System

Abstract

A system is provided.SOLUTION: A system includes reception means, analysis means for analyzing an input idea, brush-up means for generating an improvement proposal by a plurality of algorithms having different characteristics on the basis of an analysis result, integration means for integrating the generated improvement proposals, and outputting means for outputting the integrated improvement proposal.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] Idea contests using generative AI receive a large number of submissions, but some ideas are poorly evaluated due to a lack of polishing. Participants also face difficulties in improving the quality of their ideas due to lack of time, difficulty in creating materials, or lack of someone to consult with. These issues need to be resolved to raise the overall level of the contest. [Means for solving the problem]

[0005] The present invention provides a system including a receiving means, an analysis means for analyzing input ideas, a refinement means for generating improvement proposals based on the analysis results using multiple algorithms with different characteristics, an integration means for integrating the generated improvement proposals, and an output means for outputting the integrated improvement proposals. The present invention also includes a presentation generation means for automatically generating a presentation file based on an input theme, an output means for outputting the generated presentation file, a code generation means for generating mockup code for a website or application based on input requirements, a manuscript generation means for generating an oral manuscript based on the presentation content and duration, and an evaluation means for analyzing submitted materials and virtually evaluating them. In this way, a system is realized that comprehensively supports participants and improves their evaluation in contests by providing idea refinement from various perspectives, the generation of concrete deliverables, presentation preparation, and virtual evaluation.

[0006] Understood. Below are definitions of important terms contained in the claims:

[0007] The "receiving means" is a device or program that has the function of receiving data or instructions input by a user.

[0008] "Analysis means" refers to a device or program used to analyze received data and understand its contents.

[0009] The "brush-up means" is a device or program that has the function of generating improvement proposals for an idea using a plurality of different algorithms based on the results obtained by the analysis means.

[0010] The "integration means" is a device or program that has the function of combining improvement proposals generated from multiple algorithms into one.

[0011] The "output means" is a device or program having a function for providing the improvement proposals and products compiled by the integration means to the user.

[0012] The "presentation generation means" is a device or program that has the function of automatically creating a presentation file based on a theme specified by the user.

[0013] The "code generation means" is a device or program that has the function of automatically generating mockup code for a website or application based on requirements specified by a user.

[0014] The "script generation means" is a device or program that has the function of automatically creating a script for an oral presentation based on the presentation content and time specified by the user.

[0015] The "evaluation means" is a device or program that has the function of analyzing the materials submitted by the user, virtually evaluating them, and providing the results. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

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

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

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

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0031] 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.

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

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] Understood. The following describes in detail the mode for carrying out the invention based on the claims.

[0038] ---

[0039] This invention is a contest support system that uses generative AI, linking multiple AIs with different characteristics to provide functions such as idea refinement, presentation file creation, mockup site code generation, oral presentation script creation, and virtual evaluation. This system allows contest participants to save time and create higher quality ideas and presentations.

[0040] System Overview

[0041] This system is mainly divided into a server and a terminal (user device), each of which performs processing according to its role. Below we will explain each major component and its specific operation.

[0042] Example of idea brush-up function

[0043] The terminal provides an interface for accepting user input. The user inputs an idea and clicks the submit button to send the idea to the system. For example, the user inputs "an idea for a new mobile app."

[0044] The server analyzes the received ideas and transfers the data to four AIs with different personalities: a dreamer, a hedonist, a realist, and a critic. The dreamer AI proposes the idea's future potential, the hedonist AI suggests elements to improve the user experience, the realist AI evaluates the idea's technical feasibility, and the critic AI comments on the idea's consistency and marketability.

[0045] Once these AI-generated feedbacks are generated, the server integrates the suggestions and presents them as improvement points for the user, which are then sent to the device, where they are displayed to the user.

[0046] Presentation file creation support function

[0047] Users input the presentation topic and the number of slides they require from their device. For example, they can request a 10-slide presentation on "New Mobile Apps."

[0048] The server generates a presentation structure based on the theme, and the AI ​​automatically creates the slide content and design. The final presentation file is sent to the user's device, where it can be viewed and edited.

[0049] An embodiment of the code generation function of the mockup site

[0050] The device provides an interface where the user can input the purpose and basic requirements of the mockup site. For example, a user may request a "mockup of a task management app."

[0051] The server parses the input requirements and generates the necessary HTML, CSS, and JavaScript code, which is then sent to the device, which displays it to the user and allows them to run and modify it.

[0052] Presentation oral manuscript preparation support implementation form

[0053] The user inputs the presentation content and time from the terminal. For example, they can request a "3-minute presentation on a new mobile app."

[0054] The server extracts the main points of the speech based on the input content and time, and generates an oral transcript, which is sent to the terminal and can be used for display and practice.

[0055] Embodiment of the virtual evaluation function

[0056] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[0057] The server analyzes the submitted materials, and the generating AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The evaluation results and points for improvement are generated and sent to the device, which then displays the evaluation results and points for improvement to the user.

[0058] ---

[0059] In this way, the present invention reduces the burden on contest participants and raises the overall level of the contest by providing consistent support from brushing up ideas to preparing presentations and virtual evaluation.

[0060] The processing flow will be explained below.

[0061] I understand. Now, I will explain the flow of program processing of the invention based on the claims, broken down into specific steps.

[0062] ---

[0063] Idea brush-up function

[0064] Step 1:

[0065] A user inputs an idea from a device, for example, by typing "Idea for a new mobile app" into a text field.

[0066] Step 2:

[0067] The terminal transmits the user's input data to the server.

[0068] Step 3:

[0069] The server analyzes the received idea text and uses a natural language processing engine to extract key elements and concepts.

[0070] Step 4:

[0071] Based on the analysis results, the server transfers the data to four AIs (Dreamer AI, Hedonist AI, Realist AI, and Critic AI).

[0072] Step 5:

[0073] Each AI generates feedback from its own perspective.

[0074] Dreamer AI: Suggests future possibilities and dream elements of ideas.

[0075] Hedonist AI: Suggests enjoyable elements that improve the user experience.

[0076] Realistic AI: Point out technical feasibility and practical challenges.

[0077] Critic AI: Comments on the overall evaluation and marketability of the idea.

[0078] Step 6:

[0079] The server aggregates the feedback from the four AIs and generates unified improvement suggestions.

[0080] Step 7:

[0081] The server sends the integrated improvement suggestions to the user's terminal.

[0082] Step 8:

[0083] The device displays integrated improvement suggestions to the user.

[0084] ---

[0085] Presentation file creation support function

[0086] Step 1:

[0087] The user inputs the presentation topic and the number of slides required from the device. Example: Requesting 10 slides for a presentation on "New Mobile App."

[0088] Step 2:

[0089] The device sends a request to the server, including the theme and number of slides.

[0090] Step 3:

[0091] The server analyzes the theme and determines the basic framework for the presentation, creating sections such as "Overview," "Feature Introduction," and "Market Analysis."

[0092] Step 4:

[0093] The server generates the content for each section and uses AI to automatically create slide designs.

[0094] Step 5:

[0095] The server creates the final slide deck and converts it to the appropriate format (e.g. PowerPoint, PDF).

[0096] Step 6:

[0097] The server transmits the generated presentation file to the user's terminal.

[0098] Step 7:

[0099] The device displays the presentation file to the user and allows them to download and edit it as needed.

[0100] ---

[0101] Code generation for mockup sites

[0102] Step 1:

[0103] A user inputs the purpose and basic requirements of the mockup site from their device. For example, they request a "task management app mockup."

[0104] Step 2:

[0105] The terminal transmits the requirement data to the server.

[0106] Step 3:

[0107] The server analyzes the requirements and extracts the necessary components and UI design elements.

[0108] Step 4:

[0109] The server generates the necessary HTML, CSS, and JavaScript code based on the analysis results.

[0110] Step 5:

[0111] The server combines the generated files (HTML, CSS, JavaScript) into a single mockup file.

[0112] Step 6:

[0113] The server sends the integrated mockup code to the user's device.

[0114] Step 7:

[0115] The device displays a mockup site and allows the user to run and modify it.

[0116] ---

[0117] Presentation manuscript preparation support

[0118] Step 1:

[0119] The user inputs the presentation content and presentation time from the device. Example: Request a "3-minute presentation on a new mobile app."

[0120] Step 2:

[0121] The device sends a request including the presentation content and time to the server.

[0122] Step 3:

[0123] The server extracts the main points of the speech based on the content and time, and creates the basic structure of the oral transcript.

[0124] Step 4:

[0125] The server summarizes what is said and generates an oral transcript by adding appropriate storytelling elements.

[0126] Step 5:

[0127] The server transmits the generated oral manuscript to the user's terminal.

[0128] Step 6:

[0129] The terminal displays the oral transcript to the user and provides tools for practice.

[0130] ---

[0131] Virtual evaluation function

[0132] Step 1:

[0133] Users can upload ideas and presentation materials they have created from their devices. For example, submit a "Presentation material for a new mobile app."

[0134] Step 2:

[0135] The terminal transmits the materials to the server.

[0136] Step 3:

[0137] The server analyzes the submitted materials and begins evaluation based on the evaluation criteria. For example, analysis is performed using natural language processing or machine learning.

[0138] Step 4:

[0139] The server generates an evaluation based on the idea's originality, feasibility, user satisfaction, etc.

[0140] Step 5:

[0141] Based on the evaluation, the server will extract specific areas for improvement.

[0142] Step 6:

[0143] The server sends the evaluation results and improvements to the user's device.

[0144] Step 7:

[0145] The device displays the evaluation results and areas for improvement to the user, and suggests an action plan for the next step.

[0146] ---

[0147] Based on the above-mentioned processing steps, users can efficiently proceed from refining their ideas to preparing for presentations and virtual evaluations while receiving consistent support from the system.

[0148] Example 1

[0149] 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."

[0150] Traditionally, refining ideas, creating presentations, and creating mockup websites has often been done manually, requiring a great deal of time and effort. Furthermore, many of the tasks require multiple areas of expertise, making it difficult to handle on your own. Furthermore, it has been difficult to obtain improvement suggestions from different perspectives, making it difficult to objectively evaluate the quality and feasibility of ideas.

[0151] 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.

[0152] In this invention, the server includes a receiving means, an analyzing means for analyzing data entered by a user, a proposal generating means for generating improvement proposals using multiple generative AI models with different characteristics based on the analysis results, an integrating means for integrating the generated improvement proposals, and an output means for outputting the integrated improvement proposals. This makes it possible to improve the quality of ideas, efficiently create presentation materials and mockup sites, and significantly reduce the burden on contest participants.

[0153] The "receiving means" is a device or function for receiving input data from a user.

[0154] The "analysis means" is a device or function for analyzing the data obtained by the receiving means and processing it in an appropriate form.

[0155] The "proposal generation means" is a device or function that generates improvement proposals based on the data processed by the analysis means, using multiple generative AI models with different characteristics.

[0156] An "integration means" is a device or function that integrates improvement suggestions generated by multiple generative AI models and compiles them into unified feedback.

[0157] The "output means" is a device or function for transmitting the integrated improvement proposal to a user terminal or the like and displaying it.

[0158] The "generation means" is a device or function for automatically generating a presentation file based on an input theme.

[0159] "Code Generator" means a device or function for generating mockup code for an internet site or software based on input requirements.

[0160] This invention is a contest support system that utilizes generative AI models, and uses multiple generative AI models with different characteristics to provide functions such as idea refinement, presentation file creation, mockup site code generation, oral presentation script creation, and virtual evaluation. The system is divided into a server and a terminal (user device), each of which performs processing according to its respective role.

[0161] Idea brush-up function

[0162] A user submits an idea to the system by entering it into the device's input field and clicking the submit button. For example, they enter "idea for a new mobile app." The device then sends the data to the server. The server analyzes the received idea and transfers the data to a generative AI model with multiple different personalities. For example, OpenAI's GPT-4 is used for this generative AI model.

[0163] Specifically, the Dreamer AI proposes the idea's future potential, the Enjoyer AI suggests elements that will improve the user experience, the Realist AI evaluates the idea's technical feasibility, and the Critic AI comments on the idea's consistency and marketability. Once feedback from each AI is generated, the server integrates this feedback, summarizes it as points for improvement, and sends it to the device, which then displays it to the user.

[0164] Specific examples

[0165] A user inputs an idea for a new mobile app and clicks the submit button. The generating AI then provides feedback, such as, "This idea has great potential for future growth (Visionary AI)," "It includes features that would allow users to have an intuitive operating interface (Enjoyment AI)," and "It is evaluated as being technically feasible (Realist AI)."

[0166] Example prompt: "Please provide suggestions for refining our new mobile app idea."

[0167] Presentation file creation support function

[0168] The user inputs the presentation theme and the number of slides required from their device. For example, a user requests a 10-slide presentation on a "new mobile app." The device then sends the input information to the server. The server generates a presentation structure based on the theme, and the generation AI automatically creates the slide content and design. The generated presentation file is then sent to the user's device, where it can be viewed and edited.

[0169] Specific examples

[0170] A user requests a 10-slide presentation for a "new mobile app." The AI ​​automatically generates content such as an introduction, target market, product features, competitive analysis, marketing strategy, financial plan, development roadmap, risks and countermeasures, future outlook, and conclusion.

[0171] Example prompt: "Create a 10-slide presentation about a new mobile app."

[0172] Code generation for mockup sites

[0173] The user enters the purpose and basic requirements of the mockup site into input fields on the device. For example, they request a "task management app mockup." The device then sends the requirements to the server. The server analyzes the input requirements and uses a generative AI model to generate the necessary HTML, CSS, and JavaScript code. The generated code is then sent to the device, which displays it to the user and allows them to run and modify it.

[0174] Specific examples

[0175] When a user requests a "mockup of a task management app," the AI ​​generates HTML, CSS, and JavaScript code that includes features such as "displaying a to-do list, adding and deleting tasks, and managing task completion status."

[0176] Example prompt: "Generate HTML, CSS, and JavaScript code for a task management app."

[0177] Virtual evaluation function

[0178] Users upload their ideas and presentation materials from their devices. For example, a user may submit a "presentation for a new mobile app." The server analyzes the submitted materials, and the generative AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The evaluation results and suggestions for improvement are generated and sent to the device, which then displays them to the user.

[0179] As a result, the present invention can provide consistent support from refining ideas to preparing presentations and virtual evaluation, reducing the burden on contest participants and improving the overall level.

[0180] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0181] Idea brush-up function processing steps

[0182] Step 1:

[0183] The user inputs an idea.

[0184] Specific operation: The user enters "New mobile app idea" in the dedicated input field on the device and clicks the "Submit button."

[0185] Input: User's idea data (text format)

[0186] Output: When the send button is pressed, the idea data proceeds to the next processing step.

[0187] Step 2:

[0188] The device sends the idea to the server.

[0189] Specific operation: The device converts the input idea data into an HTTP request (e.g., POST request) and sends it to the server.

[0190] Input: User's idea data (text format)

[0191] Output: Idea data sent to the server

[0192] Step 3:

[0193] The server analyzes the received ideas.

[0194] How it works: The server processes the received idea data using Python scripts, converting it into a format that can be analyzed by the AI ​​model, and segmenting the text data to extract keywords and themes.

[0195] Input: Submitted idea data (text format)

[0196] Output: Parsed data (structured data)

[0197] Step 4:

[0198] The server transfers the ideas to a generative AI model with four different personalities.

[0199] Specific operation: The server sends the analyzed data to each AI model (Dreamer AI, Hedonist AI, Realist AI, Critic AI) as input data. It calls the model's API and passes the analyzed data.

[0200] Input: Parsed data (structured data)

[0201] Output: Feedback data from each AI model

[0202] Step 5:

[0203] The server integrates the feedback from each AI.

[0204] How it works: The server integrates the feedback data returned by each AI model and compiles it into a comprehensive set of improvement suggestions. It uses an integrated algorithm to generate consistent feedback.

[0205] Input: Feedback data from each AI (text format)

[0206] Output: Consolidated improvement suggestions (text format)

[0207] Step 6:

[0208] The server sends the integrated improvement suggestions to the terminal.

[0209] Specific operation: The server returns the integrated improvement suggestions to the terminal as an HTTP response.

[0210] Input: Consolidated improvement suggestions (text format)

[0211] Output: Improvement suggestions sent to the device (text format)

[0212] Step 7:

[0213] The device displays improvement suggestions to the user.

[0214] Specific operation: The device displays the received improvement suggestions in the user interface for the user to view, using a dialog box or a dedicated display area.

[0215] Input: Improvement suggestions received from the server (in text format)

[0216] Output: Improvement suggestions displayed to the user (in text format)

[0217] Presentation file creation support function processing steps

[0218] Step 1:

[0219] The user inputs the presentation topic and number of slides.

[0220] Specific operation: The user enters "New mobile app" and the number of slides "10" into the input fields on the device and presses the submit button.

[0221] Input: Presentation topic and number of slides (text format)

[0222] Output: When the submit button is pressed, the input data proceeds to the next processing step.

[0223] Step 2:

[0224] The terminal sends the input information to the server.

[0225] Specific operation: The device sends the entered theme and number of slides to the server via an HTTP request.

[0226] Input: Presentation topic and number of slides (text format)

[0227] Output: Themes and slide counts sent to the server

[0228] Step 3:

[0229] The server generates the presentation configuration.

[0230] How it works: The server uses a generative AI model to generate a proposed structure for each slide, breaking down the content based on the theme and designing an appropriate slide structure.

[0231] Input: Presentation topic and number of slides (text format)

[0232] Output: Slide layout proposal (structured data)

[0233] Step 4:

[0234] The server creates the slide content and design.

[0235] How it works: The server uses a generative AI model to automatically generate the text content and design elements (e.g., graphs and images) for each slide.

[0236] Input: Slide layout plan (structured data)

[0237] Output: Slide content and design (file format)

[0238] Step 5:

[0239] The server transmits the generated presentation file to the terminal.

[0240] Specific operation: The server returns the generated presentation file to the terminal as an HTTP response.

[0241] Input: Slide content and design (file format)

[0242] Output: Presentation file sent to your device

[0243] Step 6:

[0244] Allows the device to view and edit presentation files.

[0245] Specific operation: The device displays the received presentation file and provides an editor that allows the user to easily edit it.

[0246] Input: Presentation file (file format) received from the server

[0247] Output: A presentation file that users can view and edit

[0248] (Application example 1)

[0249] 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."

[0250] The purpose of this invention is to enable factory technicians and engineers to quickly and effectively refine ideas for improving new production lines and production processes, and to automatically generate the necessary information, such as presentation materials and code. In particular, by providing consistent support from idea refinement to evaluation, the invention aims to provide efficient work support and solve the problem of improving factory productivity.

[0251] 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.

[0252] In this invention, the server includes a receiving means, an analysis means for analyzing the input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, a integrating means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, an execution means for testing on an actual machine the code generated based on the input ideas, and a display means for allowing contest participants to receive the improvement proposals in real time. This enables factory technicians and engineers to quickly and effectively brush up on new ideas, create presentation materials, and generate and evaluate mockup code.

[0253] "Receiving means" refers to a device or process by which the system receives data or ideas input by a user.

[0254] An "analysis means" is a device or process whose purpose is to understand and analyze the content of input data or ideas.

[0255] A "brush-up means" is a device or process that generates improvement proposals based on analyzed data using multiple algorithms with different characteristics.

[0256] The "integration means" is a device or process that integrates multiple generated improvement proposals into one.

[0257] "Output means" refers to a device or process for providing the user with the integrated improvement suggestions and generated data.

[0258] An "execution means" is a device or process intended to test the generated code or proposals in a real environment or device.

[0259] "Display means" means a device or process for visually presenting improvement suggestions and feedback to the user in real time.

[0260] A "presentation generation means" is a device or process that automatically creates presentation materials based on an input theme.

[0261] A "script generator" is a device or process that automatically generates a spoken script to complement the content of a presentation.

[0262] "Code generator" means a device or process that generates mockup code for a website or application based on input requirements.

[0263] An "evaluation means" is a device or process that evaluates generated code or proposals in a virtual environment and provides results.

[0264] The present invention is a system that allows engineers and technicians to effectively refine ideas for improving new production lines and production processes using factory robots, generate presentation materials and mockup code, and perform virtual evaluations. Specific embodiments of this system are described below.

[0265] System Overview

[0266] This system mainly consists of a server and smart glasses (terminals) used by users. The server includes a receiving means, an analyzing means, a brushing up means, a integrating means, an outputting means, an executing means, a displaying means, a presentation generating means, a script generating means, a code generating means, and an evaluation means.

[0267] Idea brush-up function

[0268] The terminal provides an interface for users to input ideas. For example, a user can input and submit an "idea for automating a new production line." The server's analysis means analyzes this idea and sends it to AI models with different personalities: a dreamer, a hedonist, a realist, and a critic. Each model generates improvement suggestions from its own unique perspective, and these suggestions are integrated by the integration means and fed back to the user in real time via the terminal's display means.

[0269] Presentation file creation support function

[0270] The user inputs the theme of the presentation and the number of slides required from the terminal. For example, a request is made for "Explanation of the automation of a new production line" with 10 slides. The server's presentation generation means creates automatically generated slides based on the theme and provides them to the user through the output means. In addition, an oral manuscript to complement the presentation is generated by the script generation means and provided to the user.

[0271] Code generation for mockup sites

[0272] A user can input the purpose and basic requirements of the mockup site from a terminal. For example, a user can request a "mockup of a task management app that improves productivity." The server's code generation means automatically generates the necessary HTML, CSS, and JavaScript code based on the requirements and provides it to the user through the output means. The generated code is then executed in real time through the execution means.

[0273] Virtual evaluation function

[0274] Users upload their ideas and presentation materials from their devices to the server. For example, a user submits a "presentation material for a new production line." The server's evaluation means analyzes the submitted materials and performs a virtual evaluation from the perspectives of originality, feasibility, user satisfaction, etc. The evaluation results are fed back to the user via the output means.

[0275] Specific examples

[0276] For example, if an engineer inputs "an idea for automating a new production line," the following prompt sentence is generated:

[0277] New production line automation idea: To improve production efficiency, we would like to introduce a real-time monitoring system using AI.

[0278] In response to this idea, the dreamer AI suggests that "fully automating it in the future is possible," while the realist AI points out that "integration with the current system is a challenge." By combining these feedbacks, users can obtain refined ideas.

[0279] As described above, by using this system, factory technicians and engineers can quickly and efficiently generate new ideas and create presentation materials and implementation plans.

[0280] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0281] Step 1:

[0282] A user inputs an idea using a terminal, for example, a prompt sentence such as "An idea for automating a new production line," and clicks the submit button. The input data is sent to the server.

[0283] Step 2:

[0284] The server analyzes the received ideas. It uses analytical tools to convert the content of the prompt into structured data and forwards the data to AIs with different personalities (Dreamer, Hedonist, Realist, Critic). In this step, the input data is passed through a text analysis algorithm and converted into a format that can be handled by various AIs.

[0285] Step 3:

[0286] The server generates feedback using each AI model. The dreamer AI suggests the idea's future potential, the hedonist AI suggests elements that will improve the user experience, the realist AI evaluates the idea's technical feasibility, and the critic AI comments on the idea's consistency and marketability. Each feedback is sent back to the server.

[0287] Step 4:

[0288] The server consolidates the generated feedback. It uses a consolidation method to combine the feedback from each AI into a single consolidated improvement proposal. This process includes prioritizing the feedback and merging overlapping elements.

