System

Abstract

A system is provided.SOLUTION: This system is provided with terminals for inputting information, a server for receiving information inputted from the terminals, and for transmitting it to a generation AI, a means for extracting examination items and points of concern from the result analyzed by the generation AI, and for generating an examination sheet, and a means for providing the generated examination sheet to the terminals and a department in charge of examination.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] When developing a new service, conducting a speedy and accurate review while taking into account laws, internal regulations, and past review results is extremely labor-intensive, placing a heavy burden on the relevant departments. Furthermore, the current manual review process lacks comprehensiveness and accuracy, and is unable to keep up with the modern business environment, where speed of release is required. Furthermore, it is difficult to effectively utilize data from similar past cases, so there is a need to improve the accuracy of the review. [Means for solving the problem]

[0005] The present invention solves the above problem by providing a system that includes a terminal for inputting information, a server that receives the data input from the terminal and transmits it to a generation AI, a means for extracting review items and concerns from the results of the analysis by the generation AI and generating a review sheet, and a means for providing the generated review sheet to the terminal and the review department.

[0006] Specifically, the generative AI analyzes input data based on previously learned laws, company regulations, and past review results, and extracts review items and points of concern. It also has a means of receiving feedback from the review department and updating the review sheet based on that feedback, realizing a fast and accurate review process, improving work efficiency and review accuracy.

[0007] "Information" refers to data about the details of the new service, its purpose, target customers, features offered, and relevant laws and regulations.

[0008] A "terminal" is an input device, such as a computer or mobile device, used to input information.

[0009] "Data" refers to content including information about new services sent from the terminal.

[0010] The "server" is a computer system that processes data received from the terminal and sends it to the generation AI.

[0011] "Generative AI" is an artificial intelligence system that learns laws and regulations, company regulations, and past review results in advance, and analyzes input data to extract review items and concerns.

[0012] "Review items" are specific checkpoints that indicate the standards and requirements that a new service must meet.

[0013] "Concerns" are matters that indicate potential problems or deficiencies identified during the review of a new service.

[0014] The "review sheet" is a document containing review items and concerns, created based on the results of analysis by the generation AI.

[0015] The "review department" is an organization that includes the department and staff responsible for reviewing new services.

[0016] "Feedback" refers to the response, such as additional information or correction instructions, provided by the review department based on the review sheet. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] This invention relates to a system and its program for efficiently and accurately reviewing new service development, taking into consideration laws and regulations, company regulations, and past review results. This system includes a terminal for inputting information, a server for receiving the input data and sending it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, and a means for providing the generated review sheet to the terminal and the review department.

[0039] Program processing explanation

[0040] The program of this system operates as follows.

[0041] A. User Input Processing

[0042] The user enters information about the new service into the terminal, specifically, the name of the new service, its purpose, target customers, the functions it provides, and data about related laws and regulations through a form.

[0043] Example: A user enters information about an "online education platform." For example, the name could be "online education platform," the purpose could be "to improve learning outcomes for junior high school students," and the functions provided could be "video lessons, learning material downloads, and ranking tests."

[0044] B. Data Transmission

[0045] The terminal sends the information entered by the user to the server. The data is sent in JSON format or similar, and the server receives it.

[0046] C. Analysis and Extraction

[0047] The server sends the received data to the generation AI, which analyzes the input data based on laws and regulations, company regulations, and past review results that it has previously studied, and extracts review items and points of concern.

[0048] Example: The server sends data from an "online education platform" to a generation AI, which then extracts review items such as "personal information protection measures" and "copyright confirmation."

[0049] D. Generating and providing review sheets

[0050] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[0051] Example: The server creates an inspection sheet that includes personal information protection measures, copyright confirmation, and the legality of the educational content, and shares it with the user and the legal department.

[0052] E. Feedback and Response to Review Results

[0053] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on the feedback and update the review sheet. The updated review sheet will be sent back to the server for review.

[0054] Example: The legal department points out that "safety measures for personal information protection have not been confirmed," and the user takes action in accordance with the guidelines and resubmits the sheet.

[0055] Specific processing flow

[0056] In the system of the present invention, the examination is carried out through the following specific processing flow.

[0057] 1. The user enters new service information from the terminal.

[0058] 2. The device sends the entered information to the server.

[0059] 3. The server sends the received information to the generation AI for analysis.

[0060] 4. The generation AI returns the analysis results to the server.

[0061] 5. The server generates the review sheet and provides it to the terminal and the review department.

[0062] 6. The review department provides feedback and the user responds.

[0063] As described above, the system of the present invention can improve the efficiency and accuracy of the examination of new services.

[0064] The processing flow will be explained below.

[0065] Step 1:

[0066] The user opens the information input form for the new service on their device. In the form, they enter the name of the new service, its purpose, target customers, the functions it will provide, and any relevant laws and regulations. After completing the input, they click the send button to send the information to the server.

[0067] Step 2:

[0068] The terminal converts the data entered by the user into JSON format, and then makes an API request to the server and sends the data to the server.

[0069] Step 3:

[0070] The server receives the JSON data sent from the device. After receiving it, the server analyzes the data and stores it in an internal database. After storing it, the server prepares to send the data to the generation AI.

[0071] Step 4:

[0072] The server sends the saved data to the AI's API, which then begins analyzing the data.

[0073] Step 5:

[0074] The AI ​​analyzes the submitted data based on previously learned laws, company regulations, and past review results, and extracts review items and points of concern as a result of the analysis.

[0075] Step 6:

[0076] The server receives the analysis results returned by the generation AI. It generates an evaluation sheet based on the received analysis results. The evaluation sheet lists the extracted evaluation items and concerns.

[0077] Step 7:

[0078] The server then initiates a procedure to provide the generated review sheet to the user's terminal and the review department, specifically by attaching it to an email or via a specialized web interface.

[0079] Step 8:

[0080] The user receives and checks the review sheet provided via the terminal. The sheet is also provided to the review department, and each department begins their review.

[0081] Step 9:

[0082] The review department checks the details of the new service based on the review sheet and provides feedback on any necessary corrections or additional information, which is then sent to the user and the server.

[0083] Step 10:

[0084] The user receives the feedback and takes any necessary action, after which the user re-enters the corrected information into the system and submits it to the server.

[0085] Step 11:

[0086] The server then sends the corrected information received again to the generation AI, which reanalyzes it as necessary, and updates the review sheet based on the analysis results.

[0087] Step 12:

[0088] The server again provides the updated review sheet to the user and the review department for final confirmation and approval.

[0089] This is the detailed process flow of the new service examination assistance system. This step makes it possible to speed up examinations and improve their accuracy.

[0090] Example 1

[0091] 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."

[0092] Conventionally, when developing a new service, a review is conducted taking into account laws and regulations, internal company rules, and past review results. However, this process is laborious and time-consuming, and has problems with inefficiency and inaccuracy. In addition, specialized knowledge is required to accurately identify review items and concerns, placing a heavy burden on human resources. There was a need for a system that could solve these issues and review new services efficiently and accurately.

[0093] 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.

[0094] In this invention, the server includes a device for inputting information, a means for receiving data input from the device and sending it to the generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating review documents, a means for providing the generated review documents to the device and the review department, and a means for receiving opinions from the evaluation department and updating the review documents based on the opinions. This makes it possible to streamline the review process for new services and increase accuracy.

[0095] The "device for inputting information" is a device used by the user to input information about the new service.

[0096] A "server that receives data and sends it to the generation AI" is a computer system that has the function of receiving data sent from an information input device and sending that data to the generation AI.

[0097] "Generative AI" is an artificial intelligence that analyzes data based on pre-trained laws, regulations, and past evaluation results, and extracts review items and points of concern.

[0098] "Review items" are the criteria and checkpoints necessary to evaluate and confirm new services.

[0099] "Concerns" are issues that could pose problems or risks with the new service.

[0100] A "review document" is a document containing review items and concerns created based on the results of analysis by the generation AI.

[0101] The "review department" is a department that receives the generated review documents and provides evaluation and feedback.

[0102] "Opinions from the evaluation department" refers to feedback on corrections and additional information provided by the evaluation department to the evaluation document.

[0103] "Means for updating review documents" refers to means that have the function of amending and updating review documents based on feedback from the evaluation department.

[0104] The present invention relates to a system and its program for efficiently and accurately reviewing new service development, taking into consideration laws and regulations, company regulations, and past review results. The system includes a device for inputting information, a server that receives the input data and sends it to a generative AI model, a means for extracting review items and concerns based on the results of the generative AI's analysis and generating review documents, and a means for providing the generated review documents to the device and the review department.

[0105] The user inputs information about the new service into the device. In this process, the user uses a form to enter detailed data about the new service's name, purpose, target customers, functions to be provided, and relevant laws and regulations. For example, the user might enter the name "online education platform," the purpose as "improving learning effectiveness for junior high school students," and the functions to be provided as "video lessons, learning material downloads, and ranking tests."

[0106] The device sends the information entered by the user to the server. At this time, the data is sent in a structured data format such as JSON, and the server receives this data. For example, the device sends the following data to the server in JSON format: "New service name: Online education platform, Purpose: Improving learning effectiveness for junior high school students, Functions provided: Video lessons, learning material downloads, Rank test."

[0107] The server sends the received data to a generative AI model. The generative AI model analyzes the input data based on previously learned laws, regulations, and past evaluation results, and extracts review items and concerns. For example, if the server sends the received data to the generative AI model as "New service: online education platform, purpose: improving learning effectiveness for junior high school students, provided functions: video lessons, learning material downloads, rank tests," the generative AI model will return important review items such as "personal information protection measures" and "copyright confirmation" as analysis results.

[0108] Sample prompt: Analyze the concerns regarding privacy and copyright for a new online education platform.

[0109] The server creates an inspection document based on the inspection items and concerns obtained from the generative AI model. This inspection document is provided to the user's device and the inspection department. For example, the server creates an inspection document based on the analysis results, including "personal information protection measures," "copyright confirmation," and "legality of educational content," and generates it in PDF format or similar and provides it to the user and the inspection department via email or the system's notification function.

[0110] The review department conducts a detailed review based on the review documents provided. During this process, any necessary corrections or additional information is identified. For example, the legal department may provide feedback pointing out that "the explanation regarding personal information protection measures is insufficient." The user takes the necessary action based on the feedback and updates the review document to reflect the corrections and additional information. The updated review document is then sent back to the server for re-review.

[0111] As described above, the system of the present invention can improve the efficiency and accuracy of the review process for new services.

[0112] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0113] Program processing explanation

[0114] Step 1: Process User Input

[0115] The user inputs information about the new service into the device. Specifically, the user enters detailed data about the new service's name, purpose, target customers, provided functions, and relevant laws and regulations through a form. The input data is saved in the device and prepared for the next step.

[0116] Input: New service name, purpose, target customers, provided functions, relevant laws and regulations

[0117] Output: New service information entered in the form

[0118] Specific operation: The user enters the name "online education platform" into the form on the device, enters "improving learning effectiveness for junior high school students" as the purpose, and enters "video lessons, learning material downloads, rank tests" as the functions to be provided.

[0119] Step 2: Send data

[0120] The device sends the information entered by the user to the server. In this process, the data is sent in a structured data format such as JSON, and the server receives it.

[0121] Input: New service information entered in the form

[0122] Output: JSON formatted data sent to the server

[0123] Specific operation: The device sends the following data in JSON format to the server: "New service name: Online education platform, Purpose: Improving learning effectiveness for junior high school students, Functions provided: Video lessons, downloading teaching materials, Rank test."

[0124] Step 3: Parsing and Extraction

[0125] The server sends the received data to a generative AI model, which analyzes the input data based on previously learned laws, regulations, and past evaluation results, and extracts review items and concerns. This clarifies the criteria and risks required for the review.

[0126] Input: JSON format data received by the server

[0127] Output: The assessment items and concerns returned by the generative AI model

[0128] Specific operation: The server sends the received data to the generation AI model as "New service: online education platform, purpose: improving learning effectiveness for junior high school students, provided functions: video lessons, learning material downloads, rank tests." The generation AI model then returns important review items such as "personal information protection measures" and "copyright confirmation" as analysis results.

[0129] Step 4: Generate and provide review documentation

[0130] The server creates an inspection document based on the inspection items and concerns obtained from the generative AI model, and provides the generated inspection document to the user's device and inspection department.

[0131] Input: Analysis results of the generative AI model (evaluation items and concerns)

[0132] Output: Generated audit document

[0133] Specific operation: Based on the analysis results, the server generates a review document in PDF format, including information on "personal information protection measures," "copyright confirmation," and "legality of educational content," and provides it to the user and review department. For example, the review document is sent via email or the system's notification function.

[0134] Step 5: Feedback and response to review results

[0135] The review department conducts a detailed review based on the provided review documents. During this process, they check for any necessary corrections or additional information and provide feedback. The user receives the feedback, takes the necessary action, and updates the review document to reflect the corrections and additional information. The updated review document is sent back to the server for re-review.

[0136] Input: Review documents provided, feedback from the review department

[0137] Output: Revised and updated audit document

[0138] Specific operation: The legal department reports that the explanation of personal information protection measures is insufficient. The user adds details about the specific protection measures according to the guidelines, updates the review document on the terminal again, and sends it to the server. The server then analyzes and reviews it again.

[0139] Through the above processing steps, the system of the present invention can improve the efficiency and accuracy of the review process for new services.

[0140] (Application example 1)

[0141] 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."

[0142] Currently, when introducing new robots or adding new functions to a factory, it is necessary to comply with numerous laws and company regulations, and the review process is often time-consuming and labor-intensive. Furthermore, there is no system in place to accurately identify review items and concerns and address them efficiently. As a result, the introduction process is delayed, resulting in problems such as reduced productivity.

[0143] 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.

[0144] In this invention, the server includes means for extracting inspection items and concerns based on new information and settings of factory robots and generating an inspection sheet, means for analyzing input data and extracting inspection items and concerns based on laws, regulations, and past inspection results that the generation AI has previously learned, and means for receiving feedback from the inspection department and updating the inspection sheet based on the feedback.This enables quick and accurate inspections that comply with laws, regulations, and rules when introducing new robots or adding functions to factories.

[0145] "Information input terminal" refers to a device that allows users to input information about new services or robots. Generally, this includes computers, tablets, smartphones, etc.

[0146] A "server" is a computer system on a network that receives input data and sends it to the generating AI.

[0147] "Generative AI" is an artificial intelligence that analyzes input data based on pre-trained data and extracts review items and points of concern.

[0148] "Inspection items" are specific checkpoints or requirements that must be verified when introducing a new service or robot or adding new features.

[0149] "Concerns" refer to the risks and problems associated with introducing new services and robots.

[0150] The "review sheet" is a document that organizes the review items and concerns extracted by the generation AI and provides them to the review department.

[0151] The "review department" is a department within the company that reviews applications based on the provided review sheets and provides necessary feedback.

[0152] "Feedback" refers to opinions and information that the review department provides based on the review sheet and requests corrections.

[0153] The system for realizing the present invention mainly includes the following hardware and software:

[0154] Hardware used: high-performance cloud servers, desktop terminals for users to input information, tablets, and smartphones

[0155] Software used: API server built with Flask, pre-trained natural language processing model (GPT-4)

[0156] The operation of the system is as follows.

[0157] First, users input new information and settings for their factory robots, including the robot's name, function, intended location, and applicable regulations, via a desktop, tablet, or smartphone.

[0158] The device then sends the information entered by the user to the server, with the data being sent in a standard format such as JSON.

[0159] The server sends the received data to the generation AI for analysis. The generation AI model analyzes the input data based on previously learned laws and regulations, company regulations, and past inspection results, and extracts inspection items and points of concern.

[0160] Based on the analysis results of the generative AI model, the server generates an evaluation sheet, which details the extracted evaluation items and concerns. The generated evaluation sheet is provided to the user's device and the device of the evaluation department.

[0161] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The review department's feedback will be communicated to the user via the server.

[0162] The user receives the feedback, takes necessary action based on the content, and updates the evaluation sheet. The updated evaluation sheet is then sent back to the server and reanalyzed by the generative AI model.

[0163] Specific examples

[0164] For example, consider the case where a factory employee installing a new high-precision welding robot enters the following information:

[0165] Robot name: New welding robot

[0166] Function:High precision welding

[0167] Planned installation location: 2nd Factory

[0168] Related laws and regulations: Labor safety regulations, environmental protection laws

[0169] Based on the submitted information, the generative AI model extracts review items related to occupational safety regulations and environmental protection laws (e.g., measures to ensure worker safety and regulations on the emission of hazardous substances) and generates a review sheet.

[0170] Example prompts for generative AI models

[0171] Analyze information to qualify new factory robots.

[0172] Robot name: "New welding robot"

[0173] Function: "High precision welding"

[0174] Planned installation location: "Second Factory"

[0175] Related laws and regulations: "Occupational Safety Regulations" and "Environmental Protection Act"

[0176] Extract the review items and concerns and generate a review sheet.

[0177] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0178] Step 1:

[0179] Users input information, such as the name of the new robot, its functions, the planned location for its deployment, and relevant laws and regulations, using a desktop, tablet, or smartphone.

[0180] Input: New robot information (name, function, planned installation location, relevant laws and regulations)

[0181] Output: Input data (e.g., JSON format)

[0182] Step 2:

[0183] The terminal sends the entered data to the server, where it is sent using a secure protocol (e.g., HTTPS).

[0184] Input: Data entered by the user

[0185] Output: Data sent to the server

[0186] Step 3:

[0187] The server sends the received data to a generative AI model, which has been pre-trained with laws, regulations, company rules, and past review results.

[0188] Input: Data sent from the terminal

[0189] Output: Data sent to the generative AI model

[0190] Step 4:

[0191] A generative AI model analyzes input data and extracts review items and concerns, using natural language processing techniques to identify checkpoints that comply with laws, regulations, etc.

[0192] Input: Data sent from the server

[0193] Output: Analysis results (review items and concerns)

[0194] Step 5:

[0195] The server generates an evaluation sheet based on the analysis results from the AI ​​model, which details the extracted evaluation items and concerns.

[0196] Input: Analysis results from a generative AI model

[0197] Output: Review sheet

[0198] Step 6:

[0199] The server provides the generated review sheet to the user's terminal and the terminal of the review department. The review sheet is often provided in PDF or HTML format.

[0200] Input: Generated review sheet

[0201] Output: Terminal and review sheet provided to the review department

[0202] Step 7:

[0203] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information.

[0204] Input: Review sheet

[0205] Output: Feedback

[0206] Step 8:

[0207] The user receives the feedback, takes necessary action based on the content, and updates the evaluation sheet. The updated evaluation sheet is then sent back to the server.

[0208] Input: Feedback from the review department

[0209] Output: Updated review sheet

[0210] Step 9:

[0211] The server sends the updated review sheet back to the generative AI model for re-analysis, and if necessary, repeats the process.

[0212] Input: Updated review sheet

[0213] Output: Reparsed review sheet

[0214] 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.

[0215] The present invention relates to a system and program for efficiently and accurately reviewing new service development, taking into account laws and regulations, company regulations, and past review results, while recognizing user emotions and providing further interactive feedback. This system includes a terminal for inputting information, a server that receives the input data and sends it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, and an emotion engine that recognizes user emotions.

