system

Abstract

We provide the system. [Solution] Means for obtaining and reflecting information from digital databases, A means of storing multiple information formats and designs and enabling rapid customization, A means of automatically sending the generated electronic documents to the content management system, A means of guaranteeing data integrity and security using blockchain technology, A means of using artificial intelligence to evaluate the content of electronic documents and suggest corrections, A system that includes this.

Description

Technical Field

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

Background Art

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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a business environment, it is required to efficiently generate and manage electronic documents while ensuring information format, design selection and application, real-time data reflection, and security. However, current systems are in a situation where it is difficult to satisfy these requirements simultaneously. Also, when data acquisition and reflection are manual, efficiency decreases and human errors are likely to occur. As a result, it becomes difficult to maintain consistency in the content of the created electronic documents, and vulnerabilities may be pointed out in terms of security.

Means for Solving the Problems

[0005] This invention provides a means for automatically retrieving necessary information from a digital database and efficiently customizing the format and design of electronic documents. Furthermore, it employs blockchain technology to securely manage these electronic documents and includes a function for automatically uploading them to a content management system. It also utilizes artificial intelligence to review the content of generated electronic documents and suggest revisions as needed, thereby improving the consistency and accuracy of the documents. In this way, it provides a system that allows users to create high-quality and secure electronic documents in a short amount of time.

[0006] A "digital database" is a platform that systematically stores information in electronic format, allowing for quick access to necessary information.

[0007] An "information format" is a template that formats data into a specific structure or style, and is used in presentations, reports, and other similar documents.

[0008] "Design" is a general term for the layout and style elements used to visually represent information and content.

[0009] "Electronic documents" refer to documents created, saved, and edited on a computer, and shared in digital format.

[0010] A "content management system" is a software platform for managing, storing, editing, and publishing digital content.

[0011] Blockchain technology is a technology that uses a distributed ledger of data to guarantee data security, tamper resistance, and reliability.

[0012] "Artificial intelligence" is a technology in which computers mimic some aspects of human intelligence, possessing the ability to learn, reason, and solve problems.

[0013] "Automatic upload" refers to the process by which a system sends specified digital content to a designated location without manual intervention. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention aims to enable the efficient creation and management of electronic documents in business, and its specific embodiments are described below. This system provides an environment in which servers, terminals, and users interact to create and manage electronic documents quickly and securely.

[0036] System Program and Processing Overview

[0037] 1. Server Role

[0038] The server stores multiple information formats and designs, providing them based on user requests. The server connects to a digital database and retrieves the information users need in real time. This data is immediately reflected in the specified template, keeping it up-to-date.

[0039] 2. The role of the terminal

[0040] The terminal acts as the user interface, sending user requests to the server. It assists users in selecting and customizing templates, and appropriately displays review results and revision suggestions after document generation.

[0041] 3. User actions

[0042] Users log in via their device and select a template suitable for their work. They then customize the template, which is saved to the server for future use. Users review the generated electronic document and make necessary revisions based on suggestions from the AI ​​review process.

[0043] Specific example

[0044] For example, when creating a meeting report, the user selects a meeting report format on their device. Then, data related to the month's meetings is retrieved from the server in real time and reflected in the template. The user reviews the report, and if any deficiencies are pointed out by the AI, they make corrections based on the AI's suggestions. Finally, the electronic document is automatically uploaded to the content management system via the server and immediately shared with the relevant departments.

[0045] In this way, the system consistently supports everything from template selection to real-time data reflection and AI-powered review, helping users efficiently create high-quality documents.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] The user logs into the system using their device. Here, user authentication takes place, and a list of templates corresponding to the user's permission level is displayed.

[0049] Step 2:

[0050] The user selects their preferred template from the displayed template list. The device then sends this selection information to the server.

[0051] Step 3:

[0052] The server prepares a template based on the user's selection and sends back the design and customization options associated with that template to the device.

[0053] Step 4:

[0054] The user customizes the template on their device. This includes selecting colors, logos, and fonts, and the customized results are sent to the server.

[0055] Step 5:

[0056] The server saves the customizations and then extracts relevant data from a digital database in real time based on those customizations.

[0057] Step 6:

[0058] The extracted data is reflected in the template via the server, and an initial electronic document is generated. This electronic document is then sent to the terminal for review before finalization.

[0059] Step 7:

[0060] The device displays electronic documents to the user, and an automated review is performed by AI. The AI ​​analyzes the content of the document and provides suggestions for improvement.

[0061] Step 8:

[0062] The user reviews the AI's suggestions and makes any necessary corrections via their device. Once the corrections are complete, the user orders the creation of the final version.

[0063] Step 9:

[0064] The server generates the final electronic document, and its security is guaranteed using blockchain technology.

[0065] Step 10:

[0066] The final version is automatically uploaded to the CMS, and users with access rights are notified. This allows for sharing with other members.

[0067] (Example 1)

[0068] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0069] Conventional electronic document creation systems lacked the means to efficiently and securely perform the entire process of data acquisition, template selection and customization, and evaluation and revision of created documents. In particular, there were challenges regarding the reliability of technologies that ensure real-time updates of electronic documents and data integrity and security. Furthermore, the insufficient functionality to automatically evaluate document content and suggest revisions using machine learning resulted in a heavy burden on users. Therefore, the present invention aims to solve these problems.

[0070] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0071] In this invention, the server includes components for retrieving and reflecting information from data storage, components for storing multiple data formats and designs and enabling rapid customization, and components for automatically transmitting generated electronic documents to an information management system. This enables real-time data retrieval and secure and efficient creation and management of electronic documents.

[0072] "Data storage" refers to a place for storing and managing information, maintaining its content in a digital format.

[0073] "Information retrieval" refers to the process of searching for necessary information from data storage and retrieving it in a usable format.

[0074] A "data format" is a standard for arranging information in a specific structure or style, and is used when sharing information between different systems and applications.

[0075] "Design" refers to the planning and arrangement style for visually arranging and representing information, and plays a role in making information easier for users to understand.

[0076] An "information management system" refers to a system designed to efficiently store, organize, search, and share information.

[0077] "Distributed ledger technology" refers to technologies like blockchain that securely record transactions and data on a decentralized network and guarantee their integrity.

[0078] Machine learning is a branch of artificial intelligence that enables computer systems to automatically learn from experience and data and improve.

[0079] A "user interface" is the interface that users use to interact directly with a system, and it greatly influences operability and ease of use.

[0080] A "template" refers to a framework that provides standardized forms or formats suited to a specific purpose, making it easier for users to efficiently input information.

[0081] To implement this invention, a system is provided in which a server, terminal, and user cooperate to efficiently and securely create and manage electronic documents.

[0082] The server interacts with data storage to retrieve necessary information. This allows the data required by the user to be reflected in the template in real time, ensuring it is always up-to-date. The server also has the capability to store multiple data formats and designs, providing them based on user requests. Utilizing machine learning technology, the server analyzes the document content and suggests revisions. This enables users to efficiently create high-quality content. The created electronic documents are then automatically sent to the information management system for secure storage and sharing. Distributed ledger technology is used to ensure data integrity and security.

[0083] The terminal provides an interface for users to interact with the system. Users log in using the terminal and select a template suitable for their work purpose. The terminal sends user actions to the server, supporting the data retrieval and document generation processes. It also presents the user with review results using a generative AI model, visually assisting with necessary corrections.

[0084] Users select a template for the electronic document they want to create via the terminal interface and enter or edit data. They then review the document through machine learning-based evaluation results and make revisions as needed to complete a high-quality document. The document reviewed by the user is immediately shared with relevant departments via an automatic synchronization function.

[0085] As a concrete example, one could use a prompt such as, "Create meeting minutes for this month and apply AI review." In this way, this invention provides a system for the efficient creation and management of electronic documents.

[0086] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0087] Step 1:

[0088] The user logs into the system using a terminal. The terminal receives input for user authentication and sends it to the server. The server compares the authentication information with records in data storage to verify that the user has access rights. If successful, it sends a success message to the terminal and allows it to proceed to the next step.

[0089] Step 2:

[0090] The user selects a suitable template via the terminal. The terminal receives the user's selection as input and sends it to the server. The server retrieves the corresponding template information from its data storage and returns that information to the terminal. The terminal displays the retrieved template to the user and prepares it for customization.

[0091] Step 3:

[0092] The server starts data processing for document generation using the template and associated data. First, it retrieves the necessary information from data storage. This includes meeting information and business data. The server converts the retrieved data into the appropriate data format and reflects it in the template. This process generates a template containing the latest information, which is then sent to the terminal.

[0093] Step 4:

[0094] The user reviews the document generated through the terminal and makes any necessary corrections. The terminal then sends the user's corrections back to the server as input. The server reflects the corrections in data storage and checks for consistency. This ensures that the user can always finalize documents based on the latest information.

[0095] Step 5:

[0096] The server analyzes the document using a generative AI model and evaluates the quality of its content. Based on the input document, the AI ​​model checks for typos and grammatical errors, optimizes syntax, and generates revision suggestions. These suggestions are then fed back to the user through the terminal.

[0097] Step 6:

[0098] The user considers the revision suggestions from the AI ​​model and finalizes the document. The terminal sends the finalized information to the server, which stores it in the information management system and automatically shares it with the relevant departments. This ensures secure storage of content and smooth information sharing.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] In industrial product manufacturing, there is a need to efficiently record assembly processes and quality control, and to detect and correct defects in real time. However, conventional systems rely on manual data acquisition and recording, leading to issues such as reduced accuracy and wasted time. Furthermore, it is difficult to efficiently manage and share the generated data while guaranteeing the security and integrity of electronic documents.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes a device for acquiring and reflecting information from a digital data storage device, a device for recording multiple data formats and designs to enable rapid optimization, and a device for detecting the assembly process using image processing technology, processing the data in real time, and reflecting it in an electronic document. This enables improved accuracy of data recording and rapid detection of defects in the manufacturing site.

[0104] A "digital data storage device" is a device for electronically recording and storing information, and plays a role in efficiently managing various forms of data.

[0105] "Information format" refers to a framework or format for structuring data, and serves as a foundation for facilitating the organization and distribution of information.

[0106] "Design" refers to a plan or specification created to achieve a specific purpose, which defines in detail the structure and function of a system or product.

[0107] "Real-time" refers to a situation where an event is processed immediately upon its occurrence, resulting in near-instantaneous results.

[0108] "Image processing technology" refers to the techniques for manipulating and analyzing digital image data, and is a means of extracting, transforming, and recognizing visual information.

[0109] An "electronic document" is a document created and stored in digital format, and is an information medium that can be viewed and edited on a computer or digital device.

[0110] An "information management platform" is a foundational system for the integrated management and distribution of information, enabling efficient storage, access, and sharing of data.

[0111] "Machine learning technology" is a collection of algorithms and methods aimed at enabling computer systems to automatically improve their performance through experience, and possesses the ability to extract patterns and knowledge from data.

[0112] "Distributed ledger technology" is a digital ledger used to prevent data tampering and is a technological foundation for securely sharing data among participants across multiple networks.

[0113] The system for implementing this invention operates based on hardware and software such as a digital data storage device, an information management platform, image processing technology, and machine learning technology.

[0114] The server acquires various types of data from digital data storage devices in real time and reflects them in the information management platform. This enables the creation of electronic documents based on the latest information at all times. Furthermore, it incorporates machine learning technology to automatically classify and assign quality to the acquired data, achieving efficient management.

[0115] Meanwhile, the terminal is responsible for inputting and processing information, and for customizing the generated electronic documents. Users can easily review documents created using this terminal and receive feedback on the generated data through image processing technology. This improves the quality and accuracy of the documents.

[0116] For example, consider a scenario in a factory production line where defects are detected during the product assembly process. In this case, a generative AI model can analyze the assembly video and automatically identify the problems, enabling a rapid response.

[0117] Examples of prompt statements to input to a generative AI model include the following:

[0118] "Create prompts for a system that records the product assembly process in a factory and uses AI to detect defects, identifying areas that need correction in real time."

[0119] This system configuration enables rapid acquisition and analysis of information, leading to increased efficiency and improved quality in the manufacturing of industrial products.

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] The server retrieves image data of product assembly from a digital data storage device. When retrieving this image data, the server accesses a database via the network to collect the latest images related to a specific manufacturing line. The input is images of the product, and the output is a dataset for image processing.