[0289] Step 5:

[0290] The integrated improvement proposals are sent to the terminal through the output means. The user receives feedback in real time and the feedback is displayed on the display means of the terminal. In this step, the integrated data is converted into a user-friendly format and visually displayed.

[0291] Step 6:

[0292] The user inputs the topic and number of slides of the presentation into the terminal. For example, a request is made for "Explanation of the automation of a new production line" with 10 slides. The input data is sent to the server again.

[0293] Step 7:

[0294] The server uses a presentation generation means to automatically create presentation slides based on the theme. The server uses a generative AI model to automatically place appropriate content and design on each slide. The generated slides are then sent to the terminal via an output means.

[0295] Step 8:

[0296] An oral script is generated to complement the presentation. The user inputs the presentation content and time, and the server creates the oral script using a script generation means. The created oral script is sent to the terminal, where the user can check the display.

[0297] Step 9:

[0298] A user inputs requirements for a mockup site using a terminal. For example, they input requirements such as "a mockup of a task management app that improves productivity" and submit the request.

[0299] Step 10:

[0300] The server uses the code generation means to generate the necessary HTML, CSS, and JavaScript code based on the input requirements. The generated code is sent to the terminal through the output means, allowing the user to try it out on the actual device in real time.

[0301] Step 11:

[0302] The user uploads the ideas and presentation materials they have created from their terminal to the server, and the input data is sent to the evaluation means.

[0303] Step 12:

[0304] The server uses the evaluation means to analyze the submitted materials and conduct a virtual evaluation from the perspectives of originality, feasibility, user satisfaction, etc. The evaluation results are sent to the terminal via the output means and fed back to the user.

[0305] The above is the specific processing flow of the system that realizes the application example.

[0306] 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.

[0307] Understood. The following describes in detail the mode for carrying out the invention based on the claims.

[0308] ---

[0309] This invention combines a contest support system using generative AI with an emotion engine that recognizes user emotions to more effectively refine ideas, create presentation files, generate code for mockup sites, create oral presentation scripts, and participate in virtual evaluations. This system allows contest participants to save time and create high-quality ideas and presentations that take emotions into consideration.

[0310] System Overview

[0311] This system is mainly divided into a server and a terminal (user device), each of which performs processing according to its role. Below we will explain each major component and its specific operation.

[0312] Example of idea brush-up function

[0313] The terminal provides an interface for accepting user input. The user inputs an idea and clicks the submit button to send the idea to the system. For example, the user inputs "an idea for a new mobile app."

[0314] The server analyzes the received ideas and transfers the data to four AIs with different personalities: a Dreamer AI, a Hedonist AI, a Realist AI, and a Critic AI. The Dreamer AI proposes the idea's future potential, the Hedonist AI proposes elements to improve the user experience, the Realist AI evaluates the idea's technical feasibility, and the Critic AI comments on the idea's consistency and marketability.

[0315] The server also uses emotion recognition to identify emotions from user input and behavior. This emotional information can then be used to further optimize the AI ​​feedback. For example, if the user is not satisfied with an idea, the Hedonist AI will suggest more appealing elements.

[0316] Once these AI-generated feedbacks are generated, the server integrates the suggestions and presents them as improvement points for the user, which are then sent to the device, where they are displayed to the user.

[0317] Presentation file creation support function

[0318] Users input the presentation topic and the number of slides they require from their device. For example, they can request a 10-slide presentation on "New Mobile Apps."

[0319] The server generates a presentation structure based on the theme, and the generation AI automatically creates the content and design of the slides. In addition, an emotion recognition system analyzes the user's emotional information and optimizes the presentation content based on that information. For example, if anxiety about preparing a presentation is detected, the server will suggest concise and easy-to-understand slides.

[0320] The final presentation file is sent to the user's terminal, where it can be viewed and edited.

[0321] An embodiment of the code generation function of the mockup site

[0322] The device provides an interface where the user can input the purpose and basic requirements of the mockup site. For example, a user may request a "mockup of a task management app."

[0323] The server analyzes the input requirements and generates the necessary HTML, CSS, and JavaScript code. Furthermore, an emotion recognition mechanism analyzes the user's emotional information and optimizes the design of the mockup code based on that information. For example, if the user prefers a simple and easy-to-use design, the server generates code that includes design elements that meet that preference.

[0324] The generated code is sent to the terminal, which displays it to the user and allows it to be executed and modified.

[0325] Presentation oral manuscript preparation support implementation form

[0326] The user inputs the presentation content and presentation time from the terminal. For example, they request a "3-minute presentation on a new mobile app."

[0327] The server extracts the main points of the speech based on the input content and time, and generates an oral transcript. Furthermore, an emotion recognition unit analyzes the user's emotional information and optimizes the transcript content based on that information. For example, it generates a transcript that includes positive and powerful expressions to help the user speak with confidence.

[0328] The generated oral transcript is sent to the terminal and can be used for display and practice on the terminal.

[0329] Embodiment of the virtual evaluation function

[0330] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[0331] The server analyzes the submitted materials, and the generating AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. An emotion recognition system analyzes the user's emotions and reflects that information in the evaluation. For example, if a user feels anxious about being evaluated, an encouraging message can be included.

[0332] The evaluation results and points for improvement are generated and sent to the device, which then displays them to the user and proposes an action plan for the next step.

[0333] ---

[0334] In this way, by combining an emotion engine, the present invention realizes a system that supports idea refinement, presentation preparation, and virtual evaluation while taking into consideration the user's emotions, allowing users to achieve better results and raising the overall level of the contest.

[0335] The processing flow will be explained below.

[0336] I understand. Now, I will explain the flow of program processing of the invention based on the claims, broken down into specific steps.

[0337] ---

[0338] Idea brush-up function

[0339] Step 1:

[0340] A user enters an idea into the device and clicks the submit button. For example, the user enters "Idea for a new mobile app" into the text field.

[0341] Step 2:

[0342] The terminal transmits the user's input data to the server.

[0343] Step 3:

[0344] The server analyzes the received idea text and uses a natural language processing engine to extract key elements and concepts.

[0345] Step 4:

[0346] Based on the analysis results, the server transfers the data to four AIs (Dreamer AI, Hedonist AI, Realist AI, and Critic AI).

[0347] Step 5:

[0348] Each AI generates feedback from its own perspective.

[0349] Dreamer AI: Suggests future possibilities and dream elements of ideas.

[0350] Hedonist AI: Suggests enjoyable elements that improve the user experience.

[0351] Realistic AI: Point out technical feasibility and practical challenges.

[0352] Critic AI: Comments on the overall evaluation and marketability of the idea.

[0353] Step 6:

[0354] The server uses emotion recognition means to recognize emotions from the user's input and actions, for example, by analyzing the user's facial expressions and input speed.

[0355] Step 7:

[0356] The server optimizes the AI's feedback based on the recognized emotional information. For example, if the user is dissatisfied with an idea, the Hedonist AI will suggest more positive elements.

[0357] Step 8:

[0358] The server aggregates the feedback from the four AIs and generates unified improvement suggestions.

[0359] Step 9:

[0360] The server sends the integrated improvement suggestions to the user's terminal.

[0361] Step 10:

[0362] The device displays integrated improvement suggestions to the user.

[0363] ---

[0364] Presentation file creation support function

[0365] Step 1:

[0366] The user inputs the presentation topic and the number of slides required from the device. Example: Requesting 10 slides for a presentation on "New Mobile App."

[0367] Step 2:

[0368] The device sends a request to the server, including the theme and number of slides.

[0369] Step 3:

[0370] The server analyzes the theme and determines the basic framework for the presentation, creating sections such as "Overview," "Feature Introduction," and "Market Analysis."

[0371] Step 4:

[0372] The server generates the content for each section and uses AI to automatically create slide designs.

[0373] Step 5:

[0374] The server analyzes the user's emotional information using emotion recognition means, e.g., analyzing the user's facial expression or voice tone.

[0375] Step 6:

[0376] The server then optimizes the presentation content based on the emotional information it recognizes. For example, it suggests simple, friendly slides to a user who is feeling nervous.

[0377] Step 7:

[0378] The server creates the final slide deck and converts it to the appropriate format (e.g. PowerPoint, PDF).

[0379] Step 8:

[0380] The server transmits the generated presentation file to the user's terminal.

[0381] Step 9:

[0382] The device displays the presentation file to the user and allows them to download and edit it as needed.

[0383] ---

[0384] Code generation for mockup sites

[0385] Step 1:

[0386] A user inputs the purpose and basic requirements of the mockup site from their device. For example, they request a "task management app mockup."

[0387] Step 2:

[0388] The terminal transmits the requirement data to the server.

[0389] Step 3:

[0390] The server analyzes the requirements and extracts the necessary components and UI design elements.

[0391] Step 4:

[0392] The server generates the necessary HTML, CSS, and JavaScript code based on the analysis results.

[0393] Step 5:

[0394] The server uses emotion recognition means to analyze the user's emotion information, such as the user's typing speed and screen transition frequency.

[0395] Step 6:

[0396] The server optimizes the design of the mockup code based on the recognized emotion information. For example, if the user prefers a simple design, the server generates code that meets that preference.

[0397] Step 7:

[0398] The server combines the generated files (HTML, CSS, JavaScript) into a single mockup file.

[0399] Step 8:

[0400] The server sends the integrated mockup code to the user's device.

[0401] Step 9:

[0402] The device displays a mockup site and allows the user to run and modify it.

[0403] ---

[0404] Presentation manuscript preparation support

[0405] Step 1:

[0406] The user inputs the presentation content and presentation time from the device. Example: Request a "3-minute presentation on a new mobile app."

[0407] Step 2:

[0408] The device sends a request including the presentation content and time to the server.

[0409] Step 3:

[0410] The server extracts the main points of the speech based on the content and time, and creates the basic structure of the oral manuscript.

[0411] Step 4:

[0412] The server summarizes what is said and generates an oral transcript by adding appropriate storytelling elements.

[0413] Step 5:

[0414] The server uses emotion recognition means to analyze the user's emotion information, for example, by analyzing the user's tone of voice and pronunciation rhythm.

[0415] Step 6:

[0416] The server optimizes the content of the transcript based on the recognized emotional information, for example by generating a transcript that includes positive and powerful expressions to help the user speak with confidence.

[0417] Step 7:

[0418] The server transmits the generated oral manuscript to the user's terminal.

[0419] Step 8:

[0420] The terminal displays the oral transcript to the user and provides tools for practice.

[0421] ---

[0422] Virtual evaluation function

[0423] Step 1:

[0424] Users can upload ideas and presentation materials they have created from their devices. For example, submit a "Presentation material for a new mobile app."

[0425] Step 2:

[0426] The terminal transmits the materials to the server.

[0427] Step 3:

[0428] The server analyzes the submitted materials and begins evaluation based on the evaluation criteria. For example, analysis is performed using natural language processing or machine learning.

[0429] Step 4:

[0430] The server analyzes the user's emotional information using emotion recognition means. For example, analyzing the user's facial expression and tone of voice when submitting documents.

[0431] Step 5:

[0432] The server optimizes the evaluation based on the recognized emotion information. For example, it includes an encouraging message for a user who is nervous about submitting a document.

[0433] Step 6:

[0434] The server generates an evaluation based on the idea's originality, feasibility, user satisfaction, etc.

[0435] Step 7:

[0436] Based on the evaluation, the server will extract specific areas for improvement.

[0437] Step 8:

[0438] The server sends the evaluation results and improvements to the user's device.

[0439] Step 9:

[0440] The device displays the evaluation results and areas for improvement to the user and suggests an action plan for the next step.

[0441] ---

[0442] Based on the above processing steps, users can receive consistent support from the system and efficiently proceed through the process from refining their ideas to preparing presentations and virtual evaluations. By combining it with an emotion engine, support can be provided while taking into consideration the user's emotions, resulting in higher quality output.

[0443] Example 2

[0444] 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."

[0445] Contest participants often spend a lot of time and effort refining their ideas, creating presentation files, and generating mockups of websites and applications. Furthermore, they struggle to create high-quality deliverables because they lack optimal feedback and suggestions based on the user's emotions. This invention aims to automate these processes while providing support that takes the user's emotions into consideration.

[0446] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a receiving means, an analysis means for analyzing input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, an integration means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, an emotion engine for recognizing the user's emotions, and an optimization means for optimizing the generated improvement proposals based on the analysis results by the emotion engine. This enables the user to reduce effort and time and efficiently create high-quality ideas and presentation materials that take emotions into consideration.

[0447] "Receiving means" is a function for receiving data and information sent from a user.

[0448] "Analysis means" is a function that analyzes and evaluates input data and information.

[0449] "Brush-up means" is a function that generates improvement suggestions using multiple algorithms based on the analysis results.

[0450] "Integration means" is a function that organizes and combines multiple improvement proposals into a single integrated proposal.

[0451] The "output means" is a function for providing the user with the integrated improvement proposals and the generated files.

[0452] The "emotion engine" is a feature used to analyze the user's emotional state and optimize feedback and suggestions.

[0453] The "optimization means" is a function that adjusts feedback and output according to the user's emotional state based on the analysis results of the emotion engine.

[0454] The "presentation generation means" is a function that automatically generates a presentation file based on an input theme.

[0455] "Code generation means" is a function that automatically generates mockup code for websites and applications based on input requirements.

[0456] The present invention is a user assistance system that uses a generative AI model, and is implemented by the following main components and their processing flow.

[0457] System Overview

[0458] This system is composed of a server and a terminal (user device), each of which performs processing according to its role. Each component has the following functions.

[0459] Idea brush-up function

[0460] The user inputs the idea into the terminal and sends it to the system by pressing the send button. For example, the user inputs "Idea for a new mobile app."

[0461] The device uses a receiving means to send this idea to the server. The server then analyzes the idea using an analytical means and distributes the data to four algorithms with different personalities: Dreamer AI, Hedonist AI, Realist AI, and Critic AI. Each AI provides the following feedback:

[0462] Visionary AI: Proposing future possibilities.

[0463] Hedonist AI: Suggests elements to improve the user experience.

[0464] Realist AI: Assessing technical feasibility.

[0465] Critic AI: Evaluates the consistency and marketability of ideas.

[0466] The server analyzes the user's emotions using an emotion engine and optimizes the feedback. For example, if the user expresses dissatisfaction, the Hedonist AI will suggest more appealing elements. These feedbacks are integrated by the integration means and provided to the user as improvement points via the output means.

[0467] Example prompt sentence:

[0468] "Tell us your ideas. We'll have a Dreamer AI, a Hedonist AI, a Realist AI, and a Critic AI to give you feedback."

[0469] Presentation file creation support function

[0470] The user inputs the topic of the presentation and the number of slides required into the device, for example, "Request a 10-slide presentation on a new mobile app."

[0471] The device sends this information to the server. The server uses a presentation generation means to automatically generate the content and design of the slides and analyzes the user's emotional state using an emotion engine. By providing slides that succinctly summarize the important points based on the emotional information, the presentation is optimized to a structure that is less likely to make the user feel anxious. The generated presentation file is sent to the device, where it can be edited by the user.

[0472] Example prompt sentence:

[0473] "Please tell me the topic of your presentation and how many slides you need."

[0474] Code generation for mockup sites

[0475] The user inputs the purpose and basic requirements of the mockup site into the device, for example, requesting a "mockup of a task management app."

[0476] The device sends this to the server, which uses a code generator to generate HTML, CSS, and JavaScript code based on the input requirements. The server uses an emotion engine to analyze the user's emotions and optimize design elements based on that. For example, if a user prefers a simple design, the server will generate code that meets that preference. The generated code is then sent to the device, where the user can run and modify it.

[0477] Example prompt sentence:

[0478] "What is the purpose and basic requirements of the mockup site?"

[0479] Presentation script creation support function

[0480] The user inputs the presentation content and presentation time into the terminal. For example, they request a "3-minute presentation on a new mobile app."

[0481] The terminal sends this information to the server, which then uses an oral script generation means to extract the main points of the speech and generate a script. Based on the analysis results of the emotion engine, the server generates a script with positive and powerful expressions, optimizing it so that the user can speak with confidence. The generated script is sent to the terminal and can be used by the user for display and practice.

[0482] Example prompt sentence:

[0483] Please tell me the content of your presentation and the time of your presentation.

[0484] Virtual evaluation function

[0485] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[0486] The device sends the materials to the server, which then evaluates them using analytical means. A generative AI model is used to perform a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. An emotion engine analyzes the user's emotions and reflects them in the evaluation. For example, it generates evaluation results that include encouraging messages to alleviate evaluation anxiety. The evaluation results and points for improvement are sent to the device and displayed to the user, providing an action plan for the next step.

[0487] Example prompt sentence:

[0488] "Upload your ideas and presentation materials and we'll do a virtual evaluation."

[0489] As described above, the present invention effectively supports idea refinement, presentation preparation, mockup creation, oral manuscript creation, and virtual evaluation while taking into consideration the user's emotions by combining an emotion engine. This allows users to efficiently create high-quality deliverables and improve overall results.

[0490] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0491] Idea brush-up function

[0492] Step 1:

[0493] The user enters an idea into the device and clicks the submit button. The entered idea might be something like "An idea for a new mobile app."

[0494] Step 2:

[0495] The terminal sends the input idea to the server using an HTTP request. The input is the idea data, and the output is confirmation of the request.

[0496] Step 3:

[0497] The server analyzes the received ideas using an analysis means. The input is the received idea data, and the output is the analysis result. Specifically, the server uses a text analysis algorithm to extract the main elements of the idea.

[0498] Step 4:

[0499] The server distributes the data to four AIs with different personalities (Dreamer AI, Hedonist AI, Realist AI, and Critic AI) based on the analysis results. The input is the analysis results, and the output is the data sent to each AI. Requests are sent via a RESTful API.

[0500] Step 5:

[0501] The server receives feedback from each AI. The dreamer AI suggests future possibilities, the enjoyer AI suggests ways to improve the user experience, the realist AI evaluates technical feasibility, and the critic AI evaluates consistency and marketability. The input is the data sent to the AI, and the output is feedback information.

[0502] Step 6:

[0503] The server uses an emotion engine to analyze the user's emotional information. For example, if an emotion indicating dissatisfaction is detected, the server adjusts the feedback content based on that. The input is the user's emotional information, and the output is the emotion analysis result.

[0504] Step 7:

[0505] The server integrates the feedback from each AI with the results of emotion analysis using an integration method. Specifically, it organizes the feedback content and reconstructs it into an optimal form for the user. The input is the feedback information and the results of emotion analysis, and the output is an integrated improvement proposal.

[0506] Step 8:

[0507] The server transmits the integrated improvement proposal to the terminal using the output means. At this time, an HTTP response is used. The input is the integrated improvement proposal, and the output is transmission confirmation information.

[0508] Step 9:

[0509] The terminal displays the received improvement suggestions to the user. The input is the improvement suggestions, and the output is the displayed suggestion information.

[0510] Presentation file creation support function

[0511] Step 1:

[0512] The user inputs the topic of the presentation and the number of slides required into the device, for example, "Request a 10-slide presentation on a new mobile app."

[0513] Step 2:

[0514] The terminal sends information about the theme and the number of slides to the server. The input is the theme and the number of slides, and the output is a confirmation of the request.

[0515] Step 3:

[0516] The server generates a presentation structure based on the theme. It uses a generative AI model to automatically create the slide content and design. The input is the theme and the number of slides, and the output is a presentation file.

[0517] Step 4:

[0518] The server uses an emotion engine to analyze the user's emotional information and optimize the presentation content. For example, if anxiety is detected, it creates concise and easy-to-understand slides. The input is the user's emotional information, and the output is the emotion analysis results.

[0519] Step 5:

[0520] The server sends the final presentation file to the terminal, where the input is the optimized presentation file and the output is a transmission confirmation.

[0521] Step 6:

[0522] The terminal displays the received presentation file and allows the user to edit it. The input is the presentation file and the output is the displayed file.

[0523] Code generation for mockup sites

[0524] Step 1:

[0525] The user inputs the purpose and basic requirements of the mockup site into the device, for example, requesting a "mockup of a task management app."

[0526] Step 2:

[0527] The terminal sends this to the server. The input is the requirements for the mockup site, and the output is confirmation of the request submission.

[0528] Step 3:

[0529] The server parses the input requirements and uses a generative AI model to generate the necessary HTML, CSS, and JavaScript code. The input is the requirements for the mockup site, and the output is the mockup code.

[0530] Step 4:

[0531] The server uses an emotion engine to analyze the user's emotional information and optimize the code design. For example, if a user prefers a simple design, it generates code that includes design elements that meet that preference. The input is the user's emotional information, and the output is optimized code.

[0532] Step 5:

[0533] The server sends the generated code to the terminal. The input is the generated code and the output is the transmission confirmation information.

[0534] Step 6:

[0535] The terminal displays the received code and allows the user to execute and modify it. The input is the generated code and the output is the displayed code.

[0536] Presentation script creation support function

[0537] Step 1:

[0538] The user inputs the presentation content and presentation time into the terminal. For example, the user requests a "3-minute presentation on a new mobile app."

[0539] Step 2:

[0540] The terminal sends this information to the server. The input is the presentation content and time, and the output is confirmation of the request.

[0541] Step 3:

[0542] The server extracts the main points of the speech based on the content and time, and generates an oral transcript. The input is the presentation content and time, and the output is the oral transcript.

[0543] Step 4:

[0544] The server uses an emotion engine to analyze the user's emotional information and optimize the content of the spoken script. For example, it generates a script containing positive and powerful expressions to help the user speak with confidence. The input is the user's emotional information, and the output is the optimized script.

[0545] Step 5:

[0546] The server transmits the generated oral manuscript to the terminal, where the input is the generated manuscript and the output is transmission confirmation information.

[0547] Step 6:

[0548] The terminal displays the received oral transcript so that the user can use it for practice. The input is the generated transcript and the output is the displayed transcript.

[0549] Virtual evaluation function

[0550] Step 1:

[0551] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[0552] Step 2:

[0553] The terminal sends the submitted documents to the server. The input is the submitted documents, and the output is confirmation of the request submission.

[0554] Step 3:

[0555] The server analyzes the submitted materials and uses a generative AI model to perform a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The input is the submitted materials, and the output is the virtual evaluation results.

[0556] Step 4:

[0557] The server uses an emotion engine to analyze the user's emotions and reflects that information in the evaluation. For example, if a user feels anxious about being evaluated, the server generates an evaluation result that includes an encouraging message. The input is the user's emotional information, and the output is an optimized evaluation result.

[0558] Step 5:

[0559] The server generates evaluation results and improvements and sends them to the terminal. The input is the evaluation results and improvements, and the output is a transmission confirmation.

[0560] Step 6:

[0561] The terminal displays the evaluation results and points for improvement to the user and proposes an action plan for the next step. The input is the evaluation results and points for improvement, and the output is the displayed results and suggestions.

[0562] The above is the specific flow of processing in this system.

[0563] (Application example 2)

[0564] 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."

[0565] When multiple robots work together in a factory, maintenance and work optimization proposals for each robot may not be implemented promptly. This can result in reduced production efficiency and robot breakdowns or malfunctions. Furthermore, workers who are not familiar with robot operation and maintenance may find it difficult to take appropriate action, which could lead to further problems. It is necessary to resolve these issues and efficiently perform maintenance while optimizing robot operation.

[0566] 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.