[0216] Program processing explanation

[0217] The program of this system operates as follows.

[0218] A. User Input Processing

[0219] The user enters information about the new service into the terminal. Specifically, the user enters the name of the new service, its purpose, target customers, the functions it will provide, and any related laws and regulations through a form. The emotion engine then obtains emotion data from the user's input and actions.

[0220] Example: A user inputs information about an "online education platform." For example, the name may be "online education platform," the purpose may be "to improve learning outcomes for junior high school students," and the functions provided may be "video lessons, learning material downloads, and rank tests." The emotion engine analyzes the user's input speed and keystroke patterns to estimate the user's emotions (e.g., excitement, impatience).

[0221] B. Data Transmission and Emotion Transmission

[0222] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[0223] C. Analysis and Extraction

[0224] The server receives the data sent from the device. It then sends the received new service information and emotion data to the generation AI. The generation AI analyzes the input data based on previously learned laws and regulations, company regulations, past review results, and emotion data, and extracts review items and concerns.

[0225] Example: The server sends data from an "online education platform" and user emotional data to a generation AI, which then extracts concerns about "personal information protection measures" and "copyright confirmation," as well as "excessive expectations for specific functions" if the user is excited.

[0226] D. Generating and providing review sheets

[0227] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[0228] Example: The server creates an evaluation sheet that includes personal information protection measures, copyright confirmation, legality of the training content, and "excessive expectations for specific functions," and shares it with the user and the legal department.

[0229] E. Feedback and Response to Review Results

[0230] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on the feedback, update the review sheet, and submit it again to the server to complete the review process.

[0231] Example: The legal department makes specific suggestions about "failure to confirm safety measures for personal information protection," and the user takes action based on those suggestions. After that, the updated information is re-entered into the system and the review sheet is updated.

[0232] Specific processing flow

[0233] The addition of an emotion engine to the system of the present invention enables interactive feedback that takes into account the user's emotions, thereby speeding up and improving the accuracy of the review process, and thereby realizing a more user-friendly review process.

[0234] As described above, the system of the present invention not only improves the efficiency and accuracy of the review of new services, but also recognizes the user's emotions, making it possible to provide more appropriate feedback.

[0235] The processing flow will be explained below.

[0236] Step 1:

[0237] The user opens the information input form for the new service on their device. In the form, they enter the name of the new service, its purpose, target customers, the functions it provides, and any relevant laws and regulations. After completing the input, they click the send button to send the information to the server.

[0238] Example: A user enters information about an "online education platform." For example, the name may be "online education platform," the purpose may be "to improve learning effectiveness for junior high school students," and the functions provided may be "video lessons, learning material downloads, and ranking tests." Furthermore, while the user is entering information, the emotion engine obtains emotion data from the input speed and keystrokes.

[0239] Step 2:

[0240] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[0241] Example: The device converts information about the "online education platform" and the user's emotional data into JSON format and sends it to the server.

[0242] Step 3:

[0243] The server receives the JSON data sent from the device. After receiving the data, the server analyzes it and stores it in its internal database. After storing it, the server prepares to send the data and emotion data to the generation AI.

[0244] Example: The server stores the information and emotional data of the "online education platform" received from the device in a database.

[0245] Step 4:

[0246] The server sends the saved data and emotion data to the generation AI's API, which then begins analyzing the input data.

[0247] Example: The server sends information and emotional data from the "online education platform" to the generation AI, which then begins analysis.

[0248] Step 5:

[0249] The AI ​​analyzes the submitted data based on pre-trained laws, company regulations, past review results, and emotional data, and extracts review items and points of concern as a result of the analysis.

[0250] Example: Generative AI analyzes information on an "online education platform" and, in addition to "personal information protection measures" and "copyright confirmation," extracts "excessive expectations for certain features" as concerns if the user is excited.

[0251] Step 6:

[0252] The server receives the analysis results returned by the generation AI. It generates an evaluation sheet based on the received analysis results. The evaluation sheet lists the extracted evaluation items and concerns.

[0253] Example: The server creates a review sheet that includes personal information protection measures, copyright confirmation, and "excessive expectations for specific features."

[0254] Step 7:

[0255] The server then initiates a procedure to provide the generated review sheet to the user's terminal and the review department, specifically by attaching it to an email or via a specialized web interface.

[0256] Example: The server sends the review sheet to the user and the review department by email.

[0257] Step 8:

[0258] The user receives and checks the review sheet provided via the terminal. The sheet is also provided to the review department, and each department begins their review.

[0259] Example: The user reviews the provided review sheet, and the legal department also receives the same sheet and reviews it.

[0260] Step 9:

[0261] The review department checks the details of the new service based on the review sheet and provides feedback on any necessary corrections or additional information, which is then sent to the user and the server.

[0262] Example: The legal department points out that "safety measures for personal information protection have not been confirmed" and sends this information to the user and server as feedback.

[0263] Step 10:

[0264] The user receives the feedback and takes any necessary action, after which the user re-enters the corrected information into the system and submits it to the server.

[0265] Example: The user takes the necessary action based on the legal department's feedback, re-enters the corrected information into the system, and submits it to the server.

[0266] Step 11:

[0267] The server then sends the corrected information and emotion data it has received back to the AI, and reanalyzes it as necessary. The review sheet is updated based on the analysis results.

[0268] Example: The server sends the corrected information and newly acquired emotion data to the generation AI, which then reanalyzes and updates the review sheet.

[0269] Step 12:

[0270] The server again provides the updated review sheet to the user and the review department for final confirmation and approval.

[0271] Example: The server sends the updated review sheet again to the user and the review department for final confirmation.

[0272] The above is a detailed processing flow of the new service review assistance system that combines an emotion engine. This step not only speeds up and improves the accuracy of the review, but also enables interactive feedback that takes the user's emotions into consideration.

[0273] Example 2

[0274] 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."

[0275] The review system for the previous new service took into account laws, company regulations, and past review results, but did not provide feedback that took user emotions into account, making the review process unfriendly and making it difficult to conduct a fast and accurate review.In addition, the lack of an interactive review process that reflected user emotions made improving user satisfaction a challenge.

[0276] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0277] In this invention, the server includes means for extracting review items and concerns from the results of the analysis by the generation AI, including the user's emotional data acquired by the emotion engine, and generating a review sheet, means for providing the generated review sheet to the terminal and the review department, and means for receiving feedback from the review department and updating the review sheet based on the feedback, thereby enabling a fast and accurate review that takes into account the user's emotional data.

[0278] The "terminal for inputting information" refers to a device such as a computer or smartphone that a user uses to input information about a new service.

[0279] The "server" is a high-performance computer system that transmits data received from the terminal to the generation AI and receives the analysis results from the generation AI.

[0280] "Generative AI" is an artificial intelligence model that analyzes laws and regulations, internal regulations, past judgment results, and emotional data that it has previously studied, and extracts review items and points of concern.

[0281] The "emotion engine" is a software module that analyzes user input and operation data in real time and generates user emotion data.

[0282] "Review items" are the elements and criteria that the generating AI analyzes the input data and determines to be essential for review.

[0283] "Concerns" are issues that the generating AI has identified from its analysis results that could pose problems or risks during the review process.

[0284] The "review sheet" is a document that summarizes the review items and concerns extracted by the generation AI and is used to review new services.

[0285] "Feedback" refers to a response such as corrections or additional information provided to the user after the review department makes a judgment based on the review sheet.

[0286] "Rules" is a general term for laws, regulations, and internal company rules and guidelines.

[0287] "Internal regulations" refer to rules and policies that must be followed within an organization.

[0288] "Past judgment results" refers to data and records relating to the results of past inspections.

[0289] "Emotion data" is data relating to the user's emotional state analyzed by the emotion engine.

[0290] This invention is a system that not only considers laws and regulations, company regulations, and past review results when developing new services, but also performs efficient and accurate reviews and provides interactive feedback by recognizing the user's emotions. This system includes a terminal for inputting information, a server that receives the input data and sends it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, and an emotion engine that recognizes the user's emotions.

[0291] Hardware and software used

[0292] Device: A computer or smartphone is used by users to enter information, such as the name of the new service, its purpose, target customers, the functions it provides, and relevant laws and regulations, through a web form.

[0293] Server: A high-performance server receives data, communicates with the AI, and generates the evaluation sheet. The server can use web server software such as Apache or NGINX.

[0294] Generative AI: An artificial intelligence model that performs analysis based on pre-trained data. For example, analysis is performed using a large-scale language model such as GPT-4.

[0295] Emotion engine: A software module that analyzes a user's emotions in real time. Specifically, it is emotion recognition software that analyzes input speed, keystroke patterns, etc.

[0296] Program processing overview

[0297] The program of this system operates as follows.

[0298] User Input Processing

[0299] The user inputs information about the new service into the device. This input includes the name of the new service, its purpose, target customers, the functions it provides, and information about related laws and regulations. The emotion engine then analyzes the user's input and operation data in real time to generate emotion data.

[0300] Data transmission and emotion transmission

[0301] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[0302] Parsing and Extraction

[0303] The server receives the data sent from the device. It then sends the received new service information and emotion data to the generation AI. The generation AI analyzes the input data based on previously learned laws and regulations, company regulations, past review results, and emotion data, and extracts review items and concerns.

[0304] Generation and provision of review sheets

[0305] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[0306] Feedback and Updates

[0307] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will receive the feedback, take the necessary action, update the review sheet, and send it back to the server.

[0308] Specific processing examples

[0309] A user inputs information about an "online education platform." For example, the name is "online education platform," the purpose is "to improve learning effectiveness for junior high school students," and the functions provided are "video lessons, learning material downloads, and rank tests." The emotion engine analyzes the user's input speed and keystroke patterns to estimate emotions such as "excitement" and "expectation."

[0310] The server receives new service information and emotion data sent from the device and sends it to the generation AI, which then extracts review items such as "personal information protection" and "copyright confirmation" and identifies "excessive expectations for specific functions" as a concern.

[0311] The server then creates an assessment sheet based on the assessment items and concerns, and provides it to the user's device and the assessment department. The legal department reviews the assessment sheet and provides specific feedback to the user, such as "personal information protection measures not confirmed." The user then takes action based on this feedback, re-enters the updated information into the system, and updates the assessment sheet.

[0312] Prompt Sentence Examples

[0313] "We'd like you to review a new online education platform. Its name is 'Online Education Platform,' its purpose is 'to improve learning outcomes for junior high school students,' and its functions are 'video lessons, learning material downloads, and rank tests.' Please identify review items and concerns based on laws and regulations, company regulations, past review results, and user sentiment."

[0314] As a result, the system of the present invention not only makes the screening of new services more efficient and improves accuracy, but also recognizes the user's emotions, allowing it to provide more appropriate feedback.

[0315] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0316] Step 1:

[0317] The user inputs information about the new service into the terminal.

[0318] The input includes the name of the new service, its purpose, target customers, the functions it provides, and information on relevant laws and regulations. The emotion engine analyzes this input and operation data in real time to generate user emotion data.

[0319] Input: New service information (name, purpose, target customers, provided functions, relevant laws and regulations)

[0320] Data processing: The emotion engine analyzes input speed and keystroke patterns to generate emotion data.

[0321] Output: Input new service information, user emotion data (e.g., excitement, anticipation)

[0322] Step 2:

[0323] The terminal converts the data entered by the user into JSON format.

[0324] The converted data includes information about the new service and emotion data, and is sent to the server.

[0325] Input: New service information and emotion data entered by the user

[0326] Data processing: Convert new service information and emotion data into JSON format

[0327] Output: JSON format data

[0328] Step 3:

[0329] The server receives the JSON data sent from the terminal.

[0330] The received data is sent to the generation AI, which analyzes the input data and extracts review items and concerns based on previously studied laws and regulations, company regulations, past review results, and emotional data.

[0331] Input: New service information and emotion data in JSON format sent from the device

[0332] Data processing: Generative AI analyzes JSON data and extracts review items and concerns

[0333] Output: Extracted review items and concerns

[0334] Step 4:

[0335] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI.

[0336] The generated review sheet is provided to the user's terminal and the review department.

[0337] Input: Review items and concerns obtained from the generative AI

[0338] Data processing: Create an evaluation sheet by combining the evaluation items and concerns.

[0339] Output: Review sheet

[0340] Step 5:

[0341] The review department will conduct the review based on the review sheet provided.

[0342] Generate feedback and notify the user with any necessary corrections or additional information.

[0343] Input: Provided review sheet

[0344] Data processing: Check the review contents and make corrections or add additional information

[0345] Output: Feedback

[0346] Step 6:

[0347] The user makes corrections based on the feedback received.

[0348] The corrected information is re-entered into the system and the updated review sheet is sent to the server.

[0349] Input: Feedback

[0350] Data processing: Modify new service information based on feedback

[0351] Output: Revised new service information

[0352] Step 7:

[0353] The server receives the retransmitted data and retransmits it to the generating AI.

[0354] The generating AI will reanalyze and update if any new review items or concerns arise.

[0355] Input: Revised new service information

[0356] Data processing: Generative AI reanalyzes data and updates the review items and concerns.

[0357] Output: Updated review criteria and concerns

[0358] This results in a user-friendly, efficient and accurate review process.

[0359] (Application example 2)

[0360] 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."

[0361] Introducing or modifying new production lines or work processes in factories requires compliance with laws, regulations, and company rules, and therefore screening is essential. However, conventional screening systems rely on the judgment of personnel, which can be inefficient and time-consuming. Furthermore, because they do not take user feelings into consideration, feedback can be inappropriate. This can delay the implementation process and have a negative impact on production efficiency and safety. Therefore, there is a need for a system that improves the efficiency and accuracy of screening, as well as the user experience.

[0362] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0363] In this invention, the server includes a terminal for inputting information, a means for receiving data input from the terminal and sending it to the generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, an emotion engine for recognizing the user's emotions, and a means for generating interactive feedback taking the user's emotion data into consideration. This not only improves the efficiency and accuracy of the review, but also makes it possible to provide appropriate feedback that takes the user's emotions into consideration.

[0364] The "information input terminal" is a device that allows a user to input information about a new production line or work process.

[0365] "Generative AI" is an artificial intelligence system that analyzes input data based on previously learned laws and regulations, company regulations, and past review results, and extracts review items and points of concern.

[0366] A "server" is a computer system that receives data entered from a terminal and sends it to the generation AI.

[0367] The "means of generating an evaluation sheet" refers to the process of compiling evaluation items and concerns from the results of the analysis by the generation AI and creating a final evaluation sheet.

[0368] The "review department" is a department that reviews the application based on the generated review sheet and provides necessary corrections and additional information as feedback.

[0369] An "emotion engine" is a system that recognizes emotions from user input and operation data and acquires emotion data.

[0370] The "means for generating interactive feedback" is a process that takes into account the user's emotional data and generates and provides appropriate feedback.

[0371] The present invention provides a system for efficiently and accurately reviewing the introduction or modification of new production lines or work processes in factories. The system includes a terminal for inputting information, a server that receives the data input from the terminal and sends it to a generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating a review sheet, and a means for providing the generated review sheet to the terminal and the review department. The system also includes an emotion engine that recognizes user emotions and a means for generating interactive feedback taking into account the user's emotion data.

[0372] Program processing explanation

[0373] The user uses a terminal to input information related to a new production line or work process. This terminal can be a desktop computer, tablet, or smartphone. The input information is sent to a server. Upon receiving this data, the server sends it to a generative AI model. The generative AI model analyzes the input data based on previously learned laws and regulations, company regulations, and past review results, and extracts review items and concerns. Furthermore, an emotion engine recognizes emotions from the user's input and operation data, and acquires emotional data.

[0374] Based on the analysis results of the generation AI, the server generates an evaluation sheet. The generated evaluation sheet is sent back to the terminal and provided to the evaluation department. The terminal receives feedback from the evaluation department, sends it to the server, and updates the evaluation sheet.

[0375] As a concrete example, consider the case where a user is installing a new production line. The user inputs information about the "new assembly line" into the terminal. Specifically, the information entered includes the name "new assembly line," the purpose "improving production efficiency," the functions provided "automated machinery, quality inspection system," and related laws and regulations "Occupational Safety and Health Act, Product Liability Act." At this stage, the emotion engine obtains emotion data from the user's input speed, keystroke patterns, and facial expressions, and sends it to the server.

[0376] The generative AI model analyzes this data and extracts review items such as "personal information protection measures" and "safety management confirmation." If the user is feeling impatient, "preventing mistakes due to excessive pressure" may also be cited as a concern. This generates a review sheet that is provided to the user's device and the review department. If feedback is received from the review department, the review sheet is updated based on that feedback. This process improves the efficiency and accuracy of reviews, and also contributes to an improved user experience.

[0377] Prompt Sentence Examples

[0378] - "Please enter information about the new assembly line."

[0379] - "Objective: Improve production efficiency"

[0380] -"Provided functions: automated machinery, quality inspection systems"

[0381] - "Related laws and regulations: Occupational Safety and Health Act, Product Liability Act"

[0382] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0383] Step 1:

[0384] The user enters information

[0385] The user uses the device to input information related to the new production line and work process. Specific input data includes the name, purpose, provided functions, relevant laws and regulations, etc. The input data is stored on the device and prepared for later transmission to the server. The emotion engine also analyzes the user's input speed and keystroke patterns to obtain the user's emotional data.

[0386] Input: Information related to the new production line and work process

[0387] Output: Input data and emotion data

[0388] Step 2:

[0389] The device sends data to the server

[0390] The device converts the data entered by the user and the acquired emotion data into JSON format and sends it to the server. This conversion process is important for maintaining data consistency.

[0391] Input: Input data and emotion data

[0392] Output: JSON format data

[0393] Step 3:

[0394] The server sends the data to the generation AI

[0395] The server sends the JSON-formatted data received from the device to the generative AI model, which then analyzes the data based on previously learned laws, regulations, company rules, and past review results.

[0396] Input: JSON format data

[0397] Output: Analysis request by the generated AI

[0398] Step 4:

[0399] Generative AI analyzes data

[0400] The generative AI model analyzes the received data and extracts review items and concerns, while also taking into account the user's emotional data to identify additional emotion-based concerns and warnings.

[0401] Input: Analysis request by the generated AI

[0402] Output: List of review items and concerns

[0403] Step 5:

[0404] The server generates the review sheet

[0405] The server generates an evaluation sheet based on the list of evaluation items and concerns obtained from the generation AI. The evaluation sheet includes individual evaluation items and their corresponding concerns.

[0406] Input: List of review items and concerns

[0407] Output: Review sheet

[0408] Step 6:

[0409] The server provides the review sheet to the terminal and the review department.

[0410] The server provides the generated review sheet to the user's terminal and the review department, which allows both the user and the reviewer to check the review sheet.

[0411] Input: Review sheet

[0412] Output: Provided to the user's terminal and the review department

[0413] Step 7:

[0414] Receive and respond to feedback from the review department

[0415] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on this feedback and re-enter the updated information into the system.

[0416] Input: Feedback on the review sheet

[0417] Output: Updated information

[0418] Step 8:

[0419] The server updates the review sheet again and provides

[0420] The server updates the review sheet again based on the updated information and provides it again to the user and the review department, thereby completing the review process.

