the sentence.

[1359] 5. Emotional Data Analysis:

[1360] The server analyzes the emotional data using an emotion engine and identifies that the user is feeling stressed.

[1361] 6. Legal check and correction suggestion generation:

[1362] Based on the analysis results, the server searches for relevant laws and regulations (e.g., Article 4 of the Industrial Safety and Health Act) in a legal database and checks whether the regulations comply with the laws and regulations.

[1363] Taking emotion data into consideration, the system generates revision suggestions that are easy for users to accept. For example, it generates a revision suggestion such as, "Teleworking must, in principle, be carried out with the approval of a supervisor. In addition, measures to ensure employee safety must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1364] 7. Submitting suggested revisions:

[1365] The server sends the generated revision suggestions to the user's device and presents them to the user. They may be presented in stages based on the results of the emotion engine.

[1366] 8. Approval or Amendment:

[1367] The user checks the proposal and either approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[1368] 9. Edit and save the final document:

[1369] The server edits the final document to reflect the user's approval and saves it to the database. Once the save is complete, a notification is sent stating, "The new 'Telecommuting Rules' has been saved to the database."

[1370] The system streamlines policy creation and modification, ensures regulatory compliance, and provides a more intuitive and friendly process that takes into account the user's emotional state.

[1371] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1372] Step 1: Accepting user input

[1373] The user opens a dedicated application (for example, a web browser or dedicated software) on the device and accesses the screen for creating or modifying regulations.

[1374] The user enters the text of the regulations they want to create or modify into the input form. For example, they might enter "Telecommuting must be approved by a supervisor as a general rule."

[1375] Input: The policy text entered by the user.

[1376] Data processing / calculation: None.

[1377] Output: The input text is passed to the next process as is.

[1378] Step 2: Collecting emotion data

[1379] (Terminal) measures the user's input speed (keyboard typing speed) and records it as a log.

[1380] The device uses the user's camera image to recognize facial expressions and analyze changes in facial expression. This is done using a facial recognition library (e.g., OpenCV).

[1381] The device captures the microphone data and analyzes the tone and pitch of the voice, for example using a voice analysis library (e.g., Praat).

[1382] Input: User keyboard typing speed, camera footage, microphone data.

[1383] Data processing / calculation: measuring input speed, analyzing facial expressions, analyzing voice tones.

[1384] Output: Measured and analyzed emotion data (keyboard speed, facial expression data, voice tone data).

[1385] Step 3: Sending data

[1386] (Device) compiles the collected text data and emotion data into a single dataset.

[1387] The device sends this dataset to the server using a secure communication protocol (e.g., HTTPS).

[1388] Input: Text data, emotion data.

[1389] Data processing / computation: Formation of data sets.

[1390] Output: The dataset that is sent to the server.

[1391] Step 4: Data analysis and natural language processing

[1392] The server inputs the received text data into a natural language processing engine, such as "SpaCy" or "BERT."

[1393] (Server) analyzes the text data and extracts important keywords (e.g., "telecommuting" and "supervisor's approval").

[1394] (Server) performs syntactic analysis of the sentence and understands its meaning.

[1395] Input: Text data.

[1396] Data processing / calculation: Keyword extraction and syntactic analysis using natural language processing.

[1397] Output: Analysis results (keywords, syntax information).

[1398] Step 5: Analyze the sentiment data

[1399] The (server) uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the received emotion data.

[1400] (Server) determines the user's current emotional state (e.g., stress, joy, frustration, etc.).

[1401] Input: Emotion data (keyboard speed, facial expression data, voice tone data).

[1402] Data processing / calculation: Emotion analysis using an emotion engine.

[1403] Output: Sentiment analysis results (user's emotional state).

[1404] Step 6: Legal check and correction proposal generation

[1405] (Server) combines the analysis results of the NLP engine (keywords, syntactic information) with the emotion analysis results (user's emotional state).

[1406] The server accesses its internal database of laws and regulations and searches for relevant laws and regulations, for example, "Article 4 of the Industrial Safety and Health Act."

[1407] The server checks whether the content of the regulations complies with the law and generates a revision proposal based on the results.

[1408] The system takes into account the results of sentiment analysis and tailors the suggestions to make them more acceptable to the user. For example, if the user is feeling stressed, the system makes the suggestions simpler and easier to understand.

[1409] Input: Analysis results (keywords, syntactic information), sentiment analysis results (user's emotional state).

[1410] Data processing / calculation: checking compliance with laws and regulations, generating correction suggestions.

[1411] Output: Fix suggestions.

[1412] Step 7: Present suggested revisions

[1413] The (server) sends the generated revision proposal to the (terminal).

[1414] The device displays suggested revisions to the user, reflecting emotional data and presenting them in a format that is easy for the user to understand. Suggestions may also be presented in stages.

[1415] Input: suggested fix.

[1416] Data processing / calculation: Proposals for corrections are presented to the user.

[1417] Output: Correction suggestions presented to the user.

[1418] Step 8: Approve or amend

[1419] The user checks the proposal and either approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[1420] The (terminal) sends the user's approval or modification to the server.

[1421] Input: User approval or correction.

[1422] Data processing / calculation: Approval or submission of corrections.

[1423] Output: The approval or correction sent to the server.

[1424] Step 9: Edit and save the final document

[1425] The (server) edits the final document based on the user's approval or modifications.

[1426] The server stores the final completed document in a database, along with its location and metadata.

[1427] Input: User approval or correction.

[1428] Data processing / calculation: Editing of final document.

[1429] Output: The final document stored in the database.

[1430] The above is the specific processing flow of the system's program. This process enables efficient creation and revision of regulations that comply with laws and regulations, and also enables intuitive operation that takes user feelings into consideration.

[1431] (Application example 2)

[1432] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1433] Creating and amending regulations manually takes a lot of time and effort, and verifying compliance with laws and regulations is cumbersome. There is also a need to reduce the stress and burden users feel when creating and amending regulations. Furthermore, there is a need for a system that allows workers to propose new work procedures and streamlines the process of amending regulations, proposing amendments in real time while ensuring legal compliance.

[1434] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input details of creating new rules or amending existing rules; means for receiving the data input by the user and analyzing the text using a natural language processing engine; means for searching for relevant laws and regulations based on the analysis results and confirming the document's compliance; means for generating proposed document amendments based on the results of the conformance check; means for sending the generated proposed amendments to the user and accepting user approval or additional amendments; means for editing and saving the final document based on the user's approval or additional amendments; means for accepting user voice and manual input; means for collecting and analyzing emotion data; and means for presenting proposed amendments in real time and confirming user approval. This enables the creation and amendment of rules to be performed quickly and reliably, facilitating compliance with laws and regulations, and enabling an intuitive and low-burden process for the user.

[1435] "User" means a person or organization that uses the system to create new rules or modify existing rules.

[1436] The "means for inputting" is a device or interface that allows a user to provide the content of new rules or amendments to existing rules as text to the system.

[1437] A "natural language processing engine" is software that analyzes text entered by a user and understands its meaning.

[1438] "Means for analyzing text" refers to the process of using a natural language processing engine to analyze the structure of text entered by a user and understand its meaning.

[1439] "Means for searching laws and regulations" is the process of searching a database for relevant laws and regulations and verifying whether the entered text complies with them.

[1440] "Means for verifying compliance" is a function that compares the searched laws and regulations with the input text and determines whether the text complies with the laws and regulations.