[0567] In this invention, the server includes a receiving means, an analysis means for analyzing input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, an integration means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, a data collection means for collecting and analyzing robot operation data, an optimization proposal means for proposing task optimization based on the robot's operating status, and an anomaly detection means for detecting robot abnormalities and the need for maintenance. This enables real-time analysis of the robot's operations in a factory, efficient task proposals, and early anomaly detection.

[0568] definition statement

[0569] The "receiving means" is a means for receiving various input information such as ideas from users and robot operation data.

[0570] "Analysis means" refers to the means for analyzing ideas and data received by the receiving means, and for understanding and evaluating their contents.

[0571] The "brush-up means" is a means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results obtained by the analysis means.

[0572] The "integration means" is a means for combining multiple improvement proposals generated by the brush-up means into one.

[0573] The "output means" is a means for providing the improvement proposal obtained by the integration means to the user.

[0574] The "data collection means" is a means for collecting operational data from robots in a factory.

[0575] The "optimization suggestion means" is a means for analyzing the robot operation data collected by the data collection means and making suggestions for improving work efficiency.

[0576] The "abnormality detection means" is a means for monitoring the operation data of the robot and detecting abnormalities or the need for maintenance.

[0577] MODE FOR CARRYING OUT THE INVENTION

[0578] The present invention relates to a system for improving the efficiency of robot management in a factory and supporting maintenance and work optimization. Specific embodiments for carrying out the present invention will be described below.

[0579] System Overview

[0580] This system is mainly composed of a server and a terminal (user device), each of which performs processing according to its respective role. The server is responsible for analyzing and generating data, while the user's terminal is responsible for inputting and outputting data.

[0581] Robot data collection and analysis

[0582] The terminal provides a means for collecting operational data from the robots in the factory, such as temperature, operating time, and the number of errors that have occurred.

[0583] The server has a "receiving means" that receives the collected data and an "analysis means" that analyzes the data. The analysis means evaluates the robot's operating status and detects abnormalities.

[0584] Work optimization and maintenance proposals

[0585] Based on the analysis results, the server uses the "optimization proposal method" and "anomaly detection method" to detect the need for improvement proposals and maintenance. Using these methods, specific improvement measures and maintenance proposals for the robot are generated.

[0586] For example, if robot R1 reaches a high temperature (85°C) during operation and has been operating for more than 5,000 hours, the analysis means will detect that it is experiencing stress based on that data, and the optimization suggestion means will send a signal to check the cooling system for temperature control.

[0587] Feedback and Integration

[0588] The server generates optimization and maintenance proposals using the "brush-up means," and then integrates them using the "integration means." This generates comprehensive improvement proposals and provides them to the user.

[0589] The terminal uses the "output means" to display the integrated improvement proposals to the user, for example, as an alert on the user's smartphone.

[0590] Examples and prompts

[0591] Below is a concrete example of how the system works.

[0592] Specific examples

[0593] Robot R1 in the factory has reached a high temperature (85°C) during operation and has been running for over 5000 hours. Analysis by the emotion engine has detected that this robot is feeling stressed. Please generate appropriate maintenance suggestions and work optimization suggestions.

[0594] Prompt Sentence Examples

[0595] "Robot R1 in the factory has reached a high temperature (85°C) during operation and has been operating for over 5000 hours. Analysis by the emotion engine has detected that this robot is experiencing stress. Please generate appropriate maintenance suggestions and work optimization suggestions."

[0596] In this way, the present invention realizes a system that improves efficiency and reliability within factories by collecting robot operation data and using a generative AI model to make specific improvement suggestions.

[0597] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0598] Program processing flow

[0599] Step 1: Data collection

[0600] The terminal collects operational data from robots in the factory.

[0601] Input: Robot operation data (temperature, operating time, number of errors, etc.)

[0602] Output: raw data collected

[0603] Specific operation: Collects data in real time from various sensors such as temperature sensors and work time recording devices and sends it to a server.

[0604] Step 2: Receiving data

[0605] The server receives the operation data sent from the terminal.

[0606] Input: Raw data from the terminal

[0607] Output: Robot movement data stored in the server

[0608] Specific operation: Receives data from the device and stores it in a database.

[0609] Step 3: Data analysis

[0610] The server analyzes the received motion data.

[0611] Input: Collected robot movement data

[0612] Output: Analysis results (temperature rise, abnormality detection, etc.)

[0613] Specific operation: Based on the received data, the temperature, operating time, and number of errors are analyzed to check for abnormalities. For example, if the temperature exceeds a set reference value (e.g., 85°C), an abnormality is detected.

[0614] Step 4: Sentiment analysis and maintenance need assessment

[0615] Based on the analysis results, the server uses an emotion engine to analyze the robot's "emotions" and evaluate the need for maintenance.

[0616] Input: Analysis results

[0617] Output: Sentiment data and maintenance suggestions

[0618] Specific operation: The emotion engine analyzes emotions, such as "feeling stressed" in response to a high temperature, and determines whether maintenance is necessary. For example, based on data such as "R1 has been operating at 85°C for 5,000 hours," it suggests checking the cooling system.

[0619] Step 5: Generate improvement suggestions

[0620] The server generates improvement suggestions using a generative AI model.

[0621] Input: Sentiment data and maintenance suggestions

[0622] Output: Improvement suggestions

[0623] Specific actions: Based on the analyzed emotions and maintenance need assessment data, the generative AI generates specific improvement suggestions, such as suggestions for improving the robot's operating environment or proposing new operating procedures.

[0624] Step 6: Proposal Integration

[0625] The server integrates multiple improvement suggestions.

[0626] Input: Multiple improvement suggestions

[0627] Output: Consolidated improvement suggestions

[0628] Specific operation: Consolidate multiple improvement suggestions generated by the generative AI into one. For example, consolidate suggestions for temperature control and maintenance needs into a clearer format.

[0629] Step 7: Provide feedback

[0630] The terminal notifies the user of the integrated proposal.

[0631] Input: Consolidated improvement suggestions

[0632] Output: User notification

[0633] Specific actions: The integrated improvement suggestions are sent to the device, and alerts and specific actions are displayed to the user. For example, a notification is displayed on the smartphone app with the message "Please check the cooling system of your R1."

[0634] The above are the specific processing steps for carrying out the present invention.

[0635] 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.

[0636] 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.

[0637] 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.

[0638] [Second embodiment]

[0639] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0640] 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.

[0641] 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).

[0642] 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.

[0643] 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.

[0644] 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).

[0645] 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.

[0646] 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.

[0647] 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.

[0648] 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.

[0649] 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.

[0650] 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."

[0651] Understood. The following describes in detail the mode for carrying out the invention based on the claims.

[0652] ---

[0653] This invention is a contest support system that uses generative AI, linking multiple AIs with different characteristics to provide functions such as idea refinement, presentation file creation, mockup site code generation, oral presentation script creation, and virtual evaluation. This system allows contest participants to save time and create higher quality ideas and presentations.

[0654] System Overview

[0655] This system is mainly divided into a server and a terminal (user device), each of which performs processing according to its role. Below we will explain each major component and its specific operation.

[0656] Example of idea brush-up function

[0657] The terminal provides an interface for accepting user input. The user inputs an idea and clicks the submit button to send the idea to the system. For example, the user inputs "an idea for a new mobile app."

[0658] The server analyzes the received ideas and transfers the data to four AIs with different personalities: a dreamer, a hedonist, a realist, and a critic. The dreamer AI proposes the idea's future potential, the hedonist AI suggests elements to improve the user experience, the realist AI evaluates the idea's technical feasibility, and the critic AI comments on the idea's consistency and marketability.

[0659] Once these AI-generated feedbacks are generated, the server integrates the suggestions and presents them as improvement points for the user, which are then sent to the device, where they are displayed to the user.

[0660] Presentation file creation support function

[0661] Users input the presentation topic and the number of slides they require from their device. For example, they can request a 10-slide presentation on "New Mobile Apps."

[0662] The server generates a presentation structure based on the theme, and the AI ​​automatically creates the slide content and design. The final presentation file is sent to the user's device, where it can be viewed and edited.

[0663] An embodiment of the code generation function of the mockup site

[0664] The device provides an interface where the user can input the purpose and basic requirements of the mockup site. For example, a user may request a "mockup of a task management app."

[0665] The server parses the input requirements and generates the necessary HTML, CSS, and JavaScript code, which is then sent to the device, which displays it to the user and allows them to run and modify it.

[0666] Presentation oral manuscript preparation support implementation form

[0667] The user inputs the presentation content and time from the terminal. For example, they can request a "3-minute presentation on a new mobile app."

[0668] The server extracts the main points of the speech based on the input content and time, and generates an oral transcript, which is sent to the terminal and can be used for display and practice.

[0669] Embodiment of the virtual evaluation function

[0670] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[0671] The server analyzes the submitted materials, and the generating AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The evaluation results and points for improvement are generated and sent to the device, which then displays the evaluation results and points for improvement to the user.

[0672] ---

[0673] In this way, the present invention reduces the burden on contest participants and raises the overall level of the contest by providing consistent support from brushing up ideas to preparing presentations and virtual evaluation.

[0674] The processing flow will be explained below.

[0675] I understand. Now, I will explain the flow of program processing of the invention based on the claims, broken down into specific steps.

[0676] ---

[0677] Idea brush-up function

[0678] Step 1:

[0679] A user inputs an idea from a device, for example, by typing "Idea for a new mobile app" into a text field.

[0680] Step 2:

[0681] The terminal transmits the user's input data to the server.

[0682] Step 3:

[0683] The server analyzes the received idea text and uses a natural language processing engine to extract key elements and concepts.

[0684] Step 4:

[0685] Based on the analysis results, the server transfers the data to four AIs (Dreamer AI, Hedonist AI, Realist AI, and Critic AI).

[0686] Step 5:

[0687] Each AI generates feedback from its own perspective.

[0688] Dreamer AI: Suggests future possibilities and dream elements of ideas.

[0689] Hedonist AI: Suggests enjoyable elements that improve the user experience.

[0690] Realistic AI: Point out technical feasibility and practical challenges.

[0691] Critic AI: Comments on the overall evaluation and marketability of the idea.

[0692] Step 6:

[0693] The server aggregates the feedback from the four AIs and generates unified improvement suggestions.

[0694] Step 7:

[0695] The server sends the integrated improvement suggestions to the user's terminal.

[0696] Step 8:

[0697] The device displays integrated improvement suggestions to the user.

[0698] ---

[0699] Presentation file creation support function

[0700] Step 1:

[0701] The user inputs the presentation topic and the number of slides required from the device. Example: Requesting 10 slides for a presentation on "New Mobile App."

[0702] Step 2:

[0703] The device sends a request to the server, including the theme and number of slides.

[0704] Step 3:

[0705] The server analyzes the theme and determines the basic framework for the presentation, creating sections such as "Overview," "Feature Introduction," and "Market Analysis."

[0706] Step 4:

[0707] The server generates the content for each section and uses AI to automatically create slide designs.

[0708] Step 5:

[0709] The server creates the final slide deck and converts it to the appropriate format (e.g. PowerPoint, PDF).

[0710] Step 6:

[0711] The server transmits the generated presentation file to the user's terminal.

[0712] Step 7:

[0713] The device displays the presentation file to the user and allows them to download and edit it as needed.

[0714] ---

[0715] Code generation for mockup sites

[0716] Step 1:

[0717] A user inputs the purpose and basic requirements of the mockup site from their device. For example, they request a "task management app mockup."

[0718] Step 2:

[0719] The terminal transmits the requirement data to the server.

[0720] Step 3:

[0721] The server analyzes the requirements and extracts the necessary components and UI design elements.

[0722] Step 4:

[0723] The server generates the necessary HTML, CSS, and JavaScript code based on the analysis results.

[0724] Step 5:

[0725] The server combines the generated files (HTML, CSS, JavaScript) into a single mockup file.

[0726] Step 6:

[0727] The server sends the integrated mockup code to the user's device.

[0728] Step 7:

[0729] The device displays a mockup site and allows the user to run and modify it.

[0730] ---

[0731] Presentation manuscript preparation support

[0732] Step 1:

[0733] The user inputs the presentation content and presentation time from the device. Example: Request a "3-minute presentation on a new mobile app."

[0734] Step 2:

[0735] The device sends a request including the presentation content and time to the server.

[0736] Step 3:

[0737] The server extracts the main points of the speech based on the content and time, and creates the basic structure of the oral manuscript.

[0738] Step 4:

[0739] The server summarizes what is said and generates an oral transcript by adding appropriate storytelling elements.

[0740] Step 5:

[0741] The server transmits the generated oral manuscript to the user's terminal.

[0742] Step 6:

[0743] The terminal displays the oral transcript to the user and provides tools for practice.

[0744] ---

[0745] Virtual evaluation function

[0746] Step 1:

[0747] Users can upload ideas and presentation materials they have created from their devices. For example, submit a "Presentation material for a new mobile app."

[0748] Step 2:

[0749] The terminal transmits the materials to the server.

[0750] Step 3:

[0751] The server analyzes the submitted materials and begins evaluation based on the evaluation criteria. For example, analysis is performed using natural language processing or machine learning.

[0752] Step 4:

[0753] The server generates an evaluation based on the idea's originality, feasibility, user satisfaction, etc.

[0754] Step 5:

[0755] Based on the evaluation, the server will extract specific areas for improvement.

[0756] Step 6:

[0757] The server sends the evaluation results and improvements to the user's device.

[0758] Step 7:

[0759] The device displays the evaluation results and areas for improvement to the user, and suggests an action plan for the next step.

[0760] ---

[0761] Based on the above-mentioned processing steps, users can efficiently proceed from refining their ideas to preparing for presentations and virtual evaluations while receiving consistent support from the system.

[0762] Example 1

[0763] 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."

[0764] Traditionally, refining ideas, creating presentations, and creating mockup websites has often been done manually, requiring a great deal of time and effort. Furthermore, many of the tasks require multiple areas of expertise, making it difficult to handle on your own. Furthermore, it has been difficult to obtain improvement suggestions from different perspectives, making it difficult to objectively evaluate the quality and feasibility of ideas.

[0765] 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.

[0766] In this invention, the server includes a receiving means, an analyzing means for analyzing data entered by a user, a proposal generating means for generating improvement proposals using multiple generative AI models with different characteristics based on the analysis results, an integrating means for integrating the generated improvement proposals, and an output means for outputting the integrated improvement proposals. This makes it possible to improve the quality of ideas, efficiently create presentation materials and mockup sites, and significantly reduce the burden on contest participants.

[0767] The "receiving means" is a device or function for receiving input data from a user.

[0768] The "analysis means" is a device or function for analyzing the data obtained by the receiving means and processing it in an appropriate form.

[0769] The "proposal generation means" is a device or function that generates improvement proposals based on the data processed by the analysis means, using multiple generative AI models with different characteristics.

[0770] An "integration means" is a device or function that integrates improvement suggestions generated by multiple generative AI models and compiles them into unified feedback.

[0771] The "output means" is a device or function for transmitting the integrated improvement proposal to a user terminal or the like and displaying it.

[0772] The "generation means" is a device or function for automatically generating a presentation file based on an input theme.

[0773] "Code Generator" means a device or function for generating mockup code for an internet site or software based on input requirements.

[0774] This invention is a contest support system that utilizes generative AI models, and uses multiple generative AI models with different characteristics to provide functions such as idea refinement, presentation file creation, mockup site code generation, oral presentation script creation, and virtual evaluation. The system is divided into a server and a terminal (user device), each of which performs processing according to its respective role.

[0775] Idea brush-up function

[0776] A user submits an idea to the system by entering it into the device's input field and clicking the submit button. For example, they enter "idea for a new mobile app." The device then sends the data to the server. The server analyzes the received idea and transfers the data to a generative AI model with multiple different personalities. For example, OpenAI's GPT-4 is used for this generative AI model.

[0777] Specifically, the Dreamer AI proposes the idea's future potential, the Enjoyer AI suggests elements that will improve the user experience, the Realist AI evaluates the idea's technical feasibility, and the Critic AI comments on the idea's consistency and marketability. Once feedback from each AI is generated, the server integrates this feedback, summarizes it as points for improvement, and sends it to the device, which then displays it to the user.

[0778] Specific examples

[0779] A user inputs an idea for a new mobile app and clicks the submit button. The generating AI then provides feedback, such as, "This idea has great potential for future growth (Visionary AI)," "It includes features that would allow users to have an intuitive operating interface (Enjoyment AI)," and "It is evaluated as being technically feasible (Realist AI)."

[0780] Example prompt: "Please provide suggestions for refining our new mobile app idea."

[0781] Presentation file creation support function

[0782] The user inputs the presentation theme and the number of slides required from their device. For example, a user requests a 10-slide presentation on a "new mobile app." The device then sends the input information to the server. The server generates a presentation structure based on the theme, and the generation AI automatically creates the slide content and design. The generated presentation file is then sent to the user's device, where it can be viewed and edited.

[0783] Specific examples

[0784] A user requests a 10-slide presentation for a "new mobile app." The AI ​​automatically generates content such as an introduction, target market, product features, competitive analysis, marketing strategy, financial plan, development roadmap, risks and countermeasures, future outlook, and conclusion.

[0785] Example prompt: "Create a 10-slide presentation about a new mobile app."

[0786] Code generation for mockup sites

[0787] The user enters the purpose and basic requirements of the mockup site into input fields on the device. For example, they request a "task management app mockup." The device then sends the requirements to the server. The server analyzes the input requirements and uses a generative AI model to generate the necessary HTML, CSS, and JavaScript code. The generated code is then sent to the device, which displays it to the user and allows them to run and modify it.

[0788] Specific examples

[0789] When a user requests a "mockup of a task management app," the AI ​​generates HTML, CSS, and JavaScript code that includes features such as "displaying a to-do list, adding and deleting tasks, and managing task completion status."

[0790] Example prompt: "Generate HTML, CSS, and JavaScript code for a task management app."

[0791] Virtual evaluation function

[0792] Users upload their ideas and presentation materials from their devices. For example, a user may submit a "presentation for a new mobile app." The server analyzes the submitted materials, and the generative AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The evaluation results and suggestions for improvement are generated and sent to the device, which then displays them to the user.

[0793] As a result, the present invention can provide consistent support from refining ideas to preparing presentations and virtual evaluation, reducing the burden on contest participants and improving the overall level.

[0794] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0795] Idea brush-up function processing steps

[0796] Step 1:

[0797] The user inputs an idea.

[0798] Specific operation: The user enters "New mobile app idea" in the dedicated input field on the device and clicks the "Submit button."

[0799] Input: User's idea data (text format)

[0800] Output: When the send button is pressed, the idea data proceeds to the next processing step.

[0801] Step 2:

[0802] The device sends the idea to the server.

[0803] Specific operation: The device converts the input idea data into an HTTP request (e.g., POST request) and sends it to the server.

[0804] Input: User's idea data (text format)

[0805] Output: Idea data sent to the server

[0806] Step 3:

[0807] The server analyzes the received ideas.

[0808] How it works: The server processes the received idea data using Python scripts, converting it into a format that can be analyzed by the AI ​​model, and segmenting the text data to extract keywords and themes.

[0809] Input: Submitted idea data (text format)

[0810] Output: Parsed data (structured data)

[0811] Step 4:

[0812] The server transfers the ideas to a generative AI model with four different personalities.

[0813] Specific operation: The server sends the analyzed data to each AI model (Dreamer AI, Hedonist AI, Realist AI, Critic AI) as input data. It calls the model's API and passes the analyzed data.

[0814] Input: Parsed data (structured data)

[0815] Output: Feedback data from each AI model

[0816] Step 5:

[0817] The server integrates the feedback from each AI.

[0818] How it works: The server integrates the feedback data returned by each AI model and compiles it into a comprehensive set of improvement suggestions. It uses an integrated algorithm to generate consistent feedback.

[0819] Input: Feedback data from each AI (text format)

[0820] Output: Consolidated improvement suggestions (text format)

[0821] Step 6:

[0822] The server sends the integrated improvement suggestions to the terminal.

[0823] Specific operation: The server returns the integrated improvement suggestions to the terminal as an HTTP response.

[0824] Input: Consolidated improvement suggestions (text format)

[0825] Output: Improvement suggestions sent to the device (text format)

[0826] Step 7:

[0827] The device displays improvement suggestions to the user.

[0828] Specific operation: The device displays the received improvement suggestions in the user interface for the user to view, using a dialog box or a dedicated display area.

[0829] Input: Improvement suggestions received from the server (in text format)

[0830] Output: Improvement suggestions displayed to the user (in text format)

[0831] Presentation file creation support function processing steps

[0832] Step 1:

[0833] The user inputs the presentation topic and number of slides.

[0834] Specific operation: The user enters "New mobile app" and the number of slides "10" into the input fields on the device and presses the submit button.

[0835] Input: Presentation topic and number of slides (text format)

[0836] Output: When the submit button is pressed, the input data proceeds to the next processing step.

[0837] Step 2:

[0838] The terminal sends the input information to the server.

[0839] Specific operation: The device sends the entered theme and number of slides to the server via an HTTP request.

[0840] Input: Presentation topic and number of slides (text format)

[0841] Output: Themes and slide counts sent to the server

[0842] Step 3:

[0843] The server generates the presentation configuration.

[0844] How it works: The server uses a generative AI model to generate a proposed structure for each slide, breaking down the content based on the theme and designing an appropriate slide structure.

[0845] Input: Presentation topic and number of slides (text format)

[0846] Output: Slide layout proposal (structured data)

[0847] Step 4:

[0848] The server creates the slide content and design.

[0849] How it works: The server uses a generative AI model to automatically generate the text content and design elements (e.g., graphs and images) for each slide.

[0850] Input: Slide layout plan (structured data)

[0851] Output: Slide content and design (file format)

[0852] Step 5:

[0853] The server transmits the generated presentation file to the terminal.

[0854] Specific operation: The server returns the generated presentation file to the terminal as an HTTP response.

[0855] Input: Slide content and design (file format)

[0856] Output: Presentation file sent to your device

[0857] Step 6:

[0858] Allows the device to view and edit presentation files.

[0859] Specific operation: The device displays the received presentation file and provides an editor that allows the user to easily edit it.

[0860] Input: Presentation file (file format) received from the server

[0861] Output: A presentation file that users can view and edit

[0862] (Application example 1)

[0863] 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."

[0864] The purpose of this invention is to enable factory technicians and engineers to quickly and effectively refine ideas for improving new production lines and production processes, and to automatically generate the necessary information, such as presentation materials and code. In particular, by providing consistent support from idea refinement to evaluation, the invention aims to provide efficient work support and solve the problem of improving factory productivity.

[0865] 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.

[0866] In this invention, the server includes a receiving means, an analysis means for analyzing the input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, a integrating means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, an execution means for testing on an actual machine the code generated based on the input ideas, and a display means for allowing contest participants to receive the improvement proposals in real time. This enables factory technicians and engineers to quickly and effectively brush up on new ideas, create presentation materials, and generate and evaluate mockup code.

[0867] "Receiving means" refers to a device or process by which the system receives data or ideas input by a user.

[0868] An "analysis means" is a device or process whose purpose is to understand and analyze the content of input data or ideas.

[0869] A "brush-up means" is a device or process that generates improvement proposals based on analyzed data using multiple algorithms with different characteristics.

[0870] The "integration means" is a device or process that integrates multiple generated improvement proposals into one.

[0871] "Output means" refers to a device or process for providing the user with the integrated improvement suggestions and generated data.

[0872] An "execution means" is a device or process intended to test the generated code or proposals in a real environment or device.