[0123] Step 2:

[0124] The acquired image data is analyzed using image processing technology installed on the server. Specifically, libraries such as OpenCV are used to automatically detect abnormal areas and specific anomalies within the image. The input is the image data before processing, and the output is the analysis results that point out the anomalies or the marked image.

[0125] Step 3:

[0126] The server inputs the analysis results from image processing into a generative AI model based on machine learning technology to obtain suggestions for further improvement and correction. This process uses a learning model generated based on multiple historical data sets to identify potential problems. The input is the results after image processing, and the output is specific correction suggestions.

[0127] Step 4:

[0128] The terminal displays analysis results and suggested corrections sent from the server to the user. The user uses this information to identify actual problems on the production line and decide how to address them. The input is the analysis results from the server, and the output is information formatted in a way that the user can understand.

[0129] Step 5:

[0130] The user modifies the manufacturing process based on the correction suggestions displayed on the terminal. In this step, the user directly changes the settings of production machinery or revises personnel allocation. The output is the state of the manufacturing line after the problems have been corrected.

[0131] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0132] This invention relates to a system that incorporates an emotion engine for creating and managing electronic documents, which recognizes user emotions and dynamically adjusts the design and content of those emotions based on those emotions. This system operates collaboratively between a server, a terminal, and a user, and aims to improve the user experience by utilizing emotion recognition technology.

[0133] System Program and Processing Overview

[0134] 1. Server Role

[0135] The server interacts with a digital database to retrieve the latest information in real time and reflect it in the template. It also incorporates an emotion engine to assess the user's emotional state, collecting and analyzing emotional data displayed by the user while creating electronic documents. This allows the server to make adaptive design changes based on the emotional data.

[0136] 2. The role of the terminal

[0137] The device provides a user interface and sends emotional data to the server in real time as the user selects and customizes templates. The emotion engine analyzes the user's emotions, receives feedback to adjust templates and content, and presents it to the user visually.

[0138] 3. User actions

[0139] Users select templates and customize their content via their devices. The system analyzes the user's emotions in real time during creation, and emotional data is managed to protect privacy. For example, if a user is stressed, the system automatically adjusts the template to a more relaxing design.

[0140] Specific example

[0141] For example, when a user creates a marketing report, they select an appropriate template on their device. Based on the user's facial expressions and voice tone, the emotion engine built into the server determines that the user is feeling anxious. In that case, the server automatically selects fonts and color schemes that do not emphasize text and applies a calm layout. After generation, this report undergoes AI review and user confirmation before the final version is uploaded to the CMS.

[0142] In this way, the system assists in document creation while taking user emotions into consideration, providing a more user-friendly and productive work environment.

[0143] The following describes the processing flow.

[0144] Step 1:

[0145] The user logs into the device and begins accessing the system. The device sends the user's authentication information to the server for permission verification.

[0146] Step 2:

[0147] The server provides the terminal with a list of available templates and design options based on the user's permissions. The user then selects the appropriate template.

[0148] Step 3:

[0149] The user selects a template, and the device sends that information to the server. Based on this, the emotion engine prepares to begin analyzing the user's emotions.

[0150] Step 4:

[0151] While the user customizes templates through the device, the device continuously monitors the user's emotional state using its camera and microphone.

[0152] Step 5:

[0153] The device sends the collected emotional data to the server. An emotion engine built into the server analyzes this data to identify the user's current emotions.

[0154] Step 6:

[0155] The server dynamically adjusts the template design and structure based on analyzed sentiment data. For example, if the user is feeling stressed, it will change to a calmer color scheme and font.

[0156] Step 7:

[0157] The adjusted template is generated by the server and sent to the terminal. The terminal then presents the user with the visual changes and asks for confirmation.

[0158] Step 8:

[0159] The user approves the adjustments and completes the document creation. The terminal then sends a request for final confirmation to the server.

[0160] Step 9:

[0161] The server generates the final version of the document, which is then reviewed by AI, and its security is guaranteed using blockchain technology.

[0162] Step 10:

[0163] Secure electronic documents are automatically uploaded to the CMS by the server, and sharing notifications are sent to the relevant users.

[0164] (Example 2)

[0165] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0166] In today's information society, the creation and management of electronic documents are becoming increasingly important. However, traditional methods cannot dynamically adjust document design to respond to user emotions, making it difficult to improve the user experience. Furthermore, there is a need to reflect the content of electronic documents in a timely and accurate manner and to guarantee data integrity.

[0167] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0168] In this invention, the server includes means for acquiring and reflecting information from an electronic database, means for sensing and analyzing the user's emotional state, and means for dynamically adjusting the document design and content based on the analyzed emotional results. This enables the generation of optimal electronic documents tailored to the user's emotions and secure data management.

[0169] An "electronic database" is a system that stores and manages information in a structured, digital format.

[0170] "Information format" refers to the structure and type of data or information that is displayed.

[0171] An "information management system" is a system for organizing, storing, retrieving, and sharing information and data.

[0172] "Distributed ledger technology" is a distributed database technology in which multiple nodes cooperate to manage data in order to guarantee its integrity and security.

[0173] "Machine learning technology" is a technology that gives computers the ability to learn from data and find patterns.

[0174] "User emotional state" refers to a situation that demonstrates a user's psychological or emotional response.

[0175] "Dynamic adjustment" means making immediate changes in response to the situation.

[0176] This invention is a system for dynamically adjusting the design and content of electronic documents, taking into account the user's emotional state. The system mainly consists of collaboration between a server, a terminal, and the user.

[0177] The server functions as the central hub for managing information, retrieving necessary information from electronic databases and incorporating it into documents. The hardware used here is standard server equipment, and the software incorporates protocols that support distributed ledger technology. The server also features an emotion engine that utilizes machine learning techniques, analyzing user emotion data using a generative AI model. This model uses the prompt "Please propose a design that will help the user relax" to provide design suggestions based on the analysis results.

[0178] The terminal acts as the interface with the user, sensing the user's facial expressions and voice tone in real time through sensors and microphones. This emotional data is processed through appropriate software (e.g., OpenCV for face recognition, Praat for voice analysis) and sent to the server. The terminal also visually presents feedback to the user based on the analysis results sent from the server, helping the user customize documents.

[0179] This system allows users to select templates tailored to their purpose and create documents that align with their emotions. For example, when creating a marketing report, if a user feels stressed, the system automatically suggests calming color tones. This enables users to create documents more efficiently and stress-free.

[0180] This invention aims to significantly improve the user experience and enable adaptive and interactive document management.

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] The user begins creating an electronic document using the terminal. When the user selects a template, the terminal receives this selection information as input and applies it to the user interface. At this time, the displayed content (output) is configured based on the template selected by the user. Specifically, the terminal displays a list of templates and sets the template clicked by the user as the currently selected template.

[0184] Step 2:

[0185] The device monitors the user's facial expressions and voice tone in real time. It acquires emotional data from sensors and a microphone as input. This data is processed by facial recognition software (e.g., OpenCV) and voice analysis software (e.g., Praat) to estimate the user's emotional state (output). Specifically, the device continuously acquires information from the camera and microphone and prepares to send it to the emotion engine.

[0186] Step 3:

[0187] The device sends the acquired emotion data to the server. The input data is the emotion estimation result, which is encrypted and sent to the server. The transmitted data is used for analysis on the server. Specifically, the device sends data to the server using a secure communication protocol.

[0188] Step 4:

[0189] The server uses an emotion engine to analyze the received emotional data. Using emotional data as input, it employs a generative AI model to perform analysis according to the prompt "Please propose a design that will help the user relax." This generates design proposals (outputs) that match the user's emotions. Specifically, the AI ​​analyzes the data and creates suggestions for adjusting the template's colors and fonts.

[0190] Step 5:

[0191] The server sends the analysis results to the terminal. It receives design proposals as input and outputs them to the terminal. Specifically, the server sends the created design change proposals back to the terminal via secure communication.

[0192] Step 6:

[0193] The terminal presents design suggestions received from the server to the user. It receives server suggestions as input and integrates them into the user interface. The user reviews the visually adjusted design and makes final edits (output). Specifically, the terminal reflects the new design on the screen in real time and provides the user with options.

[0194] Step 7:

[0195] The user completes the final edits and saves or sends the electronic document. The system receives the edited document as input and saves it within the system or outputs it to an external information management system. Specifically, the user presses a confirmation button to complete the document and, if necessary, shares it with others via the internet or uploads it to a CMS.

[0196] (Application Example 2)

[0197] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0198] Traditionally, a challenge in the creation and management of electronic records has been the insufficient dynamic content adjustment based on the user's emotional state. Furthermore, while providing information tailored to individual emotions is crucial for improving the user experience, achieving this is often difficult.

[0199] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0200] In this invention, the server includes means for acquiring and reflecting information from a digital recording medium, means for accumulating multiple information formats and designs and enabling rapid adjustment, and means for analyzing the user's emotional state and dynamically adjusting the content delivered based on that analysis. This enables the delivery of personalized content that responds to the user's emotions.

[0201] A "digital recording medium" is a medium for electronically storing, managing, and transmitting information, and includes databases and cloud storage.

[0202] "Information acquisition" refers to the act of obtaining requested information from a digital recording medium and providing it in a format that meets the user's requirements.

[0203] An "information format" is a format that defines the structure and layout of data, and includes templates that can be customized for various purposes.

[0204] "Design" refers to the structure and style used to visually represent information and data, and is used to present them in a way that is easily recognizable to users.

[0205] "Rapid adjustment" refers to the ability to change and adapt information formats and designs in a short amount of time, enabling the provision of optimal information tailored to the user's needs and circumstances.

[0206] "User's emotional state" refers to the emotional state and psychological condition expressed by the user, and is analyzed using facial recognition and voice analysis.

[0207] "Dynamic adjustment" refers to flexibly changing the content and method of delivery of information in accordance with real-time changing situations and conditions.

[0208] "Personalized content delivery" is a delivery method that selects and provides the most relevant information based on the user's emotional state and individual preferences.

[0209] In the system that implements this application example, the server acts as a central control unit, acquiring necessary information from digital storage media and processing it to analyze the user's emotional state. The server uses an emotion recognition API (e.g., emotion judgment software) to receive and analyze the user's emotional data in real time. Subsequently, based on the analysis results, it selects the optimal content and sends it to the terminal. At this time, the design is quickly adjusted from template information on the digital storage media (e.g., cloud storage).

[0210] The device interacts directly with the user through its user interface, displaying dynamic content provided by the server. The device incorporates facial and voice recognition capabilities, periodically sending this data to the server. This allows the server to constantly maintain an up-to-date understanding of the user's emotional state and continuously optimize the content.

[0211] Users access content on a daily basis using their devices. The system provides information in a way that is sensitive to the user's mood, offering content with a relaxing design when the user is feeling stressed, and analytical content when the user is feeling excited and highly focused.

[0212] For example, when a user opens a news app, if it's determined that they are highly focused, it will display detailed economic analysis articles. When they want to relax, it will display articles about travel or hobbies.

[0213] Examples of prompt messages include, "Get the user's emotional state and recommend travel-related articles if they are calm," and "Play relaxation music if the user is judged to be highly stressed."

[0214] In this way, the embodiment for carrying out the invention enables personalized content delivery based on user emotions, contributing to an improved experience.

[0215] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0216] Step 1:

[0217] The server receives user emotion data (e.g., facial expressions, voice tone) from the terminal. The input data is acquired in real time using facial recognition technology and voice analysis software. This data is analyzed for emotional state via an emotion recognition API. The output is a numerical value or category indicating the user's emotional state.

[0218] Step 2:

[0219] The server selects appropriate information formats and content from digital storage media based on the analysis of the user's emotional state. The input is emotional data, and the output is corresponding content IDs and template information. A generative AI model is used to recommend content optimized for the user's emotions.

[0220] Step 3:

[0221] The terminal receives content information sent from the server and displays it through the user interface. Input is selected content or template data, and output is a visually adjusted content screen. The terminal renders the visual elements, taking into account screen resolution and interaction.

[0222] Step 4:

[0223] The user provides interaction and feedback on the displayed content. Input is the content display on the device, and output is new data resulting from the user's actions (e.g., scrolling, clicking). User action information is sent from the device to the server and used to select the next content.

[0224] Step 5:

[0225] The server accumulates user interaction data and analyzes it to improve future content delivery. The input is user interaction data, and the output is updated information for the predictive model used for future content adjustments. It generates prompt messages, enabling more accurate content recommendations in subsequent processing.