[0421] Input: Updated information

[0422] Output: Updated review sheet

[0423] Through these steps, the introduction and modification of new production lines and work processes in factories can be reviewed efficiently and accurately.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] [Second embodiment]

[0428] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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).

[0434] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0439] 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."

[0440] This invention relates to a system and its program for efficiently and accurately reviewing new service development, taking into consideration laws and regulations, company regulations, and past review results. This system includes a terminal for inputting information, a server for receiving the input data and sending it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, and a means for providing the generated review sheet to the terminal and the review department.

[0441] Program processing explanation

[0442] The program of this system operates as follows.

[0443] A. User Input Processing

[0444] The user enters information about the new service into the terminal, specifically, the name of the new service, its purpose, target customers, the functions it provides, and data about related laws and regulations through a form.

[0445] Example: A user enters information about an "online education platform." For example, the name could be "online education platform," the purpose could be "to improve learning outcomes for junior high school students," and the functions provided could be "video lessons, learning material downloads, and ranking tests."

[0446] B. Data Transmission

[0447] The terminal sends the information entered by the user to the server. The data is sent in JSON format or similar, and the server receives it.

[0448] C. Analysis and Extraction

[0449] The server sends the received data to the generation AI, which analyzes the input data based on laws and regulations, company regulations, and past review results that it has previously studied, and extracts review items and points of concern.

[0450] Example: The server sends data from an "online education platform" to a generation AI, which then extracts review items such as "personal information protection measures" and "copyright confirmation."

[0451] D. Generating and providing review sheets

[0452] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[0453] Example: The server creates an inspection sheet that includes personal information protection measures, copyright confirmation, and the legality of the educational content, and shares it with the user and the legal department.

[0454] E. Feedback and Response to Review Results

[0455] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on the feedback and update the review sheet. The updated review sheet will be sent back to the server for review.

[0456] Example: The legal department points out that "safety measures for personal information protection have not been confirmed," and the user takes action in accordance with the guidelines and resubmits the sheet.

[0457] Specific processing flow

[0458] In the system of the present invention, the examination is carried out through the following specific processing flow.

[0459] 1. The user enters new service information from the terminal.

[0460] 2. The device sends the entered information to the server.

[0461] 3. The server sends the received information to the generation AI for analysis.

[0462] 4. The generation AI returns the analysis results to the server.

[0463] 5. The server generates the review sheet and provides it to the terminal and the review department.

[0464] 6. The review department provides feedback and the user responds.

[0465] As described above, the system of the present invention can improve the efficiency and accuracy of the examination of new services.

[0466] The processing flow will be explained below.

[0467] Step 1:

[0468] The user opens the information input form for the new service on their device. In the form, they enter the name of the new service, its purpose, target customers, the functions it will provide, and any relevant laws and regulations. After completing the input, they click the send button to send the information to the server.

[0469] Step 2:

[0470] The terminal converts the data entered by the user into JSON format, and then makes an API request to the server and sends the data to the server.

[0471] Step 3:

[0472] The server receives the JSON data sent from the device. After receiving it, the server analyzes the data and stores it in an internal database. After storing it, the server prepares to send the data to the generation AI.

[0473] Step 4:

[0474] The server sends the saved data to the AI's API, which then begins analyzing the data.

[0475] Step 5:

[0476] The AI ​​analyzes the submitted data based on previously learned laws, company regulations, and past review results, and extracts review items and points of concern as a result of the analysis.

[0477] Step 6:

[0478] The server receives the analysis results returned by the generation AI. It generates an evaluation sheet based on the received analysis results. The evaluation sheet lists the extracted evaluation items and concerns.

[0479] Step 7:

[0480] The server then initiates a procedure to provide the generated review sheet to the user's terminal and the review department, specifically by attaching it to an email or via a specialized web interface.

[0481] Step 8:

[0482] The user receives and checks the review sheet provided via the terminal. The sheet is also provided to the review department, and each department begins their review.

[0483] Step 9:

[0484] The review department checks the details of the new service based on the review sheet and provides feedback on any necessary corrections or additional information, which is then sent to the user and the server.

[0485] Step 10:

[0486] The user receives the feedback and takes any necessary action, after which the user re-enters the corrected information into the system and submits it to the server.

[0487] Step 11:

[0488] The server then sends the corrected information received again to the generation AI, which reanalyzes it as necessary, and updates the review sheet based on the analysis results.

[0489] Step 12:

[0490] The server again provides the updated review sheet to the user and the review department for final confirmation and approval.

[0491] This is the detailed process flow of the new service examination assistance system. This step makes it possible to speed up examinations and improve their accuracy.

[0492] Example 1

[0493] 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."

[0494] Conventionally, when developing a new service, a review is conducted taking into account laws and regulations, internal company rules, and past review results. However, this process is laborious and time-consuming, and has problems with inefficiency and inaccuracy. In addition, specialized knowledge is required to accurately identify review items and concerns, placing a heavy burden on human resources. There was a need for a system that could solve these issues and review new services efficiently and accurately.

[0495] 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.

[0496] In this invention, the server includes a device for inputting information, a means for receiving data input from the device and sending it to the generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating review documents, a means for providing the generated review documents to the device and the review department, and a means for receiving opinions from the evaluation department and updating the review documents based on the opinions. This makes it possible to streamline the review process for new services and increase accuracy.

[0497] The "device for inputting information" is a device used by the user to input information about the new service.

[0498] A "server that receives data and sends it to the generation AI" is a computer system that has the function of receiving data sent from an information input device and sending that data to the generation AI.

[0499] "Generative AI" is an artificial intelligence that analyzes data based on pre-trained laws, regulations, and past evaluation results, and extracts review items and points of concern.

[0500] "Review items" are the criteria and checkpoints necessary to evaluate and confirm new services.

[0501] "Concerns" are issues that could pose problems or risks with the new service.

[0502] A "review document" is a document containing review items and concerns created based on the results of analysis by the generation AI.

[0503] The "review department" is a department that receives the generated review documents and provides evaluation and feedback.

[0504] "Opinions from the evaluation department" refers to feedback on corrections and additional information provided by the evaluation department to the evaluation document.

[0505] "Means for updating review documents" refers to means that have the function of amending and updating review documents based on feedback from the evaluation department.

[0506] The present invention relates to a system and its program for efficiently and accurately reviewing new service development, taking into consideration laws and regulations, company regulations, and past review results. The system includes a device for inputting information, a server that receives the input data and sends it to a generative AI model, a means for extracting review items and concerns based on the results of the generative AI's analysis and generating review documents, and a means for providing the generated review documents to the device and the review department.

[0507] The user inputs information about the new service into the device. In this process, the user uses a form to enter detailed data about the new service's name, purpose, target customers, functions to be provided, and relevant laws and regulations. For example, the user might enter the name "online education platform," the purpose as "improving learning effectiveness for junior high school students," and the functions to be provided as "video lessons, learning material downloads, and ranking tests."

[0508] The device sends the information entered by the user to the server. At this time, the data is sent in a structured data format such as JSON, and the server receives this data. For example, the device sends the following data to the server in JSON format: "New service name: Online education platform, Purpose: Improving learning effectiveness for junior high school students, Functions provided: Video lessons, learning material downloads, Rank test."

[0509] The server sends the received data to a generative AI model. The generative AI model analyzes the input data based on previously learned laws, regulations, and past evaluation results, and extracts review items and concerns. For example, if the server sends the received data to the generative AI model as "New service: online education platform, purpose: improving learning effectiveness for junior high school students, provided functions: video lessons, learning material downloads, rank tests," the generative AI model will return important review items such as "personal information protection measures" and "copyright confirmation" as analysis results.

[0510] Sample prompt: Analyze the concerns regarding privacy and copyright for a new online education platform.

[0511] The server creates an inspection document based on the inspection items and concerns obtained from the generative AI model. This inspection document is provided to the user's device and the inspection department. For example, the server creates an inspection document based on the analysis results, including "personal information protection measures," "copyright confirmation," and "legality of educational content," and generates it in PDF format or similar and provides it to the user and the inspection department via email or the system's notification function.

[0512] The review department conducts a detailed review based on the review documents provided. During this process, any necessary corrections or additional information is identified. For example, the legal department may provide feedback pointing out that "the explanation regarding personal information protection measures is insufficient." The user takes the necessary action based on the feedback and updates the review document to reflect the corrections and additional information. The updated review document is then sent back to the server for re-review.

[0513] As described above, the system of the present invention can improve the efficiency and accuracy of the review process for new services.

[0514] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0515] Program processing explanation

[0516] Step 1: Process User Input

[0517] The user inputs information about the new service into the device. Specifically, the user enters detailed data about the new service's name, purpose, target customers, provided functions, and relevant laws and regulations through a form. The input data is saved in the device and prepared for the next step.

[0518] Input: New service name, purpose, target customers, provided functions, relevant laws and regulations

[0519] Output: New service information entered in the form

[0520] Specific operation: The user enters the name "online education platform" into the form on the device, enters "improving learning effectiveness for junior high school students" as the purpose, and enters "video lessons, learning material downloads, rank tests" as the functions to be provided.

[0521] Step 2: Send data

[0522] The device sends the information entered by the user to the server. In this process, the data is sent in a structured data format such as JSON, and the server receives it.

[0523] Input: New service information entered in the form

[0524] Output: JSON formatted data sent to the server

[0525] Specific operation: The device sends the following data in JSON format to the server: "New service name: Online education platform, Purpose: Improving learning effectiveness for junior high school students, Functions provided: Video lessons, downloading teaching materials, Rank test."

[0526] Step 3: Parsing and Extraction

[0527] The server sends the received data to a generative AI model, which analyzes the input data based on previously learned laws, regulations, and past evaluation results, and extracts review items and concerns. This clarifies the criteria and risks required for the review.

[0528] Input: JSON format data received by the server

[0529] Output: The assessment items and concerns returned by the generative AI model

[0530] Specific operation: The server sends the received data to the generation AI model as "New service: online education platform, purpose: improving learning effectiveness for junior high school students, provided functions: video lessons, learning material downloads, rank tests." The generation AI model then returns important review items such as "personal information protection measures" and "copyright confirmation" as analysis results.

[0531] Step 4: Generate and provide review documentation

[0532] The server creates an inspection document based on the inspection items and concerns obtained from the generative AI model, and provides the generated inspection document to the user's device and inspection department.

[0533] Input: Analysis results of the generative AI model (evaluation items and concerns)

[0534] Output: Generated audit document

[0535] Specific operation: Based on the analysis results, the server generates a review document in PDF format, including information on "personal information protection measures," "copyright confirmation," and "legality of educational content," and provides it to the user and review department. For example, the review document is sent via email or the system's notification function.

[0536] Step 5: Feedback and response to review results

[0537] The review department conducts a detailed review based on the provided review documents. During this process, they check for any necessary corrections or additional information and provide feedback. The user receives the feedback, takes the necessary action, and updates the review document to reflect the corrections and additional information. The updated review document is sent back to the server for re-review.

[0538] Input: Review documents provided, feedback from the review department

[0539] Output: Revised and updated audit document

[0540] Specific operation: The legal department reports that the explanation of personal information protection measures is insufficient. The user adds details about the specific protection measures according to the guidelines, updates the review document on the terminal again, and sends it to the server. The server then analyzes and reviews it again.

[0541] Through the above processing steps, the system of the present invention can improve the efficiency and accuracy of the review process for new services.

[0542] (Application example 1)

[0543] 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."

[0544] Currently, when introducing new robots or adding new functions to a factory, it is necessary to comply with numerous laws and company regulations, and the review process is often time-consuming and labor-intensive. Furthermore, there is no system in place to accurately identify review items and concerns and address them efficiently. As a result, the introduction process is delayed, resulting in problems such as reduced productivity.

[0545] 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.

[0546] In this invention, the server includes means for extracting inspection items and concerns based on new information and settings of factory robots and generating an inspection sheet, means for analyzing input data and extracting inspection items and concerns based on laws, regulations, and past inspection results that the generation AI has previously learned, and means for receiving feedback from the inspection department and updating the inspection sheet based on the feedback.This enables quick and accurate inspections that comply with laws, regulations, and rules when introducing new robots or adding functions to factories.

[0547] "Information input terminal" refers to a device that allows users to input information about new services or robots. Generally, this includes computers, tablets, smartphones, etc.

[0548] A "server" is a computer system on a network that receives input data and sends it to the generating AI.

[0549] "Generative AI" is an artificial intelligence that analyzes input data based on pre-trained data and extracts review items and points of concern.

[0550] "Inspection items" are specific checkpoints or requirements that must be verified when introducing a new service or robot or adding new features.

[0551] "Concerns" refer to the risks and problems associated with introducing new services and robots.

[0552] The "review sheet" is a document that organizes the review items and concerns extracted by the generation AI and provides them to the review department.

[0553] The "review department" is a department within the company that reviews applications based on the provided review sheets and provides necessary feedback.

[0554] "Feedback" refers to opinions and information that the review department provides based on the review sheet and requests corrections.

[0555] The system for realizing the present invention mainly includes the following hardware and software:

[0556] Hardware used: high-performance cloud servers, desktop terminals for users to input information, tablets, and smartphones

[0557] Software used: API server built with Flask, pre-trained natural language processing model (GPT-4)

[0558] The operation of the system is as follows.

[0559] First, users input new information and settings for their factory robots, including the robot's name, function, intended location, and applicable regulations, via a desktop, tablet, or smartphone.

[0560] The device then sends the information entered by the user to the server, with the data being sent in a standard format such as JSON.

[0561] The server sends the received data to the generation AI for analysis. The generation AI model analyzes the input data based on previously learned laws and regulations, company regulations, and past inspection results, and extracts inspection items and points of concern.

[0562] Based on the analysis results of the generative AI model, the server generates an evaluation sheet, which details the extracted evaluation items and concerns. The generated evaluation sheet is provided to the user's device and the device of the evaluation department.

[0563] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The review department's feedback will be communicated to the user via the server.

[0564] The user receives the feedback, takes necessary action based on the content, and updates the evaluation sheet. The updated evaluation sheet is then sent back to the server and reanalyzed by the generative AI model.

[0565] Specific examples

[0566] For example, consider the case where a factory employee installing a new high-precision welding robot enters the following information:

[0567] Robot name: New welding robot

[0568] Function:High precision welding

[0569] Planned installation location: 2nd Factory

[0570] Related laws and regulations: Labor safety regulations, environmental protection laws

[0571] Based on the submitted information, the generative AI model extracts review items related to occupational safety regulations and environmental protection laws (e.g., measures to ensure worker safety and regulations on the emission of hazardous substances) and generates a review sheet.

[0572] Example prompts for generative AI models

[0573] Analyze information to qualify new factory robots.

[0574] Robot name: "New welding robot"

[0575] Function: "High precision welding"

[0576] Planned installation location: "Second Factory"

[0577] Related laws and regulations: "Occupational Safety Regulations" and "Environmental Protection Act"

[0578] Extract the review items and concerns and generate a review sheet.

[0579] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0580] Step 1:

[0581] Users input information, such as the name of the new robot, its functions, the planned location for its deployment, and relevant laws and regulations, using a desktop, tablet, or smartphone.

[0582] Input: New robot information (name, function, planned installation location, relevant laws and regulations)

[0583] Output: Input data (e.g., JSON format)

[0584] Step 2:

[0585] The terminal sends the entered data to the server, where it is sent using a secure protocol (e.g., HTTPS).

[0586] Input: Data entered by the user

[0587] Output: Data sent to the server

[0588] Step 3:

[0589] The server sends the received data to a generative AI model, which has been pre-trained with laws, regulations, company rules, and past review results.

[0590] Input: Data sent from the terminal

[0591] Output: Data sent to the generative AI model

[0592] Step 4:

[0593] A generative AI model analyzes input data and extracts review items and concerns, using natural language processing techniques to identify checkpoints that comply with laws, regulations, etc.

[0594] Input: Data sent from the server

[0595] Output: Analysis results (review items and concerns)

[0596] Step 5:

[0597] The server generates an evaluation sheet based on the analysis results from the AI ​​model, which details the extracted evaluation items and concerns.

[0598] Input: Analysis results from a generative AI model

[0599] Output: Review sheet

[0600] Step 6:

[0601] The server provides the generated review sheet to the user's terminal and the terminal of the review department. The review sheet is often provided in PDF or HTML format.

[0602] Input: Generated review sheet

[0603] Output: Terminal and review sheet provided to the review department

[0604] Step 7:

[0605] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information.

[0606] Input: Review sheet

[0607] Output: Feedback

[0608] Step 8:

[0609] The user receives the feedback, takes necessary action based on the content, and updates the evaluation sheet. The updated evaluation sheet is then sent back to the server.

[0610] Input: Feedback from the review department

[0611] Output: Updated review sheet

[0612] Step 9:

[0613] The server sends the updated review sheet back to the generative AI model for re-analysis, and if necessary, repeats the process.

[0614] Input: Updated review sheet

[0615] Output: Reparsed review sheet

[0616] 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.

[0617] The present invention relates to a system and program for efficiently and accurately reviewing new service development, taking into account laws and regulations, company regulations, and past review results, while recognizing user emotions and providing further interactive feedback. This system includes a terminal for inputting information, a server that receives the input data and sends it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, and an emotion engine that recognizes user emotions.

[0618] Program processing explanation

[0619] The program of this system operates as follows.

[0620] A. User Input Processing

[0621] The user enters information about the new service into the terminal. Specifically, the user enters the name of the new service, its purpose, target customers, the functions it will provide, and any related laws and regulations through a form. The emotion engine then obtains emotion data from the user's input and actions.

[0622] Example: A user inputs information about an "online education platform." For example, the name may be "online education platform," the purpose may be "to improve learning outcomes for junior high school students," and the functions provided may be "video lessons, learning material downloads, and rank tests." The emotion engine analyzes the user's input speed and keystroke patterns to estimate the user's emotions (e.g., excitement, impatience).

[0623] B. Data Transmission and Emotion Transmission

[0624] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[0625] C. Analysis and Extraction

[0626] The server receives the data sent from the device. It then sends the received new service information and emotion data to the generation AI. The generation AI analyzes the input data based on previously learned laws and regulations, company regulations, past review results, and emotion data, and extracts review items and concerns.

[0627] Example: The server sends data from an "online education platform" and user emotional data to a generation AI, which then extracts concerns about "personal information protection measures" and "copyright confirmation," as well as "excessive expectations for specific functions" if the user is excited.

[0628] D. Generating and providing review sheets

[0629] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[0630] Example: The server creates an evaluation sheet that includes personal information protection measures, copyright confirmation, legality of the training content, and "excessive expectations for specific functions," and shares it with the user and the legal department.

[0631] E. Feedback and Response to Review Results

[0632] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on the feedback, update the review sheet, and submit it again to the server to complete the review process.

[0633] Example: The legal department makes specific recommendations regarding "failure to confirm safety measures for personal information protection," and the user takes action based on those recommendations. After that, the updated information is re-entered into the system and the review sheet is updated.

[0634] Specific processing flow

[0635] The addition of an emotion engine to the system of the present invention enables interactive feedback that takes into account the user's emotions, thereby speeding up and improving the accuracy of the review process, and thereby realizing a more user-friendly review process.