[0873] "Display means" means a device or process for visually presenting improvement suggestions and feedback to the user in real time.

[0874] A "presentation generation means" is a device or process that automatically creates presentation materials based on an input theme.

[0875] A "script generator" is a device or process that automatically generates a spoken script to complement the content of a presentation.

[0876] "Code generator" means a device or process that generates mockup code for a website or application based on input requirements.

[0877] An "evaluation means" is a device or process that evaluates generated code or proposals in a virtual environment and provides results.

[0878] The present invention is a system that allows engineers and technicians to effectively refine ideas for improving new production lines and production processes using factory robots, generate presentation materials and mockup code, and perform virtual evaluations. Specific embodiments of this system are described below.

[0879] System Overview

[0880] This system mainly consists of a server and smart glasses (terminals) used by users. The server includes a receiving means, an analyzing means, a brushing up means, a integrating means, an outputting means, an executing means, a displaying means, a presentation generating means, a script generating means, a code generating means, and an evaluation means.

[0881] Idea brush-up function

[0882] The terminal provides an interface for users to input ideas. For example, a user can input and submit an "idea for automating a new production line." The server's analysis means analyzes this idea and sends it to AI models with different personalities: a dreamer, a hedonist, a realist, and a critic. Each model generates improvement suggestions from its own unique perspective, and these suggestions are integrated by the integration means and fed back to the user in real time via the terminal's display means.

[0883] Presentation file creation support function

[0884] The user inputs the theme of the presentation and the number of slides required from the terminal. For example, a request is made for "Explanation of the automation of a new production line" with 10 slides. The server's presentation generation means creates automatically generated slides based on the theme and provides them to the user through the output means. In addition, an oral manuscript to complement the presentation is generated by the script generation means and provided to the user.

[0885] Code generation for mockup sites

[0886] A user can input the purpose and basic requirements of the mockup site from a terminal. For example, a user can request a "mockup of a task management app that improves productivity." The server's code generation means automatically generates the necessary HTML, CSS, and JavaScript code based on the requirements and provides it to the user through the output means. The generated code is then executed in real time through the execution means.

[0887] Virtual evaluation function

[0888] Users upload their ideas and presentation materials from their devices to the server. For example, a user submits a "presentation material for a new production line." The server's evaluation means analyzes the submitted materials and performs a virtual evaluation from the perspectives of originality, feasibility, user satisfaction, etc. The evaluation results are fed back to the user via the output means.

[0889] Specific examples

[0890] For example, if an engineer inputs "an idea for automating a new production line," the following prompt sentence is generated:

[0891] New production line automation idea: To improve production efficiency, we would like to introduce a real-time monitoring system using AI.

[0892] In response to this idea, the dreamer AI suggests that "fully automating it in the future is possible," while the realist AI points out that "integration with the current system is a challenge." By combining these feedbacks, users can obtain refined ideas.

[0893] As described above, by using this system, factory technicians and engineers can quickly and efficiently generate new ideas and create presentation materials and implementation plans.

[0894] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0895] Step 1:

[0896] A user inputs an idea using a terminal, for example, a prompt sentence such as "An idea for automating a new production line," and clicks the submit button. The input data is sent to the server.

[0897] Step 2:

[0898] The server analyzes the received ideas. It uses analytical tools to convert the content of the prompt into structured data and forwards the data to AIs with different personalities (Dreamer, Hedonist, Realist, Critic). In this step, the input data is passed through a text analysis algorithm and converted into a format that can be handled by various AIs.

[0899] Step 3:

[0900] The server generates feedback using each AI model. The dreamer AI suggests the idea's future potential, the hedonist AI suggests elements that will improve the user experience, the realist AI evaluates the idea's technical feasibility, and the critic AI comments on the idea's consistency and marketability. Each feedback is sent back to the server.

[0901] Step 4:

[0902] The server consolidates the generated feedback. It uses a consolidation method to combine the feedback from each AI into a single consolidated improvement proposal. This process includes prioritizing the feedback and merging overlapping elements.

[0903] Step 5:

[0904] The integrated improvement proposals are sent to the terminal through the output means. The user receives feedback in real time and the feedback is displayed on the display means of the terminal. In this step, the integrated data is converted into a user-friendly format and visually displayed.

[0905] Step 6:

[0906] The user inputs the topic and number of slides of the presentation into the terminal. For example, a request is made for "Explanation of the automation of a new production line" with 10 slides. The input data is sent to the server again.

[0907] Step 7:

[0908] The server uses a presentation generation means to automatically create presentation slides based on the theme. The server uses a generative AI model to automatically place appropriate content and design on each slide. The generated slides are then sent to the terminal via an output means.

[0909] Step 8:

[0910] An oral script is generated to complement the presentation. The user inputs the presentation content and time, and the server creates the oral script using a script generation means. The created oral script is sent to the terminal, where the user can check the display.

[0911] Step 9:

[0912] A user inputs requirements for a mockup site using a terminal. For example, they input requirements such as "a mockup of a task management app that improves productivity" and submit the request.

[0913] Step 10:

[0914] The server uses the code generation means to generate the necessary HTML, CSS, and JavaScript code based on the input requirements. The generated code is sent to the terminal through the output means, allowing the user to try it out on the actual device in real time.

[0915] Step 11:

[0916] The user uploads the ideas and presentation materials they have created from their terminal to the server, and the input data is sent to the evaluation means.

[0917] Step 12:

[0918] The server uses the evaluation means to analyze the submitted materials and conduct a virtual evaluation from the perspectives of originality, feasibility, user satisfaction, etc. The evaluation results are sent to the terminal via the output means and fed back to the user.

[0919] The above is the specific processing flow of the system that realizes the application example.

[0920] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0921] Understood. The following describes in detail the mode for carrying out the invention based on the claims.

[0922] ---

[0923] This invention combines a contest support system using generative AI with an emotion engine that recognizes user emotions to more effectively refine ideas, create presentation files, generate code for mockup sites, create oral presentation scripts, and participate in virtual evaluations. This system allows contest participants to save time and create high-quality ideas and presentations that take emotions into consideration.

[0924] System Overview

[0925] This system is mainly divided into a server and a terminal (user device), each of which performs processing according to its role. Below we will explain each major component and its specific operation.

[0926] Example of idea brush-up function

[0927] The terminal provides an interface for accepting user input. The user inputs an idea and clicks the submit button to send the idea to the system. For example, the user inputs "an idea for a new mobile app."

[0928] The server analyzes the received ideas and transfers the data to four AIs with different personalities: a Dreamer AI, a Hedonist AI, a Realist AI, and a Critic AI. The Dreamer AI proposes the idea's future potential, the Hedonist AI proposes elements to improve the user experience, the Realist AI evaluates the idea's technical feasibility, and the Critic AI comments on the idea's consistency and marketability.

[0929] The server also uses emotion recognition to identify emotions from user input and behavior. This emotional information can then be used to further optimize the AI ​​feedback. For example, if the user is not satisfied with an idea, the Hedonist AI will suggest more appealing elements.

[0930] Once these AI-generated feedbacks are generated, the server integrates the suggestions and presents them as improvement points for the user, which are then sent to the device, where they are displayed to the user.

[0931] Presentation file creation support function

[0932] Users input the presentation topic and the number of slides they require from their device. For example, they can request a 10-slide presentation on "New Mobile Apps."

[0933] The server generates a presentation structure based on the theme, and the generation AI automatically creates the content and design of the slides. In addition, an emotion recognition system analyzes the user's emotional information and optimizes the presentation content based on that information. For example, if anxiety about preparing a presentation is detected, the server will suggest concise and easy-to-understand slides.

[0934] The final presentation file is sent to the user's terminal, where it can be viewed and edited.

[0935] An embodiment of the code generation function of the mockup site

[0936] The device provides an interface where the user can input the purpose and basic requirements of the mockup site. For example, a user may request a "mockup of a task management app."

[0937] The server analyzes the input requirements and generates the necessary HTML, CSS, and JavaScript code. Furthermore, an emotion recognition mechanism analyzes the user's emotional information and optimizes the design of the mockup code based on that information. For example, if the user prefers a simple and easy-to-use design, the server generates code that includes design elements that meet that preference.

[0938] The generated code is sent to the terminal, which displays it to the user and allows it to be executed and modified.

[0939] Presentation oral manuscript preparation support implementation form

[0940] The user inputs the presentation content and presentation time from the terminal. For example, they request a "3-minute presentation on a new mobile app."

[0941] The server extracts the main points of the speech based on the input content and time, and generates an oral transcript. Furthermore, an emotion recognition unit analyzes the user's emotional information and optimizes the transcript content based on that information. For example, it generates a transcript that includes positive and powerful expressions to help the user speak with confidence.

[0942] The generated oral transcript is sent to the terminal and can be used for display and practice on the terminal.

[0943] Embodiment of the virtual evaluation function

[0944] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[0945] The server analyzes the submitted materials, and the generating AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. An emotion recognition system analyzes the user's emotions and reflects that information in the evaluation. For example, if a user feels anxious about being evaluated, an encouraging message can be included.

[0946] The evaluation results and points for improvement are generated and sent to the device, which then displays them to the user and proposes an action plan for the next step.

[0947] ---

[0948] In this way, by combining an emotion engine, the present invention realizes a system that supports idea refinement, presentation preparation, and virtual evaluation while taking into consideration the user's emotions, allowing users to achieve better results and raising the overall level of the contest.

[0949] The processing flow will be explained below.

[0950] I understand. Now, I will explain the flow of program processing of the invention based on the claims, broken down into specific steps.

[0951] ---

[0952] Idea brush-up function

[0953] Step 1:

[0954] A user enters an idea into the device and clicks the submit button. For example, the user enters "Idea for a new mobile app" into the text field.

[0955] Step 2:

[0956] The terminal transmits the user's input data to the server.

[0957] Step 3:

[0958] The server analyzes the received idea text and uses a natural language processing engine to extract key elements and concepts.

[0959] Step 4:

[0960] Based on the analysis results, the server transfers the data to four AIs (Dreamer AI, Hedonist AI, Realist AI, and Critic AI).

[0961] Step 5:

[0962] Each AI generates feedback from its own perspective.

[0963] Dreamer AI: Suggests future possibilities and dream elements of ideas.

[0964] Hedonist AI: Suggests enjoyable elements that improve the user experience.

[0965] Realistic AI: Point out technical feasibility and practical challenges.

[0966] Critic AI: Comments on the overall evaluation and marketability of the idea.

[0967] Step 6:

[0968] The server uses emotion recognition means to recognize emotions from the user's input and actions, for example, by analyzing the user's facial expressions and input speed.

[0969] Step 7:

[0970] The server optimizes the AI's feedback based on the recognized emotional information. For example, if the user is dissatisfied with an idea, the Hedonist AI will suggest more positive elements.

[0971] Step 8:

[0972] The server aggregates the feedback from the four AIs and generates unified improvement suggestions.

[0973] Step 9:

[0974] The server sends the integrated improvement suggestions to the user's terminal.

[0975] Step 10:

[0976] The device displays integrated improvement suggestions to the user.

[0977] ---

[0978] Presentation file creation support function

[0979] Step 1:

[0980] The user inputs the presentation topic and the number of slides required from the device. Example: Requesting 10 slides for a presentation on "New Mobile App."

[0981] Step 2:

[0982] The device sends a request to the server, including the theme and number of slides.

[0983] Step 3:

[0984] The server analyzes the theme and determines the basic framework for the presentation, creating sections such as "Overview," "Feature Introduction," and "Market Analysis."

[0985] Step 4:

[0986] The server generates the content for each section and uses AI to automatically create slide designs.

[0987] Step 5:

[0988] The server analyzes the user's emotional information using emotion recognition means, e.g., analyzing the user's facial expression or voice tone.

[0989] Step 6:

[0990] The server then optimizes the presentation content based on the emotional information it recognizes. For example, it suggests simple, friendly slides to a user who is feeling nervous.

[0991] Step 7:

[0992] The server creates the final slide deck and converts it to the appropriate format (e.g. PowerPoint, PDF).

[0993] Step 8:

[0994] The server transmits the generated presentation file to the user's terminal.

[0995] Step 9:

[0996] The device displays the presentation file to the user and allows them to download and edit it as needed.

[0997] ---

[0998] Code generation for mockup sites

[0999] Step 1:

[1000] A user inputs the purpose and basic requirements of the mockup site from their device. For example, they request a "task management app mockup."

[1001] Step 2:

[1002] The terminal transmits the requirement data to the server.

[1003] Step 3:

[1004] The server analyzes the requirements and extracts the necessary components and UI design elements.

[1005] Step 4:

[1006] The server generates the necessary HTML, CSS, and JavaScript code based on the analysis results.

[1007] Step 5:

[1008] The server uses emotion recognition means to analyze the user's emotion information, such as the user's typing speed and screen transition frequency.

[1009] Step 6:

[1010] The server optimizes the design of the mockup code based on the recognized emotion information. For example, if the user prefers a simple design, the server generates code that meets that preference.

[1011] Step 7:

[1012] The server combines the generated files (HTML, CSS, JavaScript) into a single mockup file.

[1013] Step 8:

[1014] The server sends the integrated mockup code to the user's device.

[1015] Step 9:

[1016] The device displays a mockup site and allows the user to run and modify it.

[1017] ---

[1018] Presentation manuscript preparation support

[1019] Step 1:

[1020] The user inputs the presentation content and presentation time from the device. Example: Request a "3-minute presentation on a new mobile app."

[1021] Step 2:

[1022] The device sends a request including the presentation content and time to the server.

[1023] Step 3:

[1024] The server extracts the main points of the speech based on the content and time, and creates the basic structure of the oral manuscript.

[1025] Step 4:

[1026] The server summarizes what is said and generates an oral transcript by adding appropriate storytelling elements.

[1027] Step 5:

[1028] The server uses emotion recognition means to analyze the user's emotion information, for example, by analyzing the user's tone of voice and pronunciation rhythm.

[1029] Step 6:

[1030] The server optimizes the content of the transcript based on the recognized emotional information, for example by generating a transcript that includes positive and powerful expressions to help the user speak with confidence.

[1031] Step 7:

[1032] The server transmits the generated oral manuscript to the user's terminal.

[1033] Step 8:

[1034] The terminal displays the oral transcript to the user and provides tools for practice.

[1035] ---

[1036] Virtual evaluation function

[1037] Step 1:

[1038] Users can upload ideas and presentation materials they have created from their devices. For example, submit a "Presentation material for a new mobile app."

[1039] Step 2:

[1040] The terminal transmits the materials to the server.

[1041] Step 3:

[1042] The server analyzes the submitted materials and begins evaluation based on the evaluation criteria. For example, analysis is performed using natural language processing or machine learning.

[1043] Step 4:

[1044] The server analyzes the user's emotional information using emotion recognition means. For example, analyzing the user's facial expression and tone of voice when submitting documents.

[1045] Step 5:

[1046] The server optimizes the evaluation based on the recognized emotion information. For example, it includes an encouraging message for a user who is nervous about submitting a document.

[1047] Step 6:

[1048] The server generates an evaluation based on the idea's originality, feasibility, user satisfaction, etc.

[1049] Step 7:

[1050] Based on the evaluation, the server will extract specific areas for improvement.

[1051] Step 8:

[1052] The server sends the evaluation results and improvements to the user's device.

[1053] Step 9:

[1054] The device displays the evaluation results and areas for improvement to the user and suggests an action plan for the next step.

[1055] ---

[1056] Based on the above processing steps, users can receive consistent support from the system and efficiently proceed through the process from refining their ideas to preparing presentations and virtual evaluations. By combining it with an emotion engine, support can be provided while taking into consideration the user's emotions, resulting in higher quality output.

[1057] Example 2

[1058] 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."

[1059] Contest participants often spend a lot of time and effort refining their ideas, creating presentation files, and generating mockups of websites and applications. Furthermore, they struggle to create high-quality deliverables because they lack optimal feedback and suggestions based on the user's emotions. This invention aims to automate these processes while providing support that takes the user's emotions into consideration.

[1060] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a receiving means, an analysis means for analyzing input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, an integration means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, an emotion engine for recognizing the user's emotions, and an optimization means for optimizing the generated improvement proposals based on the analysis results by the emotion engine. This enables the user to reduce effort and time and efficiently create high-quality ideas and presentation materials that take emotions into consideration.

[1061] "Receiving means" is a function for receiving data and information sent from a user.

[1062] "Analysis means" is a function that analyzes and evaluates input data and information.

[1063] "Brush-up means" is a function that generates improvement suggestions using multiple algorithms based on the analysis results.

[1064] "Integration means" is a function that organizes and combines multiple improvement proposals into a single integrated proposal.

[1065] The "output means" is a function for providing the user with the integrated improvement proposals and the generated files.

[1066] The "emotion engine" is a feature used to analyze the user's emotional state and optimize feedback and suggestions.

[1067] The "optimization means" is a function that adjusts feedback and output according to the user's emotional state based on the analysis results of the emotion engine.

[1068] The "presentation generation means" is a function that automatically generates a presentation file based on an input theme.

[1069] "Code generation means" is a function that automatically generates mockup code for websites and applications based on input requirements.

[1070] The present invention is a user assistance system that uses a generative AI model, and is implemented by the following main components and their processing flow.

[1071] System Overview

[1072] This system is composed of a server and a terminal (user device), each of which performs processing according to its role. Each component has the following functions.

[1073] Idea brush-up function

[1074] The user inputs the idea into the terminal and sends it to the system by pressing the send button. For example, the user inputs "Idea for a new mobile app."

[1075] The device uses a receiving means to send this idea to the server. The server then analyzes the idea using an analytical means and distributes the data to four algorithms with different personalities: Dreamer AI, Hedonist AI, Realist AI, and Critic AI. Each AI provides the following feedback:

[1076] Visionary AI: Proposing future possibilities.

[1077] Hedonist AI: Suggests elements to improve the user experience.

[1078] Realist AI: Assessing technical feasibility.

[1079] Critic AI: Evaluates the consistency and marketability of ideas.

[1080] The server analyzes the user's emotions using an emotion engine and optimizes the feedback. For example, if the user expresses dissatisfaction, the Hedonist AI will suggest more appealing elements. These feedbacks are integrated by the integration means and provided to the user as improvement points via the output means.

[1081] Example prompt sentence:

[1082] "Tell us your ideas. We'll have a Dreamer AI, a Hedonist AI, a Realist AI, and a Critic AI to give you feedback."

[1083] Presentation file creation support function

[1084] The user inputs the topic of the presentation and the number of slides required into the device, for example, "Request a 10-slide presentation on a new mobile app."

[1085] The device sends this information to the server. The server uses a presentation generation means to automatically generate the content and design of the slides and analyzes the user's emotional state using an emotion engine. By providing slides that succinctly summarize the important points based on the emotional information, the presentation is optimized to a structure that is less likely to make the user feel anxious. The generated presentation file is sent to the device, where it can be edited by the user.

[1086] Example prompt sentence:

[1087] "Please tell me the topic of your presentation and how many slides you need."

[1088] Code generation for mockup sites

[1089] The user inputs the purpose and basic requirements of the mockup site into the device, for example, requesting a "mockup of a task management app."

[1090] The device sends this to the server, which uses a code generator to generate HTML, CSS, and JavaScript code based on the input requirements. The server uses an emotion engine to analyze the user's emotions and optimize design elements based on that. For example, if a user prefers a simple design, the server will generate code that meets that preference. The generated code is then sent to the device, where the user can run and modify it.

[1091] Example prompt sentence:

[1092] "What is the purpose and basic requirements of the mockup site?"

[1093] Presentation script creation support function

[1094] The user inputs the presentation content and presentation time into the terminal. For example, they request a "3-minute presentation on a new mobile app."

[1095] The terminal sends this information to the server, which then uses an oral script generation means to extract the main points of the speech and generate a script. Based on the analysis results of the emotion engine, the server generates a script with positive and powerful expressions, optimizing it so that the user can speak with confidence. The generated script is sent to the terminal and can be used by the user for display and practice.

[1096] Example prompt sentence:

[1097] Please tell me the content of your presentation and the time of your presentation.

[1098] Virtual evaluation function

[1099] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[1100] The device sends the materials to the server, which then evaluates them using analytical means. A generative AI model is used to perform a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. An emotion engine analyzes the user's emotions and reflects them in the evaluation. For example, it generates evaluation results that include encouraging messages to alleviate evaluation anxiety. The evaluation results and points for improvement are sent to the device and displayed to the user, providing an action plan for the next step.

[1101] Example prompt sentence:

[1102] "Upload your ideas and presentation materials and we'll do a virtual evaluation."

[1103] As described above, the present invention effectively supports idea refinement, presentation preparation, mockup creation, oral manuscript creation, and virtual evaluation while taking into consideration the user's emotions by combining an emotion engine. This allows users to efficiently create high-quality deliverables and improve overall results.

[1104] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1105] Idea brush-up function

[1106] Step 1:

[1107] The user enters an idea into the device and clicks the submit button. The entered idea might be something like "An idea for a new mobile app."

[1108] Step 2:

[1109] The terminal sends the input idea to the server using an HTTP request. The input is the idea data, and the output is confirmation of the request.

[1110] Step 3:

[1111] The server analyzes the received ideas using an analysis means. The input is the received idea data, and the output is the analysis result. Specifically, the server uses a text analysis algorithm to extract the main elements of the idea.

[1112] Step 4:

[1113] The server distributes the data to four AIs with different personalities (Dreamer AI, Hedonist AI, Realist AI, and Critic AI) based on the analysis results. The input is the analysis results, and the output is the data sent to each AI. Requests are sent via a RESTful API.

[1114] Step 5:

[1115] The server receives feedback from each AI. The dreamer AI suggests future possibilities, the enjoyer AI suggests ways to improve the user experience, the realist AI evaluates technical feasibility, and the critic AI evaluates consistency and marketability. The input is the data sent to the AI, and the output is feedback information.

[1116] Step 6:

[1117] The server uses an emotion engine to analyze the user's emotional information. For example, if an emotion indicating dissatisfaction is detected, the server adjusts the feedback content based on that. The input is the user's emotional information, and the output is the emotion analysis result.

[1118] Step 7:

[1119] The server integrates the feedback from each AI with the results of emotion analysis using an integration method. Specifically, it organizes the feedback content and reconstructs it into an optimal form for the user. The input is the feedback information and the results of emotion analysis, and the output is an integrated improvement proposal.

[1120] Step 8:

[1121] The server transmits the integrated improvement proposal to the terminal using the output means. At this time, an HTTP response is used. The input is the integrated improvement proposal, and the output is transmission confirmation information.

[1122] Step 9:

[1123] The terminal displays the received improvement suggestions to the user. The input is the improvement suggestions, and the output is the displayed suggestion information.

[1124] Presentation file creation support function

[1125] Step 1:

[1126] The user inputs the topic of the presentation and the number of slides required into the device, for example, "Request a 10-slide presentation on a new mobile app."

[1127] Step 2:

[1128] The terminal sends information about the theme and the number of slides to the server. The input is the theme and the number of slides, and the output is a confirmation of the request.

[1129] Step 3:

[1130] The server generates a presentation structure based on the theme. It uses a generative AI model to automatically create the slide content and design. The input is the theme and the number of slides, and the output is a presentation file.

[1131] Step 4:

[1132] The server uses an emotion engine to analyze the user's emotional information and optimize the presentation content. For example, if anxiety is detected, it creates concise and easy-to-understand slides. The input is the user's emotional information, and the output is the emotion analysis results.