[0226] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0227] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0228] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0229] [Second Embodiment]

[0230] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0231] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0232] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0233] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0234] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0235] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0236] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0237] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0238] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0239] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0240] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0241] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0242] This invention aims to enable the efficient creation and management of electronic documents in business, and its specific embodiments are described below. This system provides an environment in which servers, terminals, and users interact to create and manage electronic documents quickly and securely.

[0243] System Program and Processing Overview

[0244] 1. Server Role

[0245] The server stores multiple information formats and designs, providing them based on user requests. The server connects to a digital database and retrieves the information users need in real time. This data is immediately reflected in the specified template, keeping it up-to-date.

[0246] 2. The role of the terminal

[0247] The terminal acts as the user interface, sending user requests to the server. It assists users in selecting and customizing templates, and appropriately displays review results and revision suggestions after document generation.

[0248] 3. User actions

[0249] Users log in via their device and select a template suitable for their work. They then customize the template, which is saved to the server for future use. Users review the generated electronic document and make necessary revisions based on suggestions from the AI ​​review process.

[0250] Specific example

[0251] For example, when creating a meeting report, the user selects a meeting report format on their device. Then, data related to the month's meetings is retrieved from the server in real time and reflected in the template. The user reviews the report, and if any deficiencies are pointed out by the AI, they make corrections based on the AI's suggestions. Finally, the electronic document is automatically uploaded to the content management system via the server and immediately shared with the relevant departments.

[0252] In this way, the system consistently supports everything from template selection to real-time data reflection and AI-powered review, helping users efficiently create high-quality documents.

[0253] The following describes the processing flow.

[0254] Step 1:

[0255] The user logs into the system using their device. Here, user authentication takes place, and a list of templates corresponding to the user's permission level is displayed.

[0256] Step 2:

[0257] The user selects their preferred template from the displayed template list. The device then sends this selection information to the server.

[0258] Step 3:

[0259] The server prepares a template based on the user's selection and sends back the design and customization options associated with that template to the device.

[0260] Step 4:

[0261] The user customizes the template on their device. This includes selecting colors, logos, and fonts, and the customized results are sent to the server.

[0262] Step 5:

[0263] The server saves the customizations and then extracts relevant data from a digital database in real time based on those customizations.

[0264] Step 6:

[0265] The extracted data is reflected in the template via the server, and an initial electronic document is generated. This electronic document is then sent to the terminal for review before finalization.

[0266] Step 7:

[0267] The device displays electronic documents to the user, and an automated review is performed by AI. The AI ​​analyzes the content of the document and provides suggestions for improvement.

[0268] Step 8:

[0269] The user reviews the AI's suggestions and makes any necessary corrections via their device. Once the corrections are complete, the user orders the creation of the final version.

[0270] Step 9:

[0271] The server generates the final electronic document, and its security is guaranteed using blockchain technology.

[0272] Step 10:

[0273] The final version is automatically uploaded to the CMS, and users with access rights are notified. This allows for sharing with other members.

[0274] (Example 1)

[0275] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0276] Conventional electronic document creation systems lacked the means to efficiently and securely perform the entire process of data acquisition, template selection and customization, and evaluation and revision of created documents. In particular, there were challenges regarding the reliability of technologies that ensure real-time updates of electronic documents and data integrity and security. Furthermore, the insufficient functionality to automatically evaluate document content and suggest revisions using machine learning resulted in a heavy burden on users. Therefore, the present invention aims to solve these problems.

[0277] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0278] In this invention, the server includes components for acquiring and reflecting information from data storage, components for storing multiple data formats and designs to enable rapid customization, and components for automatically transmitting the generated electronic documents to an information management system. This enables real-time acquisition of data and creation and management of secure and efficient electronic documents.

[0279] "Data storage" refers to a place for storing and managing information and maintains its content in digital form.

[0280] "Information acquisition" refers to the process of searching for necessary information from data storage and retrieving it in a usable state.

[0281] "Data format" is a standard for arranging information in a specific structure or style and is used when sharing information between different systems and applications.

[0282] "Design" refers to the plan or style of arrangement for visually arranging and expressing information and plays a role in making it easier for users to understand the information.

[0283] "Information management system" refers to a system designed to efficiently store, organize, search for, and share information.

[0284] "Distributed ledger technology" refers to technologies such as blockchain that securely record transactions and data on a distributed network and guarantee their integrity.

[0285] "Machine learning" is a field of artificial intelligence that enables computer systems to automatically learn from experience and data and improve.

[0286] "User interface" is an interface used when a user directly interacts with a system and greatly affects operability and ease of use.

[0287] A "template" refers to a framework that provides a standardized form or format suitable for a specific purpose, making it easier for users to efficiently input information.

[0288] To implement this invention, a system is provided in which a server, a terminal, and a user cooperate to efficiently and securely create and manage electronic documents.

[0289] The server collaborates with data storage to obtain necessary information. As a result, the data required by the user can be reflected in the template in real time, always maintaining the latest state. The server further has the function of storing multiple data formats and designs and providing them based on requests from the user. Utilizing machine learning technology, the server analyzes the content of the document and proposes revisions. Thereby, the user can efficiently create high-quality content. And the created electronic documents are automatically sent to the information management system and securely stored and shared. This utilizes distributed ledger technology to ensure the integrity and security of the data.

[0290] The terminal provides an interface for the user to interact with the system. The user uses the terminal to log in and select a template suitable for the work purpose. The terminal sends the user's operations to the server and supports the process of data acquisition and document generation. Also, it presents the review results using a generation AI model to the user and visually supports necessary corrections.

[0291] The user selects a template for the electronic document to be created via the interface of the terminal and inputs or edits the data. Then, by checking the document through the evaluation results by machine learning and making corrections as needed, the final high-quality document is completed. The document confirmed by the user is immediately shared with the relevant departments through the automatic synchronization function.

[0292] As a concrete example, one could use a prompt such as, "Create meeting minutes for this month and apply AI review." In this way, this invention provides a system for the efficient creation and management of electronic documents.

[0293] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0294] Step 1:

[0295] The user logs into the system using a terminal. The terminal receives input for user authentication and sends it to the server. The server compares the authentication information with records in data storage to verify that the user has access rights. If successful, it sends a success message to the terminal and allows it to proceed to the next step.

[0296] Step 2:

[0297] The user selects a suitable template via the terminal. The terminal receives the user's selection as input and sends it to the server. The server retrieves the corresponding template information from its data storage and returns that information to the terminal. The terminal displays the retrieved template to the user and prepares it for customization.

[0298] Step 3:

[0299] The server starts data processing for document generation using the template and associated data. First, it retrieves the necessary information from data storage. This includes meeting information and business data. The server converts the retrieved data into the appropriate data format and reflects it in the template. This process generates a template containing the latest information, which is then sent to the terminal.

[0300] Step 4:

[0301] The user checks the document generated through the terminal and makes necessary corrections. The terminal resends the corrections made by the user to the server as input. The server reflects the correction content in the data storage and checks the consistency of the content. As a result, the user can always finish the document based on the latest information.

[0302] Step 5:

[0303] The server analyzes the document using the generation AI model and evaluates the quality of the content. Based on the input document, the AI model checks for spelling and grammar errors, optimizes the syntax, and generates correction proposals. This proposal is fed back to the user through the terminal.

[0304] Step 6:

[0305] [[ID=I5]] The user considers the correction proposals from the AI model and finalizes the final document. The terminal sends the finalized information to the server, and the server saves it in the information management system and automatically shares it with the relevant departments. As a result, secure storage of the content and smooth information sharing are realized.

[0306] (Application Example 1)

[0307] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0308] In the manufacturing site of industrial products, it is required to efficiently record the assembly process and quality control records and discover and correct defects in real time. However, in the conventional system, since data acquisition and recording rely on manual operations, problems such as a decrease in accuracy and waste of time have arisen. Furthermore, it is difficult to efficiently manage and share the generated data while ensuring the safety and integrity of electronic documents.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0310] In this invention, the server includes a device for acquiring and reflecting information from a digital data storage device, a device for recording multiple data formats and designs to enable rapid optimization, and a device for detecting the assembly process using image processing technology, processing the data in real time, and reflecting it in an electronic document. This enables improved accuracy of data recording and rapid detection of defects in the manufacturing site.

[0311] A "digital data storage device" is a device for electronically recording and storing information, and plays a role in efficiently managing various forms of data.

[0312] "Information format" refers to a framework or format for structuring data, and serves as a foundation for facilitating the organization and distribution of information.

[0313] "Design" refers to a plan or specification created to achieve a specific purpose, which defines in detail the structure and function of a system or product.

[0314] "Real-time" refers to a situation where an event is processed immediately upon its occurrence, resulting in near-instantaneous results.

[0315] "Image processing technology" refers to the techniques for manipulating and analyzing digital image data, and is a means of extracting, transforming, and recognizing visual information.

[0316] An "electronic document" is a document created and stored in digital format, and is an information medium that can be viewed and edited on a computer or digital device.

[0317] An "information management platform" is a foundational system for the integrated management and distribution of information, enabling efficient storage, access, and sharing of data.

[0318] "Machine learning technology" is a collection of algorithms and methods aimed at enabling computer systems to automatically improve their performance through experience, and possesses the ability to extract patterns and knowledge from data.

[0319] "Distributed ledger technology" is a digital ledger used to prevent data tampering and is a technological foundation for securely sharing data among participants across multiple networks.

[0320] The system for implementing this invention operates based on hardware and software such as a digital data storage device, an information management platform, image processing technology, and machine learning technology.

[0321] The server acquires various types of data from digital data storage devices in real time and reflects them in the information management platform. This enables the creation of electronic documents based on the latest information at all times. Furthermore, it incorporates machine learning technology to automatically classify and assign quality to the acquired data, achieving efficient management.

[0322] Meanwhile, the terminal is responsible for inputting and processing information, and for customizing the generated electronic documents. Users can easily review documents created using this terminal and receive feedback on the generated data through image processing technology. This improves the quality and accuracy of the documents.

[0323] For example, consider a scenario in a factory production line where defects are detected during the product assembly process. In this case, a generative AI model can analyze the assembly video and automatically identify the problems, enabling a rapid response.

[0324] Examples of prompt statements to input to a generative AI model include the following:

[0325] "Create prompts for a system that records the product assembly process in a factory and uses AI to detect defects, identifying areas that need correction in real time."

[0326] This system configuration enables rapid acquisition and analysis of information, leading to increased efficiency and improved quality in the manufacturing of industrial products.

[0327] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0328] Step 1:

[0329] The server retrieves image data of product assembly from a digital data storage device. When retrieving this image data, the server accesses a database via the network to collect the latest images related to a specific manufacturing line. The input is images of the product, and the output is a dataset for image processing.

[0330] Step 2:

[0331] The acquired image data is analyzed using image processing technology installed on the server. Specifically, libraries such as OpenCV are used to automatically detect abnormal areas and specific anomalies within the image. The input is the image data before processing, and the output is the analysis results that point out the anomalies or the marked image.

[0332] Step 3:

[0333] The server inputs the analysis results from image processing into a generative AI model based on machine learning technology to obtain suggestions for further improvement and correction. This process uses a learning model generated based on multiple historical data sets to identify potential problems. The input is the results after image processing, and the output is specific correction suggestions.

[0334] Step 4:

[0335] The terminal displays analysis results and suggested corrections sent from the server to the user. The user uses this information to identify actual problems on the production line and decide how to address them. The input is the analysis results from the server, and the output is information formatted in a way that the user can understand.

[0336] Step 5:

[0337] The user modifies the manufacturing process based on the correction suggestions displayed on the terminal. In this step, the user directly changes the settings of production machinery or revises personnel allocation. The output is the state of the manufacturing line after the problems have been corrected.

[0338] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0339] This invention relates to a system that incorporates an emotion engine for creating and managing electronic documents, which recognizes user emotions and dynamically adjusts the design and content of those emotions based on those emotions. This system operates collaboratively between a server, a terminal, and a user, and aims to improve the user experience by utilizing emotion recognition technology.

[0340] System Program and Processing Overview

[0341] 1. Server Role

[0342] The server interacts with a digital database to retrieve the latest information in real time and reflect it in the template. It also incorporates an emotion engine to assess the user's emotional state, collecting and analyzing emotional data displayed by the user while creating electronic documents. This allows the server to make adaptive design changes based on the emotional data.