[0636] As described above, the system of the present invention not only improves the efficiency and accuracy of the review of new services, but also recognizes the user's emotions, making it possible to provide more appropriate feedback.

[0637] The processing flow will be explained below.

[0638] Step 1:

[0639] The user opens the information input form for the new service on their device. In the form, they enter the name of the new service, its purpose, target customers, the functions it will provide, and any relevant laws and regulations. After completing the input, they click the send button to send the information to the server.

[0640] Example: A user enters information about an "online education platform." For example, the name may be "online education platform," the purpose may be "to improve learning effectiveness for junior high school students," and the functions provided may be "video lessons, learning material downloads, and ranking tests." Furthermore, while the user is entering information, the emotion engine obtains emotion data from the input speed and keystrokes.

[0641] Step 2:

[0642] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[0643] Example: The device converts information about the "online education platform" and the user's emotional data into JSON format and sends it to the server.

[0644] Step 3:

[0645] The server receives the JSON data sent from the device. After receiving the data, the server analyzes it and stores it in its internal database. After storing it, the server prepares to send the data and emotion data to the generation AI.

[0646] Example: The server stores the information and emotional data of the "online education platform" received from the device in a database.

[0647] Step 4:

[0648] The server sends the saved data and emotion data to the generation AI's API, which then begins analyzing the input data.

[0649] Example: The server sends information and emotional data from the "online education platform" to the generation AI, which then begins analysis.

[0650] Step 5:

[0651] The AI ​​analyzes the submitted data based on pre-trained laws, company regulations, past review results, and emotional data, and extracts review items and points of concern as a result of the analysis.

[0652] Example: Generative AI analyzes information on an "online education platform" and, in addition to "personal information protection measures" and "copyright confirmation," extracts "excessive expectations for certain features" as concerns if the user is excited.

[0653] Step 6:

[0654] The server receives the analysis results returned by the generation AI. It generates an evaluation sheet based on the received analysis results. The evaluation sheet lists the extracted evaluation items and concerns.

[0655] Example: The server creates a review sheet that includes personal information protection measures, copyright confirmation, and "excessive expectations for specific features."

[0656] Step 7:

[0657] The server then initiates a procedure to provide the generated review sheet to the user's terminal and the review department, specifically by attaching it to an email or via a specialized web interface.

[0658] Example: The server sends the review sheet to the user and the review department by email.

[0659] Step 8:

[0660] The user receives and checks the review sheet provided via the terminal. The sheet is also provided to the review department, and each department begins their review.

[0661] Example: The user reviews the provided review sheet, and the legal department also receives the same sheet and reviews it.

[0662] Step 9:

[0663] The review department checks the details of the new service based on the review sheet and provides feedback on any necessary corrections or additional information, which is then sent to the user and the server.

[0664] Example: The legal department points out that "safety measures for personal information protection have not been confirmed" and sends this information to the user and server as feedback.

[0665] Step 10:

[0666] The user receives the feedback and takes any necessary action, after which the user re-enters the corrected information into the system and submits it to the server.

[0667] Example: The user takes the necessary action based on the legal department's feedback, re-enters the corrected information into the system, and submits it to the server.

[0668] Step 11:

[0669] The server then sends the corrected information and emotion data it has received back to the AI, and reanalyzes it as necessary. The review sheet is updated based on the analysis results.

[0670] Example: The server sends the corrected information and newly acquired emotion data to the generation AI, which then reanalyzes and updates the review sheet.

[0671] Step 12:

[0672] The server again provides the updated review sheet to the user and the review department for final confirmation and approval.

[0673] Example: The server sends the updated review sheet again to the user and the review department for final confirmation.

[0674] The above is a detailed processing flow of the new service review assistance system that combines an emotion engine. This step not only speeds up and improves the accuracy of the review, but also enables interactive feedback that takes the user's emotions into consideration.

[0675] Example 2

[0676] 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."

[0677] The review system for the previous new service took into account laws, company regulations, and past review results, but did not provide feedback that took user emotions into account, making the review process unfriendly and making it difficult to conduct a fast and accurate review.In addition, the lack of an interactive review process that reflected user emotions made improving user satisfaction a challenge.

[0678] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0679] In this invention, the server includes means for extracting review items and concerns from the results of the analysis by the generation AI, including the user's emotional data acquired by the emotion engine, and generating a review sheet, means for providing the generated review sheet to the terminal and the review department, and means for receiving feedback from the review department and updating the review sheet based on the feedback, thereby enabling a fast and accurate review that takes into account the user's emotional data.

[0680] The "terminal for inputting information" refers to a device such as a computer or smartphone that a user uses to input information about a new service.

[0681] The "server" is a high-performance computer system that transmits data received from the terminal to the generation AI and receives the analysis results from the generation AI.

[0682] "Generative AI" is an artificial intelligence model that analyzes laws and regulations, internal regulations, past judgment results, and emotional data that it has previously studied, and extracts review items and points of concern.

[0683] The "emotion engine" is a software module that analyzes user input and operation data in real time and generates user emotion data.

[0684] "Review items" are the elements and criteria that the generating AI analyzes the input data and determines to be essential for review.

[0685] "Concerns" are issues that the generating AI has identified from its analysis results that could pose problems or risks during the review process.

[0686] The "review sheet" is a document that summarizes the review items and concerns extracted by the generation AI and is used to review new services.

[0687] "Feedback" refers to a response such as corrections or additional information provided to the user after the review department makes a judgment based on the review sheet.

[0688] "Rules" is a general term for laws, regulations, and internal company rules and guidelines.

[0689] "Internal regulations" refer to rules and policies that must be followed within an organization.

[0690] "Past judgment results" refers to data and records relating to the results of past inspections.

[0691] "Emotion data" is data relating to the user's emotional state analyzed by the emotion engine.

[0692] This invention is a system that not only considers laws and regulations, company regulations, and past review results when developing new services, but also performs efficient and accurate reviews and provides interactive feedback by recognizing the user's emotions. This system includes a terminal for inputting information, a server that receives the input data and sends it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, and an emotion engine that recognizes the user's emotions.

[0693] Hardware and software used

[0694] Device: A computer or smartphone is used by users to enter information, such as the name of the new service, its purpose, target customers, the functions it provides, and relevant laws and regulations, through a web form.

[0695] Server: A high-performance server receives data, communicates with the AI, and generates the evaluation sheet. The server can use web server software such as Apache or NGINX.

[0696] Generative AI: An artificial intelligence model that performs analysis based on pre-trained data. For example, analysis is performed using a large-scale language model such as GPT-4.

[0697] Emotion engine: A software module that analyzes a user's emotions in real time. Specifically, it is emotion recognition software that analyzes input speed, keystroke patterns, etc.

[0698] Program processing overview

[0699] The program of this system operates as follows.

[0700] User Input Processing

[0701] The user inputs information about the new service into the device. This input includes the name of the new service, its purpose, target customers, the functions it provides, and information about related laws and regulations. The emotion engine then analyzes the user's input and operation data in real time to generate emotion data.

[0702] Data transmission and emotion transmission

[0703] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[0704] Parsing and Extraction

[0705] The server receives the data sent from the device. It then sends the received new service information and emotion data to the generation AI. The generation AI analyzes the input data based on previously learned laws and regulations, company regulations, past review results, and emotion data, and extracts review items and concerns.

[0706] Generation and provision of review sheets

[0707] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[0708] Feedback and Updates

[0709] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will receive the feedback, take the necessary action, update the review sheet, and send it back to the server.

[0710] Specific processing examples

[0711] A user inputs information about an "online education platform." For example, the name is "online education platform," the purpose is "to improve learning effectiveness for junior high school students," and the functions provided are "video lessons, learning material downloads, and rank tests." The emotion engine analyzes the user's input speed and keystroke patterns to estimate emotions such as "excitement" and "expectation."

[0712] The server receives new service information and emotion data sent from the device and sends it to the generation AI, which then extracts review items such as "personal information protection" and "copyright confirmation" and identifies "excessive expectations for specific functions" as a concern.

[0713] The server then creates an assessment sheet based on the assessment items and concerns, and provides it to the user's device and the assessment department. The legal department reviews the assessment sheet and provides specific feedback to the user, such as "personal information protection measures not confirmed." The user then takes action based on this feedback, re-enters the updated information into the system, and updates the assessment sheet.

[0714] Prompt Sentence Examples

[0715] "We'd like you to review a new online education platform. Its name is 'Online Education Platform,' its purpose is 'to improve learning outcomes for junior high school students,' and its functions are 'video lessons, learning material downloads, and rank tests.' Please identify review items and concerns based on laws and regulations, company regulations, past review results, and user sentiment."

[0716] This not only enables the system of the present invention to streamline and improve the accuracy of the review of new services, but also to provide more appropriate feedback by recognizing the user's emotions.

[0717] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0718] Step 1:

[0719] The user inputs information about the new service into the terminal.

[0720] Input includes the name of the new service, its purpose, target customers, the features it provides, and information on relevant laws and regulations. The emotion engine analyzes this input and operation data in real time to generate user emotion data.

[0721] Input: New service information (name, purpose, target customers, provided functions, relevant laws and regulations)

[0722] Data processing: The emotion engine analyzes input speed and keystroke patterns to generate emotion data.

[0723] Output: Input new service information, user emotion data (e.g., excitement, anticipation)

[0724] Step 2:

[0725] The terminal converts the data entered by the user into JSON format.

[0726] The converted data includes information about the new service and emotion data, and is sent to the server.

[0727] Input: New service information and emotion data entered by the user

[0728] Data processing: Convert new service information and emotion data into JSON format

[0729] Output: JSON format data

[0730] Step 3:

[0731] The server receives the JSON data sent from the terminal.

[0732] The received data is sent to the generation AI, which analyzes the input data and extracts review items and concerns based on previously studied laws and regulations, company regulations, past review results, and emotional data.

[0733] Input: New service information and emotion data in JSON format sent from the device

[0734] Data processing: Generative AI analyzes JSON data and extracts review items and concerns

[0735] Output: Extracted review items and concerns

[0736] Step 4:

[0737] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI.

[0738] The generated review sheet is provided to the user's terminal and the review department.

[0739] Input: Review items and concerns obtained from the generative AI

[0740] Data processing: Create an evaluation sheet by combining the evaluation items and concerns.

[0741] Output: Review sheet

[0742] Step 5:

[0743] The review department will conduct the review based on the review sheet provided.

[0744] Generate feedback and notify the user with any necessary corrections or additional information.

[0745] Input: Provided review sheet

[0746] Data processing: Check the review contents and make corrections or add additional information

[0747] Output: Feedback

[0748] Step 6:

[0749] The user makes corrections based on the feedback received.

[0750] The corrected information is re-entered into the system and the updated review sheet is sent to the server.

[0751] Input: Feedback

[0752] Data processing: Modify new service information based on feedback

[0753] Output: Revised new service information

[0754] Step 7:

[0755] The server receives the retransmitted data and retransmits it to the generating AI.

[0756] The generating AI will reanalyze and update if any new review items or concerns arise.

[0757] Input: Revised new service information

[0758] Data processing: Generative AI reanalyzes data and updates the review items and concerns.

[0759] Output: Updated review criteria and concerns

[0760] This results in a user-friendly, efficient and accurate review process.

[0761] (Application example 2)

[0762] 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."

[0763] Introducing or modifying new production lines or work processes in factories requires compliance with laws, regulations, and company rules, and therefore screening is essential. However, conventional screening systems rely on the judgment of personnel, which can be inefficient and time-consuming. Furthermore, because they do not take user feelings into consideration, feedback can be inappropriate. This can delay the implementation process and have a negative impact on production efficiency and safety. Therefore, there is a need for a system that improves the efficiency and accuracy of screening, as well as the user experience.

[0764] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0765] In this invention, the server includes a terminal for inputting information, a means for receiving data input from the terminal and sending it to the generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, an emotion engine for recognizing the user's emotions, and a means for generating interactive feedback taking the user's emotion data into consideration. This not only improves the efficiency and accuracy of the review, but also makes it possible to provide appropriate feedback that takes the user's emotions into consideration.

[0766] The "information input terminal" is a device that allows a user to input information about a new production line or work process.

[0767] "Generative AI" is an artificial intelligence system that analyzes input data based on previously learned laws and regulations, company regulations, and past review results, and extracts review items and points of concern.

[0768] A "server" is a computer system that receives data entered from a terminal and sends it to the generation AI.

[0769] The "means of generating an evaluation sheet" refers to the process of compiling evaluation items and concerns from the results of the analysis by the generation AI and creating a final evaluation sheet.

[0770] The "review department" is a department that reviews the application based on the generated review sheet and provides necessary corrections and additional information as feedback.

[0771] An "emotion engine" is a system that recognizes emotions from user input and operation data and acquires emotion data.

[0772] The "means for generating interactive feedback" is a process that takes into account the user's emotional data and generates and provides appropriate feedback.

[0773] The present invention provides a system for efficiently and accurately reviewing the introduction or modification of new production lines or work processes in factories. The system includes a terminal for inputting information, a server that receives the data input from the terminal and sends it to a generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating a review sheet, and a means for providing the generated review sheet to the terminal and the review department. The system also includes an emotion engine that recognizes user emotions and a means for generating interactive feedback taking into account the user's emotion data.

[0774] Program processing explanation

[0775] The user uses a terminal to input information related to a new production line or work process. This terminal can be a desktop computer, tablet, or smartphone. The input information is sent to a server. Upon receiving this data, the server sends it to a generative AI model. The generative AI model analyzes the input data based on previously learned laws and regulations, company regulations, and past review results, and extracts review items and concerns. Furthermore, an emotion engine recognizes emotions from the user's input and operation data, and acquires emotional data.

[0776] Based on the analysis results of the generation AI, the server generates an evaluation sheet. The generated evaluation sheet is sent back to the terminal and provided to the evaluation department. The terminal receives feedback from the evaluation department, sends it to the server, and updates the evaluation sheet.

[0777] As a concrete example, consider the case where a user is installing a new production line. The user inputs information about the "new assembly line" into the terminal. Specifically, the information entered includes the name "new assembly line," the purpose "improving production efficiency," the functions provided "automated machinery, quality inspection system," and related laws and regulations "Occupational Safety and Health Act, Product Liability Act." At this stage, the emotion engine obtains emotion data from the user's input speed, keystroke patterns, and facial expressions, and sends it to the server.

[0778] The generative AI model analyzes this data and extracts review items such as "personal information protection measures" and "safety management confirmation." If the user is feeling impatient, "preventing mistakes due to excessive pressure" may also be cited as a concern. This generates a review sheet that is provided to the user's device and the review department. If feedback is received from the review department, the review sheet is updated based on that feedback. This process improves the efficiency and accuracy of reviews, and also contributes to an improved user experience.

[0779] Prompt Sentence Examples

[0780] - "Please enter information about the new assembly line."

[0781] - "Objective: Improve production efficiency"

[0782] -"Provided functions: automated machinery, quality inspection systems"

[0783] - "Related laws and regulations: Occupational Safety and Health Act, Product Liability Act"

[0784] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0785] Step 1:

[0786] The user enters information

[0787] The user uses the device to input information related to the new production line and work process. Specific input data includes the name, purpose, provided functions, relevant laws and regulations, etc. The input data is stored on the device and prepared for later transmission to the server. The emotion engine also analyzes the user's input speed and keystroke patterns to obtain the user's emotional data.

[0788] Input: Information related to the new production line and work process

[0789] Output: Input data and emotion data

[0790] Step 2:

[0791] The device sends data to the server

[0792] The device converts the data entered by the user and the acquired emotion data into JSON format and sends it to the server. This conversion process is important for maintaining data consistency.

[0793] Input: Input data and emotion data

[0794] Output: JSON format data

[0795] Step 3:

[0796] The server sends the data to the generation AI

[0797] The server sends the JSON-formatted data received from the device to the generative AI model, which then analyzes the data based on previously learned laws, regulations, company rules, and past review results.

[0798] Input: JSON format data

[0799] Output: Analysis request by the generated AI

[0800] Step 4:

[0801] Generative AI analyzes data

[0802] The generative AI model analyzes the received data and extracts review items and concerns, while also taking into account the user's emotional data to identify additional emotion-based concerns and warnings.

[0803] Input: Analysis request by the generated AI

[0804] Output: List of review items and concerns

[0805] Step 5:

[0806] The server generates the review sheet

[0807] The server generates an evaluation sheet based on the list of evaluation items and concerns obtained from the generation AI. The evaluation sheet includes individual evaluation items and their corresponding concerns.

[0808] Input: List of review items and concerns

[0809] Output: Review sheet

[0810] Step 6:

[0811] The server provides the review sheet to the terminal and the review department.

[0812] The server provides the generated review sheet to the user's terminal and the review department, which allows both the user and the reviewer to check the review sheet.

[0813] Input: Review sheet

[0814] Output: Provided to the user's terminal and the review department

[0815] Step 7:

[0816] Receive and respond to feedback from the review department

[0817] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on this feedback and re-enter the updated information into the system.

[0818] Input: Feedback on the review sheet

[0819] Output: Updated information

[0820] Step 8:

[0821] The server updates the review sheet again and provides

[0822] The server updates the review sheet again based on the updated information and provides it again to the user and the review department, thereby completing the review process.

[0823] Input: Updated information

[0824] Output: Updated review sheet

[0825] Through these steps, the introduction and modification of new production lines and work processes in factories can be reviewed efficiently and accurately.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] [Third embodiment]

[0830] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0831] 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.

[0832] 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).

[0833] 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.

[0834] 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.

[0835] 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).

[0836] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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."

[0842] This invention relates to a system and its program for efficiently and accurately reviewing new service development, taking into consideration laws and regulations, company regulations, and past review results. This system includes a terminal for inputting information, a server for receiving the input data and sending it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, and a means for providing the generated review sheet to the terminal and the review department.

[0843] Program processing explanation

[0844] The program of this system operates as follows.

[0845] A. User Input Processing

[0846] The user enters information about the new service into the terminal, specifically, the name of the new service, its purpose, target customers, the functions it provides, and data on related laws and regulations through a form.

[0847] Example: A user enters information about an "online education platform." For example, the name could be "online education platform," the purpose could be "to improve learning outcomes for junior high school students," and the functions provided could be "video lessons, downloading teaching materials, and ranking tests."

[0848] B. Data Transmission

[0849] The terminal sends the information entered by the user to the server. The data is sent in JSON format or similar, and the server receives it.

[0850] C. Analysis and Extraction

[0851] The server sends the received data to the generation AI, which analyzes the input data based on laws and regulations, company regulations, and past review results that it has previously studied, and extracts review items and points of concern.

[0852] Example: The server sends data from an "online education platform" to a generation AI, which then extracts review items such as "personal information protection measures" and "copyright confirmation."

[0853] D. Generating and providing review sheets

[0854] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[0855] Example: The server creates an inspection sheet that includes personal information protection measures, copyright confirmation, and the legality of the educational content, and shares it with the user and the legal department.

[0856] E. Feedback and Response to Review Results

[0857] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on the feedback and update the review sheet. The updated review sheet will be sent back to the server for review.