[1441] The "means for generating suggested corrections" is a process that, when text does not comply with the law, automatically generates suggested corrections to ensure compliance.

[1442] The "means for sending revision suggestions" is an interface for notifying the user of the generated revision suggestions and obtaining the user's approval.

[1443] A "means for accepting approval or further modifications" is an interface that supports the process by which a user can approve a proposed modification or make further modifications.

[1444] The "means for editing and saving the final document" is a process for creating a final document that reflects the user's approval and additional modifications, and saving it in a database.

[1445] "Means for accepting voice and manual input" refers to an interface that allows a user to create or modify rules by voice or keyboard input.

[1446] The "means for collecting and analyzing emotional data" is the process of collecting the user's emotional state and analyzing the input content based on that.

[1447] The "means for presenting revision suggestions in real time" is a function for instantly presenting generated revision suggestions to the user and receiving feedback in real time.

[1448] The present invention provides a system for efficiently managing the creation and modification of rules, and further enables more intuitive and effective rule management by recognizing and reflecting the user's emotions. Specific embodiments for implementing the present invention are described below.

[1449] The system uses smart glasses or tablets as a means for users to input new policies or modify existing policies, and has an interface that accepts voice and manual input, with user input transmitted to the system in real time.

[1450] The server receives the user's input data and analyzes the text using a natural language processing engine. Natural language processing includes sentence structure analysis, semantic understanding, and keyword extraction. For example, when the voice input system of the smart glasses recognizes "I would like to update the work procedure," the voice data is sent to the server, where the natural language processing engine analyzes it.

[1451] The server also has a means of collecting and analyzing emotional data. Using the camera in the smart glasses or the front-facing camera on the tablet, the system analyzes the user's facial expressions and vocal tone to identify their emotional state. The results of this emotional analysis are then reflected in the process of generating suggested revisions to the document.

[1452] Based on the analysis results, the server searches a database for relevant laws and regulations to verify whether the input text complies with them. This legal check includes, for example, the Industrial Safety and Health Act.

[1453] The proposed corrections are generated based on the results of the legal compliance check and sentiment analysis data. The suggestions are tailored to be easy to understand for the user. For example, if the user is feeling stressed, the suggestions will be made simple and easy to understand.

[1454] The generated correction suggestions are presented to the user in real time. The correction suggestions are displayed on the smart glasses display, and the user confirms the correction by replying "I accept" via voice input.

[1455] The final document is compiled by the server and stored in a database. This process makes creating and amending policies fast and efficient, and ensures compliance with regulations.

[1456] Specific examples

[1457] As a concrete example, we present a scenario in which a factory worker proposes a new work procedure.

[1458] 1. A factory worker uses voice input to propose a new work procedure: 'Handle parts safely and inspect equipment every Monday.'

[1459] 2. The camera in the smart glasses captures the worker's face and performs emotion analysis.

[1460] 3. The server receives the voice data and emotion data and performs text analysis and emotion analysis.

[1461] 4. Check compliance with the law and generate a correction proposal. The correction proposal is "Handle parts safely and inspect equipment every Monday in accordance with Article 4 of the Industrial Safety and Health Act."

[1462] 5. Correction suggestions are displayed in real time on the smart glasses.

[1463] 6. The worker responds by voice input, "I approve the proposal," and the correction is confirmed.

[1464] 7. The final document is edited and stored in the database.

[1465] Prompt Sentence Examples

[1466] (Voice input)

[1467] "Propose new work procedures: 'Handle parts safely and inspect equipment every Monday.'"

[1468] (Proposal from the system)

[1469] "Proposed amendment: 'Parts will be handled safely, and equipment will be inspected every Monday in accordance with Article 4 of the Industrial Safety and Health Act.'"

[1470] (Confirmation of workers)

[1471] "I accept the proposal."

[1472] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1473] Step 1:

[1474] Users can create new rules or modify existing rules by voice or manually. Input is done using smart glasses or a tablet device. For example, a worker can use smart glasses to input "I'm proposing a new work procedure. 'Parts will be handled safely and equipment will be inspected every Monday.'"

[1475] Input: User voice or text input

[1476] Output: Input audio or text data

[1477] Step 2:

[1478] The device converts the input voice data into text data. It then uses a voice recognition engine (e.g., the SpeechRecognition library) to analyze the voice data and generate text. This text data is then sent from the device to the server.

[1479] Input: Audio data

[1480] Output: Text data

[1481] Step 3:

[1482] The server sends the received text data to a natural language processing (NLP) engine for analysis. The NLP engine (for example, a model using the Transformers library) analyzes the sentence structure, understands its meaning, and extracts keywords. For example, keywords such as "work procedures," "parts handling," and "equipment inspection" are extracted.

[1483] Input: Text data

[1484] Output: Analysis results (sentence structure, meaning, keywords)

[1485] Step 4:

[1486] The device's camera is used to collect user emotion data. The camera captures facial expressions and uses an emotion analysis model (e.g., OpenCV or a specific emotion analysis library) to obtain analysis results. The user's emotional state (e.g., stress, joy, etc.) is identified.

[1487] Input: Video data (facial expression)

[1488] Output: Emotion analysis results

[1489] Step 5:

[1490] The server uses the results of NLP analysis and sentiment analysis to search a database for relevant laws and regulations and check the suitability of the entered text. For example, it searches for "Article 4 of the Industrial Safety and Health Act" and checks whether the regulations comply with the law.

[1491] Input: NLP analysis results, sentiment analysis results

[1492] Output: Compliance check results

[1493] Step 6:

[1494] The server generates correction suggestions based on the results of the legal compliance check and the emotion analysis. The suggestions are adjusted to be easy to understand, taking into account the user's emotional state. For example, a correction suggestion might be generated such as, "Handle parts safely, and in accordance with Article 4 of the Industrial Safety and Health Act, inspect equipment every Monday."

[1495] Input: Legal compliance check results, sentiment analysis results

[1496] Output: suggested fixes

[1497] Step 7:

[1498] The server sends the generated correction suggestions to the terminal and presents them to the user, who can then see the correction suggestions on the smart glasses display and accept or make additional corrections.

[1499] Input: Suggested correction

[1500] Output: Proposal for corrections presented to the user

[1501] Step 8:

[1502] The user checks the proposed corrections and approves them by voice or manually. For example, the user can say "I approve the proposal" through the smart glasses. The device accepts this input and sends it to the server.

[1503] Input: Voice or text input of user approval or further correction

[1504] Output: Approval or correction data

[1505] Step 9:

[1506] The server edits and saves the final document based on the user's approval or additional modifications. The edited final document is saved in a database and can be referenced and used when needed, ensuring compliance with regulations.

[1507] Input: Approval or correction data

[1508] Output: Final document saved in database

[1509] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1510] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1511] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1512] [Fourth embodiment]

[1513] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1514] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1515] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1516] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1517] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1518] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1519] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1520] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1521] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1522] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1523] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1524] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1525] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1526] ---

[1527] The present invention is a system for efficiently managing the creation and revision of regulations. This system analyzes regulation data entered by users and automatically generates revision suggestions to comply with relevant laws and regulations. The system can also edit and save the final regulation document.

[1528] Program processing

[1529] 1. Accepting user input

[1530] The user inputs the text of a new rule they want to create or an existing rule they want to modify from a terminal. For example, a user might input the text "Telecommuting, in principle, requires the approval of a supervisor" as the initial draft of a new "telecommuting rule."