[0343] 2. The role of the terminal

[0344] The device provides a user interface and sends emotional data to the server in real time as the user selects and customizes templates. The emotion engine analyzes the user's emotions, receives feedback to adjust templates and content, and presents it to the user visually.

[0345] 3. User actions

[0346] Users select templates and customize their content via their devices. The system analyzes the user's emotions in real time during creation, and emotional data is managed to protect privacy. For example, if a user is stressed, the system automatically adjusts the template to a more relaxing design.

[0347] Specific example

[0348] For example, when a user creates a marketing report, they select an appropriate template on their device. Based on the user's facial expressions and voice tone, the emotion engine built into the server determines that the user is feeling anxious. In that case, the server automatically selects fonts and color schemes that do not emphasize text and applies a calm layout. After generation, this report undergoes AI review and user confirmation before the final version is uploaded to the CMS.

[0349] In this way, the system assists in document creation while taking user emotions into consideration, providing a more user-friendly and productive work environment.

[0350] The following describes the processing flow.

[0351] Step 1:

[0352] The user logs into the device and begins accessing the system. The device sends the user's authentication information to the server for permission verification.

[0353] Step 2:

[0354] The server provides the terminal with a list of available templates and design options based on the user's permissions. The user then selects the appropriate template.

[0355] Step 3:

[0356] The user selects a template, and the device sends that information to the server. Based on this, the emotion engine prepares to begin analyzing the user's emotions.

[0357] Step 4:

[0358] While the user customizes templates through the device, the device continuously monitors the user's emotional state using its camera and microphone.

[0359] Step 5:

[0360] The device sends the collected emotional data to the server. An emotion engine built into the server analyzes this data to identify the user's current emotions.

[0361] Step 6:

[0362] The server dynamically adjusts the template design and structure based on analyzed sentiment data. For example, if the user is feeling stressed, it will change to a calmer color scheme and font.

[0363] Step 7:

[0364] The adjusted template is generated by the server and sent to the terminal. The terminal then presents the user with the visual changes and asks for confirmation.

[0365] Step 8:

[0366] The user approves the adjustments and completes the document creation. The terminal then sends a request for final confirmation to the server.

[0367] Step 9:

[0368] The server generates the final version of the document, which is then reviewed by AI, and its security is guaranteed using blockchain technology.

[0369] Step 10:

[0370] Secure electronic documents are automatically uploaded to the CMS by the server, and sharing notifications are sent to the relevant users.

[0371] (Example 2)

[0372] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0373] In today's information society, the creation and management of electronic documents are becoming increasingly important. However, traditional methods cannot dynamically adjust document design to respond to user emotions, making it difficult to improve the user experience. Furthermore, there is a need to reflect the content of electronic documents in a timely and accurate manner and to guarantee data integrity.

[0374] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0375] In this invention, the server includes means for acquiring and reflecting information from an electronic database, means for sensing and analyzing the user's emotional state, and means for dynamically adjusting the document design and content based on the analyzed emotional results. This enables the generation of optimal electronic documents tailored to the user's emotions and secure data management.

[0376] An "electronic database" is a system that stores and manages information in a structured, digital format.

[0377] "Information format" refers to the structure and type of data or information that is displayed.

[0378] An "information management system" is a system for organizing, storing, retrieving, and sharing information and data.

[0379] "Distributed ledger technology" is a distributed database technology in which multiple nodes cooperate to manage data in order to guarantee its integrity and security.

[0380] "Machine learning technology" is a technology that gives computers the ability to learn from data and find patterns.

[0381] "User emotional state" refers to a situation that demonstrates a user's psychological or emotional response.

[0382] "Dynamic adjustment" means making immediate changes in response to the situation.

[0383] This invention is a system for dynamically adjusting the design and content of electronic documents, taking into account the user's emotional state. The system mainly consists of collaboration between a server, a terminal, and the user.

[0384] The server functions as the central hub for managing information, retrieving necessary information from electronic databases and incorporating it into documents. The hardware used here is standard server equipment, and the software incorporates protocols that support distributed ledger technology. The server also features an emotion engine that utilizes machine learning techniques, analyzing user emotion data using a generative AI model. This model uses the prompt "Please propose a design that will help the user relax" to provide design suggestions based on the analysis results.

[0385] The terminal acts as the interface with the user, sensing the user's facial expressions and voice tone in real time through sensors and microphones. This emotional data is processed through appropriate software (e.g., OpenCV for face recognition, Praat for voice analysis) and sent to the server. The terminal also visually presents feedback to the user based on the analysis results sent from the server, helping the user customize documents.

[0386] This system allows users to select templates tailored to their purpose and create documents that align with their emotions. For example, when creating a marketing report, if a user feels stressed, the system automatically suggests calming color tones. This enables users to create documents more efficiently and stress-free.

[0387] This invention aims to significantly improve the user experience and enable adaptive and interactive document management.

[0388] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0389] Step 1:

[0390] The user begins creating an electronic document using the terminal. When the user selects a template, the terminal receives this selection information as input and applies it to the user interface. At this time, the displayed content (output) is configured based on the template selected by the user. Specifically, the terminal displays a list of templates and sets the template clicked by the user as the currently selected template.

[0391] Step 2:

[0392] The device monitors the user's facial expressions and voice tone in real time. It acquires emotional data from sensors and a microphone as input. This data is processed by facial recognition software (e.g., OpenCV) and voice analysis software (e.g., Praat) to estimate the user's emotional state (output). Specifically, the device continuously acquires information from the camera and microphone and prepares to send it to the emotion engine.

[0393] Step 3:

[0394] The device sends the acquired emotion data to the server. The input data is the emotion estimation result, which is encrypted and sent to the server. The transmitted data is used for analysis on the server. Specifically, the device sends data to the server using a secure communication protocol.

[0395] Step 4:

[0396] The server uses an emotion engine to analyze the received emotional data. Using emotional data as input, it employs a generative AI model to perform analysis according to the prompt "Please propose a design that will help the user relax." This generates design proposals (outputs) that match the user's emotions. Specifically, the AI ​​analyzes the data and creates suggestions for adjusting the template's colors and fonts.

[0397] Step 5:

[0398] The server sends the analysis results to the terminal. It receives design proposals as input and outputs them to the terminal. Specifically, the server sends the created design change proposals back to the terminal via secure communication.

[0399] Step 6:

[0400] The terminal presents design suggestions received from the server to the user. It receives server suggestions as input and integrates them into the user interface. The user reviews the visually adjusted design and makes final edits (output). Specifically, the terminal reflects the new design on the screen in real time and provides the user with options.

[0401] Step 7:

[0402] The user completes the final edits and saves or sends the electronic document. The system receives the edited document as input and saves it within the system or outputs it to an external information management system. Specifically, the user presses a confirmation button to complete the document and, if necessary, shares it with others via the internet or uploads it to a CMS.

[0403] (Application Example 2)

[0404] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0405] Traditionally, a challenge in the creation and management of electronic records has been the insufficient dynamic content adjustment based on the user's emotional state. Furthermore, while providing information tailored to individual emotions is crucial for improving the user experience, achieving this is often difficult.

[0406] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0407] In this invention, the server includes means for acquiring and reflecting information from a digital recording medium, means for accumulating multiple information formats and designs and enabling rapid adjustment, and means for analyzing the user's emotional state and dynamically adjusting the content delivered based on that analysis. This enables the delivery of personalized content that responds to the user's emotions.

[0408] A "digital recording medium" is a medium for electronically storing, managing, and transmitting information, and includes databases and cloud storage.

[0409] "Information acquisition" refers to the act of obtaining requested information from a digital recording medium and providing it in a format that meets the user's requirements.

[0410] An "information format" is a format that defines the structure and layout of data, and includes templates that can be customized for various purposes.

[0411] "Design" refers to the structure and style used to visually represent information and data, and is used to present them in a way that is easily recognizable to users.

[0412] "Rapid adjustment" refers to the ability to change and adapt information formats and designs in a short amount of time, enabling the provision of optimal information tailored to the user's needs and circumstances.

[0413] "User's emotional state" refers to the emotional state and psychological condition expressed by the user, and is analyzed using facial recognition and voice analysis.

[0414] "Dynamic adjustment" refers to flexibly changing the content and method of delivery of information in accordance with real-time changing situations and conditions.

[0415] "Personalized content delivery" is a delivery method that selects and provides the most relevant information based on the user's emotional state and individual preferences.

[0416] In the system that implements this application example, the server acts as a central control unit, acquiring necessary information from digital storage media and processing it to analyze the user's emotional state. The server uses an emotion recognition API (e.g., emotion judgment software) to receive and analyze the user's emotional data in real time. Subsequently, based on the analysis results, it selects the optimal content and sends it to the terminal. At this time, the design is quickly adjusted from template information on the digital storage media (e.g., cloud storage).

[0417] The device interacts directly with the user through its user interface, displaying dynamic content provided by the server. The device incorporates facial and voice recognition capabilities, periodically sending this data to the server. This allows the server to constantly maintain an up-to-date understanding of the user's emotional state and continuously optimize the content.

[0418] Users access content on a daily basis using their devices. The system provides information in a way that is sensitive to the user's mood, offering content with a relaxing design when the user is feeling stressed, and analytical content when the user is feeling excited and highly focused.

[0419] For example, when a user opens a news app, if it's determined that they are highly focused, it will display detailed economic analysis articles. When they want to relax, it will display articles about travel or hobbies.

[0420] Examples of prompt messages include, "Get the user's emotional state and recommend travel-related articles if they are calm," and "Play relaxation music if the user is judged to be highly stressed."

[0421] In this way, the embodiment for carrying out the invention enables personalized content delivery based on user emotions, contributing to an improved experience.

[0422] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0423] Step 1:

[0424] The server receives user emotion data (e.g., facial expressions, voice tone) from the terminal. The input data is acquired in real time using facial recognition technology and voice analysis software. This data is analyzed for emotional state via an emotion recognition API. The output is a numerical value or category indicating the user's emotional state.

[0425] Step 2:

[0426] The server selects appropriate information formats and content from digital storage media based on the analysis of the user's emotional state. The input is emotional data, and the output is corresponding content IDs and template information. A generative AI model is used to recommend content optimized for the user's emotions.

[0427] Step 3:

[0428] The terminal receives content information sent from the server and displays it through the user interface. Input is selected content or template data, and output is a visually adjusted content screen. The terminal renders the visual elements, taking into account screen resolution and interaction.

[0429] Step 4:

[0430] The user provides interaction and feedback on the displayed content. Input is the content display on the device, and output is new data resulting from the user's actions (e.g., scrolling, clicking). User action information is sent from the device to the server and used to select the next content.

[0431] Step 5:

[0432] The server accumulates user interaction data and analyzes it to improve future content delivery. The input is user interaction data, and the output is updated information for the predictive model used for future content adjustments. It generates prompt messages, enabling more accurate content recommendations in subsequent processing.

[0433] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0434] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0435] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0436] [Third Embodiment]

[0437] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0438] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0439] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0440] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0441] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0442] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0443] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0444] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0445] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0446] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0447] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0448] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0449] This invention aims to enable the efficient creation and management of electronic documents in business, and its specific embodiments are described below. This system provides an environment in which servers, terminals, and users interact to create and manage electronic documents quickly and securely.

[0450] System Program and Processing Overview

[0451] 1. Server Role

[0452] The server stores multiple information formats and designs, providing them based on user requests. The server connects to a digital database and retrieves the information users need in real time. This data is immediately reflected in the specified template, keeping it up-to-date.

[0453] 2. The role of the terminal

[0454] The terminal acts as the user interface, sending user requests to the server. It assists users in selecting and customizing templates, and appropriately displays review results and revision suggestions after document generation.

[0455] 3. User actions

[0456] Users log in via their device and select a template suitable for their work. They then customize the template, which is saved to the server for future use. Users review the generated electronic document and make necessary revisions based on suggestions from the AI ​​review process.

[0457] Specific example

[0458] For example, when creating a meeting report, the user selects a meeting report format on their device. Then, data related to the month's meetings is retrieved from the server in real time and reflected in the template. The user reviews the report, and if any deficiencies are pointed out by the AI, they make corrections based on the AI's suggestions. Finally, the electronic document is automatically uploaded to the content management system via the server and immediately shared with the relevant departments.

[0459] In this way, the system consistently supports everything from template selection to real-time data reflection and AI-powered review, helping users efficiently create high-quality documents.