[1133] Step 5:

[1134] The server sends the final presentation file to the terminal, where the input is the optimized presentation file and the output is a transmission confirmation.

[1135] Step 6:

[1136] The terminal displays the received presentation file and allows the user to edit it. The input is the presentation file and the output is the displayed file.

[1137] Code generation for mockup sites

[1138] Step 1:

[1139] The user inputs the purpose and basic requirements of the mockup site into the device, for example, requesting a "mockup of a task management app."

[1140] Step 2:

[1141] The terminal sends this to the server. The input is the requirements for the mockup site, and the output is confirmation of the request submission.

[1142] Step 3:

[1143] The server parses the input requirements and uses a generative AI model to generate the necessary HTML, CSS, and JavaScript code. The input is the requirements for the mockup site, and the output is the mockup code.

[1144] Step 4:

[1145] The server uses an emotion engine to analyze the user's emotional information and optimize the code design. For example, if a user prefers a simple design, it generates code that includes design elements that meet that preference. The input is the user's emotional information, and the output is optimized code.

[1146] Step 5:

[1147] The server sends the generated code to the terminal. The input is the generated code and the output is the transmission confirmation information.

[1148] Step 6:

[1149] The terminal displays the received code and allows the user to execute and modify it. The input is the generated code and the output is the displayed code.

[1150] Presentation script creation support function

[1151] Step 1:

[1152] The user inputs the presentation content and presentation time into the terminal. For example, the user requests a "3-minute presentation on a new mobile app."

[1153] Step 2:

[1154] The terminal sends this information to the server. The input is the presentation content and time, and the output is confirmation of the request.

[1155] Step 3:

[1156] The server extracts the main points of the speech based on the content and time, and generates an oral transcript. The input is the presentation content and time, and the output is the oral transcript.

[1157] Step 4:

[1158] The server uses an emotion engine to analyze the user's emotional information and optimize the content of the spoken script. For example, it generates a script containing positive and powerful expressions to help the user speak with confidence. The input is the user's emotional information, and the output is the optimized script.

[1159] Step 5:

[1160] The server transmits the generated oral manuscript to the terminal, where the input is the generated manuscript and the output is transmission confirmation information.

[1161] Step 6:

[1162] The terminal displays the received oral transcript so that the user can use it for practice. The input is the generated transcript and the output is the displayed transcript.

[1163] Virtual evaluation function

[1164] Step 1:

[1165] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[1166] Step 2:

[1167] The terminal sends the submitted documents to the server. The input is the submitted documents, and the output is confirmation of the request submission.

[1168] Step 3:

[1169] The server analyzes the submitted materials and uses a generative AI model to perform a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The input is the submitted materials, and the output is the virtual evaluation results.

[1170] Step 4:

[1171] The server uses an emotion engine to analyze the user's emotions and reflects that information in the evaluation. For example, if a user feels anxious about being evaluated, the server generates an evaluation result that includes an encouraging message. The input is the user's emotional information, and the output is an optimized evaluation result.

[1172] Step 5:

[1173] The server generates evaluation results and improvements and sends them to the terminal. The input is the evaluation results and improvements, and the output is a transmission confirmation.

[1174] Step 6:

[1175] The terminal displays the evaluation results and points for improvement to the user and proposes an action plan for the next step. The input is the evaluation results and points for improvement, and the output is the displayed results and suggestions.

[1176] The above is the specific flow of processing in this system.

[1177] (Application example 2)

[1178] 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."

[1179] When multiple robots work together in a factory, maintenance and work optimization proposals for each robot may not be implemented promptly. This can result in reduced production efficiency and robot breakdowns or malfunctions. Furthermore, workers who are not familiar with robot operation and maintenance may find it difficult to take appropriate action, which could lead to further problems. It is necessary to resolve these issues and efficiently perform maintenance while optimizing robot operation.

[1180] 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.

[1181] In this invention, the server includes a receiving means, an analysis means for analyzing input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, an integration means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, a data collection means for collecting and analyzing robot operation data, an optimization proposal means for proposing task optimization based on the robot's operating status, and an anomaly detection means for detecting robot abnormalities and the need for maintenance. This enables real-time analysis of the robot's operations in a factory, efficient task proposals, and early anomaly detection.

[1182] definition statement

[1183] The "receiving means" is a means for receiving various input information such as ideas from users and robot operation data.

[1184] "Analysis means" refers to the means for analyzing ideas and data received by the receiving means, and for understanding and evaluating their contents.

[1185] The "brush-up means" is a means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results obtained by the analysis means.

[1186] The "integration means" is a means for combining multiple improvement proposals generated by the brush-up means into one.

[1187] The "output means" is a means for providing the improvement proposal obtained by the integration means to the user.

[1188] The "data collection means" is a means for collecting operational data from robots in a factory.

[1189] The "optimization suggestion means" is a means for analyzing the robot operation data collected by the data collection means and making suggestions for improving work efficiency.

[1190] The "abnormality detection means" is a means for monitoring the operation data of the robot and detecting abnormalities or the need for maintenance.

[1191] MODE FOR CARRYING OUT THE INVENTION

[1192] The present invention relates to a system for improving the efficiency of robot management in a factory and supporting maintenance and work optimization. Specific embodiments for carrying out the present invention will be described below.

[1193] System Overview

[1194] This system is mainly composed of a server and a terminal (user device), each of which performs processing according to its respective role. The server is responsible for analyzing and generating data, while the user's terminal is responsible for inputting and outputting data.

[1195] Robot data collection and analysis

[1196] The terminal provides a means for collecting operational data from the robots in the factory, such as temperature, operating time, and the number of errors that have occurred.

[1197] The server has a "receiving means" that receives the collected data and an "analysis means" that analyzes the data. The analysis means evaluates the robot's operating status and detects abnormalities.

[1198] Work optimization and maintenance proposals

[1199] Based on the analysis results, the server uses the "optimization proposal method" and "anomaly detection method" to detect the need for improvement proposals and maintenance. Using these methods, specific improvement measures and maintenance proposals for the robot are generated.

[1200] For example, if robot R1 reaches a high temperature (85°C) during operation and has been operating for more than 5,000 hours, the analysis means will detect that it is experiencing stress based on that data, and the optimization suggestion means will send a signal to check the cooling system for temperature control.

[1201] Feedback and Integration

[1202] The server generates optimization and maintenance proposals using the "brush-up means," and then integrates them using the "integration means." This generates comprehensive improvement proposals and provides them to the user.

[1203] The terminal uses the "output means" to display the integrated improvement proposals to the user, for example, as an alert on the user's smartphone.

[1204] Examples and prompts

[1205] Below is a concrete example of how the system works.

[1206] Specific examples

[1207] Robot R1 in the factory has reached a high temperature (85°C) during operation and has been running for over 5000 hours. Analysis by the emotion engine has detected that this robot is feeling stressed. Please generate appropriate maintenance suggestions and work optimization suggestions.

[1208] Prompt Sentence Examples

[1209] "Robot R1 in the factory has reached a high temperature (85°C) during operation and has been operating for over 5000 hours. Analysis by the emotion engine has detected that this robot is experiencing stress. Please generate appropriate maintenance suggestions and work optimization suggestions."

[1210] In this way, the present invention realizes a system that improves efficiency and reliability within factories by collecting robot operation data and using a generative AI model to make specific improvement suggestions.

[1211] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1212] Program processing flow

[1213] Step 1: Data collection

[1214] The terminal collects operational data from robots in the factory.

[1215] Input: Robot operation data (temperature, operating time, number of errors, etc.)

[1216] Output: raw data collected

[1217] Specific operation: Collects data in real time from various sensors such as temperature sensors and work time recording devices and sends it to a server.

[1218] Step 2: Receiving data

[1219] The server receives the operation data sent from the terminal.

[1220] Input: Raw data from the terminal

[1221] Output: Robot movement data stored in the server

[1222] Specific operation: Receives data from the device and stores it in a database.

[1223] Step 3: Data analysis

[1224] The server analyzes the received motion data.

[1225] Input: Collected robot movement data

[1226] Output: Analysis results (temperature rise, abnormality detection, etc.)

[1227] Specific operation: Based on the received data, the temperature, operating time, and number of errors are analyzed to check for abnormalities. For example, if the temperature exceeds a set reference value (e.g., 85°C), an abnormality is detected.

[1228] Step 4: Sentiment analysis and maintenance need assessment

[1229] Based on the analysis results, the server uses an emotion engine to analyze the robot's "emotions" and evaluate the need for maintenance.

[1230] Input: Analysis results

[1231] Output: Sentiment data and maintenance suggestions

[1232] Specific operation: The emotion engine analyzes emotions, such as "feeling stressed" in response to a high temperature, and determines whether maintenance is necessary. For example, based on data such as "R1 has been operating at 85°C for 5,000 hours," it suggests checking the cooling system.

[1233] Step 5: Generate improvement suggestions

[1234] The server generates improvement suggestions using a generative AI model.

[1235] Input: Sentiment data and maintenance suggestions

[1236] Output: Improvement suggestions

[1237] Specific actions: Based on the analyzed emotions and maintenance need assessment data, the generative AI generates specific improvement suggestions, such as suggestions for improving the robot's operating environment or proposing new operating procedures.

[1238] Step 6: Proposal Integration

[1239] The server integrates multiple improvement suggestions.

[1240] Input: Multiple improvement suggestions

[1241] Output: Consolidated improvement suggestions

[1242] Specific operation: Consolidate multiple improvement suggestions generated by the generative AI into one. For example, consolidate suggestions for temperature control and maintenance needs into a clearer format.

[1243] Step 7: Provide feedback

[1244] The terminal notifies the user of the integrated proposal.

[1245] Input: Consolidated improvement suggestions

[1246] Output: User notification

[1247] Specific actions: The integrated improvement suggestions are sent to the device, and alerts and specific actions are displayed to the user. For example, a notification is displayed on the smartphone app with the message "Please check the cooling system of your R1."

[1248] The above are the specific processing steps for carrying out the present invention.

[1249] 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.

[1250] 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.

[1251] 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.

[1252] [Third embodiment]

[1253] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1254] 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.

[1255] 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).

[1256] 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.

[1257] 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.

[1258] 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).

[1259] 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.

[1260] 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.

[1261] 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.

[1262] 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.

[1263] 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.

[1264] 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."

[1265] Understood. The following describes in detail the mode for carrying out the invention based on the claims.

[1266] ---

[1267] This invention is a contest support system that uses generative AI, linking multiple AIs with different characteristics to provide functions such as idea refinement, presentation file creation, mockup site code generation, oral presentation script creation, and virtual evaluation. This system allows contest participants to save time and create higher quality ideas and presentations.

[1268] System Overview

[1269] This system is mainly divided into a server and a terminal (user device), each of which performs processing according to its role. Below we will explain each major component and its specific operation.

[1270] Example of idea brush-up function

[1271] The terminal provides an interface for accepting user input. The user inputs an idea and clicks the submit button to send the idea to the system. For example, the user inputs "an idea for a new mobile app."

[1272] The server analyzes the received ideas and transfers the data to four AIs with different personalities: a dreamer, a hedonist, a realist, and a critic. The dreamer AI proposes the idea's future potential, the hedonist AI suggests elements to improve the user experience, the realist AI evaluates the idea's technical feasibility, and the critic AI comments on the idea's consistency and marketability.

[1273] Once these AI-generated feedbacks are generated, the server integrates the suggestions and presents them as improvement points for the user, which are then sent to the device, where they are displayed to the user.

[1274] Presentation file creation support function

[1275] Users input the presentation topic and the number of slides they require from their device. For example, they can request a 10-slide presentation on "New Mobile Apps."

[1276] The server generates a presentation structure based on the theme, and the AI ​​automatically creates the slide content and design. The final presentation file is sent to the user's device, where it can be viewed and edited.

[1277] An embodiment of the code generation function of the mockup site

[1278] The device provides an interface where the user can input the purpose and basic requirements of the mockup site. For example, a user may request a "mockup of a task management app."

[1279] The server parses the input requirements and generates the necessary HTML, CSS, and JavaScript code, which is then sent to the device, which displays it to the user and allows them to run and modify it.

[1280] Presentation oral manuscript preparation support implementation form

[1281] The user inputs the presentation content and time from the terminal. For example, they can request a "3-minute presentation on a new mobile app."

[1282] The server extracts the main points of the speech based on the input content and time, and generates an oral transcript, which is sent to the terminal and can be used for display and practice.

[1283] Embodiment of the virtual evaluation function

[1284] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[1285] The server analyzes the submitted materials, and the generating AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The evaluation results and points for improvement are generated and sent to the device, which then displays the evaluation results and points for improvement to the user.

[1286] ---

[1287] In this way, the present invention reduces the burden on contest participants and raises the overall level of the contest by providing consistent support from brushing up ideas to preparing presentations and virtual evaluation.

[1288] The processing flow will be explained below.

[1289] I understand. Now, I will explain the flow of program processing of the invention based on the claims, broken down into specific steps.

[1290] ---

[1291] Idea brush-up function

[1292] Step 1:

[1293] A user inputs an idea from a device, for example, by typing "Idea for a new mobile app" into a text field.

[1294] Step 2:

[1295] The terminal transmits the user's input data to the server.

[1296] Step 3:

[1297] The server analyzes the received idea text and uses a natural language processing engine to extract key elements and concepts.

[1298] Step 4:

[1299] Based on the analysis results, the server transfers the data to four AIs (Dreamer AI, Hedonist AI, Realist AI, and Critic AI).

[1300] Step 5:

[1301] Each AI generates feedback from its own perspective.

[1302] Dreamer AI: Suggests future possibilities and dream elements of ideas.

[1303] Hedonist AI: Suggests enjoyable elements that improve the user experience.

[1304] Realistic AI: Point out technical feasibility and practical challenges.

[1305] Critic AI: Comments on the overall evaluation and marketability of the idea.

[1306] Step 6:

[1307] The server aggregates the feedback from the four AIs and generates unified improvement suggestions.

[1308] Step 7:

[1309] The server sends the integrated improvement suggestions to the user's terminal.

[1310] Step 8:

[1311] The device displays integrated improvement suggestions to the user.

[1312] ---

[1313] Presentation file creation support function

[1314] Step 1:

[1315] The user inputs the presentation topic and the number of slides required from the device. Example: Requesting 10 slides for a presentation on "New Mobile App."

[1316] Step 2:

[1317] The device sends a request to the server, including the theme and number of slides.

[1318] Step 3:

[1319] The server analyzes the theme and determines the basic framework for the presentation, creating sections such as "Overview," "Feature Introduction," and "Market Analysis."

[1320] Step 4:

[1321] The server generates the content for each section and uses AI to automatically create slide designs.

[1322] Step 5:

[1323] The server creates the final slide deck and converts it to the appropriate format (e.g. PowerPoint, PDF).

[1324] Step 6:

[1325] The server transmits the generated presentation file to the user's terminal.

[1326] Step 7:

[1327] The device displays the presentation file to the user and allows them to download and edit it as needed.

[1328] ---

[1329] Code generation for mockup sites

[1330] Step 1:

[1331] A user inputs the purpose and basic requirements of the mockup site from their device. For example, they request a "task management app mockup."

[1332] Step 2:

[1333] The terminal transmits the requirement data to the server.

[1334] Step 3:

[1335] The server analyzes the requirements and extracts the necessary components and UI design elements.

[1336] Step 4:

[1337] The server generates the necessary HTML, CSS, and JavaScript code based on the analysis results.

[1338] Step 5:

[1339] The server combines the generated files (HTML, CSS, JavaScript) into a single mockup file.

[1340] Step 6:

[1341] The server sends the integrated mockup code to the user's device.

[1342] Step 7:

[1343] The device displays a mockup site and allows the user to run and modify it.

[1344] ---

[1345] Presentation manuscript preparation support

[1346] Step 1:

[1347] The user inputs the presentation content and presentation time from the device. Example: Request a "3-minute presentation on a new mobile app."

[1348] Step 2:

[1349] The device sends a request including the presentation content and time to the server.

[1350] Step 3:

[1351] The server extracts the main points of the speech based on the content and time, and creates the basic structure of the oral manuscript.

[1352] Step 4:

[1353] The server summarizes what is said and generates an oral transcript by adding appropriate storytelling elements.

[1354] Step 5:

[1355] The server transmits the generated oral manuscript to the user's terminal.

[1356] Step 6:

[1357] The terminal displays the oral transcript to the user and provides tools for practice.

[1358] ---

[1359] Virtual evaluation function

[1360] Step 1:

[1361] Users can upload ideas and presentation materials they have created from their devices. For example, submit a "Presentation material for a new mobile app."

[1362] Step 2:

[1363] The terminal transmits the materials to the server.

[1364] Step 3:

[1365] The server analyzes the submitted materials and begins evaluation based on the evaluation criteria. For example, analysis is performed using natural language processing or machine learning.

[1366] Step 4:

[1367] The server generates an evaluation based on the idea's originality, feasibility, user satisfaction, etc.

[1368] Step 5:

[1369] Based on the evaluation, the server will extract specific areas for improvement.

[1370] Step 6:

[1371] The server sends the evaluation results and improvements to the user's device.

[1372] Step 7:

[1373] The device displays the evaluation results and areas for improvement to the user, and suggests an action plan for the next step.

[1374] ---

[1375] Based on the above-mentioned processing steps, users can efficiently proceed from refining their ideas to preparing for presentations and virtual evaluations while receiving consistent support from the system.

[1376] Example 1

[1377] 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."

[1378] Traditionally, refining ideas, creating presentations, and creating mockup websites has often been done manually, requiring a great deal of time and effort. Furthermore, many of the tasks require multiple areas of expertise, making it difficult to handle on your own. Furthermore, it has been difficult to obtain improvement suggestions from different perspectives, making it difficult to objectively evaluate the quality and feasibility of ideas.

[1379] 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.

[1380] In this invention, the server includes a receiving means, an analyzing means for analyzing data entered by a user, a proposal generating means for generating improvement proposals using multiple generative AI models with different characteristics based on the analysis results, an integrating means for integrating the generated improvement proposals, and an output means for outputting the integrated improvement proposals. This makes it possible to improve the quality of ideas, efficiently create presentation materials and mockup sites, and significantly reduce the burden on contest participants.

[1381] The "receiving means" is a device or function for receiving input data from a user.

[1382] The "analysis means" is a device or function for analyzing the data obtained by the receiving means and processing it in an appropriate form.

[1383] The "proposal generation means" is a device or function that generates improvement proposals based on the data processed by the analysis means, using multiple generative AI models with different characteristics.

[1384] An "integration means" is a device or function that integrates improvement suggestions generated by multiple generative AI models and compiles them into unified feedback.

[1385] The "output means" is a device or function for transmitting the integrated improvement proposal to a user terminal or the like and displaying it.

[1386] The "generation means" is a device or function for automatically generating a presentation file based on an input theme.

[1387] "Code Generator" means a device or function for generating mockup code for an internet site or software based on input requirements.

[1388] This invention is a contest support system that utilizes generative AI models, and uses multiple generative AI models with different characteristics to provide functions such as idea refinement, presentation file creation, mockup site code generation, oral presentation script creation, and virtual evaluation. The system is divided into a server and a terminal (user device), each of which performs processing according to its respective role.

[1389] Idea brush-up function

[1390] A user submits an idea to the system by entering it into the device's input field and clicking the submit button. For example, they enter "idea for a new mobile app." The device then sends the data to the server. The server analyzes the received idea and transfers the data to a generative AI model with multiple different personalities. For example, OpenAI's GPT-4 is used for this generative AI model.

[1391] Specifically, the Dreamer AI proposes the idea's future potential, the Enjoyer AI suggests elements that will improve the user experience, the Realist AI evaluates the idea's technical feasibility, and the Critic AI comments on the idea's consistency and marketability. Once feedback from each AI is generated, the server integrates this feedback, summarizes it as points for improvement, and sends it to the device, which then displays it to the user.

[1392] Specific examples

[1393] A user inputs an idea for a new mobile app and clicks the submit button. The generating AI then provides feedback, such as, "This idea has great potential for future growth (Visionary AI)," "It includes features that would allow users to have an intuitive operating interface (Enjoyment AI)," and "It is evaluated as being technically feasible (Realist AI)."

[1394] Example prompt: "Please provide suggestions for refining our new mobile app idea."

[1395] Presentation file creation support function

[1396] The user inputs the presentation theme and the number of slides required from their device. For example, a user requests a 10-slide presentation on a "new mobile app." The device then sends the input information to the server. The server generates a presentation structure based on the theme, and the generation AI automatically creates the slide content and design. The generated presentation file is then sent to the user's device, where it can be viewed and edited.

[1397] Specific examples

[1398] A user requests a 10-slide presentation for a "new mobile app." The AI ​​automatically generates content such as an introduction, target market, product features, competitive analysis, marketing strategy, financial plan, development roadmap, risks and countermeasures, future outlook, and conclusion.

[1399] Example prompt: "Create a 10-slide presentation about a new mobile app."

[1400] Code generation for mockup sites

[1401] The user enters the purpose and basic requirements of the mockup site into input fields on the device. For example, they request a "task management app mockup." The device then sends the requirements to the server. The server analyzes the input requirements and uses a generative AI model to generate the necessary HTML, CSS, and JavaScript code. The generated code is then sent to the device, which displays it to the user and allows them to run and modify it.

[1402] Specific examples

[1403] When a user requests a "mockup of a task management app," the AI ​​generates HTML, CSS, and JavaScript code that includes features such as "displaying a to-do list, adding and deleting tasks, and managing task completion status."

[1404] Example prompt: "Generate HTML, CSS, and JavaScript code for a task management app."

[1405] Virtual evaluation function

[1406] Users upload their ideas and presentation materials from their devices. For example, a user may submit a "presentation for a new mobile app." The server analyzes the submitted materials, and the generative AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The evaluation results and suggestions for improvement are generated and sent to the device, which then displays them to the user.

[1407] As a result, the present invention can provide consistent support from refining ideas to preparing presentations and virtual evaluation, reducing the burden on contest participants and improving the overall level.

[1408] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1409] Idea brush-up function processing steps

[1410] Step 1:

[1411] The user inputs an idea.

[1412] Specific operation: The user enters "New mobile app idea" in the dedicated input field on the device and clicks the "Submit button."

[1413] Input: User's idea data (text format)

[1414] Output: When the send button is pressed, the idea data proceeds to the next processing step.

[1415] Step 2:

[1416] The device sends the idea to the server.

[1417] Specific operation: The device converts the input idea data into an HTTP request (e.g., POST request) and sends it to the server.

[1418] Input: User's idea data (text format)

[1419] Output: Idea data sent to the server

[1420] Step 3:

[1421] The server analyzes the received ideas.

[1422] How it works: The server processes the received idea data using Python scripts, converting it into a format that can be analyzed by the AI ​​model, and segmenting the text data to extract keywords and themes.

[1423] Input: Submitted idea data (text format)

[1424] Output: Parsed data (structured data)

[1425] Step 4:

[1426] The server transfers the ideas to a generative AI model with four different personalities.

[1427] Specific operation: The server sends the analyzed data to each AI model (Dreamer AI, Hedonist AI, Realist AI, Critic AI) as input data. It calls the model's API and passes the analyzed data.

[1428] Input: Parsed data (structured data)

[1429] Output: Feedback data from each AI model

[1430] Step 5:

[1431] The server integrates the feedback from each AI.