[1531] 2. Server data reception and natural language processing

[1532] The terminal sends the user's input data to the server, which receives it. The server then uses a natural language processing engine to analyze the text. Specifically, it analyzes the sentence structure, extracts keywords, and understands the meaning. For example, it extracts keywords such as "telecommuting" and "supervisor's approval" and understands their meaning.

[1533] 3. Legal check

[1534] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches to see if Article 4 of the Industrial Safety and Health Act, which pertains to telecommuting, is a relevant law. This confirms whether the regulations document complies with that law.

[1535] 4. Correction proposal generation

[1536] Based on the results of the conformance check, the server generates a document revision proposal, such as "Telecommuting will be carried out with the approval of the supervisor, in principle. In addition, measures to ensure employee safety will be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1537] 5. Replying to the User

[1538] After the proposed revision is generated, the server sends it to the terminal and displays it to the user. The user reviews the proposed revision and, if necessary, approves it or makes additional revisions. For example, the user may type, "I approve the proposal."

[1539] 6. Edit and save

[1540] If the amendments are approved, the server edits the final document based on the user's approval or additional amendments. After the final policy document is completed, the server saves it in the database. For example, the completion is as follows: "The new 'Telework Policy' has been saved in the database."

[1541] Specific examples

[1542] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[1543] 1. Accepting user input

[1544] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[1545] 2. Server data reception and natural language processing

[1546] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[1547] 3. Legal check

[1548] Based on the analysis results, the server searches for "Article 4 of the Industrial Safety and Health Act" and checks it against related laws and regulations.

[1549] 4. Correction proposal generation

[1550] (Server) generates a revision proposal that reads, "In principle, teleworking will be carried out with the approval of a supervisor. In addition, measures will be taken to ensure the safety of employees in accordance with Article 4 of the Industrial Safety and Health Act."

[1551] 5. Replying to the User

[1552] The server sends the proposed revision to the terminal, which the user confirms. The user approves the proposal by typing "I approve the proposal."

[1553] 6. Edit and save

[1554] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[1555] The above is a specific embodiment of the present invention. This system allows efficient creation and revision of regulations, ensuring compliance with laws and regulations.

[1556] The processing flow will be explained below.

[1557] ---

[1558] Step 1:

[1559] The user inputs the text of the new rule they want to create or the text of the existing rule they want to modify from the terminal.

[1560] Step 2:

[1561] (Terminal) receives text data entered by the user.

[1562] Step 3:

[1563] (Terminal) sends the received text data to the server.

[1564] Step 4:

[1565] (Server) receives the text data sent from the terminal.

[1566] Step 5:

[1567] The server analyzes the received text using a natural language processing (NLP) engine, specifically analyzing sentence structure, extracting keywords, and understanding meaning.

[1568] Step 6:

[1569] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches for "laws related to telecommuting."

[1570] Step 7:

[1571] The server uses the legal information retrieved from the database to verify whether the text entered by the user complies with the legal information.

[1572] Step 8:

[1573] The server generates a correction proposal based on the results of the conformance check. For example, it generates a correction proposal such as, "Telecommuting must be performed with the approval of the supervisor, in principle. In addition, measures to ensure the safety of employees must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1574] Step 9:

[1575] The server sends the generated revision suggestions to the terminal.

[1576] Step 10:

[1577] (Terminal) receives the correction suggestions sent from the server and displays them to the user.

[1578] Step 11:

[1579] The user checks the displayed correction proposal and approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[1580] Step 12:

[1581] The (terminal) sends the user's approval or additional modification data to the server.

[1582] Step 13:

[1583] The (server) edits the final document based on the user's approval or additional modifications.

[1584] Step 14:

[1585] The (server) saves the final edited document in a database.

[1586] ---

[1587] This will streamline the process of creating and amending regulations and create a system that ensures compliance with laws and regulations.

[1588] Example 1

[1589] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1590] The creation and revision of existing regulations requires a lot of manual checking work, which means that verifying compliance with laws and regulations takes a very long time. Furthermore, creating proposed revisions after verifying compliance also requires a lot of work, which is inefficient. This can delay the entire process of creating and revising regulations and reduce the certainty of compliance with laws and regulations.

[1591] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1592] In this invention, the server includes: a means for a user to input details for creating new rules or amending existing rules; a means for receiving the data input by the user and analyzing the text using a natural language processing engine; a means for searching for relevant laws and regulations based on the analysis results and checking the conformance of the document; a means for generating proposed document amendments based on the conformance check results; a means for sending the generated proposed amendments to the user and accepting user approval or additional amendments; a means for editing and saving the final document based on the user approval or additional amendments; a means for the user to input via a terminal equipped with a rules creation form; a means for the server to identify grammatical elements using the natural language processing engine; a means for the server to extract keywords using the natural language processing engine; a means for the server to search a database for relevant laws and regulations; a means for the server to generate proposed amendments using a template engine; and a means for using a generative AI model to identify templates and amendments, thereby enabling automation of conformance checks and proposed amendments.

[1593] "User" refers to an individual or legal entity that uses the System to create new rules or amend existing rules.

[1594] "Terminal" refers to a device such as a computer, tablet, or smartphone that allows a user to enter input.

[1595] "Server" refers to a central control unit for receiving, analyzing, and processing data sent by users.

[1596] A "natural language processing engine" refers to a software tool or algorithm that analyzes text data entered by a user and understands its meaning.

[1597] "Structural analysis" refers to the process of identifying grammatical elements in input text data and analyzing the structure of sentences.

[1598] "Keyword extraction" refers to the process of extracting important words and phrases from input text data.

[1599] "Database" refers to a data management system for storing and retrieving information on relevant laws and regulations.

[1600] "Template engine" refers to a software tool for generating documents, such as revision suggestions, using templates.

[1601] "Generative AI model" refers to a machine learning model that uses artificial intelligence to generate natural language.

[1602] "Proposed amendments" refers to amendments generated by the server to bring the content of the regulations entered by the user into compliance with laws and regulations.

[1603] The present invention is a system for efficiently managing the creation and revision of regulations. This system analyzes regulation data entered by users and automatically generates revision suggestions to comply with relevant laws and regulations. The system also has the function of editing and saving the final regulation document.

[1604] Hardware and Software Configuration

[1605] 1. User input terminal

[1606] Hardware: Using devices such as computers, tablets, and smartphones.

[1607] Software: Use an internet browser or dedicated application software.

[1608] 2. Server

[1609] Hardware: Use a server with a powerful processor, sufficient memory, and plenty of storage.

[1610] software:

[1611] Use a natural language processing engine (e.g., Spacy or BERT).

[1612] Create a revision suggestion template using a template engine.

[1613] Use a generative AI model (e.g., GPT-4).

[1614] Use a database that stores information on laws and regulations (e.g., LawDataDB).

[1615] Natural language processing and legal checks

[1616] 1. Data Reception and Analysis

[1617] (Terminal) sends the new regulations and amendments entered by the user to the server.

[1618] The server analyzes the received data, performs sentence structure analysis, keyword extraction, and semantic understanding using a natural language processing engine (Spacy or BERT).

[1619] 2. Legal check

[1620] Based on the analysis results, the server searches the database (LawDataDB) for relevant laws and regulations. Based on this search, it checks whether the regulations comply with the laws and regulations.

[1621] Generate correction suggestions and reply to the user

[1622] 1. Generate correction suggestions

[1623] The server generates a correction proposal based on the results of the compatibility check. It creates a template for the correction proposal using a template engine, and generates specific proposal sentences using a generative AI model.