[0460] The following describes the processing flow.

[0461] Step 1:

[0462] The user logs into the system using their device. Here, user authentication takes place, and a list of templates corresponding to the user's permission level is displayed.

[0463] Step 2:

[0464] The user selects their preferred template from the displayed template list. The device then sends this selection information to the server.

[0465] Step 3:

[0466] The server prepares a template based on the user's selection and sends back the design and customization options associated with that template to the device.

[0467] Step 4:

[0468] The user customizes the template on their device. This includes selecting colors, logos, and fonts, and the customized results are sent to the server.

[0469] Step 5:

[0470] The server saves the customizations and then extracts relevant data from a digital database in real time based on those customizations.

[0471] Step 6:

[0472] The extracted data is reflected in the template via the server, and an initial electronic document is generated. This electronic document is then sent to the terminal for review before finalization.

[0473] Step 7:

[0474] The device displays electronic documents to the user, and an automated review is performed by AI. The AI ​​analyzes the content of the document and provides suggestions for improvement.

[0475] Step 8:

[0476] The user reviews the AI's suggestions and makes any necessary corrections via their device. Once the corrections are complete, the user orders the creation of the final version.

[0477] Step 9:

[0478] The server generates the final electronic document, and its security is guaranteed using blockchain technology.

[0479] Step 10:

[0480] The final version is automatically uploaded to the CMS, and users with access rights are notified. This allows for sharing with other members.

[0481] (Example 1)

[0482] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0483] Conventional electronic document creation systems lacked the means to efficiently and securely perform the entire process of data acquisition, template selection and customization, and evaluation and revision of created documents. In particular, there were challenges regarding the reliability of technologies that ensure real-time updates of electronic documents and data integrity and security. Furthermore, the insufficient functionality to automatically evaluate document content and suggest revisions using machine learning resulted in a heavy burden on users. Therefore, the present invention aims to solve these problems.

[0484] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0485] In this invention, the server includes components for retrieving and reflecting information from data storage, components for storing multiple data formats and designs and enabling rapid customization, and components for automatically transmitting generated electronic documents to an information management system. This enables real-time data retrieval and secure and efficient creation and management of electronic documents.

[0486] "Data storage" refers to a place for storing and managing information, maintaining its content in a digital format.

[0487] "Information retrieval" refers to the process of searching for necessary information from data storage and retrieving it in a usable format.

[0488] A "data format" is a standard for arranging information in a specific structure or style, and is used when sharing information between different systems and applications.

[0489] "Design" refers to the planning and arrangement style for visually arranging and representing information, and plays a role in making information easier for users to understand.

[0490] An "information management system" refers to a system designed to efficiently store, organize, search, and share information.

[0491] "Distributed ledger technology" refers to technologies like blockchain that securely record transactions and data on a decentralized network and guarantee their integrity.

[0492] Machine learning is a branch of artificial intelligence that enables computer systems to automatically learn from experience and data and improve.

[0493] A "user interface" is the interface that users use to interact directly with a system, and it greatly influences operability and ease of use.

[0494] A "template" refers to a framework that provides standardized forms or formats suited to a specific purpose, making it easier for users to efficiently input information.

[0495] To implement this invention, a system is provided in which a server, terminal, and user cooperate to efficiently and securely create and manage electronic documents.

[0496] The server interacts with data storage to retrieve necessary information. This allows the data required by the user to be reflected in the template in real time, ensuring it is always up-to-date. The server also has the capability to store multiple data formats and designs, providing them based on user requests. Utilizing machine learning technology, the server analyzes the document content and suggests revisions. This enables users to efficiently create high-quality content. The created electronic documents are then automatically sent to the information management system for secure storage and sharing. Distributed ledger technology is used to ensure data integrity and security.

[0497] The terminal provides an interface for users to interact with the system. Users log in using the terminal and select a template suitable for their work purpose. The terminal sends user actions to the server, supporting the data retrieval and document generation processes. It also presents the user with review results using a generative AI model, visually assisting with necessary corrections.

[0498] Users select a template for the electronic document they want to create via the terminal interface and enter or edit data. They then review the document through machine learning-based evaluation results and make revisions as needed to complete a high-quality document. The document reviewed by the user is immediately shared with relevant departments via an automatic synchronization function.

[0499] As a concrete example, one could use a prompt such as, "Create meeting minutes for this month and apply AI review." In this way, this invention provides a system for the efficient creation and management of electronic documents.

[0500] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0501] Step 1:

[0502] The user logs into the system using a terminal. The terminal receives input for user authentication and sends it to the server. The server compares the authentication information with records in data storage to verify that the user has access rights. If successful, it sends a success message to the terminal and allows it to proceed to the next step.

[0503] Step 2:

[0504] The user selects a suitable template via the terminal. The terminal receives the user's selection as input and sends it to the server. The server retrieves the corresponding template information from its data storage and returns that information to the terminal. The terminal displays the retrieved template to the user and prepares it for customization.

[0505] Step 3:

[0506] The server starts data processing for document generation using the template and associated data. First, it retrieves the necessary information from data storage. This includes meeting information and business data. The server converts the retrieved data into the appropriate data format and reflects it in the template. This process generates a template containing the latest information, which is then sent to the terminal.

[0507] Step 4:

[0508] The user reviews the document generated through the terminal and makes any necessary corrections. The terminal then sends the user's corrections back to the server as input. The server reflects the corrections in data storage and checks for consistency. This ensures that the user can always finalize documents based on the latest information.

[0509] Step 5:

[0510] The server analyzes the document using a generative AI model and evaluates the quality of its content. Based on the input document, the AI ​​model checks for typos and grammatical errors, optimizes syntax, and generates revision suggestions. These suggestions are then fed back to the user through the terminal.

[0511] Step 6:

[0512] The user considers the revision suggestions from the AI ​​model and finalizes the document. The terminal sends the finalized information to the server, which stores it in the information management system and automatically shares it with the relevant departments. This ensures secure storage of content and smooth information sharing.

[0513] (Application Example 1)

[0514] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0515] In industrial product manufacturing, there is a need to efficiently record assembly processes and quality control, and to detect and correct defects in real time. However, conventional systems rely on manual data acquisition and recording, leading to issues such as reduced accuracy and wasted time. Furthermore, it is difficult to efficiently manage and share the generated data while guaranteeing the security and integrity of electronic documents.

[0516] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0517] In this invention, the server includes a device for acquiring and reflecting information from a digital data storage device, a device for recording multiple data formats and designs to enable rapid optimization, and a device for detecting the assembly process using image processing technology, processing the data in real time, and reflecting it in an electronic document. This enables improved accuracy of data recording and rapid detection of defects in the manufacturing site.

[0518] A "digital data storage device" is a device for electronically recording and storing information, and plays a role in efficiently managing various forms of data.

[0519] "Information format" refers to a framework or format for structuring data, and serves as a foundation for facilitating the organization and distribution of information.

[0520] "Design" refers to a plan or specification created to achieve a specific purpose, which defines in detail the structure and function of a system or product.

[0521] "Real-time" refers to a situation where an event is processed immediately upon its occurrence, resulting in near-instantaneous results.

[0522] "Image processing technology" refers to the techniques for manipulating and analyzing digital image data, and is a means of extracting, transforming, and recognizing visual information.

[0523] An "electronic document" is a document created and stored in digital format, and is an information medium that can be viewed and edited on a computer or digital device.

[0524] An "information management platform" is a foundational system for the integrated management and distribution of information, enabling efficient storage, access, and sharing of data.

[0525] "Machine learning technology" is a collection of algorithms and methods aimed at enabling computer systems to automatically improve their performance through experience, and possesses the ability to extract patterns and knowledge from data.

[0526] "Distributed ledger technology" is a digital ledger used to prevent data tampering and is a technological foundation for securely sharing data among participants across multiple networks.

[0527] The system for implementing this invention operates based on hardware and software such as a digital data storage device, an information management platform, image processing technology, and machine learning technology.

[0528] The server acquires various types of data from digital data storage devices in real time and reflects them in the information management platform. This enables the creation of electronic documents based on the latest information at all times. Furthermore, it incorporates machine learning technology to automatically classify and assign quality to the acquired data, achieving efficient management.

[0529] Meanwhile, the terminal is responsible for inputting and processing information, and for customizing the generated electronic documents. Users can easily review documents created using this terminal and receive feedback on the generated data through image processing technology. This improves the quality and accuracy of the documents.

[0530] For example, consider a scenario in a factory production line where defects are detected during the product assembly process. In this case, a generative AI model can analyze the assembly video and automatically identify the problems, enabling a rapid response.

[0531] Examples of prompt statements to input to a generative AI model include the following:

[0532] "Create prompts for a system that records the product assembly process in a factory and uses AI to detect defects, identifying areas that need correction in real time."

[0533] This system configuration enables rapid acquisition and analysis of information, leading to increased efficiency and improved quality in the manufacturing of industrial products.

[0534] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0535] Step 1:

[0536] The server retrieves image data of product assembly from a digital data storage device. When retrieving this image data, the server accesses a database via the network to collect the latest images related to a specific manufacturing line. The input is images of the product, and the output is a dataset for image processing.

[0537] Step 2:

[0538] The acquired image data is analyzed using image processing technology installed on the server. Specifically, libraries such as OpenCV are used to automatically detect abnormal areas and specific anomalies within the image. The input is the image data before processing, and the output is the analysis results that point out the anomalies or the marked image.

[0539] Step 3:

[0540] The server inputs the analysis results from image processing into a generative AI model based on machine learning technology to obtain suggestions for further improvement and correction. This process uses a learning model generated based on multiple historical data sets to identify potential problems. The input is the results after image processing, and the output is specific correction suggestions.

[0541] Step 4:

[0542] The terminal displays analysis results and suggested corrections sent from the server to the user. The user uses this information to identify actual problems on the production line and decide how to address them. The input is the analysis results from the server, and the output is information formatted in a way that the user can understand.

[0543] Step 5:

[0544] The user modifies the manufacturing process based on the correction suggestions displayed on the terminal. In this step, the user directly changes the settings of production machinery or revises personnel allocation. The output is the state of the manufacturing line after the problems have been corrected.

[0545] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0546] This invention relates to a system that incorporates an emotion engine for creating and managing electronic documents, which recognizes user emotions and dynamically adjusts the design and content of those emotions based on those emotions. This system operates collaboratively between a server, a terminal, and a user, and aims to improve the user experience by utilizing emotion recognition technology.

[0547] System Program and Processing Overview

[0548] 1. Server Role

[0549] The server interacts with a digital database to retrieve the latest information in real time and reflect it in the template. It also incorporates an emotion engine to assess the user's emotional state, collecting and analyzing emotional data displayed by the user while creating electronic documents. This allows the server to make adaptive design changes based on the emotional data.

[0550] 2. The role of the terminal

[0551] The device provides a user interface and sends emotional data to the server in real time as the user selects and customizes templates. The emotion engine analyzes the user's emotions, receives feedback to adjust templates and content, and presents it to the user visually.

[0552] 3. User actions

[0553] Users select templates and customize their content via their devices. The system analyzes the user's emotions in real time during creation, and emotional data is managed to protect privacy. For example, if a user is stressed, the system automatically adjusts the template to a more relaxing design.

[0554] Specific example

[0555] For example, when a user creates a marketing report, they select an appropriate template on their device. Based on the user's facial expressions and voice tone, the emotion engine built into the server determines that the user is feeling anxious. In that case, the server automatically selects fonts and color schemes that do not emphasize text and applies a calm layout. After generation, this report undergoes AI review and user confirmation before the final version is uploaded to the CMS.

[0556] In this way, the system assists in document creation while taking user emotions into consideration, providing a more user-friendly and productive work environment.

[0557] The following describes the processing flow.

[0558] Step 1:

[0559] The user logs into the device and begins accessing the system. The device sends the user's authentication information to the server for permission verification.

[0560] Step 2:

[0561] The server provides the terminal with a list of available templates and design options based on the user's permissions. The user then selects the appropriate template.

[0562] Step 3:

[0563] The user selects a template, and the device sends that information to the server. Based on this, the emotion engine prepares to begin analyzing the user's emotions.

[0564] Step 4:

[0565] While the user customizes templates through the device, the device continuously monitors the user's emotional state using its camera and microphone.

[0566] Step 5:

[0567] The device sends the collected emotional data to the server. An emotion engine built into the server analyzes this data to identify the user's current emotions.