[0858] Example: The legal department points out that "safety measures for personal information protection have not been confirmed," and the user takes action in accordance with the guidelines and resubmits the sheet.

[0859] Specific processing flow

[0860] In the system of the present invention, the examination is carried out through the following specific processing flow.

[0861] 1. The user enters new service information from the terminal.

[0862] 2. The terminal sends the entered information to the server.

[0863] 3. The server sends the received information to the generation AI for analysis.

[0864] 4. The generation AI returns the analysis results to the server.

[0865] 5. The server generates the review sheet and provides it to the terminal and the review department.

[0866] 6. The review department provides feedback and the user responds.

[0867] As described above, the system of the present invention can improve the efficiency and accuracy of the examination of new services.

[0868] The processing flow will be explained below.

[0869] Step 1:

[0870] The user opens the information input form for the new service on their device. In the form, they enter the name of the new service, its purpose, target customers, the functions it provides, and any relevant laws and regulations. After completing the input, they click the send button to send the information to the server.

[0871] Step 2:

[0872] The terminal converts the data entered by the user into JSON format, and then makes an API request to the server and sends the data to the server.

[0873] Step 3:

[0874] The server receives the JSON data sent from the device. After receiving it, the server analyzes the data and stores it in an internal database. After storing it, the server prepares to send the data to the generation AI.

[0875] Step 4:

[0876] The server sends the saved data to the AI's API, which then begins analyzing the data.

[0877] Step 5:

[0878] The AI ​​analyzes the submitted data based on previously learned laws, company regulations, and past review results, and extracts review items and points of concern as a result of the analysis.

[0879] Step 6:

[0880] The server receives the analysis results returned by the generation AI. It generates an evaluation sheet based on the received analysis results. The evaluation sheet lists the extracted evaluation items and concerns.

[0881] Step 7:

[0882] The server then initiates a procedure to provide the generated review sheet to the user's terminal and the review department, specifically by attaching it to an email or via a specialized web interface.

[0883] Step 8:

[0884] The user receives and checks the review sheet provided via the terminal. The sheet is also provided to the review department, and each department begins their review.

[0885] Step 9:

[0886] The review department checks the details of the new service based on the review sheet and provides feedback on any necessary corrections or additional information, which is then sent to the user and the server.

[0887] Step 10:

[0888] The user receives the feedback and takes any necessary action, after which the user re-enters the corrected information into the system and submits it to the server.

[0889] Step 11:

[0890] The server then sends the corrected information received again to the generation AI, which reanalyzes it as necessary, and updates the review sheet based on the analysis results.

[0891] Step 12:

[0892] The server again provides the updated review sheet to the user and the review department for final confirmation and approval.

[0893] This is the detailed process flow of the new service examination assistance system. This step makes it possible to speed up examinations and improve their accuracy.

[0894] Example 1

[0895] 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."

[0896] Conventionally, when developing a new service, a review is conducted taking into account laws and regulations, internal company rules, and past review results. However, this process is laborious and time-consuming, and has problems with inefficiency and inaccuracy. In addition, specialized knowledge is required to accurately identify review items and concerns, placing a heavy burden on human resources. There was a need for a system that could solve these issues and review new services efficiently and accurately.

[0897] 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.

[0898] In this invention, the server includes a device for inputting information, a means for receiving data input from the device and sending it to the generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating review documents, a means for providing the generated review documents to the device and the review department, and a means for receiving opinions from the evaluation department and updating the review documents based on the opinions. This makes it possible to streamline the review process for new services and increase accuracy.

[0899] The "device for inputting information" is a device used by the user to input information about the new service.

[0900] A "server that receives data and sends it to the generation AI" is a computer system that has the function of receiving data sent from an information input device and sending that data to the generation AI.

[0901] "Generative AI" is an artificial intelligence that analyzes data based on pre-trained laws, regulations, and past evaluation results, and extracts review items and points of concern.

[0902] "Review items" are the criteria and checkpoints necessary to evaluate and confirm new services.

[0903] "Concerns" are issues that could pose problems or risks with the new service.

[0904] A "review document" is a document containing review items and concerns created based on the results of analysis by the generation AI.

[0905] The "review department" is a department that receives the generated review documents and provides evaluation and feedback.

[0906] "Opinions from the evaluation department" refers to feedback on corrections and additional information provided by the evaluation department to the evaluation document.

[0907] "Means for updating review documents" refers to means that have the function of amending and updating review documents based on feedback from the evaluation department.

[0908] The present invention relates to a system and its program for efficiently and accurately reviewing new service development, taking into consideration laws and regulations, company regulations, and past review results. The system includes a device for inputting information, a server that receives the input data and sends it to a generative AI model, a means for extracting review items and concerns based on the results of the generative AI's analysis and generating review documents, and a means for providing the generated review documents to the device and the review department.

[0909] The user inputs information about the new service into the device. In this process, the user uses a form to enter detailed data about the new service's name, purpose, target customers, functions to be provided, and relevant laws and regulations. For example, the user might enter the name "online education platform," the purpose as "improving learning effectiveness for junior high school students," and the functions to be provided as "video lessons, learning material downloads, and ranking tests."

[0910] The device sends the information entered by the user to the server. At this time, the data is sent in a structured data format such as JSON, and the server receives this data. For example, the device sends the following data to the server in JSON format: "New service name: Online education platform, Purpose: Improving learning effectiveness for junior high school students, Functions provided: Video lessons, learning material downloads, Rank test."

[0911] The server sends the received data to a generative AI model. The generative AI model analyzes the input data based on previously learned laws, regulations, and past evaluation results, and extracts review items and concerns. For example, if the server sends the received data to the generative AI model as "New service: online education platform, purpose: improving learning effectiveness for junior high school students, provided functions: video lessons, learning material downloads, rank tests," the generative AI model will return important review items such as "personal information protection measures" and "copyright confirmation" as analysis results.

[0912] Sample prompt: Analyze the concerns regarding privacy and copyright for a new online education platform.

[0913] The server creates an inspection document based on the inspection items and concerns obtained from the generative AI model. This inspection document is provided to the user's device and the inspection department. For example, the server creates an inspection document based on the analysis results, including "personal information protection measures," "copyright confirmation," and "legality of educational content," and generates it in PDF format or similar and provides it to the user and the inspection department via email or the system's notification function.

[0914] The review department conducts a detailed review based on the review documents provided. During this process, any necessary corrections or additional information is identified. For example, the legal department may provide feedback pointing out that "the explanation regarding personal information protection measures is insufficient." The user takes the necessary action based on the feedback and updates the review document to reflect the corrections and additional information. The updated review document is then sent back to the server for re-review.

[0915] As described above, the system of the present invention can improve the efficiency and accuracy of the review process for new services.

[0916] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0917] Program processing explanation

[0918] Step 1: Process User Input

[0919] The user inputs information about the new service into the device. Specifically, the user enters detailed data about the new service's name, purpose, target customers, provided functions, and relevant laws and regulations through a form. The input data is saved in the device and prepared for the next step.

[0920] Input: New service name, purpose, target customers, provided functions, relevant laws and regulations

[0921] Output: New service information entered in the form

[0922] Specific operation: The user enters the name "online education platform" into the form on the device, enters "improving learning effectiveness for junior high school students" as the purpose, and enters "video lessons, learning material downloads, rank tests" as the functions to be provided.

[0923] Step 2: Send data

[0924] The device sends the information entered by the user to the server. In this process, the data is sent in a structured data format such as JSON, and the server receives it.

[0925] Input: New service information entered in the form

[0926] Output: JSON formatted data sent to the server

[0927] Specific operation: The device sends the following data in JSON format to the server: "New service name: Online education platform, Purpose: Improving learning effectiveness for junior high school students, Functions provided: Video lessons, downloading teaching materials, Rank test."

[0928] Step 3: Parsing and Extraction

[0929] The server sends the received data to a generative AI model, which analyzes the input data based on previously learned laws, regulations, and past evaluation results, and extracts review items and concerns. This clarifies the criteria and risks required for the review.

[0930] Input: JSON format data received by the server

[0931] Output: The assessment items and concerns returned by the generative AI model

[0932] Specific operation: The server sends the received data to the generation AI model as "New service: online education platform, purpose: improving learning effectiveness for junior high school students, provided functions: video lessons, learning material downloads, rank tests." The generation AI model then returns important review items such as "personal information protection measures" and "copyright confirmation" as analysis results.

[0933] Step 4: Generate and provide review documentation

[0934] The server creates an inspection document based on the inspection items and concerns obtained from the generative AI model, and provides the generated inspection document to the user's device and inspection department.

[0935] Input: Analysis results of the generative AI model (evaluation items and concerns)

[0936] Output: Generated audit document

[0937] Specific operation: Based on the analysis results, the server generates a review document in PDF format, including information on "personal information protection measures," "copyright confirmation," and "legality of educational content," and provides it to the user and review department. For example, the review document can be sent via email or the system's notification function.

[0938] Step 5: Feedback and response to review results

[0939] The review department conducts a detailed review based on the provided review documents. During this process, they check for any necessary corrections or additional information and provide feedback. The user receives the feedback, takes the necessary action, and updates the review document to reflect the corrections and additional information. The updated review document is sent back to the server for re-review.

[0940] Input: Review documents provided, feedback from the review department

[0941] Output: Revised and updated audit document

[0942] Specific operation: The legal department reports that the explanation of personal information protection measures is insufficient. The user adds details about the specific protection measures according to the guidelines, updates the review document on the terminal again, and sends it to the server. The server then analyzes and reviews it again.

[0943] Through the above processing steps, the system of the present invention can improve the efficiency and accuracy of the review process for new services.

[0944] (Application example 1)

[0945] 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."

[0946] Currently, when introducing new robots or adding new functions to a factory, it is necessary to comply with numerous laws and company regulations, and the review process is often time-consuming and labor-intensive. Furthermore, there is no system in place to accurately identify review items and concerns and address them efficiently. As a result, the introduction process is delayed, resulting in problems such as reduced productivity.

[0947] 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.

[0948] In this invention, the server includes means for extracting inspection items and concerns based on new information and settings of factory robots and generating an inspection sheet, means for analyzing input data and extracting inspection items and concerns based on laws, regulations, and past inspection results that the generation AI has previously learned, and means for receiving feedback from the inspection department and updating the inspection sheet based on the feedback.This enables quick and accurate inspections that comply with laws, regulations, and rules when introducing new robots or adding functions to factories.

[0949] "Information input terminal" refers to a device that allows users to input information about new services or robots. Generally, this includes computers, tablets, smartphones, etc.

[0950] A "server" is a computer system on a network that receives input data and sends it to the generating AI.

[0951] "Generative AI" is an artificial intelligence that analyzes input data based on pre-trained data and extracts review items and points of concern.

[0952] "Inspection items" are specific checkpoints or requirements that must be confirmed when introducing a new service or robot or adding a new function.

[0953] "Concerns" refer to the risks and problems associated with introducing new services and robots.

[0954] The "review sheet" is a document that organizes the review items and concerns extracted by the generation AI and provides them to the review department.

[0955] The "review department" is a department within the company that reviews applications based on the provided review sheets and provides necessary feedback.

[0956] "Feedback" refers to opinions and information that the review department provides based on the review sheet and requests corrections.

[0957] The system for realizing the present invention mainly includes the following hardware and software:

[0958] Hardware used: high-performance cloud servers, desktop terminals for users to input information, tablets, and smartphones

[0959] Software used: API server built with Flask, pre-trained natural language processing model (GPT-4)

[0960] The operation of the system is as follows.

[0961] First, users input new information and settings for their factory robots, including the robot's name, function, intended location, and applicable regulations, via a desktop, tablet, or smartphone.

[0962] The device then sends the information entered by the user to the server, with the data being sent in a standard format such as JSON.

[0963] The server sends the received data to the generation AI for analysis. The generation AI model analyzes the input data based on previously learned laws and regulations, company regulations, and past inspection results, and extracts inspection items and points of concern.

[0964] Based on the analysis results of the generative AI model, the server generates an evaluation sheet, which details the extracted evaluation items and concerns. The generated evaluation sheet is provided to the user's device and the device of the evaluation department.

[0965] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The review department's feedback will be communicated to the user via the server.

[0966] The user receives the feedback, takes necessary action based on the content, and updates the evaluation sheet. The updated evaluation sheet is then sent back to the server and reanalyzed by the generative AI model.

[0967] Specific examples

[0968] For example, consider the case where a factory employee installing a new high-precision welding robot enters the following information:

[0969] Robot name: New welding robot

[0970] Function:High precision welding

[0971] Planned installation location: 2nd Factory

[0972] Related laws and regulations: Labor safety regulations, environmental protection laws

[0973] Based on the submitted information, the generative AI model extracts review items related to occupational safety regulations and environmental protection laws (e.g., measures to ensure worker safety and regulations on the emission of hazardous substances) and generates a review sheet.

[0974] Example prompts for generative AI models

[0975] Analyze information to qualify new factory robots.

[0976] Robot name: "New welding robot"

[0977] Function: "High precision welding"

[0978] Planned installation location: "Second Factory"

[0979] Related laws and regulations: "Occupational Safety Regulations" and "Environmental Protection Act"

[0980] Extract the review items and concerns and generate a review sheet.

[0981] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0982] Step 1:

[0983] Users input information, such as the name of the new robot, its functions, the planned location for its deployment, and relevant laws and regulations, using a desktop, tablet, or smartphone.

[0984] Input: New robot information (name, function, planned installation location, relevant laws and regulations)

[0985] Output: Input data (e.g., JSON format)

[0986] Step 2:

[0987] The terminal sends the entered data to the server, where it is sent using a secure protocol (e.g., HTTPS).

[0988] Input: Data entered by the user

[0989] Output: Data sent to the server

[0990] Step 3:

[0991] The server sends the received data to a generative AI model, which has been pre-trained with laws, regulations, company rules, and past review results.

[0992] Input: Data sent from the terminal

[0993] Output: Data sent to the generative AI model

[0994] Step 4:

[0995] A generative AI model analyzes input data and extracts review items and concerns, using natural language processing techniques to identify checkpoints that comply with laws, regulations, etc.

[0996] Input: Data sent from the server

[0997] Output: Analysis results (review items and concerns)

[0998] Step 5:

[0999] The server generates an evaluation sheet based on the analysis results from the AI ​​model, which details the extracted evaluation items and concerns.

[1000] Input: Analysis results from a generative AI model

[1001] Output: Review sheet

[1002] Step 6:

[1003] The server provides the generated review sheet to the user's terminal and the terminal of the review department. The review sheet is often provided in PDF or HTML format.

[1004] Input: Generated review sheet

[1005] Output: Terminal and review sheet provided to the review department

[1006] Step 7:

[1007] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information.

[1008] Input: Review sheet

[1009] Output: Feedback

[1010] Step 8:

[1011] The user receives the feedback, takes necessary action based on the content, and updates the evaluation sheet. The updated evaluation sheet is then sent back to the server.

[1012] Input: Feedback from the review department

[1013] Output: Updated review sheet

[1014] Step 9:

[1015] The server sends the updated review sheet back to the generative AI model for re-analysis, and if necessary, repeats the process.

[1016] Input: Updated review sheet

[1017] Output: Reparsed review sheet

[1018] 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.

[1019] The present invention relates to a system and program for efficiently and accurately reviewing new service development, taking into account laws and regulations, company regulations, and past review results, while recognizing user emotions and providing further interactive feedback. This system includes a terminal for inputting information, a server that receives the input data and sends it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, and an emotion engine that recognizes user emotions.

[1020] Program processing explanation

[1021] The program of this system operates as follows.

[1022] A. User Input Processing

[1023] The user enters information about the new service into the terminal. Specifically, the user enters the name of the new service, its purpose, target customers, the functions it will provide, and any related laws and regulations through a form. The emotion engine then obtains emotion data from the user's input and actions.

[1024] Example: A user inputs information about an "online education platform." For example, the name may be "online education platform," the purpose may be "to improve learning outcomes for junior high school students," and the functions provided may be "video lessons, learning material downloads, and rank tests." The emotion engine analyzes the user's input speed and keystroke patterns to estimate the user's emotions (e.g., excitement, impatience).

[1025] B. Data Transmission and Emotion Transmission

[1026] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[1027] C. Analysis and Extraction

[1028] The server receives the data sent from the device. It then sends the received new service information and emotion data to the generation AI. The generation AI analyzes the input data based on previously learned laws and regulations, company regulations, past review results, and emotion data, and extracts review items and concerns.

[1029] Example: The server sends data from an "online education platform" and user emotional data to a generation AI, which then extracts concerns about "personal information protection measures" and "copyright confirmation," as well as "excessive expectations for specific functions" if the user is excited.

[1030] D. Generating and providing review sheets

[1031] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[1032] Example: The server creates an evaluation sheet that includes personal information protection measures, copyright confirmation, legality of the training content, and "excessive expectations for specific functions," and shares it with the user and the legal department.

[1033] E. Feedback and Response to Review Results

[1034] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on the feedback, update the review sheet, and submit it again to the server to complete the review process.

[1035] Example: The legal department makes specific recommendations regarding "failure to confirm safety measures for personal information protection," and the user takes action based on those recommendations. After that, the updated information is re-entered into the system and the review sheet is updated.

[1036] Specific processing flow

[1037] The addition of an emotion engine to the system of the present invention enables interactive feedback that takes into account the user's emotions, thereby speeding up and improving the accuracy of the review process, and thereby realizing a more user-friendly review process.

[1038] As described above, the system of the present invention not only improves the efficiency and accuracy of the review of new services, but also recognizes the user's emotions, making it possible to provide more appropriate feedback.

[1039] The processing flow will be explained below.

[1040] Step 1:

[1041] The user opens the information input form for the new service on their device. In the form, they enter the name of the new service, its purpose, target customers, the functions it will provide, and any relevant laws and regulations. After completing the input, they click the send button to send the information to the server.

[1042] Example: A user enters information about an "online education platform." For example, the name may be "online education platform," the purpose may be "to improve learning effectiveness for junior high school students," and the functions provided may be "video lessons, learning material downloads, and ranking tests." Furthermore, while the user is entering information, the emotion engine obtains emotion data from the input speed and keystrokes.

[1043] Step 2:

[1044] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[1045] Example: The device converts information about the "online education platform" and the user's emotional data into JSON format and sends it to the server.

[1046] Step 3:

[1047] The server receives the JSON data sent from the device. After receiving the data, the server analyzes it and stores it in its internal database. After storing it, the server prepares to send the data and emotion data to the generation AI.

[1048] Example: The server stores the information and emotional data of the "online education platform" received from the device in a database.

[1049] Step 4:

[1050] The server sends the saved data and emotion data to the generation AI's API, which then begins analyzing the input data.

[1051] Example: The server sends information and emotional data from the "online education platform" to the generation AI, which then begins analysis.

[1052] Step 5:

[1053] The AI ​​analyzes the submitted data based on pre-trained laws, company regulations, past review results, and emotional data, and extracts review items and points of concern as a result of the analysis.

[1054] Example: Generative AI analyzes information on an "online education platform" and, in addition to "personal information protection measures" and "copyright confirmation," extracts "excessive expectations for certain features" as concerns if the user is excited.