[1624] 2. Reply to the user

[1625] The (server) sends the generated revision suggestions to the (terminal) so that the (user) can review them.

[1626] (User) reviews the proposed revisions and approves or makes additional revisions as necessary.

[1627] Edit and save the final document

[1628] 1. Edit and save

[1629] The (server) edits the final document based on the user's approval or additional modifications.

[1630] The final edited document is stored in a database (e.g., RegulationDB).

[1631] Specific examples

[1632] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[1633] 1. Accepting user input

[1634] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[1635] 2. Server data reception and natural language processing

[1636] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[1637] 3. Legal check

[1638] Based on the analysis results, the server searches for "Article 4 of the Industrial Safety and Health Act" and checks it against related laws and regulations.

[1639] 4. Correction proposal generation

[1640] (Server) generates a revision proposal that reads, "In principle, teleworking will be carried out with the approval of a supervisor. In addition, measures will be taken to ensure the safety of employees in accordance with Article 4 of the Industrial Safety and Health Act."

[1641] 5. Replying to the User

[1642] The server sends the proposed revision to the terminal, which the user confirms. The user approves the proposal by typing "I approve the proposal."

[1643] 6. Edit and save

[1644] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[1645] This system will enable efficient creation and revision of regulations and ensure compliance with the law.

[1646] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1647] Step 1: Accepting user input

[1648] The user creates new rules or enters the details of amendments to existing rules into the terminal. For example, the user might enter, "I would like to create a new 'telecommuting rules'. The initial draft is as follows: 'Telecommuting must, in principle, be approved by a supervisor.'"

[1649] Input: User-created policy text

[1650] Output: The input text data

[1651] Step 2: Server receives data and processes natural language

[1652] The terminal sends the input text data to the server. The server receives this data and analyzes the text using a natural language processing engine. The server analyzes the sentence structure, extracts keywords, and understands the meaning.

[1653] Input: Text data sent by the user

[1654] Output: Parsed grammatical structure, extracted keywords, semantic understanding results

[1655] Specific behavior:

[1656] The server receives the HTTP request and retrieves the content as text data.

[1657] A natural language processing engine (e.g., Spacy or BERT) is used to perform grammatical analysis, keyword extraction, and semantic analysis.

[1658] Step 3: Legal check

[1659] Based on the analysis results, the server searches for relevant laws and regulations in a database (LawDataDB). The server creates a database query using keywords from the analysis results and retrieves the search results.

[1660] Input: Parsed text data, extracted keywords

[1661] Output: Relevant statutory and regulatory data

[1662] Specific behavior:

[1663] The server runs SQL queries against a database (LawDataDB) to retrieve relevant laws and regulations.

[1664] Check compliance with regulations based on search results.

[1665] Step 4: Generate correction suggestions

[1666] The server generates revision suggestions based on the results of the legal check. It uses a template engine to create a revision suggestion template, and uses a generative AI model to generate specific suggested sentences.

[1667] Input: Legal check results, analyzed text data

[1668] Output: Suggested corrections

[1669] Specific behavior:

[1670] The server uses a template engine to prepare a template for the proposed revision.

[1671] Use a generative AI model (e.g., GPT-4) to generate suggested revisions.

[1672] Step 5: Respond to the user

[1673] The server sends the generated revision proposal to the terminal for the user to review. The user reviews the revision proposal and approves it or makes additional revisions as necessary.

[1674] Input: Generated suggested correction text

[1675] Output: User approval or further modifications

[1676] Specific behavior:

[1677] The server sends the proposed revisions to the terminal as an HTTP response.

[1678] The user checks the proposal via the terminal and inputs approval or additional corrections.

[1679] Step 6: Edit and save

[1680] The server edits the final document based on the user's approval or additional modifications, and the edited final document is stored in the database (RegulationDB).

[1681] Input: User approval or additional modifications

[1682] Output: The final completed document

[1683] Specific behavior:

[1684] The server edits the final document to reflect the user's input.

[1685] The final edited document is saved in the database (RegulationDB).

[1686] (Application example 1)

[1687] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1688] The management and revision of regulations in factories is complicated, and there is a problem that they are not updated in a timely manner based on the latest laws. There is also a high risk of human error or failure to update regulations, which increases the risk of legal violations. There are concerns that this situation will have a negative impact on worker safety and factory operations.

[1689] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1690] In this invention, the server includes: means for a user to input details of creating new rules or amending existing rules; means for receiving the data input by the user and analyzing the text using a natural language processing engine; means for searching for relevant laws and regulations based on the analysis results and checking the document's compliance; means for generating document amendment suggestions based on the compliance check results; means for sending the generated amendment suggestions to the user and accepting user approval or additional amendments; means for editing and saving the final document based on the user approval or additional amendments; and means for automatically managing and amending factory rule data in accordance with laws and regulations to keep the rules up to date at all times. This improves the efficiency of factory rule management, ensures compliance with laws and regulations, and improves worker safety and the reliability of factory operations.

[1691] "User" means the person who creates or modifies a Policy.

[1692] "Input means" refers to an interface that allows a user to enter details of creating new rules or amending existing rules.

[1693] A "natural language processing engine" refers to software that analyzes text data entered by a user and performs sentence structure analysis, semantic understanding, and keyword extraction.

[1694] "Means for searching laws and regulations" refers to technology for searching relevant laws and regulations in a database and verifying the compliance of documents.

[1695] The "means for generating correction suggestions" refers to a technology for creating correction suggestions for a document based on the results of the conformance check.

[1696] "Means for sending to user" refers to an interface for notifying the user of generated revision suggestions and receiving feedback from the user.

[1697] "Means for editing and storing" refers to the technology for compiling the final document based on the user's approval or additional modifications and storing it in a database.

[1698] "Factory regulation data" refers to document data on regulations and guidelines necessary for factory operations.

[1699] "Means for automatically managing and correcting regulations and always maintaining the latest regulations" refers to technology that continuously updates and corrects regulation data in factories in response to changes in laws and regulations, and keeps it up to date.

[1700] This invention is a system that automatically manages and modifies factory regulation data in accordance with laws and regulations, and always keeps the regulations up to date.

[1701] The system includes a means for a user to input details for creating new regulations or amending existing regulations, a means for receiving the input data and analyzing the text using a natural language processing engine, a means for searching for relevant laws and regulations based on the analysis results and confirming the document's compliance, a means for generating suggested amendments to the document based on the results of the compliance confirmation, a means for sending the generated suggested amendments to the user and accepting the user's approval or additional amendments, and a means for editing and saving the final document based on the user's approval or additional amendments.

[1702] Hardware and software used

[1703] Hardware

[1704] Factory robots: Used for implementing and managing regulation data.

[1705] Server: Performs data analysis and stores results.

[1706] User terminal: An interface for entering regulations and reviewing and approving proposed amendments.

[1707] software

[1708] Python: A programming language used for the basic implementation of programs.

[1709] OpenAI API: Used for text analysis using generative AI models.

[1710] SpaCy: A natural language processing engine for text analysis.

[1711] FuzzyWuzzy: Used for similarity searches with laws and regulations.

[1712] Data processing and calculation

[1713] The server receives new regulations or amendments from the user's device. The received data is first subjected to text analysis using a natural language processing engine (SpaCy). Text analysis involves analyzing the structure of the sentence, understanding its meaning, and extracting keywords, thereby obtaining the necessary information. Next, related laws and regulations are searched for based on the analysis results. This search uses a database of laws and regulations and a similarity search algorithm (FuzzyWuzzy).