[0568] Step 6:

[0569] The server dynamically adjusts the template design and structure based on analyzed sentiment data. For example, if the user is feeling stressed, it will change to a calmer color scheme and font.

[0570] Step 7:

[0571] The adjusted template is generated by the server and sent to the terminal. The terminal then presents the user with the visual changes and asks for confirmation.

[0572] Step 8:

[0573] The user approves the adjustments and completes the document creation. The terminal then sends a request for final confirmation to the server.

[0574] Step 9:

[0575] The server generates the final version of the document, which is then reviewed by AI, and its security is guaranteed using blockchain technology.

[0576] Step 10:

[0577] Secure electronic documents are automatically uploaded to the CMS by the server, and sharing notifications are sent to the relevant users.

[0578] (Example 2)

[0579] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0580] In today's information society, the creation and management of electronic documents are becoming increasingly important. However, traditional methods cannot dynamically adjust document design to respond to user emotions, making it difficult to improve the user experience. Furthermore, there is a need to reflect the content of electronic documents in a timely and accurate manner and to guarantee data integrity.

[0581] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0582] In this invention, the server includes means for acquiring and reflecting information from an electronic database, means for sensing and analyzing the user's emotional state, and means for dynamically adjusting the document design and content based on the analyzed emotional results. This enables the generation of optimal electronic documents tailored to the user's emotions and secure data management.

[0583] An "electronic database" is a system that stores and manages information in a structured, digital format.

[0584] "Information format" refers to the structure and type of data or information that is displayed.

[0585] An "information management system" is a system for organizing, storing, retrieving, and sharing information and data.

[0586] "Distributed ledger technology" is a distributed database technology in which multiple nodes cooperate to manage data in order to guarantee its integrity and security.

[0587] "Machine learning technology" is a technology that gives computers the ability to learn from data and find patterns.

[0588] "User emotional state" refers to a situation that demonstrates a user's psychological or emotional response.

[0589] "Dynamic adjustment" means making immediate changes in response to the situation.

[0590] This invention is a system for dynamically adjusting the design and content of electronic documents, taking into account the user's emotional state. The system mainly consists of collaboration between a server, a terminal, and the user.

[0591] The server functions as the central hub for managing information, retrieving necessary information from electronic databases and incorporating it into documents. The hardware used here is standard server equipment, and the software incorporates protocols that support distributed ledger technology. The server also features an emotion engine that utilizes machine learning techniques, analyzing user emotion data using a generative AI model. This model uses the prompt "Please propose a design that will help the user relax" to provide design suggestions based on the analysis results.

[0592] The terminal acts as the interface with the user, sensing the user's facial expressions and voice tone in real time through sensors and microphones. This emotional data is processed through appropriate software (e.g., OpenCV for face recognition, Praat for voice analysis) and sent to the server. The terminal also visually presents feedback to the user based on the analysis results sent from the server, helping the user customize documents.

[0593] This system allows users to select templates tailored to their purpose and create documents that align with their emotions. For example, when creating a marketing report, if a user feels stressed, the system automatically suggests calming color tones. This enables users to create documents more efficiently and stress-free.

[0594] This invention aims to significantly improve the user experience and enable adaptive and interactive document management.

[0595] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0596] Step 1:

[0597] The user begins creating an electronic document using the terminal. When the user selects a template, the terminal receives this selection information as input and applies it to the user interface. At this time, the displayed content (output) is configured based on the template selected by the user. Specifically, the terminal displays a list of templates and sets the template clicked by the user as the currently selected template.

[0598] Step 2:

[0599] The device monitors the user's facial expressions and voice tone in real time. It acquires emotional data from sensors and a microphone as input. This data is processed by facial recognition software (e.g., OpenCV) and voice analysis software (e.g., Praat) to estimate the user's emotional state (output). Specifically, the device continuously acquires information from the camera and microphone and prepares to send it to the emotion engine.

[0600] Step 3:

[0601] The device sends the acquired emotion data to the server. The input data is the emotion estimation result, which is encrypted and sent to the server. The transmitted data is used for analysis on the server. Specifically, the device sends data to the server using a secure communication protocol.

[0602] Step 4:

[0603] The server uses an emotion engine to analyze the received emotional data. Using emotional data as input, it employs a generative AI model to perform analysis according to the prompt "Please propose a design that will help the user relax." This generates design proposals (outputs) that match the user's emotions. Specifically, the AI ​​analyzes the data and creates suggestions for adjusting the template's colors and fonts.

[0604] Step 5:

[0605] The server sends the analysis results to the terminal. It receives design proposals as input and outputs them to the terminal. Specifically, the server sends the created design change proposals back to the terminal via secure communication.

[0606] Step 6:

[0607] The terminal presents design suggestions received from the server to the user. It receives server suggestions as input and integrates them into the user interface. The user reviews the visually adjusted design and makes final edits (output). Specifically, the terminal reflects the new design on the screen in real time and provides the user with options.

[0608] Step 7:

[0609] The user completes the final edits and saves or sends the electronic document. The system receives the edited document as input and saves it within the system or outputs it to an external information management system. Specifically, the user presses a confirmation button to complete the document and, if necessary, shares it with others via the internet or uploads it to a CMS.

[0610] (Application Example 2)

[0611] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0612] Traditionally, a challenge in the creation and management of electronic records has been the insufficient dynamic content adjustment based on the user's emotional state. Furthermore, while providing information tailored to individual emotions is crucial for improving the user experience, achieving this is often difficult.

[0613] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0614] In this invention, the server includes means for acquiring and reflecting information from a digital recording medium, means for accumulating multiple information formats and designs and enabling rapid adjustment, and means for analyzing the user's emotional state and dynamically adjusting the content delivered based on that analysis. This enables the delivery of personalized content that responds to the user's emotions.

[0615] A "digital recording medium" is a medium for electronically storing, managing, and transmitting information, and includes databases and cloud storage.

[0616] "Information acquisition" refers to the act of obtaining requested information from a digital recording medium and providing it in a format that meets the user's requirements.

[0617] An "information format" is a format that defines the structure and layout of data, and includes templates that can be customized for various purposes.

[0618] "Design" refers to the structure and style used to visually represent information and data, and is used to present them in a way that is easily recognizable to users.

[0619] "Rapid adjustment" refers to the ability to change and adapt information formats and designs in a short amount of time, enabling the provision of optimal information tailored to the user's needs and circumstances.

[0620] "User's emotional state" refers to the emotional state and psychological condition expressed by the user, and is analyzed using facial recognition and voice analysis.

[0621] "Dynamic adjustment" refers to flexibly changing the content and method of delivery of information in accordance with real-time changing situations and conditions.

[0622] "Personalized content delivery" is a delivery method that selects and provides the most relevant information based on the user's emotional state and individual preferences.

[0623] In the system that implements this application example, the server acts as a central control unit, acquiring necessary information from digital storage media and processing it to analyze the user's emotional state. The server uses an emotion recognition API (e.g., emotion judgment software) to receive and analyze the user's emotional data in real time. Subsequently, based on the analysis results, it selects the optimal content and sends it to the terminal. At this time, the design is quickly adjusted from template information on the digital storage media (e.g., cloud storage).

[0624] The device interacts directly with the user through its user interface, displaying dynamic content provided by the server. The device incorporates facial and voice recognition capabilities, periodically sending this data to the server. This allows the server to constantly maintain an up-to-date understanding of the user's emotional state and continuously optimize the content.

[0625] Users access content on a daily basis using their devices. The system provides information in a way that is sensitive to the user's mood, offering content with a relaxing design when the user is feeling stressed, and analytical content when the user is feeling excited and highly focused.

[0626] For example, when a user opens a news app, if it's determined that they are highly focused, it will display detailed economic analysis articles. When they want to relax, it will display articles about travel or hobbies.

[0627] Examples of prompt messages include, "Get the user's emotional state and recommend travel-related articles if they are calm," and "Play relaxation music if the user is judged to be highly stressed."

[0628] In this way, the embodiment for carrying out the invention enables personalized content delivery based on user emotions, contributing to an improved experience.

[0629] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0630] Step 1:

[0631] The server receives user emotion data (e.g., facial expressions, voice tone) from the terminal. The input data is acquired in real time using facial recognition technology and voice analysis software. This data is analyzed for emotional state via an emotion recognition API. The output is a numerical value or category indicating the user's emotional state.

[0632] Step 2:

[0633] The server selects appropriate information formats and content from digital storage media based on the analysis of the user's emotional state. The input is emotional data, and the output is corresponding content IDs and template information. A generative AI model is used to recommend content optimized for the user's emotions.

[0634] Step 3:

[0635] The terminal receives content information sent from the server and displays it through the user interface. Input is selected content or template data, and output is a visually adjusted content screen. The terminal renders the visual elements, taking into account screen resolution and interaction.

[0636] Step 4:

[0637] The user provides interaction and feedback on the displayed content. Input is the content display on the device, and output is new data resulting from the user's actions (e.g., scrolling, clicking). User action information is sent from the device to the server and used to select the next content.

[0638] Step 5:

[0639] The server accumulates user interaction data and analyzes it to improve future content delivery. The input is user interaction data, and the output is updated information for the predictive model used for future content adjustments. It generates prompt messages, enabling more accurate content recommendations in subsequent processing.

[0640] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0641] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0642] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0643] [Fourth Embodiment]

[0644] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0645] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0646] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0647] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0648] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0649] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0650] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0651] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0652] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0653] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0654] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0655] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0656] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0657] This invention aims to enable the efficient creation and management of electronic documents in business, and its specific embodiments are described below. This system provides an environment in which servers, terminals, and users interact to create and manage electronic documents quickly and securely.

[0658] System Program and Processing Overview

[0659] 1. Server Role

[0660] The server stores multiple information formats and designs, providing them based on user requests. The server connects to a digital database and retrieves the information users need in real time. This data is immediately reflected in the specified template, keeping it up-to-date.

[0661] 2. The role of the terminal

[0662] The terminal acts as the user interface, sending user requests to the server. It assists users in selecting and customizing templates, and appropriately displays review results and revision suggestions after document generation.

[0663] 3. User actions

[0664] Users log in via their device and select a template suitable for their work. They then customize the template, which is saved to the server for future use. Users review the generated electronic document and make necessary revisions based on suggestions from the AI ​​review process.

[0665] Specific example

[0666] For example, when creating a meeting report, the user selects a meeting report format on their device. Then, data related to the month's meetings is retrieved from the server in real time and reflected in the template. The user reviews the report, and if any deficiencies are pointed out by the AI, they make corrections based on the AI's suggestions. Finally, the electronic document is automatically uploaded to the content management system via the server and immediately shared with the relevant departments.

[0667] In this way, the system consistently supports everything from template selection to real-time data reflection and AI-powered review, helping users efficiently create high-quality documents.

[0668] The following describes the processing flow.

[0669] Step 1:

[0670] The user logs into the system using their device. Here, user authentication takes place, and a list of templates corresponding to the user's permission level is displayed.

[0671] Step 2:

[0672] The user selects their preferred template from the displayed template list. The device then sends this selection information to the server.

[0673] Step 3:

[0674] The server prepares a template based on the user's selection and sends back the design and customization options associated with that template to the device.

[0675] Step 4:

[0676] The user customizes the template on their device. This includes selecting colors, logos, and fonts, and the customized results are sent to the server.

[0677] Step 5:

[0678] The server saves the customizations and then extracts relevant data from a digital database in real time based on those customizations.

[0679] Step 6:

[0680] The extracted data is reflected in the template via the server, and an initial electronic document is generated. This electronic document is then sent to the terminal for review before finalization.

[0681] Step 7:

[0682] The device displays electronic documents to the user, and an automated review is performed by AI. The AI ​​analyzes the content of the document and provides suggestions for improvement.

[0683] Step 8:

[0684] The user reviews the AI's suggestions and makes any necessary corrections via their device. Once the corrections are complete, the user orders the creation of the final version.

[0685] Step 9:

[0686] The server generates the final electronic document, and its security is guaranteed using blockchain technology.

[0687] Step 10:

[0688] The final version is automatically uploaded to the CMS, and users with access rights are notified. This allows for sharing with other members.