[1055] Step 6:

[1056] The server receives the analysis results returned by the generation AI. It generates an evaluation sheet based on the received analysis results. The evaluation sheet lists the extracted evaluation items and concerns.

[1057] Example: The server creates a review sheet that includes personal information protection measures, copyright confirmation, and "excessive expectations for specific features."

[1058] Step 7:

[1059] The server then initiates a procedure to provide the generated review sheet to the user's terminal and the review department, specifically by attaching it to an email or via a specialized web interface.

[1060] Example: The server sends the review sheet to the user and the review department by email.

[1061] Step 8:

[1062] The user receives and checks the review sheet provided via the terminal. The sheet is also provided to the review department, and each department begins their review.

[1063] Example: The user reviews the provided review sheet, and the legal department also receives the same sheet and reviews it.

[1064] Step 9:

[1065] The review department checks the details of the new service based on the review sheet and provides feedback on any necessary corrections or additional information, which is then sent to the user and the server.

[1066] Example: The legal department points out that "safety measures for personal information protection have not been confirmed" and sends this information to the user and server as feedback.

[1067] Step 10:

[1068] The user receives the feedback and takes any necessary action, after which the user re-enters the corrected information into the system and submits it to the server.

[1069] Example: The user takes the necessary action based on the legal department's feedback, re-enters the corrected information into the system, and submits it to the server.

[1070] Step 11:

[1071] The server then sends the corrected information and emotion data it has received back to the AI, and reanalyzes it as necessary. The review sheet is updated based on the analysis results.

[1072] Example: The server sends the corrected information and newly acquired emotion data to the generation AI, which then reanalyzes and updates the review sheet.

[1073] Step 12:

[1074] The server again provides the updated review sheet to the user and the review department for final confirmation and approval.

[1075] Example: The server sends the updated review sheet again to the user and the review department for final confirmation.

[1076] The above is a detailed processing flow of the new service review assistance system that combines an emotion engine. This step not only speeds up and improves the accuracy of the review, but also enables interactive feedback that takes the user's emotions into consideration.

[1077] Example 2

[1078] 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."

[1079] The review system for the previous new service took into account laws, company regulations, and past review results, but did not provide feedback that took user emotions into account, making the review process unfriendly and making it difficult to conduct a fast and accurate review.In addition, the lack of an interactive review process that reflected user emotions made improving user satisfaction a challenge.

[1080] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1081] In this invention, the server includes means for extracting review items and concerns from the results of the analysis by the generation AI, including the user's emotional data acquired by the emotion engine, and generating a review sheet, means for providing the generated review sheet to the terminal and the review department, and means for receiving feedback from the review department and updating the review sheet based on the feedback, thereby enabling a fast and accurate review that takes into account the user's emotional data.

[1082] The "terminal for inputting information" refers to a device such as a computer or smartphone that a user uses to input information about a new service.

[1083] The "server" is a high-performance computer system that transmits data received from the terminal to the generation AI and receives the analysis results from the generation AI.

[1084] "Generative AI" is an artificial intelligence model that analyzes laws and regulations, internal regulations, past judgment results, and emotional data that it has previously studied, and extracts review items and points of concern.

[1085] The "emotion engine" is a software module that analyzes user input and operation data in real time and generates user emotion data.

[1086] "Review items" are the elements and criteria that the generating AI analyzes the input data and determines to be essential for review.

[1087] "Concerns" are issues that the generating AI has identified from its analysis results that could pose problems or risks during the review process.

[1088] The "review sheet" is a document that summarizes the review items and concerns extracted by the generation AI and is used to review new services.

[1089] "Feedback" refers to a response such as corrections or additional information provided to the user after the review department makes a judgment based on the review sheet.

[1090] "Rules" is a general term for laws, regulations, and internal company rules and guidelines.

[1091] "Internal regulations" refer to rules and policies that must be followed within an organization.

[1092] "Past judgment results" refers to data and records relating to the results of past inspections.

[1093] "Emotion data" is data relating to the user's emotional state analyzed by the emotion engine.

[1094] This invention is a system that not only considers laws and regulations, company regulations, and past review results when developing new services, but also performs efficient and accurate reviews and provides interactive feedback by recognizing the user's emotions. This system includes a terminal for inputting information, a server that receives the input data and sends it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, and an emotion engine that recognizes the user's emotions.

[1095] Hardware and software used

[1096] Device: A computer or smartphone is used by users to enter information, such as the name of the new service, its purpose, target customers, the functions it provides, and relevant laws and regulations, through a web form.

[1097] Server: A high-performance server receives data, communicates with the AI, and generates the evaluation sheet. The server can use web server software such as Apache or NGINX.

[1098] Generative AI: An artificial intelligence model that performs analysis based on pre-trained data. For example, analysis is performed using a large-scale language model such as GPT-4.

[1099] Emotion engine: A software module that analyzes a user's emotions in real time. Specifically, it is emotion recognition software that analyzes input speed, keystroke patterns, etc.

[1100] Program processing overview

[1101] The program of this system operates as follows.

[1102] User Input Processing

[1103] The user inputs information about the new service into the device. This input includes the name of the new service, its purpose, target customers, the functions it provides, and information about related laws and regulations. The emotion engine then analyzes the user's input and operation data in real time to generate emotion data.

[1104] Data transmission and emotion transmission

[1105] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[1106] Parsing and Extraction

[1107] The server receives the data sent from the device. It then sends the received new service information and emotion data to the generation AI. The generation AI analyzes the input data based on previously learned laws and regulations, company regulations, past review results, and emotion data, and extracts review items and concerns.

[1108] Generation and provision of review sheets

[1109] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[1110] Feedback and Updates

[1111] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will receive the feedback, take the necessary action, update the review sheet, and send it back to the server.

[1112] Specific processing examples

[1113] A user inputs information about an "online education platform." For example, the name is "online education platform," the purpose is "to improve learning effectiveness for junior high school students," and the functions provided are "video lessons, learning material downloads, and rank tests." The emotion engine analyzes the user's input speed and keystroke patterns to estimate emotions such as "excitement" and "expectation."

[1114] The server receives new service information and emotion data sent from the device and sends it to the generation AI, which then extracts review items such as "personal information protection" and "copyright confirmation" and identifies "excessive expectations for specific functions" as a concern.

[1115] The server then creates an assessment sheet based on the assessment items and concerns, and provides it to the user's device and the assessment department. The legal department reviews the assessment sheet and provides specific feedback to the user, such as "personal information protection measures not confirmed." The user then takes action based on this feedback, re-enters the updated information into the system, and updates the assessment sheet.

[1116] Prompt Sentence Examples

[1117] "We'd like you to review a new online education platform. Its name is 'Online Education Platform,' its purpose is 'to improve learning outcomes for junior high school students,' and its functions are 'video lessons, learning material downloads, and rank tests.' Please identify review items and concerns based on laws and regulations, company regulations, past review results, and user sentiment."

[1118] This not only enables the system of the present invention to streamline and improve the accuracy of the review of new services, but also to provide more appropriate feedback by recognizing the user's emotions.

[1119] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1120] Step 1:

[1121] The user inputs information about the new service into the terminal.

[1122] Input includes the name of the new service, its purpose, target customers, the features it provides, and information on relevant laws and regulations. The emotion engine analyzes this input and operation data in real time to generate user emotion data.

[1123] Input: New service information (name, purpose, target customers, provided functions, relevant laws and regulations)

[1124] Data processing: The emotion engine analyzes input speed and keystroke patterns to generate emotion data.

[1125] Output: Input new service information, user emotion data (e.g., excitement, anticipation)

[1126] Step 2:

[1127] The terminal converts the data entered by the user into JSON format.

[1128] The converted data includes information about the new service and emotion data, and is sent to the server.

[1129] Input: New service information and emotion data entered by the user

[1130] Data processing: Convert new service information and emotion data into JSON format

[1131] Output: JSON format data

[1132] Step 3:

[1133] The server receives the JSON data sent from the terminal.

[1134] The received data is sent to the generation AI, which analyzes the input data and extracts review items and concerns based on previously studied laws and regulations, company regulations, past review results, and emotional data.

[1135] Input: New service information and emotion data in JSON format sent from the device

[1136] Data processing: Generative AI analyzes JSON data and extracts review items and concerns

[1137] Output: Extracted review items and concerns

[1138] Step 4:

[1139] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI.

[1140] The generated review sheet is provided to the user's terminal and the review department.

[1141] Input: Review items and concerns obtained from the generative AI

[1142] Data processing: Create an evaluation sheet by combining the evaluation items and concerns.

[1143] Output: Review sheet

[1144] Step 5:

[1145] The review department will conduct the review based on the review sheet provided.

[1146] Generate feedback and notify the user with any necessary corrections or additional information.

[1147] Input: Provided review sheet

[1148] Data processing: Check the review contents and make corrections or add additional information

[1149] Output: Feedback

[1150] Step 6:

[1151] The user makes corrections based on the feedback received.

[1152] The corrected information is re-entered into the system and the updated review sheet is sent to the server.

[1153] Input: Feedback

[1154] Data processing: Modify new service information based on feedback

[1155] Output: Revised new service information

[1156] Step 7:

[1157] The server receives the retransmitted data and retransmits it to the generating AI.

[1158] The generating AI will reanalyze and update if any new review items or concerns arise.

[1159] Input: Revised new service information

[1160] Data processing: Generative AI reanalyzes data and updates the review items and concerns.

[1161] Output: Updated review criteria and concerns

[1162] This results in a user-friendly, efficient and accurate review process.

[1163] (Application example 2)

[1164] 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."

[1165] Introducing or modifying new production lines or work processes in factories requires compliance with laws, regulations, and company rules, and therefore screening is essential. However, conventional screening systems rely on the judgment of personnel, which can be inefficient and time-consuming. Furthermore, because they do not take user feelings into consideration, feedback can be inappropriate. This can delay the implementation process and have a negative impact on production efficiency and safety. Therefore, there is a need for a system that improves the efficiency and accuracy of screening, as well as the user experience.

[1166] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1167] In this invention, the server includes a terminal for inputting information, a means for receiving data input from the terminal and sending it to the generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, an emotion engine for recognizing the user's emotions, and a means for generating interactive feedback taking the user's emotion data into consideration. This not only improves the efficiency and accuracy of the review, but also makes it possible to provide appropriate feedback that takes the user's emotions into consideration.

[1168] The "information input terminal" is a device that allows a user to input information about a new production line or work process.

[1169] "Generative AI" is an artificial intelligence system that analyzes input data based on previously learned laws and regulations, company regulations, and past review results, and extracts review items and points of concern.

[1170] A "server" is a computer system that receives data entered from a terminal and sends it to the generation AI.

[1171] The "means of generating an evaluation sheet" refers to the process of compiling evaluation items and concerns from the results of the analysis by the generation AI and creating a final evaluation sheet.

[1172] The "review department" is a department that reviews the application based on the generated review sheet and provides necessary corrections and additional information as feedback.

[1173] An "emotion engine" is a system that recognizes emotions from user input and operation data and acquires emotion data.

[1174] The "means for generating interactive feedback" is a process that takes into account the user's emotional data and generates and provides appropriate feedback.

[1175] The present invention provides a system for efficiently and accurately reviewing the introduction or modification of new production lines or work processes in factories. The system includes a terminal for inputting information, a server that receives the data input from the terminal and sends it to a generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating a review sheet, and a means for providing the generated review sheet to the terminal and the review department. The system also includes an emotion engine that recognizes user emotions and a means for generating interactive feedback taking into account the user's emotion data.

[1176] Program processing explanation

[1177] The user uses a terminal to input information related to a new production line or work process. This terminal can be a desktop computer, tablet, or smartphone. The input information is sent to a server. Upon receiving this data, the server sends it to a generative AI model. The generative AI model analyzes the input data based on previously learned laws and regulations, company regulations, and past review results, and extracts review items and concerns. Furthermore, an emotion engine recognizes emotions from the user's input and operation data, and acquires emotional data.

[1178] Based on the analysis results of the generation AI, the server generates an evaluation sheet. The generated evaluation sheet is sent back to the terminal and provided to the evaluation department. The terminal receives feedback from the evaluation department, sends it to the server, and updates the evaluation sheet.

[1179] As a concrete example, consider the case where a user is installing a new production line. The user inputs information about the "new assembly line" into the terminal. Specifically, the information entered includes the name "new assembly line," the purpose "improving production efficiency," the functions provided "automated machinery, quality inspection system," and related laws and regulations "Occupational Safety and Health Act, Product Liability Act." At this stage, the emotion engine obtains emotion data from the user's input speed, keystroke patterns, and facial expressions, and sends it to the server.

[1180] The generative AI model analyzes this data and extracts review items such as "personal information protection measures" and "safety management confirmation." If the user is feeling impatient, "preventing mistakes due to excessive pressure" may also be cited as a concern. This generates a review sheet that is provided to the user's device and the review department. If feedback is received from the review department, the review sheet is updated based on that feedback. This process improves the efficiency and accuracy of reviews, and also contributes to an improved user experience.

[1181] Prompt Sentence Examples

[1182] - "Please enter information about the new assembly line."

[1183] - "Objective: Improve production efficiency"

[1184] -"Provided functions: automated machinery, quality inspection systems"

[1185] - "Related laws and regulations: Occupational Safety and Health Act, Product Liability Act"

[1186] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1187] Step 1:

[1188] The user enters information

[1189] The user uses the device to input information related to the new production line and work process. Specific input data includes the name, purpose, provided functions, relevant laws and regulations, etc. The input data is stored on the device and prepared for later transmission to the server. The emotion engine also analyzes the user's input speed and keystroke patterns to obtain the user's emotional data.

[1190] Input: Information related to the new production line and work process

[1191] Output: Input data and emotion data

[1192] Step 2:

[1193] The device sends data to the server

[1194] The device converts the data entered by the user and the acquired emotion data into JSON format and sends it to the server. This conversion process is important for maintaining data consistency.

[1195] Input: Input data and emotion data

[1196] Output: JSON format data

[1197] Step 3:

[1198] The server sends the data to the generation AI

[1199] The server sends the JSON-formatted data received from the device to the generative AI model, which then analyzes the data based on previously learned laws, regulations, company rules, and past review results.

[1200] Input: JSON format data

[1201] Output: Analysis request by the generated AI

[1202] Step 4:

[1203] Generative AI analyzes data

[1204] The generative AI model analyzes the received data and extracts review items and concerns, while also taking into account the user's emotional data to identify additional emotion-based concerns and warnings.

[1205] Input: Analysis request by the generated AI

[1206] Output: List of review items and concerns

[1207] Step 5:

[1208] The server generates the review sheet

[1209] The server generates an evaluation sheet based on the list of evaluation items and concerns obtained from the generation AI. The evaluation sheet includes individual evaluation items and their corresponding concerns.

[1210] Input: List of review items and concerns

[1211] Output: Review sheet

[1212] Step 6:

[1213] The server provides the review sheet to the terminal and the review department.

[1214] The server provides the generated review sheet to the user's terminal and the review department, which allows both the user and the reviewer to check the review sheet.

[1215] Input: Review sheet

[1216] Output: Provided to the user's terminal and the review department

[1217] Step 7:

[1218] Receive and respond to feedback from the review department

[1219] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on this feedback and re-enter the updated information into the system.

[1220] Input: Feedback on the review sheet

[1221] Output: Updated information

[1222] Step 8:

[1223] The server updates the review sheet again and provides

[1224] The server updates the review sheet again based on the updated information and provides it again to the user and the review department, thereby completing the review process.

[1225] Input: Updated information

[1226] Output: Updated review sheet

[1227] Through these steps, the introduction and modification of new production lines and work processes in factories can be reviewed efficiently and accurately.

[1228] 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.

[1229] 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.

[1230] 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.

[1231] [Fourth embodiment]

[1232] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1233] 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.

[1234] 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).

[1235] 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.

[1236] 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.

[1237] 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).

[1238] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1239] 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.

[1240] 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.

[1241] 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.

[1242] 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.

[1243] 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.

[1244] 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."

[1245] This invention relates to a system and its program for efficiently and accurately reviewing new service development, taking into consideration laws and regulations, company regulations, and past review results. This system includes a terminal for inputting information, a server for receiving the input data and sending it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, and a means for providing the generated review sheet to the terminal and the review department.

[1246] Program processing explanation

[1247] The program of this system operates as follows.

[1248] A. User Input Processing

[1249] The user enters information about the new service into the terminal, specifically, the name of the new service, its purpose, target customers, the functions it provides, and data on related laws and regulations through a form.

[1250] Example: A user enters information about an "online education platform." For example, the name could be "online education platform," the purpose could be "to improve learning outcomes for junior high school students," and the functions provided could be "video lessons, downloading teaching materials, and ranking tests."

[1251] B. Data Transmission

[1252] The terminal sends the information entered by the user to the server. The data is sent in JSON format or similar, and the server receives it.

[1253] C. Analysis and Extraction

[1254] The server sends the received data to the generation AI, which analyzes the input data based on laws and regulations, company regulations, and past review results that it has previously studied, and extracts review items and points of concern.

[1255] Example: The server sends data from an "online education platform" to a generation AI, which then extracts review items such as "personal information protection measures" and "copyright confirmation."

[1256] D. Generating and providing review sheets

[1257] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[1258] Example: The server creates an inspection sheet that includes personal information protection measures, copyright confirmation, and the legality of the educational content, and shares it with the user and the legal department.

[1259] E. Feedback and Response to Review Results

[1260] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on the feedback and update the review sheet. The updated review sheet will be sent back to the server for review.

[1261] Example: The legal department points out that "safety measures for personal information protection have not been confirmed," and the user takes action in accordance with the guidelines and resubmits the sheet.

[1262] Specific processing flow

[1263] In the system of the present invention, the examination is carried out through the following specific processing flow.

[1264] 1. The user enters new service information from the terminal.

[1265] 2. The terminal sends the entered information to the server.

[1266] 3. The server sends the received information to the generation AI for analysis.

[1267] 4. The generation AI returns the analysis results to the server.

[1268] 5. The server generates the review sheet and provides it to the terminal and the review department.

[1269] 6. The review department provides feedback and the user responds.

[1270] As described above, the system of the present invention can improve the efficiency and accuracy of the examination of new services.

[1271] The processing flow will be explained below.

[1272] Step 1:

[1273] The user opens the information input form for the new service on their device. In the form, they enter the name of the new service, its purpose, target customers, the functions it provides, and any relevant laws and regulations. After completing the input, they click the send button to send the information to the server.

[1274] Step 2:

[1275] The terminal converts the data entered by the user into JSON format, and then makes an API request to the server and sends the data to the server.

[1276] Step 3:

[1277] The server receives the JSON data sent from the device. After receiving it, the server analyzes the data and stores it in an internal database. After storing it, the server prepares to send the data to the generation AI.

[1278] Step 4:

[1279] The server sends the saved data to the AI's API, which then begins analyzing the data.

[1280] Step 5:

[1281] The AI ​​analyzes the submitted data based on previously learned laws, company regulations, and past review results, and extracts review items and points of concern as a result of the analysis.

[1282] Step 6:

[1283] The server receives the analysis results returned by the generation AI. It generates an evaluation sheet based on the received analysis results. The evaluation sheet lists the extracted evaluation items and concerns.