[1714] The server then checks compliance with laws and regulations and automatically generates proposed revisions if necessary. The proposed revisions are sent to the user's device for review and approval. If the user approves or makes revisions, the final regulations document is edited based on the proposal and saved in the database.

[1715] Specific example explanation

[1716] As a concrete example, if a user enters, "I would like to create a new 'Safety Regulations'. Here is the initial draft: 'Helmets shall be worn while working.'", the system will automatically search the relevant legal database (e.g., the Industrial Safety and Health Act) and generate a proposed amendment: "In accordance with Article 4 of the Industrial Safety and Health Act, wearing helmets is mandatory to ensure safety while working." The user can then review the proposal and approve or make additional amendments. The final regulations document is saved in the database after approval.

[1717] Prompt Sentence Examples

[1718] The following are examples of prompts that users may enter into the system:

[1719] We want to create a new "safety rule." Here's an initial draft: 'Helmets must be worn while working.'

[1720] In this way, the present invention streamlines the management and revision of regulations within factories, enabling regulations to be maintained in strict compliance with relevant laws and regulations, which is expected to ensure compliance with laws and regulations and significantly improve worker safety and the reliability of factory operations.

[1721] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1722] Step 1:

[1723] A user uses a terminal to input the details of a new rule or an existing rule to be modified. For example, the user might input, "I would like to create a new 'Safety Rule'. Here is the initial draft: 'Helmets must be worn while working.'" This input data becomes a prompt for the system.

[1724] Step 2:

[1725] The terminal transmits the input data to the server, specifically, the text data input by the user.

[1726] Step 3:

[1727] The server analyzes the received text data using a natural language processing engine (SpaCy). It performs sentence structure analysis, semantic understanding, and keyword extraction to identify the meaning of keywords and sentences. For example, the keywords "helmet" and "working" are extracted.

[1728] Step 4:

[1729] The server then refers to the database of laws and regulations based on the analysis results and searches for relevant laws and regulations. Specifically, it uses FuzzyWuzzy to search for relevant laws and regulations in the database based on the extracted keywords, and identifies "Article 4 of the Industrial Safety and Health Act" as the result.

[1730] Step 5:

[1731] The server checks the document's relevance based on the search results. Specifically, it determines whether the current regulations comply with the applicable laws and regulations. For example, it checks whether "wearing a helmet" complies with Article 4 of the Industrial Safety and Health Act.

[1732] Step 6:

[1733] As a result of the conformance check, if necessary, a correction suggestion is generated. For example, a correction suggestion such as "In accordance with Article 4 of the Industrial Safety and Health Act, wearing a helmet is required to ensure safety during work" is automatically generated.

[1734] Step 7:

[1735] The server sends the generated revision proposal to the terminal and notifies the user, who then confirms the revision proposal through the terminal.

[1736] Step 8:

[1737] The user checks the proposed correction and approves it or makes additional corrections, for example, by typing "I approve the proposal."

[1738] Step 9:

[1739] The server edits the final document based on the user's approval or additional modifications, specifically by incorporating the approved modifications into the original document.

[1740] Step 10:

[1741] The server saves the final edited document in the database. As a result, the latest regulation data is accumulated in the database. For example, a message is displayed saying, "The new 'Safety Regulations' have been saved in the database."

[1742] The above are the specific processing steps for carrying out the present invention. This system allows for efficient management and revision of factory regulations, ensuring compliance with laws and regulations.

[1743] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1744] ---

[1745] The present invention is a system for efficiently managing the creation and revision of regulations, and furthermore, it enables more intuitive and effective regulation management by recognizing and reflecting user emotions. This system analyzes regulation data entered by the user, automatically generates revision suggestions to comply with relevant laws and regulations, and can edit and save the final regulation document. Another feature is that it collects and analyzes user emotions as they are entered and adjusts the revision suggestions based on them.

[1746] Program processing

[1747] 1. Accepting user input

[1748] The user inputs the text of a new rule they want to create or an existing rule they want to modify from a terminal. For example, a user might input the text "Telecommuting, in principle, requires the approval of a supervisor" as the initial draft of a new "telecommuting rule."

[1749] 2. Collecting Emotional Data

[1750] The device collects emotional data as users type, including keyboard typing speed, facial expression recognition, and tone of voice.

[1751] 3. Server data reception and natural language processing

[1752] (Terminal) transmits input text data and emotion data from the user to the server.

[1753] The server analyzes the received text data using a natural language processing (NLP) engine to analyze sentence structure, extract keywords, and understand meaning.

[1754] 4. Analysis by Emotion Engine

[1755] The server analyzes the emotion data with an emotion engine to identify the user's current emotional state, for example, detecting if the user is feeling stressed.

[1756] 5. Legal check and correction suggestion generation

[1757] Based on the analysis results, the server searches the database for relevant laws and regulations and checks whether the text entered by the user complies with the laws and regulations.

[1758] The server generates a correction suggestion based on the results of the compatibility check, but also reflects the results of the emotion engine and adjusts it to make it more acceptable to the user. For example, if the user is feeling stressed, the suggestion will be made more concise and easy to understand.

[1759] 6. Replying to the User

[1760] After the revision suggestions are generated, the (server) sends them to the (terminal) and displays them to the (user).

[1761] The device also reflects the results of the emotion engine and presents suggestions in a format that is easy for the user to understand. For example, suggestions may be presented in stages to reduce stress.

[1762] 7. User Authorization or Modification

[1763] The user checks the displayed correction proposal and accepts it or makes additional corrections as necessary. For example, the user may type "I accept the proposal."

[1764] 8. Edit and save

[1765] If the modifications are approved, the server edits the final document based on the user's approval or additional modifications.

[1766] The (server) saves the final edited document in a database.

[1767] Specific examples

[1768] As a concrete example, the process for creating new "telecommuting regulations" is shown below.

[1769] 1. Accepting user input

[1770] (User) types into the terminal, "I would like to create a new 'Telecommuting Regulations'. Below is the initial draft: 'Telecommuting will, in principle, be carried out with the approval of a supervisor.'"

[1771] 2. Collecting Emotional Data

[1772] The device monitors the user's typing speed and facial expressions to collect emotional data. For example, if the user is typing quickly, they may be feeling stressed.

[1773] 3. Server data reception and natural language processing

[1774] The (terminal) sends this data to the (server), which receives it and begins analyzing it. The keywords "telecommuting" and "supervisor's approval" are extracted, and the meaning of the sentence is understood.

[1775] 4. Analysis by Emotion Engine

[1776] (Server) analyzes the emotion data and determines that the user is feeling stressed.

[1777] 5. Legal check and correction suggestion generation

[1778] (Server) searches for "Article 4 of the Industrial Safety and Health Act" based on the analysis results and checks it against related laws and regulations.

[1779] The results of the emotion engine are reflected in the generation of concise and easy-to-understand revision suggestions: "Teleworking must, in principle, be carried out with the approval of the supervisor. In addition, measures to ensure employee safety must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1780] 6. Replying to the User

[1781] The server sends the proposed corrections to the device, which the user confirms. The suggestions may be displayed in stages to make them easier for the user to understand.

[1782] 7. User Authorization or Modification

[1783] (User) approves by typing "I approve the proposal."

[1784] 8. Edit and save

[1785] The server reflects the user's approval, completes the final document, and saves it in the database. The process is completed with the message "The new 'Telecommuting Regulations' has been saved in the database."