[1432] How it works: The server integrates the feedback data returned by each AI model and compiles it into a comprehensive set of improvement suggestions. It uses an integrated algorithm to generate consistent feedback.

[1433] Input: Feedback data from each AI (text format)

[1434] Output: Consolidated improvement suggestions (text format)

[1435] Step 6:

[1436] The server sends the integrated improvement suggestions to the terminal.

[1437] Specific operation: The server returns the integrated improvement suggestions to the terminal as an HTTP response.

[1438] Input: Consolidated improvement suggestions (text format)

[1439] Output: Improvement suggestions sent to the device (text format)

[1440] Step 7:

[1441] The device displays improvement suggestions to the user.

[1442] Specific operation: The device displays the received improvement suggestions in the user interface for the user to view, using a dialog box or a dedicated display area.

[1443] Input: Improvement suggestions received from the server (in text format)

[1444] Output: Improvement suggestions displayed to the user (in text format)

[1445] Presentation file creation support function processing steps

[1446] Step 1:

[1447] The user inputs the presentation topic and number of slides.

[1448] Specific operation: The user enters "New mobile app" and the number of slides "10" into the input fields on the device and presses the submit button.

[1449] Input: Presentation topic and number of slides (text format)

[1450] Output: When the submit button is pressed, the input data proceeds to the next processing step.

[1451] Step 2:

[1452] The terminal sends the input information to the server.

[1453] Specific operation: The device sends the entered theme and number of slides to the server via an HTTP request.

[1454] Input: Presentation topic and number of slides (text format)

[1455] Output: Themes and slide counts sent to the server

[1456] Step 3:

[1457] The server generates the presentation configuration.

[1458] How it works: The server uses a generative AI model to generate a proposed structure for each slide, breaking down the content based on the theme and designing an appropriate slide structure.

[1459] Input: Presentation topic and number of slides (text format)

[1460] Output: Slide layout proposal (structured data)

[1461] Step 4:

[1462] The server creates the slide content and design.

[1463] How it works: The server uses a generative AI model to automatically generate the text content and design elements (e.g., graphs and images) for each slide.

[1464] Input: Slide layout plan (structured data)

[1465] Output: Slide content and design (file format)

[1466] Step 5:

[1467] The server transmits the generated presentation file to the terminal.

[1468] Specific operation: The server returns the generated presentation file to the terminal as an HTTP response.

[1469] Input: Slide content and design (file format)

[1470] Output: Presentation file sent to your device

[1471] Step 6:

[1472] Allows the device to view and edit presentation files.

[1473] Specific operation: The device displays the received presentation file and provides an editor that allows the user to easily edit it.

[1474] Input: Presentation file (file format) received from the server

[1475] Output: A presentation file that users can view and edit

[1476] (Application example 1)

[1477] 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."

[1478] The purpose of this invention is to enable factory technicians and engineers to quickly and effectively refine ideas for improving new production lines and production processes, and to automatically generate the necessary information, such as presentation materials and code. In particular, by providing consistent support from idea refinement to evaluation, the invention aims to provide efficient work support and solve the problem of improving factory productivity.

[1479] 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.

[1480] In this invention, the server includes a receiving means, an analysis means for analyzing the input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, a integrating means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, an execution means for testing on an actual machine the code generated based on the input ideas, and a display means for allowing contest participants to receive the improvement proposals in real time. This enables factory technicians and engineers to quickly and effectively brush up on new ideas, create presentation materials, and generate and evaluate mockup code.

[1481] "Receiving means" refers to a device or process by which the system receives data or ideas input by a user.

[1482] An "analysis means" is a device or process whose purpose is to understand and analyze the content of input data or ideas.

[1483] A "brush-up means" is a device or process that generates improvement proposals based on analyzed data using multiple algorithms with different characteristics.

[1484] The "integration means" is a device or process that integrates multiple generated improvement proposals into one.

[1485] "Output means" refers to a device or process for providing the user with the integrated improvement suggestions and generated data.

[1486] An "execution means" is a device or process intended to test the generated code or proposals in a real environment or device.

[1487] "Display means" means a device or process for visually presenting improvement suggestions and feedback to the user in real time.

[1488] A "presentation generation means" is a device or process that automatically creates presentation materials based on an input theme.

[1489] A "script generator" is a device or process that automatically generates a spoken script to complement the content of a presentation.

[1490] "Code generator" means a device or process that generates mockup code for a website or application based on input requirements.

[1491] An "evaluation means" is a device or process that evaluates generated code or proposals in a virtual environment and provides results.

[1492] The present invention is a system that allows engineers and technicians to effectively refine ideas for improving new production lines and production processes using factory robots, generate presentation materials and mockup code, and perform virtual evaluations. Specific embodiments of this system are described below.

[1493] System Overview

[1494] This system mainly consists of a server and smart glasses (terminals) used by users. The server includes a receiving means, an analyzing means, a brushing up means, a integrating means, an outputting means, an executing means, a displaying means, a presentation generating means, a script generating means, a code generating means, and an evaluation means.

[1495] Idea brush-up function

[1496] The terminal provides an interface for users to input ideas. For example, a user can input and submit an "idea for automating a new production line." The server's analysis means analyzes this idea and sends it to AI models with different personalities: a dreamer, a hedonist, a realist, and a critic. Each model generates improvement suggestions from its own unique perspective, and these suggestions are integrated by the integration means and fed back to the user in real time via the terminal's display means.

[1497] Presentation file creation support function

[1498] The user inputs the theme of the presentation and the number of slides required from the terminal. For example, a request is made for "Explanation of the automation of a new production line" with 10 slides. The server's presentation generation means creates automatically generated slides based on the theme and provides them to the user through the output means. In addition, an oral manuscript to complement the presentation is generated by the script generation means and provided to the user.

[1499] Code generation for mockup sites

[1500] A user can input the purpose and basic requirements of the mockup site from a terminal. For example, a user can request a "mockup of a task management app that improves productivity." The server's code generation means automatically generates the necessary HTML, CSS, and JavaScript code based on the requirements and provides it to the user through the output means. The generated code is then executed in real time through the execution means.

[1501] Virtual evaluation function

[1502] Users upload their ideas and presentation materials from their devices to the server. For example, a user submits a "presentation material for a new production line." The server's evaluation means analyzes the submitted materials and performs a virtual evaluation from the perspectives of originality, feasibility, user satisfaction, etc. The evaluation results are fed back to the user via the output means.

[1503] Specific examples

[1504] For example, if an engineer inputs "an idea for automating a new production line," the following prompt sentence is generated:

[1505] New production line automation idea: To improve production efficiency, we would like to introduce a real-time monitoring system using AI.

[1506] In response to this idea, the dreamer AI suggests that "fully automating it in the future is possible," while the realist AI points out that "integration with the current system is a challenge." By combining these feedbacks, users can obtain refined ideas.

[1507] As described above, by using this system, factory technicians and engineers can quickly and efficiently generate new ideas and create presentation materials and implementation plans.

[1508] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1509] Step 1:

[1510] A user inputs an idea using a terminal, for example, a prompt sentence such as "An idea for automating a new production line," and clicks the submit button. The input data is sent to the server.

[1511] Step 2:

[1512] The server analyzes the received ideas. It uses analytical tools to convert the content of the prompt into structured data and forwards the data to AIs with different personalities (Dreamer, Hedonist, Realist, Critic). In this step, the input data is passed through a text analysis algorithm and converted into a format that can be handled by various AIs.

[1513] Step 3:

[1514] The server generates feedback using each AI model. The dreamer AI suggests the idea's future potential, the hedonist AI suggests elements that will improve the user experience, the realist AI evaluates the idea's technical feasibility, and the critic AI comments on the idea's consistency and marketability. Each feedback is sent back to the server.

[1515] Step 4:

[1516] The server consolidates the generated feedback. It uses a consolidation method to combine the feedback from each AI into a single consolidated improvement proposal. This process includes prioritizing the feedback and merging overlapping elements.

[1517] Step 5:

[1518] The integrated improvement proposals are sent to the terminal through the output means. The user receives feedback in real time and the feedback is displayed on the display means of the terminal. In this step, the integrated data is converted into a user-friendly format and visually displayed.

[1519] Step 6:

[1520] The user inputs the topic and number of slides of the presentation into the terminal. For example, a request is made for "Explanation of the automation of a new production line" with 10 slides. The input data is sent to the server again.

[1521] Step 7:

[1522] The server uses a presentation generation means to automatically create presentation slides based on the theme. The server uses a generative AI model to automatically place appropriate content and design on each slide. The generated slides are then sent to the terminal via an output means.

[1523] Step 8:

[1524] An oral script is generated to complement the presentation. The user inputs the presentation content and time, and the server creates the oral script using a script generation means. The created oral script is sent to the terminal, where the user can check the display.

[1525] Step 9:

[1526] A user inputs requirements for a mockup site using a terminal. For example, they input requirements such as "a mockup of a task management app that improves productivity" and submit the request.

[1527] Step 10:

[1528] The server uses the code generation means to generate the necessary HTML, CSS, and JavaScript code based on the input requirements. The generated code is sent to the terminal through the output means, allowing the user to try it out on the actual device in real time.

[1529] Step 11:

[1530] The user uploads the ideas and presentation materials they have created from their terminal to the server, and the input data is sent to the evaluation means.

[1531] Step 12:

[1532] The server uses the evaluation means to analyze the submitted materials and conduct a virtual evaluation from the perspectives of originality, feasibility, user satisfaction, etc. The evaluation results are sent to the terminal via the output means and fed back to the user.

[1533] The above is the specific processing flow of the system that realizes the application example.

[1534] 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.

[1535] Understood. The following describes in detail the mode for carrying out the invention based on the claims.

[1536] ---

[1537] This invention combines a contest support system using generative AI with an emotion engine that recognizes user emotions to more effectively refine ideas, create presentation files, generate code for mockup sites, create oral presentation scripts, and participate in virtual evaluations. This system allows contest participants to save time and create high-quality ideas and presentations that take emotions into consideration.

[1538] System Overview

[1539] This system is mainly divided into a server and a terminal (user device), each of which performs processing according to its role. Below we will explain each major component and its specific operation.

[1540] Example of idea brush-up function

[1541] The terminal provides an interface for accepting user input. The user inputs an idea and clicks the submit button to send the idea to the system. For example, the user inputs "an idea for a new mobile app."

[1542] The server analyzes the received ideas and transfers the data to four AIs with different personalities: a Dreamer AI, a Hedonist AI, a Realist AI, and a Critic AI. The Dreamer AI proposes the idea's future potential, the Hedonist AI proposes elements to improve the user experience, the Realist AI evaluates the idea's technical feasibility, and the Critic AI comments on the idea's consistency and marketability.

[1543] The server also uses emotion recognition to identify emotions from user input and behavior. This emotional information can then be used to further optimize the AI ​​feedback. For example, if the user is not satisfied with an idea, the Hedonist AI will suggest more appealing elements.

[1544] Once these AI-generated feedbacks are generated, the server integrates the suggestions and presents them as improvement points for the user, which are then sent to the device, where they are displayed to the user.

[1545] Presentation file creation support function

[1546] Users input the presentation topic and the number of slides they require from their device. For example, they can request a 10-slide presentation on "New Mobile Apps."

[1547] The server generates a presentation structure based on the theme, and the generation AI automatically creates the content and design of the slides. In addition, an emotion recognition system analyzes the user's emotional information and optimizes the presentation content based on that information. For example, if anxiety about preparing a presentation is detected, the server will suggest concise and easy-to-understand slides.

[1548] The final presentation file is sent to the user's terminal, where it can be viewed and edited.

[1549] An embodiment of the code generation function of the mockup site

[1550] The device provides an interface where the user can input the purpose and basic requirements of the mockup site. For example, a user may request a "mockup of a task management app."

[1551] The server analyzes the input requirements and generates the necessary HTML, CSS, and JavaScript code. Furthermore, an emotion recognition mechanism analyzes the user's emotional information and optimizes the design of the mockup code based on that information. For example, if the user prefers a simple and easy-to-use design, the server generates code that includes design elements that meet that preference.

[1552] The generated code is sent to the terminal, which displays it to the user and allows it to be executed and modified.

[1553] Presentation oral manuscript preparation support implementation form

[1554] The user inputs the presentation content and presentation time from the terminal. For example, they request a "3-minute presentation on a new mobile app."

[1555] The server extracts the main points of the speech based on the input content and time, and generates an oral transcript. Furthermore, an emotion recognition unit analyzes the user's emotional information and optimizes the transcript content based on that information. For example, it generates a transcript that includes positive and powerful expressions to help the user speak with confidence.

[1556] The generated oral transcript is sent to the terminal and can be used for display and practice on the terminal.

[1557] Embodiment of the virtual evaluation function

[1558] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[1559] The server analyzes the submitted materials, and the generating AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. An emotion recognition system analyzes the user's emotions and reflects that information in the evaluation. For example, if a user feels anxious about being evaluated, an encouraging message can be included.

[1560] The evaluation results and points for improvement are generated and sent to the device, which then displays them to the user and proposes an action plan for the next step.

[1561] ---

[1562] In this way, by combining an emotion engine, the present invention realizes a system that supports idea refinement, presentation preparation, and virtual evaluation while taking into consideration the user's emotions, allowing users to achieve better results and raising the overall level of the contest.

[1563] The processing flow will be explained below.

[1564] I understand. Now, I will explain the flow of program processing of the invention based on the claims, broken down into specific steps.

[1565] ---

[1566] Idea brush-up function

[1567] Step 1:

[1568] A user enters an idea into the device and clicks the submit button. For example, the user enters "Idea for a new mobile app" into the text field.

[1569] Step 2:

[1570] The terminal transmits the user's input data to the server.

[1571] Step 3:

[1572] The server analyzes the received idea text and uses a natural language processing engine to extract key elements and concepts.

[1573] Step 4:

[1574] Based on the analysis results, the server transfers the data to four AIs (Dreamer AI, Hedonist AI, Realist AI, and Critic AI).

[1575] Step 5:

[1576] Each AI generates feedback from its own perspective.

[1577] Dreamer AI: Suggests future possibilities and dream elements of ideas.

[1578] Hedonist AI: Suggests enjoyable elements that improve the user experience.

[1579] Realistic AI: Point out technical feasibility and practical challenges.

[1580] Critic AI: Comments on the overall evaluation and marketability of the idea.

[1581] Step 6:

[1582] The server uses emotion recognition means to recognize emotions from the user's input and actions, for example, by analyzing the user's facial expressions and input speed.

[1583] Step 7:

[1584] The server optimizes the AI's feedback based on the recognized emotional information. For example, if the user is dissatisfied with an idea, the Hedonist AI will suggest more positive elements.

[1585] Step 8:

[1586] The server aggregates the feedback from the four AIs and generates unified improvement suggestions.

[1587] Step 9:

[1588] The server sends the integrated improvement suggestions to the user's terminal.

[1589] Step 10:

[1590] The device displays integrated improvement suggestions to the user.

[1591] ---

[1592] Presentation file creation support function

[1593] Step 1:

[1594] The user inputs the presentation topic and the number of slides required from the device. Example: Requesting 10 slides for a presentation on "New Mobile App."

[1595] Step 2:

[1596] The device sends a request to the server, including the theme and number of slides.

[1597] Step 3:

[1598] The server analyzes the theme and determines the basic framework for the presentation, creating sections such as "Overview," "Feature Introduction," and "Market Analysis."

[1599] Step 4:

[1600] The server generates the content for each section and uses AI to automatically create slide designs.

[1601] Step 5:

[1602] The server analyzes the user's emotional information using emotion recognition means, e.g., analyzing the user's facial expression or voice tone.

[1603] Step 6:

[1604] The server then optimizes the presentation content based on the emotional information it recognizes. For example, it suggests simple, friendly slides to a user who is feeling nervous.

[1605] Step 7:

[1606] The server creates the final slide deck and converts it to the appropriate format (e.g. PowerPoint, PDF).

[1607] Step 8:

[1608] The server transmits the generated presentation file to the user's terminal.

[1609] Step 9:

[1610] The device displays the presentation file to the user and allows them to download and edit it as needed.

[1611] ---

[1612] Code generation for mockup sites

[1613] Step 1:

[1614] A user inputs the purpose and basic requirements of the mockup site from their device. For example, they request a "task management app mockup."

[1615] Step 2:

[1616] The terminal transmits the requirement data to the server.

[1617] Step 3:

[1618] The server analyzes the requirements and extracts the necessary components and UI design elements.

[1619] Step 4:

[1620] The server generates the necessary HTML, CSS, and JavaScript code based on the analysis results.

[1621] Step 5:

[1622] The server uses emotion recognition means to analyze the user's emotion information, such as the user's typing speed and screen transition frequency.

[1623] Step 6:

[1624] The server optimizes the design of the mockup code based on the recognized emotion information. For example, if the user prefers a simple design, the server generates code that meets that preference.

[1625] Step 7:

[1626] The server combines the generated files (HTML, CSS, JavaScript) into a single mockup file.

[1627] Step 8:

[1628] The server sends the integrated mockup code to the user's device.

[1629] Step 9:

[1630] The device displays a mockup site and allows the user to run and modify it.

[1631] ---

[1632] Presentation manuscript preparation support

[1633] Step 1:

[1634] The user inputs the presentation content and presentation time from the device. Example: Request a "3-minute presentation on a new mobile app."

[1635] Step 2:

[1636] The device sends a request including the presentation content and time to the server.

[1637] Step 3:

[1638] The server extracts the main points of the speech based on the content and time, and creates the basic structure of the oral manuscript.

[1639] Step 4:

[1640] The server summarizes what is said and generates an oral transcript by adding appropriate storytelling elements.

[1641] Step 5:

[1642] The server uses emotion recognition means to analyze the user's emotion information, for example, by analyzing the user's tone of voice and pronunciation rhythm.

[1643] Step 6:

[1644] The server optimizes the content of the transcript based on the recognized emotional information, for example by generating a transcript that includes positive and powerful expressions to help the user speak with confidence.

[1645] Step 7:

[1646] The server transmits the generated oral manuscript to the user's terminal.

[1647] Step 8:

[1648] The terminal displays the oral transcript to the user and provides tools for practice.

[1649] ---

[1650] Virtual evaluation function

[1651] Step 1:

[1652] Users can upload ideas and presentation materials they have created from their devices. For example, submit a "Presentation material for a new mobile app."

[1653] Step 2:

[1654] The terminal transmits the materials to the server.

[1655] Step 3:

[1656] The server analyzes the submitted materials and begins evaluation based on the evaluation criteria. For example, analysis is performed using natural language processing or machine learning.

[1657] Step 4:

[1658] The server analyzes the user's emotional information using emotion recognition means. For example, analyzing the user's facial expression and tone of voice when submitting documents.

[1659] Step 5:

[1660] The server optimizes the evaluation based on the recognized emotion information. For example, it includes an encouraging message for a user who is nervous about submitting a document.

[1661] Step 6:

[1662] The server generates an evaluation based on the idea's originality, feasibility, user satisfaction, etc.

[1663] Step 7:

[1664] Based on the evaluation, the server will extract specific areas for improvement.

[1665] Step 8:

[1666] The server sends the evaluation results and improvements to the user's device.

[1667] Step 9:

[1668] The device displays the evaluation results and areas for improvement to the user and suggests an action plan for the next step.

[1669] ---

[1670] Based on the above processing steps, users can receive consistent support from the system and efficiently proceed through the process from refining their ideas to preparing presentations and virtual evaluations. By combining it with an emotion engine, support can be provided while taking into consideration the user's emotions, resulting in higher quality output.

[1671] Example 2

[1672] 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."

[1673] Contest participants often spend a lot of time and effort refining their ideas, creating presentation files, and generating mockups of websites and applications. Furthermore, they struggle to create high-quality deliverables because they lack optimal feedback and suggestions based on the user's emotions. This invention aims to automate these processes while providing support that takes the user's emotions into consideration.

[1674] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a receiving means, an analysis means for analyzing input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, an integration means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, an emotion engine for recognizing the user's emotions, and an optimization means for optimizing the generated improvement proposals based on the analysis results by the emotion engine. This enables the user to reduce effort and time and efficiently create high-quality ideas and presentation materials that take emotions into consideration.

[1675] "Receiving means" is a function for receiving data and information sent from a user.

[1676] "Analysis means" is a function that analyzes and evaluates input data and information.

[1677] "Brush-up means" is a function that generates improvement suggestions using multiple algorithms based on the analysis results.

[1678] "Integration means" is a function that organizes and combines multiple improvement proposals into a single integrated proposal.

[1679] The "output means" is a function for providing the user with the integrated improvement proposals and the generated files.

[1680] The "emotion engine" is a feature used to analyze the user's emotional state and optimize feedback and suggestions.

[1681] The "optimization means" is a function that adjusts feedback and output according to the user's emotional state based on the analysis results of the emotion engine.

[1682] The "presentation generation means" is a function that automatically generates a presentation file based on an input theme.

[1683] "Code generation means" is a function that automatically generates mockup code for websites and applications based on input requirements.

[1684] The present invention is a user assistance system that uses a generative AI model, and is implemented by the following main components and their processing flow.

[1685] System Overview

[1686] This system is composed of a server and a terminal (user device), each of which performs processing according to its role. Each component has the following functions.

[1687] Idea brush-up function

[1688] The user inputs the idea into the terminal and sends it to the system by pressing the send button. For example, the user inputs "Idea for a new mobile app."

[1689] The device uses a receiving means to send this idea to the server. The server then analyzes the idea using an analytical means and distributes the data to four algorithms with different personalities: Dreamer AI, Hedonist AI, Realist AI, and Critic AI. Each AI provides the following feedback:

[1690] Visionary AI: Proposing future possibilities.

[1691] Hedonist AI: Suggests elements to improve the user experience.

[1692] Realist AI: Assessing technical feasibility.

[1693] Critic AI: Evaluates the consistency and marketability of ideas.

[1694] The server analyzes the user's emotions using an emotion engine and optimizes the feedback. For example, if the user expresses dissatisfaction, the Hedonist AI will suggest more appealing elements. These feedbacks are integrated by the integration means and provided to the user as improvement points via the output means.

[1695] Example prompt sentence:

[1696] "Tell us your ideas. We'll have a Dreamer AI, a Hedonist AI, a Realist AI, and a Critic AI to give you feedback."

[1697] Presentation file creation support function

[1698] The user inputs the topic of the presentation and the number of slides required into the device, for example, "Request a 10-slide presentation on a new mobile app."

[1699] The device sends this information to the server. The server uses a presentation generation means to automatically generate the content and design of the slides and analyzes the user's emotional state using an emotion engine. By providing slides that succinctly summarize the important points based on the emotional information, the presentation is optimized to a structure that is less likely to make the user feel anxious. The generated presentation file is sent to the device, where it can be edited by the user.

[1700] Example prompt sentence:

[1701] "Please tell me the topic of your presentation and how many slides you need."

[1702] Code generation for mockup sites

[1703] The user inputs the purpose and basic requirements of the mockup site into the device, for example, requesting a "mockup of a task management app."

[1704] The device sends this to the server, which uses a code generator to generate HTML, CSS, and JavaScript code based on the input requirements. The server uses an emotion engine to analyze the user's emotions and optimize design elements based on that. For example, if a user prefers a simple design, the server will generate code that meets that preference. The generated code is then sent to the device, where the user can run and modify it.

[1705] Example prompt sentence:

[1706] "What is the purpose and basic requirements of the mockup site?"