[1284] Step 7:

[1285] The server then initiates a procedure to provide the generated review sheet to the user's terminal and the review department, specifically by attaching it to an email or via a specialized web interface.

[1286] Step 8:

[1287] The user receives and checks the review sheet provided via the terminal. The sheet is also provided to the review department, and each department begins their review.

[1288] Step 9:

[1289] The review department checks the details of the new service based on the review sheet and provides feedback on any necessary corrections or additional information, which is then sent to the user and the server.

[1290] Step 10:

[1291] The user receives the feedback and takes any necessary action, after which the user re-enters the corrected information into the system and submits it to the server.

[1292] Step 11:

[1293] The server then sends the corrected information received again to the generation AI, which reanalyzes it as necessary, and updates the review sheet based on the analysis results.

[1294] Step 12:

[1295] The server again provides the updated review sheet to the user and the review department for final confirmation and approval.

[1296] This is the detailed process flow of the new service examination assistance system. This step makes it possible to speed up examinations and improve their accuracy.

[1297] Example 1

[1298] 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."

[1299] Conventionally, when developing a new service, a review is conducted taking into account laws and regulations, internal company rules, and past review results. However, this process is laborious and time-consuming, and has problems with inefficiency and inaccuracy. In addition, specialized knowledge is required to accurately identify review items and concerns, placing a heavy burden on human resources. There was a need for a system that could solve these issues and review new services efficiently and accurately.

[1300] 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.

[1301] In this invention, the server includes a device for inputting information, a means for receiving data input from the device and sending it to the generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating review documents, a means for providing the generated review documents to the device and the review department, and a means for receiving opinions from the evaluation department and updating the review documents based on the opinions. This makes it possible to streamline the review process for new services and increase accuracy.

[1302] The "device for inputting information" is a device used by the user to input information about the new service.

[1303] A "server that receives data and sends it to the generation AI" is a computer system that has the function of receiving data sent from an information input device and sending that data to the generation AI.

[1304] "Generative AI" is an artificial intelligence that analyzes data based on pre-trained laws, regulations, and past evaluation results, and extracts review items and points of concern.

[1305] "Review items" are the criteria and checkpoints necessary to evaluate and confirm new services.

[1306] "Concerns" are issues that could pose problems or risks with the new service.

[1307] A "review document" is a document containing review items and concerns created based on the results of analysis by the generation AI.

[1308] The "review department" is a department that receives the generated review documents and provides evaluation and feedback.

[1309] "Opinions from the evaluation department" refers to feedback on corrections and additional information provided by the evaluation department to the evaluation document.

[1310] "Means for updating review documents" refers to means that have the function of amending and updating review documents based on feedback from the evaluation department.

[1311] The present invention relates to a system and its program for efficiently and accurately reviewing new service development, taking into consideration laws and regulations, company regulations, and past review results. The system includes a device for inputting information, a server that receives the input data and sends it to a generative AI model, a means for extracting review items and concerns based on the results of the generative AI's analysis and generating review documents, and a means for providing the generated review documents to the device and the review department.

[1312] The user inputs information about the new service into the device. In this process, the user uses a form to enter detailed data about the new service's name, purpose, target customers, functions to be provided, and relevant laws and regulations. For example, the user might enter the name "online education platform," the purpose as "improving learning effectiveness for junior high school students," and the functions to be provided as "video lessons, learning material downloads, and ranking tests."

[1313] The device sends the information entered by the user to the server. At this time, the data is sent in a structured data format such as JSON, and the server receives this data. For example, the device sends the following data to the server in JSON format: "New service name: Online education platform, Purpose: Improving learning effectiveness for junior high school students, Functions provided: Video lessons, learning material downloads, Rank test."

[1314] The server sends the received data to a generative AI model. The generative AI model analyzes the input data based on previously learned laws, regulations, and past evaluation results, and extracts review items and concerns. For example, if the server sends the received data to the generative AI model as "New service: online education platform, purpose: improving learning effectiveness for junior high school students, provided functions: video lessons, learning material downloads, rank tests," the generative AI model will return important review items such as "personal information protection measures" and "copyright confirmation" as analysis results.

[1315] Sample prompt: Analyze the concerns regarding privacy and copyright for a new online education platform.

[1316] The server creates an inspection document based on the inspection items and concerns obtained from the generative AI model. This inspection document is provided to the user's device and the inspection department. For example, the server creates an inspection document based on the analysis results, including "personal information protection measures," "copyright confirmation," and "legality of educational content," and generates it in PDF format or similar and provides it to the user and the inspection department via email or the system's notification function.

[1317] The review department conducts a detailed review based on the review documents provided. During this process, any necessary corrections or additional information is identified. For example, the legal department may provide feedback pointing out that "the explanation regarding personal information protection measures is insufficient." The user takes the necessary action based on the feedback and updates the review document to reflect the corrections and additional information. The updated review document is then sent back to the server for re-review.

[1318] As described above, the system of the present invention can improve the efficiency and accuracy of the review process for new services.

[1319] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1320] Program processing explanation

[1321] Step 1: Process User Input

[1322] The user inputs information about the new service into the device. Specifically, the user enters detailed data about the new service's name, purpose, target customers, provided functions, and relevant laws and regulations through a form. The input data is saved in the device and prepared for the next step.

[1323] Input: New service name, purpose, target customers, provided functions, relevant laws and regulations

[1324] Output: New service information entered in the form

[1325] Specific operation: The user enters the name "online education platform" into the form on the device, enters "improving learning effectiveness for junior high school students" as the purpose, and enters "video lessons, learning material downloads, rank tests" as the functions to be provided.

[1326] Step 2: Send data

[1327] The device sends the information entered by the user to the server. In this process, the data is sent in a structured data format such as JSON, and the server receives it.

[1328] Input: New service information entered in the form

[1329] Output: JSON formatted data sent to the server

[1330] Specific operation: The device sends the following data in JSON format to the server: "New service name: Online education platform, Purpose: Improving learning effectiveness for junior high school students, Functions provided: Video lessons, downloading teaching materials, Rank test."

[1331] Step 3: Parsing and Extraction

[1332] The server sends the received data to a generative AI model, which analyzes the input data based on previously learned laws, regulations, and past evaluation results, and extracts review items and concerns. This clarifies the criteria and risks required for the review.

[1333] Input: JSON format data received by the server

[1334] Output: The assessment items and concerns returned by the generative AI model

[1335] Specific operation: The server sends the received data to the generation AI model as "New service: online education platform, purpose: improving learning effectiveness for junior high school students, provided functions: video lessons, learning material downloads, rank tests." The generation AI model then returns important review items such as "personal information protection measures" and "copyright confirmation" as analysis results.

[1336] Step 4: Generate and provide review documentation

[1337] The server creates an inspection document based on the inspection items and concerns obtained from the generative AI model, and provides the generated inspection document to the user's device and inspection department.

[1338] Input: Analysis results of the generative AI model (evaluation items and concerns)

[1339] Output: Generated audit document

[1340] Specific operation: Based on the analysis results, the server generates a review document in PDF format, including information on "personal information protection measures," "copyright confirmation," and "legality of educational content," and provides it to the user and review department. For example, the review document can be sent via email or the system's notification function.

[1341] Step 5: Feedback and response to review results

[1342] The review department conducts a detailed review based on the provided review documents. During this process, they check for any necessary corrections or additional information and provide feedback. The user receives the feedback, takes the necessary action, and updates the review document to reflect the corrections and additional information. The updated review document is sent back to the server for re-review.

[1343] Input: Review documents provided, feedback from the review department

[1344] Output: Revised and updated audit document

[1345] Specific operation: The legal department reports that the explanation of personal information protection measures is insufficient. The user adds details about the specific protection measures according to the guidelines, updates the review document on the terminal again, and sends it to the server. The server then analyzes and reviews it again.

[1346] Through the above processing steps, the system of the present invention can improve the efficiency and accuracy of the review process for new services.

[1347] (Application example 1)

[1348] 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."

[1349] Currently, when introducing new robots or adding new functions to a factory, it is necessary to comply with numerous laws and company regulations, and the review process is often time-consuming and labor-intensive. Furthermore, there is no system in place to accurately identify review items and concerns and address them efficiently. As a result, the introduction process is delayed, resulting in problems such as reduced productivity.

[1350] 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.

[1351] In this invention, the server includes means for extracting inspection items and concerns based on new information and settings of factory robots and generating an inspection sheet, means for analyzing input data and extracting inspection items and concerns based on laws, regulations, and past inspection results that the generation AI has previously learned, and means for receiving feedback from the inspection department and updating the inspection sheet based on the feedback.This enables quick and accurate inspections that comply with laws, regulations, and rules when introducing new robots or adding functions to factories.

[1352] "Information input terminal" refers to a device that allows users to input information about new services or robots. Generally, this includes computers, tablets, smartphones, etc.

[1353] A "server" is a computer system on a network that receives input data and sends it to the generating AI.

[1354] "Generative AI" is an artificial intelligence that analyzes input data based on pre-trained data and extracts review items and points of concern.

[1355] "Inspection items" are specific checkpoints or requirements that must be confirmed when introducing a new service or robot or adding a new function.

[1356] "Concerns" refer to the risks and problems associated with introducing new services and robots.

[1357] The "review sheet" is a document that organizes the review items and concerns extracted by the generation AI and provides them to the review department.

[1358] The "review department" is a department within the company that reviews applications based on the provided review sheets and provides necessary feedback.

[1359] "Feedback" refers to opinions and information that the review department provides based on the review sheet and requests corrections.

[1360] The system for realizing the present invention mainly includes the following hardware and software:

[1361] Hardware used: high-performance cloud servers, desktop terminals for users to input information, tablets, and smartphones

[1362] Software used: API server built with Flask, pre-trained natural language processing model (GPT-4)

[1363] The operation of the system is as follows.

[1364] First, users input new information and settings for their factory robots, including the robot's name, function, intended location, and applicable regulations, via a desktop, tablet, or smartphone.

[1365] The device then sends the information entered by the user to the server, with the data being sent in a standard format such as JSON.

[1366] The server sends the received data to the generation AI for analysis. The generation AI model analyzes the input data based on previously learned laws and regulations, company regulations, and past inspection results, and extracts inspection items and points of concern.

[1367] Based on the analysis results of the generative AI model, the server generates an evaluation sheet, which details the extracted evaluation items and concerns. The generated evaluation sheet is provided to the user's device and the device of the evaluation department.

[1368] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The review department's feedback will be communicated to the user via the server.

[1369] The user receives the feedback, takes necessary action based on the content, and updates the evaluation sheet. The updated evaluation sheet is then sent back to the server and reanalyzed by the generative AI model.

[1370] Specific examples

[1371] For example, consider the case where a factory employee installing a new high-precision welding robot enters the following information:

[1372] Robot name: New welding robot

[1373] Function:High precision welding

[1374] Planned installation location: 2nd Factory

[1375] Related laws and regulations: Labor safety regulations, environmental protection laws

[1376] Based on the submitted information, the generative AI model extracts review items related to occupational safety regulations and environmental protection laws (e.g., measures to ensure worker safety and regulations on the emission of hazardous substances) and generates a review sheet.

[1377] Example prompts for generative AI models

[1378] Analyze information to qualify new factory robots.

[1379] Robot name: "New welding robot"

[1380] Function: "High precision welding"

[1381] Planned installation location: "Second Factory"

[1382] Related laws and regulations: "Occupational Safety Regulations" and "Environmental Protection Act"

[1383] Extract the review items and concerns and generate a review sheet.

[1384] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1385] Step 1:

[1386] Users input information, such as the name of the new robot, its functions, the planned location for its deployment, and relevant laws and regulations, using a desktop, tablet, or smartphone.

[1387] Input: New robot information (name, function, planned installation location, relevant laws and regulations)

[1388] Output: Input data (e.g., JSON format)

[1389] Step 2:

[1390] The terminal sends the entered data to the server, where it is sent using a secure protocol (e.g., HTTPS).

[1391] Input: Data entered by the user

[1392] Output: Data sent to the server

[1393] Step 3:

[1394] The server sends the received data to a generative AI model, which has been pre-trained with laws, regulations, company rules, and past review results.

[1395] Input: Data sent from the terminal

[1396] Output: Data sent to the generative AI model

[1397] Step 4:

[1398] A generative AI model analyzes input data and extracts review items and concerns, using natural language processing techniques to identify checkpoints that comply with laws, regulations, etc.

[1399] Input: Data sent from the server

[1400] Output: Analysis results (review items and concerns)

[1401] Step 5:

[1402] The server generates an evaluation sheet based on the analysis results from the AI ​​model, which details the extracted evaluation items and concerns.

[1403] Input: Analysis results from a generative AI model

[1404] Output: Review sheet

[1405] Step 6:

[1406] The server provides the generated review sheet to the user's terminal and the terminal of the review department. The review sheet is often provided in PDF or HTML format.

[1407] Input: Generated review sheet

[1408] Output: Terminal and review sheet provided to the review department

[1409] Step 7:

[1410] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information.

[1411] Input: Review sheet

[1412] Output: Feedback

[1413] Step 8:

[1414] The user receives the feedback, takes necessary action based on the content, and updates the evaluation sheet. The updated evaluation sheet is then sent back to the server.

[1415] Input: Feedback from the review department

[1416] Output: Updated review sheet

[1417] Step 9:

[1418] The server sends the updated review sheet back to the generative AI model for re-analysis, and if necessary, repeats the process.

[1419] Input: Updated review sheet

[1420] Output: Reparsed review sheet

[1421] 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.

[1422] The present invention relates to a system and program for efficiently and accurately reviewing new service development, taking into account laws and regulations, company regulations, and past review results, while recognizing user emotions and providing further interactive feedback. This system includes a terminal for inputting information, a server that receives the input data and sends it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, and an emotion engine that recognizes user emotions.

[1423] Program processing explanation

[1424] The program of this system operates as follows.

[1425] A. User Input Processing

[1426] The user enters information about the new service into the terminal. Specifically, the user enters the name of the new service, its purpose, target customers, the functions it will provide, and any related laws and regulations through a form. The emotion engine then obtains emotion data from the user's input and actions.

[1427] Example: A user inputs information about an "online education platform." For example, the name may be "online education platform," the purpose may be "to improve learning outcomes for junior high school students," and the functions provided may be "video lessons, learning material downloads, and rank tests." The emotion engine analyzes the user's input speed and keystroke patterns to estimate the user's emotions (e.g., excitement, impatience).

[1428] B. Data Transmission and Emotion Transmission

[1429] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[1430] C. Analysis and Extraction

[1431] The server receives the data sent from the device. It then sends the received new service information and emotion data to the generation AI. The generation AI analyzes the input data based on previously learned laws and regulations, company regulations, past review results, and emotion data, and extracts review items and concerns.

[1432] Example: The server sends data from an "online education platform" and user emotional data to a generation AI, which then extracts concerns about "personal information protection measures" and "copyright confirmation," as well as "excessive expectations for specific functions" if the user is excited.

[1433] D. Generating and providing review sheets

[1434] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[1435] Example: The server creates an evaluation sheet that includes personal information protection measures, copyright confirmation, legality of the training content, and "excessive expectations for specific functions," and shares it with the user and the legal department.

[1436] E. Feedback and Response to Review Results

[1437] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on the feedback, update the review sheet, and submit it again to the server to complete the review process.

[1438] Example: The legal department makes specific suggestions about "failure to confirm safety measures for personal information protection," and the user takes action based on those suggestions. After that, the updated information is re-entered into the system and the review sheet is updated.

[1439] Specific processing flow

[1440] The addition of an emotion engine to the system of the present invention enables interactive feedback that takes into account the user's emotions, thereby speeding up and improving the accuracy of the review process, and thereby realizing a more user-friendly review process.

[1441] As described above, the system of the present invention not only improves the efficiency and accuracy of the review of new services, but also recognizes the user's emotions, making it possible to provide more appropriate feedback.

[1442] The processing flow will be explained below.

[1443] Step 1:

[1444] The user opens the information input form for the new service on their device. In the form, they enter the name of the new service, its purpose, target customers, the functions it provides, and any relevant laws and regulations. After completing the input, they click the send button to send the information to the server.

[1445] Example: A user enters information about an "online education platform." For example, the name may be "online education platform," the purpose may be "to improve learning effectiveness for junior high school students," and the functions provided may be "video lessons, learning material downloads, and ranking tests." Furthermore, while the user is entering information, the emotion engine obtains emotion data from the input speed and keystrokes.

[1446] Step 2:

[1447] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[1448] Example: The device converts information about the "online education platform" and the user's emotional data into JSON format and sends it to the server.

[1449] Step 3:

[1450] The server receives the JSON data sent from the device. After receiving the data, the server analyzes it and stores it in its internal database. After storing it, the server prepares to send the data and emotion data to the generation AI.

[1451] Example: The server stores the information and emotional data of the "online education platform" received from the device in a database.

[1452] Step 4:

[1453] The server sends the saved data and emotion data to the generation AI's API, which then begins analyzing the input data.

[1454] Example: The server sends information and emotional data from the "online education platform" to the generation AI, which then begins analysis.

[1455] Step 5:

[1456] The AI ​​analyzes the submitted data based on pre-trained laws, company regulations, past review results, and emotional data, and extracts review items and points of concern as a result of the analysis.

[1457] Example: Generative AI analyzes information on an "online education platform" and, in addition to "personal information protection measures" and "copyright confirmation," extracts "excessive expectations for certain features" as concerns if the user is excited.

[1458] Step 6:

[1459] The server receives the analysis results returned by the generation AI. It generates an evaluation sheet based on the received analysis results. The evaluation sheet lists the extracted evaluation items and concerns.

[1460] Example: The server creates a review sheet that includes personal information protection measures, copyright confirmation, and "excessive expectations for specific features."

[1461] Step 7:

[1462] The server then initiates a procedure to provide the generated review sheet to the user's terminal and the review department, specifically by attaching it to an email or via a specialized web interface.

[1463] Example: The server sends the review sheet to the user and the review department by email.

[1464] Step 8:

[1465] The user receives and checks the review sheet provided via the terminal. The sheet is also provided to the review department, and each department begins their review.

[1466] Example: The user reviews the provided review sheet, and the legal department also receives the same sheet and reviews it.

[1467] Step 9:

[1468] The review department checks the details of the new service based on the review sheet and provides feedback on any necessary corrections or additional information, which is then sent to the user and the server.

[1469] Example: The legal department points out that "safety measures for personal information protection have not been confirmed" and sends this information to the user and server as feedback.

[1470] Step 10:

[1471] The user receives the feedback and takes any necessary action, after which the user re-enters the corrected information into the system and submits it to the server.

[1472] Example: The user takes the necessary action based on the legal department's feedback, re-enters the corrected information into the system, and submits it to the server.

[1473] Step 11:

[1474] The server then sends the corrected information and emotion data it has received back to the AI, and reanalyzes it as necessary. The review sheet is updated based on the analysis results.

[1475] Example: The server sends the corrected information and newly acquired emotion data to the generation AI, which then reanalyzes and updates the review sheet.

[1476] Step 12:

[1477] The server again provides the updated review sheet to the user and the review department for final confirmation and approval.