[1786] The above is a specific embodiment of the present invention, which allows efficient policy creation and modification, ensures regulatory compliance, and provides a more intuitive and user-friendly process that takes into account the user's emotional state.

[1787] The processing flow will be explained below.

[1788] ---

[1789] Step 1:

[1790] The user inputs the text of the new rule they want to create or the existing rule they want to modify from the terminal. For example, they can input "Telecommuting must be performed with the approval of the supervisor as a general rule."

[1791] Step 2:

[1792] While the user types, the device collects emotional data such as keyboard typing speed, facial expression recognition, and tone of voice.

[1793] Step 3:

[1794] (Terminal) transmits the collected text data and emotion data to the server.

[1795] Step 4:

[1796] (Server) receives text data and emotion data sent from the terminal.

[1797] Step 5:

[1798] The server uses a natural language processing (NLP) engine to analyze the received text data, specifically analyzing the sentence structure, extracting keywords, and understanding the meaning.

[1799] Step 6:

[1800] The server uses an emotion engine to analyze the received emotion data and identify the user's emotional state, such as "feeling stressed."

[1801] Step 7:

[1802] Based on the analysis results, the server searches the database for relevant laws and regulations. For example, it searches for "laws regarding telecommuting."

[1803] Step 8:

[1804] The server uses the legal information retrieved from the database to verify whether the text entered by the user complies with the legal information.

[1805] Step 9:

[1806] The server generates a correction proposal based on the results of the conformance check. For example, it generates a correction proposal such as, "Telecommuting must be performed with the approval of the supervisor, in principle. In addition, measures to ensure the safety of employees must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1807] Step 10:

[1808] The server reflects the results of the emotion engine and adjusts the suggested corrections in an easy-to-understand manner that takes into account the user's emotional state. For example, if the user is feeling stressed, the suggested corrections will be concise and easy to understand.

[1809] Step 11:

[1810] The (server) sends the generated revision suggestions to the terminal and displays them to the (user).

[1811] Step 12:

[1812] The user checks the displayed correction proposal and accepts it or makes additional corrections as necessary. For example, the user enters "I accept the proposal."

[1813] Step 13:

[1814] The (terminal) sends the user's approval or additional modification data to the server.

[1815] Step 14:

[1816] The (server) edits the final document based on the user's approval or additional modifications.

[1817] Step 15:

[1818] The server saves the final edited document to the database. For example, the process is completed as follows: "The new 'Telecommuting Regulations' has been saved to the database."

[1819] ---

[1820] This will streamline the process of creating and amending regulations, ensuring compliance with laws and regulations. Furthermore, by taking into account the user's emotional state, the system will be more user-friendly and intuitive to use.

[1821] Example 2

[1822] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1823] In current policy management systems, when users create or modify policies, the process of checking compliance with laws and regulations is cumbersome, often resulting in a poor user experience. Furthermore, the system does not provide suggested modifications that reflect the user's feelings, often causing frustration for users. Therefore, there is a need for an efficient and user-friendly policy management system.

[1824] The identification process by the identification 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 means for a user to input details of creating new rules or amending existing rules; a means for collecting emotional data, including keyboard speed, facial expression recognition, and tone of voice, when the user inputs the rules; a means for receiving the user's input data and emotional data and analyzing the text using a natural language processing engine; a means for searching for relevant laws and regulations based on the analysis results and the emotional data and confirming the document's compliance; a means for generating document revision suggestions based on the compliance confirmation results and the emotional data; a means for sending the generated revision suggestions to the user and reflecting the emotional data to receive user approval or additional revisions; and a means for editing and saving the final document based on the user's approval or additional revisions. This realizes efficient and compliant rule creation and amendment, and also enables an intuitive and familiar process that takes the user's emotional state into consideration.

[1825] "User" means a person or entity that uses the System to create new rules or modify existing rules.

[1826] A "terminal" is a computer or digital device through which a user inputs regulatory data and collects emotional data.

[1827] "Emotional data" is data that indicates the user's emotional state, such as the user's keyboard speed, facial expression recognition, tone of voice, etc.

[1828] A "server" is a central computer system for analyzing received data and generating and sending correction suggestions.

[1829] A "natural language processing engine" is an algorithm or software that analyzes received text data and performs sentence structure analysis, semantic understanding, and keyword extraction.

[1830] A "legal database" is a database system that stores and makes searchable relevant laws and regulations.

[1831] A "revision proposal" is a proposed revision of a rule that is adjusted to comply with laws and regulations, and is a proposal that is generated taking into account the emotional state of the user.

[1832] "Final Document" means the completed version of the regulations document that has been edited based on the user's approval or additional modifications.

[1833] The present invention is a system for efficiently managing the creation and revision of regulations, and furthermore, it enables more intuitive and effective regulation management by recognizing and reflecting user emotions. This system analyzes regulation data entered by the user, automatically generates revision suggestions to comply with relevant laws and regulations, and can edit and save the final regulation document. Another feature is that it collects and analyzes user emotions as they are entered and adjusts the revision suggestions based on them.

[1834] Hardware and Software Configuration

[1835] User terminal: A device through which a user inputs input data and emotion data. This includes a general personal computer, tablet, smartphone, etc.

[1836] Emotion data collection module: Software that collects keyboard speed, facial expression recognition, and voice tone in real time on the device. For example, it uses standard typing speed monitoring software to measure keyboard speed, OpenCV for facial expression recognition, and libraries such as Praat for voice tone recognition.

[1837] Communication protocol: A secure communication protocol (e.g., HTTPS) is used to transmit data from the device to the server.

[1838] Server: A central computer system that analyzes data and generates correction suggestions. It contains the following modules:

[1839] Natural language processing engine: Software for analyzing user input text, such as SpaCy or BERT, to analyze sentence structure, understand meaning, and extract keywords.

[1840] Emotion engine: Software for analyzing user emotional data. For example, it uses the IBM Watson Tone Analyzer to identify the user's emotional state.

[1841] Legal database: A database system that stores data on relevant laws and regulations.

[1842] Correction proposal generation module: Software that uses the analysis results of the NLP engine and emotion engine to generate correction proposals in a form that is easy for users to accept.

[1843] Specific examples

[1844] Here is an example of creating a new "telecommuting policy."

[1845] Example prompt sentence:

[1846] I'd like to create a new "telecommuting policy." Here's the initial draft: 'Telecommuting must be approved by a supervisor.'

[1847] 1. User input:

[1848] The user uses a terminal to input an initial draft of the new "telecommuting regulations." For example, the user might input "telecommuting must be performed with the approval of a supervisor, in principle."

[1849] 2. Collecting Emotional Data:

[1850] The device measures the user's keyboard input speed as they type, and also uses a camera to analyze the user's facial expressions and a microphone to analyze the tone of their voice.

[1851] 3. Data transmission:

[1852] The device sends the collected text data and emotion data to the server using a secure communication protocol such as HTTPS.

[1853] 4. Data Analysis and Natural Language Processing:

[1854] The server uses a natural language processing engine to analyze the received text data and extract important keywords (e.g., "telecommuting" and "supervisor's approval"), while simultaneously analyzing the syntax of the text and understanding the meaning of the sentence.

[1855] 5. Emotional Data Analysis:

[1856] The server analyzes the emotional data using an emotion engine and identifies that the user is feeling stressed.