[1707] Presentation script creation support function

[1708] The user inputs the presentation content and presentation time into the terminal. For example, they request a "3-minute presentation on a new mobile app."

[1709] The terminal sends this information to the server, which then uses an oral script generation means to extract the main points of the speech and generate a script. Based on the analysis results of the emotion engine, the server generates a script with positive and powerful expressions, optimizing it so that the user can speak with confidence. The generated script is sent to the terminal and can be used by the user for display and practice.

[1710] Example prompt sentence:

[1711] Please tell me the content of your presentation and the time of your presentation.

[1712] Virtual evaluation function

[1713] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[1714] The device sends the materials to the server, which then evaluates them using analytical means. A generative AI model is used to perform a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. An emotion engine analyzes the user's emotions and reflects them in the evaluation. For example, it generates evaluation results that include encouraging messages to alleviate evaluation anxiety. The evaluation results and points for improvement are sent to the device and displayed to the user, providing an action plan for the next step.

[1715] Example prompt sentence:

[1716] "Upload your ideas and presentation materials and we'll do a virtual evaluation."

[1717] As described above, the present invention effectively supports idea refinement, presentation preparation, mockup creation, oral manuscript creation, and virtual evaluation while taking into consideration the user's emotions by combining an emotion engine. This allows users to efficiently create high-quality deliverables and improve overall results.

[1718] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1719] Idea brush-up function

[1720] Step 1:

[1721] The user enters an idea into the device and clicks the submit button. The entered idea might be something like "An idea for a new mobile app."

[1722] Step 2:

[1723] The terminal sends the input idea to the server using an HTTP request. The input is the idea data, and the output is confirmation of the request.

[1724] Step 3:

[1725] The server analyzes the received ideas using an analysis means. The input is the received idea data, and the output is the analysis result. Specifically, the server uses a text analysis algorithm to extract the main elements of the idea.

[1726] Step 4:

[1727] The server distributes the data to four AIs with different personalities (Dreamer AI, Hedonist AI, Realist AI, and Critic AI) based on the analysis results. The input is the analysis results, and the output is the data sent to each AI. Requests are sent via a RESTful API.

[1728] Step 5:

[1729] The server receives feedback from each AI. The dreamer AI suggests future possibilities, the enjoyer AI suggests ways to improve the user experience, the realist AI evaluates technical feasibility, and the critic AI evaluates consistency and marketability. The input is the data sent to the AI, and the output is feedback information.

[1730] Step 6:

[1731] The server uses an emotion engine to analyze the user's emotional information. For example, if an emotion indicating dissatisfaction is detected, the server adjusts the feedback content based on that. The input is the user's emotional information, and the output is the emotion analysis result.

[1732] Step 7:

[1733] The server integrates the feedback from each AI with the results of emotion analysis using an integration method. Specifically, it organizes the feedback content and reconstructs it into an optimal form for the user. The input is the feedback information and the results of emotion analysis, and the output is an integrated improvement proposal.

[1734] Step 8:

[1735] The server transmits the integrated improvement proposal to the terminal using the output means. At this time, an HTTP response is used. The input is the integrated improvement proposal, and the output is transmission confirmation information.

[1736] Step 9:

[1737] The terminal displays the received improvement suggestions to the user. The input is the improvement suggestions, and the output is the displayed suggestion information.

[1738] Presentation file creation support function

[1739] Step 1:

[1740] The user inputs the topic of the presentation and the number of slides required into the device, for example, "Request a 10-slide presentation on a new mobile app."

[1741] Step 2:

[1742] The terminal sends information about the theme and the number of slides to the server. The input is the theme and the number of slides, and the output is a confirmation of the request.

[1743] Step 3:

[1744] The server generates a presentation structure based on the theme. It uses a generative AI model to automatically create the slide content and design. The input is the theme and the number of slides, and the output is a presentation file.

[1745] Step 4:

[1746] The server uses an emotion engine to analyze the user's emotional information and optimize the presentation content. For example, if anxiety is detected, it creates concise and easy-to-understand slides. The input is the user's emotional information, and the output is the emotion analysis results.

[1747] Step 5:

[1748] The server sends the final presentation file to the terminal, where the input is the optimized presentation file and the output is a transmission confirmation.

[1749] Step 6:

[1750] The terminal displays the received presentation file and allows the user to edit it. The input is the presentation file and the output is the displayed file.

[1751] Code generation for mockup sites

[1752] Step 1:

[1753] The user inputs the purpose and basic requirements of the mockup site into the device, for example, requesting a "mockup of a task management app."

[1754] Step 2:

[1755] The terminal sends this to the server. The input is the requirements for the mockup site, and the output is confirmation of the request submission.

[1756] Step 3:

[1757] The server parses the input requirements and uses a generative AI model to generate the necessary HTML, CSS, and JavaScript code. The input is the requirements for the mockup site, and the output is the mockup code.

[1758] Step 4:

[1759] The server uses an emotion engine to analyze the user's emotional information and optimize the code design. For example, if a user prefers a simple design, it generates code that includes design elements that meet that preference. The input is the user's emotional information, and the output is optimized code.

[1760] Step 5:

[1761] The server sends the generated code to the terminal. The input is the generated code and the output is the transmission confirmation information.

[1762] Step 6:

[1763] The terminal displays the received code and allows the user to execute and modify it. The input is the generated code and the output is the displayed code.

[1764] Presentation script creation support function

[1765] Step 1:

[1766] The user inputs the presentation content and presentation time into the terminal. For example, the user requests a "3-minute presentation on a new mobile app."

[1767] Step 2:

[1768] The terminal sends this information to the server. The input is the presentation content and time, and the output is confirmation of the request.

[1769] Step 3:

[1770] The server extracts the main points of the speech based on the content and time, and generates an oral transcript. The input is the presentation content and time, and the output is the oral transcript.

[1771] Step 4:

[1772] The server uses an emotion engine to analyze the user's emotional information and optimize the content of the spoken script. For example, it generates a script containing positive and powerful expressions to help the user speak with confidence. The input is the user's emotional information, and the output is the optimized script.

[1773] Step 5:

[1774] The server transmits the generated oral manuscript to the terminal, where the input is the generated manuscript and the output is transmission confirmation information.

[1775] Step 6:

[1776] The terminal displays the received oral transcript so that the user can use it for practice. The input is the generated transcript and the output is the displayed transcript.

[1777] Virtual evaluation function

[1778] Step 1:

[1779] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[1780] Step 2:

[1781] The terminal sends the submitted documents to the server. The input is the submitted documents, and the output is confirmation of the request submission.

[1782] Step 3:

[1783] The server analyzes the submitted materials and uses a generative AI model to perform a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The input is the submitted materials, and the output is the virtual evaluation results.

[1784] Step 4:

[1785] The server uses an emotion engine to analyze the user's emotions and reflects that information in the evaluation. For example, if a user feels anxious about being evaluated, the server generates an evaluation result that includes an encouraging message. The input is the user's emotional information, and the output is an optimized evaluation result.

[1786] Step 5:

[1787] The server generates evaluation results and improvements and sends them to the terminal. The input is the evaluation results and improvements, and the output is a transmission confirmation.

[1788] Step 6:

[1789] The terminal displays the evaluation results and points for improvement to the user and proposes an action plan for the next step. The input is the evaluation results and points for improvement, and the output is the displayed results and suggestions.

[1790] The above is the specific flow of processing in this system.

[1791] (Application example 2)

[1792] 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."

[1793] When multiple robots work together in a factory, maintenance and work optimization proposals for each robot may not be implemented promptly. This can result in reduced production efficiency and robot breakdowns or malfunctions. Furthermore, workers who are not familiar with robot operation and maintenance may find it difficult to take appropriate action, which could lead to further problems. It is necessary to resolve these issues and efficiently perform maintenance while optimizing robot operation.

[1794] 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.

[1795] In this invention, the server includes a receiving means, an analysis means for analyzing input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, an integration means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, a data collection means for collecting and analyzing robot operation data, an optimization proposal means for proposing task optimization based on the robot's operating status, and an anomaly detection means for detecting robot abnormalities and the need for maintenance. This enables real-time analysis of the robot's operations in a factory, efficient task proposals, and early anomaly detection.

[1796] definition statement

[1797] The "receiving means" is a means for receiving various input information such as ideas from users and robot operation data.

[1798] "Analysis means" refers to the means for analyzing ideas and data received by the receiving means, and for understanding and evaluating their contents.

[1799] The "brush-up means" is a means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results obtained by the analysis means.

[1800] The "integration means" is a means for combining multiple improvement proposals generated by the brush-up means into one.

[1801] The "output means" is a means for providing the improvement proposal obtained by the integration means to the user.

[1802] The "data collection means" is a means for collecting operational data from robots in a factory.

[1803] The "optimization suggestion means" is a means for analyzing the robot operation data collected by the data collection means and making suggestions for improving work efficiency.

[1804] The "abnormality detection means" is a means for monitoring the operation data of the robot and detecting abnormalities or the need for maintenance.

[1805] MODE FOR CARRYING OUT THE INVENTION

[1806] The present invention relates to a system for improving the efficiency of robot management in a factory and supporting maintenance and work optimization. Specific embodiments for carrying out the present invention will be described below.

[1807] System Overview

[1808] This system is mainly composed of a server and a terminal (user device), each of which performs processing according to its respective role. The server is responsible for analyzing and generating data, while the user's terminal is responsible for inputting and outputting data.

[1809] Robot data collection and analysis

[1810] The terminal provides a means for collecting operational data from the robots in the factory, such as temperature, operating time, and the number of errors that have occurred.

[1811] The server has a "receiving means" that receives the collected data and an "analysis means" that analyzes the data. The analysis means evaluates the robot's operating status and detects abnormalities.

[1812] Work optimization and maintenance proposals

[1813] Based on the analysis results, the server uses the "optimization proposal method" and "anomaly detection method" to detect the need for improvement proposals and maintenance. Using these methods, specific improvement measures and maintenance proposals for the robot are generated.

[1814] For example, if robot R1 reaches a high temperature (85°C) during operation and has been operating for more than 5,000 hours, the analysis means will detect that it is experiencing stress based on that data, and the optimization suggestion means will send a signal to check the cooling system for temperature control.

[1815] Feedback and Integration

[1816] The server generates optimization and maintenance proposals using the "brush-up means," and then integrates them using the "integration means." This generates comprehensive improvement proposals and provides them to the user.

[1817] The terminal uses the "output means" to display the integrated improvement proposals to the user, for example, as an alert on the user's smartphone.

[1818] Examples and prompts

[1819] Below is a concrete example of how the system works.

[1820] Specific examples

[1821] Robot R1 in the factory has reached a high temperature (85°C) during operation and has been running for over 5000 hours. Analysis by the emotion engine has detected that this robot is feeling stressed. Please generate appropriate maintenance suggestions and work optimization suggestions.

[1822] Prompt Sentence Examples

[1823] "Robot R1 in the factory has reached a high temperature (85°C) during operation and has been operating for over 5000 hours. Analysis by the emotion engine has detected that this robot is experiencing stress. Please generate appropriate maintenance suggestions and work optimization suggestions."

[1824] In this way, the present invention realizes a system that improves efficiency and reliability within factories by collecting robot operation data and using a generative AI model to make specific improvement suggestions.

[1825] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1826] Program processing flow

[1827] Step 1: Data collection

[1828] The terminal collects operational data from robots in the factory.

[1829] Input: Robot operation data (temperature, operating time, number of errors, etc.)

[1830] Output: raw data collected

[1831] Specific operation: Collects data in real time from various sensors such as temperature sensors and work time recording devices and sends it to a server.

[1832] Step 2: Receiving data

[1833] The server receives the operation data sent from the terminal.

[1834] Input: Raw data from the terminal

[1835] Output: Robot movement data stored in the server

[1836] Specific operation: Receives data from the device and stores it in a database.

[1837] Step 3: Data analysis

[1838] The server analyzes the received motion data.

[1839] Input: Collected robot movement data

[1840] Output: Analysis results (temperature rise, abnormality detection, etc.)

[1841] Specific operation: Based on the received data, the temperature, operating time, and number of errors are analyzed to check for abnormalities. For example, if the temperature exceeds a set reference value (e.g., 85°C), an abnormality is detected.

[1842] Step 4: Sentiment analysis and maintenance need assessment

[1843] Based on the analysis results, the server uses an emotion engine to analyze the robot's "emotions" and evaluate the need for maintenance.

[1844] Input: Analysis results

[1845] Output: Sentiment data and maintenance suggestions

[1846] Specific operation: The emotion engine analyzes emotions, such as "feeling stressed" in response to a high temperature, and determines whether maintenance is necessary. For example, based on data such as "R1 has been operating at 85°C for 5,000 hours," it suggests checking the cooling system.

[1847] Step 5: Generate improvement suggestions

[1848] The server generates improvement suggestions using a generative AI model.

[1849] Input: Sentiment data and maintenance suggestions

[1850] Output: Improvement suggestions

[1851] Specific actions: Based on the analyzed emotions and maintenance need assessment data, the generative AI generates specific improvement suggestions, such as suggestions for improving the robot's operating environment or proposing new operating procedures.

[1852] Step 6: Proposal Integration

[1853] The server integrates multiple improvement suggestions.

[1854] Input: Multiple improvement suggestions

[1855] Output: Consolidated improvement suggestions

[1856] Specific operation: Consolidate multiple improvement suggestions generated by the generative AI into one. For example, consolidate suggestions for temperature control and maintenance needs into a clearer format.

[1857] Step 7: Provide feedback

[1858] The terminal notifies the user of the integrated proposal.

[1859] Input: Consolidated improvement suggestions

[1860] Output: User notification

[1861] Specific actions: The integrated improvement suggestions are sent to the device, and alerts and specific actions are displayed to the user. For example, a notification is displayed on the smartphone app with the message "Please check the cooling system of your R1."

[1862] The above are the specific processing steps for carrying out the present invention.

[1863] 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.

[1864] 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.

[1865] 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.

[1866] [Fourth embodiment]

[1867] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1868] 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.

[1869] 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).

[1870] 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.

[1871] 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.

[1872] 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).

[1873] 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.

[1874] 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.

[1875] 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.

[1876] 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.

[1877] 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.

[1878] 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.

[1879] 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."

[1880] Understood. The following describes in detail the mode for carrying out the invention based on the claims.

[1881] ---

[1882] This invention is a contest support system that uses generative AI, linking multiple AIs with different characteristics to provide functions such as idea refinement, presentation file creation, mockup site code generation, oral presentation script creation, and virtual evaluation. This system allows contest participants to save time and create higher quality ideas and presentations.

[1883] System Overview

[1884] This system is mainly divided into a server and a terminal (user device), each of which performs processing according to its role. Below we will explain each major component and its specific operation.

[1885] Example of idea brush-up function

[1886] The terminal provides an interface for accepting user input. The user inputs an idea and clicks the submit button to send the idea to the system. For example, the user inputs "an idea for a new mobile app."

[1887] The server analyzes the received ideas and transfers the data to four AIs with different personalities: a dreamer, a hedonist, a realist, and a critic. The dreamer AI proposes the idea's future potential, the hedonist AI suggests elements to improve the user experience, the realist AI evaluates the idea's technical feasibility, and the critic AI comments on the idea's consistency and marketability.

[1888] Once these AI-generated feedbacks are generated, the server integrates the suggestions and presents them as improvement points for the user, which are then sent to the device, where they are displayed to the user.

[1889] Presentation file creation support function

[1890] Users input the presentation topic and the number of slides they require from their device. For example, they can request a 10-slide presentation on "New Mobile Apps."

[1891] The server generates a presentation structure based on the theme, and the AI ​​automatically creates the slide content and design. The final presentation file is sent to the user's device, where it can be viewed and edited.

[1892] An embodiment of the code generation function of the mockup site

[1893] The device provides an interface where the user can input the purpose and basic requirements of the mockup site. For example, a user may request a "mockup of a task management app."

[1894] The server parses the input requirements and generates the necessary HTML, CSS, and JavaScript code, which is then sent to the device, which displays it to the user and allows them to run and modify it.

[1895] Presentation oral manuscript preparation support implementation form

[1896] The user inputs the presentation content and time from the terminal. For example, they can request a "3-minute presentation on a new mobile app."

[1897] The server extracts the main points of the speech based on the input content and time, and generates an oral transcript, which is sent to the terminal and can be used for display and practice.

[1898] Embodiment of the virtual evaluation function

[1899] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[1900] The server analyzes the submitted materials, and the generating AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The evaluation results and points for improvement are generated and sent to the device, which then displays the evaluation results and points for improvement to the user.

[1901] ---

[1902] In this way, the present invention reduces the burden on contest participants and raises the overall level of the contest by providing consistent support from brushing up ideas to preparing presentations and virtual evaluation.

[1903] The processing flow will be explained below.

[1904] I understand. Now, I will explain the flow of program processing of the invention based on the claims, broken down into specific steps.

[1905] ---

[1906] Idea brush-up function

[1907] Step 1:

[1908] A user inputs an idea from a device, for example, by typing "Idea for a new mobile app" into a text field.

[1909] Step 2:

[1910] The terminal transmits the user's input data to the server.

[1911] Step 3:

[1912] The server analyzes the received idea text and uses a natural language processing engine to extract key elements and concepts.

[1913] Step 4:

[1914] Based on the analysis results, the server transfers the data to four AIs (Dreamer AI, Hedonist AI, Realist AI, and Critic AI).

[1915] Step 5:

[1916] Each AI generates feedback from its own perspective.

[1917] Dreamer AI: Suggests future possibilities and dream elements of ideas.

[1918] Hedonist AI: Suggests enjoyable elements that improve the user experience.

[1919] Realistic AI: Point out technical feasibility and practical challenges.

[1920] Critic AI: Comments on the overall evaluation and marketability of the idea.

[1921] Step 6:

[1922] The server aggregates the feedback from the four AIs and generates unified improvement suggestions.

[1923] Step 7:

[1924] The server sends the integrated improvement suggestions to the user's terminal.

[1925] Step 8:

[1926] The device displays integrated improvement suggestions to the user.

[1927] ---

[1928] Presentation file creation support function

[1929] Step 1:

[1930] The user inputs the presentation topic and the number of slides required from the device. Example: Requesting 10 slides for a presentation on "New Mobile App."

[1931] Step 2:

[1932] The device sends a request to the server, including the theme and number of slides.

[1933] Step 3:

[1934] The server analyzes the theme and determines the basic framework for the presentation, creating sections such as "Overview," "Feature Introduction," and "Market Analysis."

[1935] Step 4:

[1936] The server generates the content for each section and uses AI to automatically create slide designs.

[1937] Step 5:

[1938] The server creates the final slide deck and converts it to the appropriate format (e.g. PowerPoint, PDF).

[1939] Step 6:

[1940] The server transmits the generated presentation file to the user's terminal.

[1941] Step 7:

[1942] The device displays the presentation file to the user and allows them to download and edit it as needed.

[1943] ---

[1944] Code generation for mockup sites

[1945] Step 1:

[1946] A user inputs the purpose and basic requirements of the mockup site from their device. For example, they request a "task management app mockup."

[1947] Step 2:

[1948] The terminal transmits the requirement data to the server.

[1949] Step 3:

[1950] The server analyzes the requirements and extracts the necessary components and UI design elements.

[1951] Step 4:

[1952] The server generates the necessary HTML, CSS, and JavaScript code based on the analysis results.

[1953] Step 5:

[1954] The server combines the generated files (HTML, CSS, JavaScript) into a single mockup file.

[1955] Step 6:

[1956] The server sends the integrated mockup code to the user's device.

[1957] Step 7:

[1958] The device displays a mockup site and allows the user to run and modify it.

[1959] ---

[1960] Presentation manuscript preparation support

[1961] Step 1:

[1962] The user inputs the presentation content and presentation time from the device. Example: Request a "3-minute presentation on a new mobile app."

[1963] Step 2:

[1964] The device sends a request including the presentation content and time to the server.

[1965] Step 3:

[1966] The server extracts the main points of the speech based on the content and time, and creates the basic structure of the oral manuscript.

[1967] Step 4:

[1968] The server summarizes what is said and generates an oral transcript by adding appropriate storytelling elements.

[1969] Step 5:

[1970] The server transmits the generated oral manuscript to the user's terminal.

[1971] Step 6:

[1972] The terminal displays the oral transcript to the user and provides tools for practice.

[1973] ---

[1974] Virtual evaluation function

[1975] Step 1:

[1976] Users can upload ideas and presentation materials they have created from their devices. For example, submit a "Presentation material for a new mobile app."

[1977] Step 2:

[1978] The terminal transmits the materials to the server.

[1979] Step 3:

[1980] The server analyzes the submitted materials and begins evaluation based on the evaluation criteria. For example, analysis is performed using natural language processing or machine learning.

[1981] Step 4:

[1982] The server generates an evaluation based on the idea's originality, feasibility, user satisfaction, etc.

[1983] Step 5:

[1984] Based on the evaluation, the server will extract specific areas for improvement.

[1985] Step 6:

[1986] The server sends the evaluation results and improvements to the user's device.

[1987] Step 7:

[1988] The device displays the evaluation results and areas for improvement to the user, and suggests an action plan for the next step.

[1989] ---

[1990] Based on the above-mentioned processing steps, users can efficiently proceed from refining their ideas to preparing for presentations and virtual evaluations while receiving consistent support from the system.

[1991] Example 1

[1992] 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."

[1993] Traditionally, refining ideas, creating presentations, and creating mockup websites has often been done manually, requiring a great deal of time and effort. Furthermore, many of the tasks require multiple areas of expertise, making it difficult to handle on your own. Furthermore, it has been difficult to obtain improvement suggestions from different perspectives, making it difficult to objectively evaluate the quality and feasibility of ideas.

[1994] 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.

[1995] In this invention, the server includes a receiving means, an analyzing means for analyzing data entered by a user, a proposal generating means for generating improvement proposals using multiple generative AI models with different characteristics based on the analysis results, an integrating means for integrating the generated improvement proposals, and an output means for outputting the integrated improvement proposals. This makes it possible to improve the quality of ideas, efficiently create presentation materials and mockup sites, and significantly reduce the burden on contest participants.

[1996] The "receiving means" is a device or function for receiving input data from a user.

[1997] The "analysis means" is a device or function for analyzing the data obtained by the receiving means and processing it in an appropriate form.

[1998] The "proposal generation means" is a device or function that generates improvement proposals based on the data processed by the analysis means, using multiple generative AI models with different characteristics.

[1999] An "integration means" is a device or function that integrates improvement suggestions generated by multiple generative AI models and compiles them into unified feedback.

[2000] The "output means" is a device or function for transmitting the integrated improvement proposal to a user terminal or the like and displaying it.

[2001] The "generation means" is a device or function for automatically generating a presentation file based on an input theme.

[2002] "Code Generator" means a device or function for generating mockup code for an internet site or software based on input requirements.

[2003] This invention is a contest support system that utilizes generative AI models, and uses multiple generative AI models with different characteristics to provide functions such as idea refinement, presentation file creation, mockup site code generation, oral presentation script creation, and virtual evaluation. The system is divided into a server and a terminal (user device), each of which performs processing according to its respective role.

[2004] Idea brush-up function

[2005] A user submits an idea to the system by entering it into the device's input field and clicking the submit button. For example, they enter "idea for a new mobile app." The device then sends the data to the server. The server analyzes the received idea and transfers the data to a generative AI model with multiple different personalities. For example, OpenAI's GPT-4 is used for this generative AI model.