[0689] (Example 1)

[0690] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0691] Conventional electronic document creation systems lacked the means to efficiently and securely perform the entire process of data acquisition, template selection and customization, and evaluation and revision of created documents. In particular, there were challenges regarding the reliability of technologies that ensure real-time updates of electronic documents and data integrity and security. Furthermore, the insufficient functionality to automatically evaluate document content and suggest revisions using machine learning resulted in a heavy burden on users. Therefore, the present invention aims to solve these problems.

[0692] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0693] In this invention, the server includes components for retrieving and reflecting information from data storage, components for storing multiple data formats and designs and enabling rapid customization, and components for automatically transmitting generated electronic documents to an information management system. This enables real-time data retrieval and secure and efficient creation and management of electronic documents.

[0694] "Data storage" refers to a place for storing and managing information, maintaining its content in a digital format.

[0695] "Information retrieval" refers to the process of searching for necessary information from data storage and retrieving it in a usable format.

[0696] A "data format" is a standard for arranging information in a specific structure or style, and is used when sharing information between different systems and applications.

[0697] "Design" refers to the planning and arrangement style for visually arranging and representing information, and plays a role in making information easier for users to understand.

[0698] An "information management system" refers to a system designed to efficiently store, organize, search, and share information.

[0699] "Distributed ledger technology" refers to technologies like blockchain that securely record transactions and data on a decentralized network and guarantee their integrity.

[0700] Machine learning is a branch of artificial intelligence that enables computer systems to automatically learn from experience and data and improve.

[0701] A "user interface" is the interface that users use to interact directly with a system, and it greatly influences operability and ease of use.

[0702] A "template" refers to a framework that provides standardized forms or formats suited to a specific purpose, making it easier for users to efficiently input information.

[0703] To implement this invention, a system is provided in which a server, terminal, and user cooperate to efficiently and securely create and manage electronic documents.

[0704] The server interacts with data storage to retrieve necessary information. This allows the data required by the user to be reflected in the template in real time, ensuring it is always up-to-date. The server also has the capability to store multiple data formats and designs, providing them based on user requests. Utilizing machine learning technology, the server analyzes the document content and suggests revisions. This enables users to efficiently create high-quality content. The created electronic documents are then automatically sent to the information management system for secure storage and sharing. Distributed ledger technology is used to ensure data integrity and security.

[0705] The terminal provides an interface for users to interact with the system. Users log in using the terminal and select a template suitable for their work purpose. The terminal sends user actions to the server, supporting the data retrieval and document generation processes. It also presents the user with review results using a generative AI model, visually assisting with necessary corrections.

[0706] Users select a template for the electronic document they want to create via the terminal interface and enter or edit data. They then review the document through machine learning-based evaluation results and make revisions as needed to complete a high-quality document. The document reviewed by the user is immediately shared with relevant departments via an automatic synchronization function.

[0707] As a concrete example, one could use a prompt such as, "Create meeting minutes for this month and apply AI review." In this way, this invention provides a system for the efficient creation and management of electronic documents.

[0708] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0709] Step 1:

[0710] The user logs into the system using a terminal. The terminal receives input for user authentication and sends it to the server. The server compares the authentication information with records in data storage to verify that the user has access rights. If successful, it sends a success message to the terminal and allows it to proceed to the next step.

[0711] Step 2:

[0712] The user selects a suitable template via the terminal. The terminal receives the user's selection as input and sends it to the server. The server retrieves the corresponding template information from its data storage and returns that information to the terminal. The terminal displays the retrieved template to the user and prepares it for customization.

[0713] Step 3:

[0714] The server starts data processing for document generation using the template and associated data. First, it retrieves the necessary information from data storage. This includes meeting information and business data. The server converts the retrieved data into the appropriate data format and reflects it in the template. This process generates a template containing the latest information, which is then sent to the terminal.

[0715] Step 4:

[0716] The user reviews the document generated through the terminal and makes any necessary corrections. The terminal then sends the user's corrections back to the server as input. The server reflects the corrections in data storage and checks for consistency. This ensures that the user can always finalize documents based on the latest information.

[0717] Step 5:

[0718] The server analyzes the document using a generative AI model and evaluates the quality of its content. Based on the input document, the AI ​​model checks for typos and grammatical errors, optimizes syntax, and generates revision suggestions. These suggestions are then fed back to the user through the terminal.

[0719] Step 6:

[0720] The user considers the revision suggestions from the AI ​​model and finalizes the document. The terminal sends the finalized information to the server, which stores it in the information management system and automatically shares it with the relevant departments. This ensures secure storage of content and smooth information sharing.

[0721] (Application Example 1)

[0722] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0723] In industrial product manufacturing, there is a need to efficiently record assembly processes and quality control, and to detect and correct defects in real time. However, conventional systems rely on manual data acquisition and recording, leading to issues such as reduced accuracy and wasted time. Furthermore, it is difficult to efficiently manage and share the generated data while guaranteeing the security and integrity of electronic documents.

[0724] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0725] In this invention, the server includes a device for acquiring and reflecting information from a digital data storage device, a device for recording multiple data formats and designs to enable rapid optimization, and a device for detecting the assembly process using image processing technology, processing the data in real time, and reflecting it in an electronic document. This enables improved accuracy of data recording and rapid detection of defects in the manufacturing site.

[0726] A "digital data storage device" is a device for electronically recording and storing information, and plays a role in efficiently managing various forms of data.

[0727] "Information format" refers to a framework or format for structuring data, and serves as a foundation for facilitating the organization and distribution of information.

[0728] "Design" refers to a plan or specification created to achieve a specific purpose, which defines in detail the structure and function of a system or product.

[0729] "Real-time" refers to a situation where an event is processed immediately upon its occurrence, resulting in near-instantaneous results.

[0730] "Image processing technology" refers to the techniques for manipulating and analyzing digital image data, and is a means of extracting, transforming, and recognizing visual information.

[0731] An "electronic document" is a document created and stored in digital format, and is an information medium that can be viewed and edited on a computer or digital device.

[0732] An "information management platform" is a foundational system for the integrated management and distribution of information, enabling efficient storage, access, and sharing of data.

[0733] "Machine learning technology" is a collection of algorithms and methods aimed at enabling computer systems to automatically improve their performance through experience, and possesses the ability to extract patterns and knowledge from data.

[0734] "Distributed ledger technology" is a digital ledger used to prevent data tampering and is a technological foundation for securely sharing data among participants across multiple networks.

[0735] The system for implementing this invention operates based on hardware and software such as a digital data storage device, an information management platform, image processing technology, and machine learning technology.

[0736] The server acquires various types of data from digital data storage devices in real time and reflects them in the information management platform. This enables the creation of electronic documents based on the latest information at all times. Furthermore, it incorporates machine learning technology to automatically classify and assign quality to the acquired data, achieving efficient management.

[0737] Meanwhile, the terminal is responsible for inputting and processing information, and for customizing the generated electronic documents. Users can easily review documents created using this terminal and receive feedback on the generated data through image processing technology. This improves the quality and accuracy of the documents.

[0738] For example, consider a scenario in a factory production line where defects are detected during the product assembly process. In this case, a generative AI model can analyze the assembly video and automatically identify the problems, enabling a rapid response.

[0739] Examples of prompt statements to input to a generative AI model include the following:

[0740] "Create prompts for a system that records the product assembly process in a factory and uses AI to detect defects, identifying areas that need correction in real time."

[0741] This system configuration enables rapid acquisition and analysis of information, leading to increased efficiency and improved quality in the manufacturing of industrial products.

[0742] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0743] Step 1:

[0744] The server retrieves image data of product assembly from a digital data storage device. When retrieving this image data, the server accesses a database via the network to collect the latest images related to a specific manufacturing line. The input is images of the product, and the output is a dataset for image processing.

[0745] Step 2:

[0746] The acquired image data is analyzed using image processing technology installed on the server. Specifically, libraries such as OpenCV are used to automatically detect abnormal areas and specific anomalies within the image. The input is the image data before processing, and the output is the analysis results that point out the anomalies or the marked image.

[0747] Step 3:

[0748] The server inputs the analysis results from image processing into a generative AI model based on machine learning technology to obtain suggestions for further improvement and correction. This process uses a learning model generated based on multiple historical data sets to identify potential problems. The input is the results after image processing, and the output is specific correction suggestions.

[0749] Step 4:

[0750] The terminal displays analysis results and suggested corrections sent from the server to the user. The user uses this information to identify actual problems on the production line and decide how to address them. The input is the analysis results from the server, and the output is information formatted in a way that the user can understand.

[0751] Step 5:

[0752] The user modifies the manufacturing process based on the correction suggestions displayed on the terminal. In this step, the user directly changes the settings of production machinery or revises personnel allocation. The output is the state of the manufacturing line after the problems have been corrected.

[0753] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0754] This invention relates to a system that incorporates an emotion engine for creating and managing electronic documents, which recognizes user emotions and dynamically adjusts the design and content of those emotions based on those emotions. This system operates collaboratively between a server, a terminal, and a user, and aims to improve the user experience by utilizing emotion recognition technology.

[0755] System Program and Processing Overview

[0756] 1. Server Role

[0757] The server interacts with a digital database to retrieve the latest information in real time and reflect it in the template. It also incorporates an emotion engine to assess the user's emotional state, collecting and analyzing emotional data displayed by the user while creating electronic documents. This allows the server to make adaptive design changes based on the emotional data.

[0758] 2. The role of the terminal

[0759] The device provides a user interface and sends emotional data to the server in real time as the user selects and customizes templates. The emotion engine analyzes the user's emotions, receives feedback to adjust templates and content, and presents it to the user visually.

[0760] 3. User actions

[0761] Users select templates and customize their content via their devices. The system analyzes the user's emotions in real time during creation, and emotional data is managed to protect privacy. For example, if a user is stressed, the system automatically adjusts the template to a more relaxing design.

[0762] Specific example

[0763] For example, when a user creates a marketing report, they select an appropriate template on their device. Based on the user's facial expressions and voice tone, the emotion engine built into the server determines that the user is feeling anxious. In that case, the server automatically selects fonts and color schemes that do not emphasize text and applies a calm layout. After generation, this report undergoes AI review and user confirmation before the final version is uploaded to the CMS.

[0764] In this way, the system assists in document creation while taking user emotions into consideration, providing a more user-friendly and productive work environment.

[0765] The following describes the processing flow.

[0766] Step 1:

[0767] The user logs into the device and begins accessing the system. The device sends the user's authentication information to the server for permission verification.

[0768] Step 2:

[0769] The server provides the terminal with a list of available templates and design options based on the user's permissions. The user then selects the appropriate template.

[0770] Step 3:

[0771] The user selects a template, and the device sends that information to the server. Based on this, the emotion engine prepares to begin analyzing the user's emotions.

[0772] Step 4:

[0773] While the user customizes templates through the device, the device continuously monitors the user's emotional state using its camera and microphone.

[0774] Step 5:

[0775] The device sends the collected emotional data to the server. An emotion engine built into the server analyzes this data to identify the user's current emotions.

[0776] Step 6:

[0777] The server dynamically adjusts the template design and structure based on analyzed sentiment data. For example, if the user is feeling stressed, it will change to a calmer color scheme and font.

[0778] Step 7:

[0779] The adjusted template is generated by the server and sent to the terminal. The terminal then presents the user with the visual changes and asks for confirmation.

[0780] Step 8:

[0781] The user approves the adjustments and completes the document creation. The terminal then sends a request for final confirmation to the server.

[0782] Step 9:

[0783] The server generates the final version of the document, which is then reviewed by AI, and its security is guaranteed using blockchain technology.

[0784] Step 10:

[0785] Secure electronic documents are automatically uploaded to the CMS by the server, and sharing notifications are sent to the relevant users.

[0786] (Example 2)

[0787] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0788] In today's information society, the creation and management of electronic documents are becoming increasingly important. However, traditional methods cannot dynamically adjust document design to respond to user emotions, making it difficult to improve the user experience. Furthermore, there is a need to reflect the content of electronic documents in a timely and accurate manner and to guarantee data integrity.

[0789] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0790] In this invention, the server includes means for acquiring and reflecting information from an electronic database, means for sensing and analyzing the user's emotional state, and means for dynamically adjusting the document design and content based on the analyzed emotional results. This enables the generation of optimal electronic documents tailored to the user's emotions and secure data management.

[0791] An "electronic database" is a system that stores and manages information in a structured, digital format.

[0792] "Information format" refers to the structure and type of data or information that is displayed.

[0793] An "information management system" is a system for organizing, storing, retrieving, and sharing information and data.