[1857] 6. Legal check and correction suggestion generation:

[1858] Based on the analysis results, the server searches for relevant laws and regulations (e.g., Article 4 of the Industrial Safety and Health Act) in a legal database and checks whether the regulations comply with the laws and regulations.

[1859] Taking emotion data into consideration, the system generates revision suggestions that are easy for users to accept. For example, it generates a revision suggestion such as, "Teleworking must, in principle, be carried out with the approval of a supervisor. In addition, measures to ensure employee safety must be taken in accordance with Article 4 of the Industrial Safety and Health Act."

[1860] 7. Submitting suggested revisions:

[1861] The server sends the generated revision suggestions to the user's device and presents them to the user. They may be presented in stages based on the results of the emotion engine.

[1862] 8. Approval or Amendment:

[1863] The user checks the proposal and either approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[1864] 9. Edit and save the final document:

[1865] The server edits the final document to reflect the user's approval and saves it to the database. Once the save is complete, a notification is sent stating, "The new 'Telecommuting Rules' has been saved to the database."

[1866] The system streamlines policy creation and modification, ensures regulatory compliance, and provides a more intuitive and friendly process that takes into account the user's emotional state.

[1867] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1868] Step 1: Accepting user input

[1869] The user opens a dedicated application (for example, a web browser or dedicated software) on the device and accesses the screen for creating or modifying regulations.

[1870] The user enters the text of the regulations they want to create or modify into the input form. For example, they might enter "Telecommuting must be approved by a supervisor as a general rule."

[1871] Input: The policy text entered by the user.

[1872] Data processing / calculation: None.

[1873] Output: The input text is passed to the next process as is.

[1874] Step 2: Collecting emotion data

[1875] (Terminal) measures the user's input speed (keyboard typing speed) and records it as a log.

[1876] The device uses the user's camera image to recognize facial expressions and analyze changes in facial expression. This is done using a facial recognition library (e.g., OpenCV).

[1877] The device captures the microphone data and analyzes the tone and pitch of the voice, for example using a voice analysis library (e.g., Praat).

[1878] Input: User keyboard typing speed, camera footage, microphone data.

[1879] Data processing / calculation: measuring input speed, analyzing facial expressions, analyzing voice tones.

[1880] Output: Measured and analyzed emotion data (keyboard speed, facial expression data, voice tone data).

[1881] Step 3: Sending data

[1882] (Device) compiles the collected text data and emotion data into a single dataset.

[1883] The device sends this dataset to the server using a secure communication protocol (e.g., HTTPS).

[1884] Input: Text data, emotion data.

[1885] Data processing / computation: Formation of data sets.

[1886] Output: The dataset that is sent to the server.

[1887] Step 4: Data analysis and natural language processing

[1888] The server inputs the received text data into a natural language processing engine, such as "SpaCy" or "BERT."

[1889] (Server) analyzes the text data and extracts important keywords (e.g., "telecommuting" and "supervisor's approval").

[1890] (Server) performs syntactic analysis of the sentence and understands its meaning.

[1891] Input: Text data.

[1892] Data processing / calculation: Keyword extraction and syntactic analysis using natural language processing.

[1893] Output: Analysis results (keywords, syntax information).

[1894] Step 5: Analyze the sentiment data

[1895] The (server) uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the received emotion data.

[1896] (Server) determines the user's current emotional state (e.g., stress, joy, frustration, etc.).

[1897] Input: Emotion data (keyboard speed, facial expression data, voice tone data).

[1898] Data processing / calculation: Emotion analysis using an emotion engine.

[1899] Output: Sentiment analysis results (user's emotional state).

[1900] Step 6: Legal check and correction proposal generation

[1901] (Server) combines the analysis results of the NLP engine (keywords, syntactic information) with the emotion analysis results (user's emotional state).

[1902] The server accesses its internal database of laws and regulations and searches for relevant laws and regulations, for example, "Article 4 of the Industrial Safety and Health Act."

[1903] The server checks whether the content of the regulations complies with the law and generates a revision proposal based on the results.

[1904] The system takes into account the results of sentiment analysis and tailors the suggestions to make them more acceptable to the user. For example, if the user is feeling stressed, the system makes the suggestions simpler and easier to understand.

[1905] Input: Analysis results (keywords, syntactic information), sentiment analysis results (user's emotional state).

[1906] Data processing / calculation: checking compliance with laws and regulations, generating correction suggestions.

[1907] Output: Fix suggestions.

[1908] Step 7: Present suggested revisions

[1909] The (server) sends the generated revision proposal to the (terminal).

[1910] The device displays suggested revisions to the user, reflecting emotional data and presenting them in a format that is easy for the user to understand. Suggestions may also be presented in stages.

[1911] Input: suggested fix.

[1912] Data processing / calculation: Proposals for corrections are presented to the user.

[1913] Output: Correction suggestions presented to the user.

[1914] Step 8: Approve or amend

[1915] The user checks the proposal and either approves it or makes additional corrections. For example, the user enters "I approve the proposal."

[1916] The (terminal) sends the user's approval or modification to the server.

[1917] Input: User approval or correction.

[1918] Data processing / calculation: Approval or submission of corrections.

[1919] Output: The approval or correction sent to the server.

[1920] Step 9: Edit and save the final document

[1921] The (server) edits the final document based on the user's approval or modifications.

[1922] The server stores the final completed document in a database, along with its location and metadata.

[1923] Input: User approval or correction.

[1924] Data processing / calculation: Editing of final document.

[1925] Output: The final document stored in the database.

[1926] The above is the specific processing flow of the system's program. This process enables efficient creation and revision of regulations that comply with laws and regulations, and also enables intuitive operation that takes user feelings into consideration.

[1927] (Application example 2)

[1928] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1929] Creating and amending regulations manually takes a lot of time and effort, and verifying compliance with laws and regulations is cumbersome. There is also a need to reduce the stress and burden users feel when creating and amending regulations. Furthermore, there is a need for a system that allows workers to propose new work procedures and streamlines the process of amending regulations, proposing amendments in real time while ensuring legal compliance.

[1930] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input details of creating new rules or amending existing rules; means for receiving the data input by the user and analyzing the text using a natural language processing engine; means for searching for relevant laws and regulations based on the analysis results and confirming the document's compliance; means for generating proposed document amendments based on the results of the conformance check; means for sending the generated proposed amendments to the user and accepting user approval or additional amendments; means for editing and saving the final document based on the user's approval or additional amendments; means for accepting user voice and manual input; means for collecting and analyzing emotion data; and means for presenting proposed amendments in real time and confirming user approval. This enables the creation and amendment of rules to be performed quickly and reliably, facilitating compliance with laws and regulations, and enabling an intuitive and low-burden process for the user.

[1931] "User" means a person or organization that uses the system to create new rules or modify existing rules.

[1932] The "means for inputting" is a device or interface that allows a user to provide the content of new rules or amendments to existing rules as text to the system.

[1933] A "natural language processing engine" is software that analyzes text entered by a user and understands its meaning.

[1934] "Means for analyzing text" refers to the process of using a natural language processing engine to analyze the structure of text entered by a user and understand its meaning.

[1935] "Means for searching laws and regulations" is the process of searching a database for relevant laws and regulations and verifying whether the entered text complies with them.

[1936] "Means for verifying compliance" is a function that compares the searched laws and regulations with the input text and determines whether the text complies with the laws and regulations.

[1937] The "means for generating suggested corrections" is a process that, when text does not comply with the law, automatically generates suggested corrections to ensure compliance.