[2006] Specifically, the Dreamer AI proposes the idea's future potential, the Enjoyer AI suggests elements that will improve the user experience, the Realist AI evaluates the idea's technical feasibility, and the Critic AI comments on the idea's consistency and marketability. Once feedback from each AI is generated, the server integrates this feedback, summarizes it as points for improvement, and sends it to the device, which then displays it to the user.

[2007] Specific examples

[2008] A user inputs an idea for a new mobile app and clicks the submit button. The generating AI then provides feedback, such as, "This idea has great potential for future growth (Visionary AI)," "It includes features that would allow users to have an intuitive operating interface (Enjoyment AI)," and "It is evaluated as being technically feasible (Realist AI)."

[2009] Example prompt: "Please provide suggestions for refining our new mobile app idea."

[2010] Presentation file creation support function

[2011] The user inputs the presentation theme and the number of slides required from their device. For example, a user requests a 10-slide presentation on a "new mobile app." The device then sends the input information to the server. The server generates a presentation structure based on the theme, and the generation AI automatically creates the slide content and design. The generated presentation file is then sent to the user's device, where it can be viewed and edited.

[2012] Specific examples

[2013] A user requests a 10-slide presentation for a "new mobile app." The AI ​​automatically generates content such as an introduction, target market, product features, competitive analysis, marketing strategy, financial plan, development roadmap, risks and countermeasures, future outlook, and conclusion.

[2014] Example prompt: "Create a 10-slide presentation about a new mobile app."

[2015] Code generation for mockup sites

[2016] The user enters the purpose and basic requirements of the mockup site into input fields on the device. For example, they request a "task management app mockup." The device then sends the requirements to the server. The server analyzes the input requirements and uses a generative AI model to generate the necessary HTML, CSS, and JavaScript code. The generated code is then sent to the device, which displays it to the user and allows them to run and modify it.

[2017] Specific examples

[2018] When a user requests a "mockup of a task management app," the AI ​​generates HTML, CSS, and JavaScript code that includes features such as "displaying a to-do list, adding and deleting tasks, and managing task completion status."

[2019] Example prompt: "Generate HTML, CSS, and JavaScript code for a task management app."

[2020] Virtual evaluation function

[2021] Users upload their ideas and presentation materials from their devices. For example, a user may submit a "presentation for a new mobile app." The server analyzes the submitted materials, and the generative AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. The evaluation results and suggestions for improvement are generated and sent to the device, which then displays them to the user.

[2022] As a result, the present invention can provide consistent support from refining ideas to preparing presentations and virtual evaluation, reducing the burden on contest participants and improving the overall level.

[2023] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2024] Idea brush-up function processing steps

[2025] Step 1:

[2026] The user inputs an idea.

[2027] Specific operation: The user enters "New mobile app idea" in the dedicated input field on the device and clicks the "Submit button."

[2028] Input: User's idea data (text format)

[2029] Output: When the send button is pressed, the idea data proceeds to the next processing step.

[2030] Step 2:

[2031] The device sends the idea to the server.

[2032] Specific operation: The device converts the input idea data into an HTTP request (e.g., POST request) and sends it to the server.

[2033] Input: User's idea data (text format)

[2034] Output: Idea data sent to the server

[2035] Step 3:

[2036] The server analyzes the received ideas.

[2037] How it works: The server processes the received idea data using Python scripts, converting it into a format that can be analyzed by the AI ​​model, and segmenting the text data to extract keywords and themes.

[2038] Input: Submitted idea data (text format)

[2039] Output: Parsed data (structured data)

[2040] Step 4:

[2041] The server transfers the ideas to a generative AI model with four different personalities.

[2042] Specific operation: The server sends the analyzed data to each AI model (Dreamer AI, Hedonist AI, Realist AI, Critic AI) as input data. It calls the model's API and passes the analyzed data.

[2043] Input: Parsed data (structured data)

[2044] Output: Feedback data from each AI model

[2045] Step 5:

[2046] The server integrates the feedback from each AI.

[2047] How it works: The server integrates the feedback data returned by each AI model and compiles it into a comprehensive set of improvement suggestions. It uses an integrated algorithm to generate consistent feedback.

[2048] Input: Feedback data from each AI (text format)

[2049] Output: Consolidated improvement suggestions (text format)

[2050] Step 6:

[2051] The server sends the integrated improvement suggestions to the terminal.

[2052] Specific operation: The server returns the integrated improvement suggestions to the terminal as an HTTP response.

[2053] Input: Consolidated improvement suggestions (text format)

[2054] Output: Improvement suggestions sent to the device (text format)

[2055] Step 7:

[2056] The device displays improvement suggestions to the user.

[2057] Specific operation: The device displays the received improvement suggestions in the user interface for the user to view, using a dialog box or a dedicated display area.

[2058] Input: Improvement suggestions received from the server (in text format)

[2059] Output: Improvement suggestions displayed to the user (in text format)

[2060] Presentation file creation support function processing steps

[2061] Step 1:

[2062] The user inputs the presentation topic and number of slides.

[2063] Specific operation: The user enters "New mobile app" and the number of slides "10" into the input fields on the device and presses the submit button.

[2064] Input: Presentation topic and number of slides (text format)

[2065] Output: When the submit button is pressed, the input data proceeds to the next processing step.

[2066] Step 2:

[2067] The terminal sends the input information to the server.

[2068] Specific operation: The device sends the entered theme and number of slides to the server via an HTTP request.

[2069] Input: Presentation topic and number of slides (text format)

[2070] Output: Themes and slide counts sent to the server

[2071] Step 3:

[2072] The server generates the presentation configuration.

[2073] How it works: The server uses a generative AI model to generate a proposed structure for each slide, breaking down the content based on the theme and designing an appropriate slide structure.

[2074] Input: Presentation topic and number of slides (text format)

[2075] Output: Slide layout proposal (structured data)

[2076] Step 4:

[2077] The server creates the slide content and design.

[2078] How it works: The server uses a generative AI model to automatically generate the text content and design elements (e.g., graphs and images) for each slide.

[2079] Input: Slide layout plan (structured data)

[2080] Output: Slide content and design (file format)

[2081] Step 5:

[2082] The server transmits the generated presentation file to the terminal.

[2083] Specific operation: The server returns the generated presentation file to the terminal as an HTTP response.

[2084] Input: Slide content and design (file format)

[2085] Output: Presentation file sent to your device

[2086] Step 6:

[2087] Allows the device to view and edit presentation files.

[2088] Specific operation: The device displays the received presentation file and provides an editor that allows the user to easily edit it.

[2089] Input: Presentation file (file format) received from the server

[2090] Output: A presentation file that users can view and edit

[2091] (Application example 1)

[2092] 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."

[2093] The purpose of this invention is to enable factory technicians and engineers to quickly and effectively refine ideas for improving new production lines and production processes, and to automatically generate the necessary information, such as presentation materials and code. In particular, by providing consistent support from idea refinement to evaluation, the invention aims to provide efficient work support and solve the problem of improving factory productivity.

[2094] 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.

[2095] In this invention, the server includes a receiving means, an analysis means for analyzing the input ideas, a brush-up means for generating improvement proposals using a plurality of algorithms with different characteristics based on the analysis results, a integrating means for integrating the generated improvement proposals, an output means for outputting the integrated improvement proposals, an execution means for testing on an actual machine the code generated based on the input ideas, and a display means for allowing contest participants to receive the improvement proposals in real time. This enables factory technicians and engineers to quickly and effectively brush up on new ideas, create presentation materials, and generate and evaluate mockup code.

[2096] "Receiving means" refers to a device or process by which the system receives data or ideas input by a user.

[2097] An "analysis means" is a device or process whose purpose is to understand and analyze the content of input data or ideas.

[2098] A "brush-up means" is a device or process that generates improvement proposals based on analyzed data using multiple algorithms with different characteristics.

[2099] The "integration means" is a device or process that integrates multiple generated improvement proposals into one.

[2100] "Output means" refers to a device or process for providing the user with the integrated improvement suggestions and generated data.

[2101] An "execution means" is a device or process intended to test the generated code or proposals in a real environment or device.

[2102] "Display means" means a device or process for visually presenting improvement suggestions and feedback to the user in real time.

[2103] A "presentation generation means" is a device or process that automatically creates presentation materials based on an input theme.

[2104] A "script generator" is a device or process that automatically generates a spoken script to complement the content of a presentation.

[2105] "Code generator" means a device or process that generates mockup code for a website or application based on input requirements.

[2106] An "evaluation means" is a device or process that evaluates generated code or proposals in a virtual environment and provides results.

[2107] The present invention is a system that allows engineers and technicians to effectively refine ideas for improving new production lines and production processes using factory robots, generate presentation materials and mockup code, and perform virtual evaluations. Specific embodiments of this system are described below.

[2108] System Overview

[2109] This system mainly consists of a server and smart glasses (terminals) used by users. The server includes a receiving means, an analyzing means, a brushing up means, a integrating means, an outputting means, an executing means, a displaying means, a presentation generating means, a script generating means, a code generating means, and an evaluation means.

[2110] Idea brush-up function

[2111] The terminal provides an interface for users to input ideas. For example, a user can input and submit an "idea for automating a new production line." The server's analysis means analyzes this idea and sends it to AI models with different personalities: a dreamer, a hedonist, a realist, and a critic. Each model generates improvement suggestions from its own unique perspective, and these suggestions are integrated by the integration means and fed back to the user in real time via the terminal's display means.

[2112] Presentation file creation support function

[2113] The user inputs the theme of the presentation and the number of slides required from the terminal. For example, a request is made for "Explanation of the automation of a new production line" with 10 slides. The server's presentation generation means creates automatically generated slides based on the theme and provides them to the user through the output means. In addition, an oral manuscript to complement the presentation is generated by the script generation means and provided to the user.

[2114] Code generation for mockup sites

[2115] A user can input the purpose and basic requirements of the mockup site from a terminal. For example, a user can request a "mockup of a task management app that improves productivity." The server's code generation means automatically generates the necessary HTML, CSS, and JavaScript code based on the requirements and provides it to the user through the output means. The generated code is then executed in real time through the execution means.

[2116] Virtual evaluation function

[2117] Users upload their ideas and presentation materials from their devices to the server. For example, a user submits a "presentation material for a new production line." The server's evaluation means analyzes the submitted materials and performs a virtual evaluation from the perspectives of originality, feasibility, user satisfaction, etc. The evaluation results are fed back to the user via the output means.

[2118] Specific examples

[2119] For example, if an engineer inputs "an idea for automating a new production line," the following prompt sentence is generated:

[2120] New production line automation idea: To improve production efficiency, we would like to introduce a real-time monitoring system using AI.

[2121] In response to this idea, the dreamer AI suggests that "fully automating it in the future is possible," while the realist AI points out that "integration with the current system is a challenge." By combining these feedbacks, users can obtain refined ideas.

[2122] As described above, by using this system, factory technicians and engineers can quickly and efficiently generate new ideas and create presentation materials and implementation plans.

[2123] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2124] Step 1:

[2125] A user inputs an idea using a terminal, for example, a prompt sentence such as "An idea for automating a new production line," and clicks the submit button. The input data is sent to the server.

[2126] Step 2:

[2127] The server analyzes the received ideas. It uses analytical tools to convert the content of the prompt into structured data and forwards the data to AIs with different personalities (Dreamer, Hedonist, Realist, Critic). In this step, the input data is passed through a text analysis algorithm and converted into a format that can be handled by various AIs.

[2128] Step 3:

[2129] The server generates feedback using each AI model. The dreamer AI suggests the idea's future potential, the hedonist AI suggests elements that will improve the user experience, the realist AI evaluates the idea's technical feasibility, and the critic AI comments on the idea's consistency and marketability. Each feedback is sent back to the server.

[2130] Step 4:

[2131] The server consolidates the generated feedback. It uses a consolidation method to combine the feedback from each AI into a single consolidated improvement proposal. This process includes prioritizing the feedback and merging overlapping elements.

[2132] Step 5:

[2133] The integrated improvement proposals are sent to the terminal through the output means. The user receives feedback in real time and the feedback is displayed on the display means of the terminal. In this step, the integrated data is converted into a user-friendly format and visually displayed.

[2134] Step 6:

[2135] The user inputs the topic and number of slides of the presentation into the terminal. For example, a request is made for "Explanation of the automation of a new production line" with 10 slides. The input data is sent to the server again.

[2136] Step 7:

[2137] The server uses a presentation generation means to automatically create presentation slides based on the theme. The server uses a generative AI model to automatically place appropriate content and design on each slide. The generated slides are then sent to the terminal via an output means.

[2138] Step 8:

[2139] An oral script is generated to complement the presentation. The user inputs the presentation content and time, and the server creates the oral script using a script generation means. The created oral script is sent to the terminal, where the user can check the display.

[2140] Step 9:

[2141] A user inputs requirements for a mockup site using a terminal. For example, they input requirements such as "a mockup of a task management app that improves productivity" and submit the request.

[2142] Step 10:

[2143] The server uses the code generation means to generate the necessary HTML, CSS, and JavaScript code based on the input requirements. The generated code is sent to the terminal through the output means, allowing the user to try it out on the actual device in real time.

[2144] Step 11:

[2145] The user uploads the ideas and presentation materials they have created from their terminal to the server, and the input data is sent to the evaluation means.

[2146] Step 12:

[2147] The server uses the evaluation means to analyze the submitted materials and conduct a virtual evaluation from the perspectives of originality, feasibility, user satisfaction, etc. The evaluation results are sent to the terminal via the output means and fed back to the user.

[2148] The above is the specific processing flow of the system that realizes the application example.

[2149] 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.

[2150] Understood. The following describes in detail the mode for carrying out the invention based on the claims.

[2151] ---

[2152] This invention combines a contest support system using generative AI with an emotion engine that recognizes user emotions to more effectively refine ideas, create presentation files, generate code for mockup sites, create oral presentation scripts, and participate in virtual evaluations. This system allows contest participants to save time and create high-quality ideas and presentations that take emotions into consideration.

[2153] System Overview

[2154] This system is mainly divided into a server and a terminal (user device), each of which performs processing according to its role. Below we will explain each major component and its specific operation.

[2155] Example of idea brush-up function

[2156] The terminal provides an interface for accepting user input. The user inputs an idea and clicks the submit button to send the idea to the system. For example, the user inputs "an idea for a new mobile app."

[2157] The server analyzes the received ideas and transfers the data to four AIs with different personalities: a Dreamer AI, a Hedonist AI, a Realist AI, and a Critic AI. The Dreamer AI proposes the idea's future potential, the Hedonist AI proposes elements to improve the user experience, the Realist AI evaluates the idea's technical feasibility, and the Critic AI comments on the idea's consistency and marketability.

[2158] The server also uses emotion recognition to identify emotions from user input and behavior. This emotional information can then be used to further optimize the AI ​​feedback. For example, if the user is not satisfied with an idea, the Hedonist AI will suggest more appealing elements.

[2159] Once these AI-generated feedbacks are generated, the server integrates the suggestions and presents them as improvement points for the user, which are then sent to the device, where they are displayed to the user.

[2160] Presentation file creation support function

[2161] Users input the presentation topic and the number of slides they require from their device. For example, they can request a 10-slide presentation on "New Mobile Apps."

[2162] The server generates a presentation structure based on the theme, and the generation AI automatically creates the content and design of the slides. In addition, an emotion recognition system analyzes the user's emotional information and optimizes the presentation content based on that information. For example, if anxiety about preparing a presentation is detected, the server will suggest concise and easy-to-understand slides.

[2163] The final presentation file is sent to the user's terminal, where it can be viewed and edited.

[2164] An embodiment of the code generation function of the mockup site

[2165] The device provides an interface where the user can input the purpose and basic requirements of the mockup site. For example, a user may request a "mockup of a task management app."

[2166] The server analyzes the input requirements and generates the necessary HTML, CSS, and JavaScript code. Furthermore, an emotion recognition mechanism analyzes the user's emotional information and optimizes the design of the mockup code based on that information. For example, if the user prefers a simple and easy-to-use design, the server generates code that includes design elements that meet that preference.

[2167] The generated code is sent to the terminal, which displays it to the user and allows it to be executed and modified.

[2168] Presentation oral manuscript preparation support implementation form

[2169] The user inputs the presentation content and presentation time from the terminal. For example, they request a "3-minute presentation on a new mobile app."

[2170] The server extracts the main points of the speech based on the input content and time, and generates an oral transcript. Furthermore, an emotion recognition unit analyzes the user's emotional information and optimizes the transcript content based on that information. For example, it generates a transcript that includes positive and powerful expressions to help the user speak with confidence.

[2171] The generated oral transcript is sent to the terminal and can be used for display and practice on the terminal.

[2172] Embodiment of the virtual evaluation function

[2173] Users upload their ideas and presentation materials from their devices. For example, they can submit a "presentation for a new mobile app."

[2174] The server analyzes the submitted materials, and the generating AI performs a virtual evaluation based on factors such as originality, feasibility, and user satisfaction. An emotion recognition system analyzes the user's emotions and reflects that information in the evaluation. For example, if a user feels anxious about being evaluated, an encouraging message can be included.

[2175] The evaluation results and points for improvement are generated and sent to the device, which then displays them to the user and proposes an action plan for the next step.

[2176] ---

[2177] In this way, by combining an emotion engine, the present invention realizes a system that supports idea refinement, presentation preparation, and virtual evaluation while taking into consideration the user's emotions, allowing users to achieve better results and raising the overall level of the contest.

[2178] The processing flow will be explained below.

[2179] I understand. Now, I will explain the flow of program processing of the invention based on the claims, broken down into specific steps.

[2180] ---

[2181] Idea brush-up function

[2182] Step 1:

[2183] A user enters an idea into the device and clicks the submit button. For example, the user enters "Idea for a new mobile app" into the text field.

[2184] Step 2:

[2185] The terminal transmits the user's input data to the server.

[2186] Step 3:

[2187] The server analyzes the received idea text and uses a natural language processing engine to extract key elements and concepts.

[2188] Step 4:

[2189] Based on the analysis results, the server transfers the data to four AIs (Dreamer AI, Hedonist AI, Realist AI, and Critic AI).

[2190] Step 5:

[2191] Each AI generates feedback from its own perspective.

[2192] Dreamer AI: Suggests future possibilities and dream elements of ideas.

[2193] Hedonist AI: Suggests enjoyable elements that improve the user experience.

[2194] Realistic AI: Point out technical feasibility and practical challenges.

[2195] Critic AI: Comments on the overall evaluation and marketability of the idea.

[2196] Step 6:

[2197] The server uses emotion recognition means to recognize emotions from the user's input and actions, for example, by analyzing the user's facial expressions and input speed.

[2198] Step 7:

[2199] The server optimizes the AI's feedback based on the recognized emotional information. For example, if the user is dissatisfied with an idea, the Hedonist AI will suggest more positive elements.

[2200] Step 8:

[2201] The server aggregates the feedback from the four AIs and generates unified improvement suggestions.

[2202] Step 9:

[2203] The server sends the integrated improvement suggestions to the user's terminal.

[2204] Step 10:

[2205] The device displays integrated improvement suggestions to the user.

[2206] ---

[2207] Presentation file creation support function

[2208] Step 1:

[2209] The user inputs the presentation topic and the number of slides required from the device. Example: Requesting 10 slides for a presentation on "New Mobile App."

[2210] Step 2:

[2211] The device sends a request to the server, including the theme and number of slides.

[2212] Step 3:

[2213] The server analyzes the theme and determines the basic framework for the presentation, creating sections such as "Overview," "Feature Introduction," and "Market Analysis."

[2214] Step 4:

[2215] The server generates the content for each section and uses AI to automatically create slide designs.

[2216] Step 5:

[2217] The server analyzes the user's emotional information using emotion recognition means, e.g., analyzing the user's facial expression or voice tone.

[2218] Step 6:

[2219] The server then optimizes the presentation content based on the emotional information it recognizes. For example, it suggests simple, friendly slides to a user who is feeling nervous.

[2220] Step 7:

[2221] The server creates the final slide deck and converts it to the appropriate format (e.g. PowerPoint, PDF).

[2222] Step 8:

[2223] The server transmits the generated presentation file to the user's terminal.

[2224] Step 9:

[2225] The device displays the presentation file to the user and allows them to download and edit it as needed.

[2226] ---

[2227] Code generation for mockup sites

[2228] Step 1:

[2229] A user inputs the purpose and basic requirements of the mockup site from their device. For example, they request a "task management app mockup."

[2230] Step 2:

[2231] The terminal transmits the requirement data to the server.

[2232] Step 3:

[2233] The server analyzes the requirements and extracts the necessary components and UI design elements.

[2234] Step 4:

[2235] The server generates the necessary HTML, CSS, and JavaScript code based on the analysis results.

[2236] Step 5:

[2237] The server uses emotion recognition means to analyze the user's emotion information, such as the user's typing speed and screen transition frequency.

[2238] Step 6:

[2239] The server optimizes the design of the mockup code based on the recognized emotion information. For example, if the user prefers a simple design, the server generates code that meets that preference.

[2240] Step 7:

[2241] The server combines the generated files (HTML, CSS, JavaScript) into a single mockup file.

[2242] Step 8:

[2243] The server sends the integrated mockup code to the user's device.

[2244] Step 9:

[2245] The device displays a mockup site and allows the user to run and modify it.

[2246] ---

[2247] Presentation manuscript preparation support

[2248] Step 1:

[2249] The user inputs the presentation content and presentation time from the device. Example: Request a "3-minute presentation on a new mobile app."

[2250] Step 2:

[2251] The device sends a request including the presentation content and time to the server.

[2252] Step 3:

[2253] The server extracts the main points of the speech based on the content and time, and creates the basic structure of the oral manuscript.

[2254] Step 4:

[2255] The server summarizes what is said and generates an oral transcript by adding appropriate storytelling elements.

[2256] Step 5:

[2257] The server uses emotion recognition means to analyze the user's emotion information, for example, by analyzing the user's tone of voice and pronunciation rhythm.

[2258] Step 6:

[2259] The server optimizes the content of the transcript based on the recognized emotional information, for example by generating a transcript that includes positive and powerful expressions to help the user speak with confidence.

[2260] Step 7:

[2261] The server transmits the generated oral manuscript to the user's terminal.

[2262] Step 8:

[2263] The terminal displays the oral transcript to the user and provides tools for practice.

[2264] ---

[2265] Virtual evaluation function

[2266] Step 1:

[2267] Users can upload ideas and presentation materials they have created from their devices. For example, submit a "Presentation material for a new mobile app."

[2268] Step 2:

[2269] T...

Claims

1. receiving means; an analysis means for analyzing the input idea; A brush-up method that generates improvement proposals based on the analysis results using multiple algorithms with different characteristics; an integration means for integrating the generated improvement suggestions; an output means for outputting the integrated improvement proposal; A system including:

2. a presentation generation means for automatically generating a presentation file based on an input theme; an output means for outputting the generated presentation file; The system of claim 1 further comprising:

3. a code generation means for generating mockup code for a website or application based on input requirements; an output means for outputting the generated mockup code; The system of claim 1 further comprising:

4. a script generating means for generating an oral script based on the content and time of the presentation; an output means for outputting the generated oral manuscript; The system of claim 1 further comprising:

5. an evaluation means for analyzing and virtually evaluating the submitted materials; an output means for outputting the evaluation result; The system of claim 1 further comprising:

Images