[0794] "Distributed ledger technology" is a distributed database technology in which multiple nodes cooperate to manage data in order to guarantee its integrity and security.

[0795] "Machine learning technology" is a technology that gives computers the ability to learn from data and find patterns.

[0796] "User emotional state" refers to a situation that demonstrates a user's psychological or emotional response.

[0797] "Dynamic adjustment" means making immediate changes in response to the situation.

[0798] This invention is a system for dynamically adjusting the design and content of electronic documents, taking into account the user's emotional state. The system mainly consists of collaboration between a server, a terminal, and the user.

[0799] The server functions as the central hub for managing information, retrieving necessary information from electronic databases and incorporating it into documents. The hardware used here is standard server equipment, and the software incorporates protocols that support distributed ledger technology. The server also features an emotion engine that utilizes machine learning techniques, analyzing user emotion data using a generative AI model. This model uses the prompt "Please propose a design that will help the user relax" to provide design suggestions based on the analysis results.

[0800] The terminal acts as the interface with the user, sensing the user's facial expressions and voice tone in real time through sensors and microphones. This emotional data is processed through appropriate software (e.g., OpenCV for face recognition, Praat for voice analysis) and sent to the server. The terminal also visually presents feedback to the user based on the analysis results sent from the server, helping the user customize documents.

[0801] This system allows users to select templates tailored to their purpose and create documents that align with their emotions. For example, when creating a marketing report, if a user feels stressed, the system automatically suggests calming color tones. This enables users to create documents more efficiently and stress-free.

[0802] This invention aims to significantly improve the user experience and enable adaptive and interactive document management.

[0803] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0804] Step 1:

[0805] The user begins creating an electronic document using the terminal. When the user selects a template, the terminal receives this selection information as input and applies it to the user interface. At this time, the displayed content (output) is configured based on the template selected by the user. Specifically, the terminal displays a list of templates and sets the template clicked by the user as the currently selected template.

[0806] Step 2:

[0807] The device monitors the user's facial expressions and voice tone in real time. It acquires emotional data from sensors and a microphone as input. This data is processed by facial recognition software (e.g., OpenCV) and voice analysis software (e.g., Praat) to estimate the user's emotional state (output). Specifically, the device continuously acquires information from the camera and microphone and prepares to send it to the emotion engine.

[0808] Step 3:

[0809] The device sends the acquired emotion data to the server. The input data is the emotion estimation result, which is encrypted and sent to the server. The transmitted data is used for analysis on the server. Specifically, the device sends data to the server using a secure communication protocol.

[0810] Step 4:

[0811] The server uses an emotion engine to analyze the received emotional data. Using emotional data as input, it employs a generative AI model to perform analysis according to the prompt "Please propose a design that will help the user relax." This generates design proposals (outputs) that match the user's emotions. Specifically, the AI ​​analyzes the data and creates suggestions for adjusting the template's colors and fonts.

[0812] Step 5:

[0813] The server sends the analysis results to the terminal. It receives design proposals as input and outputs them to the terminal. Specifically, the server sends the created design change proposals back to the terminal via secure communication.

[0814] Step 6:

[0815] The terminal presents design suggestions received from the server to the user. It receives server suggestions as input and integrates them into the user interface. The user reviews the visually adjusted design and makes final edits (output). Specifically, the terminal reflects the new design on the screen in real time and provides the user with options.

[0816] Step 7:

[0817] The user completes the final edits and saves or sends the electronic document. The system receives the edited document as input and saves it within the system or outputs it to an external information management system. Specifically, the user presses a confirmation button to complete the document and, if necessary, shares it with others via the internet or uploads it to a CMS.

[0818] (Application Example 2)

[0819] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0820] Traditionally, a challenge in the creation and management of electronic records has been the insufficient dynamic content adjustment based on the user's emotional state. Furthermore, while providing information tailored to individual emotions is crucial for improving the user experience, achieving this is often difficult.

[0821] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0822] In this invention, the server includes means for acquiring and reflecting information from a digital recording medium, means for accumulating multiple information formats and designs and enabling rapid adjustment, and means for analyzing the user's emotional state and dynamically adjusting the content delivered based on that analysis. This enables the delivery of personalized content that responds to the user's emotions.

[0823] A "digital recording medium" is a medium for electronically storing, managing, and transmitting information, and includes databases and cloud storage.

[0824] "Information acquisition" refers to the act of obtaining requested information from a digital recording medium and providing it in a format that meets the user's requirements.

[0825] An "information format" is a format that defines the structure and layout of data, and includes templates that can be customized for various purposes.

[0826] "Design" refers to the structure and style used to visually represent information and data, and is used to present them in a way that is easily recognizable to users.

[0827] "Rapid adjustment" refers to the ability to change and adapt information formats and designs in a short amount of time, enabling the provision of optimal information tailored to the user's needs and circumstances.

[0828] "User's emotional state" refers to the emotional state and psychological condition expressed by the user, and is analyzed using facial recognition and voice analysis.

[0829] "Dynamic adjustment" refers to flexibly changing the content and method of delivery of information in accordance with real-time changing situations and conditions.

[0830] "Personalized content delivery" is a delivery method that selects and provides the most relevant information based on the user's emotional state and individual preferences.

[0831] In the system that implements this application example, the server acts as a central control unit, acquiring necessary information from digital storage media and processing it to analyze the user's emotional state. The server uses an emotion recognition API (e.g., emotion judgment software) to receive and analyze the user's emotional data in real time. Subsequently, based on the analysis results, it selects the optimal content and sends it to the terminal. At this time, the design is quickly adjusted from template information on the digital storage media (e.g., cloud storage).

[0832] The device interacts directly with the user through its user interface, displaying dynamic content provided by the server. The device incorporates facial and voice recognition capabilities, periodically sending this data to the server. This allows the server to constantly maintain an up-to-date understanding of the user's emotional state and continuously optimize the content.

[0833] Users access content on a daily basis using their devices. The system provides information in a way that is sensitive to the user's mood, offering content with a relaxing design when the user is feeling stressed, and analytical content when the user is feeling excited and highly focused.

[0834] For example, when a user opens a news app, if it's determined that they are highly focused, it will display detailed economic analysis articles. When they want to relax, it will display articles about travel or hobbies.

[0835] Examples of prompt messages include, "Get the user's emotional state and recommend travel-related articles if they are calm," and "Play relaxation music if the user is judged to be highly stressed."

[0836] In this way, the embodiment for carrying out the invention enables personalized content delivery based on user emotions, contributing to an improved experience.

[0837] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0838] Step 1:

[0839] The server receives user emotion data (e.g., facial expressions, voice tone) from the terminal. The input data is acquired in real time using facial recognition technology and voice analysis software. This data is analyzed for emotional state via an emotion recognition API. The output is a numerical value or category indicating the user's emotional state.

[0840] Step 2:

[0841] The server selects appropriate information formats and content from digital storage media based on the analysis of the user's emotional state. The input is emotional data, and the output is corresponding content IDs and template information. A generative AI model is used to recommend content optimized for the user's emotions.

[0842] Step 3:

[0843] The terminal receives content information sent from the server and displays it through the user interface. Input is selected content or template data, and output is a visually adjusted content screen. The terminal renders the visual elements, taking into account screen resolution and interaction.

[0844] Step 4:

[0845] The user provides interaction and feedback on the displayed content. Input is the content display on the device, and output is new data resulting from the user's actions (e.g., scrolling, clicking). User action information is sent from the device to the server and used to select the next content.

[0846] Step 5:

[0847] The server accumulates user interaction data and analyzes it to improve future content delivery. The input is user interaction data, and the output is updated information for the predictive model used for future content adjustments. It generates prompt messages, enabling more accurate content recommendations in subsequent processing.

[0848] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0849] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0850] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0851] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0852] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0853] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0854] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0855] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0856] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0857] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0858] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0859] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0860] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0861] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0862] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0863] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0864] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0865] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0866] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0867] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0868] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0869] The following is further disclosed regarding the embodiments described above.

[0870] (Claim 1)

[0871] Means for obtaining and reflecting information from digital databases,

[0872] A means of storing multiple information formats and designs and enabling rapid customization,

[0873] A means of automatically sending the generated electronic documents to the content management system,

[0874] A means of guaranteeing data integrity and security using blockchain technology,

[0875] A means of using artificial intelligence to evaluate the content of electronic documents and suggest corrections,

[0876] A system that includes this.

[0877] (Claim 2)

[0878] The system according to claim 1, which customizes the information format selected by the user and stores it for later use.

[0879] (Claim 3)

[0880] The system according to claim 1, which interacts with a digital database in real time and generates electronic documents based on the latest data.

[0881] "Example 1"

[0882] (Claim 1)

[0883] Components for retrieving and reflecting information from data storage,

[0884] Components that store multiple data formats and designs and enable rapid customization,

[0885] Components that automatically send generated electronic documents to an information management system,

[0886] Components that use distributed ledger technology to guarantee data integrity and security,

[0887] Components that use machine learning to evaluate the content of electronic documents and suggest corrections,

[0888] Components that allow template selection and customization through a user interface, and enable the display and modification of generated electronic documents,

[0889] Components that acquire data in real time and reflect it in the template,

[0890] A system that includes this.

[0891] (Claim 2)

[0892] The system according to claim 1, which customizes the data format selected by the user and stores it for later use.

[0893] (Claim 3)

[0894] The system according to claim 1, which interacts with data storage in real time and generates electronic documents based on the latest data.

[0895] "Application Example 1"

[0896] (Claim 1)

[0897] A device for acquiring and reflecting information from a digital data storage device,

[0898] A device that records multiple data formats and designs, enabling rapid optimization,

[0899] A device that automatically transmits generated electronic documents to an information management platform,

[0900] A device that uses distributed ledger technology to guarantee data integrity and security,

[0901] A device that uses machine learning technology to evaluate the content of electronic documents and propose corrections,

[0902] A device that uses image processing technology to detect the assembly process, processes the data in real time, and reflects it in an electronic document,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, which optimizes the information format selected by the user and stores it for later use.

[0906] (Claim 3)

[0907] The system according to claim 1, which interacts with a digital data storage device in real time to generate electronic documents based on the latest information.

[0908] "Example 2 of combining an emotion engine"

[0909] (Claim 1)

[0910] Means for obtaining and reflecting information from electronic databases,

[0911] A means for storing multiple information formats and configurations and enabling rapid adaptation,

[0912] A means for automatically sending the generated electronic document to the information management system,

[0913] A means of guaranteeing data integrity and security using distributed ledger technology,

[0914] A means of evaluating the content of an electronic document and suggesting corrections using machine learning technology,

[0915] A means of sensing and analyzing the user's emotional state,

[0916] A means of dynamically adjusting the design and content of a document based on the analyzed sentiment results,

[0917] A system that includes this.

[0918] (Claim 2)

[0919] The system according to claim 1, which adapts the information format selected by the user and stores it for later use.

[0920] (Claim 3)

[0921] The system according to claim 1, which interacts with an electronic database in real time and generates electronic documents based on the latest information.

[0922] "Application example 2 when combining with an emotional engine"

[0923] (Claim 1)

[0924] Means for acquiring and reflecting information from digital recording media,

[0925] A means of accumulating multiple information formats and designs and enabling rapid adjustment,

[0926] A means for automatically transmitting the generated electronic records to an information management system,

[0927] A means of guaranteeing the integrity and security of information using distributed ledger technology,

[0928] A means of evaluating the content of electronic records and proposing corrections using machine learning technology,

[0929] A means for analyzing the emotional state of users and dynamically adjusting the content delivered based on that analysis,

[0930] A system that includes this.

[0931] (Claim 2)

[0932] The system according to claim 1, which adjusts the information format selected by the user and stores it for later use.

[0933] (Claim 3)

[0934] The system according to claim 1, which interacts with a digital recording medium in real time and generates an electronic record based on the latest information. [Explanation of symbols]

[0935] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for obtaining and reflecting information from digital databases, A means of storing multiple information formats and designs and enabling rapid customization, A means of automatically sending the generated electronic documents to the content management system, A means of guaranteeing data integrity and security using blockchain technology, A means of using artificial intelligence to evaluate the content of electronic documents and suggest corrections, A system that includes this.

2. The system according to claim 1, which customizes the information format selected by the user and stores it for later use.

3. The system according to claim 1, which links with a digital database in real time and generates electronic documents based on the latest data.

Images