[1478] Example: The server sends the updated review sheet again to the user and the review department for final confirmation.

[1479] The above is a detailed processing flow of the new service review assistance system that combines an emotion engine. This step not only speeds up and improves the accuracy of the review, but also enables interactive feedback that takes the user's emotions into consideration.

[1480] Example 2

[1481] 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."

[1482] The review system for the previous new service took into account laws, company regulations, and past review results, but did not provide feedback that took user emotions into account, making the review process unfriendly and making it difficult to conduct a fast and accurate review.In addition, the lack of an interactive review process that reflected user emotions made improving user satisfaction a challenge.

[1483] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1484] In this invention, the server includes means for extracting review items and concerns from the results of the analysis by the generation AI, including the user's emotional data acquired by the emotion engine, and generating a review sheet, means for providing the generated review sheet to the terminal and the review department, and means for receiving feedback from the review department and updating the review sheet based on the feedback, thereby enabling a fast and accurate review that takes into account the user's emotional data.

[1485] The "terminal for inputting information" refers to a device such as a computer or smartphone that a user uses to input information about a new service.

[1486] The "server" is a high-performance computer system that transmits data received from the terminal to the generation AI and receives the analysis results from the generation AI.

[1487] "Generative AI" is an artificial intelligence model that analyzes laws and regulations, internal regulations, past judgment results, and emotional data that it has previously studied, and extracts review items and points of concern.

[1488] The "emotion engine" is a software module that analyzes user input and operation data in real time and generates user emotion data.

[1489] "Review items" are the elements and criteria that the generating AI analyzes the input data and determines to be essential for review.

[1490] "Concerns" are issues that the generating AI has identified from its analysis results that could pose problems or risks during the review process.

[1491] The "review sheet" is a document that summarizes the review items and concerns extracted by the generation AI and is used to review new services.

[1492] "Feedback" refers to a response such as corrections or additional information provided to the user after the review department makes a judgment based on the review sheet.

[1493] "Rules" is a general term for laws, regulations, and internal company rules and guidelines.

[1494] "Internal regulations" refer to rules and policies that must be followed within an organization.

[1495] "Past judgment results" refers to data and records relating to the results of past inspections.

[1496] "Emotion data" is data relating to the user's emotional state analyzed by the emotion engine.

[1497] This invention is a system that not only considers laws and regulations, company regulations, and past review results when developing new services, but also performs efficient and accurate reviews and provides interactive feedback by recognizing the user's emotions. This system includes a terminal for inputting information, a server that receives the input data and sends it to a generation AI, a means for extracting review items and concerns based on the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, and an emotion engine that recognizes the user's emotions.

[1498] Hardware and software used

[1499] Device: A computer or smartphone is used by users to enter information, such as the name of the new service, its purpose, target customers, the functions it provides, and relevant laws and regulations, through a web form.

[1500] Server: A high-performance server receives data, communicates with the AI, and generates the evaluation sheet. The server can use web server software such as Apache or NGINX.

[1501] Generative AI: An artificial intelligence model that performs analysis based on pre-trained data. For example, analysis is performed using a large-scale language model such as GPT-4.

[1502] Emotion engine: A software module that analyzes a user's emotions in real time. Specifically, it is emotion recognition software that analyzes input speed, keystroke patterns, etc.

[1503] Program processing overview

[1504] The program of this system operates as follows.

[1505] User Input Processing

[1506] The user inputs information about the new service into the device. This input includes the name of the new service, its purpose, target customers, the functions it provides, and information about related laws and regulations. The emotion engine then analyzes the user's input and operation data in real time to generate emotion data.

[1507] Data transmission and emotion transmission

[1508] The device converts the data entered by the user into JSON format and simultaneously transmits the emotion data obtained from the emotion engine to the server.

[1509] Parsing and Extraction

[1510] The server receives the data sent from the device. It then sends the received new service information and emotion data to the generation AI. The generation AI analyzes the input data based on previously learned laws and regulations, company regulations, past review results, and emotion data, and extracts review items and concerns.

[1511] Generation and provision of review sheets

[1512] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI. The generated evaluation sheet is provided to the user's device and the evaluation department.

[1513] Feedback and Updates

[1514] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will receive the feedback, take the necessary action, update the review sheet, and send it back to the server.

[1515] Specific processing examples

[1516] A user inputs information about an "online education platform." For example, the name is "online education platform," the purpose is "to improve learning effectiveness for junior high school students," and the functions provided are "video lessons, learning material downloads, and rank tests." The emotion engine analyzes the user's input speed and keystroke patterns to estimate emotions such as "excitement" and "expectation."

[1517] The server receives new service information and emotion data sent from the device and sends it to the generation AI, which then extracts review items such as "personal information protection" and "copyright confirmation" and identifies "excessive expectations for specific functions" as a concern.

[1518] The server then creates an assessment sheet based on the assessment items and concerns, and provides it to the user's device and the assessment department. The legal department reviews the assessment sheet and provides specific feedback to the user, such as "personal information protection measures not confirmed." The user then takes action based on this feedback, re-enters the updated information into the system, and updates the assessment sheet.

[1519] Prompt Sentence Examples

[1520] "We'd like you to review a new online education platform. Its name is 'Online Education Platform,' its purpose is 'to improve learning outcomes for junior high school students,' and its functions are 'video lessons, learning material downloads, and rank tests.' Please identify review items and concerns based on laws and regulations, company regulations, past review results, and user sentiment."

[1521] As a result, the system of the present invention not only makes the screening of new services more efficient and improves accuracy, but also recognizes the user's emotions, allowing it to provide more appropriate feedback.

[1522] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1523] Step 1:

[1524] The user inputs information about the new service into the terminal.

[1525] The input includes the name of the new service, its purpose, target customers, the functions it provides, and information on relevant laws and regulations. The emotion engine analyzes this input and operation data in real time to generate user emotion data.

[1526] Input: New service information (name, purpose, target customers, provided functions, relevant laws and regulations)

[1527] Data processing: The emotion engine analyzes input speed and keystroke patterns to generate emotion data.

[1528] Output: Input new service information, user emotion data (e.g., excitement, anticipation)

[1529] Step 2:

[1530] The terminal converts the data entered by the user into JSON format.

[1531] The converted data includes information about the new service and emotion data, and is sent to the server.

[1532] Input: New service information and emotion data entered by the user

[1533] Data processing: Convert new service information and emotion data into JSON format

[1534] Output: JSON format data

[1535] Step 3:

[1536] The server receives the JSON data sent from the terminal.

[1537] The received data is sent to the generation AI, which analyzes the input data and extracts review items and concerns based on previously studied laws and regulations, company regulations, past review results, and emotional data.

[1538] Input: New service information and emotion data in JSON format sent from the device

[1539] Data processing: Generative AI analyzes JSON data and extracts review items and concerns

[1540] Output: Extracted review items and concerns

[1541] Step 4:

[1542] The server creates an evaluation sheet based on the evaluation items and concerns obtained from the generation AI.

[1543] The generated review sheet is provided to the user's terminal and the review department.

[1544] Input: Review items and concerns obtained from the generative AI

[1545] Data processing: Create an evaluation sheet by combining the evaluation items and concerns.

[1546] Output: Review sheet

[1547] Step 5:

[1548] The review department will conduct the review based on the review sheet provided.

[1549] Generate feedback and notify the user with any necessary corrections or additional information.

[1550] Input: Provided review sheet

[1551] Data processing: Check the review contents and make corrections or add additional information

[1552] Output: Feedback

[1553] Step 6:

[1554] The user makes corrections based on the feedback received.

[1555] The corrected information is re-entered into the system and the updated review sheet is sent to the server.

[1556] Input: Feedback

[1557] Data processing: Modify new service information based on feedback

[1558] Output: Revised new service information

[1559] Step 7:

[1560] The server receives the retransmitted data and retransmits it to the generating AI.

[1561] The generating AI will reanalyze and update if any new review items or concerns arise.

[1562] Input: Revised new service information

[1563] Data processing: Generative AI reanalyzes data and updates the review items and concerns.

[1564] Output: Updated review criteria and concerns

[1565] This results in a user-friendly, efficient and accurate review process.

[1566] (Application example 2)

[1567] 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."

[1568] Introducing or modifying new production lines or work processes in factories requires compliance with laws, regulations, and company rules, and therefore screening is essential. However, conventional screening systems rely on the judgment of personnel, which can be inefficient and time-consuming. Furthermore, because they do not take user feelings into consideration, feedback can be inappropriate. This can delay the implementation process and have a negative impact on production efficiency and safety. Therefore, there is a need for a system that improves the efficiency and accuracy of screening, as well as the user experience.

[1569] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1570] In this invention, the server includes a terminal for inputting information, a means for receiving data input from the terminal and sending it to the generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating a review sheet, a means for providing the generated review sheet to the terminal and the review department, an emotion engine for recognizing the user's emotions, and a means for generating interactive feedback taking the user's emotion data into consideration. This not only improves the efficiency and accuracy of the review, but also makes it possible to provide appropriate feedback that takes the user's emotions into consideration.

[1571] The "information input terminal" is a device that allows a user to input information about a new production line or work process.

[1572] "Generative AI" is an artificial intelligence system that analyzes input data based on previously learned laws and regulations, company regulations, and past review results, and extracts review items and points of concern.

[1573] A "server" is a computer system that receives data entered from a terminal and sends it to the generation AI.

[1574] The "means of generating an evaluation sheet" refers to the process of compiling evaluation items and concerns from the results of the analysis by the generation AI and creating a final evaluation sheet.

[1575] The "review department" is a department that reviews the application based on the generated review sheet and provides necessary corrections and additional information as feedback.

[1576] An "emotion engine" is a system that recognizes emotions from user input and operation data and acquires emotion data.

[1577] The "means for generating interactive feedback" is a process that takes into account the user's emotional data and generates and provides appropriate feedback.

[1578] The present invention provides a system for efficiently and accurately reviewing the introduction or modification of new production lines or work processes in factories. The system includes a terminal for inputting information, a server that receives the data input from the terminal and sends it to a generation AI, a means for extracting review items and concerns from the analysis results of the generation AI and generating a review sheet, and a means for providing the generated review sheet to the terminal and the review department. The system also includes an emotion engine that recognizes user emotions and a means for generating interactive feedback taking into account the user's emotion data.

[1579] Program processing explanation

[1580] The user uses a terminal to input information related to a new production line or work process. This terminal can be a desktop computer, tablet, or smartphone. The input information is sent to a server. Upon receiving this data, the server sends it to a generative AI model. The generative AI model analyzes the input data based on previously learned laws and regulations, company regulations, and past review results, and extracts review items and concerns. Furthermore, an emotion engine recognizes emotions from the user's input and operation data, and acquires emotional data.

[1581] Based on the analysis results of the generation AI, the server generates an evaluation sheet. The generated evaluation sheet is sent back to the terminal and provided to the evaluation department. The terminal receives feedback from the evaluation department, sends it to the server, and updates the evaluation sheet.

[1582] As a concrete example, consider the case where a user is installing a new production line. The user inputs information about the "new assembly line" into the terminal. Specifically, the information entered includes the name "new assembly line," the purpose "improving production efficiency," the functions provided "automated machinery, quality inspection system," and related laws and regulations "Occupational Safety and Health Act, Product Liability Act." At this stage, the emotion engine obtains emotion data from the user's input speed, keystroke patterns, and facial expressions, and sends it to the server.

[1583] The generative AI model analyzes this data and extracts review items such as "personal information protection measures" and "safety management confirmation." If the user is feeling impatient, "preventing mistakes due to excessive pressure" may also be cited as a concern. This generates a review sheet that is provided to the user's device and the review department. If feedback is received from the review department, the review sheet is updated based on that feedback. This process improves the efficiency and accuracy of reviews, and also contributes to an improved user experience.

[1584] Prompt Sentence Examples

[1585] - "Please enter information about the new assembly line."

[1586] - "Objective: Improve production efficiency"

[1587] -"Provided functions: automated machinery, quality inspection systems"

[1588] - "Related laws and regulations: Occupational Safety and Health Act, Product Liability Act"

[1589] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1590] Step 1:

[1591] The user enters information

[1592] The user uses the device to input information related to the new production line and work process. Specific input data includes the name, purpose, provided functions, relevant laws and regulations, etc. The input data is stored on the device and prepared for later transmission to the server. The emotion engine also analyzes the user's input speed and keystroke patterns to obtain the user's emotional data.

[1593] Input: Information related to the new production line and work process

[1594] Output: Input data and emotion data

[1595] Step 2:

[1596] The device sends data to the server

[1597] The device converts the data entered by the user and the acquired emotion data into JSON format and sends it to the server. This conversion process is important for maintaining data consistency.

[1598] Input: Input data and emotion data

[1599] Output: JSON format data

[1600] Step 3:

[1601] The server sends the data to the generation AI

[1602] The server sends the JSON-formatted data received from the device to the generative AI model, which then analyzes the data based on previously learned laws, regulations, company rules, and past review results.

[1603] Input: JSON format data

[1604] Output: Analysis request by the generated AI

[1605] Step 4:

[1606] Generative AI analyzes data

[1607] The generative AI model analyzes the received data and extracts review items and concerns, while also taking into account the user's emotional data to identify additional emotion-based concerns and warnings.

[1608] Input: Analysis request by the generated AI

[1609] Output: List of review items and concerns

[1610] Step 5:

[1611] The server generates the review sheet

[1612] The server generates an evaluation sheet based on the list of evaluation items and concerns obtained from the generation AI. The evaluation sheet includes individual evaluation items and their corresponding concerns.

[1613] Input: List of review items and concerns

[1614] Output: Review sheet

[1615] Step 6:

[1616] The server provides the review sheet to the terminal and the review department.

[1617] The server provides the generated review sheet to the user's terminal and the review department, which allows both the user and the reviewer to check the review sheet.

[1618] Input: Review sheet

[1619] Output: Provided to the user's terminal and the review department

[1620] Step 7:

[1621] Receive and respond to feedback from the review department

[1622] The review department will review the application based on the provided review sheet and provide feedback on any necessary corrections or additional information. The user will then take the necessary action based on this feedback and re-enter the updated information into the system.

[1623] Input: Feedback on the review sheet

[1624] Output: Updated information

[1625] Step 8:

[1626] The server updates the review sheet again and provides

[1627] The server updates the review sheet again based on the updated information and provides it again to the user and the review department, thereby completing the review process.

[1628] Input: Updated information

[1629] Output: Updated review sheet

[1630] Through these steps, the introduction and modification of new production lines and work processes in factories can be reviewed efficiently and accurately.

[1631] 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.

[1632] 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.

[1633] 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.

[1634] 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.

[1635] 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.

[1636] 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.

[1637] 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).

[1638] 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.

[1639] 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."

[1640] 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.

[1641] 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).

[1642] 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.

[1643] 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.

[1644] 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.

[1645] 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.

[1646] 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.

[1647] 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.

[1648] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1649] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1650] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1651] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1652] The following is further disclosed regarding the above embodiment.

[1653] (Claim 1)

[1654] A terminal for inputting information;

[1655] A server that receives data input from the terminal and transmits it to the generation AI;

[1656] A means for extracting review items and concerns from the results of the analysis by the generation AI and generating a review sheet;

[1657] A means for providing the generated examination sheet to the terminal and the examination department;

[1658] A system including:

[1659] (Claim 2)

[1660] The system of claim 1, comprising a means for analyzing input data and extracting review items and concerns based on laws and regulations, company regulations, and past review results that the generation AI has previously learned.

[1661] (Claim 3)

[1662] 10. The system of claim 1, further comprising means for receiving feedback from the review department and updating the review sheet based on said feedback.

[1663] "Example 1"

[1664] (Claim 1)

[1665] a device for inputting information;

[1666] A server that receives data input from the device and transmits it to the generation AI;

[1667] A means for extracting review items and concerns from the results of the analysis by the generation AI and generating review documents;

[1668] means for providing the generated review document to said device and review department;

[1669] A system including:

[1670] (Claim 2)

[1671] The system of claim 1, further comprising a means for analyzing input data and extracting review items and concerns based on laws, regulations, and past evaluation results that the generation AI has previously learned.

[1672] (Claim 3)

[1673] 10. The system of claim 1, further comprising means for receiving comments from the evaluation department and updating the review document based on the comments.

[1674] "Application Example 1"

[1675] (Claim 1)

[1676] A terminal for inputting information;

[1677] A server that receives data input from the terminal and transmits it to the generation AI;

[1678] A means for extracting review items and concerns from the results of the analysis by the generation AI and generating a review sheet;

[1679] A means for extracting inspection items and concerns based on new information and settings of the factory robot and generating an inspection sheet;

[1680] A means for providing the generated examination sheet to the terminal and the examination department;

[1681] A system including:

[1682] (Claim 2)

[1683] The system of claim 1, comprising a means for analyzing input data and extracting review items and concerns based on laws, regulations, and past review results that the generation AI has previously learned.

[1684] (Claim 3)

[1685] 10. The system of claim 1, further comprising means for receiving feedback from the review department and updating the review sheet based on said feedback.

[1686] "Example 2: Combining Emotion Engines"

[1687] (Claim 1)

[1688] A terminal for inputting information;

[1689] A server that receives data input from the terminal and transmits it to the generation AI;

[1690] A means for extracting review items and concerns from the results of the analysis by the generation AI, including the user's emotional data acquired by the emotion engine, and generating a review sheet;

[1691] A means for providing the generated examination sheet to the terminal and the examination department;

[1692] A system including:

[1693] (Claim 2)

[1694] The system of claim 1, further comprising a means for analyzing input data and emotional data based on rules, internal regulations, and past judgment results that the generation AI has previously learned, and extracting review items and points of concern.

[1695] (Claim 3)

[1696] 10. The system of claim 1, further comprising means for receiving feedback from the review department and updating the review sheet based on said feedback.

[1697] "Application example 2 when combining emotion engines"

[1698] (Claim 1)

[1699] A terminal for inputting information;

[1700] A server that receives data input from the terminal and transmits it to the generation AI;

[1701] A means for extracting review items and concerns from the results of the analysis by the generation AI and generating a review sheet;

[1702] A means for providing the generated examination sheet to the terminal and the examination department;

[1703] an emotion engine that recognizes the user's emotions;

[1704] means for generating interactive feedback taking into account the user's emotional data;

[1705] A system including:

[1706] (Claim 2)

[1707] The system of claim 1, comprising a means for analyzing input data and extracting review items and concerns based on laws and regulations, company regulations, and past review results that the generation AI has previously learned.

[1708] (Claim 3)

[1709] 10. The system of claim 1, further comprising means for receiving feedback from the review department and updating the review sheet based on said feedback. [Explanation of symbols]

[1710] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A terminal for inputting information; A server that receives data input from the terminal and transmits it to the generation AI; A means for extracting review items and concerns from the results of the analysis by the generation AI and generating a review sheet; A means for providing the generated examination sheet to the terminal and the examination department; A system including:

2. The system of claim 1, further comprising a means for analyzing input data and extracting review items and concerns based on laws and regulations, company regulations, and past review results that the generation AI has previously learned.

3. 2. The system of claim 1, further comprising means for receiving feedback from the review department and updating the review sheet based on said feedback.

Images