[1938] The "means for sending revision suggestions" is an interface for notifying the user of the generated revision suggestions and obtaining the user's approval.

[1939] A "means for accepting approval or further modifications" is an interface that supports the process by which a user can approve a proposed modification or make further modifications.

[1940] The "means for editing and saving the final document" is a process for creating a final document that reflects the user's approval and additional modifications, and saving it in a database.

[1941] "Means for accepting voice and manual input" refers to an interface that allows a user to create or modify rules by voice or keyboard input.

[1942] The "means for collecting and analyzing emotional data" is the process of collecting the user's emotional state and analyzing the input content based on that.

[1943] The "means for presenting revision suggestions in real time" is a function for instantly presenting generated revision suggestions to the user and receiving feedback in real time.

[1944] The present invention provides a system for efficiently managing the creation and modification of rules, and further enables more intuitive and effective rule management by recognizing and reflecting the user's emotions. Specific embodiments for implementing the present invention are described below.

[1945] The system uses smart glasses or tablets as a means for users to input new policies or modify existing policies, and has an interface that accepts voice and manual input, with user input transmitted to the system in real time.

[1946] The server receives the user's input data and analyzes the text using a natural language processing engine. Natural language processing includes sentence structure analysis, semantic understanding, and keyword extraction. For example, when the voice input system of the smart glasses recognizes "I would like to update the work procedure," the voice data is sent to the server, where the natural language processing engine analyzes it.

[1947] The server also has a means of collecting and analyzing emotional data. Using the camera in the smart glasses or the front-facing camera on the tablet, the system analyzes the user's facial expressions and vocal tone to identify their emotional state. The results of this emotional analysis are then reflected in the process of generating suggested revisions to the document.

[1948] Based on the analysis results, the server searches a database for relevant laws and regulations to verify whether the input text complies with them. This legal check includes, for example, the Industrial Safety and Health Act.

[1949] The proposed corrections are generated based on the results of the legal compliance check and sentiment analysis data. The suggestions are tailored to be easy to understand for the user. For example, if the user is feeling stressed, the suggestions will be made simple and easy to understand.

[1950] The generated correction suggestions are presented to the user in real time. The correction suggestions are displayed on the smart glasses display, and the user confirms the correction by replying "I accept" via voice input.

[1951] The final document is compiled by the server and stored in a database. This process makes creating and amending policies fast and efficient, and ensures compliance with regulations.

[1952] Specific examples

[1953] As a concrete example, we present a scenario in which a factory worker proposes a new work procedure.

[1954] 1. A factory worker uses voice input to propose a new work procedure: 'Handle parts safely and inspect equipment every Monday.'

[1955] 2. The camera in the smart glasses captures the worker's face and performs emotion analysis.

[1956] 3. The server receives the voice data and emotion data and performs text analysis and emotion analysis.

[1957] 4. Check compliance with the law and generate a correction proposal. The correction proposal is "Handle parts safely and inspect equipment every Monday in accordance with Article 4 of the Industrial Safety and Health Act."

[1958] 5. Correction suggestions are displayed in real time on the smart glasses.

[1959] 6. The worker responds by voice input, "I approve the proposal," and the correction is confirmed.

[1960] 7. The final document is edited and stored in the database.

[1961] Prompt Sentence Examples

[1962] (Voice input)

[1963] "Propose new work procedures: 'Handle parts safely and inspect equipment every Monday.'"

[1964] (Proposal from the system)

[1965] "Proposed amendment: 'Parts will be handled safely, and equipment will be inspected every Monday in accordance with Article 4 of the Industrial Safety and Health Act.'"

[1966] (Confirmation of workers)

[1967] "I accept the proposal."

[1968] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1969] Step 1:

[1970] Users can create new rules or modify existing rules by voice or manually. Input is done using smart glasses or a tablet device. For example, a worker can use smart glasses to input "I'm proposing a new work procedure. 'Parts will be handled safely and equipment will be inspected every Monday.'"

[1971] Input: User voice or text input

[1972] Output: Input audio or text data

[1973] Step 2:

[1974] The device converts the input voice data into text data. It then uses a voice recognition engine (e.g., the SpeechRecognition library) to analyze the voice data and generate text. This text data is then sent from the device to the server.

[1975] Input: Audio data

[1976] Output: Text data

[1977] Step 3:

[1978] The server sends the received text data to a natural language processing (NLP) engine for analysis. The NLP engine (for example, a model using the Transformers library) analyzes the sentence structure, understands its meaning, and extracts keywords. For example, keywords such as "work procedures," "parts handling," and "equipment inspection" are extracted.

[1979] Input: Text data

[1980] Output: Analysis results (sentence structure, meaning, keywords)

[1981] Step 4:

[1982] The device's camera is used to collect user emotion data. The camera captures facial expressions and uses an emotion analysis model (e.g., OpenCV or a specific emotion analysis library) to obtain analysis results. The user's emotional state (e.g., stress, joy, etc.) is identified.

[1983] Input: Video data (facial expression)

[1984] Output: Emotion analysis results

[1985] Step 5:

[1986] The server uses the results of NLP analysis and sentiment analysis to search a database for relevant laws and regulations and check the suitability of the entered text. For example, it searches for "Article 4 of the Industrial Safety and Health Act" and checks whether the regulations comply with the law.

[1987] Input: NLP analysis results, sentiment analysis results

[1988] Output: Compliance check results

[1989] Step 6:

[1990] The server generates correction suggestions based on the results of the legal compliance check and the emotion analysis. The suggestions are adjusted to be easy to understand, taking into account the user's emotional state. For example, a correction suggestion might be generated such as, "Handle parts safely, and in accordance with Article 4 of the Industrial Safety and Health Act, inspect equipment every Monday."

[1991] Input: Legal compliance check results, sentiment analysis results

[1992] Output: suggested fixes

[1993] Step 7:

[1994] The server sends the generated correction suggestions to the terminal and presents them to the user, who can then see the correction suggestions on the smart glasses display and accept or make additional corrections.

[1995] Input: Suggested correction

[1996] Output: Proposal for corrections presented to the user

[1997] Step 8:

[1998] The user checks the proposed corrections and approves them by voice or manually. For example, the user can say "I approve the proposal" through the smart glasses. The device accepts this input and sends it to the server.

[1999] Input: Voice or text input of user approval or further correction

[2000] Output: Approval or correction data

[2001] Step 9:

[2002] The server edits and saves the final document based on the user's approval or additional modifications. The edited final document is saved in a database and can be referenced and used when needed, ensuring compliance with regulations.

[2003] Input: Approval or correction data

[2004] Output: Final document saved in database

[2005] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2006] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2007] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2008] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2009] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2010] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2011] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2012] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2013] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2014] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2015] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2016] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2017] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2018] 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.

[2019] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2020] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2021] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2022] As an example of a system configured with a single processor, first, one processor is conf...

Claims

1. A means for a user to input new rules or modifications to existing rules; means for receiving the user-entered data and analyzing the text using a natural language processing engine; A means for searching for relevant laws and regulations based on the analysis results and verifying the conformity of the document; means for generating suggested modifications to the document based on the results of the conformance check; means for transmitting the generated revision suggestions to a user and accepting approval or further revisions from the user; means for editing and saving the final document based on said user's approval or further modifications; A system including:

2. 2. The system according to claim 1, wherein the natural language processing engine performs sentence structure analysis, semantic understanding, and keyword extraction.

3. 2. The system according to claim 1, further comprising a database for searching said laws and regulations and a means for referencing said database.

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